Stress, Health, and Behavior 1462552609, 9781462552603

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STRESS, HEALTH, AND BEHAVIOR

STRESS, HEALTH, AND BEHAVIOR Richard McCarty

THE GUILFORD PRESS New York London

Copyright © 2023 The Guilford Press A Division of Guilford Publications, Inc. 370 Seventh Avenue, Suite 1200, New York, NY 10001 www.guilford.com All rights reserved No part of this book may be reproduced, translated, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, microfilming, recording, or otherwise, without written permission from the publisher. Printed in the United States of America This book is printed on acid-free paper. The author has checked with sources believed to be reliable in his efforts to provide information that is complete and generally in accord with the standards of practice that are accepted at the time of publication. However, in view of the possibility of human error or changes in behavioral, mental health, or medical sciences, neither the author, nor the editors and publisher, nor any other party who has been involved in the preparation or publication of this work warrants that the information contained herein is in every respect accurate or complete, and they are not responsible for any errors or omissions or the results obtained from the use of such information. Readers are encouraged to confirm the information contained in this book with other sources. Last digit is print number: 9 8 7 6 5 4 3 2 1 Library of Congress Cataloging-in-Publication Data is available from the publisher. ISBN 978-1-4625-5260-3 (paperback) ISBN 978-1-4625-5169-9 (hardcover)

About the Author

Richard McCarty, PhD, is Research Professor of Psychology at Vanderbilt University, where he has taught undergraduate courses in stress and health since 2015. Dr. McCarty started his academic career at the University of Virginia and previously served as Dean of the College of Arts and Science and Vice Chancellor for Academic Affairs and Provost at Vanderbilt. He is author of the book Stress and Mental Disorders: Insights from Animal Models and coeditor of eight volumes, and has published more than 200 articles and book chapters. Dr. McCarty is a Fellow of the American Psychological Association, the Association for Psychological Science, and the American Association for the Advancement of Science.

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Preface

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efore you read further in this preface and look through the chapters in the book, I have a small request. Think back over your interactions with friends, family members, and others you have encountered over the past week. How many times during those 7 days did the term stress come up in conversation? You might have asked why your friend seemed to be so stressed out. A sibling may have asked your advice for the best way to deal with a highly stressful situation at school. And you might have posted a picture on Snapchat to convey how stressed out you were because of several tests that were looming during that week. I think it is safe to say that all of us use the word stress to capture the trials and tribulations of our daily lives. And yet, despite how frequently stress is a part of our daily conversations, there is not a clear understanding of the powerful connections between long-­term exposure to high levels of stress and our health. The idea for this volume took shape as I taught a writing seminar at Vanderbilt University on “Stress, Health, and Behavior” for the first time during the fall semester in 2015. My goal for this course was to shed light on the ways in which high levels of stress could lead to chronic health problems. I am grateful to my students who have taken this seminar for the feedback they have provided over the years, giving me a sense of the things that have worked well and the things that have fallen flat. When did stress burst onto the scene as a major factor in human health? In Chapter 1, I discuss the insights of human beings over several millennia regarding the health benefits of living a life in harmony and balance with the natural world. From those insights it followed that if harmony and balance were disrupted, health suffered. As knowledge expanded regarding human anatomy and physiology, Dr. Hans Selye advanced stress as a key unifying concept related to the etiology of a variety of diseases. Although physicians dominated the field of stress research from its earliest days, the pendulum began to shift to include major contributions by behavioral and social scientists. Today, stress research is a dynamic interdisciplinary field of inquiry that has contributed in important ways to a deeper understanding of disease processes.

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One of my goals for this book is to provide students with a sense of the experimental approaches taken by scientists across a range of disciplines to explore the influences of stressful experiences on human health and well-­being. Chapters 2 and 3 provide information on methods used by researchers to quantify biological and behavioral measures of stress in human beings. In addition, later chapters include, where appropriate, information on sample sizes, the makeup of study participants, and the statistical significance of various findings for many of the studies presented in the chapters that follow. Another goal of this book is to highlight the range of medical problems that have been connected to stressful life experiences. These problems range from psychiatric disorders in Chapters 4–­6 to chronic diseases in Chapters 7–­10 and infectious diseases in Chapter 11. In Chapter 12, I attempt to capture the insidious effects of structural racism on health, with a focus on African Americans. I hope this chapter broadens your perspective as you read it as much as it did for me when I wrote it. Finally, I end on a hopeful note with a discussion of resilience in Chapter 13. My goal was to make this a user-­friendly book for instructors and students alike. I attempted to keep acronyms to a minimum throughout the book so that it would make for an easier read. (An extensive glossary at the end of the book provides a quick source for definitions of key terms.) I also tried to strike a balance between covering the biological aspects of stress and the behavioral responses to stressors. I emphasize recent peer-­ reviewed journal articles for each of the chapters, and there is an extensive bibliography that is current through late 2022, when the book went into review and production. Several colleagues in Nashville, including a few of my neighbors, provided valuable feedback on specific chapters. For their helpful comments, I thank Hector Myers, PhD, Bruce Wolf, MD, Christopher Lind, MD, and Ryan Mire, MD. I also thank Professor David Barlow of Boston University for his advice and encouragement as I was developing the prospectus for this book and for his suggestion to approach Jim Nageotte, Senior Editor at The Guilford Press, with my idea. I am grateful to Jim and Associate Editor Jane Keislar and Senior Production Editor Jeannie Tang, his colleagues at Guilford, for assisting me in bringing this project to completion with dedication and attention to detail. They were wonderful partners to work with as the book took shape, and I am most grateful for their support and encouragement at every turn. My wife, Sheila, encouraged me over the many months I worked on the manuscript in our front guest bedroom while staring at a computer screen. On some days, I did much more staring at a blank screen than producing text, but that is the nature of such an undertaking. Without Sheila’s love and support, I could not have brought this project over the finish line.

Contents

CHAPTER 1. Historical Aspects of the Stress Field

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Early History 1 Stress Comes of Age  10 Forging Early Connections between Stress and Disease  10 The Biopsychosocial Model of Disease  13 Allostasis and Allostatic Load  16 Contributions of Social Scientists to Stress Research  19 Molecular Aspects of Stress Research  22 Toward a Unified View of Stress, Health, and Disease  24 Conclusions 25 What Lies Ahead?  25

CHAPTER 2. Biological Measures of Stress

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Biological Markers of Stress  28 Point‑of‑Use Sensors 42 Gene Expression Biomarkers  43 Epigenetic Biomarkers 44 Conclusions 47

CHAPTER 3. Behavioral Measures of Stress Acute Laboratory Paradigms for Provoking Stress Responses  49 Acute Psychological Measures of Stress Appraisal  53 Electronic Health Records  57 Social Isolation and Loneliness  58 ix

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Work‑Related Stressors 60 Social Capital 60 Early Life Stressors  62 The Stress of Major Life Events  63 Smartphone Applications 64 Conclusions 66 APPENDIX 3.1.  Quantitative Analyses of Health Risks

from Stressors 67

CHAPTER 4. Stress and Alcohol Use

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Global Aspects of Alcohol Use  68 The Impact of Alcohol Consumption in the United States  69 Diagnosis of AUD  71 Genetics of AUD  73 A Conceptual Framework for Stress and Alcohol Abuse  75 Stress‑Targeted Interventions for AUD  84 Conclusions 87

CHAPTER 5. Posttraumatic Stress Disorder

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Diagnosis of PTSD  90 Using Fear Conditioning to Probe the Mechanisms of PTSD  93 Genetics of PTSD  94 Transgenerational Transmission of Trauma  98 Inflammation and PTSD  102 Brain‑Imaging Studies and PTSD  104 Stress‑Targeted Interventions for PTSD  105 Conclusions 109

CHAPTER 6. Stress and Depression Overview of Major Depressive Disorder  110 Genetic Aspects of Depression  111 Depression and Global Burden of Disease  113 Is Depression an Adaptive Behavioral Response?  114 Theories of Depression  115 Stress and Depression  117 Twin Studies and Depression  120 Stress from Infancy through Adolescence  122 Intergenerational Transmission of Stress and Depression  124 Depression and Chronic Medical Diseases  125 Stress‑Targeted Interventions for MDD  126 Conclusions 129

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CHAPTER 7. Stress and Cardiovascular Disease

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Stress and Heart Disease  130 Stress‑Related Disorders and Cardiovascular Diseases  136 The Stress of a Cancer Diagnosis  137 Depression and the Heart  138 Work‑Related Stressors and the Heart  141 Beliefs about Stress and the Heart  144 Brain Responses to Stress  144 The Protective Effect of Social Networks  145 Stress‑Targeted Interventions Following a Heart Attack  145 Stress and Hypertension  147 Stress‑Targeted Interventions and Hypertension  152 Conclusions 153

CHAPTER 8. Stress and Diabetes

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Why Is Regulation of Blood Glucose So Important?  155 Metabolic Syndrome 158 Contributions of Genes and Environment to T2DM  159 Stress and T2DM  160 Stress‑Targeted Interventions for T2DM  168 Conclusions 171

CHAPTER 9. Stress and the Gastrointestinal System

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The Microbiome–Gut–Brain Axis  172 Peptic Ulcers and Stress  176 Inflammatory Bowel Diseases  181 Stress‑Targeted Interventions for IBD  186 Irritable Bowel Syndrome  189 Stress‑Targeted Interventions for IBS  191 Conclusions 193

CHAPTER 10. Stress and Cancer Historical Connections between Stress and Cancer  195 Cancer and the Global Burden of Disease  196 Psychosocial Stressors Increase the Risk of Developing Cancer  197 The Impact of Psychosocial Stressors and Levels of Social Support on Morbidity and Mortality Following a Diagnosis of Cancer 201 Psychosocial Stressors Promote Cancer Metastasis  204 Depression Affects Cancer Morbidity and Mortality  208 Stress‑Targeted Interventions Following a Cancer Diagnosis  212 Conclusions 215

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CHAPTER 11. Stress and Infectious Diseases

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Herpes Zoster 217 Upper Respiratory Infections  219 Human Immunodeficiency Virus  221 Vaginal Infections 226 Stress and Life‑Threatening Infections  227 Stress and Vaccine Challenge Studies  228 Stress Effects on Wound Healing  230 The COVID‑19 Pandemic  233 Conclusions 234

CHAPTER 12. Systemic Racism as a Stressor

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Racism in Medical Research: The Tuskegee Syphilis Study  237 Racial Inequities and Allostatic Load  239 Behind from the Beginning  243 Racial Disparities and Health Outcomes  247 Racism and Brain Health  252 Racial Inequities in Mortality  254 Stress‑Targeted Interventions to Reduce the Effects of Systemic Racism on Health  257 Conclusions 258

CHAPTER 13. Resilience

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Measuring Resilience 261 Molecular and Genetic Contributions to Resilience  264 Resilience Levels and Health Outcomes  269 Stress‑Targeted Interventions to Enhance Resilience  275 Conclusions 277



Glossary of Terms

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References

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Index

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CHAPTER 1

Historical Aspects of the Stress Field

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tress is a relatively recent concept in the social, behavioral, and biomedical sciences, having been popularized by Hans Selye in the mid-20th century as a key component of many chronic illnesses. However, the foundations that contributed to the development of the stress concept can be traced back to concepts of health and disease in ancient Chinese and Greek medicine, to paradigm-shifting discoveries as early Renaissance scholars began to question long-held doctrines espoused by the Greek physician Galen of Pergamon, to the elucidation of basic principles of regulatory physiology in the 19th and early 20th centuries, and to the formalization of stress as a factor in disease etiology in the last century. In this introductory chapter, I will touch on some of the key insights and discoveries that made stress a key component in the etiology of a broad range of diseases and a new word in many languages around the world. As you will see, many of these advances were made by physicians who were rightly concerned about promoting health and preventing disease.

EARLY HISTORY Galen of Pergamon Claudius Galenus, or Galen or Pergamon, was born into a wealthy family around 129 C.E. in the Greek city of Pergamon, which is in present-day Turkey. He benefited from a broad education, eventually settling on a career in medicine. During his medical training, he traveled extensively throughout the Mediterranean region to benefit from the most up-to-date teachings, including time spent at the illustrious medical school in Alexandria, Egypt. His first official post was as surgeon to the gladiators in his hometown of Pergamon around 157 C.E. Given this assignment, it is easy to imagine that Galen became all too familiar with human anatomy as he treated injured combatants. 1

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In 162 C.E., he traveled to Rome, where his reputation as a highly skilled physician resulted in his appointment as physician to several Roman emperors. He frequently experimented with animals, including Barbary apes, but he could not conduct studies on human corpses because of prohibitions on the use of corpses in Roman law. He was a target of intense jealousy from other Roman physicians, and on one occasion he even fled Rome for fear of his life. The exact date of his death is unknown but was probably around 210 C.E. (Fullerton & Silverman, 2009). Galen’s extensive writings cast a long shadow over the practice of medicine from the second century until the late 1500s and beyond. Galen, who is regarded as one of the founders of experimental physiology, created a system of pathology that combined Hippocrates’ humoral theories with the Pythagorean theory, which held that the four elements (earth, air, fire, and water) corresponded to various combinations of what were considered to be physiological characteristics: dry, cold, hot, and moist. The combinations of these characteristics corresponded roughly to the four humors of the human body: hot + moist = blood; hot + dry = yellow bile; cold + moist = phlegm; and cold + dry = black bile. Galen’s dogmatic approach to medicine essentially brought innovation and discovery in European medicine to a standstill for nearly 14 centuries. As an example, as late as the 16th century, an English physician could be fined if he questioned Galen’s teachings. Anything relating to anatomy, physiology, and disease required that physicians refer back to the writings of Galen as the final authority from whom there could be no further debate, even when Galen’s views were clearly wrong. Such was not the case in the Islamic world, where Ibn al-Nafis of Damascus provided an accurate description of the pulmonary circulation and noted that blood did not flow from the right ventricle to the left ventricle via invisible pores. Rather, he stated clearly that blood from the right ventricle flowed to the lungs through the pulmonary artery and returned to the left side of the heart via the pulmonary vein. He also hypothesized the existence of connections or pores between the pulmonary artery and the pulmonary vein. Unfortunately, these early findings from the 13th century were not read by scholars in the Western world and would require “re-­discovery” four centuries later (West, 2008).

Revolutionizing Human Anatomy Galen’s stranglehold on the teaching and practice of medicine in Europe changed abruptly when a paradigm shift was initiated by a most remarkable scholar, Andreas Vesalius of Brussels (O’Malley, 1964). After a broad education that included studies of Greek, Latin, Hebrew, and Arabic texts and early entry into the University of Louvain, Vesalius traveled to Paris in 1533 to begin his medical studies. At that time, Paris was a recognized center of medical education in Europe, and works by Galen were a featured part of the curriculum for medical students. But Vesalius grew frustrated by his professors’ approach to and the poor quality of instruction in human anatomy and began to study human anatomy on his own (Ball, 1910). Vesalius returned to the University of Louvain at the end of 1536, where he was awarded the Bachelor of Medicine degree the following year. He then moved to Italy, where he received his Doctor of Medicine degree and was appointed Professor of Surgery at the University of Padua. Through his frequent dissections and lectures, he became



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convinced that Galen’s teachings relating to human anatomy and physiology were inaccurate; he formally broke with the Galenic doctrine and forged a new and more accurate path for the study of human anatomy and physiology. This new path involved a handson approach to gross anatomy and emphasized direct observations of many corpses to gain an appreciation for the natural variation across developmental stages and between males and females (Ball, 1910). Vesalius began 3 years of focused work on his most famous publication, De humani corpis fabrica (On the Fabric of the Human Body), which was published in Basel in 1543. This magnificent work, which is considered by many to number among the great classics of medical scholarship, included seven books that described human anatomy in exquisite detail. In his relatively brief but extraordinary career, Vesalius changed forever the teaching of human anatomy. More importantly, he was among the first scholars to openly refute Galen’s teachings and to expose medical students to content that was verified by careful observations and that placed great value on an open and inquiring mind.

William Harvey and the Heart Just as Vesalius had challenged the prevailing Galenic doctrine relating to human anatomy in the 16th century, William Harvey upended Galenic orthodoxy on the organization of the circulatory system during the 17th century (Shackelford, 2003). Harvey completed his medical education at the University of Padua, where he received his Doctor of Medicine degree and eventually made his way back to England. In 1628, he published his monumental treatise on the heart and circulation of the blood, Exercitatio Anatomica de Motu Cordis et Sanguinis in Animalibus (Anatomical Exercise on the Motion of the Heart and Blood in Animals). Harvey drew on his classical education to describe extensive experiments with a wide array of animals as well as humans to make a compelling case for the circulation of blood throughout the body through a system of arteries and return of the blood to the heart through a system of veins. Through his studies, he laid to rest the legacy of Galen and his assertions that the arteries and veins were separate systems and that blood was consumed as it entered body tissues. For 20 years following the publication of his treatise on the heart and circulation, Harvey traveled widely and conferred with many distinguished physicians who were initially skeptical of his conclusions regarding the circulation of the blood. Such was the powerful hold that Galen still exerted over physicians in the 17th century. In contrast, many younger scientists and physicians embraced Harvey’s views and provided additional experimental evidence to bolster his claims. In 1649, he published a brief response to some of his major critics. After that, he assumed the status of an elder statesman in British medical circles while continuing his commitments to the Royal College of Physicians.

Claude Bernard The next major advance for consideration was more conceptual than empirical. It occurred in the second half of the 19th century, and its impact extends to the present. The scientist behind this new concept of the constancy of the internal environment was the most distinguished physiologist of his generation, Claude Bernard. He was accepted as a medical student at the Collège de France, and in 1843, he completed his thesis for

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the Doctor of Medicine degree. In 1853, the Sorbonne awarded Bernard a Doctor of Natural Sciences degree for his pioneering work on sugar metabolism and the liver, and the following year he was appointed to the newly created Chair of General Physiology at the Sorbonne. Many of Bernard’s major discoveries foreshadowed the emergence of stress as a key concept in biology and medicine in the 20th century. Without question, Bernard is best remembered today for his original formulation of the critical importance of maintaining the constancy of the internal environment (le milieu intérieur). He thought about this concept and also mentioned it in his lectures for a quarter-­century. In a final book that he edited on his deathbed, Bernard (1974) expressed his mature view of the regulation of the internal environment: The fixity of the milieu [intérieur] presupposes a perfection of the organism such that the external variations are at each instance compensated for and equilibrated. Consequently, far from being indifferent to the external world, the higher animal is, on the contrary, in a tight and informed relationship with it, of such a nature that its equilibrium results from continual and delicate compensation, established as if by the most sensitive of balances. All of the vital mechanisms, however varied they may be, have always one goal, to maintain the uniformity of the conditions of life in the internal environment. . . . The stability of the internal environment is the condition for the free and independent life. (p. 84)

In discussing the far-­reaching implications of Bernard’s conception of the le milieu intérieur, Cooper (2008) emphasized the dynamic nature of compensatory alterations to maintain the equilibrium of internal parameters, such that an organism is capable of a free and independent life. Bernard (1974) added: ‘’In the perfected animal, whose existence is independent, the nervous system is called upon to regulate the harmony which exists between all these conditions’’ (p. 84). Thus, if regulatory capacities among bodily systems (i.e., harmony) were compromised, the risk of disease was greatly enhanced. Drawing upon his experience as a physician, Bernard argued that detailed studies of physiological systems under normal conditions were essential for understanding disease states and developing effective therapies (Conti, 2001; Cooper, 2008).

Walter B. Cannon If Claude Bernard was the preeminent physiologist of the 19th century, then Walter Bradford Cannon was his worthy successor for at least the first half of the 20th century (McCarty, 2016b). Cannon entered Harvard College as an undergraduate in 1892, where he took a course in psychology from William James. Upon graduation, he entered Harvard Medical School, receiving his MD in 1900. He accepted an instructorship in the Department of Physiology under the direction of Henry P. Bowditch, MD, George Higginson Professor of Physiology and a former dean of the medical school. Cannon succeeded Bowditch as Higginson Professor and Chair of the Department of Physiology in 1906, a position he held until his retirement in 1942. Cannon is best known for his studies of the sympathetic nerves and the adrenal medulla in fearful and stressful situations (Gervais & Saini, 1995). His studies of epinephrine secretion from the adrenal medulla also led to his description of the fightor-­flight response, triggered when animals and humans are exposed to life-or-death



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situations and must attack a threatening individual or escape to survive. In presenting a summary of experiments from his laboratory, Cannon noted the powerful effects of fear, rage, asphyxia, and pain in stimulating adrenal medullary secretion of epinephrine under control of the splanchnic nerves (Cannon, 1914a). As early as 1914, Cannon employed the term stress to describe experiments on physiological responses to emotional stimuli (Cannon, 1914b). He continued to use this term as a means of describing the relationship between emotional and physical stimuli and the concomitant physiological responses in his laboratory experiments (e.g., Cannon, 1928). In a later paper (Cannon, 1935), he addressed the consequences of exceeding “critical stress levels,” thereby overwhelming the homeostatic capacities of organisms and disrupting the internal environment. This work foreshadowed the embrace of the term stress by scientists and medical researchers to connect exposure to stressors and increased susceptibility to various diseases. Another aspect of Cannon’s rich legacy as an investigator was his description of physiological homeostasis (Cannon, 1929). He selected this term with care, and it conveyed two key ideas: homeo (meaning similar but with variations) and stasis (meaning a condition but not with stagnation). In a highly regarded monograph, he defined homeostasis in the following way: The coordinated physiological processes which maintain most of the steady states in the organism are so complex and so peculiar to living beings—­involving, as they may, the brain and nerves, the heart, lungs, kidneys and spleen, all working cooperatively—­ that I have suggested a special designation for these states, homeostasis. The word does not imply something set and immobile, a stagnation. It means a condition—­a condition which may vary, but which is relatively constant. (Cannon, 1939, p. 24)

In advancing this idea of physiological regulation, Cannon paid homage to the critical work of Claude Bernard nearly 50 years earlier through his description of the milieu intérieur, where the blood and lymph bathing the cells and tissues of complex organisms buffered them from alterations in the external environment. Not surprisingly, Cannon expanded the role of the sympathetic–­adrenal medullary system from a system involved in emergency functions to one that was also involved intimately in maintaining homeostatic balance (Cooper, 2008). A great deal of research since the initial formulation of the concept of homeostasis has been directed at understanding how stressful stimuli can disrupt these internal regulatory processes and increase the risk of disease. Cannon was moving steadily along a path to the Nobel Prize in Physiology or Medicine as he pursued a vigorous program of research on sympathetic–­adrenal medullary system responses to stressful stimuli. A major unresolved issue at this time was the nature of neural transmission—­was it chemical or electrical in nature? But Cannon was never able to conduct experiments that would demonstrate conclusively the chemical nature of neurotransmission in sympathetic nerves, in part because he was deployed to serve as a medical officer in France during World War I. In 1921, Otto Loewi, an Austrian who was to become a close friend of Cannon later in life, utilized the isolated frog heart maintained in vitro to demonstrate that inhibitory transmission from vagal nerve terminals to cardiac muscle cells involved the chemical transmitter, acetylcholine. For this simple but elegant experiment, Loewi shared the 1936 Nobel Prize for Physiology or Medicine with another of Cannon’s close colleagues, Sir Henry H. Dale

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(Loewi, 1960). It wasn’t until just after World War II that Swedish scientist Ulf S. von Euler provided definitive evidence that norepinephrine was the chemical transmitter at sympathetic nerve terminals. For this discovery, von Euler shared the 1970 Nobel Prize in Physiology or Medicine (von Euler, 1971). Unfortunately, Cannon did not live long enough to benefit from von Euler’s critical discovery.

Hans Selye No scientist is more closely associated with the concept of stress than Hans Selye (McCarty, 2016a). Much of the current discussion regarding the ways in which stress influences the onset of various diseases can be traced back to Selye’s concerted efforts to educate health care professionals and scientists as well as the general public about the dangers of stress. In the sections that follow, I will present a detailed analysis of Selye’s legacy as one of the early proponents of the connections between stress and disease. Selye attended the German University of Prague, where he graduated with an MD in 1929. Next, he completed a PhD in organic chemistry in just two years. With the strong support of his Dean in Prague, he was awarded a Rockefeller Foundation research fellowship and spent one year at The Johns Hopkins University School of Medicine. The ambience in Baltimore was not to his liking, so Selye transferred his fellowship to McGill University in Montreal to work in the laboratory of the distinguished biochemist, Professor James B. Collip. At the end of his fellowship, he returned to Prague for a brief period, but he then traveled back to McGill at the invitation of Professor Collip, first as a lecturer and later as an assistant professor in the Department of Biochemistry (Selye, 1977). Collip tasked Selye with the search for a possible new ovarian hormone, and as part of this effort, Selye injected rats with an extract of ovarian tissue from cows. He quickly observed three key alterations in female rats that received the extracts: reduction in the size of the thymus, enlargement of the adrenal glands, and ulceration of the stomach and duodenum. To determine if these changes were caused by an as yet undiscovered ovarian hormone, Selye injected rats with extracts of other tissues as an experimental control. He was disappointed when the same three pathological alterations were observed at autopsy. For Selye, his hopes of discovering a new hormone were quickly dashed. But much to the dismay of his supervisor, Selye continued this line of research by exposing rats to many different “nocuous agents,” including cold exposure, surgical injury, spinal shock, muscular exercise, or sublethal doses of a variety of drugs or tissue extracts. Selye convinced himself that he was on to something meaningful for medical science, even if he couldn’t convince his supervisor. On July 4, 1936, Selye published a 74-line letter to the editor in the prestigious international journal, Nature, in which he summarized this series of experiments on laboratory rats exposed to a variety of nocuous agents (Fink, 2016; Neylan, 1998). He concluded that the rats developed a consistent triad of symptoms in three stages that was largely independent of the type of nocuous agent employed. He labeled this triad of responses the general adaptation syndrome (GAS). Remarkably, this brief publication contained no descriptions of experimental procedures, no quantitative data, and no photomicrographs, and it listed no references. In spite of these obvious shortcomings, this article continues to be cited today and has stimulated tens of thousands of experiments on stress and its role in disease processes. The field of stress research continues



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to be influenced by this initial report and Selye’s subsequent voluminous publication record over the next 46 years until his death in 1982 (e.g., Selye, 1946, 1951, 1955, 1973, 1975). Much of his research emphasized the role of the hypothalamic–­pituitary–­ adrenocortical (HPA) system in the effects of stress on diseases of adaptation. Selye included three phases of physiological and pathological changes in the GAS:

• Alarm phase: these changes occurred within 6–48 hours following exposure to a nocuous stimulus and were attended by decreases in the weights of the thymus, spleen, lymph glands and liver; reduced fatty tissue; loss of muscle tone; decrease in body temperature; and gastrointestinal erosions. • Adaptation phase: these changes occurred from 48 hours until 1–3 months after the beginning of repetitive exposure to a nocuous stimulus; the adrenals were greatly enlarged, body growth ceased, there was atrophy of the gonads, lactation ceased, and enhanced production of thyrotropic and adrenotropic factors from the pituitary took place. Animals adapted to the deleterious effects of the nocuous stimulus but were more susceptible than controls to the deleterious effects of another stressor. • Exhaustion phase: depending on the severity of and continued exposure to the nocuous agent, animals died at some unspecified point (usually within 3 months), with symptoms similar to those observed during the alarm phase. Selye hypothesized that the animals died because they had exhausted their stores of “adaptation energy,” though he was never able to define or measure adaptive energy (Figure 1.1). Whenever a new theory is advanced, criticisms are sure to follow. Let’s begin with Selye’s definition of stress: “the nonspecific response of the body to any demand.” Given this broad definition, virtually anything could be viewed as a stressor, ranging from

FIGURE 1.1.  As originally presented by Selye (1946), the general adaptation syndrome (GAS) included three distinct stages an animal or human undergoes when exposed to chronic stress: (1) the initial alarm reaction, which occurs after stressor onset, (2) the resistance stage, which includes a time when adaptive mechanisms counter the adverse impact of the stressor, and (3) the stage of exhaustion, when the individual is no longer capable of mounting adaptive responses to the stressor. In some instances, death may occur.

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getting out of a chair after breakfast to walking your dog to climbing a flight of stairs to being deployed into a combat zone. Interestingly, Walter Cannon was one of the first senior scientists to criticize Selye’s formulation of stress during a visit to present a lecture at McGill University, probably in the early 1940s. In response to some of the early criticisms, including Cannon’s, Selye fine-tuned his theory in the following ways:

• With exposure to stress, the demand could be pleasant or unpleasant and could result in happiness or sadness. The pleasant demands were defined as eustress, and the unpleasant demands were defined as distress. The biological changes effected in eustress and distress were similar, but the damage to bodily systems was much greater with distress. • Stress always expressed itself in a nonspecific syndrome, and the whole body was involved. • Conditioning factors were introduced to explain why individuals differed in their responses to the same stressor. These factors included genetic differences, differences in prior experiences, and dietary differences. But, if one stripped away those conditioning factors, the constellation of nonspecific responses remained (Taché & Selye, 1985). Following the publication of Selye’s first monograph describing experiments relating to the GAS (Selye, 1950), The Lancet (Anonymous, 1951) included a review of the book, described as “Selye’s gospel,” with comments on the author and his body of work at that still-early point in his career. The reviewer stated, “Selye’s Stress must be read by anyone who seriously professes to follow the most important trend of medicine at the opening of the second half of the 20th century” (p.  279). However, the reviewer expressed skepticism of Selye’s theories until they were carefully evaluated and subjected to experimental verification. John W. Mason, a distinguished psychiatrist at Yale University, published a twopart critique of Selye’s theories of stress and diseases of adaptation in 1975 that appeared in the first two issues of a new publication, the Journal of Human Stress. In the first article (Mason, 1975a), Mason argued that findings from psychosocial aspects of the stress response made clear the many interacting variables that determined how a given individual would respond to a stressful stimulus. These variables included genetics, previous experiences, and behavioral predispositions. Thus, while Selye argued for a consistent and nonspecific response to stressful stimuli, Mason presented strong evidence in favor of more nuanced and heterogeneous patterns of responses to stressful stimuli. Was there a path forward such that these two disparate approaches to stress research could be integrated (Mason, 1975a)? In the second part of his analysis, Mason (1975b) emphasized that some of Selye’s stressors (e.g., exposure to heat or cold, forced exercise, restraint, injection of formalin) also included a strong measure of emotional distress, fear, and pain. Selye’s inadvertent inclusion of stressors that had psychological as well as physiological dimensions raised additional concerns about the nonspecific nature of the stress response. But Selye’s research depended on indirect measures of endocrine activity, including tissue weights



Historical Aspects of the Stress Field 9

and histological analyses. At the time the experiments were conducted, there were no methods to permit a direct assessment of endocrine activity by measurement of circulating hormone levels. With the advent of sensitive and specific methods for measurement of circulating steroid and peptide hormones beginning in the 1950s, it was possible to test directly some of these hypotheses about responses to psychological versus physiological stressors and the doctrine of nonspecificity. In Mason’s own laboratory research, direct measures of circulating hormones revealed highly specific patterns of adrenocortical responses to various stressful stimuli in rhesus monkeys. These and other findings raised serious concerns about the validity of the doctrine of nonspecificity (Mason, 1971). More recently, Pacak et al. (1998) conducted a series of experiments that also soundly rejected the doctrine of nonspecificity. In response to Mason’s two-part critique, Selye, not surprisingly, mounted a spirited defense of his positions by responding to each of Mason’s major concerns. He explained his initial reluctance in using the term stress and why he ultimately employed this term and encouraged its usage in all languages that lacked an appropriate descriptor. He paid homage to Walter B. Cannon and also asserted that his collection of more than 100,000 publications mostly supported his description of the general adaptation syndrome and the nonspecific nature of the response to stressful stimulation. He addressed the confusion created by the use of the terms stress and stressor over the years. He also invoked the importance of “conditioning factors” such as genotype, age, sex, and prior exposure to stress to explain why animals exposed to the same stressors might develop different patterns of pathology. Selye also pointed out that exposure to stress resulted in nonspecific effects as well as specific effects. This latter assertion continues to create confusion among researchers and did not adequately address several of Mason’s specific concerns. Selye concluded with a strong statement of support for continued use of the term stress in the experimental and medical literature (Selye, 1975). In spite of the criticisms of Selye’s formulation of stress and diseases of adaptation, his legacy as one of the early leaders of this field of investigation is secure (McCarty, 2016a). As we will see in later chapters in this book, his influence is still being felt today in experiments that explore the links between life stressors and the onset of various illnesses.

Summary For more than 3,000 years, philosophers, physicians, and scientists have written about and studied how one lives a life in harmony and balance with nature. After fundamental discoveries in anatomy and physiology were reported, a major challenge was to understand how organisms, including humans, maintained a constancy of the internal environment. The culmination of these inquiries was the concept of homeostasis as promulgated initially by Cannon. Selye was the first scientist to appreciate the importance of stressful stimuli as disruptors of homeostatic balance and risk factors for a variety of diseases. Selye’s conceptions of stress have been frequently refined over the years, but his lasting contribution was to establish a clear link between exposure to stress and negative health outcomes. This will be a continuing theme for the remainder of this book.

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STRESS COMES OF AGE I have situated the beginning of the maturation of stress research as a scientific enterprise at about 1950. This is when Selye’s original ideas were embraced by several medical specialties and the connections among stress, health, and disease were initially mapped out. As we will see later in this chapter, the stress concept was also fully embraced by psychologists, sociologists, nursing researchers, and epidemiologists. This broad-based engagement represents a critical transition to a deeper understanding of stress and its impact on human health and disease. When the World Health Organization was founded in 1948 in the aftermath of World War II, it defined health as “a state of complete physical, mental, and social wellbeing, and not merely the absence of disease or infirmity” (Constitution of the World Health Organization, 1946). Imagine for a moment the juxtaposition of this uplifting and idealistic definition of health against the reality at the time of its publication—­just three years following the widespread devastation in much of the world resulting from World War II. Now, more than 75 years later, an overwhelming majority of biomedical and social science research has continued to focus on a narrow and inverted view of health: one that emphasizes illness. This prioritization of efforts to understand illness is exemplified by the stated mission of the U.S. Centers for Disease Control and Prevention (CDC): to prevent disease and lessen the burden of injuries (Centers for Disease Control & Prevention, 2015). Similarly, the National Institute of Mental Health (NIMH) describes its vision as seeking “to transform the understanding and treatment of mental illnesses through basic and clinical research, paving the way for prevention, recovery and cure” (National Institute of Mental Health, 2015). The study of physical and mental illness is unquestionably important, but the CDC’s and NIMH’s narrow focus on illness provides an incomplete conceptualization of health, including mental health, that can only yield a limited means for understanding and promoting well-being and resilience and improving quality of life. Abstract conceptions of health and disease do not actually represent clearly defined states, but rather occur as points along a continuum. Where health ends and diseases begin is arbitrary and varies across individuals and societies; consequently, conceptions of health should not be restricted to a narrow slice at one extreme of the continuum (Engel, 1960; Lewis, 1953).

FORGING EARLY CONNECTIONS BETWEEN STRESS AND DISEASE One challenge for early researchers in the field of stress was to develop ways to measure stress levels in patients with various illnesses. Several physician-­scientists led the way in these initial efforts, and their approaches are highlighted in the following sections.

Harold G. Wolff Harold G. Wolff, MD (1898–1962), was a distinguished neurologist who for most of his professional career was an attending physician at the New York Hospital–­Cornell Medical Center in New York City. In addition to his research on the mechanisms of migraines and on cerebral circulation, Wolff and his collaborators investigated the role of stressful life experiences in the development of various diseases. His monograph Stress and



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Disease (Wolff, 1953) was published at about the same time that Selye was making his mark in Montreal primarily through research with laboratory animals. Wolff emphasized the importance of how a given individual’s perception of a stressor ultimately determines whether that stressor contributes to disease processes. Other considerations by Wolff and his colleagues included the impact of prior exposure to life stressors as well as social and cultural influences on subsequent physiological and behavioral adaptations to life’s challenges. Current researchers are still investigating these important issues. The early studies directed by Wolff and his colleagues of 739 patients with stress-­ related disorders who were seen in the Medicine A Clinic of the New York Hospital would certainly not fare well if judged by contemporary standards for peer review (Berle, Pinsky, Wolf, & Wolff, 1952; Ripley, Wolf, & Wolff, 1948). This descriptive program of research focused on patients with essential hypertension, migraine, asthma, or other chronic medical conditions during their regular clinic visits, at which time a checklist of more than 800 items pertaining to personal characteristics and life experiences was completed by the patients and their attending physicians over a 3-year period. At the conclusion of the study, the subjects were found to fall into three separate groups: 34% of the patients showed no evidence of improvement, 42% showed symptomatic improvement, and 24% demonstrated significant improvement. A prognostic scale, later referred to as the Berle Index, was constructed from those checklist items that appeared to be most closely related to the improvement of patients. This scale was utilized as a measure of psychosocial assets and reflected how well an individual could cope with life stressors. When the Berle Index was tested in a separate group of 207 patients, the data resulted in a stratification of patients into the same three separate groups based on their treatment outcomes. The frequent interactions between physicians and their patients during clinic visits led to changes in how patients dealt with their illnesses and were summarized as follows: The most powerful therapeutic force stemmed from the ability of the physician and the clinic to inculcate in the patient faith in himself and the capacity to recognize and deal constructively with his problems. This usually involved a reorientation of attitude and entailed far more than a personal attachment to the physician. Only when he had acquired such faith and confidence was it possible for him to abandon costly inappropriate emergency patterns and deal more directly and constructively with threats and challenges of day to day living. (Ripley et al., 1948, p. 951)

Thomas H. Holmes Thomas H. Holmes, MD (1919–1989), began his fellowship in psychosomatic medicine under the direction of Dr. Wolff. Following completion of his fellowship with Wolff, Holmes accepted a position in Seattle in the Department of Psychiatry at the University of Washington Medical School. Soon after his arrival, he was appointed the staff psychiatrist at Firland, the public tuberculosis (TB) sanitorium (Lerner, 1996). It was at Firland Sanatorium that Holmes conducted a series of studies on the role of stressful life events on the course of TB. With the availability of antibiotics for the effective treatment of Mycobacterium tuberculosis, the cause of TB, many infectious disease experts were inclined to emphasize the administration of antibiotics as the most

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effective treatment for TB. However, drug-­resistant strains of M. tuberculosis quickly emerged and treatment protocols had to evolve. In addition, it was well known that many individuals who tested positive for M. tuberculosis did not develop symptoms of TB. Reflecting his training under Wolff, Holmes quantified the stress responses of 109 TB patients at Firland by measuring the urinary levels of 17-ketosteroid, a measure that was prompted by Selye’s earlier work. Surprisingly, Holmes reported that 17-ketosteroid excretion was much higher in those patients with fewer symptoms of TB. In contrast, patients with lower levels of 17-ketosteroid displayed TB symptoms that were more serious and had more advanced stages of the disease. In addition, patients with fewer symptoms of TB tended to exhibit signs of anxiety and tension, while those with more serious symptoms of TB tended to exhibit signs of depression. The study concluded that emotional state influenced adrenal responses as well as the clinical course of the disease (Clarke et al., 1954). Additional studies followed this initial report and attempted to address the critical methodological shortcomings of the early studies of TB patients. Were the emotional responses and stress levels causes or consequences of TB? What was an appropriate control group for these experiments? How did stressors affect the clinical course of TB? It was well established that TB was a disease that preferentially affected the down-and-out of society, individuals who were poor, lacked a steady income, and often did not have secure housing. A later study compared 20 Firland employees who developed TB over a 5-year period with 20 employees who did not develop TB and who were matched in age, sex, race, income level, and skin test results at the time they began working at the sanitorium. Stressful life events occurred, with significantly greater frequency in employees in the 2 years before diagnosis of TB compared to frequencies of occurrence in employees who did not develop TB (Hawkins, Davies, & Holmes, 1957). Later, Holmes, Joffe, Ketcham, and Sheehy (1961) tested the hypothesis that patients with fewer psychosocial resources would be more likely to exhibit recurrence of TB following treatment than individuals with greater levels of psychosocial support. The Berle Index was utilized to quantify psychosocial resources, and a high score was indicative of significant psychosocial resources. In a sample of 41 patients randomly selected at admission, 26 patients were identified 5 years later and were found to have high Berle scores and no recurrence of TB. In contrast, 5 of 15 patients with low Berle scores did develop TB symptoms and required treatment for the disease. In looking back on the work of Holmes and his colleagues, it is obvious that their studies raised as many questions as were answered. But this corpus of work did contribute to an eventual recognition that psychosocial factors, including life stressors, could influence the development and course of TB. Lest you think that TB is a disease from the Dark Ages, consider these sobering facts. In 2018, TB was one of the 10 leading causes of death worldwide, with 1.5 million deaths and 10 million cases diagnosed. Close to a half-­million of the new cases were classified as involving drug-­resistant strains of M. tuberculosis (World Health Organization, 2019). Finally, a recent report estimated that 1.7 billion people worldwide had latent infections in 2014, and this represents a gigantic reservoir of potentially new cases (Houben & Dodd, 2016). The stated goal of the World Health Organization is complete eradication of TB by 2050, a major challenge to say the least.



Historical Aspects of the Stress Field 13

Richard H. Rahe As a third-year medical student at the University of Washington Medical School, Richard H. Rahe, MD, began to work with Thomas H. Holmes to construct an inventory of stressful life events and to determine the role of adaptations to these vicissitudes of life on illness onset. As stated in the introduction to their landmark paper (Holmes & Rahe, 1967, p. 213), “It has been adduced from these studies that this clustering of social or life events achieves etiologic significance as a necessary but not sufficient cause of illness and accounts in part for the time of onset of disease.” This scale was originally presented as the Social Readjustment Rating Scale and more recently has been referred to as the Holmes–­Rahe Stress Inventory (HRSI). To construct the scale, 394 individuals were asked to rate 43 life events for their intensity and the length of time an average person would require to adapt to each. One of the life events, marriage, was arbitrarily assigned a rating of 500 and each individual rated the other 42 life events relative to the stress of marriage. After compiling all responses, the score for marriage was reset to 50 and all other life events were scaled appropriately. A summary of the 43 life events is included in Table 1.1. Further studies settled on the following scale for those completing the HRSI: ≤ 150: low-­stress levels and a 30% chance of illness in the next 2 years 150–299: moderate stress levels and a 50% chance of illness in the next 2 years ≥ 300: high-­stress levels and an 80% chance of illness in the next 2 years Not surprisingly, there were many criticisms of the HRSI. The initial rating scale was based on impressions of how an average person might respond to each stressful life event. However, there was a wide range in the magnitude of stress responses across individuals. The initial raters may have interpreted each life event in a uniquely personal way. There may also be cross-­cultural differences in the way individuals deal with life stressors and draw on social support from family members, their faith, and their friends. Finally, the magnitude and type of life events that people experience have changed over the past 50 years. In spite of these limitations, the HRSI has been cited more than 20,000 times, and modifications of the original scale continue to be used in laboratory and field studies of stress and illness (Hobson et al., 1998).

THE BIOPSYCHOSOCIAL MODEL OF DISEASE In a highly influential paper, George L. Engel, a noted psychiatrist at the University of Rochester Medical Center, called into question the single-­minded focus of many physicians at the time, including some psychiatrists, on the biomedical model of disease (Engel, 1977). The biomedical model has traditionally viewed disease through the lens of molecular biology, such that a given disease was thought to have resulted from deviations in measurable biological and chemical parameters. Given this reductionistic orientation, a disease was treated by attempts to restore these biological and chemical parameters to within normal ranges. There was little room within the biomedical model for concerns about behavioral, social, or cultural influences on susceptibility to or progression of disease, including exposure to stressful stimuli.

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S t r e ss , H e a lt h , a n d B e h av i o r TABLE 1.1.  The Holmes–Rahe Stress Inventory as Originally Presented by Holmes and Rahe Life event   1.  Death of spouse  2. Divorce   3.  Marital separation   4.  Jail term   5.  Death of close family member   6.  Personal injury or illness  7. Marriage   8.  Fired at work   9.  Marital reconciliation 10. Retirement 11.  Change in health of family member 12. Pregnancy 13.  Sex difficulties 14.  Gain of new family member 15.  Business readjustment 16.  Change in financial state 17.  Death of close friend 18.  Change to different line of work 19.  Change in number of arguments with spouse 20.  Mortgage over $10,000 21.  Foreclosure of mortgage or loan 22.  Change in responsibilities at work 23.  Son or daughter leaving home 24.  Trouble with in-laws 25.  Outstanding personal achievement 26.  Wife begin or stop work 27.  Begin or end school 28.  Change in living conditions 29.  Revision of personal habits 30.  Trouble with boss 31.  Change in work hours or conditions 32.  Change in residence 33.  Change in schools 34.  Change in recreation 35.  Change in church activities 36.  Change in social activities 37.  Mortgage or loan less than $10,000 38.  Change in sleeping habits 39.  Change in number of family get-togethers 40.  Change in eating habits 41. Vacation 42. Christmas 43.  Minor violations of the law Note. From Holmes and Rahe (1967). Used with permission.

Mean value 100  73  65  63  63  53  50  47  45  44  40  39  39  39  38  37  36  35  31  30  29  29  29  28  26  26  25  25  24  23  20  20  20  19  19  18  17  16  15  15  13  12  11



Historical Aspects of the Stress Field 15

As an alternative to the biomedical model of disease, Engel (1977) presented the benefits of a biopsychosocial (BPS) model of health, disease, and healing. He argued persuasively that the biomedical model was severely limited as it did not take into full account real patients and the ever-­changing interactions that unfold between biological, psychological, and social factors in shaping the onset and course of illnesses and the maintenance of health. The BPS model was based on systems theory, which provides an approach for studying organized wholes and their component parts (von Bertalanffy, 1972). A foundational principle of systems theory as applied to health and illness is that a reductionistic approach cannot be successful in understanding an individual patient. That is, approaching the problem of illness by adopting a reductionistic approach to understand the component parts is doomed to failure because it cannot explain the whole (i.e., the patient). Although Engel was a psychiatrist by training, he was successful in catalyzing a dramatic change in the way physicians across specialties interacted with patients and the ways medical students were taught to interact with their patients, in the United States and in other countries. To illustrate the complex interactions that undergird the BPS model, Engel presented a hierarchical depiction of interacting components from subatomic particles to individuals to complex societies. A notable quality of such a hierarchy is that each level of the hierarchy exhibits distinctive characteristics that can be studied using appropriate methodologies. In addition, each level is a component of higher levels, is composed of lower levels, and is part of the greater whole (Engel, 1980). To illustrate how the BPS model and the biomedical model might impact the care of an acutely ill patient, Engel provided an example of a middle-­aged man with a history of a heart attack who presented in the emergency department complaining of chest pains that radiated down his left arm. The focus of a physician who embraced the biomedical model would be on isolating the cause of the chest pains and would diagnose the disturbance in the heart at the expense of gathering information about the patient’s onset of symptoms, his family situation, his concerns about completing his commitments at work, and his general reluctance to seek medical help. Only after the patient’s supervisor discussed with him the importance of seeking immediate medical attention had the patient agreed to leave his office to get medical attention. Engel did a masterful job of demonstrating how these behavioral and psychological factors exerted a significant impact on the patient and his overall response to treatment for his initial heart attack. These factors would exert a continuing impact after the patient had a second heart attack and was discharged from the hospital (Engel, 1980). Fast forward to the present day, and it is clear that the influence of Engel’s seminal paper is still being felt and that its validity for understanding health and disease is actively being debated. As a case in point, Engert, Grant, and Strauss (2020) argued for an embrace of the biopsychosocial model while commenting on a meta-­analysis of psychosocial interventions designed to affect stress-­responsive immune parameters. Fava and Sonino (2017) have related the staying power of Engel’s conceptual model to several key advances that the model encouraged. First, Engel recognized the limitations of a reductionistic approach for understanding complex clinical cases. He also expressed concern at the time about the lack of integration of findings from the behavioral and social sciences with clinical medicine. Finally, Engel appreciated the physician’s important role in encouraging a patient to modify his or her behavior to improve health and well-being. Of great importance to the approach taken throughout this book is that the

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BPS model emphasized that stressful life events were a significant facet of vulnerability to a variety of illnesses (Engert et al., 2020; Fava & Sonino, 2017). An updated version of the BPS model is included in Figure 1.2.

ALLOSTASIS AND ALLOSTATIC LOAD As we saw earlier in this chapter, Selye (1973) left us with a challenging situation when he defined stress as “the nonspecific response of the body to any demand.” How can a definition as broad as that possibly allow us to make sense of connections between stress and illness? Can you imagine that homeostatic systems have evolved in such a way that stress responses are nonspecific rather than being precisely tuned to the type of stressor, its intensity, its duration, and the context in which it occurs? Several attempts have been made to develop alternatives to Selye’s definition of stress and to refine our thinking about the flexibility of homeostatic systems during physiological or environmental challenges. A productive response to this state of confusion in the field of stress research was a collaborative effort involving Bruce McEwen (1938–2020) of the Rockefeller University and Eliot Stellar (1919–1993) of the University of Pennsylvania. McEwen and Stellar advanced the term allostasis to capture the nature of the body’s exquisitely balanced responses to various stressors in the environment (McEwen & Stellar, 1993). They adopted this term from the earlier work of Sterling and Eyer (1988), who sought to understand the physiological underpinnings of morbidity and mortality in humans.

FIGURE 1.2.  Updated presentation of the biopsychosocial model of disease as originally presented by Engel (1977). Health outcomes in individuals are influenced by a range of factors, including environmental influences, early life stressors, and the way one perceives, responds to, and copes with psychosocial stressors.



Historical Aspects of the Stress Field 17

As an alternative to Bernard and Cannon’s concept of homeostasis, Sterling and Eyer proposed the concept of allostasis, which describes the processes whereby the central nervous system oversees variations in internal states to meet perceived and anticipated demands from environmental stressors (see also Schulkin & Sterling, 2019). McEwen and Stellar were especially struck by the influence of behavioral states (including during exposure to stressors) on a host of physiological parameters, including blood pressure, blood flow to tissues, hormone levels in blood, and mobilization of energy from stored forms, such as glycogen. They argued persuasively that an organism must regulate all homeostatic systems of its internal milieu and match them to prevailing environmental demands. This is the essence of their concept of allostasis (Sterling & Eyer, 1988). McEwen and Stellar (1993) also added a temporal dimension to the allostatic concept to capture the wear and tear on animals and humans from repeated neural, endocrine, and immune responses to chronic exposure to stressful stimuli that vary in frequency, duration, and intensity. Over time, these recurring physiological responses could render individuals susceptible to a variety of chronic diseases and mental disorders. They referred to this state of biological adaptation to chronic exposure to stressors as allostatic load, where internal physiological systems adjust to new setpoints (Figures 1.3 and 1.4).

FIGURE 1.3.  A variety of psychosocial stressors are perceived and interpreted by the brain, which may result in the activation of peripheral stress responsive systems, including the hypothalamic–­ pituitary–­adrenocortical (HPA) axis, the sympathetic nervous system (SNS), the parasympathetic nervous system (PSNS), the immune system, the gastrointestinal system (GI), and the cardiovascular system. These stress-­induced alterations can increase allostatic load and the risk of adverse health outcomes.

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Allostatic load may be a useful concept, but is it possible to quantify it? McEwen (1998) presented four ways in which stressors and the responses to them could lead to allostatic load: 1. Frequent exposure to stressors over the course of weeks or months, even if they are of moderate intensity, may lead to pathophysiological changes in the brain and in peripheral tissues. 2. Repeated exposure to a stressor does not result in habituation of allostatic responses over time, leading to exposure to elevated levels of hormones or other signaling molecules. 3. There is an inability to terminate an allostatic response following cessation of a stressor. 4. An inadequate allostatic response to a stressor leads to compensatory increases in other allostatic systems. Table 1.2 summarizes two approaches for quantifying allostatic load in healthy adults (McCaffery, Marsland, Strohacker, Muldoon, & Manuck, 2012; Seeman, ­McEwen, Rowe, & Singer, 2001). In both approaches, measures included traditional risk factors related to cardiovascular disease, metabolic syndrome, and diabetes as well as indices of stress-­induced activation of the sympathetic nervous system, HPA axis, and the immune system. McCaffery et al. (2012) reported that their findings were consistent with a single, second-­order factor relating to metabolic, vagal, and inflammatory measures of allostatic load. Seeman et al. (2001) suggested that measures of allostatic

FIGURE 1.4.  Allostasis refers to variations in internal systems to meet perceived and anticipated demands, including those associated with exposure to stressors. During chronic intermittent exposure to stressors, allostatic changes may lead to increases in allostatic load and the maintenance of a new steady state. Negative health outcomes may follow periods of increased allostatic load as described by McEwen and Stellar (1993).



Historical Aspects of the Stress Field 19 TABLE 1.2.  Two Approaches to Quantifying Allostatic Load in Healthy Adults Seeman et al. (2001)a

McCaffery et al. (2012)b

SBP and DBP

SBP and DBP

Waist-to-hip ratio

BMI

Serum HDL and total cholesterol

Waist circumference

HbA1c in blood

Serum levels of glucose, insulin, HDL, triglycerides, IL-6, CRP

Serum DHEA-S Urinary levels of CORT, NE, EPI Note. SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index, HDL, highdensity lipoprotein, HbA1c, glycosylated hemoglobin, a measure reflecting glucose metabolism over several months; serum DHEA-S, dihydroepiandrosterone sulfate, an androgen produced by the adrenal cortex; CORT, cortisol; NE, norepinephrine; EPI, epinephrine; IL-6, interleukin-6, a pro-inflammatory cytokine; CRP, C-reactive protein, a protein produced by the liver that increases in blood in response to inflammation. a Seeman et al. (2001): 1,189 participants included men and women scoring in the top third for their age cohort based on multiple measures of physical and cognitive functioning. bMcCaffery et al. (2012): 1,007 participants included men and women 30–54 years of age with no obvious medical issues.

load could serve as an early warning system for onset of multiple diseases, including psychiatric and substance use disorders (Berger et al., 2018; Fronk, Sant’Ana, Kaye, & Curtin, 2020), even when a single parameter is not outside of what is considered the normal clinical range. Some of these ideas will re-­surface in later chapters on specific diseases of adaptation. Duong, Bingham, Aldana, Chung, and Sumner (2017) presented their analysis of 21 studies that employed data from the National Health and Nutrition Examination Survey (NHANES). Although there was general agreement that biomarkers from three categories (cardiovascular, metabolic, and immune) should be used to calculate allostatic load scores, significant variation exists in how allostatic load score is computed in a given study. Liu, Juster, Dams-O’Connor, and Spicer (2021) presented their concerns about the computation of allostatic load scores, where all measures have typically been given equal weight in developing the composite score. Using data on 12 biomarkers of allostatic load from the 2015–2016 NHANES data, they found that body mass index and C-­reactive protein were the most informative biomarkers for allostatic load based on their analyses. Another concern with allostatic load scores is that the measures fail to capture any dynamic responses of stress system parameters, such as increases in cortisol levels in blood plasma or saliva following acute exposure to stress. Finally, Kerr, ­K heloui, Rossi, Désilets, and Juster (2020) emphasized the importance of careful analyses of allostatic load scores of males and females in determining the risk of various diseases. They also pointed out that allostatic load scores appear to be higher for males than for females, based on their review of the literature.

CONTRIBUTIONS OF SOCIAL SCIENTISTS TO STRESS RESEARCH Much of the information I have presented thus far on the history of stress research has been dominated by physicians and biomedically oriented scientists. But this domination

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of the field by the medical model took a dramatic turn beginning in the 1970s, and this change continues to the present.

Appraisal and Coping Selye and other early pioneers in the field of stress research did not generally concern themselves with the possibility of individual differences in responses to stressors. Richard Lazarus (1922–2002), a distinguished clinical psychologist at the University of California, Berkeley, for most of his career, introduced the concepts of appraisal and coping to the field of stress research, and he and his students built on these concepts to revolutionize the study of stress and health. In one of his early experiments (Lazarus, Deese, & Osler, 1952), Lazarus and his coworkers discussed individual differences in responses to stressful laboratory test procedures, based in part on differences in motivation. These differences in response would become recurring themes in his research over the course of his career. In his first major monograph, Psychological Stress and the Coping Process (Lazarus, 1966), Lazarus introduced his theory of psychological stress that emphasized cognitive appraisal of and coping with stressors. These concepts were clearly ahead of the curve for the broader field of stress research. Eighteen years later, Lazarus joined forces with his former graduate student, Susan Folkman, and published a landmark study in the field of stress research, Stress, Appraisal, and Coping (Lazarus & Folkman, 1984). Taken together, these two monographs were important components of a paradigm shift away from behaviorist approaches to understanding behavior and toward the recognition that cognitive processes were critically involved in regulation of human behavior and responses to stressful stimuli. As a clear indication of its monumental impact on the field of stress research, consider that the Lazarus and Folkman monograph (1984) has been cited more than 75,000 times, making it one of the most mentioned books in the history of psychology. I especially like their definition of stress that appeared in the first chapter: Psychological stress is a particular relationship between the person and the environment that is appraised by the person as taxing or exceeding his or her resources and endangering his or her well-being. (Lazarus & Folkman, 1984, p. 10)

They further stated that the person–­environment dynamic is associated with cognitive appraisal of the stressor and coping with the stressor where possible. Cognitive appraisal involves ongoing evaluations of environmental stressors with respect to their effects on the individual. There are three types of cognitive appraisal processes: 1.  Primary appraisal: Within this category, Lazarus and Folkman listed three kinds: irrelevant, benign-­positive, and stressful. Irrelevant appraisals involve no effect on an individual’s well-being. Benign-­positive appraisals occur when an encounter preserves or enhances well-being or has the potential to do so. Stressful appraisals result from harm to self or others, anticipation of future harm or loss, and challenges, where there is potential for growth and positive gains in dealing effectively with a stressor. 2.  Secondary appraisal: During exposure to a threatening or challenging stressor, an active evaluation of available coping options takes place, such that an effective



Historical Aspects of the Stress Field 21

coping strategy is selected and evaluated for its potential to deal successfully with the stressor. 3.  Reappraisal: As new information is received from the environment, a previous appraisal of a given stressor may be modified. For example, a prior benign appraisal may be converted into a stressful appraisal given new information. A second major focus of Lazarus and Folkman (1984, p. 141) was on coping processes. They defined coping as “constantly changing cognitive and behavioral efforts to manage specific external and/or internal demands that are appraised as taxing or exceeding the resources of the person.” They argued that coping processes place emphasis on what an individual thinks or actions that are taken within a specific context and that change over time as the encounter with a given stressor unfolds. Managing internal and/or external demands did not equate coping with mastery of a situation as it could involve avoiding, tolerating, or accepting the effects of a stressor. Finally, they distinguished between problem-­focused coping, in which efforts are made to manage or alter the stressor, and emotion-­focused coping, in which attempts are made to regulate emotional responses to the stressor. These key concepts regarding stress, appraisal, and coping still occupy center-­stage in current efforts to promote well-being and prevent diseases, both physical and mental, in the face of a constant parade of stressful events that humans experience across the lifespan. We will return to these key concepts in later chapters as we delve into the role of stress in specific diseases such as obesity, cancer, depression, and hypertension.

Health Psychology: A New Field Emerges Following an influential article by Schofield (1969), the American Psychological Association (APA) began to discuss an expansion of the ways in which psychologists interacted with health delivery systems. In this wide-­ranging article, Schofield challenged the leadership of APA to imagine the value to society of having psychologists contribute to a broader range of health-­related services and research activities than simply mental health, which would encompass health promotion, treatment of specific diseases, and prevention of illness. Schofield was rewarded for his hard work by being appointed Chair of the APA Task Force on Health Research. Continued discussions ensued until 1978, when APA formally established a new home for this effort, Division 38 (Health Psychology), with Professor Joseph Matarazzo of the Oregon Health Sciences Center as its first president. In his 1979 presidential address, Matarazzo (1980, p. 815) defined health psychology as “the aggregate of the specific educational, scientific, and professional contributions of the discipline of psychology to the promotion and maintenance of health, the prevention and treatment of illness, and the identification of etiologic and diagnostic correlates of health, illness, and related dysfunction.”

Tend and Befriend It is difficult to imagine a conversation about stress and health without a reference to the fight-or-­f light response introduced by Cannon (1939). This concept has become embedded in the field of stress research over many decades, and it conveys how individuals (typically males) deal physiologically and behaviorally to threatening stimuli. Taylor et

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al. (2000) introduced a dramatically different perspective to describe how female animals, including humans, adjust to stressful stimulation. Called “tend and befriend,” this theory argues that when females are subjected to stressful stimulation, they focus on providing care for their young, affiliate with social groups to reduce their vulnerability, and contribute to social networks, especially female social networks, to promote the exchange of resources and the sharing of responsibilities. Some of the bias toward the fight-or-­flight framework was explained by an exclusive dependence on male animals for many of the foundational studies. Fortunately, a more balanced approach for including females as well as males in experiments with laboratory animal models and human participants will ensure the emergence of new perspectives regarding sex differences in responses to stressful stimuli (Beery, 2018; Clayton & Collins, 2014). In support of the tend-and-­ befriend theory, Taylor et al. (2000) reviewed the extensive literature on neuroendocrine responses to stressors and concluded that male responses appear to be influenced to a significant degree by the pre- and postnatal organizational effects of androgens (e.g., testosterone) on stress responses. In striking contrast to males, females appear to downregulate sympathetic and HPA axis responses to stressors by the actions of the posterior pituitary hormone, oxytocin. In addition, oxytocin, in combination with endogenous opioids and estrogens, promote maternal and affiliative behaviors in females. Taylor et al. also suggested that these female-­specific patterns could be instilled in part by social roles and cultural norms.

MOLECULAR ASPECTS OF STRESS RESEARCH As social scientists began to make important contributions to the study of stress and health, advances in neuroscience, immunology, and microbiology also began to expand our understanding of the effects of stressful stimulation on the inner workings of the body. Much of this research has been conducted in animal models, especially laboratory strains of mice and rats, but these mechanistic studies have also had an enduring impact on clinical studies. It is beyond the scope of this book to delve into these mechanistic studies, but it might be beneficial to introduce some of these topics now as a means of providing context for later discussions in disease-­specific chapters.

The Brain and Stress Bruce McEwen provided key findings on how the brain responds and adapts to stressful stimulation. He and his colleagues were the first to demonstrate that neurons in the brain contain receptors for steroid hormones released from the adrenal cortex (McEwen et al., 1968). The adrenal cortex is part of the HPA axis, an important component of the body’s adaptive responses to stress. Cortisol is the primary hormone of the human adrenal cortex that is released during stressful stimulation, and it readily crosses the blood-brain barrier. Cortisol binds to two classes of receptors in brain areas, including the hippocampus, as part of a negative feedback loop to regulate the HPA axis. In addition, cortisol actions in the brain affect neural, endocrine, and behavioral changes during and after stressful stimulation (McEwen, 2007). The landmark finding from McEwen’s laboratory more than 50 years ago was a powerful catalyst for continuing studies of how the brain adapts to acute and chronic



Historical Aspects of the Stress Field 23

stressors and its role in stress-­related diseases. McEwen (2007, p. 873) placed the brain at the center of processes relating to stress and adaptation by stating “The brain is the key organ of the response to stress because it determines what is threatening and, therefore, potentially stressful, as well as the physiological and behavioral responses which can be either adaptive or damaging.” In addition to the HPA axis, brain circuits also regulate the activity of the sympathetic nervous system, which innervates virtually every organ and tissue of the body through the actions of its primary neurotransmitter, norepinephrine. A critical component of the sympathetic nervous system is the adrenal medulla, which releases epinephrine into the circulation in times of stress. The sympathetic nervous system plays an important role in the fight-or-­f light response as originally described by Cannon (1914a, 1914b). Experiments with laboratory mice and rats have clearly shown that the brain is altered by stressful stimulation, with changes ranging from the rates at which genes are transcribed, to circuit-­level changes in neuronal activity, to structural changes in individual neurons (McCarty, 2020). We will discuss these structural and functional changes in brain areas as we delve into specific diseases in later chapters in this book.

Immune Responses and Stress The immune system plays an important role in defending the body against invading bacteria and viruses and clearing tissues of cellular debris. Two components of the immune system subserve these functions: the innate immune system and the adaptive immune system. The rapidly mobilized and phylogenetically older innate immune system has evolved to detect and eliminate invading pathogens based on their molecular differences from host cells. Signaling molecules of the innate immune system can also activate the adaptive immune system, which attacks an invading pathogen with targeted antibodies but which requires 4–5 days to become fully activated. For many decades, the immune system was assumed to be largely self-­regulating and focused on distinctions between “self” and “non-self.” There was little evidence that the immune system was influenced by the stresses and strains of daily life. A major change in understanding regulation of the immune system was reflected in the work of Matzinger (1994, 2002), who argued that the role of the immune system was to detect damage and signal danger. Several key findings beginning in the 1970s revealed that the immune system is remarkably sensitive to environmental perturbations and that these changes in function play a critical role in maintaining a balance between health and disease. Central nervous system regulation of the immune system was reported by Ader and Cohen (1975) in experiments on conditioned immunosuppression in laboratory rats by pairing the taste of a saccharin solution with the illness-­ inducing side effects of the immunosuppressive drug, cyclophosphamide. This important series of experiments paved the way for probing interactions between the brain and the immune system and led to establishing a new interdisciplinary field, psychoneuroimmunology (Dantzer, 2018). Psychoneuroimmunology remains a vital field of inquiry and provides important insights into the role of stress in the etiology of various diseases. In Chapter 2, we will discuss in greater detail the components of the endocrine and immune systems and their reciprocal interactions with brain circuits.

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Transgenerational Stress Signatures Recent experiments with laboratory animals suggest that the deleterious effects of exposure to stressful experiences prior to mating can be transmitted to succeeding generations through epigenetic alterations in the paternal or maternal germ line (Ryan & Kuzawa, 2020). These findings could have important implications for human males and females exposed to traumatic experiences prior to reproducing. Chapter 2 discusses epigenetic effects on gene transcription in more detail. For now, consider the challenges associated with paternal germline transmission of stress across generations. Given the multitude of nuclear, cytoplasmic, and morphological changes that occur during spermatogenesis, DNA is tightly packaged into the sperm head and there is a cessation of transcriptional activity. In addition, the volume of cytoplasm is greatly reduced and there are few remaining ribonucleic acid (RNA) transcripts (Miller, Brinkworth, & Iles, 2010). How then can paternal stressful experiences be transmitted to the next generation? Morgan, Chan, and Bale (2019) discussed potential mechanisms for germline transmission of nongenetic information from fathers to their offspring and beyond. They argued that stress-­relevant information transfer from a father to his offspring would require three critical processes: (1) a vector to convey information from the father to the maternal reproductive tract and a future embryo, (2) a molecular signal that could encode a paternal stressful experience and transfer this molecular information to precipitate downstream responses, and (3) a target cell or tissue that could recognize the signal and encode the information to effect a change in embryonic development or alterations in the maternal reproductive tract.

TOWARD A UNIFIED VIEW OF STRESS, HEALTH, AND DISEASE Several investigators have attempted to unite the biological and behavioral findings relevant to the effects of chronic stress on the development of various diseases. One prominent theory that I will highlight places an emphasis on principles of evolutionary theory that relate exposure to chronic stressors with health outcomes and disease etiology. In his social safety theory, Slavich (2020, p. 3) argued that “forming and maintaining friendly social bonds (i.e., fostering social safety) is a fundamental organizing principle of human behavior and that threats to social safety (e.g., social conflict, isolation, rejection, exclusion) are a key feature of psychological stressors that most strongly impact health and behavior.” For most of our evolutionary history as a species, human beings have lived in environments that have been replete with physical threats from predators and aggressive conspecifics, and risk of infections from viruses and bacteria. Individuals who were fully integrated members of cohesive social groups and who were able to mount immune responses in anticipation of physical and social threats may have enjoyed greater rates of survival and reproduction than those who did not benefit from a cohesive social group and who were not adept at detecting and responding to threats. If this conceptualization is accurate, a hierarchy of threats related to social safety might include the following: physical danger, such as attacks, abuse, or neglect; social conflict within one’s social group, including threats of aggression; and other forms of within-­group disruptions, including forced isolation, discrimination, rejection, and exclusion (Slavich, 2020). These actual and implied threats to social safety appear to activate a family of immune signaling molecules called pro-­inflammatory cytokines, which are released



Historical Aspects of the Stress Field 25

from immune cells and are critically involved in mounting innate immune responses. These cytokines promote inflammation and affect behavioral responses to social threats ranging from cognitive behaviors, emotional responses, patterns of sleep, pain sensitivity, and feeding. This complex web of interactions between the brain, the autonomic nervous system, the HPA axis, and the immune system will be discussed in greater detail in Chapter 2. The downside to this delicately balanced system of neural, endocrine, and immune responses is that perceived or imagined social threats are just as capable of eliciting a robust pro-­inflammatory cytokine response as an actual physical threat to one’s safety and survival (Miller & Raison, 2016; Slavich, 2020; Slavich & Irwin, 2014). There are two sides to the stress–­inflammation coin. On the one hand, seeking and maintaining strong social relationships are associated with increased longevity and lower levels of circulating pro-­inflammatory immune signaling molecules, such as interkeukin-­6, tumor necrosis factor a, and C-­related peptide (Holt-­Lunstat, Smith, Baker, ­Harris, & Stephenson, 2015; Holt-­Lunstat, Smith, & Layton, 2010; Uchino et al., 2018). In contrast, persistent activation of the neural–­endocrine–­immune system by psychological and other environmental stressors has been linked to increased susceptibility to a range of chronic diseases, including cardiovascular disease, cancer, diabetes, kidney disease, nonalcoholic fatty liver disease, autoimmune diseases, and neurodegenerative diseases (Furman et al., 2019). Later in this book, we will discuss in greater detail the connections between stress-­induced activation of the immune system and specific diseases and health-­related outcomes.

CONCLUSIONS As stress matured as a field of study in the 1950s and assumed a prominent role in the etiology of a variety of diseases, many attempts were made to clarify, correct, or expand upon some of Hans Selye’s early formulations. The highly influential biopsychosocial model of disease, as proposed by Engel (1977), represented a major advance in the conceptualization of disease processes, and life stressors were an important component. McEwen and Stellar (1993) offered a new way to look at stress by introducing allostasis as a more inclusive term to capture the effects of stressors on homeostatic setpoints. They extended the impact of allostasis by emphasizing allostatic load as a new measure of the wear and tear that an individual experiences with repeated exposures to high-­ intensity stressors. As we will see in later chapters, allostatic load captures the sustained impact of stressors, including systemic racism, on health status. As the impact of stress research expanded, new research directions were explored, including changes in genetic and immune system markers of stress. Many of these studies have opened up new targets for the treatment of diseases with drugs and psychosocial interventions to reduce the negative effects of stress on well-being.

WHAT LIES AHEAD? I hope this chapter has left you with a more detailed view of how the field of stress research has become so important for understanding health and disease. In Chapters 2 and 3, I present approaches to quantifying stress responses using biological measures

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and behavioral measures, respectively. Armed with this information, we are prepared to explore in detail connections between stressful stimuli and the onset and maintenance of a variety of diseases. In Chapters 4 through 6, I present studies that connect stressors to three psychiatric disorders: alcohol use disorder, posttraumatic stress disorder, and depression. In Chapters 7 through 11, I present information on associations between psychosocial stressors and a variety of chronic diseases, including heart disease, type 2 diabetes, gastrointestinal disorders, cancer, and infectious diseases. In Chapter 12, I introduce the concept of systemic racism as a chronic stressor and discuss the pervasive negative health consequences of chronic exposure to racism and discrimination. The final chapter of the book ends on a more optimistic note with a discussion of resilience to the negative effects of acute and chronic stressors. A consistent theme of this book is that chronic stress results in increases in allostatic load, which is strongly associated with adverse health outcomes. If stressful stimuli result in poor health, it follows that reducing the impact of stressors or improving skills for coping with and managing life stressors should have beneficial effects on health outcomes. To delve into these connections, I have included sections in Chapters 4–12 on stress-­targeted interventions that are somewhat specific to each of the disorders or diseases that were discussed. This area remains ripe for further research and implementation into clinical practice. The major opportunities that lie ahead include the following:

• Development of personalized approaches to disrupt the negative effects of psychosocial stressors on chronic diseases.

• Expanded use of smartphones and other wearables to track key measures relating

to the impact of stressors and to deliver therapeutic interventions on a just-intime basis. • Capitalization on data analytics relating to life stressors from smartphones and electronic health records to guide physicians in their efforts to improve the health and well-being of their patients. In writing this book, I wanted to share my enthusiasm and excitement for the field of stress research and present some of the opportunities and challenges that lie ahead. I hope the information in the chapters that follow will ignite your passion for research or clinical practice. Perhaps you will be one of the people who will make a difference in the lives of the many individuals who are currently dealing with stress-­related disorders.

CHAPTER 2

Biological Measures of Stress

W

hat is stress? In Chapter 1, we explored how the scientific community has attempted to identify stress as a factor in the onset of illness and how various researchers have sharpened the definition of stress. But how do we quantify individual responses to stressful stimuli and relate those responses to one’s susceptibility to a particular disease? Broadly speaking, we can sort approaches to measuring stress into two categories: biological and behavioral. In Chapter 3 we will discuss some of the key behavioral markers of stress and how to assess them. But first, in this chapter, we discuss some of the basic physiological changes that occur when a human body is exposed to stressful stimuli. It is difficult to imagine conducting research on a scientific topic in which there are no established methods for sensitive and specific measurements. But where do we begin to investigate methods to measure stress? We could focus on stress as an input variable and quantify the intensity, frequency, and duration of a given stressor. Alternatively, we could focus on stress as an output variable and quantify the physiological and behavioral responses following exposure to a given stressful stimulus. Or we could look at how individuals differ in their appraisal of a common stressor. We might tackle questions such as the following:

• Will we focus on physiological and behavioral changes when an individual is exposed to a stressor under controlled conditions in a laboratory setting?

• Could we measure health outcomes in a large sample of people who have previously rated their exposure to various life stressors over the previous 2 years?

• Might we study adolescents who were exposed to traumatic stressors in the first 5 years of life and look for long-term consequences?

• Would it be worthwhile to quantify stress effects on health outcomes by study-

ing large cohorts of individuals who have been recruited through national health services? • Could new technologies, such as wearable devices, be valuable in relating daily stressors to health outcomes? 27

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For each of these questions, the answer is obviously yes, as each question represents a valid approach to studying stress effects in humans. Thus, our challenge in this chapter and Chapter 3 is to gain a clearer understanding of the strengths and limitations of various methods for measuring stress. To impose some order on the literature relating to measurements of stress, this chapter will cover biological measures of stress, followed in Chapter 3 with a discussion of behavioral strategies for measuring responses to stress. As we will see in the disease-­specific chapters that follow, many laboratories employ multiple biological and behavioral measures of stress responses in a single experiment. The challenge for any research team is to optimize the biological and behavioral measures of stress for the research question being addressed.

BIOLOGICAL MARKERS OF STRESS In this chapter, I will introduce background information on three peripheral stress-­ responsive systems that are influenced by and provide feedback to specific brain circuits. These peripheral systems are the HPA axis, the autonomic nervous system, and the immune system. For each of these systems, I will also summarize the primary endpoints that have been employed to quantify responses to stress under laboratory conditions and in more naturalistic settings. Permit me to add a disclaimer. My purpose here is to provide you with enough background information on these three systems so that you will be prepared to appreciate the complex influences of stress stimuli on biological responses in the chapters that follow. You may be interested much more in the underlying biology of these systems, and I encourage you to pursue those interests by identifying sources from the primary literature.

The HPA Axis The three main components of the HPA axis are the paraventricular nucleus of the hypothalamus (PVN), the anterior pituitary gland, and the adrenal cortex (Figure 2.1). A portion of the PVN contains the cell bodies of neurosecretory neurons that project to the median eminence on the ventral surface of the brain and synthesize corticotropin-­ releasing factor (CRF). CRF is a 41-amino acid peptide that enters the blood vessels that connect the median eminence to the pituitary gland. When it reaches the anterior pituitary gland, CRF stimulates the release of ACTH (adrenocorticotropic hormone), a peptide hormone that enters the circulation and later stimulates the release of the hormone, cortisol, from the adrenal cortex. Cortisol is highly lipid soluble and is synthesized when specialized adrenal cells are stimulated by ACTH. There is a delay of approximately 3–5 minutes between elevations in ACTH in blood and synthesis and secretion of cortisol. The HPA axis exhibits negative feedback regulation, with increasing levels of cortisol inhibiting ACTH release from the anterior pituitary, CRF release from PVN neurons, and inhibitory control of the PVN by other brain areas, including the hippocampus (McCarty, 2020).

Glucocorticoid Receptors Two classes of intracellular receptors for cortisol have been isolated and characterized, including the mineralocorticoid receptor (MR) and the glucocorticoid receptor (GR).



Biological Measures of Stress 29

FIGURE 2.1.  Organization of the HPA axis and the negative feedback effects of cortisol at the level of the anterior pituitary, the paraventricular nucleus (PVN), and the hippocampus.

The former is the primary receptor for the mineralocorticoid hormone, aldosterone, while the latter is the primary receptor for cortisol. MRs and GRs in their unbound form are found primarily in the cytoplasm of cells in peripheral tissues and neurons in the brain. Receptor activation occurs when the MR or GR receptor binds the cortisol molecule, transforms into an activated state, and moves into the nucleus, where it binds to specific sequences of the DNA molecule, often located in the vicinity of the promoter region of target genes that are either activated or repressed. There is a significant time delay of at least an hour between translocation of MRs/GRs to the nucleus and the resulting effects on gene transcription that occur in the target cells. These changes

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in the function of target cells can persist for several hours to multiple days. GRs are widely distributed in cells throughout the body, whereas MRs are much more restricted in their distribution. In brain tissue, MRs have a 10-fold greater affinity for cortisol than GRs. This difference has important implications for how these two classes of receptors function under basal conditions and during stressful stimulation (McCarty, 2020). Cortisol secretion exhibits a distinct circadian (about a day) rhythm that is regulated in part by the body’s master clock in the suprachiasmatic nucleus (SCN) of the hypothalamus, with levels increasing in anticipation of waking, then reaching a peak during the midmorning, followed by a progressive decrease to lowest levels just after midnight. Cortisol inhibits inflammatory responses, mobilizes glucose and free fatty acids, reduces insulin secretion, increases cardiovascular tone, and alters brain circuits involved in cognitive and emotional processing for meeting the immediate energetic and behavioral demands of acutely stressful stimuli (McCarty, 2020).

Plasma ACTH and Cortisol Measurement of plasma levels of ACTH and cortisol provides an accurate index of the secretory activity of the anterior pituitary and the adrenal cortex, respectively. In any studies where blood samples are collected for measurement of ACTH and/or cortisol, care must be taken to obtain baseline blood samples that take into account the circadian changes in these measures and the stress of having a blood sample taken. The half-life of ACTH in the circulation is approximately 22 minutes, and peak plasma levels are attained within 12–15 minutes after onset of a stressful stimulus. The half-life of cortisol in the circulation is approximately 100 minutes, and peak plasma levels are attained within 15–20 minutes after onset of a stressor (Russell & Lightman, 2019).

Salivary Cortisol Salivary cortisol has been employed for more than three decades as an indirect measure of HPA axis activity. There are several attractive features relating to the use of salivary cortisol as a stress biomarker, including the stress-­free collection of samples, a method that is easily adaptable to children or to people reluctant to provide blood samples, and there is no requirement for medical supervision of sample collection. Collection of saliva samples can also occur in community settings such as schools or medical clinics. In any studies of circadian rhythms of salivary cortisol, care must be taken to obtain saliva samples just after a participant wakes up and at intervals thereafter to ensure that the cortisol awakening response is accurately determined. Finally, about 30% of free cortisol in saliva is enzymatically converted to cortisone, resulting in relatively lower levels of unbound cortisol in saliva as compared to plasma (Clow & Smyth, 2020; Hellhammer, Wüst, & Kudielka, 2009). Young et al. (2021) utilized measures of cortisol in saliva under basal conditions and following exposure to a laboratory stressor to probe the effects of exposure to a life stressor during development on the reactivity of the HPA axis. Their results using 37-year-old participants from the Minnesota Longitudinal Study of Risk and Adaptation revealed a blunted response of the HPA axis to an acute laboratory stressor in individuals exposed to early life stressors.



Biological Measures of Stress 31

Autonomic Nervous System The autonomic nervous system is composed of two major subdivisions: the sympathetic nervous system and the parasympathetic nervous system. The former is typically associated with responses to emergencies (fight-or-­f light), while the latter is more active under less demanding conditions (rest-and-­digest). The exquisitely coordinated and often complementary activities of these two systems affect most of the tissues of the body and are vital to maintaining homeostatic balance under resting conditions and following exposure to various stressors. Although most descriptions of the autonomic nervous system imply that the sympathetic and parasympathetic divisions are largely independent of and antagonistic toward one another, these two systems interact in multiple ways at the level of the central nervous system and in the periphery to finely tune the activity of many bodily processes (Ondicova & Mravec, 2010). In addition, the suggestion that the sympathetic and parasympathetic systems are antagonistic in their actions is simply not accurate. Rather, a target tissue will often respond to sympathetic stimulation but have no response to parasympathetic stimulation and vice versa. One prominent exception is the heart, where sympathetic stimulation increases cardiac rate and contractility, while parasympathetic stimulation has opposite effects (refer to Table 2.1 for additional information). We will explore these two systems in greater detail in the chapters that follow as we seek to understand how stress affects health and promotes the onset of various diseases.

Sympathetic Nervous System The primary signaling molecules of the sympathetic nervous system are the catecholamines, norepinephrine and epinephrine. The precursor for catecholamine biosynthesis is the amino acid tyrosine, which is derived from the diet or from hydroxylation of the amino acid phenylalanine in the liver. Tyrosine is taken up into catecholaminergic nerve terminals in the brain and periphery as well as chromaffin cells of the adrenal medulla and is converted into dihydroxyphenylalanine (DOPA) by the actions of the soluble cytoplasmic enzyme, tyrosine hydroxylase. The conversion of tyrosine to DOPA is the rate-­limiting step in catecholamine biosynthesis, and tyrosine hydroxylase activity is in turn regulated by several processes, including feedback inhibition by catecholamines. DOPA is converted into dopamine by aromatic amino acid decarboxylase in the cytoplasm, and then dopamine is taken up into storage vesicles and converted into norepinephrine by the enzyme dopamine b-hydroxylase (Figure 2.2). Norepinephrine functions as a neurotransmitter in its own right, or it may be converted into epinephrine by the enzyme, phenylethanolamine N-methyltransferase (PNMT). PNMT catalyzes the formation of epinephrine in chromaffin cells of the adrenal medulla; however, it is also present in some brain neurons as well as extra-­adrenal chromaffin tissues in the periphery (Kvetnansky, Sabban, & Palkovits, 2009). The cell bodies of preganglionic sympathetic nerves are located in the spinal cord and receive direct synaptic input from neurons in various stress-­responsive brain areas. The axons of preganglionic sympathetic nerves exit the spinal cord and make synaptic contact with postganglionic sympathetic cell bodies in ganglia or with cells in the adrenal medulla. Postganglionic sympathetic nerves innervate most of the peripheral tissues of the body and play critical roles in physiological responses to various stressful stimuli.

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TABLE 2.1.  Responses of Various Peripheral Tissues to Activation of Sympathetic versus Parasympathetic Neurons Organ/tissue

Sympathetic stimulation

Type of receptor

Parasympathetic stimulation

Chromaffin cell

Secretion (cholinergic)

Nn

0

Cardiac muscle

Increased HR

b1

Decreased HR

M2

Cardiac muscle

Increased contractility

b1

Decreased contractility

M2

Arteries in skin of body

Vasoconstriction

a1

0

Visceral arteries

Vasoconstriction

a1

0

Arteries in skeletal muscles

Vasoconstriction

a1

0

Bronchi

Bronchodilation

b2

Bronchoconstriction

Arteries in skeletal muscles

Vasodilation (EPI)

b2

0

GI motility

Relaxation

b2

Stimulation

Digestive glands

0

Bladder smooth muscle

Relaxation

b1

Contraction

Dilator muscle of pupil

Contraction

a1

0

Sphincter muscle of pupil

0

Piloerector muscles of skin

Contraction

a1

0

Salivary glands

Slight mucous secretion

a1

Serous secretion

Sweat glands

Secretion (cholinergic)

M3

0

Fat cell

Lipolysis

b2

0

Brown adipose tissue

Heat production

b3

0

Beta cells in islets of pancreas

Decreased secretion of insulin

a2

Increased secretion of insulin

Secretion

Contraction

Cholinergic receptor

M3 M3 M1, M3 M3 M3 M1, M3

M3

Note. The types of receptors involved in the tissue responses are specified for both systems. EPI, epinephrine; GI, gastrointestinal; HR, heart rate; M1–M3, muscarinic cholinergic receptors; Nn, nicotinic cholinergic receptor.

Norepinephrine is the primary neurotransmitter of postganglionic sympathetic nerves, but neuropeptide Y (NPY) may be co-­localized with norepinephrine and released from nerve terminals during stimulation.

Adrenal Medulla In many respects, the adrenal medulla resembles a sympathetic ganglion that contains postganglionic cell bodies that lack axons. The secretory cells of the adrenal medulla are referred to as chromaffin cells. They secrete norepinephrine and epinephrine into the circulation in response to release of acetylcholine from sympathetic preganglionic fibers of the splanchnic nerve, followed by stimulation of nicotinic acetylcholine receptors. Secretory cells within the adrenal medulla are characterized as epinephrine-­containing and norepinephrine-­containing, with the former differing from the latter by the presence of the enzyme PNMT.



Biological Measures of Stress 33

FIGURE 2.2.  Diagram of a noradrenergic nerve terminal and the biosynthetic pathway for dopamine (DA) and norepinephrine (NE). NE is primarily inactivated by reuptake into the presynaptic nerve terminal.

The secretory activity of the adrenal medulla has traditionally been viewed as a relatively straightforward process, reflecting Cannon’s original concept of the fight-or-­f light response. Stressful stimuli or internal disruptions to homeostasis (e.g., decrease in blood glucose) → increased central stimulation of sympathetic preganglionic cell bodies → increased firing of sympathetic preganglionic fibers in the splanchnic nerves → release of acetylcholine onto nicotinic receptors on adrenal medullary chromaffin cells → depolarization of chromaffin cells and release of norepinephrine and epinephrine. More recent studies have revealed a much more complex and highly regulated process for release of catecholamines from the adrenal medulla during times of sustained stressful stimulation.

Adrenergic Receptors Norepinephrine and epinephrine exert their biological effects on target cells in the brain and the periphery by binding to cell surface receptors. There are two major classes of adrenergic receptors, alpha (a) and beta (b), which are further subdivided into three subtypes of a1 and a2 receptors and three subtypes of b receptors. Adrenergic receptors are included in the broader category of G-­protein-­coupled receptors, which, when stimulated, result in a cascade of intracellular changes in patterns of activation of enzymes and changes in ion channels. These receptor subtypes and selected biological responses in peripheral tissues are summarized in Table 2.2. Many of the physiological changes that occur when adrenergic receptors are stimulated are associated with responses to

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TABLE 2.2.  Classes of Catecholamine Receptors and Their Associated G Proteins, Second Messenger Responses, and Selected Peripheral Tissues with Their Physiological Responses Second messenger response

Tissue

Response

Gq

↑↑↑ IP3, ↑↑↑ DAG

Blood vessels of skin, kidney, GI system

Vasoconstriction

a2

Gi

↓↓↓ cAMP

Presynaptic nerve terminals

↑↑↑ NE release

b1

Gs

↑↑↑ cAMP

Heart Kidney Stomach

↑↑↑ HR and stroke volume ↑↑↑ renin release ↑↑↑ ghrelin release

b2

Gs

↑↑↑ cAMP

GI tract Adipocytes Skeletal muscle

↓↓↓ motility ↑↑↑ lipolysis Vasodilation

b3

Gs

↑↑↑ cAMP

Adipocytes

↑↑↑ lipolysis

Receptor type: adrenergic

G protein

a1

Note. IP3, inositol triphosphate; DAG, diaceylglycerol; cAMP, cyclic adenosyl monophosphate; HR, heart rate; GI, gastrointestinal.

stressful stimulation. In addition, drugs have been developed that target a specific subtype of an adrenergic receptor so that side effects from a given drug are minimized (McCarty, 2020).

Plasma Catecholamines The primary neurotransmitter of postganglionic sympathetic nerves is norepinephrine. Sympathetic nerves innervate most tissues of the body (e.g., heart, blood vessels, spleen, intestines), where norepinephrine is released from sympathetic nerve terminals and binds to adrenergic receptors on target cells. The primary pathway for inactivation of norepinephrine is by reuptake of released norepinephrine through the action of presynaptic norepinephrine transporter molecules. A small percentage is subject to enzymatic inactivation. Some of the locally released norepinephrine (5–20%, depending on the morphology of the junction between the nerve terminal and the target cell membrane) leaks away unmetabolized and enters the circulation (refer to Figure 2.2). Norepinephrine is also released from the adrenal medulla directly into the circulation upon stimulation of adrenal medullary chromaffin cells by sympathetic preganglionic nerves that release acetylcholine, especially during exposure to stress or decreases in blood glucose levels. In most studies of plasma catecholamines in humans, an indwelling catheter is placed in the antecubital vein of the arm to provide samples of venous blood from the hand and forearm. Thus, these plasma samples may not accurately reflect norepinephrine release from other parts of the body. Resting plasma levels of norepinephrine are typically in the range of 200 pg/ml, and the half-life of norepinephrine in blood is about 2 minutes (Goldstein, McCarty, Polinsky, & Kopin, 1983; Goldstein, Eisenhofer, & Kopin, 2003).



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The adrenal medulla is the source of virtually all of the epinephrine found in the circulation. Epinephrine is released from adrenomedullary chromaffin cells directly into the adrenal vein, and circulating levels increase dramatically in response to stressful stimulation. Resting plasma levels of epinephrine are quite low, usually around 50 pg/ml, and the half-life is approximately 3 minutes (Goldstein et al., 1983, 2003). Levels of plasma catecholamines reflect their rate of entry into plasma and their rate of removal from plasma. In addition, sympathetic input to various organs and vascular beds may vary, and these subtle changes cannot be detected by measuring plasma norepinephrine in an arm vein.

Urinary Catecholamines Some of the circulating catecholamines are excreted into the urine unmetabolized and have been utilized as an integrative index of sympathetic–­adrenal medullary activity over extended periods of time. In the 1980s, such measures were especially popular prior to the advent of sensitive assays to measure levels of catecholamines in plasma (Dimsdale & Ziegler, 1991). An excellent example of the use of urinary catecholamine excretion as an index of cumulative stress is reflected in research on occupational stress in men and women (Lundberg & Frankenhaeuser, 1999).

Plasma NPY Neuropeptide Y (NPY) is a 36-amino acid peptide that is found in the central nervous system as well as in sympathetic nerve terminals in the periphery (Reichmann & ­Holzer, 2016; Zukowska-­Grojec, Konarska, & McCarty, 1988). Its name derives from its enrichment of tyrosine (one-­letter abbreviation: Y). In the periphery, NPY is a potent vasoconstrictor, is co-­localized with norepinephrine in sympathetic nerves innervating the heart and vasculature, and is also present in the adrenal medulla and platelets. NPY is co-­released with norepinephrine during sustained periods of stressful stimulation, such as occur during prolonged exposure to stress (Kuo & Zukowska, 2007). Plasma NPY levels have been studied in humans exposed to traumatic stressors, such as lengthy combat deployments, in an attempt to identify biomarkers associated with susceptibility to posttraumatic stress disorder (Reijnen et al., 2018).

Salivary Alpha‑Amylase Measurement of alpha-­amylase in saliva (sAA) provides an index of sympathetic nervous system activity. sAA is an enzyme that is synthesized in acinar cells of the salivary glands and breaks down starch into smaller soluble components such as maltose. Parasympathetic nerves releasing acetylcholine stimulate salivary flow rates while sympathetic nerves releasing norepinephrine stimulate protein secretion into saliva. sAA decreases significantly following administration of a b-adrenergic blocker and increases dramatically following administration of a b-adrenergic stimulant. More importantly, levels of sAA correlate well with plasma levels of norepinephrine but not epinephrine in humans at rest and following exposure to stress paradigms (Thoma, Kirschbaum, Wolf, & Rohleder, 2012). In addition, sAA levels increase rapidly in response to a stressor and return to baseline levels within 10 minutes after termination of the stressor (Jones, Rohleder, & Schreier, 2020). Levels of sAA are affected by a range of variables (time of day, health status, medications, ovarian hormones, smoking, alcohol use, etc.) that must

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be controlled in any experimental design (Strahler, Skoluda, Kappert, & Nater, 2017). Collection of saliva samples is much less invasive than venipuncture that is required for collection of blood samples for measuring plasma norepinephrine.

Parasympathetic Nervous System The primary neurotransmitter of postganglionic parasympathetic neurons as well as at the junction between motor neurons and muscle cells is acetylcholine. The enzyme choline acetyltransferase catalyzes the formation of acetylcholine from the precursors, choline and acetyl coenzyme A. Choline is taken up by cholinergic nerve terminals in the brain and the periphery by the actions of a high-­affinity choline transporter protein. The availability of choline within nerve terminals is the rate-­limiting step in the biosynthesis of acetylcholine. Acetylcholine is metabolized by the actions of the enzyme acetylcholinesterase, generating free choline and acetate. The actions of the parasympathetic nervous system are often complementary to the actions of the sympathetic nervous system. The cell bodies for the preganglionic parasympathetic nerves arise from four of the cranial nerves—­oculomotor (III), facial (VII), glossopharyngeal (IX), and vagus (X)—and from the spinal cord. Preganglionic and postganglionic parasympathetic nerve terminals employ acetylcholine as the primary neurotransmitter.

Cholinergic Receptors As a general rule, activation of parasympathetic outflow results in stimulation of exocrine glands (e.g., mammary, sweat, and salivary), nonvascular smooth muscle cells, cardiac pacemaker cells, and some specialized blood vessels. These biological effects are mediated by the binding of acetylcholine to one of two broad classes of receptors, G-­protein-­coupled muscarinic receptors (M1–M5) and ionotropic nicotinic receptors (Nm and Nn). M1–M3 receptors are found in peripheral tissues, whereas M4 and M5 receptors are found in the central nervous system. Nm receptors mediate neuromuscular transmission, and Nn receptors are responsible for activation of sympathetic and parasympathetic postganglionic neurons and chromaffin cells of the adrenal medulla.

Heart Rate Variability Because acetylcholine is rapidly inactivated by acetylcholinesterase after being released from cholinergic nerve terminals, it is not possible to accurately measure acetylcholine in blood samples. One indirect approach that has been developed to measure parasympathetic nerve activity under basal conditions and following exposure to stressful stimuli is to measure heart rate variability (HRV) by analysis of beat-to-beat variations from heart rate data (R-R interval) continuously recorded from electrocardiograms (ECGs). Fluctuations in heart rate over time display a marked synchrony with respiration, with increases during inspiration and decreases during expiration. This pattern is referred to as respiratory sinus arrhythmia (RSA) and is widely believed to reflect changes in cardiac autonomic regulation by acetylcholine and norepinephrine. HRV may be analyzed by two principal methods, time domain and frequency domain analyses. For example, one can analyze a sequence of normal heart beats for a period of time (e.g., baseline and during exposure to a stressor) by calculating the



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standard deviation (SD, the square root of the variance), a measure of total R-R interval variability. Frequency domain analysis of HRV typically reveals three peaks: a verylow-­frequency peak (< 0.04 Hz), a low-­frequency peak (0.04–0.15 Hz), and a high-­ frequency peak (0.15–0.40 Hz). Some investigators have argued that cardiac sympathetic and parasympathetic tone corresponds to the low- and high-­frequency peaks, respectively. Unfortunately, these simplistic notions have not been confirmed in careful clinical studies, especially for the low-­frequency peak being used as an indicator of cardiac sympathetic tone. The data are somewhat more supportive of a relationship between high-­frequency power and cardiac parasympathetic activity, but concerns have been expressed about this relationship as well (Berntson et al., 1997). Finally, others have suggested that the low-­frequency/high-­frequency ratio provides an indirect measure of sympatho–­vagal balance, but this measure, too, has not stood up to careful scrutiny. Thus, measures of HRV are the closest approximation available for quantifying autonomic (and especially parasympathetic) regulation of the heart under basal conditions and in response to stressors, as imperfect as they are (Billman, 2011). A recent refinement in the analysis of HRV data, especially as it relates to individuals exposed to life stressors, was presented by von Rosenberg et al. (2017). These investigators presented the low-­frequency and high-­frequency bands of HRV in two-­dimensional scatterplots instead of combining the two frequency bands as a low-­frequency/high-­ frequency ratio. This change in the data-­analytic strategy improved the investigators’ ability to discriminate between basal states and the period following exposure of participants to a variety of mental and physical stressors. These stressors included solving mental math problems, doing physical exercise, and giving an oral presentation. Given continuing concerns about the measurement of HRV in humans, Ottaviani, Wright, Dawood, and Macefield (2020) developed an exciting new method for measuring vagal activity in conscious human research participants using ultrasound-­guided microneurography. Because the vagus nerve in the neck region is located in close proximity to the internal carotid artery and the internal jugular vein, there have been long-­ standing concerns about inserting a microelectrode into this delicate region of the body. Use of an ultrasound probe allows for the safe placement of a microelectrode into axons of the vagus nerve, with minimal discomfort or risk to the individual. With further technical refinements, recordings from efferent and afferent axons of the vagus nerve will provide new insights into the role of the vagus nerve in stress-­related disturbances to mental and physical health (Park, 2020).

The Immune System If a virus or bacterium successfully gains entry into the body by breaching the skin or mucous membranes, then a rapid response is necessary to recognize and eliminate the invader. Two components of the immune system fulfill this function: the innate immune system and the adaptive immune system. The innate immune system is a rapid response system that detects and eliminates invading pathogens based on their molecular differences from host cells. Components of the innate immune system can also activate the adaptive immune system, which is highly specific in producing antibodies that attack an invading pathogen, but this method requires 4–5 days to become fully mobilized. In this section, we will explore the ways that stressful stimuli can activate the immune system, especially the innate immune system, in the absence of an infection or a nonpenetrating injury such as a blow to the stomach.

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The immune system is not the first thing that comes to mind when one considers physiological responses to stressors. As noted in Chapter 1, the prevailing view for many decades was that the immune system protected the body from invading pathogens and was largely self-­regulating and concerned with making distinctions between “self” and “non-self.” Therefore, it made little sense for the immune system to also be activated in response to the stresses and strains of daily life. Now, a radically different view of the immune system has emerged that suggests it has evolved to detect damage and protect against danger. In doing so, the immune system interacts with a network of other bodily tissues, including the brain (Matzinger, 1994, 2002). The first experiments to suggest a role for the brain in regulating immune function were conducted in the 1920s by investigators at the Institut Pasteur in Paris, who described alterations in immune function in guinea pigs exposed to Pavlovian conditioning (Metalnikov & Chorine, 1926). This line of research was given new life by Ader and Cohen (1975), who reintroduced the phenomenon of conditioned immunosuppression. If the activity of the immune system was subject to conditioning, then it quickly followed that brain circuits must play a key role. Several early reports in the 1970s and 1980s provided convincing evidence of interactions between the central nervous system, the endocrine system, and the immune system. Other studies provided clear evidence of direct innervation of immune cells of the spleen, bone marrow, lymphatic tissue, and thymus by postganglionic sympathetic nerve terminals (Madden & Felton, 1995). In their influential review, Elenkov, Wilder, Chrousos, and Vizi (2000) described the presence of sympathetic noradrenergic nerve fibers in various lymphoid organs, the release of norepinephrine from the sympathetic nerve terminals in these organs, and the expression of adrenergic receptors on lymphoid cells, which were able to respond functionally to adrenergic stimulation. The axon terminals of sympathetic nerves do not make synaptic contact with immune cells; rather, norepinephrine released from sympathetic nerve terminals diffuses a considerable distance from its site of release and exerts its effects nonsynaptically. In multicellular organisms, the innate immune system has evolved to recognize, contain, and eliminate invading pathogens. The basis for recognizing invading pathogens is tied to pathogen-­associated molecular patterns (PAMPs), highly conserved molecules (e.g., proteins, carbohydrates, and double-­stranded RNAs) that are unique to pathogens and that are not found in the host. An example of a PAMP is lipopolysaccharide (LPS), an endotoxin that is a component of the outer membrane of gram-­negative bacteria. Molecules like LPS are detected by soluble or membrane-­associated pattern recognition receptors (PRRs) (Janeway, 1989). One family of PRRs, the toll-like receptors (TLRs), are expressed on the outer plasma membrane of neutrophils, macrophages, and dendritic cells, and when activated, they stimulate inflammatory and antimicrobial innate immune responses. Among the multiple genes that may be upregulated are the antiviral interferons; the proinflammatory cytokines interleukin-1b (IL-1b), IL-6, and IL-12; tumor necrosis factor a (TNF-a); and various chemokines, all of which can serve as chemo-­attractants and guide immune cells in moving to the site of an infection or tissue damage (Akdis et al., 2016). The first interleukin, leukocyte pyrogen (IL-1), was initially described by Dinarello, Renfer, and Wolff (1977), and this seminal discovery has been followed by many additions to the growing list of ILs since that time. A second family of receptors, the nucleotide-­ binding oligomerization domain (NOD)-­ like receptors (NLRs), are cytoplasmic receptors that recognize microbial



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products and danger-­associated molecular patterns within body cells. Upon activation, NLRs activate multiple downstream signaling pathways that promote inflammatory responses, inflammasome assembly, and transcriptional activity (Motta, Soares, Sun, & Philpott, 2015). Following a nonpenetrating blow to the body (sterile inflammation), damage to bodily tissues can result in cell death and the release of molecules that are usually safely tucked away in the cytoplasm of cells (Chen & Nuñez, 2010). These molecules, referred to as damage-­associated molecular patterns (DAMPs) or alarmins, are bound by PRRs, and the damaged cells can be eliminated by phagocytosis. More recently, Rider, Voronov, Dinarello, Apte, and Cohen (2017) suggested that some alarmins could serve a dual purpose within cells that are not necrotic and have not lost the integrity of the plasma membrane. In such instances, these molecules, now referred to as stressorins, may reflect cellular stress resulting from DNA damage, heat shock, or oxidative stress. Stressorins, including IL-1a, IL-33, and IL-16, share structural and sequence similarities, do not require receptor stimulation or de novo synthesis, and likely sense intracellular damage through posttranslational modifications. Similar to cytokines, but in contrast with alarmins, they are most likely actively secreted by somatic cells, but they require no additional processing by specific innate immune cell proteases and signal in a manner similar to alarmins (Rider et al., 2017). In addition, immune cells can recruit other cells to engage with the invading pathogens by secreting two diverse classes of proteins, cytokines and chemokines. Cytokines are a broad class of small peptides that act through cell surface receptors and play an important role in signaling between cells, especially cells of the immune system. They typically do not cross the blood–brain barrier. Chemokines are also a family of small proteins that act through cell surface receptors to guide the movement of cells. This is especially true in guiding the movement of immune cells such as lymphocytes from the blood to sites of infection and tissue damage. The sentinel function is carried out by macrophages and dendritic cells, specialized immune cells that are found throughout the body and that constantly sample the local tissue environment in search of invading pathogens. When PAMPs or DAMPs are detected and PRRs are activated, specific genes in the macrophages are induced and the cells change into an activated state. For inflammasome-­independent cytokines, such as IL-6 and IL-10, there is an increase in inflammatory gene transcription, translation, protein synthesis, and cytokine release. The rapid and relatively indiscriminate targeting of PAMPs is usually sufficient to beat back an invading pathogen. Unfortunately, the potential for rapid proliferation by many bacterial pathogens, which can undergo cell divisions about every 20 minutes, occasionally overwhelms the innate immune response. At this point, the phylogenetically more recently evolved adaptive immune system springs into action. The adaptive immune system only occurs in vertebrates. Although it is slower to attain full capacity, it has the ability to target a specific pathogen based on antigens present on its outer cell membrane. Importantly, the adaptive immune system becomes more effective with each exposure to a given pathogen, and some of its cells retain a memory of the antigen associated with a given pathogen. Cells of the adaptive immune system also benefit from signaling molecules released from cells associated with the innate immune response, receiving information relating to the location of the challenge and when to terminate the response. Let’s return to the critical question: why do social stressors stimulate a pro-­ inflammatory response in humans? One answer to this critical question was offered by

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Slavich and Irwin (2014), who described an anticipatory response of the innate immune system prior to an injury that could lead to tissue damage and increase the chances of an infection. By directing immune cells to potential sites of infection, the probability of postinjury wound healing and recovery would be enhanced. For most of our evolutionary history as a species, humans have confronted potential sources of danger from predators or from aggressive neighbors. The anticipatory immune responses that served us so well for thousands of years have now carried over to modern humans, who confront a range of nonlethal social stressors related to social conflict and isolation, rejection by a loved one, loss of a job, and so on. Repeated exposure to social adversity results in an upregulation of pro-­inflammatory innate immune response genes and a downregulation of antiviral innate immune response genes. These transcriptional effects are tied to sympathetic–­adrenal medullary and cortisol responses to repeated stressors. Slavich and Irwin (2014) have termed this anticipatory response the conserved transcriptional response to adversity. In a similar way, Miller and Raison (2016) argued that modern humans continue to carry with them an evolutionary bias in how the innate immune system responds to stressors. The prevailing dangers confronting early humans were associated with hunting for food, being hunted by predators, or direct competition with group members for social status and access to food and mates. They recalled that early humans evolved in a pathogen-­rich environment, so any serious break in the skin could be viewed as a possible life-or-death situation. They suggested that individuals who responded to threatening social or environmental cues with an anticipatory activation of the innate immune system would have enjoyed higher survival rates. Such a system would not place a high penalty on false alarms, such as when the threats did not materialize. But anticipatory immune activation evolved in such a way that activation was rapid, but equally important, a return to a basal state occurred when the threat had passed. Fast-­forward to modern humans, and we retain the capacity for nonthreatening social stressors to activate the innate immune system, leading to deleterious effects on our health. This is especially true when the daily hassles, worries, fears, threats, competition, and microaggressions that come from living in a complex social environment lead to a state of persistent, low-grade inflammation (Furman et al., 2019). This state of systemic chronic inflammation presents a range of health challenges that we will confront later in the disease-­specific chapters. One manifestation of chronic immune activation is a constellation of behavioral and physiological changes referred to as “sickness behaviors.” These include reduced interest in social interactions, decreased energy levels, sadness, lack of interest in pleasurable activities, decreased food intake, disruptions in the sleep–wake cycle, elevated blood pressure, and insulin resistance (Dantzer & Kelley, 2007).

Pro‑inflammatory Biomarkers Interleukins and Cytokines Interleukins (ILs) are a group of more than 60 small protein molecules that provide a critical mode of communication between various types of leukocytes and other immune cells. ILs bind to cell surface receptors to alter target cell functions, where they may exert pro-­inflammatory or anti-­inflammatory effects or a combination of the two (Akdis et



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al., 2016). Many experiments relating to stress and health have measured ILs (and in some instances their soluble receptors) in blood as an index of stress responsiveness. Among the more frequently measured ILs are: 1. IL-1b: a pro-­inflammatory cytokine produced by monocytes, lymphocytes, and brain microglia. Primary targets are epithelial and endothelia cells through IL-1 type 2 receptor signaling. 2. IL-4: an anti-­inflammatory cytokine produced by several classes of T cells, platelets, and mast cells. Primary targets are T and B cells through IL-4 type I and II receptor signaling. 3.  IL-6: a pro-­inflammatory cytokine produced by endothelial cells, monocytes, macrophages, T and B cells, smooth muscle cells, glial cells, and so on. Primary targets include hepatocytes, leukocytes, and T and B cells through IL-6 receptor signaling. 4.  IL-10: an anti-­inflammatory cytokine produced by T and B cells, monocytes, macrophages, and dendritic cells. Primary targets include macrophages, monocytes, T and B cells, and dendritic cells signaling through IL-10 type 1 and type 2 complexes. 5. Tumor necrosis factor a (TNF-a): a pro-­inflammatory cytokine produced by activated macrophages, monocytes, T and B cells, microglial cells, mast cells, and so on. Primary targets include nucleated cells expressing TNF type 1 and 2 receptors. TNF-a also exerts anti-­inflammatory effects by dampening inflammatory processes and blocking tumorigenesis.

C‑Reactive Protein C-­reactive protein (CRP) is a circulating protein that is produced by the liver in response to increased levels of IL-6 secreted by macrophages. CRP binds to phosphocholine expressed on dead or dying cells and on some bacteria, which activates the complement system and promotes removal of the dying cells or bacteria by macrophages via phagocytosis. Circulating levels of CRP can increase dramatically (up to 10,000-fold) following infection, trauma, tissue death, malignancy, and allergic reactions. Because CRP levels are measured frequently in patients with autoimmune conditions and infections, they are also useful in assessing stress levels and inflammatory status in individuals caring for dementia patients as well as in large-scale studies of stress and inflammation through data mining of electronic medical records (Gouin, Glaser, Malarkey, ­Beversdorf, & Kiecolt-­Glaser, 2012).

Interpretation of Inflammatory Markers Many factors can influence circulating levels of inflammatory biomarkers that are frequently employed as dependent variables in biobehavioral research, and they should be considered when designing an experiment or interpreting the results of a published study. These factors include: age, sex, socioeconomic status, race and ethnicity, diet, fitness level, sleep–wake patterns, prescription medications, tobacco and alcohol use,

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and caffeine intake. With such an extensive list, it would seem that conducting a study of biopsychosocial influences on immune biomarkers would be a hopeless task. But as we will see, this is not the case. In fact, many exciting findings have been reported in this area based on highly controlled laboratory experiments with small sample sizes as well as larger, population-­based studies relating long-term increases in inflammation to elevated risks of various chronic diseases (Furman et al., 2019; Navarro et al., 2016; O’Connor et al., 2009; Rohleder, 2014; Shields, Spahr, & Slavich, 2020).

POINT‑OF‑USE SENSORS This relatively recent method for quantifying biomarkers of stress seeks to eliminate the need for laboratory-­based analyses and to allow rapid and sensitive measurements of stress biomarkers at reasonable cost in blood, saliva, sweat, and urine at the point of use (e.g., home-based) or the point of care (e.g., a physician’s office). The analytical approaches that have been employed include antibody- and aptamer-­based colorimetric assays, with electrochemical and optical detection of cortisol, IL-6, TNF-a, NPY, epinephrine, norepinephrine, dopamine, serotonin, oxytocin, and other stress-­related molecules. One major challenge for biosensor development is that stress biomarkers vary by up to six orders of magnitude in various bodily fluids, from a few pg/ml to hundreds of ng/ml. In addition, for any one biomarker, levels may change dramatically across body fluids (Steckl & Ray, 2018). A recent refinement in sensor technology has included the development of assays that utilize label-free optical absorbance of near-­ultraviolet light (190–400 nm), with quantification of multiple biomarkers in a single sample based on photocurrents generated at biomarker-­specific wavelengths (Ray & Steckl, 2019). This rapidly developing field bears watching, with many new advances and refinements occurring each year. As this technology matures, it could become an important component of a precision medicine approach to treating stress-­related diseases in patients (Kim, Lee, et al., 2020).

Wearables to Continuously Measure Stress‑Related Variables Smart watches and fitness-­related wearable devices have also been adapted to provide continuous quantitative measures of stress-­related variables under “real-world” conditions. One type of sensor, the HealthPatch®, illustrates the utility of these devices in studies of daily stressors in freely moving individuals. The HealthPatch is a small, flexible, self-­adhesive, battery-­powered wearable that provides continuous measurements of heart rate parameters, respiratory rate, skin temperature, and blood oxygenation, with encrypted data streamed to a smartphone via Bluetooth for later cloud-based storage and analysis. The device also computes a measure of stress levels (with a range of 0–100) every 4 seconds based on an algorithm that includes heart rate and the standard deviation of the interval between two heart beats. The resting heart rate of each individual is used to calibrate the stress measure, and computations do not occur during periods of physical activity. These devices were employed successfully in a study of stress levels experienced by medical residents and attending physicians during surgeries (Weenk et al., 2018). Gordon and Mendes (2021) recruited participants for a study of blood pressure responses to naturally occurring stressors from among those individuals who



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downloaded the MyBPLab app from the U.S. Google Playstore between March 2018 and June 2019. They engaged more than 20,000 participants who completed more than 330,000 measurements of blood pressure and heart rate under resting conditions and in response to daily life stressors by using a smartphone-­based optical sensor. Ku et al. (2020) took an innovative approach to measuring cortisol levels in tears using a smart contact lens that consisted of a cortisol sensor, a wireless antenna, capacitors, resistors, and integrated circuit chips that use stretchable interconnects to minimize obstruction of the wearer’s view. The cortisol sensor was integrated with a nearfield communication chip and antenna within the soft contact lens to facilitate real-time wireless and battery-­free transmission of data to the wearer’s smartphone or smart watch. The sensitivity of the cortisol sensor was well within the range of concentrations of cortisol found in tears.

GENE EXPRESSION BIOMARKERS Several laboratories have attempted to identify gene expression biomarkers in blood samples and relate those changes to perceived and objectively measured levels of life stress. As one example of this experimental approach, Le-­Niculescu et al. (2020) utilized a within-­subjects design to identify gene expression changes associated with self-­ reported psychological stress levels connected to mental disorders. However, the strategy could apply equally well to psychological stress levels associated with other chronic diseases. Six candidate genes in blood samples were strongly associated with psychological stress levels in patients: 1.  FK506 binding protein 5 (FKBP5). This protein regulates glucocorticoid receptor sensitivity by binding to GRs and reducing the binding affinity of cortisol and the efficiency of nuclear translocation of the hormone-­receptor complex. These changes have a direct impact on the efficiency of negative feedback regulation of the HPA axis (Matosin, Halldorsdottir, & Binder, 2018). Expression of the FKBP5 gene was decreased in response to high-­stress states in the samples of psychiatric patients. 2.  DEAD-box helicase 6 (DDX6). The highly conserved DEAD-box family of helicases plays an essential role in RNA metabolism and has pronounced effects on gene transcription, with DDX6 involved in RNA storage and breakdown (Linder & Jankowsky, 2011). Expression of the DDX6 gene in the samples of psychiatric patients was increased in response to high-­stress states. 3.  Beta-2-microglobulin (B2M). B2M, a highly conserved small protein, plays an important role in immune surveillance and IL signaling (Li, Dong, & Wang, 2016). Expression of the B2M gene was increased in response to high-­stress states in the samples of psychiatric patients. 4.  Leukocyte-­ associated immunoglobulin-­ like receptor 1 (LAIR1). LAIR1 is expressed on most cells of the immune system and is regulated by extracellular matrix collagens. LAIR1 signaling is important in preventing the development of autoimmunity (Meyaard, 2008). Expression of the LAIR1 gene was decreased in response to high-­ stress states in the samples of psychiatric patients.

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5.  Reticulon 4 (RTN4). RTN4 is a member of a family of proteins that are localized to the endoplasmic reticulum of most cells. RTN4 plays a role in vascular remodeling as well as recruitment of macrophages to areas of inflammation and tissue damage (Yu et al., 2009). Expression of the RTN4 gene was increased in response to high-­stress states in the samples of psychiatric patients. 6.  Negative regulator of ubiquitin like proteins 1 (NUB1). NUB1 is an interferon-­ inducible protein that regulates the cell cycle and neurodegeneration (Kito, Yeh, & Kamiani, 2001). Expression of the NUB1 gene was increased in response to high-­stress states in the samples of psychiatric patients, especially in females. At first glance, this list of the six genes that exhibited the greatest changes in response to psychological stress might be a bit surprising. With the exception of FKBP5, which is strongly associated with regulation of the HPA axis, four of the remaining five genes are involved in immune regulation. But there is a growing body of convergent evidence from studies of animal models and from clinical studies that dysregulated immune response genes play critical roles in adaptive and maladaptive responses to stressful stimulation (e.g., Breen et al., 2018).

EPIGENETIC BIOMARKERS The term epigenetics was first employed by Conrad H. Waddington (1905–1975) to reflect, from an embryological perspective, the dynamic processes that could result in changes in the phenotype in the absence of changes in the genotype (Waddington, 1942). Over time, the definition of epigenetics was refined to reflect three key features: (1) Epigenetic changes do not result in a change in the sequence of bases in the DNA molecule, but rather affect the transcription of genes, (2) epigenetic changes are readily reversible, and (3) some epigenetic alterations may endure for the life of an organism and can be passed to succeeding generations through epigenetic changes in germ cells (Jawaid & Mansuy, 2019; Keller & Roth, 2016; Mashoodh & Champagne, 2019; Morgan et al., 2019). In all cells with a defined nucleus (e.g., eukaryotes), more than 2 meters of linear DNA must be packaged into the small confines of a nucleus that is approximately 10 mM in diameter. To solve this problem, DNA forms complexes with specialized histone and nonhistone proteins to yield chromatin. The basic unit of chromatin is the nucleosome, which consists of a disc made up of two copies each of four histone proteins (H2A, H2B, H3, and H4). DNA wraps around this disc like thread around a spool, with 146 base pairs of DNA making slightly less than two turns around the histone disc. After a short spacer segment of 10–50 base pairs of DNA, the next nucleosome forms, such that chromatin takes on the appearance of beads on a string. A fifth histone, H1, serves as a connector between successive nucleosomes. The long string of nucleosomes is further compacted into a secondary helical structure, a pipe-like solenoid array that is further condensed into loops of approximately 100,000 base pairs each. The N-­terminal tails of the histone proteins protrude from the nucleosome cores and may be modified by methylation, acetylation, ubiquitination, or phosphorylation of individual amino acids.



Biological Measures of Stress 45

These histone modifications have been referred to collectively as the “histone code,” and these alterations significantly enhance the information capacity of the genetic code (Allis & Jenuwein, 2016; Jenuwein & Allis, 2001; Strahl & Allis, 2000). These modifications to histones do not act in isolation from other epigenetic changes, including direct methylation of DNA bases. Rather, they combine to form a complex network to encode responses to acute stressors, modify responses to future stressors, shape phenotypic characteristics, and influence risk for disease (Klengel & Binder, 2015; Klengel, Binder, & Mehta, 2014; Sweatt & Taminga, 2016). A natural tension arises between the need for condensation and effective storage of DNA versus the need for DNA to be accessible for transcription of genes and replication of DNA during cell division. When a portion of the DNA molecule is tightly wound around a nucleosome core, the genes it contains are not readily accessible to the transcriptional machinery required for producing the corresponding mRNAs. This relatively inactive state of DNA is referred to as heterochromatin. Euchromatin represents a more relaxed chromatin state that is mediated by acetylation or phosphorylation of amino acid residues of histone tails, thereby reducing the affinity of histone octomers for DNA and increasing rates of gene transcription (Allis & Jenuwein, 2016). A second type of epigenetic change involves direct methylation of cytosine bases within DNA. These changes are catalyzed by DNA methyltransferases and typically occur at cytosine–­phosphate–­guanine (CpG) dinucleotides. These highly stable epigenetic marks typically exert an inhibitory effect on gene transcription, but under some circumstances they may actually enhance gene transcription. A third type of epigenetic change involves synthesis of microRNAs (miRNAs) that do not code for proteins. The primary role of miRNAs is in extranuclear regulation of gene expression by inhibiting the translation of recently transcribed mRNAs into protein products. This inhibitory effect is possible because each miRNA has a nucleotide sequence that binds to complementary sequences within mRNAs, thereby limiting access of the specific mRNA to the machinery of protein synthesis. Each miRNA may regulate the translation of several to hundreds of different mRNAs into proteins, and individual mRNAs may be inhibited by multiple miRNAs. These overlapping inhibitory signals represent a complex system for regulating the translation of individual mRNAs into proteins. Zannas and Chrousos (2017) proposed two sensitive periods across the human lifespan when cortisol-­driven epigenetic changes in response to stressful stimuli are most likely to occur: during early development and in advanced age. They suggested that these stress-­induced epigenetic signatures tend to accumulate throughout life in selected regions of chromatin and on a genome-­wide basis. A major challenge going forward is to understand the molecular genetic pathways that are responsive to stressful stimuli and that influence the behavioral and physiological parameters that contribute to susceptibility to diseases (Zannas & Chrousos, 2017). While many excellent reports have been published on prenatal stress-­induced epigenetic changes in brain and other tissues in animal models (McCarty, 2020), such studies are next to impossible to conduct in pregnant women because of ethical concerns, the difficulty of randomly assigning pregnant women to control and stress exposure groups, and the importance of determining the objective and subjective responses of pregnant women to a given stressor. One creative approach to addressing some of these experimental design concerns was presented by Cao-Lei et al. (2014), who took

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advantage of the severe winter ice storms that devastated southern portions of the province of Quebec in January 1998 to recruit a sample of 176 women who were pregnant during the ice storms or who conceived within 3 months after the storms when hardship conditions persisted. Women completed two questionnaires 5 months after the storms to assess objective (property damage, injuries, days without power, etc.) and subjective (hyperarousal, intrusive thoughts and images, etc.) responses to the stressful conditions. The children of these mothers provided saliva samples at age 8 and blood samples at age 13. These samples were later analyzed for patterns of genome-­wide DNA methylation, a form of epigenetic change. The findings of this study revealed that objectively measured stress levels (but not subjective distress levels) were significantly correlated with DNA methylation patterns for 957 genes, many of which were associated with regulation of immune function. These changes were detected in saliva samples as well as T cells and mononuclear cells from blood samples, and there were no sex differences. These exciting findings documented that objectively measured levels of stress in pregnant women who experienced a punishing natural disaster were associated with persistent and widespread DNA methylation changes in cells from the blood and saliva of their offspring (Cao-Lei et al., 2014). A second approach to investigating epigenetic changes in humans exposed to significant early life stressors is by studying postmortem samples of brain tissue. In one such study, postmortem brain samples were obtained from three groups of males in their mid-30s: (1) suicide completers with a history of child abuse, (2) suicide completers without a history of child abuse, and (3) controls who died from accidental causes and with no history of child abuse. The focus of this study was on the glucocorticoid receptor promotor (NR3C1) in the hippocampus, as it plays a key role in negative feedback regulation of the HPA axis. The results of this study pointed to increased site-­specific methylation of exon 1F of the NR3C1 promoter and corresponding decreases in GR expression in suicide victims with a history of childhood abuse, compared to suicide victims with no history of childhood abuse and controls who died accidentally (McGowan et al., 2009). A third approach involves the impact of noncoding RNAs on protein synthesis. Extracellular vesicles (EVs, also referred to as microvesicles or exosomes) are likely candidates for conveying molecular signals to maturing sperm cells, fertilized ova, and tissues of the female reproductive tract, thereby influencing fetal development (Morgan et al., 2019). EVs are composed of a lipid bilayer that encloses cytosolic proteins and RNAs. EVs may be formed and released by budding from the plasma membrane of cells of origin. In addition, EVs may arise within cells of origin, with secretion occurring when the membranous structures fuse with the inner cell membrane. Surface molecules on EVs bind to receptors on target cells, and at this point receptor–­ligand interactions may occur, or the EV may be internalized into the cytoplasm of the target cell. Once liberated from the EV, the signaling molecules can alter the physiological state of the target cell (Tkach & Théry, 2016). Sperm maturation in the epididymis has been identified as a likely point at which environmental stimuli can alter sperm programming. For example, Reilly et al. (2016) reported on significant changes in the composition of miRNAs contained in specialized EVs, called epididymosomes, along the length of the mouse epididymis. Epididymosomes arise from epithelial cells lining the epididymis and contain a complex cargo of proteins, lipids, and more than 350 miRNAs. Many of these miRNAs are in much



Biological Measures of Stress 47

higher concentrations within the epididymosomes compared to the surrounding epithelial cells. In addition, more than 50 miRNAs were found only in sperm and EVs within the epididymis, but not in the surrounding epithelial cells. Epididymosomes may also deliver their miRNA cargo to the female reproductive tract and the fertilized oocyte, contributing an epigenetic memory trace of prior paternal stressful experiences to the developing embryo (Chen, Yan, & Duan, 2016; Morgan et al., 2019). This sperm-­related epigenetic signal sounds interesting in theory, but is there experimental evidence to back it up? In a report by Dickson et al. (2018), miRNAs were analyzed in sperm samples collected from male mice exposed to chronic social stress during adolescence or from human males who completed the Adverse Childhood Experiences (ACE) questionnaire. Compared to unstressed control mice, mice exposed to stress during adolescence displayed significant reductions in miRNAs 449 and 34. Remarkably, these same miRNAs exhibited an inverse correlation with ACE scores in adult male sperm samples. Reductions in these miRNAs may influence embryonic development and can be transmitted across generations in mice (Dickson et al., 2018). As we will see in some of the following chapters of this book, transgenerational epigenetic changes have been shown to affect a wide range of disease phenotypes, including those related to obesity, diabetes, cardiovascular disease, kidney disease, autoimmune diseases, cancer, and mental disorders (Tollefsbol, 2019). In summary, epigenetic changes studied in peripheral blood cells and in saliva samples provide a glimpse of stress-­induced changes in gene transcription that may persist into succeeding generations. On rare occasions, epigenetic alterations have been studied in postmortem brain samples, and these results may be compared to changes in the periphery. Many of the research questions addressed in these studies have been informed by carefully controlled studies in laboratory animals. This rapidly growing body of research is an excellent example of translating basic research findings to increase understanding of the etiology of human diseases and improvements for treatment and prevention (McCarty, 2020).

CONCLUSIONS This chapter has revealed a host of stress-­ responsive biological systems as well as approaches for measuring their activity under basal conditions and during and following exposure to stressors. From the earliest days of research on stress in the first half of the 20th century as led by Walter B. Cannon and Hans Selye, the autonomic nervous system and the HPA axis have been synonymous with stress responses in humans and in laboratory animals. More recently, immune parameters and epigenetic alterations in gene transcription have become the focus of scientists interested in the persistent role of stressful life experiences on health and disease. We will return to the methods for measuring the activities of these systems in later chapters as we tackle the impact of stress on specific diseases.

CHAPTER 3

Behavioral Measures of Stress

I

f you happen to scan the covers in the magazine section when you are grocery shopping, you quickly realize that there is a high level of interest in the connection between stress and wellness. Many of the articles from the magazine section provide strategies for effective management of stress levels and attendant improvements in health. Alternatively, these same articles often include dire warnings about the effects of persistently high-stress levels on negative health outcomes, including mental and physical disorders. As compelling as these articles are, they do not provide definitive evidence of a link between high-stress levels (allostatic load) and increased risk for disease. And yet, as we have already discussed, physicians and scientists from various disciplines have developed ways of measuring responses to stress and confirming such links. In this chapter, we will consider some of the approaches to measuring psychological adjustments following exposure to stressful stimuli in individuals, groups, and populations using a variety of approaches, including experiments under highly controlled laboratory conditions and on a cumulative basis in epidemiological studies using questionnaires to assess stress levels. We will combine these psychological measures of stress with the information on biomarkers of stress that were described in Chapter 2 to construct the pathways and processes relating stress to health and disease in later sections of this book. Even though the early emergence of stress as a field of study was dominated by biomedical researchers, our current understanding of connections between stressors and health has been greatly enhanced by the innovative work of social scientists. Epel and her colleagues (Epel et al., 2018) have developed a useful classification system relating to stressor exposure and psychological responses to stressors that will guide our survey of measures of psychological stress. Their system presents four variables relating to stressor exposure, including: 1. Timescale of stressor exposure. Acute exposure, records of daily exposures to stressors, a retrospective catalogue of significant life events, or identification of longterm, ongoing chronic stressors. 48



Behavioral Measures of Stress 49

2.  Developmental stage of stressor exposure. In utero stressor exposure due to maternal stress levels, stressor exposure during early childhood and/or adolescence, stressor exposure during adulthood, or retrospective or prospective measures of cumulative stressor exposure. 3.  Temporal aspects of stressor exposure. Moment-­ to-­ moment notations, daily entries, or retrospective accounts varying across weeks to months to years. 4.  Characteristics of the stressor. Characterization of stressors based on duration, severity, and level of control over the stressor; impact of the stressor on areas of one’s life (e.g., education, employment, housing, finances); impact of the stressor on an individual, his or her family and friends, and the local community; and potential of the stressor to inflict harm through loss of a loved one, threats to one’s person or status, and disruptions to way of life. Also of relevance to our discussion are the psychological responses following exposure to stressful stimuli in the laboratory or following naturally occurring events in one’s daily life. Drawing on the classification system of Epel et al. (2018), psychological measures of responses to stressor exposure may be grouped in the following ways: 1.  Psychological responses to specific stressors. These responses include measures of motivation, emotion, cognitive appraisals, coping strategies, emotion regulation, and rumination. 2.  Subjective measures of responses to stress within a life domain. Life domains include employment, neighborhood environment, financial strain, social interactions, and discrimination and microaggressions. 3.  Global subjective stress levels. Such measures provide a gauge of overall stress levels. In the sections that follow, I will be guided by the Epel et al. (2018) classification system as I present a range of laboratory paradigms to provoke stress responses in human participants as well as experimental approaches to measure psychological stress responses acutely or over longer time domains varying from days to months to years.

ACUTE LABORATORY PARADIGMS FOR PROVOKING STRESS RESPONSES Trier Social Stress Test The Trier Social Stress Test (TSST) was developed at the Universität Trier in Germany in the late 1980s and early 1990s by Professor Dirk H. Hellhammer (1947–2018) and his associates (Kirschbaum, Pirke, & Hellhammer, 1993). As originally described, the TSST involved bringing individual human participants into the laboratory where they were allowed 10 minutes to rest (30 minutes if a venous catheter was inserted) and have their physiological and hormonal measures return to baseline levels. Each participant

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was then taken into an adjacent room and given instructions about a public speaking task (a job interview) and a mental arithmetic task (e.g., serially subtract 13 from 1,022 as rapidly as possible) that would occur and take 10 minutes to complete. The panel of three judges and the video and audio taping equipment were present in the adjacent room while the instructions were provided. Participants then returned to the first room, were allowed 10 minutes to prepare their remarks, and then returned to the second room and delivered their remarks to the panel of experts for 5 minutes and performed serial subtraction for 5 minutes. Next, participants were returned to the first room for a debriefing and were allowed 30–70 minutes to rest quietly depending on the hormonal and physiological measures that were taken. A timeline of the TSST as originally described is presented in Figure 3.1. In the initial report that described experiments with six separate groups of participants (Kirschbaum et al., 1993), during the test there were robust and consistent increases in subjective measures of stress, circulating levels of growth hormone, ACTH, cortisol, and prolactin, as well as increases in salivary cortisol and heart rate. The combination of public speaking and mental arithmetic was a more potent psychological stressor than either stressor alone. More recent studies have added to the list of peripheral biomarkers activated by the TSST, including plasma catecholamines and sAA; the adrenal steroid dehydroepiandrosterone and its metabolite, dehydroepiandrosterone sulfate; IL-1b, IL-2, and IL-6; and systolic blood pressure and galvanic skin response. Since the formulation of the original TSST protocol, modifications have been made to permit testing of groups of participants (TSST-G) as well as children (TSST-C) with minor changes in testing procedures (Allen et al., 2014). In addition, the TSST has been modified for delivery online using Zoom (Gunnar et al., 2021). The TSST has been employed extensively to produce a consistent and reproducible level of psychological stress such that results can be compared across laboratories (Narvaez Linares, Charron, Ouimet, Labelle, & Plamondon, 2020). One major drawback in the original TSST protocol is the need to have three well-­trained confederates to serve as the evaluation panel for the public speaking component.

Other Stress Paradigms The TSST remains the most frequently employed standardized laboratory stress paradigm by far. However, other paradigms have been developed that permit alternative Arrival in the lab

A

Exposure to Panel

A

Baseline Period 30 min

B

Mental Math 5 min

Speech 5 min

A

Speech Preparation 10 min

B

B

Questions from Panel 10 min

B

A

Recovery + Debrief 30–80 min

FIGURE 3.1.  Timeline for the original TSST as described by Kirschbaum et al. (1993).



Behavioral Measures of Stress 51

TABLE 3.1.  Paradigms for Measuring Physiological and Psychological Stress Responses in Human Participants under Highly Controlled Laboratory Conditions Paradigm

Physiological effects

Advantages

Limitations

Trier Social Stress Test (TSST)

Reliable increases in HPA axis activity (↑ ACTH in plasma, ↑CORT in plasma and saliva, ↑ DHEA and DHEA-S in plasma), sympathetic– adrenal medullary system activity (↑ plasma NE and EPI, ↑ sAA), multiple pro-inflammatory immune parameters (↑ IL-1b, ↑ IL-2, ↑ IL-6), cardiovascular function (↑ SBP, ↑ HR). Increases in subjective stress and some evidence of changes in cognition.

The “gold standard,” so there is an extensive body of research. Induces significant activation of HPA axis and sympathetic nervous system. Modifications of TSST for use with children or groups. Possible to manipulate the type of feedback from the panel.

Labor-intensive with the three-judge panel. Evidence of habituation of HPA axis to repeated exposure. Modifications to the standard TSST paradigm may affect consistency across laboratories.

Socially Evaluated Cold Pressor Test (SECPT)

Moderate increase in HPA axis activity (↑ CORT in plasma and saliva). Decrease in pro-inflammatory response. Increase in subjective stress.

Less demanding on lab staff. The social evaluative component is comparable to the TSST. Short time required to administer the test.

Concern about pain levels. HPA activity less robust than TSST.

Maastricht Acute Stress Test (MAST)

Increase in HPA axis activity (↑ salivary CORT), increase in sympathetic nervous system activity (↑ sAA), increases in SBP and subjective stress.

Eliminates the socialevaluative component. Presents an array of stressors in a brief period of time. Less demanding on lab personnel than the TSST.

The MSST has not been used widely by stress researchers, so there is less information to guide future experiments.

Immersive Multimodal Virtual Environment Stress Test (IMVEST)

Increases in HR, salivary CORT, and extensive changes in the ANS based on measures extracted from electrodermal activity and the ECG.

VR allows for immersion and navigation in a variety of stressful environments. Mental math.

IMVEST requires validation across several laboratories.

Note. ANS, autonomic nervous system; HPA, hypothalamic–pituitary–adrenocortical axis; CORT, cortisol; ACTH, adrenocorticotropic hormone; DHEA, dehydroepiandrosterone; DHEA-S, dehydroepiandrosterone sulfate; ECG, electrocardiogram; NE, norepinephrine; EPI, epinephrine; sAA, salivary alpha-amylase; SBP, systolic blood pressure; HR, heart rate.

approaches to the TSST and offer some advantages as well as disadvantages. A summary of these paradigms is included later and in Table 3.1.

Socially Evaluated Cold Pressor Test The cold pressor test has a long tradition as a laboratory stressor to elicit activation of the sympathetic–­adrenal medullary system as reflected in increases in blood pressure (Hines & Brown, 1933). One drawback for many investigators was that the standard

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cold pressor test did not elicit significant increases in HPA axis activity. A rather simple modification made by Schwabe, Haddad, and Schachinger (2008) was to add a social evaluation component to the standard cold pressor test, resulting in the Socially Evaluated Cold Pressor Test (SECPT). This procedure involves videotaping each participant (all were males) while one hand was immersed in ice water (0–4o C) and a female researcher was observing. Each participant was told to keep his hand in the ice water for as long as possible (mean = 170 seconds). The test was ended at 3 minutes. The SECPT did result in a significantly great salivary CORT response compared to the standard cold pressor test. In addition, systolic blood pressure but not heart rate increased significantly with and without social evaluation. Participants rated stress and pain levels as comparable between the two cold pressor conditions. The authors concluded that the SECPT was more efficient and required fewer laboratory personnel than the TSST (Schwabe et al., 2008).

Mannheim Multicomponent Stress Test The Mannheim Multicomponent Stress Test (MMST) does not include a social evaluative component comparable to public speaking as we saw in the TSST. Instead, the MMST includes four different types of stressors, all packed into a 5-minute test period. These include a paced auditory serial addition task (cognitive stressor), a set of emotion-­ laden photographic slides (emotional stressor), white noise increasing from 7 to 93 dB and delivered through headphones (acoustic stressor), and loss of a portion of the participation fee for each incorrect answer in the serial additional task (motivational stressor). Using this combination of stressors, this team of researchers reported significant increases in subjective ratings of stress, heart rate, electrodermal activity, and salivary CORT. Compared to the TSST, the MMST does not require a panel of evaluators and is more efficient in terms of demands on laboratory personnel (Reinhardt, Wüst, & Bohus, 2012). However, the biological responses to the combination of stressors were not as dramatic as they were for the TSST.

Maastricht Acute Stress Test The Maastricht Acute Stress Test (MAST) was also developed as another option to the more frequently employed TSST. Following a 5-minute instruction and preparation phase delivered via a PowerPoint slide deck, each participant was instructed to perform five separate cold pressor tests (by immersing the hand up to the wrist in water maintained at 2o C) that were socially evaluated and lasted 60–90 seconds. During the inter-­test intervals, participants were instructed to perform a serial subtraction task as rapidly as possible while being evaluated by an experimenter. Sessions were videotaped as a further element of social evaluation. They were also instructed that the timing and duration of the cold pressor and serial subtraction tests would be randomly assigned by a computer program to reduce control and predictability. In fact, these parameters were preset and were identical for each participant. The MAST resulted in significant elevations in salivary levels of CORT and alpha-­ amylase as well as increases in subjective stress ratings. These investigators advanced the MAST as a more economical laboratory stressor compared to the TSST. In addition, the combination of physical (cold pressor test) and psychological (serial subtraction)



Behavioral Measures of Stress 53

stressors activate different brain circuits and may be more attractive than the TSST (Smeets et al., 2012). Finally, a modification of the MAST, the iMAST, has resulted in a stress paradigm that can be used in magnetic resonance imaging (MRI) studies of stress effects on brain functioning (Quaedflieg, Meyer, & Smeets, 2013).

Immersive Multimodal Virtual Environment Stress Test Rodrigues, Studer, Streuber, and Sandi (2021) reported on their characterization of physiological responses to a multimodal virtual environment stress test in which participants are exposed to mental math calculations, environmental challenges, and intense visual and auditory stimuli. A special feature of the Immersive Multimodal Virtual Environment Stress Test (IMVEST) is that it can adjust the degree of difficulty of mental math to the performance of an individual participant. In addition, control participants can be exposed to a similar but much less stressful experience. Finally, IMVEST affords an opportunity to deploy similar stressful experiences for participants in multicenter collaborative experiments (Rodrigues et al., 2021).

Summary of Laboratory‑Based Stress Paradigms The cold pressor task was introduced almost a century ago to screen for patients with cardiovascular disease. Other laboratory stressors were introduced over the years, but none caught on as a reliable and widely adopted paradigm. Then the TSST emerged as the “gold standard” for laboratory stress paradigms in the 1990s. As one measure of its impact on laboratory-­based stress research, the original paper (Kirschbaum et al., 1993) that detailed the methodology and its effect on the HPA axis has been cited more than 6,000 times. More recently, two other stress paradigms (MAST and MSST) have been described, and they tend to be less labor-­intensive than the TSST (Allen, Kennedy, Cryan, Dinan, & Clarke, 2014; Balli & Jaggi, 2015). Each of these methods for inducing stress acutely in the laboratory provides a valuable approach to compare the stress responses of various patient groups to a healthy control group to determine if the risk of a given disease or its diagnosis is associated with a disruption in regulation of various stress-­responsive systems (Table 3.1). This issue will be discussed in greater detail later in this book.

ACUTE PSYCHOLOGICAL MEASURES OF STRESS APPRAISAL When participants are exposed to one of the laboratory stress paradigms (TSST, MAST, MSST, etc.), it is often helpful to assess participants’ cognitive appraisals of task demands and their estimates of available personal cognitive resources to cope with those demands after the stress protocol has been described and following completion of the stress paradigm. An example of this approach is described in Mendes, Blascovich, Hunter, Lickel, and Jost (2007), where the response scales ranged from 1 (strongly disagree) to 7 (strongly agree). Six questions probed appraisals of task demands (demanding, stressful, distressing, threatening, uncertainty, level of effort), and then five questions examined appraisal of personal resources to perform the task (abilities, expectations, level of importance, nature of the challenge, personal qualities). Ratings for the task demand

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questions and the resource questions were averaged, and a threat index was calculated as the demands/resources ratio. After completion of the stress paradigm, similar questions relating to demands and resources were administered. Across a number of studies, it has been reported that pretask appraisals are more predictive of physiological responses during the task than posttask appraisals.

The Importance of Minor Stressors As described in Chapter 1, Holmes and Rahe (1967) stimulated a strong focus on the deleterious effects of major life events on health. Few would argue that death of a loved one, loss of a job, or even relocation to a new city constitute some of the major stressors that we face over the course of our lives. However, major life events do not provide a full picture of the stressors that are a frequent and recurring part of our lives. Indeed, minor stressors, or hassles, also contribute to allostatic load and may have a negative impact on well-being. In contrast, pleasurable events, or uplifts, are the counterpoint to hassles and provide brief moments of pleasure and joy, and they may provide buffers against the possible deleterious health effects of hassles. In one of the first comprehensive studies of daily hassles and uplifts, Kanner, Coyne, Schaefer, and Lazarus (1981) constructed scales for hassles (117 items) and uplifts (135 items) and administered them each month for 9 months to a community sample of 100 middle-­aged adults. Each hassle that was checked was rated for severity on a 3-point scale, and each uplift that was checked was also rated on a 3-point scale for how often it occurred (1, somewhat; 2, moderately; 3, extremely). Summary scores for hassles and uplifts included the following: frequency, number of items checked; cumulative intensity, the sum of the 3-point ratings; and mean intensity, sum of the 3-point ratings divided by the frequency. Table 3.2 lists the 10 most frequently reported hassles and uplifts over the 9-month sampling period. Although some of the items would surely change today, there are many familiar examples of hassles and uplifts that we continue to encounter in our everyday lives.

Perceived Stress Scale Serious reservations have been expressed over the years about the limitations of the Holmes–­Rahe Stress Inventory (HRSI) because a cumulative stress score is computed based on the occurrence of stressful life events over the previous year. However, the stressful nature of the life events was rated by an independent group of people, and those ratings do not necessarily reflect the valence that any given individual would assign to each of the life events based on his or her personal experiences. In addition, the context in which the life events occurred is not factored into the HRSI. This situation clearly calls for an innovative approach to develop a new instrument for assessing the impact of stressful life events. The Perceived Stress Scale (PSS) represents just such an innovation with the introduction of a survey instrument to measure global levels of perceived stress (Cohen, Kamarck, & Mermelstein, 1983). The PSS was initially designed to be a 14-item instrument that measures the extent to which an individual perceives events in his or her life over the past month as stressful. The items were designed to uncover how much respondents find their lives to be unpredictable, out of their control, and overwhelming. By



Behavioral Measures of Stress 55

TABLE 3.2.  The 10 Most Frequently Checked Hassles and Uplifts from the Report by Kanner et al. (1981) Rating

Hassles

Uplifts

 1.

Concerns about weight (52.4)

Relating well with spouse/lover (76.3)

 2.

Health of a family member (48.1)

Relating well with friends (74.4)

 3.

Rising prices of common goods (43.7)

Completing a task (73.3)

 4.

Home maintenance (42.8)

Feeling healthy (72.7)

 5.

Too many things to do (38.6)

Getting enough sleep (69.7)

 6.

Misplacing or losing things (38.1)

Eating out (68.4)

 7.

Yard work or outside home maintenance (38.1)

Meeting your responsibilities (68.1)

 8.

Property, investment, or taxes (37.6)

Visiting, phoning, or writing someone (67.7)

 9.

Crime (37.1)

Spending time with family (66.7)

10.

Physical appearance (35.9)

Home (inside) pleasing to you (65.5)

Note. Figures in parentheses represent the percentage of participants who checked the item each month averaged over the nine monthly questionnaires. Used with permission of the publisher.

focusing on perceived stress levels, the developers of this instrument were reflecting the critical role of appraisal in shaping the interaction between an individual and a stressful life event (Lazarus & Folkman, 1984). In contrast to the HRSI, which simply notes the occurrence of a series of life stressors, the PSS taps into the levels of appraised stress in the lives of respondents. The PSS can be completed in several minutes, it is easy to score, and it only requires a junior high school level of education to complete. Newer versions of the PSS have included fewer items than the original version (e.g., PSS-10 and PSS-4). In addition, the PSS has been translated into many languages, making it broadly appealing internationally. One concern with the PSS is that some of its items overlap with symptoms of depression, but this matter can be controlled in the design of specific experiments (Table 3.3). The PSS scores (means ± SD) in the original report by Cohen et al. (1983) were 23.18 ± 7.31 and 23.67 ± 7.79 in two undergraduate student samples and 25.0 ± 8.00 in a community sample. Mean PSS scores for females were 23.57 ± 7.55 and 25.71 ± 6.20 in the student samples and 25.6 ± 8.24 in the community sample. Mean PSS scores for males were 22.38 ± 6.79 and 21.73 ± 8.42 in the student samples and 24.0 ± 7.80 in the community sample. Although the mean PSS scores for females were slightly higher than the mean PSS scores for males in all three samples, these differences did not approach statistical significance. As a measure of the impact of the PSS on research in this area, the original article by Cohen et al. (1983) has been cited more than 30,000 times according to Google Scholar. This clearly indicates that the PSS and its various translations into other languages have become the most frequently employed index of perceived psychological stress in countries around the world.

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TABLE 3.3.  Items and Instructions for the Perceived Stress Scale (Cohen et al., 1983) The questions in this scale ask you about your feelings and thoughts during the last month. In each case, you will be asked to indicate how often you felt or thought a certain way. Although some of the questions are similar, there are differences between them, and you should treat each one as a separate question. The best approach is to answer each question fairly quickly. That is, don’t try to count up the number of times you felt a particular way, but rather indicate the alternative that seems like a reasonable estimate. For each question, choose from the following alternatives:   0  Never   1  Almost never   2 Sometimes   3  Fairly often   4  Very often Items:   1.  In the last month, how often have you been upset because of something that happened unexpectedly?       2.  In the last month, how often have you felt that you were unable to control the important things in your life?       3.  In the last month, how often have you felt nervous and “stressed”?       4.  *In the last month, how often have you dealt successfully with irritating life hassles?       5.  *In the last month, how often have you felt that you were effectively coping with important changes that were occurring in your life?       6.  *In the last month, how often have you felt confident about your ability to handle your personal problems?       7.  *In the last month, how often have you felt that things were going your way?       8.  In the last month, how often have you found that you could not cope with all the things that you had to do?       9.  *In the last month, how often have you been able to control irritations in your life?     10.  *In the last month, how often have you felt that you were on top of things?     11.  In the last month, how often have you been angered because of things that happened that were outside of your control?     12.  In the last month, how often have you found yourself thinking about things you have to accomplish?     13.  *In the last month, how often have you been able to control the way you spend your time?     14.  In the last month, how often have you felt difficulties were piling up so high that you could not overcome them?     *Scored in reverse direction.

Note. Used with permission of the copyright holder, Professor Sheldon Cohen.

Higher PSS scores correlate significantly with biomarkers of aging, higher cortisol levels, suppressed immune function, greater susceptibility to infectious diseases, and slower wound healing. Individuals with high PSS scores also are less likely to maintain behaviors that promote wellness, such as eating a balanced diet, maintaining optimal sleep habits, and consuming alcohol in moderation. The PSS was also the primary measure of psychological stress employed in three national surveys of stress and health in 1983, 2006, and 2009 (Cohen & Janicki-­Deverts, 2012).



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Stress in Context Questionnaire Global stress measures, such as the PSS, can be used in any population and social context. However, this characteristic of the PSS presents a limitation for assessing how perceptions of psychological stress may be associated with detrimental environmental contexts that contribute to allostatic load. For example, individuals facing chronic social adversity like living in a low socioeconomic neighborhood rife with danger do not have PSS scores that are as high as one might predict. This finding suggests that habituation to one’s surroundings or social comparisons may lead to normalizing the negative environment, and thus lower PSS scores. This may obscure links between allostatic load and health outcomes in populations living in dire circumstances. The Stress in Context (SIC) questionnaire was developed recently to address this limitation of the PSS. The SIC assesses stress perceptions in specific contexts, such as at home, in the neighborhood, in social relationships, at work, and retrospectively during childhood. Weighting stress perceptions to each of these environmental contexts may prompt individuals regarding the many potential sources of perceived stress from their surroundings, and thus one obtains a more accurate global measure. The SIC may be more relevant for lower-­income populations or individuals exposed to chronic adversity. Thus far, it is equivalent to the PSS in self-­reported measures of psychological distress, well-being, and self-­reported health, but it shows a unique relationship to resting sympathetic tone. The SIC is a newer stress assessment tool, but it has great potential to illuminate the differential impact of stressors based on context of occurrence (Mayer, Epel, Slavich, & Mendes, 2017).

ELECTRONIC HEALTH RECORDS Many large medical centers and physician practice groups in the United States have embraced electronic health records (EHRs) as a means of improving workflow, facilitating billing for services, and enhancing the delivery of health care services. Many patients are now able to review their laboratory test results on mobile devices soon after they are posted and discuss concerns with their physicians through secure electronic channels that protect patient privacy. EHRs have also been used to investigate health issues at a population level. However, in spite of the wealth of information on social and behavioral determinants of health, most EHRs do not collect and store this type of information in a systematic fashion in patient EHRs. An Institute of Medicine (now called the National Academy of Medicine) committee was established in 2013 to investigate the inclusion of evidence-­based social and behavioral measures in EHRs and to develop a standard panel of such measures to facilitate improvements in patient care and population health, with two reports published the following year (Institute of Medicine, 2014a, 2014b). Some of the measures that were approved can be answered directly by the patient following clinic check-in, and other measures can be addressed by clinic staff once the patient is brought to the examining room. With proper management, these additional measures should not add dramatically to the workflow demands of clinical staff, and they have the potential to enhance the quality of care for each patient. On a broader level, these data provide a more complete picture of the patient in his or her social milieu.

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The Institute of Medicine committee recommended a panel of 12 psychosocial “vital signs” as summarized in Table 3.4. Each of these vital signs was carefully vetted for usefulness for clinical practice and population health management and readiness based on the availability of standard measures and the feasibility of use in a clinical setting (Adler & Stead, 2015; Matthews, Adler, Forrest, & Stead, 2016). Not surprisingly, measures that capture sources of stress and that contribute to levels of allostatic load are well represented. For example, there is an open-ended question about levels of stress being experienced as well as questions relating to levels of financial strain, depression, levels of social engagement or loneliness, and exposure to intimate partner violence. Each of these psychosocial vital signs has been shown to have a significant impact on health and wellbeing, and including this information in a patient’s EHR has the potential to enhance delivery of care. In addition, these data inform decisions regarding patient referrals for support from social service agencies and public health offices to improve quality of life. If EHR vendors and health care providers embrace these recommendations enthusiastically, there is a possibility of increasing the precision with which care plans are developed through an active partnership between patient and health care provider.

SOCIAL ISOLATION AND LONELINESS A strong social support system is an important predictor of favorable physical and mental health outcomes and reflects the essential nature of humans as highly social beings TABLE 3.4.  Social and Behavioral Measures Recommended for Inclusion in All EHRs by an Institute of Medicine Committee, as Reported by Adler and Stead (2015) and Matthews et al. (2016) Domain

Number of questions

Frequency of data collection

1 N/A 2 2 1

Verify at each clinic visit Update with address change Initial clinic visit Initial clinic visit Screen and follow up

Sociodemographic factors Residential address for geocoding Census tract median income Racial or ethnic group Education Financial resource strain Psychosocial factors Stress Depression Social connection/isolation Intimate partner violence

1 2 4 4

Screen and follow up Screen and follow up Screen and follow up Screen and follow up

2 2 2

Screen and follow up Screen and follow up Screen and follow up

Health behaviors Physical activity Tobacco use Alcohol use



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(Baumeister & Leary, 1995; Jeste, Lee, & Cacioppo, 2020; Quadt, Esposito, Critchley, & Garfinkel, 2020; Wilson, 1978). If a dependable social network is important for well-being, how might we quantify the characteristics of one’s social network? With the advent of social media platforms such as Twitter, Snapchat, Facebook, and Instagram, should we reconsider what constitutes the essential features (virtual vs. actual) of a social network? Does lack of a dependable and supportive social network constitute a significant life stressor? Several methods have been developed to assess loneliness and to quantify the nature and frequency of contacts with members of a social network. As we will see, measures of perceived loneliness typically focus on subjective impressions of participants, whereas measures of one’s social networks quantify how connected one is to others. These two measures would appear to be strongly correlated, but in fact, they tend to have independent effects on health-­relevant outcomes (Holt-­Lunstat et al., 2015).

Social Isolation The Social Network Index measures an individual’s participation in 12 categories of social relationships. These include relationships with a spouse, parents, parents-­in-law, children, other close family members, close neighbors, friends, workmates, schoolmates, fellow volunteers in a charity or a community organization, members of groups without religious affiliations (e.g., social, recreational, or professional groups), and members of religious groups. One point is assigned for each category of social relationship where a participant speaks to an individual in that category in person or on the telephone at least once every 2 weeks (maximum score = 12). A measure is also taken of the total number of people in each category that represents the size of the social network (Cohen, Doyle, Skoner, Rabin, & Gwaltney, 1997). The Social Network Index was developed before the widespread use of email, Skype, Zoom, texting, and social media platforms as a means of regular and frequent communication with family members, loved ones, friends, and colleagues. Future research will need to show whether virtual interactions between relative strangers have as much impact on health measures as real interactions between people who are familiar with one another (Zhang & Centola, 2019).

Loneliness The 20-item UCLA Loneliness Scale was originally developed in 1978 and has been utilized extensively to examine connections between the lack of social companions and health outcomes. A brief version of the scale with only 3 items has also been developed for epidemiological research. Over time several problems emerged with the UCLA Loneliness Scale in that the scale was originally validated using college student participants, and some of the items were confusing to college students and later to older adults. A revised version of the UCLA Loneliness Scale (Version 3) addressed these concerns and was administered to groups of college students, young and middle-­aged adults, and the elderly. These analyses supported the reliability and validity of Version 3 of the Loneliness Scale (Russell, 1996). The scale has been translated into several languages and has been utilized extensively with a variety of study populations.

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WORK‑RELATED STRESSORS Much of our adult lives is spent at places of employment or in dealing with intrusions from work while we are at home or enjoying time with family and friends. For many people, there are also concerns about job security that may add significantly to one’s overall levels of psychosocial stress. Work stress can be conceptualized in several ways. Using survey data from Sweden and the United States, Karasek (1979) identified two factors contributing to work-­related psychosocial stress: job demands interacting with job decision latitude. A position that includes low decision latitude combined with high job demands leads to high levels of stress and significant job dissatisfaction. The effort–­reward imbalance model advanced by Siegrist (1996) represents another prevailing approach to work-­related stress. This model identifies individuals who readily take on more than a normal workload or expend more effort than is typically required and often have high expectations for rewards (e.g., increased salary, special recognition, promotion, increased job security) that are seldom realized. High levels of effort–­reward imbalance result in increased psychosocial stress and poor health outcomes. Methods have been developed to assess job-­related stress based on the demand–­control model and the effort–­reward imbalance model. One example for an assessment of each model is presented in the following section.

The Demand–Control Model Karasek et al. (1998) developed the Job Content Questionnaire, which includes five scales composed of 49 questions relating to decision latitude, psychological demands, social support, physical demands, and level of job insecurity. It has been translated into multiple languages, and the validity and reliability of the instrument have been confirmed in various cross-­national studies.

Effort–Reward Imbalance Model The Effort–­Reward Imbalance Questionnaire captures self-­reported information about perceived levels of job-­related effort (5–6 items) and reward (11 items) and overcommitment (6 items). The reliability and validity of this instrument have been confirmed in research in five European countries, and individual workers who scored high on the three scales of the questionnaire had poorer health-­related metrics (Siegrist et al., 2004).

SOCIAL CAPITAL The concept of social capital dates back to the 18th and 19th centuries through the writings of Tocqueville, John Stuart Mill, Locke, Rousseau, and Simmel, who stressed the importance of human interactions in a civil society. Beginning in the 1980s, the noted French sociologist Pierre Bourdieu (1930–2002) and the American sociologist James S. Coleman (1926–1995) took somewhat different paths in stimulating a renewed interest in social capital. Bourdieu focused on connections at the individual level, while Coleman concentrated on the structure of small groups (including families) and the facilitation of interactions among individuals who make up those social groups. In the 1990s,



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Robert Putnam took a decidedly macro-level approach to social capital by examining membership in social clubs and organizations as a reflection of the social fabric of societies (Adam & Rončević, 2003). When I think of social capital, Putnam’s amazing book, Bowling Alone: The Collapse and Revival of American Community, immediately comes to mind (Putnam, 2000). Toward the end of the book, Putnam makes the following claim (with a bit of humor thrown in) that reflects a striking connection between social capital and health outcomes: As a rough rule of thumb, if you belong to no groups but decide to join one, you cut your risk of dying over the next year in half. If you smoke and belong to no groups, it’s a toss-up statistically whether you should stop smoking or start joining. These findings are in some ways heartening: it’s easier to join a group than to lose weight, exercise regularly, or quit smoking. (Putnam, 2000, p. 331)

Research on social capital is by its nature interdisciplinary, attracting intense interest from researchers in sociology, psychology, political science, economics, public health, and medicine. Of special interest to this chapter is the relationship between social capital and health, especially given the provocative quote included above from Putnam. At individual and group levels, social capital may exert its positive effects on health by serving as an effective buffer to mitigate against the negative effects of stressful stimuli (Ehsan, Klaas, Bastianen, & Spini, 2019; Rodgers, Valuev, Hswen, & Subramanian, 2019; Xue, Reed, & Menclova, 2020). These issues will be discussed in detail in disease-­specific chapters later in this book.

Neighborhoods and Health The Neighborhood Disorder Scale was developed and validated by Ross and Mirowsky (1999) to measure an individual’s perception of social and physical cues associated with levels of order and control within his or her neighborhood. Indications of order include a clean environment with buildings or houses in good repair, police coverage is sufficient to keep crime at low levels, and neighbors watch out for each other. In contrast, neighborhood disorder is reflected in excessive noise levels, drug and alcohol use and abuse, difficulties with neighbors, teens congregating, and houses or apartments that are boarded up and in a poor state of repair. The scale includes 15 items rated on a 4-point scale that are associated with physical order–­disorder and social order–­disorder. An abbreviated 10-item scale also has a high reliability. Their analyses pointed to two distinct but highly related factors, disorder and decay, associated with perceptions of neighborhoods. Robinette, Charles, Almeida, and Gruenewald (2016) explored living in disordered neighborhoods as a possible stressor that contributes to allostatic load by drawing on the Midlife in the United States (MIDUS) longitudinal study involving telephone surveys of a national probability sample of approximately 3,500 individuals. This study included multiple measures to characterize the status of participants’ neighborhoods, including neighborhood socioeconomic status, based on census tract information, a two-­question neighborhood safety questionnaire, and a two-­question neighborhood cohesion questionnaire.

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Using data from telephone interviews of more than 2,700 participants in the 2008 Montreal Neighborhood Networks and Healthy Aging Study (MoNNETs-­H A), Moore et al. (2011) employed multiple measures of social ties and neighborhood connections and examined their impact on self-­perceived health status. Participants were first asked for the names of three close confidants with whom they had discussed important matters over the past 6 months. Next, the participants were asked if their close confidants lived (1) in their household, (2) in their neighborhood, (3) in the Montreal metropolitan area, or (4) outside of the Montreal metropolitan area. No specific definition of neighborhood was provided to participants, thereby allowing them to conceptualize their own neighborhood boundaries.

EARLY LIFE STRESSORS There is overwhelming evidence that adverse experiences during infancy and childhood exert deleterious effects on biological measures of stress and on measures of physical and mental health. Many of the studies in this area have concentrated on extreme examples of physical and sexual abuse and neglect of basic needs. However, an increased risk of adverse health outcomes has also been associated with less extreme stressful circumstances such as growing up in poverty, experiencing a chaotic home life, or living under the threat of neighborhood violence. Many measures of early life stressors depend on retrospective reporting by study participants when interviewed in late adolescence or adulthood. Serious reservations have often been expressed regarding the accuracy of retrospective accounts of early life stressors, and in some instances these concerns have been confirmed. In particular, the Dunedin birth cohort study compared adverse childhood experiences recorded by staff members during biennial data collections with those recalled by study participants at 38 years of age. There was significant though modest agreement between objectively recorded and retrospectively recalled adverse childhood events, suggesting that caution should be exercised in interpreting such self-­reported data and their impact on health outcomes (Reuben et al., 2016). There is no all-­encompassing gold standard for measuring adverse childhood experiences. In fact, a combination of questionnaires is often used to identify severe childhood stressors (e.g., sexual or physical abuse, extreme poverty) versus those that are less severe (day-to-day chaotic lifestyle, intrafamily conflicts, lack of consistent housing and caregiving). I will provide examples of each type of instrument below.

Childhood Trauma Questionnaire The Childhood Trauma Questionnaire (CTQ) was developed by Bernstein et al. (1994) based on testing of and interviews with patients being treated for drug and alcohol abuse. It consists of a 70-item self-­report battery that retrospectively seeks information on the occurrence of abuse and neglect in childhood as well as on child rearing. Each item is rated on a 5-point Likert Scale as to frequency of occurrence (the range of responses was “never true” to “very often true”). The questionnaire requires 15–20 minutes to complete and was designed for adolescents and adults in an inpatient setting. Detailed analyses of the data yielded four orthogonal factors that displayed high



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internal consistency: physical and emotional abuse, emotional neglect, sexual abuse, and physical neglect. The test–­retest reliability of the findings was highly consistent over a 2- to 6-month period, and the data from the CTQ were in agreement with the results of structured interviews with some of the patients. The original 70-item CTQ was later reduced to 28 items (CTQ-SF) that can be completed in 5 minutes to serve as a screening tool for inpatient and community settings. The CTQ-SF was validated in four separate and diverse groups, including a normative community sample. The CTQ-SF shared the same factor structure as the original CTQ and provides a rapid assessment of individuals who may be in need of referral for trauma-­related clinical services (Bernstein et al., 2003).

Adverse Childhood Experiences Scale The Adverse Childhood Experiences Scale was developed by Felitti et al. (1998) for more than 13,000 members of a health maintenance organization and included items dealing with family dynamics that were excerpted from related surveys. The scale included three categories of abuse (psychological, physical, and sexual) and four categories of household dysfunction (living with someone who was a substance abuser, living with someone with a mental disorder, mother was threatened or abused physically, and a household member was sentenced to prison). There were one to four questions (yes-orno responses) within each of the seven categories, for a total of 17 questions, and 1 point was assigned if a respondent answered yes to one or more of the questions within each of the seven categories. The measure of childhood exposure was the sum of the categories with at least one affirmative response (range of scores = 0–7).

Risky Families Questionnaire The Risky Families Questionnaire was adapted from a questionnaire originally reported by Felitti et al. (1998) that dealt with several forms of psychological, physical, and sexual abuse and family dysfunction. Participants answered seven questions about their family environment up to age 18 using a 4-point scale (1 = rarely to 4 = most or all of the time). The questions probed whether the participant felt loved and cared for, received physical signs of affection, was verbally abused, was physically abused, lived with someone who abused drugs, lived in a well-­functioning home, and had family members who kept close track of him or her. Ratings were converted into z scores and the cumulative z score was taken as the measure of exposure to a risky family environment. Other questions provided information on each participant’s childhood socioeconomic status (Lehman, Taylor, Kiefe, & Seeman, 2005).

THE STRESS OF MAJOR LIFE EVENTS The HRSI was one of the first instruments to associate the stress of major life events to health outcomes. As I summarized in Chapter 1, the HRSI has been criticized by a number of leading stress researcher and this has led to further development of questionnaires and structured interviews to achieve more reliable and accurate measures of the stress levels associated with major life events. In their thoughtful review, Turner and

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Wheaton (1995) recommended the exclusion of clearly positive events and a focus on negative events, the inclusion of 30–50 items in a life events inventory, use of at least a one-year time frame for specific events, and no published list was endorsed over any other as each has its strengths and limitation. In the next section, I will include features of two life events scales to provide some indication of the variety of approaches taken.

Life Events List The Life Events List (LEL) was crafted by Cohen, Tyrrell, and Smith (1991) from a longer list of life events described by Henderson, Bryne, and Duncan-­Jones (1981) for use in experiments on susceptibility to viruses that cause the common cold. Participants were asked if a series of 23 items occurred to them, and in some cases to their spouses or significant others, over the past 12 months. Some of the items included follow-­up questions to gauge the intensity of the reaction to the event. Examples include: (1) Have you moved during the last 12 months? (2) Did someone you were close to die during the last 12 months? (3) Have you, a close friend, or close family member had an accident that required emergency medical treatment during the last 12 months? and (4) During the last 12 months, have you or your spouse/partner suffered a significant business or investment loss, or has a business you owned failed? A 24th item asked for up to three additional events that occurred to the participant or to a close friend or close family member that were unusual compared to a typical year. A total of all stressful life events that occurred to the participant as well as a spouse or close family member was reported as the LEL score.

UCLA Life Stress Interview Hammen, Ellicott, Gitlin, and Jamison (1989) developed the Life Stress Interview to use in their studies on the effects of stressful life events on the development of unipolar and bipolar depression. The Life Stress Interview was designed to document the timing and stressful qualities of events that had occurred over a preceding 3-month period. Most of these interviews were conducted by telephone, and participants were provided with a list of possible stressful events and asked if and when each event had occurred and other details, including how well the participant coped with the event. Following each interview, a written report was prepared for each stressful event that included contextual details but left out how the participant felt or reacted. Each event report was then reviewed by an independent rating team that assigned two ratings: an objective threat score and an independence score (i.e., the event had nothing to do with the participant vs. the event occurred because of the participant). From this brief description, it is obvious that the Life Stress Interview places significant demands on laboratory personnel and was designed within the context of a major investigation of stressful life events and depression.

SMARTPHONE APPLICATIONS A host of smartphone applications have been developed to support stress reduction goals and to bring calm to our lives. Here I highlight two innovative smartphone-­related approaches to measuring stress-­related behaviors. Bear in mind that this is a dynamic



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area of research that is evolving rapidly and may hold promise in the near term for targeted interventions of stress-­susceptible individuals to prevent the development of physical diseases and mental disorders (DaSilva et al., 2021; Egger et al., 2020; Strain et al., 2020).

Assessing Stress Levels by Voice Analysis The capability to measure stress-­induced alterations in speech patterns noninvasively, accurately, reliably, and relatively inexpensively was not possible until the development of smartphones. A voice recording from a smartphone or a smart speaker can be analyzed for various speech parameters, including pitch, jitter (changes in pitch over brief periods of time), energy in different frequency bands, rate of speech, and length and number of pauses. One approach that has been taken to relate patterns of speech to stress levels involved an analysis of ongoing speech patterns in an indoor laboratory room and in an outdoor urban environment with levels of ambient noise (Lu et al., 2012). Data on the speech patterns of 14 university student participants (10 females and 4 males) were collected under three distinct conditions: (1) baseline condition that consisted of reading prepared materials indoors and out-of-doors with no performance expectations and no time pressures, (2) a structured job interview consisting of eight questions for a marketing position that was conducted in a quiet laboratory room, and (3) a 4-hour paid marketing position conducted on a university campus and in a city center that involved approaching strangers and recruiting them to participate in university-­based experiments. Performance-­based incentives were in place to further engage the 14 participants. To compare the data on speech patterns with an objective measure of stress, each participant wore a wrist band to collect data on galvanic skin response (GSR) during each of the three test conditions. Baseline GSRs were determined for each participant while resting and undisturbed in the laboratory. Using a one-size-fits-all algorithm to analyze speech data (StressSense), these investigators were successful in accurately detecting stressful situations in 81 and 76% of cases, respectively, for indoor and outdoor testing scenarios when compared to objectively measured GSR changes from baseline levels for each participant. The developers of StressSense and similar algorithms envision a mobile phone-based application that can monitor an individual’s stress in real time (Lu et al., 2012). However, Slavich, Taylor, and Picard (2019) have raised concerns about privacy and data security with these and other speech detection algorithms. In addition, they have recommended additional efforts to validate StressSense and other speech detection algorithms against other well-­studied stress biomarkers, such as blood and salivary levels of cortisol and alpha-­amylase, ILs, and heart rate measures. In the end, this technological approach to provide an ongoing readout of stress could provide valuable health- and wellness-­ related information for the benefit of individuals and their medical providers. A related approach that has been reported is the analysis of affective text language employed by smartphone users (Byrne et al., 2021).

Electronic Diaries Electronic diaries (eDiaries) have been used to monitor stress episodes and their timing in individuals as they go about their daily routines. Participants in these studies receive

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an audio prompt from an eDiary and then select from a menu to rate their moods, emotions, or actions for the previous interval of time (e.g., 15- to 30-minute blocks). This approach to data collection has worked especially well in studies of behavioral correlates of abnormal cardiac events revealed through continuously recorded electrocardiograms (Kivimäki & Steptoe, 2018; Lampert, 2015; Lampert et al., 2019).

CONCLUSIONS Much of what we know today about the influence of stressful life events on health, disease, and death has been gleaned from studies that utilized questionnaires to assess levels of stressful life events that were experienced at a particular point in time. Some of the questionnaires have asked for stressful experiences during the previous month to one year, while others have asked for a response based on how the individual was feeling that day. One of the earliest examples of a stressful life events questionnaire was the one developed by Holmes and Rahe (1967), which has been employed in many studies over the years. To address some of the criticisms of the Holmes and Rahe approach, Cohen et al. (1983) focused on assessing perceived levels of stress, which opened up the possibility of tapping into subjective reactions to stressors as opposed to merely counting adverse events. Thus, in spite of their limitations, questionnaires related to experiences of stress have formed the backbone of population-­based studies of stress and health outcomes. Laboratory experiments have also contributed in important ways to understanding physiological and behavioral responses to acute stressors in participants with known health risks or those who already have disease diagnosed. The TSST has been utilized extensively across laboratories to provide a consistent paradigm for inducing stress and has encouraged other innovations, including the use of virtual environments. With the widespread adoption of EHRs by academic medical centers and hospital networks, researchers are now poised to interrogate de-­identified patient records for additional insights into relationships between stress and health risks. As EHRs are populated with DNA sequences or information on risk variants, a new era in medical genomics will commence. As is always the case, however, the genomics data can only be understood with parallel information of environmental contexts, including levels of stress. In this regard, information on characteristics of neighborhoods can be included in EHRs with geocoding and provide valuable information on health risks and outcomes. Finally, smartphones, sensors, and wearable devices are ushering in a new era in collecting health-­related data in real time as individuals are exposed to daily stressors, including race-based stressors. These resulting large-scale datasets will be invaluable to behaviorally oriented stress researchers as they develop personalized intervention strategies to protect the physical and mental health of individuals who are at risk of developing stress-­related diseases. We will see many examples of these innovative approaches in the chapters that follow.



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APPENDIX 3.1.  Quantitative Analyses of Health Risks

from Stressors

In many large-scale clinical or epidemiological studies, the experimental design may reflect an interest in determining the effects of an exposure on an outcome. The statistical technique that is appropriate for such studies involves the calculation of an odds ratio (OR) to ascertain if the exposure affects the outcome of interest compared to the odds of the outcome occurring in the absence of the exposure. The OR may also indicate whether a given exposure is a risk factor for a specific outcome, and one may also compare the magnitude of various risk factors on that outcome. A hazard ratio (HR) is reported for experiments that involve time-to-event analysis or survival analysis. The HR is in fact a ratio—­chance of an event occurring in the experimental group ÷ chance of an event occurring in the control group. Thus, it follows that:

• HR = 0.5 indicates that at any given time half as many individuals in the high-­stress group will experience a heart attack compared to the low-­stress group.

• HR = 1.0 indicates that heart attack rates are the same in individuals from the high- and low-­stress groups.

• HR = 2.0 indicates that twice as many individuals in the high-­stress group will experience heart attacks compared to the low-­stress group.

To provide information on the variability of the data, the OR and the HR are accompanied by a 95% confidence interval (CI). This measure provides the range of values that will include the true value for the sample in question 95% of the time. The precision of the dataset, which is often influenced by the sample size, yields a compressed CI. In contrast, a wide-­ranging CI reflects less precision in the estimate and typically a smaller sample size. If the CI overlaps with 1.0, then the HR is not statistically significant and could have occurred by chance alone. In this book, I will report these figures in the following way:

• HR = 3.62, 95% CI = 1.59–4.23 (a highly significant adverse effect of a stressor) • HR = 1.09, 95% CI = 0.87–1.21 (no effect of a stressor; value overlaps with 1.0) • HR = 0.46, 95% CI = 0.39–0.60 (an intervention to reduce stress provides a beneficial effect)

Another ratio that will be presented is the risk ratio (RR). RR differs from HR in that a risk ratio does not concern itself with the timing of an event. Rather, RR is concerned with whether an event occurs by the end of the study period. For both HRs and RRs, values can be adjusted for other measures of risk that may not be equal between groups. Some of these variables that will be encountered in later chapters include smoking, frequency of exercise, body mass index, race, and other disease comorbidities. In some cases, adjusted values for HR or RR may change from unadjusted values. Keep an eye out for this. If you are interested in gaining more detailed information on HRs and RRs, you may wish to consult Barraclough, Simms, and Govindan (2011), Hernán (2010), and Szumilas (2010).

CHAPTER 4

Stress and Alcohol Use

H

umans have been producing and consuming fermented beverages for at least 13,000 years. The earliest archeological evidence for cereal-based beer brewing was reported by Liu et al. (2018) for samples collected in Raqefet Cave near Mount Carmel, Israel, and this activity predates domestication of cereal grains by several thousand years. It appears likely that beer brewing in Raqefet Cave was associated with ritual feasts. Additional archeological evidence for production of a fermented beverage made from a combination of rice, honey, and fruit has been obtained from a site in Henan province in China dating back approximately 9,000 years. More recent samples of fermented liquid from sealed bronze ceremonial vessels from the Shang and Western Zhou dynasties have been recovered and analyzed from sites along the Yellow River and its tributaries. These liquids appear to be derived from fermentation of cereals such as rice and millet for use by elites and date from at least 4,000 years ago (McGovern et al., 2004). The development of techniques to produce fermented beverages from carbohydratecontaining plants has occurred in most parts of the world. The ethanol produced from the fermentation process was useful as an analgesic, a disinfectant, and a mind-altering substance. Over time, fermented beverages have played a key role in the development of human cultural practices at all levels of society, including large-scale secular and religious celebrations (McGovern et al., 2004).

GLOBAL ASPECTS OF ALCOHOL USE At the present time, alcohol is the most commonly available and frequently used drug globally. The alcoholic beverage industry generated more than $1 trillion in worldwide sales based on data from 2018. Frequent and excessive intake of alcohol can result in increased risk of sexually transmitted infections and tuberculosis; adverse effects on 68



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chronic diseases, including cardiovascular diseases, cancer, and alcoholic liver diseases; adverse effects on the developing fetus if alcohol intake persists during pregnancy; alcoholic intoxication, which increases the occurrence of injuries and death; and elevated risk of suicide (World Health Organization, 2018). Alcohol use disorder (AUD) represents one of the most prevalent mental disorders worldwide, affecting 8.6% of males and 1.7% of females as revealed in data from 2016. Based on recent trends in AUD, this gender gap appears to be narrowing. Population surveys indicate that the prevalence of AUD is higher in high-­income and upper-­middle-­ income countries, including the United States, Germany, France, and Belgium, and lower in low-­income and lower-­middle-­income countries such as the Philippines, India, and Kenya. Per capita consumption of alcohol tends to be highest in high-­income and upper-­ middle-­income countries, especially countries in Europe. An exception to this pattern is the high levels of alcohol consumption in Nigeria and some other poorer countries of Africa and South America. Alcohol consumption is close to zero in countries with high percentages of Muslims, such as Bangladesh, Saudi Arabia, and Pakistan (Table 4.1). The World Health Organization has compiled information based on 2016 data on the contributions of excessive alcohol intake to deaths and the global burden of disease. Alcohol abuse resulted in 3 million deaths in 2016, representing 5.3% of all deaths globally. In addition, alcohol abuse led to 133 million disability-­adjusted lifeyears (DALYs), which was 5.1% of the global total for that same year. Strikingly, alcohol use was responsible for 7.2% of all instances of premature mortality of individuals 69 years of age or younger, with individuals 20–44 years of age especially hard hit. A diagnosis of AUD occurred in 237 million adult males (8.6% of all males) and 46 million adult females (1.7% of all females). For both males and females, the highest prevalence of AUDs was in Europe and the Americas. However, a significant economic gradient also contributed to alcohol-­related deaths and alcohol-­related disability, with higher rates in poorer countries than in wealthier countries. A similar pattern is also seen within countries, where the adverse health effects of excessive alcohol use fall disproportionately on the poor. The reasons for this greater burden on the poor are not surprising; they include lack of access to quality health care; higher rates of smoking, obesity, and lack of regular exercise; and a poor diet (Degenhardt et al., 2018). Probst, Kilian, Sanchez, Lange, and Rehm (2020) examined the relationship between patterns of alcohol use and socioeconomic inequalities in mortality through a systematic review of 10 studies published between January 1, 2013, and June 30, 2019. These studies included more than 400,000 adults, more than 30,000 deaths from all cases, and more than 3,000 events that were completely tied to alcohol as a cause of death or hospitalization. All 10 of the studies were from high-­income countries, a fact that limits the generalizability of the findings. Alcohol use was associated with as much as 27% of the socioeconomic inequalities in mortality, and this was especially true for bouts of heavy episodic drinking.

THE IMPACT OF ALCOHOL CONSUMPTION IN THE UNITED STATES Research on trends in alcohol consumption in the United States paints a bleak picture. Drawing on data from two national surveys of 12-month prevalence of alcohol use,

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high-risk drinking, and AUD, Grant et al. (2017) examined trends in these behaviors from 2001–2002 to 2012–2013. Data were obtained from face-to-face interviews that were part of two nationally representative surveys of adults in the United States: the National Epidemiologic Survey on Alcohol and Related Conditions (April 2001–June 2002, N = 43,093) and the National Epidemiologic Survey on Alcohol and Related Conditions III (April 2012–June 2013, N = 36,309). High-risk drinking was defined as five drinks per occasion for men and four drinks per occasion for women. AUD diagnoses were based on DSM-IV criteria.

TABLE 4.1.  Total Alcohol per Capita Consumption in Liters of Pure Alcohol for Individuals ≥ 15 Years of Age in 25 Selected Countries across Regions of the World and Percentage of Individuals ≥ 15 Years of Age Defined as Heavy Episodic Drinkers Liters of pure alcohol Country/income level a Nigeria (lower-middle income) Germany (high income) Ireland (high income) France (high income) Belgium (high income) Russian Federation (upper-middle income) United Kingdom (high income) New Zealand (high income) Australia (high income) South Africa (upper-middle income) Argentina (upper-middle income) United States (high income) Canada (high income) Japan (high income) Brazil (upper-middle income) Italy (high income) China (upper-middle income) Philippines (lower-middle income) Mexico (upper-middle income) India (lower-middle income) Kenya (lower-middle income) Indonesia (lower-middle income) Pakistan (lower-middle income) Saudi Arabia (high income) Bangladesh (lower-middle income)

Male consumption

Female consumption

Combined consumption

% heavy episodic drinkersb

21.9 21.3 20.3 20.3 19.4 18.7 18.4 17.2 16.7 16.2 16.1 15.8 14.6 13.5 13.4 12.5 11.7 11.3 11.1 9.4 5.8 1.4 0.5 0.3 0

4.6 5.9 5.8 5.4 5.2 5.8 4.8 4.6 4.7 2.7 4 4.1 3.4 2.9 2.4 2.8 2.5 1.9 2.1 1.7 0.9 0.2 0.1 0.1 0

13.4 13.4 13 12.6 12.1 11.7 11.4 10.7 10.6 9.3 9.8 9.8 8.9 8 7.8 7.5 7.2 6.6 6.5 5.7 10.7 0.8 0.3 0.2 0

27.3 39.7 40.5 36 36.6 38.8 33.7 35.2 39.2 17.7 23 29 24.2 28.7 19.7 25 23.6 12.1 18 17 10.3 6.4 0.1 0.2 0.8

Note. Data are from the World Health Organization (2018). a Income levels of countries are based on World Bank definitions. bThese individuals consume 60 or more grams of pure alcohol on at least one single occasion at least once per month.



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Between 2001–2002 and 2012–2013, there were significant increases in 12-month alcohol use (11.2%), high-risk drinking (29.9%), and diagnoses of AUD (49.4%). In addition, increases in these three parameters of alcohol use and abuse were fairly consistent across sociodemographic subgroups. Particularly troubling were the dramatic increases in these behaviors in women, adults 65 years of age and older, racial and ethnic minorities, and individuals with lower educational attainment and reduced income levels. The authors argued forcefully that this significant uptick in alcohol use over an 11-year period constitutes a public health crisis that will only increase with time. High rates of binge drinking among individuals 18–22 years of age too often lead to tragic outcomes. Another area of concern is the low treatment rates for individuals diagnosed with AUD (< 10%) and the negative effects these high rates of drinking have on individuals, families, and communities (Grant et al., 2017). Alcohol use and abuse may have increased during the COVID-19 quarantine, so this alcohol-­fueled crisis may have worsened over the past 10 years. The cost of excessive alcohol use in the United States in 2010 was reported to be $250 billion, a figure that is probably a significant underestimate (Sacks, Gonzales, Bouchery, Tomedi, & Brewer, 2015). Binge drinking was responsible for $191 billion of the total costs (77%), underage drinking was responsible for $24 billion (10%), and drinking while pregnant was responsible for $5.5 billion (2%). The negative impact of excessive alcohol use was accounted for in lost productivity (72%), health care costs (11%), and other costs such as crime-­related costs and property damage (17%). Given the dramatic increases in alcohol use noted above based on data available through 2012–2013 (Grant et al., 2017), it is reasonable to expect that these costs have increased substantially since 2010 and will continue to do so for the coming years. What these estimates do not reflect are the pain and suffering experienced by parents who receive a call that their son has died in a fraternity hazing incident involving alcohol or the woman who learns that her husband has been killed by a drunk driver while returning home from work. Unfortunately, these tragedies play out daily in all corners of our society. Stahre, Roeber, Kanny, Brewer, and Zhang (2014) utilized data from the Centers for Disease Control and Prevention for 2006–2010 to estimate yearly numbers of alcohol-­attributable deaths and years of potential life lost to alcohol among working-­age adults (20–64 years of age). They report a yearly average of 87,798 alcohol-­attributable deaths and 2.5 million years of potential life lost to alcohol. Fully 10% of all deaths among working-­age adults in the United States each year are tied to alcohol. These frightening statistics have not yet been sufficient to mobilize our society to institute policies that will curb excessive drinking and severely punish drunk drivers.

DIAGNOSIS OF AUD Individuals diagnosed with AUD exhibit loss of control over their ability to regulate alcohol intake, they engage in chronic alcohol use, and they display negative emotions when they refrain from drinking. This pattern of drinking followed by abstinence followed by more drinking recurs, and the disease is chronic and unremitting. Two primary approaches are available to guide the diagnosis of AUD: the Diagnostic and Statistical Manual of Mental Disorders (DSM-5-TR; American Psychiatric Association, 2022) and the International Classification of Diseases (ICD-11; World Health

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Organization, 2022). In both approaches, AUDs reflect continued alcohol intake despite a host of negative psychological, biological, behavioral, and social outcomes, of which a minimum number must occur over a 12-month period. Using DSM-5-TR, if more than one criterion is satisfied, then a diagnosis of AUD results and the severity is determined by the number of criteria that are met (Table 4.2). With a requirement for 2 out of 11 symptoms to occur, a total of 2,048 potential symptom combinations would satisfy the diagnosis of AUD. This underscores the heterogeneity of AUD and the need to develop personalized approaches for treatment of individual patients with AUD. Using ICD-11, AUDs are characterized as alcohol dependence or a harmful pattern of alcohol use, where the latter is considered more severe. As Carvalho, Heilig, Perez, Probst, and Rehm (2019) have noted, the divergent approaches to diagnosing AUD adopted by

TABLE 4.2.  Diagnosis of AUD A. A problematic pattern of alcohol use leading to clinically significant impairment or distress, as manifested by at least two of the following, occurring within a 12-month period:  1. Alcohol often taken in larger amounts or over a longer period than was intended.  2. A persistent desire or unsuccessful efforts to cut down or control alcohol use.  3. A great deal of time spent in activities necessary to obtain alcohol, use alcohol, or recover from its effects.  4. Craving, or a strong desire or urge to use alcohol.  5. Recurrent alcohol use resulting in a failure to fulfill major role obligations at work, school, or home.  6. Continued alcohol use despite having persistent or recurrent social or interpersonal problems caused or exacerbated by the effects of alcohol.  7. Important social, occupational, or recreational activities given up or reduced because of alcohol use.  8. Recurrent alcohol use in situations in which it is physically hazardous.  9. Continued alcohol use despite knowledge of having a persistent or recurrent physical or psychological problem that is likely to have been caused or exacerbated by alcohol. 10. Tolerance, as defined by either of the following: a. A need for markedly increased amounts of alcohol to achieve intoxication or desired effect. b. A markedly diminished effect with continued use of the same amount of alcohol. 11. Withdrawal, as manifested by either of the following: a. The characteristic withdrawal syndrome for alcohol (refer to Criteria A and B of the criteria set for alcohol withdrawal). b. Alcohol (or a closely related substance, such as a benzodiazepine) taken to relieve or avoid withdrawal symptoms. Specify if: • In early remission: After full criteria for alcohol use disorder were previously met, none of the criteria for alcohol use disorder have been met for at least 3 months but for less than 12 months (with the exception that Criterion A4, “Craving, or a strong desire or urge to use alcohol,” may be met). • In sustained remission: After full criteria for alcohol use disorder were previously met, none of the criteria for alcohol use disorder have been met at any time during a period of 12 months or longer (with the exception that Criterion A4, “Craving, or a strong desire or urge to use alcohol,” may be met).

Note. Reprinted with permission from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision. Copyright © 2022 American Psychiatric Association. All Rights Reserved.



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DSM-5-TR and ICD-11 present difficulties for health care providers and insurers alike. In addition, some have criticized the DSM-5-TR criteria as being so broad as to encompass many people who enjoy alcoholic beverages regularly with meals but are in no way dependent on alcohol each day.

GENETICS OF AUD Twin Studies Quantitative genetics studies have revealed a significant heritability of AUD of approximately 0.49 (95% CI = 0.47–0.54), and the proportion of shared environmental variance was 0.10 (95% CI = 0.03–0.16) based on a meta-­analysis of 13 twin and 5 adoption studies. There was no evidence for differential risk factors for AUD in males versus females. In spite of large sex differences in prevalence of AUD, genetic influences on AUD appear to be similar in males and females. AUD status was assessed in these studies by securing health registry information or by conducting personal interviews of participants. The results indicated that the method of assessment did not influence estimates of the genetic or common environmental variance components. Finally, the results of this study indicated that heritability estimates were slightly lower for adoption studies compared to twin studies, but the two estimates did not differ statistically. In aggregate, these findings indicate that AUD is approximately 50% heritable and that modest shared environmental effects contribute to the aggregation of this disorder within families (Verhulst, Neale, & Kendler, 2015).

Genome‑Wide Association Studies Several large-scale genome-­wide association studies (GWAS) have reported findings relating to the search for risk genes for alcohol consumption and for AUD. Thus far, these findings have pointed to a complex genetic architecture for AUD, in which hundreds of genetic variants, each contributing a small effect, contribute to the genetic etiology of that trait. A significant challenge for GWAS is to generate a sample size that is sufficient for achieving genome-­wide levels of significance (p = 5.0 x 10 -8) that reflect multiple genetic comparisons across the genome. Many early reports of GWAS for AUD lacked adequate statistical power to detect these relatively small effects (Deak, Miller, & Gizer, 2019). Kranzler et al. (2019) conducted a GWAS of two alcohol-­related traits, alcohol consumption levels and AUD, using a sample from the Million Veteran Program (N = 274,424) of the U.S. Veterans Administration (VA). Alcohol consumption was based on Alcohol Use Disorder Identification Test—­Consumption (AUDIT-C) scores, and AUD diagnoses were obtained from the electronic health records (EHRs) of the VA. The AUDIT-C is part of a required annual assessment of all veterans seen in primary care clinics, and it consists of 3 items: (1) typical quantity of alcohol consumed, (2) typical frequency of drinking alcohol, and (3) frequency of heavy or binge drinking. AUD was defined as alcohol abuse or alcohol dependence from EHR entries. Using a sample of 1,851 participants from the Veterans Aging Cohort, these investigators found a highly significant correlation between AUDIT-C scores and plasma levels of phosphatidylethanol, a biomarker that reflects amount of alcohol consumed. All AUDIT-C scores were

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age-­adjusted, with age 50 years as the reference age; scores of individuals younger than 50 years were downweighted and scores of those older than 50 years were upweighted. These investigators identified 18 genome-­wide significant genetic loci, with 5 associated with AUDIT-C scores and AUD diagnosis, 8 associated with AUDIT-C scores only, and 5 associated with AUD diagnosis only. Further analyses revealed significant genetic overlap between the two alcohol-­related traits, but there were also noticeable points of divergence between the two. Thus, although heavy drinking is a significant risk factor for AUD, it alone does not cause AUD. These findings have important implications for the development of new treatments for AUD, with some treatments targeting excessive alcohol intake and the resultant negative effects, while others could target core features of AUD (Kranzler et al., 2019). Sanchez-­Roige et al. (2019) also employed GWAS to identify genetic variants related to alcohol consumption and alcohol misuse by drawing on participants in the UK Biobank (N = 121,604, 56% female, mean age = 56 years) combined with customers of 23andMe (N = 20,328). Quantitative measures were drawn from AUDIT scores, with items 1–3 reflecting alcohol consumption (AUDIT-C) and items 4–10 reflecting problematic drinking behaviors (AUDIT-P). The results of this large-scale GWAS replicated previously identified genetic variants and discovered several new variants that were significantly associated with AUDIT scores. Consistent with the results reported by Kranzler et al. (2019), this study revealed AUDIT-C and AUDIT-P scores correlated with 14 loci relating to alcohol use and alcohol dependence, respectively. It is becoming clear that excessive intake of alcohol is a prerequisite for the later development of AUD. However, having an elevated AUDIT-C score is not a guarantee for a later diagnosis of AUD. These two phenotypes appear to have distinct risk gene variants associated with them, and understanding how these relationships unfold has become a focus of ongoing studies (Sanchez-­Roige et al., 2019).

Identifying Risk of Developing AUD It is one thing to identify risk gene variants associated with diagnosed cases of AUD. It is quite another thing to identify individuals at risk of developing AUD prior to displaying any symptoms associated with alcohol consumption. Kinreich et al. (2021) analyzed data from six sites that participated in the Collaborative Study of the Genetics of Alcoholism. They limited their study to participants who were unaffected on their first assessment visit and were later followed up and assessed for AUD. The participants sorted into two groups: (1) a diagnosis of AUD based on DSM-5 criteria (N = 328, mean age = 18 years, 58% male) with a mean follow-­up period of 7.36 years or (2) a control group matched as closely as possible to the AUD group (N = 328, mean age = 18 years, 58% male) that was free of symptoms of AUD on the first assessment and during a follow-­up assessment that occurred an average of 6.64 years later. The goal of the analyses was to determine which variables assessed prior to the development of AUD predicted those participants who would go on to receive an AUD diagnosis. Machine learning analysis was performed for 220 baseline electroencephalographic (EEG) measures, 149 alcohol-­related single-­nucleotide polymorphisms (SNPs) from a recent GWAS of alcohol use/misuse, and parental history of AUD. The results were more accurate for the African American than European American participants and for females compared to males. A diagnosis of AUD for the mother increased the



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model’s accuracy for African American and European American participants. Adding EEG and SNP data to the analysis was superior to models based on only EEG features or only SNP features. The results highlighted the significance of sampling uniformity followed by stratified (e.g., ancestry, gender, developmental period) analyses and wider selection of features, generating better prediction scores and allowing a more accurate estimation of AUD development. The results of this machine learning study hold great promise for predicting vulnerability to later development of AUD and informing prevention strategies. Another facet of this study included the possibility of identifying resilience factors that protect against development of AUD. Developing a model that incorporated features from different realms, including electrophysiology, genetics, and family history, was far superior to models based on features from a single realm (Kinreich et al., 2021).

A CONCEPTUAL FRAMEWORK FOR STRESS AND ALCOHOL ABUSE Dependence on alcohol is a chronic condition that often includes periods of abstinence alternating with periods of relapse. An individual diagnosed with AUD has a compulsion to seek and consume alcohol, and if access to alcohol is blocked, he or she will develop a negative emotional state involving dysphoria, anxiety, and irritability (Koob & LeMoul, 2008). Building on this view of AUD, Kwako and Koob (2017) suggested that alcohol dependence involves three interconnected stages: 1. Binge drinking and intoxication 2. Withdrawal and negative affect 3. Preoccupation with and anticipation of the next drink of alcohol This cycle of addiction to alcohol worsens progressively over time and presents a source of allostatic load to the individual. This allostatic load in turn leads to changes in brain circuits involved in reward and regulation of stress responses. Koob and Schulkin (2019) have proposed a conceptual framework for understanding the interconnections between stress-­responsive brain circuits, peripheral stress effector systems, and the onset and maintenance of drug addiction in animal models (Figure 4.1). This conceptual framework is also helpful in understanding the pathophysiology of AUD in humans, and I will adapt it for that purpose. A critical aspect of the framework proposed by Koob and Schulkin (2019) is that chronic exposure to stressors results in changes in brain corticotropin-­releasing factor (CRF) neurons that have a facilitatory impact on the development of addiction to alcohol. AUD may be thought of as a disease that results in a chronic dysregulation of allostatic mechanisms in that it worsens over time, is affected by environmental stressors, and leaves a residual neurobiological trace that may lead to a sudden relapse months or years after completing a treatment program and being abstinent from alcohol. Life stressors represent a critical driving force behind the allostatic alterations involved in AUD and act upon brain circuits involved in regulation of emotion and reward processes as well as the HPA axis. Continuing efforts to seek out and consume alcohol lead to exaggerated responses to stressors and increased activity within brain reward circuits. These repeating cycles of stress reactions and alcohol seeking/intake

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FIGURE 4.1.  Progression from casual consumption of alcoholic beverages to later stages of alcohol dependence. Periods of abstinence are interposed between the stages of increased alcohol dependence. As dependence upon alcohol increases, so, too, does the level of allostatic load and negative health consequences. This figure is based in part on the work of Koob and Schulkin (2019).

necessitate adaptations by the brain to achieve some approximation of stability against this backdrop of unrelenting challenges. This, in a nutshell, is how allostatic processes unfold and generate allostatic load in an individual with AUD. According to Koob and Schulkin (2019), binge–­withdrawal cycles of alcohol intake lead to increasingly pronounced negative emotional states that are accompanied by progressive blunting of HPA responses and sensitization of CRF circuits in several brain areas, including the bed nucleus of the stria terminalis (BNST) and the central nucleus of the amygdala. The initially rewarding effects of alcohol, facilitated in part by activation of the HPA axis, are then followed by a state of dysphoria and alcohol-­seeking behavior to dampen the intensity of the dysphoric state. Consistent with this model, dysregulation of the HPA axis is closely associated with AUD, which has a high comorbidity with other stress-­related disorders, including depression and anxiety. Clinical studies of patients with AUD have documented impairments in HPA axis responses to exogenous and endogenous stimulation by CRF and blunted ACTH and cortisol responses following exposure to the Trier Social Stress Test (TSST). In addition, the blunted HPA responses to the TSST were predictive of an earlier relapse to drinking (Adinoff, Junghanns, Kiefer, & Krishnan-­Sarin, 2005). Some anticraving drugs, such as opioid receptor antagonists, activate the HPA axis, and the strength of this activation is greater in individuals with a family history of AUD. Another link between brain CRF systems and AUD is the genetic variations that occur in the CRHR1 gene and their interaction with stressful life events to influence an earlier onset of drinking and excessive levels of drinking later in adolescence (Schmid et al., 2010; see the following section). An additional point of vulnerability during abstinence from alcohol is the



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impairment by CRF of the prefrontal cortex and its connections to the central nucleus of the amygdala. These top-down changes in executive control of motivated behaviors by the prefrontal cortex are yet another adaptation to the allostatic challenges experienced by individuals with AUD (Koob & Schulkin, 2019).

Early Life Stress and AUD Focus on CRF Receptors Schmid et al. (2010) examined interactions between early life stress and polymorphisms of the corticotropin releasing factor receptor-1 (CRFR1) gene in the onset of heavy alcohol use in adolescence. For this study, they recruited participants from the Mannheim Study of Children at Risk, a long-term birth cohort study that was started in 1986–1988 to examine the effects of early life risk factors on behavioral and health-­related outcomes. In this study, 270 participants (N = 125 males and 145 females), 15 and 19 years of age, completed a questionnaire to determine age at first alcohol use, patterns of current alcohol use, and recent stressful life events. Participants provided blood samples for genotyping two SNPs of the CRFR1 gene, rs242938 (GG, GA, and AA) and rs1876831 (CC, CT, and TT). Negative life events during childhood and evidence of child psychopathology were determined through standardized interviews with the parent(s) of each participant. The results indicated that, even after control for a range of confounding variables, higher numbers of stressful life events prior to drinking onset were significantly related to earlier age at first drink of alcohol only among homozygotes for the C allele of rs1876831 (Table 4.3). Earlier age at drinking onset was significantly associated with higher alcohol consumption levels in 19-year-olds. In addition, homozygotes of the TABLE 4.3.  Cox Regression Models Testing the Effects of CRHR1 Genotype, Stressful Life Events Prior to Drinking Onset, and Their Interaction on Age at First Drink of Alcohol Age at first drink of alcohol (years) Variable

HR

95% CI

p

Sex Psychosocial adversity Parental lifetime AUD rs1876831 genotype SLEs rs1876831 x SLEs

0.73 0.92 1.10 1.15 0.96 1.10

0.57–0.94 0.86–0.99 0.79–1.54 0.89–1.48 0.89–1.04 1.01–1.20

0.014 0.031 0.579 0.281 0.307 0.035

Sex Psychosocial adversity Parental lifetime AUD rs242938 genotype SLEs rs242938 x SLEs

0.75 0.93 1.12 0.95 1.01 1.04

0.58–0.96 0.86–0.99 0.80–1.58 0.68–1.32 0.96–1.06 0.91–1.19

0.022 0.040 0.517 0.750 0.786 0.542

Note. SLEs, significant life events. Data are expressed as hazard ratios (HRs) with 95% confidence intervals (CIs). Data are from Schmid et al. (2010) and are used with permission of the publisher.

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rs1876831 C allele as well as carriers of the rs242938 A allele, when exposed to stress, exhibited significantly higher drinking activity than carriers of other alleles. These findings extend previous reports from several laboratories by demonstrating that the CRHR1 gene and stressful life events interact to predict the initiation of alcohol drinking in adolescence and progression into heavy alcohol use in young adulthood. These findings further strengthen the connections between the development of alcohol use and abuse and stress-­related changes in the HPA axis and central CRF stress-­related circuits (Schmid et al., 2010). As is true of many clinical studies, there were some limitations of the study design. First, the sample size was relatively modest for an experiment on genetic associations. Next, occurrence of significant stressful life events was determined from parental reports. Although this is an indirect means of quantifying these adverse events, there is supporting evidence that parental reports of this type are accurate. Finally, the participants were mostly of European descent, and it is unclear if these findings would be replicated with a more diverse sample of participants (Schmid et al., 2010).

Alcohol Dependence Schwandt, Heilig, Hommer, George, and Ramachandani (2013) explored the relationship between exposure to early life stress and alcohol dependence of individuals who were alcohol-­dependent and seeking treatment. Alcohol-­dependent patients (N = 280, 32% female) and healthy controls with no history of alcohol dependence (N = 137, 38% female) completed the 28-item Childhood Trauma Questionnaire, which included information on five types of early trauma: emotional abuse, sexual abuse, physical abuse, emotional neglect, and physical neglect. The prevalence and severity of each type of childhood trauma were significantly greater in the alcohol-­dependent patients compared to healthy controls (ps < .001). No instances of early childhood trauma were reported by 26% of alcohol-­dependent patients and 59% of controls. In addition, a greater percentage of alcohol-­dependent patients experienced more than one type of childhood trauma compared to controls (53.5 and 11.1%, respectively). Emotional abuse during childhood, and to a lesser extent physical abuse, were the strongest predictors of the severity of alcohol dependence in patients. Impulsivity was a prominent mediator of the effects of emotional abuse on severity of alcohol dependence. Childhood trauma in controls was not associated with harmful use of alcohol, suggesting some level of resilience in these individuals. These findings underscore the high risk of alcohol dependence in children exposed to emotional and physical abuse and emphasize the need for effective interventions to disrupt these influences in later life.

Alcohol Abuse as a Stressor Alcohol use in moderation can reduce levels of perceived stress and anxiety. Consider that the social anxiety of being in a reception with strangers at a conference is often relieved with a glass or two of wine. But it is also apparent that excessive intake of alcohol leading to dependence can serve as a potent stressor. It has been well established that acute alcohol intake can increase HPA axis activity and the activity of dopaminergic neurons within the reward circuitry of the brain. However, the ability of alcohol to activate the HPA axis is blunted following a period of chronic alcohol intake.



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Stress and the Initiation of Drinking HPA axis activity and alcohol consumption have been linked in a host of basic and clinical research studies (Blaine & Sinha, 2017; Stephens & Wand, 2012), including research suggesting that flatter diurnal cortisol slopes are associated with greater alcohol use. A lack of longitudinal studies and a focus on adults and AUD patient populations leave open the question of whether such relationships also occur in younger individuals and whether flatter diurnal slopes are a consequence of or a preexisting risk factor for alcohol use.

HPA Axis Effects on Alcohol Use and Abuse Ruttle, Maslowsky, Armstrong, Burk, and Essex (2015) addressed some of these important issues by recruiting a group of 200 adolescents (55% female) to participate in a longitudinal study of HPA axis function and risk for alcohol use and abuse. A community sample of 200 (55% female, 93% Caucasian) adolescents contributed three saliva samples per day for three consecutive days at ages 11 and 18.5 years for measurement of cortisol. In addition, participants were asked each year at ages 15–18 how many alcoholic drinks they had consumed per occasion over the previous 30 days. The results indicated that a flatter diurnal cortisol slope at age 11 predicted higher levels of alcohol use in males and females ages 15–18 years and that heavier alcohol use in turn predicted further flattening of the diurnal cortisol slope at age 18.5 years. This study is the first to demonstrate a longitudinal chain of associations between diurnal cortisol slope at age 11 years and alcohol use during the high school years. A major concern with this study is the lack of accurate information on alcohol intake in these participants at or before 11 years of age. It is possible that some of the participants were already experienced with alcohol use, and these experiences may have affected their HPA axis activity. In addition, the results do not establish a causal link between childhood HPA axis activity and adolescent alcohol intake. The findings are consistent with blunted HPA axis activity in childhood being a risk factor for heavier alcohol intake in adolescence (Ruttle et al., 2015). These findings are in agreement with contemporary theoretical models of the neurobiological processes underlying alcohol use and can inform future research on risk factors for and consequences of underage drinking.

Excessive Social Drinking as a Risk Factor Several studies have demonstrated that chronic, heavy social drinking may eventually escalate into AUD in some individuals. The pathways through which recreational social drinking develops into compulsive and uncontrolled alcohol abuse are multifaceted. One common denominator that plays an important role in alcohol craving in social drinkers and in individuals with AUD is stressful life events. In addition, individuals who are high in impulsivity and risk taking tend to consume more alcohol and are at increased risk of developing AUD. A key challenge for researchers in this area is to be able to predict which individuals are in danger of escalating their patterns of alcohol use from the level of social drinker to dependence and the development of AUD. To address these issues, Clay and Parker (2018) examined the underlying physiological and personality traits that affected stress-­induced craving for and consumption

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of alcohol in a group of social drinkers. Their working hypothesis was that impulsivity/ risk taking would modulate stress-­induced alcohol craving and consumption. Participants in these studies included 22 males and 17 females (average age approximately 24 years) who had never been diagnosed with depression, an anxiety disorder, or AUD. Volunteers who were currently taking various prescription medications that could affect some of the dependent variables were also excluded from the study. Individuals were randomly assigned to “stress” and “no-­stress” groups, with those in the stress group exposed to an abbreviated version of the TSST, as described in Chapter 3. Participants also completed questionnaires and computer tasks to gauge previous alcohol use, impulsivity/risk taking, sensation seeking, stress reactivity, craving, and physiological biomarkers of stress. Finally, participants completed a voluntary drinking task in which increasing numbers of presses on a computer keyboard were reinforced with 5-ml shots of 37% alcohol by volume (ABV) vodka (plus mixer). Participants exposed to the TSST displayed an increase in craving for alcohol following the videotaped oral presentation. Several factors predicted voluntary drinking, including risky decision making, slower heart rate recovery following stress, lower vagal tone during recovery from stress, and greater stress reactivity. Surprisingly, there was no correlation between craving and consumption of alcohol. The authors concluded that the number of alcoholic drinks consumed was associated with greater physiological reactivity and slower physiological recovery following exposure to an abbreviated version of the TSST. This pattern of changes may provide a useful framework to investigate further early predictive markers of the shift from controlled recreational drinking to uncontrolled alcohol misuse, culminating in AUD (Clay & Parker, 2018).

Stress and Craving Guided Imagery and Stress Sinha et al. (2011) utilized personalized guided stressful and alcohol cue-­related imagery to provoke stress and high-­craving dysfunction in early abstinent alcohol-­dependent men and women. They compared a group of 4-week abstinent individuals who were undergoing treatment for AUD (N = 36) to healthy, socially drinking controls (N = 36) matched on age, race, and sex across three imagery conditions: stress, alcohol cue, and neutral/relaxing. They then measured subjective and neuroendocrine responses at baseline, immediately following guided imagery exposure, and at timed intervals following exposure. The results provided indications of HPA axis dysregulation, which included higher resting plasma ACTH levels and blunted stress- and cue-­induced ACTH and cortisol responses in the alcohol-­dependent patients compared to controls. The alcohol-­ dependent individuals also displayed higher levels of anxiety and greater stress- and alcohol cue-­induced alcohol craving compared to controls. Those alcohol-­dependent individuals who displayed higher levels of provoked alcohol craving and had higher cortisol levels and greater cortisol/ACTH ratios (a measure of sensitivity of the adrenal glands to release cortisol in response to the ACTH signal) relapsed more quickly after discharge from inpatient treatment. Additional analyses revealed that individuals with high cortisol/ACTH ratios had a 2.5 times greater risk of relapse and return to heavy drinking. These findings suggest that both craving and stress-­related HPA axis dysfunction may play a role in high-­relapse rates in alcohol-­dependent individuals and that



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targeting this stress-­related pathophysiological change pharmacologically could reduce alcohol relapse rates (Sinha et al., 2011).

Stress and Craving and Treatment Outcomes Stress has been shown to increase craving in alcohol-­dependent individuals, but the relationship between stress-­induced alcohol craving and treatment outcomes for patients with AUD is not well understood. A study by Higley et al. (2011) examined the relationship between the intensity of stress-­induced alcohol craving in a laboratory setting and subsequent alcohol drinking in a group of treatment-­seeking, alcohol-­dependent males (N = 16) and females (N = 12) enrolled in a 12-week outpatient program. All participants completed a series of questionnaires to assess history of alcohol and substance use, to quantify alcohol consumption in the previous 90 days, to determine level of craving for alcohol, and to measure mood state. Stress was induced using a personalized, audio-­recorded stress script from a salient and highly stressful life experience and validated with measures of salivary cortisol levels and subjective distress. Craving for alcohol was measured before and after listening to the stressful audiotape. Higher levels of stress-­induced craving were associated with a blunted salivary cortisol response, a reduced time to alcohol relapse (5.5 days vs. 49 days, respectively), higher mean drinks per week, a reduced frequency of days abstinent, and lower rates of complete abstinence over the length of the study (all ps < .05). It should be noted that high-­stress craving individuals did not differ from low-­stress craving individuals in the subjective ratings of the stress levels associated with the stressful audiotape, with average stress ratings for both groups of 9+ out of 10. These results suggest that greater stress-­related increases in alcohol craving are associated with more negative alcohol treatment outcomes. Stress-­induced craving appears to be an excellent predictor of the risk of alcohol relapse and such information could be especially valuable in personalizing treatment interventions. For example, interventions that target high-­stress levels and the associated high levels of alcohol craving may improve treatment outcomes in alcohol-­dependent individuals. It should be noted that the sample size for this study was limited and the means of assessing HPA axis activity was indirect. In spite of these limitations, the results of this study provide valuable insights for improving treatment outcomes in individuals with AUD (Higley et al., 2011).

Stress and the Maintenance of Drinking Considerable evidence from basic animal research as well as clinical studies links brain circuits involved in motivation, learning, and regulation of stress effector systems, including the HPA axis, with alcohol abuse and dependence (Richardson, Lee, O’Dell, Koob, & Rivier, 2008; Wieting et al., 2019). A major gap in the literature relates to potential differences between males and females in how these circuits respond to stress and influence alcohol abuse.

Brain Imaging and Dependence To address these and other issues, Grace et al. (2021) drew on a sample of 966 participants (mean age = 32.5 years) from the ENIGMA Addiction Working Group. The Enhancing NeuroImaging Genetics through Meta-­A nalysis (ENIGMA) Consortium is

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a global collaborative network of researchers from 43 countries working together on a wide range of studies in neuroscience, genetics, and medicine, with a database of more than 50,000 participants. By employing meta-­analysis of results from multiple sites that follow established protocols, ENIGMA has an ability to detect changes in brain that no individual site could detect in isolation and that address the long-­standing concern about reproducibility in brain-­imaging studies (Thompson et al., 2020). Of the 966 participants in this study, 323 individuals were without alcohol dependence (225 males and 98 females), and 643 individuals had documented cases of alcohol dependence (418 males and 225 females). The investigators generated the following hypotheses: (1) on average, people with alcohol dependence will have smaller volumes of specific amygdala nuclei (i.e., central and basolateral nuclei) and hippocampal subfields (i.e., CA1, CA3, dentate gyrus and subiculum) compared to controls; (2) females with alcohol dependence will have smaller brain nuclear volumes than female controls and males with alcohol dependence; and (3) a greater number of monthly standard alcoholic drinks will predict lower nuclear volumes in individuals of both sexes. Their findings revealed that alcohol-­dependent males had smaller volumes of the total amygdala and its basolateral nucleus than control males, and this difference was exacerbated with increasing intake of alcohol. In contrast, there were no significant differences between alcohol-­ dependent and control females in amygdala volumes. Increased levels of monthly alcohol consumption were associated with smaller total and basolateral amygdala volume in males but not in females. Alcohol dependence was also associated with smaller volumes of the hippocampus and neurons in the CA1 area and subiculum subfield in both males and females, and these effects were not influenced by increases in monthly alcohol consumption. Finally, individuals in the alcohol-­dependent group had significantly reduced total brain estimates of gray and white matter volumes compared to healthy controls. The authors concluded that systematic assessments of sex differences in brain responses to alcohol dependence are justified and should include a longitudinal approach to document changes that occur before and during the establishment of alcohol dependence and in response to recovery and relapse. Armed with this vital information, it may be possible to develop personalized treatment protocols, especially with respect to sex differences in brain responses to alcohol dependence (Grace et al., 2021).

Drinking at Work National surveys of the U.S. workforce have revealed that 26% of workers consume five or more drinks per day, 30% of workers consume alcohol until intoxicated, 23% of workers experience a hangover, and 38% of workers start drinking alcohol within 2 hours of leaving the workplace over a 12-month period (Frone, 2013). Special concerns include excessive alcohol intake, workday alcohol use, and alcohol use initiated shortly after leaving work given the negative effects of alcohol abuse on employee health, job performance, safety on and off the job, and the associated costs of alcohol misuse. Imagine the rippling effects on a family and a community of a working mother or father who is fired from a job for poor performance related to alcohol abuse. Frone (2016) analyzed data from the National Survey of Work Stress and Health telephone survey, a national probability sample of 2,808 U.S. workers. Respondents were 53% male and 69% White, had a mean age of 41 years, worked 41 hours per week



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on average, and 83% held white-­collar jobs. The results of this study were employed to test a moderated-­mediation model of work stress and alcohol use, based on the biphasic effects of alcohol, including stimulant and sedative properties, and the self-­medication and stress vulnerability models of alcohol use. Work stress can result in negative affect and fatigue, which in turn may stimulate the intake of alcohol. The results of the study revealed that exposure to stress at work promoted excessive alcohol intake by men and women who had expectations in line with the tension-­reduction properties of alcohol, and alcohol use after work among men who held strong tension-­reduction alcohol expectancies. In addition, heavy alcohol use and workday alcohol use occurred among men who associated alcohol use with reductions of work-­related fatigue. These results provide valuable baseline information as employers seek to design interventions to reduce excessive alcohol use by employees and improve workplace productivity and safety.

Stress and Relapse of Drinking Mindfulness and Relapse Garland, Franken, and Howard (2012) evaluated cue-­elicited high-­frequency heart rate variability (HFHRV) and alcohol attentional bias as potential relapse risk indices in a group of alcohol-­dependent patients who were participating in a 2-year residential treatment program. The stated goal of the treatment program was total abstinence from alcohol and other drugs. As part of their treatment program, the patients (N = 53, 79% male, 60% African American) were randomly assigned to a 10-week mindfulness-­based therapy program (Mindfulness-­Oriented Recovery Enhancement or MORE) to reduce craving for alcohol or to an addiction support group (control condition). Over the one month prior to admission to the treatment program, the mean number of current DSMIV alcohol dependence criteria met by participants was 6.5, the mean total score on the AUDIT-C was 32, and the mean number of standard alcoholic drinks consumed per day in the year prior to entering treatment was 19. Many participants had also used cocaine and/or another psychoactive drugs on a regular basis. At the time of the study, participants had completed approximately 22 months of the treatment program. Alcohol attentional bias was measured in all participants using a computer-­based system for presenting stimuli, and this task is significantly correlated with severity of alcohol dependence. For a second task, participants were prepared for continuous recording of electrocardiogram (ECG) and were told to relax during a 5-minute baseline period. Next, 30 unpleasant images (e.g., a snake preparing to strike, people threatened by guns or knives, dead bodies) appeared on a computer screen for 10 seconds each. Next, 30 images of alcoholic beverages were presented, and 12 of the 30 images included individuals who were drinking alcoholic beverages. Instructions were to stay fixated on the screen and not to move. During the 10-week intervention, six participants relapsed prior to completion of the treatment program, and nine other participants relapsed during the 6-month follow­up period. Posttreatment high-­frequency heart rate variability (HRV) cue-­reactivity and alcohol attentional bias significantly predicted the occurrence and timing of relapse by the 6-month follow-­up period. These effects were not influenced by treatment condition and remained after controlling for the severity of alcohol dependence.

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Those participants who were more disrupted by visually presented alcohol cues may exhibit greater activation of central autonomic pathways as reflected by changes in vagal input to the heart compared to those who were less affected by the visual cues. These prominent changes in central autonomic pathways may reflect conditioned responses to alcohol-­related visual cues that were not extinguished even after 2 years in a treatment program. In contrast, those participants who did not display significant high-­frequency HRV changes during exposure to visual cues may have experienced extinction of the conditioned response to alcohol-­related imagery. Although there were several limitations to this study because of restrictions imposed by the treatment program, the results hold promise for tracking self-­regulation of appetitive responses to alcohol-­related cues and predicting susceptibility for relapse during and after involvement in a treatment program (Garland et al., 2012).

Daily Stressors and Relapse Levels of stress have been shown under laboratory conditions to increase craving in individuals with AUD and are predictive of future risk of alcohol relapse. An unresolved question is whether exposure to stressors on a given day affects craving on that day to influence prospective alcohol intake in a real-world setting, particularly during early treatment and recovery. Wemm, Larkin, Hermes, Tenne, and Sinha (2019) conducted two longitudinal studies to address these issues relating to stress and alcohol relapse. The first study included 85 individuals with AUD (N = 31 females), who reported their daily levels of stress, craving, and alcohol intake in the first 2 weeks of being in an outpatient treatment program. A second validation study included 28 patients with AUD who were monitored daily during 8 weeks of an outpatient 12-step-based behavioral counseling treatment program for AUD. Data were collected from telephone-­based daily diaries for 903 days in Study 1 and 1,488 days in Study 2. Multilevel latent models tested whether daily and person-­averaged craving mediated the link between stressful events and next-day drinking during treatment. In both studies, exposure to a stressful event on a given day predicted increased craving of alcohol on that same day (ps ≤ .002); these increases in daily craving predicted the likelihood of drinking the next day (ps < .015), as well as the amount of alcohol consumed (ps < .01). Individuals who experienced more stressful events reported higher craving (ps ≤ .012), and higher cravers reported greater levels of next-day drinking (ps < .001). The findings across these two studies with independent samples of participants confirmed for the first time that craving directly mediates the association between stress and next-day alcohol intake in individuals diagnosed with AUD. There was a clear indication that developing novel treatment strategies to mitigate stress-­induced craving might improve the success rates of individuals with AUD who participate in alcohol treatment programs (Wemm et al., 2019).

STRESS‑TARGETED INTERVENTIONS FOR AUD Treatments for AUD must factor in the contributions of stressors at multiple levels of the cycles of alcohol dependence and determine ways to short-­circuit these effects on



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allostatic systems and brain circuits responsible for craving and relapse. This is a monumentally challenging undertaking and explains in part why relapse rates following treatment for AUD remain so high (40–60% lifetime relapse). Although evidence-­based practice guidelines to inform treatments of AUD are now available, no new drugs have been approved for the treatment of AUD since 2004. At present, there are only three FDA-­approved drugs for treating AUD: naltrexone, acamprosate, and disulfiram. The first two drugs are utilized to reduce craving, while disulfiram serves as a deterrent by producing an accumulation of toxic acetaldehyde if a patient consumes alcohol (Campbell, Lawrence, & Perry, 2018; Witkiewitz, Litten, & Leggio, 2019). A desperate need going forward is for the development of personalized approaches to the treatment of AUD. A personalized treatment plan would take into consideration genetic and environmental factors as well as the stage of the addiction cycle that a patient is experiencing. Additional considerations would include age, gender, ethnicity, other comorbidities, a detailed drinking history, cognitive function, and responses to alcohol-­related cues and life stressors. New behavioral therapies are being developed to facilitate this level of personalization. For example, CBT4CBT, a modularized version of cognitive-­behavioral therapy (CBT), is divided into seven separate parts that can be delivered and evaluated independently (Carroll & Kiluk, 2017). The expanded use of wearables and smartphone-­delivered modules also support this increased attention on the individual. A concern about personalized treatment programs, however desirable, is the lack of scalability given the enormous problem of AUD in the United States and countries around the world. Included below are summaries of two studies that have targeted specific aspects of the stress axis in an attempt to support abstinence in individuals with AUD. The first study targets the control of ACTH release from the anterior pituitary, and the second blocks the effects of NE released from sympathetic nerve terminals in the periphery and from NE neurons in brain.

Blockade of Vasopressin Receptors AUD has been linked to dysregulation of brain stress systems, which results in a negative emotional state and chronic relapsing alcohol intake. One reflection of the dysregulation of brain stress systems is the alteration in the HPA axis as described above (Sinha et al., 2011). Arginine vasopressin (AVP) is a hypothalamic peptide hormone that acts synergistically with CRF to regulate the release of ACTH from the anterior pituitary gland. Preclinical research with animal models has shown that AVP receptors play an important role in regulating HPA axis activity and anxiety levels and in stimulating alcohol intake. Building upon these findings, Ryan et al. (2017) evaluated the effects of a vasopressin V1b receptor antagonist, ABT-436, in alcohol-­dependent participants during a 12-week randomized, double-­blind, placebo-­controlled, parallel-­group clinical trial. Participants (N = 150 males and females) who met criteria for DSM–IV alcohol dependence were recruited at four sites. Participants received ABT-436 or placebo, together with a computerized behavioral intervention. ABT-436 was adjusted to 800 mg/day during weeks 2–12. Participants were involved in six in-­person clinic visits and six telephone interviews. Participants who received ABT-436 exhibited a slight but nonsignificant decrease in percentage of days with heavy drinking (p > .15). In contrast, ABT-436 administration

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did result in a significantly greater percentage of days of abstaining from alcohol compared to those receiving placebo (51.2 and 41.6 days, respectively; p = .037). No significant differences were found between treatment groups on any other measures of drinking, alcohol craving, or alcohol-­related consequences. In subgroup analyses, participants with relatively higher baseline levels of stress responded better to ABT-436 on some alcohol-­related outcomes, suggesting there may be benefits to testing drugs that block V1b receptors in alcohol-­dependent patients with high levels of stress.

Adrenergic Antagonists Chronic alcohol use results in changes in brain circuits regulating stress effector systems. These changes may contribute to acute alcohol withdrawal symptoms, reduced responses of the HPA axis, higher levels of stress-­induced craving, and enhanced risk of alcohol relapse. Thus, this pattern of stress regulatory alterations may jeopardize coping effectively with stressors and recovery from chronic alcohol use during early abstinence. Research with animal models suggests that noradrenergic disruption may contribute to these alcohol-­related stress arousal changes and that a1-adrenergic antagonists, such as prazosin, may normalize these stress system adaptations and lead to reductions in alcohol intake. To explore the impact of prazosin, Milivojevic, Angarita, Hermes, Sinha, and Fox (2020) hypothesized that administration of prazosin would reduce stress-­induced craving and improve neuroendocrine and autonomic responses to stressful stimulation and to alcohol cue exposure during early stages of abstinence. They also considered the role of comorbid anxiety disorders in these prazosin effects. Forty inpatient treatment-­ seeking alcohol-­dependent individuals were randomly assigned to receive placebo (N = 18) or 16 mg, three times per day, of prazosin (N = 22) in a double-­blind manner, titrated over 2 weeks. In weeks 3–4, after achieving the full daily dose, patients were exposed to three 5-minute personalized guided imagery conditions (stress cue, alcohol cue, neutral/relaxing cue) on three consecutive days in a random, counterbalanced order. Alcohol craving, anxiety levels, heart rate, and plasma levels of cortisol and ACTH were measured at baseline, following the guided imagery conditions, and at several times during recovery. Administration of prazosin reduced stress cue-­induced alcohol craving (p < .05) and stress- and alcohol cue-­induced anxiety (p < .05) and increased heart rate responses in all imagery conditions (p < .05). Prazosin also lowered resting levels of cortisol and ACTH (ps < .05) and attenuated stress cue-­induced elevations in cortisol (p < .05) compared to placebo-­treated controls. Finally, in those participants without a history of a comorbid anxiety disorder, the placebo group showed stress- and alcohol cue-­induced increases in cortisol (ps < .05), while the prazosin group did not. In this study, prazosin appeared to attenuate stress cue-­induced alcohol craving and anxiety levels during early abstinence, while improving adrenergic and stress system function, effects that are independent of a history of comorbid anxiety disorders (Milivojevic et al., 2020). Given that prazosin is sufficiently lipophilic to cross the blood– brain barrier, the physiological and behavioral effects of the drug documented in this study may have resulted from a combination of a blockade of central and peripheral a1-adrenergic receptors.



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CONCLUSIONS Genetic, neurobiological, endocrine, and environmental factors interact in a complex manner to influence the effects of stressful life events on alcohol use and abuse. During the initiation of alcohol drinking in adolescence or young adulthood, background levels of stress may enhance the anti-­anxiety and rewarding effects of alcohol. However, continuing and excessive alcohol intake may itself act as a potent life stressor that adds to allostatic load, resulting in a downward spiral of deleterious alterations in brain reward pathways and autonomic and neuroendocrine regulatory systems. The net impact on alcohol-­dependent individuals is a persistent negative emotional state coupled with impairments in executive function, such that behavioral control over further alcohol consumption fails and exposure to additional stressors results in a reinstatement of excessive alcohol consumption (Becker, 2017). An emerging concern in the field of stress and alcohol use is the dramatic increase in rates of AUD among women in the United States over the past 20 years. Women tend to experience greater alcohol-­related health problems compared to men, and stressful life events contribute to problem drinking in women as well as men (Grant et al., 2017). In general, women tend to consume alcohol to regulate negative affect and responsiveness to stressors, and they are more prone than men to relapse in response to stressful stimulation. Unfortunately, there is a relative lack of systematic research on how adolescent males and females differ in patterns of initiation and maintenance of alcohol use and abuse. Looking ahead, there are exciting opportunities to identify sex-­specific treatments to reduce the impact of stressful life events on AUD (Peltier et al., 2019).

CHAPTER 5

Posttraumatic Stress Disorder

T

hroughout recorded history, there have been references to the psychological as well as physical damage done to soldiers during armed conflicts and large-scale wars. These references to the development of chronic mental symptoms, disturbances in sleep and dreaming, and even psychic blindness after witnessing the death of a close friend or comrade appear in Greek and Roman literature beginning more than 2,000 years ago. Similar observations of the effects of traumatic experiences by soldiers have been recorded following many of the epic battles that have occurred more recently, from the time of Napoleon to the Civil War and to the major wars and conflicts of the 20th and 21st centuries. A recent and tragic example is the war in Ukraine. A variety of labels have been applied to these conditions over the years, including battle hypnosis, shell shock, and soldier’s heart. Some soldiers who displayed the effects of traumatic experiences in battle were even accused of malingering and were forced back into service. An important parallel observation was that survivors of accidents, such as train collisions, also displayed symptoms similar to soldiers in battle. An important milestone was the recognition that the common denominator for these extreme behavioral responses was the experience of trauma (Crocq & Crocq, 2000). Posttraumatic stress disorder (PTSD) was officially recognized by the psychiatric community as a mental disorder with the publication of DSM-III (American Psychiatric Association, 1980). This disorder stands apart from all other psychiatric disorders in that prior exposure to a highly stressful and traumatic event is required for a diagnosis of PTSD (Yehuda, 2002; Yehuda et al., 2015). Other psychiatric disorders include life stressors as important environmental stimuli that may contribute to the onset and/or expression of symptoms associated with these disorders, often through interaction with susceptible genotypes. However, PTSD stands apart in the tight coupling between exposure to the traumatic event and the onset of symptoms of the disorder. An unresolved issue remains: why do some individuals exposed to a traumatic event develop PTSD while others exposed to the same traumatic event don’t? The challenges for researchers and clinicians interested in PTSD center on understanding the risk 88



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factors that lead to symptoms of PTSD in susceptible individuals and the range of neural and physiological responses to the trauma that are useful in tracking the effectiveness of PTSD-­specific treatments. Epidemiological studies have shown that most individuals in the general population have been exposed to at least one traumatic event over the course of their lifetimes, but most trauma-­exposed individuals do not go on to develop PTSD. Women have been reported to be more vulnerable to the development of PTSD than men, even after controlling for prior history of victimization or abuse. These sex differences in vulnerability to PTSD appear to reflect in part greater heritability of risk in women compared to men. However, other factors are at work, including possible sex differences in neural circuits controlling fearful memories (Christiansen & Hansen, 2015; Ramikie & Ressler, 2018). Rates of PTSD following a natural disaster are relatively low (less than 5%), whereas rates of PTSD following rape are quite high (approximately 65%). In studies of combat veterans from the wars in Iraq and Afghanistan, levels of PTSD peaked at 25–30% among those individuals with the highest recurring exposures to combat-­related traumatic experiences. Finally, PTSD symptoms may persist in individuals for a decade or longer, especially those exposed to life-­threatening natural disasters or combat-­related trauma (Goenjian et al., 2021; Keane, Marshall, & Taft, 2006; Pietrzak et al., 2014; Yehuda et al., 2015). Results from the WHO-led World Mental Health Surveys of 68,894 people in 24 countries provided stark evidence of how common traumatic experiences are in people living in countries across the globe (Kessler et al., 2017). Based on face-to-face interviews, 70% of those interviewed reported exposure to traumatic experiences, with an average of 4.6 exposures per affected individual. The burden of PTSD was estimated to be 78 person-­years/100 respondents. The most significant contributors to the burden of PTSD were rape, other types of sexual assaults, being stalked, and experiencing the unexpected death of a loved one (12%). Tragically, the broad category of intimate partner sexual violence was associated with 43% of all person-­years lived with PTSD (Table 5.1). TABLE 5.1.  An Abbreviated List of the Risk of a Diagnosis of PTSD Using DSM-IV Criteria by Type of Trauma Exposure in the World Mental Health Surveys Conducted by the World Health Organization in 25 Countries between 2001 and 2012 PTSD risk given exposure (%)

Proportion of all PTSD episodes (%)

War-related traumas

 3.5

 6.4

Physical violence

 2.8

 9.7

Intimate partner/sexual violence

11.4

27.8

Accidents

 2.0

12.4

Unexpected death of loved one

 5.4

22.2

Other traumas of loved ones or witnessed

 2.4

15.0

Other traumas/private traumas

 9.2

 6.5

Type of trauma exposure

Note. Data are adapted from Kessler et al. (2017). PTSD risk given exposure reflects the conditional risk of a diagnosis of PTSD for the various types of trauma. For example, for all war-related trauma exposures, 3.5% resulted in a DSM-IV diagnosis of PTSD.

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The data from the World Mental Health Surveys also demonstrated how trauma exposure is not evenly divided across a population. Women are much more likely to experience intimate partner sexual violence, and men are much more likely to experience physical violence and accidents. Marriage tends to greatly reduce the risks associated with many types of trauma exposure, whereas being in a lower socioeconomic stratum of society tends to increase risks of violence and accidents. Finally, prior trauma history predicted future trauma exposure as well as future PTSD risk (Kessler et al., 2017).

DIAGNOSIS OF PTSD The publication of DSM-III was a critical moment in the history of American psychiatry. For the first time, PTSD was recognized as a new diagnostic category, due in part to intense lobbying efforts by Vietnam veterans’ groups and their supporters. The addition of PTSD to DSM-III also opened up the field of psychiatry to the importance of trauma studies and stimulated the development of diagnostic instruments for assessing PTSD in service members as well as civilians (Keane, Wolfe, & Taylor, 1987). None of these changes came easily, and there were many tense moments and disagreements leading up to the ultimate approval of DSM-III by the American Psychiatric Association (Wilson, 1993). DSM-5-TR (American Psychiatric Association, 2022) presents PTSD as a single broad diagnosis that includes 24 symptoms and 8 criteria (Table 5.2). Note that exposure to the traumatic event can be direct or indirect, the effects must persist over time, there may be marked behavioral and physiological responses to reminders of the trauma, and there are elevations in reactivity to alerting stimuli. The International Classification of Diseases, 11th Revision (ICD-11), was published by the WHO in 2018 and went into effect on January 1, 2022. ICD-11 is a health statistics coding system used as a guide for diagnosis of diseases and coding of causes of death in most countries of the world. In contrast to DSM-5-TR, ICD-11 proposed two related disorders, PTSD and complex PTSD (Tables 5.3 and 5.4). PTSD includes six symptoms distributed across three clusters as well as evidence of functional impairment, whereas complex PTSD includes all requirements for a diagnosis of PTSD plus three symptom clusters related to disturbances of self-­regulation. Disturbances of self-­ regulation result from traumatic events that are interpersonal in nature, especially those that occur during childhood and adolescence and from which escape is difficult or impossible. Examples include experiencing childhood sexual abuse or torture and being held captive. The clear differences in approach taken between DSM-5-TR and ICD-11 are reflected in the differences in frequency of a diagnosis between the two systems, with a more frequent diagnosis of PTSD with DSM-5-TR compared to ICD-11. These differences between the two systems will at times be a challenge to researchers globally in comparing across published reports and when conducting meta-­analyses of PTSD (Hyland et al., 2018).

TABLE 5.2.  Diagnosis of PTSD in Individuals Older Than 6 Years .

Note: The following criteria apply to adults, adolescents, and children older than 6 years. A. Exposure to actual or threatened death, serious injury, or sexual violence in one (or more) of the following ways: 1. Directly experiencing the traumatic event(s). 2. Witnessing, in person, the event(s) as it occurred to others. 3. Learning that the traumatic event(s) occurred to a close family member or close friend. In cases of actual or threatened death of a family member or friend, the event(s) must have been violent or accidental. 4. Experiencing repeated or extreme exposure to aversive details of the traumatic event(s) (e.g., first responders collecting human remains; police officers repeatedly exposed to details of child abuse). Note: Criterion A4 does not apply to exposure through electronic media, television, movies, or pictures, unless this exposure is work related. B. Presence of one (or more) of the following intrusion symptoms associated with the traumatic event(s), beginning after the traumatic event(s) occurred: 1. Recurrent, involuntary, and intrusive distressing memories of the traumatic event(s). Note: In children older than 6 years, repetitive play may occur in which themes or aspects of the traumatic event(s) are expressed. 2. Recurrent distressing dreams in which the content and/or affect of the dream are related to the traumatic event(s). Note: In children, there may be frightening dreams without recognizable content. 3. Dissociative reactions (e.g., flashbacks) in which the individual feels or acts as if the traumatic event(s) were recurring. (Such reactions may occur on a continuum, with the most extreme expression being a complete loss of awareness of present surroundings.) Note: In children, trauma-specific reenactment may occur in play. 4. Intense or prolonged psychological distress at exposure to internal or external cues that symbolize or resemble an aspect of the traumatic event(s). 5. Marked physiological reactions to internal or external cues that symbolize or resemble an aspect of the traumatic event(s). C. Persistent avoidance of stimuli associated with the traumatic event(s), beginning after the traumatic event(s) occurred, as evidenced by one or both of the following: 1. Avoidance of or efforts to avoid distressing memories, thoughts, or feelings about or closely associated with the traumatic event(s). 2. Avoidance of or efforts to avoid external reminders (people, places, conversations, activities, objects, situations) that arouse distressing memories, thoughts, or feelings about or closely associated with the traumatic event(s). D. Negative alterations in cognitions and mood associated with the traumatic event(s), beginning or worsening after the traumatic event(s) occurred, as evidenced by two (or more) of the following: 1. Inability to remember an important aspect of the traumatic event(s) (typically due to dissociative amnesia and not to other factors such as head injury, alcohol, or drugs). 2. Persistent and exaggerated negative beliefs or expectations about oneself, others, or the world (e.g., “I am bad,” “No one can be trusted,” “The world is completely dangerous,” “My whole nervous system is permanently ruined”). 3. Persistent, distorted cognitions about the cause or consequences of the traumatic event(s) that lead the individual to blame himself/herself or others. 4. Persistent negative emotional state (e.g., fear, horror, anger, guilt, or shame). 5. Markedly diminished interest or participation in significant activities. 6. Feelings of detachment or estrangement from others. 7. Persistent inability to experience positive emotions (e.g., inability to experience happiness, satisfaction, or loving feelings). (continued)

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TABLE 5.2. (continued) E. Marked alterations in arousal and reactivity associated with the traumatic event(s), beginning or worsening after the traumatic event(s) occurred, as evidenced by two (or more) of the following: 1. Irritable behavior and angry outbursts (with little or no provocation) typically expressed as verbal or physical aggression toward people or objects. 2. Reckless or self-destructive behavior. 3. Hypervigilance. 4. Exaggerated startle response. 5. Problems with concentration. 6. Sleep disturbance (e.g., difficulty falling or staying asleep or restless sleep). F. Duration of the disturbance (Criteria B, C, D, and E) is more than 1 month. G. The disturbance causes clinically significant distress or impairment in social, occupational, or other important areas of functioning. H. The disturbance is not attributable to the physiological effects of a substance (e.g., medication, alcohol) or another medical condition. Specify whether: With dissociative symptoms: The individual’s symptoms meet the criteria for posttraumatic stress disorder, and in addition, in response to the stressor, the individual experiences persistent or recurrent symptoms of either of the following: 1. Depersonalization: Persistent or recurrent experiences of feeling detached from, and as if one were an outside observer of, one’s mental processes or body (e.g., feeling as though one were in a dream; feeling a sense of unreality of self or body or of time moving slowly). 2. Derealization: Persistent or recurrent experiences of unreality of surroundings (e.g., the world around the individual is experienced as unreal, dreamlike, distant, or distorted). Note: To use this subtype, the dissociative symptoms must not be attributable to the physiological effects of a substance (e.g., blackouts, behavior during alcohol intoxication) or another medical condition (e.g., complex partial seizures). Specify if: With delayed expression: If the full diagnostic criteria are not met until at least 6 months after the event (although the onset and expression of some symptoms may be immediate).



Note. Reprinted with permission from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision. Copyright © 2022 American Psychiatric Association. All Rights Reserved.

TABLE 5.3.  Description of PTSD (6B40) from the International Classification of Diseases, 11th Revision Posttraumatic stress disorder (PTSD) may develop following exposure to an extremely threatening or horrific event or series of events. It is characterized by all of the following: 1.  Reexperiencing the traumatic event or events in the present in the form of vivid intrusive memories, flashbacks, or nightmares. Reexperiencing may occur via one or multiple sensory modalities and is typically accompanied by strong or overwhelming emotions, particularly fear or horror, and strong physical sensations. 2.  Avoiding thoughts and memories of the event or events, or avoiding activities, situations, or people reminiscent of the event(s). 3.  Having persistent perceptions of heightened current threat, for example, as indicated by hypervigilance or an enhanced startle reaction to stimuli such as unexpected noises. Note: The symptoms persist for at least several weeks and cause significant impairment in personal, family, social, educational, occupational or other important areas of functioning.



Note. Used with permission of the World Health Organization. ICD-11 license is available at https://creativecommons. org/licenses/by-nd/3.0/igo.

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Posttraumatic Stress Disorder 93 TABLE 5.4.  Description of Complex PTSD (6B41) from the International Classification of Diseases, 11th Revision Complex posttraumatic stress disorder (complex PTSD) may develop following exposure to an event or series of events of an extremely threatening or horrific nature, most commonly prolonged or repetitive events from which escape is difficult or impossible (e.g., torture, slavery, genocide campaigns, prolonged domestic violence, repeated childhood sexual or physical abuse). 1. All diagnostic requirements for PTSD are met. 2. In addition, complex PTSD is characterized by severe and persistent • problems in affect regulation. • beliefs about oneself as diminished, defeated, or worthless, accompanied by feelings of shame, guilt, or failure related to the traumatic event. • difficulties in sustaining relationships and in feeling close to others. 3. These symptoms cause significant impairment in personal, family, social, educational, occupational, or other important areas of functioning.



Note. Used with permission of the World Health Organization.

USING FEAR CONDITIONING TO PROBE THE MECHANISMS OF PTSD PTSD has been characterized by an inability to suppress trauma-­related fear even under safe conditions. In addition, individuals diagnosed with PTSD exhibit a hypersensitivity of the HPA axis to negative feedback regulation. Alterations in fear responses and HPA feedback may be affected by the same stress-­sensitive brain circuits. Jovanovic et al. (2010) explored these possible connections in trauma-­exposed participants by examining HPA axis activity and inhibition of conditioned fear using a fear-­potentiated startle paradigm. This test procedure involved using a 250-msec air blast (140 psi) directed to the larynx as the aversive stimulus and the startle response was measured by electromyographic recordings of the muscles around the eye using surface electrodes. Conditioned stimuli in the form of colored shapes were presented on a computer screen. Ninety traumatized individuals were recruited from Grady Memorial Hospital in Atlanta, Gerogia, to participate in this study. The sample was divided into those who met DSM-IV criteria for PTSD (N = 29) and non-PTSD controls (N = 61) using the PTSD symptom scale (PSS). Both groups showed significant reductions in cortisol and ACTH levels after a dexamethasone suppression test. Dexamethasone is a synthetic derivative of cortisol that is used to suppress the release of ACTH from the pituitary gland through negative feedback (refer to Chapter 2). Participants with PTSD had higher fear-­ potentiated startle to the safety signal and fear inhibition trials (ps < 0.05) compared to controls. In addition, fear-­potentiated startle was positively correlated with baseline and ACTH levels following dexamethasone suppression in participants with PTSD. These findings suggest that impaired fear inhibition and associated disruptions in negative feedback regulation of the HPA axis may reflect amygdala hyperactivity in individuals with PTSD (Jovanovic et al., 2010).

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GENETICS OF PTSD Twin Studies The Vietnam Era Twin Registry is a national sample of male twin pairs, both of whom served in branches of the U.S. military from 1964 to 1975. The registry, which is supported by the Department of Veterans Affairs, was started in 1983 and includes monozygotic and dizygotic twin pairs identified through military service records (Forsberg et al., 2019). Wolf et al. (2018) identified a sample of 3,318 twin pairs, of whom 1,936 were monozygotic and 1,382 were dizygotic. This group of participants was born between 1939 and 1957 and 93% were White, 62% were married or living with a partner, and 53% completed a high school education. The weighted lifetime prevalence of PTSD among veterans who served in Vietnam was 17.6%, and for nonwar theater veterans it was 8.9%. All participants were asked to complete the 17-item PTSD Checklist and the 10-item abbreviated version of the Connor–­Davidson Resilience Scale. The heritability of PTSD scores was 49% and that of resilience scores was 25%. The results revealed that scores on the PTSD checklist and the Connor–­Davidson Resilience Scale were significantly negatively correlated (–0.59). Further analyses indicated that a single genetic factor explained 59% of this correlation and explained 49% and 25% of the variance in PTSD and resilience scores, respectively. A single nonshared environmental factor accounted for the remaining covariance between the two measures and explained 51% of the variance in PTSD and 12% of that in resilience. A significance portion of the variance in resilience scores was attributed to common (15%) and nonshared environmental factors (48%) that were separate and apart from those associated with PTSD scores. These investigators concluded that genetic factors contributed to a single spectrum of traumatic stress that included resilience at one end of the spectrum and high symptom severity at the other (Wolf et al., 2018).

Genome‑Wide Association Studies A relatively new technique first reported in 2005, genome-­wide association studies (GWAS), affords a methodology for screening the entire genome of tens of thousands of individuals to detect associations between variants of thousands of genes, or single-­ nucleotide polymorphisms (SNPs), and specific disease outcomes. The focus of GWAS is on statistical associations between SNPs and diseases by comparing individuals with a given disease/disorder with controls who do not have the disease/disorder; however, the experimental findings reveal correlations and not causal influences. Because of the large number of pairwise comparisons of SNPs in such studies, often exceeding 1 million, statistical significance is typically set at p < 5 × 10 –8 and not p < .05, as is typical in highly controlled laboratory experiments with limited sample sizes.

Initial Findings of the Psychiatric Genomics Consortium The Psychiatric Genomics Consortium (PGC) is an international collaboration initiated in 2007 to explore genetic contributions to psychiatric disorders. At present, the PGC consists of more than 800 scientists from more than 40 countries, with more



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than 1 million samples undergoing genetic analyses. Fourteen working groups have been established to study specific psychiatric disorders or combinations of disorders as well as specific methodologies. From its founding, the PGC insisted on combining data from different laboratories and maintaining an open database of all findings. Because many of the effects of individual SNPs make such small contributions to a given disorder, samples sizes have necessarily increased (O’Donovan, 2015; Sullivan & Psychiatric Genomics Consortium, 2012). The Post-­Traumatic Stress Disorder Group of the PGC combined GWAS results across 11 multiethnic reports to determine through a meta-­analysis the heritability of PTSD and to examine the possibility of shared genetic risk between PTSD and other psychiatric disorders (Duncan et al., 2018). Results from a sample of 20,730 individuals that included approximately 25% cases of PTSD indicated a molecular genetics-­ based heritability estimate of 29% for European American females. The heritability estimate for males was much lower than previously reported and did not differ from zero. No single-­nucleotide polymorphisms exceeded genome-­wide significance level in the multiethnic meta-­analysis. In addition, there was evidence of overlapping genetic risk between PTSD and schizophrenia. Including a sample of 10,000 individuals of African ancestry greatly increased ancestral diversity for genome-­wide studies of PTSD. Unfortunately, much larger sample sizes are still required to provide sufficient statistical power to detect risk gene variants contributing to the development of PTSD. Duncan et al. (2018) took special note of the sex differences in heritability estimates for PTSD. One potential explanation for this finding is that female biological variables are more conducive to the expression of genetic risk factors for PTSD, whereas male biological variables tend to repress the expression of genetic risk factors for PTSD. The nature of these biological differences between males and females relating to trauma susceptibility remains an area of active investigation.

Expanded Findings of the PGC Following the initial report by Duncan et al. (2018), the Post-­Traumatic Stress Disorder Group was successful in bolstering the sample sizes for cases and controls through the combined data of 60 multiethnic cohorts as well as the UK Biobank to yield a final sample size of more than 205,000 controls and more than 32,000 PTSD cases (Nievergelt et al., 2019). With this greatly expanded sample size, these investigators reported heritability estimates of 5–20%, with values higher for females, and found that PTSD shared genetic overlap with major depressive disorder and schizophrenia. Three genome-­wide significant risk loci were identified, two in European ancestry samples and one in African ancestry samples. When analyses were stratified by sex, three additional risk loci were identified in men. PARK2 is associated with dopaminergic signaling, PODXL plays a role in neural development and synapse formation, SH3RF3 is involved in cognitive function, ZDHHC14 regulates b-adrenergic receptors, KAZN is underexpressed in selected brain areas of patients with schizophrenia and overexpressed in patients with Parkinson’s disease, and HLA-B contributes to inflammatory responses in stress-­ related diseases. Finally, higher polygenic risk scores were predictive of individuals who reexperienced symptoms of PTSD in the Million Veterans Program sample (Nievergelt et al., 2019).

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Genetic Markers of Combat‑Related PTSD The United States military branches had major concerns about combat-­related PTSD during the course of the extended wars in Iraq and Afghanistan. As a reflection of these concerns, major funding initiatives have been undertaken in an effort to gain insight into susceptibility and resilience to PTSD during and after deployments. One such effort was the Marine Resiliency Study (MRS), a large, prospective study (N = 3,494 males) of combat-­exposed U.S. Marines that included blood samples for genotyping and questionnaires administered before deployment and at 3 and 6 months after deployment to assess symptoms of PTSD. Nievergelt et al. (2015) performed genomic analyses on blood samples from U.S. Marines and Sailors from the MRS prior to and following their deployment to Iraq and/or Afghanistan. The MRS is a large, prospective study funded by the Department of Defense with longitudinal follow-­up designed to identify risk and resiliency factors for combat-­induced stress-­related symptoms. Previously implicated PTSD risk loci and polygenic risk scores across psychiatric disorders were also evaluated in the MRS cohort. Participants (N = 3,494) were assessed using the Clinician-­Administered PTSD Scale and diagnosed using DSM-IV diagnostic criteria. Individuals with partial and/or full PTSD diagnoses were considered cases, while all other participants were designated as controls. Individual genetic ancestry was determined by supervised cluster analyses for participants of European, African, Hispanic/Native American, and other ancestry groups. To test for associations of SNPs with PTSD, logistic regressions were performed within each ancestry group, and results were combined in meta-­analyses. Measures of childhood and adult trauma were included to test for gene × environment (G × E) interactions. Polygenic risk scores from the PGC were used for major depressive disorder (MDD), bipolar disorder (BPD), and schizophrenia (SCZ). The array produced more than 800,000 directly genotyped and more than 21 million imputed markers in 3,494 unrelated, combat-­exposed males, of whom 940 were diagnosed with partial or full PTSD. The GWAS meta-­analysis identified the phosphoribosyl transferase domain containing one gene (PRTFDC1) as a genome-­wide significant PTSD locus (OR = 1.47, SE = 0.06, p = 2.04 × 10 –9), with similar effects across ancestry groups. An association of PRTFDC1 with PTSD in an independent military cohort showed some evidence of replication. Loci with suggestive evidence of association with PTSD (N = 25 genes, ps < 5 × × 10 –6) further implicated genes related to immune response and the ubiquitin system, but these findings remain to be replicated in larger groups of participants. Ubiquitin is a small protein found in most tissues of eukaryotic organisms, including humans. A replication analysis of 25 putative PTSD genes from the literature found nominally significant SNPs for the majority of these genes, but these associations were not statistically significant after correction for multiple comparisons. A cross-­disorder analysis of polygenic risk scores from GWAS of BPD, MDD, and SCZ found that a PTSD diagnosis was associated with risk scores for BPD but not for MDD or SCZ. This first multiethnic GWAS of combat-­related PTSD highlights the potential to increase power through meta-­analyses across ancestry groups. The findings pointed to PRTFDC1 as a potential PTSD risk gene, a finding that awaits further replication. The genetic architecture of PTSD appears to be determined by many SNPs, each with a small effect, and overlaps with other neuropsychiatric disorders (Nievergelt et al., 2015).



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Transcriptome‑Wide Association Studies The transcriptome is an exhaustive catalogue of all mRNA molecules occurring in a particular type of cell or tissue. Lori et al. (2021) sought to identify biomarkers using blood transcriptomics that would predict the trajectory of PTSD symptoms following exposure to a trauma. These biomarkers could facilitate early detection or inform interventions for PTSD and might provide insight into the underlying psychopathology of the disorder. Participants (N = 377) for this prospective study were recruited from the Emergency Department of Grady Memorial Hospital in Atlanta, Georgia, within 24 hours after trauma exposure (70% of cases were road accidents) and were assessed for PTSD symptoms in the emergency department setting and 1, 3, 6, and 12 months later. Three symptom trajectories were identified in the participants based on changes in their PTSD symptoms across the four timepoints out to 1 year after the traumatic event. They included (1) persistent and unremitting symptoms of chronic PTSD (11%), (2) early symptoms of PTSD that diminished with time (33%), or (3) some transient symptoms of PTSD that quickly resolved with no evidence of lingering effects (56%). Blood transcriptomic data were analyzed for associations with longitudinal PTSD symptom trajectories. Obviously, one would aspire to quantify gene expression levels in brain areas associated with PTSD, such as the amygdala, hippocampus, and prefrontal cortex, but this is not possible. The nature of the correlation between gene expression levels in blood versus brain tissue is difficult to establish. However, brain biobanks and transcriptome databases such as BrainCloud and GTEx have contributed to a better understanding of these brain–blood correlations. GRIN3B blood mRNA levels were associated with chronic versus resilient posttrauma symptom trajectories at a transcriptome-­wide level of significance. GRIN3B encodes the 3B subunit of an N-methyl-­D -­aspartate (NMDA) receptor that is widely distributed in the central nervous system. Four genetic variants that regulate mRNA blood expression levels of GRIN3B were identified and among them, GRIN3B rs10401454 was associated with PTSD symptom levels in an independent dataset of participants in the Grady Memorial Hospital Trauma project (N = 3,521, p = .04). Examination of the BrainCloud and GTEx databases revealed that rs10401454 was associated with brain mRNA expression levels of GRIN3B. Given the design of this study, it was not possible to sample blood from participants prior to their visits to the emergency department. However, levels of GRIN3B in baseline blood samples taken in the ED were not associated with later symptoms of PTSD. Thus, blood levels of GRIN3B were not a biomarker of susceptibility for development of PTSD. While further replication and validation studies are clearly needed, these initial and promising data suggest that GRIN3B, a glutamate ionotropic receptor NMDA-type subunit-3B, may contribute to the occurrence and persistence of symptoms of PTSD. In addition, blood mRNA levels of GRIN3B may be a promising early biomarker for the development of PTSD (Lori et al., 2021).

Epigenetic Changes Epigenetic modifications of DNA or histone proteins may aid in distinguishing between PTSD cases and trauma-­exposed controls, but until recently such studies have included sample sizes that were too small to detect differences between PTSD cases and controls. The Psychiatric Genomics Consortium PTSD Epigenetics Workgroup tackled this

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major challenge of limited sample sizes for the study of epigenetic changes associated with PTSD. Smith et al. (2020) presented the results of the largest DNA methylation meta-­analysis of PTSD to date. Ten cohorts of military and civilian participants contributed blood-­derived DNA methylation data and represented a total of 1,896 PTSD cases and trauma-­exposed controls. Four cytosine-­guanine dinucleotides (CpG sites) within the arylhydrocarbon receptor repressor gene (AHRR) were associated with PTSD after adjusting for multiple comparisons, with lower levels of DNA methylation in PTSD cases relative to trauma-­exposed controls. Although AHRR methylation is known to be associated with smoking, the AHRR association with PTSD was most pronounced in nonsmoking individuals, suggesting the key finding of this study was independent of smoking status. An evaluation of metabolomics data revealed that AHRR methylation was associated with levels of kynurenine, a metabolite of l-tryptophan, which are lower in individuals diagnosed with PTSD. Lower levels of kynurenine could result in increases in pro-­inflammatory responses and may explain why individuals diagnosed with PTSD often display increased inflammatory activity. Certain limitations of this study should be kept in mind. Because this study made use of cross-­sectional data, it is not possible to determine if the changes in AHRR methylation were a cause or a consequence of PTSD. Longitudinal studies will be required to address this critical issue. The cohorts that were combined for this study included a mixture of individuals who were recently diagnosed with PTSD versus those with chronic symptoms of PTSD. Thus, the heterogeneity of the PTSD cases could have affected the results of this study. In addition, blood samples were collected to analyze methylation patterns, but some of the most critical epigenetic changes likely occur in brain. Hopefully, future studies will be able to examine epigenetic changes in tissue samples from PTSD brain banks. In spite of these limitations, this study established a link between epigenetic changes and immune system dysregulation in PTSD that could open up new avenues for developing therapies that target the kynurenine pathway (Smith et al., 2020).

TRANSGENERATIONAL TRANSMISSION OF TRAUMA David J. P. Barker (1938–2013) conducted many influential epidemiological studies that confirmed a relationship between the adverse aspects of the fetal and perinatal periods and the programming of chronic diseases later in life, such as cardiovascular disease, hypertension, and diabetes (Barker, 1990, 1999). His extensive body of research, which stimulated the emergence of a field of study referred to as “the developmental origins of health and disease,” has had an enduring impact on international efforts to improve maternal and infant health. The underlying rationale behind the developmental origins of health and disease field of research is that the prenatal and early neonatal periods are exquisitely sensitive to the enduring effects of perturbations in the environment (Bock, Wainstock, Braun, & Segal, 2015). Particular attention has been directed to studies of prenatal programming of epigenetic changes in gene expression that contribute to increased risk for mental disorders later in life (Bale et al., 2010; Chan, Nugent, & Bale, 2018; Morrison et al., 2022; O’Donnell & Meaney, 2017). The children of trauma survivors are at increased risk of developing mental disorders and physical illnesses if the trauma to the parent occurred during pregnancy through placental changes (mother → child), or prior to conception through epigenetic



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changes in gametes (mother and/or father → child) (McCarty, 2020). The best characterized examples of these transgenerational effects of trauma have involved some of the extreme deprivations that occurred during World War II. Two examples will be discussed below: the Dutch “hunger winter” at the end of World War II and the offspring of survivors of the Holocaust.

Dutch “Hunger Winter” A severe tragedy occurred at the end of World War II, when German forces imposed a tight blockade on western cities of The Netherlands, resulting in acute famine and what was referred to by the Dutch as the “hunger winter” (October 1944–May 1945). In spite of the extreme privations that occurred during this period, health registries were maintained. These records permitted researchers to identify individuals who were exposed prenatally to the famine, and the precise timing of the exposure could be determined. For those babies conceived from October 15 to December 31, 1944, there was a twofold greater risk of developing schizophrenia later in life compared to birth cohorts conceived before (N = 10 cohorts) or after (N = 6 cohorts) this 2.5-month period. The cumulative incidence of schizophrenia was approximately 1.9 cases/1,000 individuals in the 16 birth cohorts, compared to 3.8 cases/1,000 individuals in the highest risk group where intense famine occurred during the first trimester of pregnancy (Susser et al., 1996). Additional studies of adults who had been in utero during the Dutch hunger winter have expanded the range of persistent negative effects of extreme deprivation on health measures taken later in life. In a study by Tobi et al. (2014), adults were identified who had been exposed to the hunger winter from conception until 10 weeks of prenatal development and who could be compared to a same-sex sibling born less than 5 years before or after the hunger winter. Twelve female–­female pairs and 12 male–male pairs were participants in this study, and they had a mean age of 58 years at the time blood samples were obtained. Their findings revealed that differentially methylated regions of the genome mapped to genes that are differentially expressed during early development and are involved in growth and development. These persistent epigenetic changes appear to contribute to higher rates of type 2 diabetes, cardiovascular disease, and age-­ related cognitive decline in adults who were exposed early in prenatal development to the Dutch hunger winter (Tobi et al., 2014).

Offspring of Holocaust Survivors Offspring of survivors of the Holocaust are at greater risk of being diagnosed with PTSD if one or both parents had PTSD. In addition, offspring of Holocaust survivors have also experienced higher rates of type 2 diabetes, cardiovascular disease, and mood disorders compared to offspring of parents who were never at risk of being captured by the Nazis (Yehuda, Schmeidler, Wainberg, Binder-­Byrnes, & Duvdevani, 1998). Let’s take a closer look at these effects.

PTSD in Soldiers Solomon, Kotler, and Mikulincer (1988) conducted the first longitudinal study of Israeli soldiers whose parents were Holocaust survivors. The participants (N = 96), whose

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parents were of European descent, were deemed healthy physically and psychologically prior to combat and were later categorized by the Israeli Defense Forces mental health providers as having experienced “combat stress reaction” during the 1982 Lebanon War and were unable to perform their duties as soldiers. Forty-four participants were children of Holocaust survivors and 52 were not (controls). All participants completed the PTSD inventory 1, 2, and 3 years after their participation in combat. The PTSD inventory included 13 items reflecting the DSM-III criteria for PTSD as adjusted for war-­related trauma. The results of this study indicated that the percentage of soldiers having PTSD decreased over time. However, the rate of PTSD was consistently higher in offspring of Holocaust survivors compared to controls at 1, 2, and 3 years following combat. In addition, offspring of Holocaust survivors reported significantly more symptoms of PTSD and displayed a slower recovery from PTSD compared to controls. These investigators concluded that the experience of combat unmasked a latent vulnerability to PTSD in children of Holocaust survivors that had not been activated by previously experienced life stressors (Solomon et al., 1988).

PTSD in Offspring of Holocaust Survivors Yehuda et al. (1998) were concerned about controlling for confounding variables that could impact studies of the offspring of Holocaust survivors. They designed a study to examine prior stress and exposure to trauma, current and lifetime diagnoses of PTSD, and other psychiatric diagnoses in a group of offspring of Holocaust survivors (N = 100, of whom 71 were female) and a demographically matched control group (N = 44, of whom 21 were female). The offspring were defined as having at least one biological parent who survived the Holocaust and who was interned in a Nazi concentration camp or a labor camp or had to flee German-­occupied areas for fear of being captured and killed. Controls were Jewish and of the same age range (28–50 years), and their parents were not in Nazi-­occupied Europe during World War II. Based on results from the Antonovsky Life Stress Scale, adult children of Holocaust survivors reported experiencing a greater amount of lifetime stressors than the control group. However, offspring of Holocaust survivors did not experience more potentially traumatic life events based on responses to the Trauma History Questionnaire. In addition, offspring of Holocaust survivors had a higher prevalence of current and lifetime PTSD and other psychiatric diagnoses (e.g., major depression, anxiety disorder, substance abuse disorder) compared to controls. These findings are consistent with the suggestion that offspring of Holocaust survivors are at high risk for developing PTSD and other psychiatric disorders, possibly through a mechanism(s) involving transgenerational transmission of risk (Yehuda et al., 1998).

Glucocorticoid Receptor Methylation Yehuda et al. (2014) examined the relative effects of maternal versus paternal experiences with the Holocaust on offspring regulation of the gene for the glucocorticoid receptor (GR). Prior research in animal models and humans pointed to DNA methylation of the exon 1F promotor of the GR gene in brain areas and in blood cells as an experience-­dependent change with important ramifications for regulation of the HPA



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axis (McCarty, 2020; Meaney & Szyf, 2005). In this important extension of their work with children of Holocaust survivors, Yehuda and her colleagues recruited participants without a history of PTSD who had at least one parent who was a Holocaust survivor (N = 80) and a demographically matched group of controls (N = 15) whose parents were not exposed to the Holocaust and had no history of PTSD. All participants completed a clinical interview and questionnaires and provided blood samples for measurement of GR-1F methylation in mononuclear blood cells and morning cortisol levels under resting conditions on Day 1 and following response to low-dose dexamethasone (DEX; 0.5 mg) on Day 2. GR-1F methylation was quantified across 39 potential CpG binding sites and expressed as total methylation percentage. Higher levels of methylation of the GR-1F promoter reduce transcription of the GR gene, leading to fewer receptors and resistance to glucocorticoid negative feedback. The results indicated that the effects of paternal history of PTSD were moderated by maternal history of PTSD. That is, paternal PTSD in the absence of maternal PTSD resulted in higher levels of GR-1F methylation in offspring. In contrast, offspring with maternal and paternal PTSD displayed lower levels of GR-1F methylation. These differences in methylation status of the GR-1F gene had functional consequences as revealed by the DEX suppression test. Lower percentage methylation of the GR-1F promoter was associated with greater suppression of cortisol levels by DEX. There was the strong suggestion that these differences in GR-1F promoter methylation in peripheral blood cells were an accurate reflection of the methylation status of the GR-1F promoter in brain circuits involved in negative feedback regulation of the HPA axis. Finally, those offspring whose parents did not have a history of PTSD had lower levels of depression and anxiety disorders compared to offspring with at least one parent who had PTSD. These findings provide new insights into the transgenerational transmission of risk for PTSD and other mental disorders based on parental history of PTSD. Given that the offspring of Holocaust survivors who participated in this study were conceived in some cases many years after trauma exposure, it also raises the issue of germline transmission of the effects of trauma from parent to child (Yehuda et al., 2014).

Trauma and Gene Expression Daskalakis et al. (2021) expanded the scope of studies of transgenerational transmission of trauma by examining the association between parental Holocaust exposure and genome-­wide gene expression in peripheral blood mononuclear cells (PBMCs) from 77 offspring of Holocaust survivors and 15 demographically matched Jewish controls whose parents were living in North America during World War II. Forty-two differentially expressed genes were associated with parental Holocaust exposure (p < .05), and 36 of these genes were downregulated and part of a larger gene network related to reduced glucocorticoid signaling and immune cell function. When both parental Holocaust exposure and maternal age at Holocaust exposure shared differentially expressed genes, fold changes were in the opposite direction. Similarly, fold changes of shared differentially expressed genes associated with maternal PTSD and paternal PTSD were in opposite directions, while fold changes of shared differentially expressed genes associated with both maternal and paternal Holocaust exposure or associated with both maternal and paternal age at Holocaust exposure were in the same direction. Moreover, the identified genes associated with parental Holocaust exposure were enriched for

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glucocorticoid-­regulated genes and immune pathways, and some of these genes mediated the effects of parental Holocaust exposure on C-­reactive protein, a pro-­inflammatory marker released from the liver. The most significant change across all genes analyzed was MMP8, encoding matrix metalloproteinase 8, a regulator of innate immunity. This gene was downregulated in offspring of Holocaust survivors and especially in those whose mothers were young when they were exposed to the traumatic experiences associated with the Holocaust. These results extend previous findings from Yehuda’s laboratory and further solidify the effects of parental exposure to the Holocaust on offspring expression of genes involved in glucocorticoid and immune signaling. These changes in gene expression in the offspring of Holocaust survivors may be associated with the transgenerational transmission of increased risk for PTSD and other mental disorders (Daskalakis et al., 2021).

INFLAMMATION AND PTSD Significant interest has emerged with regard to the contributions of inflammatory processes to the pathophysiology of PTSD. One biomarker that has been frequently employed to assess levels of inflammation is C-­reactive protein (CRP), an acute-phase protein produced in and released by the liver in response to elevated levels of two pro-­ inflammatory cytokines, IL-6 and TNF-a. The American Heart Association had labeled CRP levels that are greater than 3 mg/L as “high,” levels that are 1–3 mg/L as “moderate,” and levels below 1 mg/L as “low” with respect to the risk of cardiovascular disease. CRP levels can increase 100- to 200-fold in blood during an acute infection (Felger et al., 2020; Yeh, 2004). One reason CRP has been studied so frequently in relation to its contributions to various diseases is that it is often measured in the course of routine clinical practice as an indicator of systemic inflammation, especially during bacterial infections. Thus, CRP measures are stored in electronic medical records, and researchers can access them in population-­based studies. Given its large size, CRP does not readily cross the blood– brain barrier, but it may influence brain inflammatory pathways through a number of indirect routes. The heritability of CRP levels in blood is in the range of 35–40% based on twin and family studies (Ligthart et al., 2018). In the three studies discussed in the following sections, I have selected reports that took different approaches to investigate links between CRP and PTSD. In the end, one of them concludes that CRP and PSTD have a bidirectional relationship such that each stimulates the other. These studies provide important insights into the role inflammation may play in the pathophysiology of PTSD and suggest potential therapeutic approaches to ameliorate the symptoms of PTSD.

CRP and PTSD Increased systemic inflammatory processes have been associated with stress-­related psychopathology. In particular, levels of the pro-­inflammatory peptide CRP have been reported to be elevated in individuals with PTSD. Additionally, SNPs in the CRP gene have been associated with circulating levels of CRP and with risk for cardiovascular disease and obesity. To extend these observations, Michopoulos et al. (2015) examined



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whether polymorphisms within the CRP gene and increased serum CRP levels were associated with PTSD symptoms and fear responses in a civilian population with high levels of trauma. Cross-­sectional data, trauma exposure, and DNA samples were collected from 2,698 participants (70% female, 93% African American, average age of 39 years) recruited from primary care clinics at Grady Memorial Hospital in Atlanta, Georgia. This inner-city public hospital serves a primarily African American, low-­ socioeconomic-­status patient population. The mean total number of traumas experienced and witnessed was 4.72. A subgroup of 187 participants who represented a cross-­ section of the larger group participated in further interviews, testing, and physiological measures; of these, 135 were tested using a fear-­potentiated startle paradigm to assess fear-­ related phenotypes of PTSD. In the fear-­ potentiated startle paradigm, colored shapes on a computer screen served as the conditioned stimuli and an air blast to the larynx (250-msec duration, 140 psi) was the unconditioned stimulus. Of six SNPs within the CRP gene, one (rs1130864) was significantly associated with elevated PTSD symptoms (p < .004), including “being overly alert” as the most significant individual symptom. This relationship was especially strong in women. Additionally, CRP genotype was associated with the odds of receiving a PTSD diagnosis (OR = 1.29, 95% CI 1.09–1.53). This SNP was also associated with increased circulating levels of CRP (p = .007), and elevated serum CRP levels (> 3 mg/L) were positively associated with PTSD symptoms (p < .004) and fear-­potentiated startle to a safety signal (p < .05). Taken together, these data indicate that genetic variability in the CRP gene was associated with serum CRP levels and PTSD symptom severity, including symptoms of hyperarousal. Elevated serum CRP levels were also associated with exacerbated fear-­ related responses and PTSD symptom ratings and diagnosis. These findings suggest a potential mechanism by which an increased pro-­inflammatory state may lead to heightened PTSD symptoms and point to a possible drug target for reducing the symptoms of PTSD in this at-risk population (Michopoulos et al., 2015).

CRP in Japanese Women with PTSD PTSD has been associated with increased inflammation. CRP is a marker of systemic inflammation, and SNPs in the CRP gene have been associated with increased blood CRP protein levels and illness severity in PTSD patients. However, the mechanism by which the CRP SNPs are involved in PTSD remains unclear. To address these issues, Otsuka et al. (2021) investigated the association of CRP genetic variation with blood pro-­inflammatory protein levels, PTSD symptoms, and cognitive function, and further explored the moderating effect of childhood maltreatment history, in adult female patients with PTSD. Fifty-seven Japanese women diagnosed with PTSD and 73 healthy female controls were recruited for this study. Three SNPs in the CRP gene (rs2794520, rs1130864, and rs3093059) were genotyped, and analyses focused on rs2794520 (T/C). Serum levels of CRP, tumor necrosis factor a (TNF-a), and interleukin-6 (IL-6) were measured. Participants with the rs2794520 CC/CT genotype, compared to those with the TT genotype, showed significantly higher levels of serum CRP (p = .009) and TNF-a (p = .001), more severe PTSD symptoms (p = .036), and poorer cognitive function (p = .018). Further analyses revealed a significant genotype × maltreatment interaction for more severe PTSD avoidance symptoms (p = .012). These findings further underscore connections between circulating pro-­inflammatory markers and symptoms of PTSD in a sample of Japanese women.

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GWAS, CRP, and PTSD The two previous studies made connections between serum CRP levels, symptoms of PTSD and traumatic experiences, but the underlying mechanisms remain unclear. To take a closer look at these relationships and to increase statistical power, Carvalho et al. (2021) investigated the relationship among serum CRP, PTSD, and traits related to traumatic events and social support using genetic association data from the PTSD Workgroup of the PGC (23,185 PTSD cases and 151,309 controls), the UK Biobank (up to 117,900 individuals), and the CHARGE study (Cohorts for Heart and Aging Research in Genomic Epidemiology, with data from 148,164 individuals). Genetic correlations of serum CRP levels were observed with PTSD (p = .026), traits related to traumatic events, and the presence of social support (p < .008). There was a bidirectional association between CRP and PTSD (CRP → PTSD: p = .015; PTSD → CRP: p = .009). CRP was also negatively associated with the “felt loved as a child” measure (UK Biobank, p = .008). Given the reported effects of socioeconomic status (SES) on PTSD, these investigators performed further analyses to investigate SES as a potential mediator. They found that household income and the deprivation index were significant contributors to the causal estimates of “felt loved as a child” and CRP on PTSD. These findings point to a bidirectional genetic association between PTSD and CRP, but they also highlight a potential role for SES in the interplay between childhood emotional support and inflammatory processes with respect to risk of PTSD (Carvalho et al., 2021).

Inflammation and Combat‑Related PTSD Increased inflammation appears to contribute to the pathophysiology of PTSD. Lindqvist et al. (2017) recruited 61 male war veterans (31 with PTSD and 30 without PTSD) and measured levels of IL-6, TNF-a, gamma interferon, and CRP in blood samples. A standardized “total pro-­inflammatory score” was calculated to limit the number of statistical comparisons. The Clinician-­Administered PTSD Scale (CAPS) was used to assess PTSD symptom severity. Participants with PTSD had significantly higher total pro-­inflammatory scores compared to non-PTSD participants in an unadjusted analysis (p = 0.005) as well as after adjusting for potentially confounding effects of age, body mass index, smoking, and potentially interfering medications and somatic comorbidities (p = .023). However, there were no significant correlations between inflammatory markers and severity of symptoms within the PTSD group. These findings strongly suggest that immune activation may be an important aspect of PTSD pathophysiology, although immune markers were not directly correlated with severity of PTSD symptoms (Lindqvist et al., 2017).

BRAIN‑IMAGING STUDIES AND PTSD Hippocampal Volume Changes in PTSD Studies using structural magnetic resonance imaging (MRI) have shown smaller hippocampal volumes in patients with PTSD. These studies were cross-­sectional in design and did not consider whether smaller hippocampal volumes were secondary to stress-­ induced damage to hippocampal cells, or whether preexisting factors accounted for the differences. To address these possibilities, Bremner et al. (2021a) employed a co-twin case control design to assess the relative contributions of genetic and environmental



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factors to hippocampal volume in PTSD. Monozygotic (N = 13 pairs) and dizygotic (N = 21 pairs) twins with a history of Vietnam-­era military service, where one brother went to Vietnam and developed PTSD, while his brother did not go to Vietnam or develop PTSD, underwent brain MRI. Structural MRI scans were used to outline the left and right hippocampus on multiple coronal slices, add the areas, and adjust for slice thickness to determine hippocampal volumes. Twins with Vietnam combat-­related PTSD had a mean 11% smaller right hippocampal volume in comparison to their twin brothers without combat exposure or PTSD (p < .05). There was no significant interaction by zygosity, suggesting that this was not a predisposing risk factor or genetic effect. This experiment found a smaller hippocampal volume in individuals with PTSD. The results from comparisons between twin brothers suggest that the effects were due in large measure to the stress of combat exposure (Bremner et al., 2021a).

Cortical Volume Changes and PTSD Prior studies of patients diagnosed with PTSD have reported volume changes in multiple regions of the cerebral cortex. However, results for many regions, especially regions outside of emotion-­related prefrontal, insular, and limbic regions, are inconsistent. In addition, a smaller number of studies has addressed the possible involvement of comorbid depression on cortical changes in PTSD. Given these concerns, Wang et al. (2021) combined the regional volume data of 68 cortical regions across both hemispheres from 1,379 PTSD patients and 2,192 controls without PTSD after data were processed by 32 international laboratories using ENIGMA-­standardized procedures. They examined whether regional cortical volumes were different in PTSD patients versus controls, were associated with PTSD symptom severity, or were affected by comorbid depression. Volumes of left and right lateral orbitofrontal gyri (LOFG), left superior temporal gyrus, and right insular, lingual and superior parietal gyri were significantly smaller, on average, in PTSD patients compared to controls (ps < 0.04) and were significantly negatively correlated with severity of PTSD symptoms. After adjusting for depressive symptoms, the results in left and right LOFG remained significant. These findings indicate that cortical volumes in PTSD patients are smaller in prefrontal regulatory regions, as well as in broader emotion and sensory processing cortical regions.

STRESS‑TARGETED INTERVENTIONS FOR PTSD It has been more than 40 years since PTSD was recognized as a psychiatric disorder in DSM-III, but little progress has been made in developing effective therapies for treating the core symptoms of the disorder. At present, only two drugs have been approved in the United States for treatment of PTSD, the selective serotonin reuptake inhibitors sertraline and paroxetine. However, both of these medications tend to reduce the severity of symptoms rather than eliminate the underlying causes of PTSD. Even more concerning is the fact that no new drug has been approved for treatment of PTSD in the past 20 years, and the pipeline for testing new drugs is all but dry (Krystal et al., 2017). In addition to drug treatments for PTSD, psychotherapeutic approaches have also been adopted for treating individuals diagnosed with PTSD. In 2017, the American

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Psychological Association (APA) and the Veterans Health Administration/Department of Defense (VA/DoD) published treatment guidelines for PTSD based upon systematic reviews of the extensive literature relating to effective treatments for PTSD. The APA guidelines related to treatment of PTSD in adults, while the VA/DoD guidelines were specific to treatment of patients within VA or DoD health care facilities (Watkins, Sprang, & Rothbaum, 2018). Among the treatments that were strongly recommended were the following:

• Prolonged exposure therapy. Traumatic experiences may be encoded in memory circuits such that stimulus elements associated with the trauma do not accurately reflect the real world, escape and avoidance responses are easily triggered by innocuous stimuli, and responses to these innocuous stimuli interfere with ongoing behavior. Prolonged exposure therapy delivered in 8–15 sessions is designed to alter these trauma memories, such that they no longer interfere with normal behavior by activating the trauma memory and providing new and accurate information that lessens or eliminates the trauma-­based distortions. • Cognitive processing therapy. This type of therapy is usually delivered in 12 weekly sessions designed for individuals or groups. Individuals identify distorted beliefs about their traumatic experiences and are guided to examine and challenge these beliefs, such that they develop a clearer understanding of why the trauma occurred and how they can go on to lead productive lives. • Cognitive-­behavioral therapy for PTSD. This type of treatment overlaps to some extent with the two previous psychotherapies. It is designed to modify negative appraisals of the traumatic memory and eliminate the dysfunctional behavioral and cognitive strategies that have developed. These negative appraisals may result in repeated strengthening of the traumatic memories and lead to avoidance of stimuli or settings associated with the trauma. Cognitive restructuring encourages individuals to identify their dysfunctional thoughts and beliefs about the trauma, elicit rational alternative thoughts and beliefs, and reappraise thoughts and beliefs about themselves and the trauma they experienced (Watkins et al., 2018). The literature on treatments for PTSD is voluminous. Rather than providing a review of the various treatments for PTSD beyond what I included above, I thought it might be helpful to highlight three recent studies that tackle the problem of advancing effective treatments for PTSD. The first is a detailed study of exposure therapy in combat veterans, the second repurposes a currently approved drug to disrupt the formation of trauma memories, and the third utilizes noninvasive stimulation of the vagus nerve to improve stress-­related symptoms of PTSD.

Exposure Therapy for Military Personnel Developing treatment protocols for active-­ duty military personnel diagnosed with PTSD presents several challenges, including the need for relatively rapid treatment protocols to maintain force readiness. To examine this issue, Foa et al. (2018) studied the effects of massed prolonged exposure therapy (massed therapy), spaced prolonged exposure therapy (spaced therapy), and present-­centered therapy (PCT) compared to a



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minimal-­contact control group (MC control) on PTSD symptom severity. This randomized clinical trial was conducted at Fort Hood, Texas, from January 2011 through July 2016, and included 366 military personnel with PTSD who had returned from deployments in Iraq, Afghanistan, or both. Prolonged exposure therapy involved exposure to trauma memories/reminders, administered as massed therapy (N = 110; 10 sessions delivered over 2 weeks) or spaced therapy (N = 109; 10 sessions delivered over 8 weeks); PCT, a nontrauma-­focused therapy that involved identifying and discussing daily stressors (N = 107; 10 sessions delivered over 8 weeks); or an MC control, which involved telephone calls to participants from therapists (N = 40; once weekly for 4 weeks). Outcomes were assessed before and after treatment and at 2-week, 12-week, and 6-month follow-­ups. The primary outcome was interviewer-­assessed PTSD symptom severity, measured by the PTSD Symptom Scale—­Interview (PSS-I; range, 0–51; higher scores indicate greater PTSD symptom severity). Three highly trained therapists were responsible for all therapy sessions and follow-­up interviews. From the 366 participants who started the study (mean age 33 years; 44 women [12.0%]; mean baseline PSS-I score of 25.49), only 216 (59%) completed the study. At 2 weeks posttreatment, the mean PSS-I score was 17.62 (mean decrease from baseline = 7.13) for massed therapy, 18.03 (mean decrease from baseline = 7.29) for the spaced therapy group, 18.65 (mean decrease from baseline = 7.61) for the PCT group, and 21.41 (mean decrease = 3.43) for MC controls. Among active-­duty military personnel with PTSD, massed therapy (10 sessions over 2 weeks) reduced PTSD symptom severity to a greater extent than the response observed in MC controls at 2-week follow-­up and was as effective as spaced therapy (10 sessions over 8 weeks). In addition, there were no significant differences between spaced therapy and PCT in reducing PTSD symptom severity. Unfortunately, the reductions in PTSD symptom severity with all treatments examined in this study were relatively modest. These findings suggest that we still have a long way to go in developing effective psychotherapies for combat-­related PTSD, especially in active-­duty military personnel (Foa et al., 2018).

Propranolol and Trauma Memories Until recently, the general consensus was that traumatic memories would persist indefinitely once memory consolidation had occurred. Exposure therapy is designed to inhibit the expression of traumatic memories through a process of extinction of the traumatic memory trace. Exposure therapy does not eliminate the traumatic memory trace; it only inhibits it. From a therapeutic perspective, exposure therapy is limited in its long-term effectiveness in that the traumatic memory trace may eventually return and lead to adverse outcomes among individuals diagnosed with PTSD (Bouton, 2014). There is an extensive foundation of research findings on pharmacological blockade of memory reconsolidation in laboratory mice and rats to inform the design of experiments with PTSD patients. Prior studies with laboratory animals suggest that disrupting reconsolidation pharmacologically may actually weaken or eliminate the fear-­induced memory trace. Building on these basic research findings, Brunet et al. (2018) examined the efficacy of trauma memory reactivation following administration of propranolol, a noradrenergic beta-­receptor antagonist that readily crosses the blood–brain barrier, as a putative reconsolidation blocker, in reducing symptoms of PTSD. The experimental

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design involved a 6-week, double-­blind, placebo-­controlled, randomized clinical trial in 60 adults diagnosed with long-­standing symptoms of PTSD. The drug (0.67 mg/kg of short-­acting propranolol plus 1.0 mg/kg of sustained release propranolol) or placebo was administered 90 minutes before a brief memory reactivation session, once a week for 6 consecutive weeks. PTSD symptoms were quantified with the Clinician-­Administered PTSD Scale (CAPS) and the patient-­rated PTSD Checklist—­Specific (PCL-S) scale. The two groups had similar pretreatment CAPS scores. At the posttreatment assessment, the CAPS scores had decreased in both groups, but the decreases were significantly greater in the propranolol group compared to the placebo group (p < .04). A similar pattern of results was found for the PCL-S scores. The two groups had similar pretreatment PCL-S scores, but the posttreatment decreases in PCL-S scores were significantly greater in the propranolol group compared to the placebo group (p < .001). Administration of propranolol prior to reactivation of a traumatic memory may provide a novel and highly effective treatment for PTSD (Brunet et al., 2018). These early findings must be replicated with a larger pool of participants, and there is a need to establish the long-term benefits of this therapeutic strategy with diverse populations of PTSD patients. An appealing aspect of this study is that propranolol is a medication utilized extensively for the treatment of hypertension, elevated heart rates, cardiac arrhythmias, and migraines, and its safety is well established (Srinivasan, 2019). The effect sizes obtained for pre-­reactivation propranolol reported in this study compare favorably to those obtained with the best current evidence-­based treatments for PTSD, including cognitive-­behavioral therapy and administration of selective serotonin reuptake inhibitors.

Transcutaneous Vagus Nerve Stimulation As summarized above, PTSD is a highly disabling condition associated with alterations in multiple neurobiological systems, including increases in inflammation and activity of the sympathetic nervous system that contribute in part to maintenance of symptoms. Current treatment options, including drugs and psychotherapy, have limited efficacy. Previous studies have shown that transcutaneous vagus nerve stimulation (VNS), a form of neuromodulation, blocks inflammatory and sympathetic nervous system responses to stressful stimulation and enhances cognitive function. Motivated by these promising reports relating to VNS, Bremner et al. (2021b) conducted a pilot study to determine the effects of VNS on PTSD symptoms and inflammatory responses to a personal trauma narrative. VNS was delivered for 2 minutes with handheld units (Gamma Core, Basking Ridge, New Jersey) that targeted the vagus nerve within the carotid sheath on the side of the neck. Sixteen patients with PTSD following exposure to a variety of traumatic experiences were randomized to active VNS (N = 8) or sham (N = 8) stimulation in conjunction with exposure to audio recordings of personal trauma narratives. Immediately after the audio recordings, active or sham VNS was initiated, and blood samples were collected for measurement of IL-6 and other biomarkers of inflammation. Patients then self-­administered active or sham VNS twice daily for 3 months. PTSD symptoms were measured with the PTSD Checklist (PCL) and the Clinician-­Administered PTSD Scale (CAPS), clinical improvement with the Clinical Global Index (CGI), and anxiety with the Hamilton Anxiety Scale (Ham-A) at baseline and at 1-month intervals, followed by a repeat of measurement of biomarkers



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after exposure to a traumatic narrative. After 3 months, patients self-­administered twice daily active or sham VNS for an additional 3 months, followed by assessment with the CGI. Listening to a recorded personal traumatic narrative increased IL-6 in sham VNS PTSD patients, an effect that was blocked by active VNS (p < .05). Active VNS treatment for 3 months resulted in a 31% greater reduction in PTSD symptoms as measured by the PCL (p < .02) and hyperarousal symptoms and somatic anxiety measured with the Ham-A compared to sham VNS (p < .05). IL-6 increased from baseline in patients who received sham VNS but not in patients who received active VNS. Active VNS also resulted in improvements measured with the CGI compared to the sham treatment group (p < .05). These preliminary results indicate that VNS reduced inflammatory responses to the stress of a personal trauma narrative, which may explain in part the beneficial effects of VNS on PTSD symptoms. This team of investigators hypothesized that VNS affected peripheral sympathetic activity as well as central noradrenergic neurons in the locus coeruleus (Bremner et al., 2021b). Obviously, these results must be replicated with much larger sample sizes and longer follow-­up periods to confirm the permanence of the VNS protocol. Patient-­administered VNS has several appealing aspects. First, it has none of the undesirable side effects that often occur with the standard drugs used to treat PTSD, such as nausea, headaches, drowsiness, agitation, and dizziness. Second, VNS itself was well tolerated, with minimal complaints from patients regarding side effects during and immediately after nerve stimulation. Finally, this therapy can be delivered by individual patients with minimal oversight or direct contact with a physician or other health care provider. This is a powerful benefit given the significant number of individuals with recurring symptoms of PTSD and the difficulty many patients experience in accessing health professionals who specialize in the treatment of PTSD.

CONCLUSIONS Traumatic experiences have always been part of the human condition. Much of the focus leading up to the 1980 revision of the DSM was on trauma exposure in combat veterans, but a hidden benefit of adding PTSD as a diagnostic category was that it opened up clinical services to those traumatized by assaults, rape, natural disasters, and automobile accidents. Unfortunately, psychotherapies and drug treatments available for individuals diagnosed with PTSD are often not highly effective, and there have been few significant advances in treatment over the past two decades. The study of memory processes in laboratory animals and in humans has provided new avenues for studying the underlying pathophysiology of PTSD (McCarty, 2020). As summarized in this chapter, targeting the traumatic memory trace for elimination may provide a novel approach to treatment for patients with PTSD. Use of patient-­ administered VNS holds significant promise for the future. In Chapter 13, we will discuss why some individuals are resilient to the effects of traumatic experiences, and we will consider whether resilience can be increased in susceptible individuals through targeted interventions.

CHAPTER 6

Stress and Depression

O

ver the course of his distinguished career as a physician– scientist at the National Institute of Mental Health in Bethesda, Maryland, Philip Gold examined the underlying mechanisms linking stress responses and mood disorders. He also recognized the far-reaching influences of major depressive disorder on overall health status. His appreciation for the devastating impact of depression on individuals is captured in the following quote (Gold, 2015, p. 45): Depression affects ways of feeling and thinking that intrude upon the features that help define our humanity. It is a neurodegenerative disease that affects key sites of the prefrontal cortex, limbic system and multiple cortical areas. In its severe manifestations, it is like a cancer of the self that impairs our self-respect, sense of well-being and capacity to think clearly. It “metastasizes” from the brain to the periphery to influence the functional integrity of the HPA axis and the SNS system, and is associated with a pro-thrombotic state, inflammation and insulin resistance. Taken together, these phenomena contribute to multiple systemic pathologies.

Gold’s quote sets the tone for this chapter on depression and the many connections that we will explore in later chapters between depression and various chronic medical conditions, including cardiovascular disease, diabetes, and cancer.

OVERVIEW OF MAJOR DEPRESSIVE DISORDER Hippocrates (460–377 B.C.E.) thought melancholia was caused by an abundance of one of the four humors, black bile. The treatment of choice at that time consisted of purging and removal of blood to reduce the negative impact of black bile. Today, major depressive disorder (MDD) is viewed as a debilitating psychiatric disorder characterized by one or more bouts of depression lasting at least 2 weeks and resulting in a depressed mood state, lack of interest in pleasurable activities, reduced energy levels, sleep disturbance, 110



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decreased ability to concentrate, feelings of worthlessness, and recurrent thoughts of death and possibly suicidal ideation (see Table 6.1). Some or all of these symptoms cause great distress and result in impairments in normal functioning at home, at school, and in the workplace based on DSM-5-TR (American Psychiatric Association, 2022). Based on the symptom checklist in DSM-5-TR, 681 combinations of symptoms satisfy the DSM criteria for a diagnosis of MDD. This observation alone underscores the heterogeneity of this disorder and its associated subtypes (psychotic, melancholic, seasonal, atypical, postpartum, etc.). Add to this extreme heterogeneity the fact that some depressive symptoms overlap with other psychiatric disorders, including anxiety disorders, schizophrenia, and bipolar disorder (Otte et al., 2016).

GENETIC ASPECTS OF DEPRESSION MDD is moderately heritable (∼40%), and there is also evidence that epigenetic alterations play an important role in the pathophysiology of the disorder. Females are almost twice as likely to be diagnosed with MDD as males. The lifetime prevalence of MDD is approximately 16%, and it occurs across racial and demographic groups. The median age of onset of a first depressive episode is in the early 20s, and the peak risk period extends into the 40s. However, depression is also a significant problem in adolescence, especially in girls around the time of puberty. A typical depressive episode in an adolescent can last approximately 6 months and have a decidedly negative effect on academic performance and social functioning. An additional concern regarding depression in adolescents is the significant risk for suicide (Miller & Campo, 2021). The average duration of a depressive episode in adults is 13–30 months based on studies with population-­ based samples, and more than 70% of individuals recover within one year. A strong case has been made that life stressors, including those experienced in early life, play a critical role in the onset and recurrence of symptoms. In addition, alterations in the regulation of the HPA axis have been a focus of research in depression over the past four decades (Otte et al., 2016; Thapar, Collishaw, Pine, & Thapar, 2012). Howard et al. (2019) combined data from three large-scale genome-­wide association studies (GWAS) of depression to increase statistical power in their efforts to identify risk gene variants for MDD. They reported 102 independent gene variants, 269 genes, and 15 gene sets associated with depression, including genes and gene pathways involved in synaptic structure and neurotransmission. Supporting evidence of the importance of prefrontal brain regions in depression was provided by an enrichment analysis. In an independent replication sample of more than 1.5 million people, 87 of the original 102 associated gene variants were significant for an effect on MDD following correction for multiple comparisons. Surprisingly, none of the risk variants was associated with serotonin neurons or their postsynaptic receptors, given that components of serotonergic signaling have been targets for MDD-­related drug development for several decades. More recently, Levey et al. (2021) conducted a meta-­analysis of MDD by combining GWAS data from the Million Veteran Program in the United States, 23andMe, the UK Biobank, and FinnGen, a public–­private partnership involving residents of Finland. The combined sample included more than 1.2 million participants, of whom 366,434 were individuals diagnosed with MDD. Their analyses identified 223 independently significant single-­nucleotide polymorphisms (SNPs) contained within 178 risk loci. In

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TABLE 6.1.  Diagnosis of MDD A. Five (or more) of the following symptoms have been present during the same 2-week period and represent a change from previous functioning; at least one of the symptoms is either (1) depressed mood or (2) loss of interest or pleasure. Note: Do not include symptoms that are clearly attributable to another medical condition. 1. Depressed mood most of the day, nearly every day, as indicated by either subjective report (e.g., feels sad, empty, hopeless) or observation made by others (e.g., appears tearful). (Note: In children and adolescents, can be irritable mood.) 2. Markedly diminished interest or pleasure in all, or almost all, activities most of the day, nearly every day (as indicated by either subjective account or observation). 3. Significant weight loss when not dieting or weight gain (e.g., a change of more than 5% of body weight in a month), or decrease or increase in appetite nearly every day. (Note: In children, consider failure to make expected weight gain.) 4. Insomnia or hypersomnia nearly every day. 5. Psychomotor agitation or retardation nearly every day (observable by others, not merely subjective feelings of restlessness or being slowed down). 6. Fatigue or loss of energy nearly every day. 7. Feelings of worthlessness or excessive or inappropriate guilt (which may be delusional) nearly every day (not merely self-reproach or guilt about being sick). 8. Diminished ability to think or concentrate, or indecisiveness, nearly every day (either by subjective account or as observed by others). 9. Recurrent thoughts of death (not just fear of dying), recurrent suicidal ideation without a specific plan, or a suicide attempt or a specific plan for committing suicide. B. The symptoms cause clinically significant distress or impairment in social, occupational, or other important areas of functioning. C. The episode is not attributable to the physiological effects of a substance or another medical condition. Note: Criteria A–C represent a major depressive episode. Note: Responses to a significant loss (e.g., bereavement, financial ruin, losses from a natural disaster, a serious medical illness or disability) may include the feelings of intense sadness, rumination about the loss, insomnia, poor appetite, and weight loss noted in Criterion A, which may resemble a depressive episode. Although such symptoms may be understandable or considered appropriate to the loss, the presence of a major depressive episode in addition to the normal response to a significant loss should also be carefully considered. This decision inevitably requires the exercise of clinical judgment based on the individual’s history and the cultural norms for the expression of distress in the context of loss.    In distinguishing grief from a major depressive episode (MDE), it is useful to consider that in grief the predominant affect is feelings of emptiness and loss, while in an MDE it is persistent depressed mood and the inability to anticipate happiness or pleasure. The dysphoria in grief is likely to decrease in intensity over days to weeks and occurs in waves, the so-called pangs of grief. These waves tend to be associated with thoughts or reminders of the deceased. The depressed mood of an MDE is more persistent and not tied to specific thoughts or preoccupations. The pain of grief may be accompanied by positive emotions and humor that are uncharacteristic of the pervasive unhappiness and misery characteristic of an MDE. The thought content associated with grief generally features a preoccupation with thoughts and memories of the deceased, rather than the self-critical or pessimistic ruminations seen in an MDE. In grief, self-esteem is generally preserved, whereas in an MDE feelings of worthlessness and self-loathing are common. If self-derogatory ideation is present in grief, it typically involves perceived failings vis-à-vis the deceased (e.g., not visiting frequently enough, not telling the deceased how much he or she was loved). If a bereaved individual thinks about death and dying, such thoughts are generally focused on the deceased and possibly about “joining” the deceased, whereas

(continued)



Stress and Depression 113 TABLE 6.1. (continued) in an MDE such thoughts are focused on ending one’s own life because of feeling worthless, undeserving of life, or unable to cope with the pain of depression.

D. At least one major depressive episode is not better explained by schizoaffective disorder and is not superimposed on schizophrenia, schizophreniform disorder, delusional disorder, or other specified and unspecified schizophrenia spectrum and other psychotic disorders. E. There has never been a manic episode or a hypomanic episode. Note: This exclusion does not apply if all of the manic-like or hypomanic-like episodes are substance-induced or are attributable to the physiological effects of another medical condition. Note. Reprinted with permission from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision. Copyright © 2022 American Psychiatric Association. All Rights Reserved.

a further extension of these findings, an independent sample provided by 23andMe that was nonoverlapping with the previous sample consisted of more than 1.3 million participants (including 455,350 individuals diagnosed with MDD). Analysis of these data showed that 99% of the 211 variants tested revealed consistent direction of effects between the two studies, with only two variants discordant between the two studies. Several risk variants were highlighted in this study for their association with potential genes involved in the pathogenesis of MDD. They included genes for neuronal growth regulator 1 (NEGR1) in the hypothalamus and dopamine D2 receptor (DRD2) in the nucleus accumbens. Through use of gene- and drug-based enrichment analyses, several targets for drug development were identified through overlapping biological properties, including glutamatergic function and estrogen action. Once again, though, there was an absence of risk variants associated with serotonergic signaling based on this GWAS meta-­analysis (Levey et al., 2021). This and related studies show that depression is a multifactorial disease and that each of the 200+ risk gene variants identified to date contributes a small amount to the overall variance associated with a depressive phenotype. That still leaves a significant role for environmental factors, and principal among them are stressful stimuli. More on the connection between stress and depression will be presented later in this chapter.

DEPRESSION AND GLOBAL BURDEN OF DISEASE MDD is a significant contributor to the global burden of disease, based on estimates of disability-­adjusted life years (DALYs). This effect is magnified given that MDD is also associated with higher risks of developing other chronic medical conditions, including type 2 diabetes, cardiovascular disease, arthritis, asthma, respiratory diseases, chronic pain, and obesity. Patients with MDD are also 20 times more likely to die from suicide than nondepressed individuals in the general population. Liu, He, et al. (2020) tracked the changes in age-­specific incidence rates for depression from 1990 to 2017 using data from the Global Burden of Disease database. The number of incident cases of MDD in 195 countries and regions increased from 162 million cases in 1990 to 241 million cases in 2017. Age-­specific rates of depression were highest in Lesotho, Morocco, and Greenland and lowest in Myanmar, Indonesia, and the Philippines. The most significant increases in incident cases of depression from 1990

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to 2017 occurred in Qatar, United Arab Emirates, and Equatorial Guinea, while Latvia, Bosnia and Herzegovena, and Georgia had the most significant decreases in incident cases. Although there were differences across regions of the world in the frequency of incident cases of depression, clearly depression is a major public health problem in every country where data are available. This challenge must be addressed through effective public health policies that increase access to care and focus on evidence-­based prevention strategies (Lui, He, et al., 2020). Rates of depression are higher in high-­income than low-­income countries. Some of these differences may be explained by variations in cross-­national patterns of access to care and thresholds for diagnosing depression. However, at a superficial level, one would expect that rates of depression would be lower in high-­income countries because their stress levels should be lower than in developing countries, given the greater availability of material resources. This apparent paradox may be explained by a greater magnitude of income inequality in high-­income countries, which results in higher levels of stress and depression in those who are most vulnerable. It has even been suggested that depression is a disease of affluence—­or lack thereof (Koplewicz, Gurian, & ­Williams, 2009). Greenberg et al. (2021) estimated the economic costs associated with major depressive disorder using data from 2010 and 2018. Estimates of costs associated with depression included direct costs associated with provision of medical care based on interrogation of an administrative claims database, suicide-­related costs, and workplace costs that included the negative impact of absenteeism and reduced productivity while at work. Using this approach, we see that the total economic burden of MDD increased from $237 billion in 2010 to $326 billion in 2018, a 38% increase in just 8 years. Approximately 40% of this rise in costs reflected an increase in the number of individuals diagnosed with MDD, while 60% was tied to the increased costs associated with MDD, especially in the costs incurred by employers. The treatment rate of individuals with MDD remained relatively stable from 2010 to 2018 at approximately 56% (­Greenberg et al., 2021). In spite of the worldwide negative impact of MDD on human health, the current outlook for treatment options for depression is anything but encouraging (Kessler, 2012; Wong & Licinio, 2001). Data from the United States indicate that the percentage of people with depression who receive treatment is troublingly low, and this figure may be even lower in developing countries. Up to 50% of patients diagnosed with MDD do not respond favorably to currently available psychological and pharmacological interventions. In addition, the approach taken by psychiatrists to develop treatment plans for many patients remains one of trial-and-error. Even though more than 40 years have passed since the introduction of the first antidepressant drugs, we still do not have reliable biomarkers to guide drug selection and to track treatment response, and many patients develop resistance to medications over time (Akil et al., 2018).

IS DEPRESSION AN ADAPTIVE BEHAVIORAL RESPONSE? Given the high incidence of MDD, it seems logical to ask why a mental disorder that has such a life-­altering impact on individuals and their loved ones could persist in the population. Shouldn’t there be strong selection pressure against the genetic contributions



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related to risks associated with MDD? While depression is only modestly heritable (∼40%), there is substantial evidence that other factors also contribute to the etiology of this disorder, including environmental stressors acting upon a susceptible genotype as well as epigenetic changes in DNA or histone proteins. Could these biological and environmental contributions to MDD be viewed through an evolutionary lens in such a way that the resulting genetic and behavioral characteristics might confer an adaptive advantage under specific conditions? In dealing with the possible adaptive advantages of depression, most evolutionary analyses begin by separating out depressive mood states from MDD. However, there is no clear distinction between the transition from a low mood state to MDD, a difficulty that further complicates such an approach (Hagen, 2011; Nesse, 2000). In taking on this challenge, we are also delving deeply into the realm of “thought experiments” as many of these hypotheses regarding the adaptive advantages of a depressed mood state cannot be tested directly, only bolstered by indirect evidence. Given the high prevalence of risk genes for depression (Wray et al., 2018), it would appear that these genes confer some net benefits to humans. Such benefits could result from two different processes. First, the depressive phenotype might have conveyed adaptive advantages in spite of the obvious costs to the depressed individual. Second, risk genes for depression may have conferred adaptive advantages through pleiotropic effects on other advantageous traits that outweighed the disadvantages of a depressed mood state.

THEORIES OF DEPRESSION Socially Based Theories Several theories relating to the adaptive advantages of depression-­like behaviors have been advanced and often revolve around the costs and benefits of social interactions (Hagen, 2011). The social competition hypothesis, for example, emphasizes submission and posits that an individual will display submissive behaviors toward higher-­ranking individuals. In so doing, the individual will adopt a sense of powerlessness, thereby inhibiting further aggression originating from those of higher rank. Such changes would be expected to have a favorable impact on group cohesion. The social risk hypothesis argues that those individuals who are not adept at forming and maintaining social relationships are less likely to engage in social risk taking. Such individuals may have perceived themselves as having low social value, are sensitive to social threats, and are expected to experience failure in their social interactions. The psychic pain hypothesis suggests that sadness and generally low affect are adaptive responses to conditions of social adversity. The situation-­symptom congruence hypothesis advances a more finely tuned system of affective responses to a variety of challenges. For example, sadness and crying often occur following the loss of a loved one, whereas pessimism and fatigue are typical responses following failure to achieve a major goal or exposure to severe life stressors or hardships. Watson and Andrews (2002) have proposed the social navigation hypothesis to account for the adaptive significance of behaviors characteristic of depression. In their elegant description and analysis, they presented two complementary functions of depression-­related behaviors that address difficulties in social relations. The first function, involving rumination, relates to the cognitive changes associated with depression that permit greater attention to analyzing complex social problems and developing

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strategies to resolve them. The second function, involving social motivation, capitalizes on the loss of pleasurable activities and the fatigue and relative inactivity of the depressed individual to motivate social partners to become more engaged and to extend assistance to the affected individual.

The Positive Side of Rumination Somewhat later, Andrews and Thomson (2009) proposed the analytical rumination hypothesis, which greatly expanded the rumination function from the social navigation hypothesis described above. The analytical rumination hypothesis views some of the symptoms associated with MDD as an adaptive response to deal with complex problems, often associated with social relationships. The loss of interest in most daily activities affords an individual with a depressed mood state the luxury of focused and largely uninterrupted attention to develop strategies to solve complex problems. There is an element of rumination, but the rumination is focused and devoted to finding a solution to a particular problem, while other activities, including pleasurable ones, are put aside.

Focus on the Immune System Miller and Raison (2016) also offered an evolutionary perspective as part of their discussions of stress, the immune system, and depression. Consider the following observations on physiological responses to a laboratory stressor, the Trier Social Stress Test, as described in Chapter 3 (Allen et al., 2014). An individual is brought into a laboratory and asked to deliver a speech to a highly critical panel of three experts. Not surprisingly, as this person prepares and then delivers the speech, a classic fight-or-­flight response is mounted, with increases in blood pressure and heart rate and secretion of epinephrine and cortisol into the circulation. But something surprising also occurs—­exposure to this relatively benign laboratory stressor also activates white blood cells and leads to increases in pro-­inflammatory cytokines, including IL-1b, IL-6, and TNF-a. Why would immune activation occur in the absence of a pathogen or an injury? Presumably, the only thing at stake in experiencing this laboratory stressor is a threat to one’s fragile ego. And of critical importance to the theme of this chapter is the question of why individuals at high risk of developing depression would have a greater pro-­inflammatory response to laboratory stressors compared to low-risk individuals. In their analysis of these issues, Miller and Raison (2016) argued that modern humans have continued to hold a genomic bias toward inflammation that may be traced back to our ancient ancestors, who evolved in a pathogen-­rich environment and were constantly confronting risks of severe wounding and associated infections from predators or human competitors. When dealing with an infection, early humans developed a constellation of “sickness behaviors” that enhanced survival through strategic alterations in ongoing patterns of behavior. These behavioral changes included conservation of energy through avoidance of social interactions and pleasurable activities, as well as hypervigilance to reduce the chance of a subsequent confrontation and exposure to further risk of infection. Of critical importance to our consideration is that these sickness behaviors bear a striking resemblance to modern-­day symptoms of depression. In the end, evolution favors those with greater levels of reproductive success through the contribution of genes to subsequent generations. Slavich and Irwin (2014)



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have advanced the social signal transduction theory of depression to support the notion that evolution favored those individuals who marshaled preemptive pro-­inflammatory responses to stressors, even if the response was occasionally a false alarm. Unfortunately, modern humans live for the most part under sanitary conditions, and the same pro-­inflammatory processes that served early humans so well have now turned into a decided liability.

Summary These and other theories of the possible adaptive aspects of MDD will not halt the search for new and more effective antidepressants, nor should they. However, these theories do inform efforts by therapists working with patients with MDD to look more broadly at the potential benefits of some symptoms associated with MDD in their efforts to personalize care.

STRESS AND DEPRESSION Studies of stressful life events and depression have a long history. One of the first well-­controlled studies was conducted by Paykel et al. (1969), using a sample of 185 depressed patients and a group of matched controls. Their findings indicated that depressed patients experienced approximately three times as many stressful life events (e.g., increase in marital discord, marital separation, serious illness of the patient or a family member, death of a family member) in the 6 months prior to onset of a depressive episode compared to controls over a comparable time period. This early study set the stage for experiments on the etiologic significance of stressful stimulation in the pathophysiology of MDD. Since Paykel et al.’s early report (1969), it has become clear that the relationship between stress and depression is much more complex than previously thought. The methods for measuring and characterizing life stressors have evolved to meet these challenges (Kessler, 1997). Important advances have been made in interview-­based, objective measures of stressful life events that quantify frequency of occurrence and intensity. Attention has also been given to stressors that are chronic and unremitting and associated with risk for a depressive episode. Chronic stressors include marital discord, financial insecurity, and adverse working conditions. Studies of chronic stress relate to the concept of allostatic load and its impact of depression and other chronic medical conditions (Hammen, 2015; McEwen, 1998).

Theories of Stress and Depression The Diathesis–Stress Theory Several theories relating to the etiology of MDD have been advanced over the years. I will limit this discussion to a subset of these theories. The diathesis–­stress theory of depression has evolved from conceptualizations of the etiology of schizophrenia, and emphasizes a process whereby stressful stimulation activates or interacts with a specific diathesis (e.g., vulnerability), resulting in the transformation of a predisposition into the

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onset of a depressive episode (Monroe & Simons, 1991). The diathesis could be cognitive (Lewinsohn, Joiner, & Rohde, 2001) or genetic (Caspi et al., 2003). Consistent with the diathesis–­stress model, a seminal report by Caspi et al. (2003) was the first to demonstrate that a polymorphism in the promoter region of the serotonin transporter (5-HTT) gene could moderate the effects of major life stressors on depressive symptoms, MDD, and suicide attempts. Using a large representative birth cohort in New Zealand (Dunedin Multidisciplinary Health and Development Study), these investigators reported that individuals with one or two short (s) alleles in the promoter region of the 5-HTTLPR gene were affected to a greater extent by exposure to major life stressors than individuals with two long (l) alleles. The s allele is less efficient transcriptionally compared to the l allele. Major life stressors included child maltreatment and financial, health, relationship, and housing issues. These basic findings of a gene × environment effect on depression have been replicated by several groups (e.g., Kendler, Kuhn, Vittum, Prescott, & Riley, 2005; Vrshek-­ Schallhorn et al., 2014) and confirmed by a major meta-­analysis of 54 studies published through November 2009 (Karg, Burmeister, Shedden, & Sen, 2011). In addition, Gotlib, Joormann, Minor, and Hallmayer (2008) provided evidence that girls 9–14 years old with two copies of the s allele had significantly greater levels of cortisol in saliva immediately and up to 45 minutes after exposure to laboratory stressors (serial subtraction followed by a stressful interview for a total of 15 minutes) compared to girls with at least one l allele, providing a potential mechanism to explain the increased susceptibility to depression in individuals homozygous for the s allele. A subsequent meta-­ analysis covering the literature published through October 2011 confirmed a significant association between 5-HTTLPR genotype and cortisol reactivity to acute psychosocial stress, with levels of reactivity significantly greater in individuals homozygous for the s allele compared to those homozygous for the l allele or heterozygotes (Miller, Wankerl, Stalder, ­Kirschbaum, & Alexander, 2013). To address the inconsistencies in the literature, Culverhouse et al. (2018) conducted a collaborative meta-­analysis of 31 datasets that contained more than 38,000 participants of European ancestry who were genotyped for the 5-HTTLPR and evaluated for depression and childhood maltreatment as well as other stressful life events. This meta-­ analytic study did not confirm a gene x environment interaction or a main effect of the s allele on occurrence of depression. However, there were significant main effects for sex and for the impact of stressors on depression. Given the findings noted above by Caspi et al. (2003), Culverhouse et al. (2018) concluded that if an interaction effect does occur, it is not generalizable from the Dunedin dataset, is of modest effect size, and only occurs in limited situations.

Kindling and Depression Another prominent theory of MDD is the kindling hypothesis originally presented by Post (1992). In his landmark paper, Post developed a framework to explain recurring episodes of depression that linked sensitization to repeated exposure to stressful stimulation, with persistent molecular changes in stress-­sensitive brain circuits. He subsequently expanded his theory to include epigenetic changes that would have profound influences on regulation of gene activity (Post, 2016). Monroe and Harkness (2005) evaluated the kindling hypothesis from the perspective of life events stress research, focusing particular attention on whether recurring



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episodes of depression become independent of input from life stressors or sensitized to them. In a test of the kindling hypothesis, Kendler, Thornton, and Gardner (2000, 2001) examined the relationship between stressful life events and occurrences of depression in a population-­based study of female twins. In the first Kendler et al. study (2000), the results indicated that with each new episode of depression, the association between stressful life events and the onset of depression decreased. This effect was especially strong for up to nine episodes of depression and confirmed the kindling hypothesis of Post (1992). Beyond nine episodes of depression, there was no evidence of further sensitization to stressful life events. In the second Kendler et al. study (2001), these investigators considered whether enhanced genetic risk increased the rate of kindling or whether it rendered individuals “pre-­kindled.” Their results clearly favored the pre-­kindled model, such that those individuals with the highest genetic risk demonstrated a weak association between stressful life events and the first episode of major depression compared to individuals with low genetic risk. With subsequent episodes of depression, the relationship between stressful life events and onset of depression changed little in those at high genetic risk, but decreased markedly in those at low genetic risk (Kendler et al., 2001).

The Cognitive Model The most comprehensive theory of depression by far is the cognitive model advanced by Beck and Bredemeier (2016). This model, which has been updated and expanded several times over the past 40 years, argues that depression results from a tendency to perceive events in a negative fashion and to evince exaggerated biological responses to stressful experiences. These disruptions in cognitive processing and regulation of stress responsiveness are regulated by specific brain circuits that render an individual susceptible to experiences of loss, such as those related to intimate relationships, membership in a group, or valued resources. The classic symptoms of depression, including lack of pleasure derived from such activities as eating, drinking, and social interactions as well as loss of energy to engage in daily activities, are manifestations of these disruptions in cognitive processing and regulation of stress-­responsive biological systems (autonomic, endocrine, and immune). An attractive feature of the expanded cognitive theory is its incorporation of an evolutionary framework for interpreting the potential survival value of the symptoms of depression. Beck and Bredemeier (2016) posit that “the perceived loss of an investment in a vital resource” leads to activation of the depression program, resulting in behavioral and physiological adaptations designed to reduce energy expenditures as a means of compensating in part for the loss. They argue that efforts to reduce energy expenditures in the face of a loss of a vital resource may well have been adaptive in the evolutionary history of our species, but they clearly are not in the present times.

Integrating Cognitive and Biological Contributions to Depression Building upon the work of Beck and Bredemeier (2016) and others, LeMoult (2020) proposed a new model of stress and depression that brings together cognitive and biological perspectives (Figure 6.1). Cognitively oriented studies of depression have shown that at-risk individuals think about their stressful life experiences in ways that result in depressed mood states and an increased risk for a depressive episode. In addition,

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FIGURE 6.1.  Exposure to psychosocial stressors increases the risk of developing symptoms of depression, especially in high-risk individuals. Stressors activate central nervous system (CNS) stress circuits and cognitive systems involved in appraisal processes, which interact to further affect depressive symptoms. HPA, hypothalamic–­pituitary–­adrenocortical; SNS, sympathetic nervous system.

biological responses to stressors also play a critical role in the onset of depressive episodes. Even though cognitive and biological responses to stressors have developed largely from separate fields of research and have been shown to contribute independently to the risk for MDD, there is also evidence for reciprocal interactions between the two types of responses. LeMoult (2020) discussed the challenges of developing and testing a model of stress and depression that encompasses cognitive and biological perspectives. First, she indicated a pressing need for longitudinal studies to delineate the time course of biological and cognitive changes that occur between stressor exposure and the onset of MDD. Second, treatment outcome studies could reveal reciprocal interactions between cognitive and biological stress reactivity and their effects on symptoms of depression. Third, it would be of great interest to understand how early life stressors impact cognitive and biological stress reactivity and the onset of depression in adolescence and adulthood. Finally, results of the studies outlined above should improve the delivery of targeted and personalized therapies for the treatment of MDD and inform the development of interventions to prevent the development of MDD (LeMoult, 2020).

TWIN STUDIES AND DEPRESSION A critical study that established a causal relationship between stressful life events and the onset of major depressive disorder was conducted by Kendler, Karkowski, and Prescott (1999), based on a 1-year study of female twins from the Virginia Twin Registry. This



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research addressed the thorny issue of the degree to which genetic and familial factors influenced exposure to stressful life experiences. That is, some individuals tend to favor environments or situations that lead them to experience stressful events, which may increase the risk of developing depression (Kendler, Neale, Kessler, Health, & Eaves, 1993). Ratings of 15 classes of stressful life events and the onset of MDD over a 1-year period were noted by the team of researchers. Participants in this study were 1,898 female twins (monozygotic and dizygotic), and the results included more than 24,000 person-­months of exposure and 316 confirmed episodes of depression. Using in-­person and telephone interviews, researchers asked first about 11 types of personal stressful experiences (e.g., assault, breakup of a relationship, financial difficulties) and 4 types of network stressors (e.g., difficulty getting along with a person, death of a person in one’s network) that occurred in a specific month during the previous year. Questions regarding specific symptoms associated with MDD were presented only after information on stressful life events was collected to avoid any undue influence of discussing depressive symptoms on recollection of specific life stressors. Across all categories of stressful life events, the occurrence of a stressor was significantly associated with the onset of a depressive episode within the next 1–2 months (p < .0001). This relationship was highly significant and held true for monozygotic as well as dizygotic twin pairs. In addition, dependent life stressors were more strongly associated with a depressive episode than independent life stressors. However, the occurrence of independent life events also strongly predicted the onset of a depressive episode (p < .0001). Of the 15 types of stressful life events, 11 were associated with the onset of a depressive episode in the same month and 2 others were associated with a depressive episode in the following months. There was no evidence to suggest that an episode of depression precipitated the occurrence of a stressful life event. These results provided conclusive evidence that stressful life events were significantly associated with the onset of depression. However, approximately one-third of the association between stressful life events and the onset of major depression was noncausal and reflects the fact that individuals at risk of major depression tend to select high-risk environments. The remaining two-­thirds of the association was clearly connected to independent stressful life experiences (Kendler et al., 1999). A remarkably consistent finding over the years has been the higher incidence of major depression in women than in men, as noted above. Might this sex difference in the prevalence of depression result from greater sensitivity to stressful life events and/ or more frequent exposure to stressful life events? Using a population-­based sample of female–­female, male–male, and female–­male twin pairs, Kendler, Thornton, and Prescott (2001) found no evidence that females and males differed in their frequency of exposure or in their sensitivity to stressful life events. However, women did report higher rates of exposure to some stressful life events (e.g., difficulties with housing, loss of a confidante, challenges with individuals in their proximal network, illness of individuals in their distal network), while men reported higher rates of exposure to other life stressors (e.g., job loss, legal problems, robbery, difficulties at work). Silberg et al. (1999) followed a sample of male and female twin pairs from childhood into adolescence to examine genetic and stressful environmental contributions to the onset of depression. There was a significant increase in depression among adolescent girls compared to boys. Stressful life events were evident for boys and girls, with a greater impact evident in girls. Genetic factors were dominant in girls, such that some

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girls in the study experienced an episode of depression in the absence of a significant stressful life event. Kendler and his colleagues also explored developmental pathways to the onset of depression in women and in men using structural equation modeling. Using a sample of female twins, Kendler, Gardner, and Prescott (2002) reported that three major pathways led to depression, one of which was psychosocial adversity. This pathway included childhood sexual abuse, parental loss, family disruptions, traumatic experiences, marital difficulties, and stressful life events. In their study of male twins, Kendler, Gardner, and Prescott (2006) also noted three major pathways to depression, one of which included adversity and interpersonal difficulties (e.g., childhood sexual abuse, loss of a parent, traumatic experiences, and stressful life events). In both men and women, genetic risk contributed to each of the three sex-­specific pathways.

STRESS FROM INFANCY THROUGH ADOLESCENCE Early Life Adversity and Depression Data from the National Survey of Health and Development (encompassing the March 3–9, 1946, British birth cohort) were studied to explore the relationship between stress and later development of depression (Colman et al., 2014). The findings from this study pointed to direct and indirect effects of early life adversity and later life stressors on depression. In addition, there was evidence of a cumulative impact of stressful experiences throughout development on the onset of MDD in adulthood. The impact of childhood adversity prior to age 17 on later development of mental disorders was studied using the National Epidemiological Survey of Alcohol and Related Conditions (McLaughlin, Conron, Koenen, & Gilman, 2010). Childhood adversity included instances of emotional and physical abuse, violence within the family, neglect, endangerment, sexual abuse, mental illness in the family, and incarceration of a parent. Stressful life events over the preceding year were associated with a significant increase in risk for depression and other disorders. However, the risk for depression in women and men was approximately two times greater in those individuals with three or more experiences of adversity during childhood compared to those without experiences of childhood adversity. Further, those individuals who experienced childhood adversity tended to perceive stressors in adulthood as more overwhelming and unmanageable. These results were presented as evidence that childhood adversities sensitize individuals to the deleterious impact of exposure to stressful life events in adulthood. In addition, the authors suggested that childhood adversities may serve as a broad-based diathesis for several categories of psychopathology over the lifespan (McLaughlin et al., 2010). Finally, Heim and Bender (2012) have pointed to the existence of sensitive periods during postnatal development when early life stressors exert their greatest effects in humans.

Types of Stressors and the Onset of Depression Vrshek-­Schallhorn et al. (2015) were interested in the types of stressors that are most closely associated with the onset of major depressive episodes in older adolescents as they transitioned to adulthood. They collected data from two distinct populations. The first group included 627 male and female high school juniors (69% females) who



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completed diagnostic and life stress interviews and were followed up for 5 years. A subset of the larger group (N = 456) completed a childhood trauma interview in year 6. The second group included 146 female high school seniors who completed a set of questionnaires followed by a face-to-face interview. These participants were followed annually for 5 years. In the first group of participants, there were 22,988 person-­months of data collected, and 163 major depressive episodes occurred in 110 participants. In the second group of participants, there were 7,167 person-­months of data collected, and 118 major depressive episodes occurred in 70 participants. The results revealed that chronic interpersonal stress and major episodes of interpersonal stressful life events were statistically unique predictors of risk for the onset of a major depressive episode. Additional analyses revealed a temporal precedence for chronic stress, found no gender effects in the first group of participants, and showed that recent chronic stress mediates the relationship between adolescent adversity and later depressive episodes. Several forms of stress interacted with socioeconomic status (SES), such that decreases in SES were associated with an enhanced role for noninterpersonal chronic stress and noninterpersonal major stressful life events, together with a decreasing role for interpersonal chronic stress (Vrshek-­ Schallhorn et al., 2015).

Meta‑Analysis of Early Life Stress and Depression Early life stress (ELS) has been established as a significant risk factor for the development of MDD in adulthood. An unresolved issue is the degree to which ELS is a risk factor for the early onset of MDD during childhood or adolescence. In a meta-­analysis, LeMoult et al. (2020) estimated the degree to which ELS was related to an increased risk for onset of MDD before 18 years of age. They also explored the associations between eight specific forms of ELS (i.e., sexual abuse, physical abuse, poverty, physical illness/ injury, death of a family member, domestic violence, natural disaster, and emotional abuse) and risk for youth-onset MDD. The meta-­analysis included 62 published journal articles with 44,066 unique participants. The results indicated that individuals who experienced ELS were more likely to develop MDD before 18 years of age compared to individuals with no history of ELS. Separate meta-­analyses for the various forms of ELS revealed a range of associations with MDD, some of which were highly significant (e.g., emotional abuse, physical abuse, domestic violence) and others that were not significant (natural disasters, illness or injury) (Table 6.2). These findings provide important evidence that the adverse effects of some forms of ELS on the risk of developing MDD before 18 years of age manifest early in development, prior to adulthood, and vary by type of ELS. It was not possible to ascertain the effects of exposure to multiple forms of ELS on children and adolescents, given the available studies that were included in this meta-­analysis. An important takeaway from these findings is that the interval between exposure to ELS and the onset of MDD may be brief and that efforts to intervene and prevent MDD should occur as soon after exposure to ELS as possible. Focusing on delivering interventions to those who have experienced ELS during childhood and adolescence, and on identifying targets for the reduction of ELS exposure, should be priorities for those who provide clinical services to these children (LeMoult et al., 2020).

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S t r e ss , H e a lt h , a n d B e h av i o r TABLE 6.2.  Results of a Meta-Analysis on the Risk of MDD Prior to 18 Years of Age in Individuals Exposed to Forms of Early Life Stress Form of ELS All forms combined Sexual abuse Physical abuse Emotional abuse Death of a family member Domestic violence Natural disaster Illness or injury

OR (95% CI)

Significance

2.50 (2.08–3.00) 1.62 (1.26–2.06) 2.13 (1.61–2.81) 2.97 (1.51–5.82) 2.96 (2.00–4.39) 2.34 (1.71–3.19) 1.62 (0.66–3.97) 1.40 (0.76–2.56)

p < .001 p < .001 p < .001 p < .01 p < .01 p < .001 NS NS

Note. ELS, early life stress. Data are from LeMoult et al. (2020). Used with permission of the publisher.

INTERGENERATIONAL TRANSMISSION OF STRESS AND DEPRESSION Children of depressed mothers not only display elevated risk for the development of MDD, but they also may experience both elevated and continuing exposure to stressful experiences because of their mothers’ experiences with their disease. Hammen, Hazel, Brennan, and Najman (2012) explored the possibility of intergenerational transmission of stress and depression, and examined the role of early childhood adversity and maternal depression in the interplay between youth depression and stress over a 20-year follow-­up. These investigators analyzed the results of a longitudinal community study of 705 families selected for the presence or absence of maternal depression, and mothers and their children were studied from pregnancy to age 5 and later when the children were 15 and 20 years old. The families were part of the Mater-­University Study of Pregnancy, a birth cohort study of more than 7,000 children born between 1981 and 1984 at Mater Misericordiae Hospital in Brisbane, Queensland, Australia. When the children were 15 years of age, the investigators selected 815 families to represent mothers with diverse experiences in severity and chronicity of depressive symptoms (including no or minimal depression) over the child’s early life. Depressive symptoms were assessed in mothers and their children using diagnostic interviews, acute and chronic interview-­based stress assessments were undertaken with the children, and contemporaneous measures of childhood adversity were obtained between pregnancy and 5 years of age. Concerns about this sample of families include the fact that mothers were predominantly Caucasian, families were lower-­ middle income, and there was a relative lack of male children. Regression analyses provided evidence of intergenerational transmission and continuity of depression over time, continuity of acute and chronic stress, and reciprocal predictive associations between depression and stress. Maternal depression and exposure to adversities by the time children reached 5 years of age contributed to the continuing experiences of depression and stress in the children. The results were consistent



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with stress continuity and intergenerational transmission, and highlighted the mediating role of chronic interpersonal stress in children who were 15 years of age. Children of depressed mothers were at risk not only for depression but also for continuing experiences of acute and chronic stress from childhood through age 20. Depression and stress levels created a vicious cycle and contributed to continuing experiences of depression and further stress in the children of depressed mothers (Hammen et al., 2012).

DEPRESSION AND CHRONIC MEDICAL DISEASES Considerable evidence points to a bidirectional relationship between major depressive disorder and serious medical diseases, including cancer, cardiovascular disease, diabetes, pulmonary diseases, neurological diseases, and inflammatory diseases (Gold et al., 2020; Katon, 2011). The toxic relationship between depression and these other life-­threatening diseases results in a shorter lifespan for individuals with depression of approximately 5–10 years, with the cause of death typically being heart disease, diabetes, cancer, or another chronic illness. But individuals with a history of depression tend to develop chronic medical illnesses earlier in life, and their depressive symptoms actually hasten the onset and worsen the course of the chronic medical illness. Depressed individuals experience limitations and challenges that nondepressed individuals do not contend with, such as higher levels of psychosocial stress, reduced adherence to treatment recommendations, and physiological changes that exacerbate the progression of their medical illness. In addition, the risk of developing depression is heightened significantly in patients with chronic medical illnesses such as cancer, heart disease, and diabetes. These bidirectional relationships will be discussed in greater detail in some of the following disease-­specific chapters. Several behavioral risk factors also undergird the interrelationship between depression and chronic medical illnesses. These factors include smoking, excessive alcohol intake, lack of regular physical exercise, and an unhealthy diet. In addition, individuals with depression tend to be less compliant with prescription medications and less adherent to treatment protocols and recommended changes in lifestyle associated with chronic medical problems such as cancer, diabetes, and cardiovascular disease (Gold et al., 2020). In the end, depression feeds off of the comorbid disease, and each makes the other worse, presenting a significant challenge to health care providers in personalizing care for an individual diagnosed with depression as well as a comorbid medical condition. Several studies have confirmed that depression affects the ability of patients with a comorbid medical condition to adapt to the specific challenges of living with a chronic disease. For example, depressed diabetic patients (N = 487) differed from diabetic patients without comorbid depression (N = 3,681) in having more diabetic symptoms from a checklist of 10 common symptoms. In addition, for each of the 10 common symptoms of diabetes, depressed diabetic patients reported experiencing each symptom more frequently than nondepressed diabetic patients (ps < .001). These differences between groups held even after adjusting for demographic variables and severity of diabetes (Ludman et al., 2004). Katon, Lin, and Kroenke (2007) conducted a meta-­analysis of 31 published studies involving a total of 16,922 participants, some of whom had a chronic medical condition

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and comorbid depression or anxiety versus individuals with a chronic medical condition but without depression or anxiety. The chronic medical conditions that were represented by the 31 studies included diabetes, heart disease, pulmonary disease, and arthritis. The researchers found that individuals with depression or anxiety and a comorbid medical illness reported significantly more disease-­related symptoms, including pain, than individuals with the chronic disease only. Indeed, depression or anxiety was more consistently related to self-­reported symptoms associated with these chronic medical conditions than objective physiological indicators of disease severity. Depression also increases the risk of severe complications and death from comorbid medical conditions. Katon (2011) provided a summary of several large epidemiological studies that established a link between comorbid depression and mortality rates from serious medical illnesses. In the 2 years after a first heart attack, comorbid depression was associated with a 2.4-fold increase in all-cause mortality, a 2.6-fold increase in cardiovascular-­related mortality, and an almost 2.0-fold increase in new adverse cardiovascular events. Similar results have been reported for diabetes and comorbid depression, with a twofold increase in noncancer and nonatherosclerotic mortality. There is clear evidence that depression increases the risk of adverse outcomes, including death in patients with comorbid chronic medical illnesses. The challenge for health care providers is to develop effective strategies for the diagnosis and treatment of depression in patients with other serious medical conditions. Treatment strategies may vary across the spectrum of medical illnesses, and few studies provide evidence-­based treatments for depression and co-­occurring chronic diseases such as diabetes and cardiovascular disease, especially in older adults. And in fact, some antidepressants may actually worsen the symptoms associated with some chronic illnesses, such as chronic kidney disease. One thing is certain: reducing depressive symptoms is an important step toward improving quality of life and survival in patients with chronic medical illnesses (Gold et al., 2020).

STRESS‑TARGETED INTERVENTIONS FOR MDD If a strong relationship exists between stress and the onset of MDD in at-risk individuals, then it follows that interventions designed to reduce stress or to alter its impact or meaning in high-risk individuals should greatly diminish the onset of a depressive episode. In this section, we will consider some of the relevant research in this area and how various interventions might be adopted more broadly to reduce the deleterious effects on MDD.

Targeting At‑Risk Adolescents Children who have a parent with MDD are at elevated risk of developing MDD in adolescence. A four-site randomized clinical trial reported by Beardslee et al. (2013) investigated the beneficial effects of a cognitive-­behavioral prevention program on decreasing the risk of onset of depression in these at-risk adolescents. Adolescents (N = 316) who had at least one parent with a history of depressive disorders and did not currently meet the criteria for a diagnosis of MDD were recruited for this trial. Participants were 13–17 years old and were currently experiencing elevated depressive symptoms but were not



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currently receiving antidepressant medications and had not previously received eight or more sessions of cognitive-­behavioral therapy. Participants were randomized to either cognitive-­behavioral prevention (CBP) or usual care. CBP emphasized cognitive restructuring and more effective problem solving delivered in eight weekly group sessions that were 90 minutes in length, followed by six monthly continuation sessions that were also 90 minutes long. Assessments involving parents and teens were conducted at baseline before the start of the intervention, after CBP or usual care at 2 months, after the continuing session in month 9, and again at months 21 and 33. Independent evaluators who were unaware of group assignment conducted the follow-­up assessments. The results indicated that the overall effect of the CBP intervention was statistically significant, with the rate of onset of a major depressive episode significantly less in the CBP group compared to the usual care group (p < .04). Over the 33-month follow-­up period, participants in the CBP group experienced a major depressive episode significantly less frequently than participants in the usual care group. Parental depression was a significant moderator of the effect of CBP in that the intervention was much more effective if parents were not in a depressed state at intake. This study was noteworthy for the persistence of the effects of the CBP intervention, especially when parents were not actively depressed at intake. This factor should be considered when interventions to prevent adolescent depression are initiated.

Personalizing Prevention Programs Most interventions to prevent depression take a one-size-fits-all approach, even though at-risk individuals represent a heterogeneous population. A more personalized approach would be to match an individual’s risk profile to a given intervention program, as was presented by Saunders et al. (2021) for patient stratification to inform treatment decisions for individual patients with MDD. A personalized approach has also been taken with respect to matching adolescents at risk of developing MDD to an intervention program. Young et al. (2021) reported on a study where 204 adolescents with a mean age of 14 years, 3 months, were evaluated for their cognitive and interpersonal risk scores for depression. After pretesting, some participants were matched to an intervention program based on their risk profiles, while others were mismatched to an intervention. The two interventions employed in this study were Coping with Stress (CWS) and Interpersonal Psychotherapy–­Adolescent Skills Training (AST). The match condition involved placing high-­cognitive–­low interpersonal risk participants in CWS and low-­cognitive–­high interpersonal risk participants in AST. In contrast, the mismatch condition involved placing high cognitive–­low interpersonal risk participants in AST and low-­cognitive–­high interpersonal risk participants in CWS. CWS involved eight weekly group sessions lasting 90 minutes each, two parent group sessions lasting 90 minutes each, and three booster sessions lasting 60 minutes each and delivered in the 6 months after the group sessions. These sessions involved teaching participants to identify negative thoughts, assess their accuracy, and generate alternative thoughts. In addition, participants learned problem-­solving skills and were introduced to relaxation and assertiveness training. AST involved one pregroup session (90 minutes, parents invited), eight weekly group sessions (90 minutes each), an individual midgroup session (60 minutes, parents invited), and three individual booster sessions

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in the 6 months following group sessions (60 minutes each). The focus of AST was on identifying goals relating to interpersonal relationships, discussing links between relationships and mood, learning different communication strategies, and utilizing these strategies to improve their relationships. Depressive symptoms were assessed in participants and their parents at the end of the intervention and 6, 12, and 18 months later. The results from this randomized controlled trial provided evidence suggestive of the benefits of matching the depression intervention to enhance treatment effects in a sample of adolescents at risk for depression by virtue of cognitive or interpersonal vulnerabilities. Although the initial findings were promising, they should be viewed with caution given that this was the first attempt to match intervention to risk profile, the sample sizes were relatively small, and there was variability across groups. However, based on these initial findings, a replication with much larger sample sizes of participants at multiple sites should be undertaken. Given the increasing rates of depression among adolescents, the significant risks and burden of disease associated with adolescent-­onset depression, and the clear promise of prevention, it is critical to optimize prevention programs for depression and then to ensure that these findings inform clinical decision making. Such a strategy holds the promise of improving outcomes in adolescents at risk of developing depression (Young et al., 2021).

Preventing Depression with a Smartphone App Developing effective interventions for the prevention of depression requires addressing issues of scalability and access to care. Unfortunately, a highly effective intervention that is time-­consuming for patients and labor-­intensive for therapists is doomed to failure. In the United States, health insurance programs provide little support for long-term mental health services, so that a request for enrollment in an extended intervention program may not receive approval. An additional concern is the sheer magnitude of need, with numbers of depressed individuals on the rise in most countries of the world. One potential solution to these significant challenges is the development of a smartphone app as the delivery platform for a behavioral intervention to prevent the onset of a major depressive episode. One such effort will be described below. Deady et al. (2022) conducted a randomized controlled trial with follow-­up assessments at 5 weeks and 3 and 12 months postbaseline. Participants in this trial were recruited online and were employed Australians who reported no clinically significant depressive symptoms at baseline. Average age was 40 years and 74% were male. The intervention group (N = 1,128) was assigned to use HeadGear, a smartphone app that included a 30-day guided behavioral activation and mindfulness intervention. Each day of the intervention, participants were provided with a brief challenge (5–10 minutes) that was based on an evidence-­based therapeutic technique. As the intervention progressed, a toolbox of behavioral skills was filled for use by participants. The attention-­ control group (N = 1,143) used an app that included a 30-day mood monitoring feature. The primary outcome was the level of depressive symptoms as indicated by the Patient Health Questionnaire–9 (PHQ-9) at 3-month follow-­up. Those assigned to the HeadGear group had fewer depressive symptoms over the course of the trial compared to participants assigned to the attention-­control group (p = .03). Prevalence of depression over the 12-month study period was 8.0% for the attention-­control group and 3.5% for the HeadGear group (OR = 0.43, 95% CI =



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0.26–0.70, p < .001). This positive effect of the intervention was even greater in those who engaged more frequently with the app. Indeed, a major challenge with smartphone apps like this is that many individuals may be less inclined to engage with the app when they are not experiencing any significant depressive symptoms. This randomized controlled trial revealed that a smartphone app could reduce symptoms of depression and possibly prevent incident cases of depression in fully employed workers in a variety of job settings. Interventions of this type hold promise for addressing issues of scalability of interventions to prevent depression in adult workers. Unfortunately, attrition rates were high over the course of the trial, and this shortcoming needs to be addressed as the HeadGear app is refined. A similar approach may be especially useful in delivering intervention programs to adolescents, who spend significant amounts of time on their smartphones.

CONCLUSIONS Viewed in isolation, MDD is a serious, chronic, and recurring mental disorder that is a major public health problem in many countries of the world. However, Gold’s quote at the start of this chapter points to a much more expansive role for MDD in disability and premature death. As we will see in some of the chapters that follow, MDD extends its tentacles of influence into a host of organs and tissues that provide the spark for the onset of other chronic diseases, including heart disease, diabetes, cancer, arthritis, respiratory diseases, and other mental disorders. Some of these relationships are bidirectional, such that MDD also draws energy from some chronic diseases that may get an earlier start. What has become apparent over the years is that cases of MDD are increasing in the United States and many other countries, and the health care system as it is currently organized is incapable of meeting the burgeoning need for delivery of mental health services. In addition, while many antidepressant medications are available for the treatment of MDD, questions have been raised about their effectiveness. Stressful life experiences interact with a plethora of risk genes to shape the onset and recurrence of depression in adolescents and young adults. Although stressful stimuli are a consistent feature of life on earth, there are some hopeful signs that intervention programs that promote more positive responses to stress may contribute to a reduction in the devastating effects of MDD. And there may be a selection of smartphone apps in the not-too-­distant future that will support individuals as they attempt to deal effectively with life stressors and reduce their risk of a depressive episode.

CHAPTER 7

Stress and Cardiovascular Disease

C

ardiovascular disease ranks as the world’s leading cause of morbidity and mortality. Globally in 2015, the total number of deaths from all causes was estimated to be 55.8 million people, of whom 17.9 million (32%) died from cardiovascular diseases. Approximately 50% of deaths from cardiovascular disease resulted from coronary artery disease, which increases the risk of a heart attack. Measures of the global burden of disease capture data on premature deaths (expressed as years of life lost) and years lived with a disability. These two measures are combined to yield disability-adjusted life years (DALYs), a measure of the burden of a given disease. Cardiovascular disease also ranks as the leading cause of DALYs globally (Joseph et al., 2017). In the United States, approximately 545,000 people died from coronary artery disease in 2016, a decrease of 15% from 1990. Not surprisingly, coronary artery disease was also the number one cause of years of life lost as well as DALYs in the United States in 2016 (Mokdad et al., 2018). In this chapter, we will explore the role of stressful stimuli and allostatic load as contributors to the burden of cardiovascular diseases, with a focus on coronary artery disease and hypertension. What is the magnitude of the risk for coronary artery disease and hypertension associated with various stress-related stimuli? How do these risks associated with stressors compare to the more typical risk factors for cardiovascular disease, such as smoking, obesity, diet, and lack of exercise? Finally, are there effective interventions to reduce the effects of psychosocial stress on coronary artery disease and hypertension?

STRESS AND HEART DISEASE By any measure, the heart is a remarkable organ. Assuming a resting heart rate of 70 beats per minute, the human heart beats about 100,000 times per day, pumping 130



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approximately 2,000 gallons of blood throughout the body. Over the course of a lifetime, that comes out to 2.5 billion beats. Given the impressive capacities of the heart to work for so many years without fail, it is tempting to think that cardiac muscle cells are miniature superheroes that keep going through good times and bad. Unfortunately, for many people the heart becomes their weak link, especially in times of stress (Figure 7.1). In the sections that follow, we will look at the compelling evidence that psychosocial stressors can compromise normal cardiac function in at-risk individuals, and all too frequently, exposure to intense stressors may lead to premature death from negative effects on the cardiovascular system (Levine et al., 2021).

The Long Arc of Abuse and Neglect Instances of abuse and neglect during early childhood and extending into adolescence may exert lifelong effects on risks for mental and substance use disorders (Cohen, Brown, & Smailes, 2001; Widom, White, Czaja, & Marmorstein, 2007). These same adverse childhood and adolescent experiences may also place individuals at greater lifetime risk of cardiovascular diseases, including coronary heart disease and heart attacks. In one large-scale meta-­analysis of health risks of adverse childhood experiences, eight reports based on data from four countries were combined to yield more than 120,000 participants, some with no occurrence of early abuse and neglect and others with four or more instances of abuse or neglect. The results indicated that exposure to abuse and neglect was associated with a significant lifetime increase in incidence of cardiovascular disease (OR = 2.07, 95% CI = 1.66–2.59).

FIGURE 7.1.  Pathways through which psychosocial stressors enhance the risk of cardiovascular disease.

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Stress Cardiomyopathy Stress cardiomyopathy, also known as takotsubo syndrome, broken heart syndrome, or even happy heart syndrome, was first described in Japan by Sato, Uchida, Dote, and Ishihara (1990) and typically involves symptoms similar to a heart attack, including pronounced left ventricular dysfunction, intense chest pains, and labored breathing. The Japanese word takotsubo (“octopus pot”) refers to the characteristic ballooning of the apex of the left ventricle to resemble the shape of an octopus pot used by Japanese fishermen. The attack is often precipitated by an intense emotional or physical stressor, including death of a loved one, having a heated argument, experiencing a surprise birthday party, fearing a medical procedure, and being in a car accident. An increase in the incidence of stress cardiomyopathy was also reported during the COVID-19 pandemic in April and May 2020 compared to control periods prior to the pandemic (Jabri et al., 2020). A recent report from 26 medical centers in Europe and the United States provided an overview of 1,750 patients diagnosed with takotsubo cardiomyopathy and compared them to age- and sex-­matched controls who experienced an acute coronary episode. Of the patients with takotsubo cardiomyopathy, 90% were female, with an average age of 67 years (Templin et al., 2015). Self-­reports indicated that 36% of patients with this syndrome experienced physical triggers before clinical symptoms occurred, 28% experienced emotional triggers, 8% experienced a combination of triggers, and 28% reported experiencing no triggers. Emotional triggers were more common among females, and physical triggers were more common among males. These patients also had a higher prevalence (56%) of prior neurologic and psychiatric diagnoses than controls with acute coronary syndrome, and 4% died while in hospital. Long-term follow-­up of takotsubo patients revealed a death rate from any cause of 5.6% per patient-­year and a rate of major adverse cardiac and cerebrovascular events of 9.9% per patient-­year (Templin et al., 2015). Physical and emotional triggers appear to precipitate takotsubo cardiomyopathy by activation of brain pathways involved in regulation of the sympathetic nervous system, resulting in excessive stimulation of the heart by catecholamines, especially epinephrine. During and after exposure to the physical or emotional triggering event, large quantities of epinephrine are released from the adrenal medulla into the circulation. In addition, norepinephrine and neuropeptide Y are co-­released from postganglionic sympathetic nerve terminals in the heart. Activation of the sympathetic–­adrenal medullary system in takotsubo cardiomyopathy patients was significantly greater than in patients experiencing an acute heart attack, and plasma catecholamine and neuropeptide Y levels remained elevated for up to 9 days after symptom onset (Wittstein et al., 2005). This significant and sustained stress-­induced surge in peripheral catecholamines appears to lead to direct and indirect damage to the myocardium, including myocardial stunning, a reversible disruption in heart contraction. Lack of estrogen in postmenopausal women also plays an important role in the pathophysiology of takotsubo cardiomyopathy (­Pelliccia, Kaski, Crea, & Camici, 2017). Lau, Chiu, Nayak, Lin, and Lee (2021) reviewed the clinical records of 519 takotsubo patients who were treated between 2006 and 2016 and were followed for an average of 5.2 years at Kaiser Permanente Southern California Health System. During the follow-­up period, 39 patients (7.5%) had a recurrence of takotsubo syndrome and 84 (16.2%) patients died. Treatment with beta-­blockers was associated with a reduced risk of recurrence of takotsubo cardiomyopathy or death.



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Stress Can Trigger Heart Attacks John Hunter, (1728–1793) was one of 18th-­century England’s most distinguished surgeons and scientists. He was elected a fellow of the Royal Society in 1767, and he is buried in Westminster Abbey. One of his research assistants characterized him as “warm and impatient, readily provoked, and when irritated, not easily soothed” (Moore, 2005, p. 346). This vivid description of Hunter foreshadowed his death from a heart attack on October 16, 1793, following an intense argument with an administrator at a St. George’s Hospital board meeting. Hunter’s death has often been advanced as early evidence of the occurrence of sudden cardiac death following exposure to an intense psychosocial stressor. More than two centuries later, anger was confirmed as a significant cross-­cultural trigger for first heart attacks in the INTERHEART study, an international, multi-site research project in 52 countries using a case–­control design. Of 12,461 participants with a first heart attack, 14.4% (N = 1,752) reported being angry or emotionally upset in the 1-hour period prior to the onset of cardiac symptoms. Anger or emotional upset in the prior 1-hour period was associated with an increased odds ratio of having a heart attack of 2.44 and a population-­attributable risk of 8.5% (Smyth et al., 2016). Living through catastrophic events such as earthquakes or missile attacks, or watching broadcasts of sports competitions offer present-­day opportunities for researchers to examine the relationship between intensely stressful events and increased incidence of heart attacks. These situations are also unusual in that the exact time of the stressor can often be specified down to the minute and the affected population can be tracked through hospital admissions and death certificates. To provide baseline levels of various cardiac events, researchers have typically measured population-­level cardiac events on the same date in previous and subsequent years or in the several days leading up to or following an event. Following are illustrative examples of some of these naturally occurring stressors.

Earthquakes

• Athens, Greece, earthquake (6.7 Richter scale). The earthquake occurred at 10:53 P.M. on February 24, 1981. In the 5 days following the earthquake, there was a 50% increase in deaths from acute cardiac events and a 100% increase in deaths from atherosclerotic heart disease (Trichopolous, Katsouyanni, Zavitsanos, Tzonou, & Dalla-­Vorgia, 1983). • San Francisco, California, earthquake (7.0 Richter scale). The earthquake occurred at 5:04 P.M. on October 17, 1989. No significant increase in the number of patients with heart attacks was reported for the day following the earthquake (Brown, 1999). • Northridge, California, earthquake (6.7 Richter scale). The earthquake occurred at 4:31 A.M. on January 17, 1994, near Los Angeles, California. There was a significant increase in the number of sudden deaths from atherosclerotic cardiovascular disease, as well as an 80% increase in hospital admissions for heart attacks, on the day of the earthquake (Brown, 1999; Leor, Poole, & Kloner, 1996).

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• Kobe, Japan, earthquake (7.2 Richter scale). The Hanshin–­Awaji earthquake occurred at 5:46 A.M. on January 17, 1995. There was a 3.5-fold increase in patients with heart attacks and a significant increase in the number of deaths from heart attacks during the 8–12 weeks after the earthquake (Kario, Matsuo, Kobayashi, Yamamoto, & Shimada, 1997). • Ji-Ji, Taiwan, earthquake (7.3 Richter scale). The Ji-Ji earthquake occurred at 1:47 A.M. on September 21, 1999. In the 6 weeks following the earthquake, there was a significant increase in the number of patients hospitalized due to heart attacks (Tsai, Llung, & Wang, 2004). In a separate report, 12 patients who were fitted with Holter ECG ambulatory monitors provided an opportunity to examine the beat-to-beat changes in heart rate before and after the earthquake. Analysis of heart rate variability immediately following the earthquake suggested a significant increase in sympathetic tone and/or a withdrawal of parasympathetic tone to the heart. The rapid increases in heart rate at the onset of the earthquake were blunted significantly in three patients who were taking a beta-­blocker (Huang, Chiou, Ting, Chen, & Chin, 2001). • Great East Japan earthquake and tsunami (9.0 Richter scale). The Great East Japan earthquake occurred at 2:46 P.M. on March 11, 2011. There was a significant increase in the number of patients seen in area emergency departments in the 3 weeks following the earthquake due to acute coronary syndrome and congestive heart failure but not because of out-of-­hospital cardiac arrests (Nozaki et al., 2013). Soccer For most of the world, soccer (i.e., football) is the sport. Intense competitions within countries (such as the English Premier League) give way to national teams competing in regional championships and the World Cup. Committed football fans are never too far from their televisions during games, there is frequently consumption of rich food and alcoholic beverages leading up to and during the matches, and the level of success of favorite teams is a source of local and national pride. Even Pope Francis has his favorite team in Argentina, the San Lorenzo Crows. Given this context, let’s explore studies that have examined cardiovascular morbidity and mortality during football championship matches.

• 1996 European Football Championship Quarterfinal Match, Netherlands versus France. This match was played in Liverpool, England. The match ended in a 0–0 tie, after which France won in a penalty shoot-out. Mortality from heart attacks and stroke in the Dutch population aged 45 years and older was increased on the day of the match relative to several control periods. This finding was true for males but not females. This spike translated into 14 more deaths than expected on the day of the match from cardiovascular disease (Witte, Bots, Hoes, & Grobbee, 2000). • 1998 FIFA (Fédération Internationale de Football Association) World Cup match, England versus Argentina. Following England’s loss to Argentina in a penalty shoot-out, there was a 25% increase in hospital admissions for heart attacks on the day of the match and for the 2 days after the match. There was no observed increase in



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admissions for other diagnoses on these 3 days (Carroll, Ebrahim, Tilling, Macleod, & Smith, 2002).

• 2006 FIFA World Cup series. Germany hosted this tournament. Cardiovascular events were studied in the Munich metropolitan area on days when the German team played and compared to various control periods. Cardiac emergencies increased 2.66-fold on days when the German team competed, with greater increases in males (3.26-fold) than females (1.82-fold). Among these patients, 47% had documented cardio­vascular disease compared to 29% during control periods (Wilpert-­Lampen et al., 2008). War and Terror

• Scud missile attacks in Israel. From January 17 to January 25, 1991, a series of Scud missiles were launched from Iraq and aimed at locations in Israel during the initial phase of the first Gulf War. In a tertiary care hospital in a suburb of Tel Aviv, there was a significant increase in patients presenting with heart attacks and sudden death during the 8-day period of attacks compared to several control time periods (Meisel et al., 1991). • 9/11 terrorist attacks in the United States. A national probability sample of more than 2,700 adults was followed before and for 3 years after the series of terrorist attacks that occurred in the United States on September 11, 2001. There was a greater than 50% increase in the incidence of physician-­diagnosed cardiovascular disease over the 3 years following the attacks (Holman et al., 2008). Summary Several key findings have emerged from studies of profoundly stressful events on the heart, such as earthquakes, national sporting events, and terrorist attacks as well as other events (e.g., job loss, intense anger, major holidays). Intense stressors can serve as emotional triggers for acute cardiac events in susceptible individuals by several mechanisms, including restriction of coronary blood flow due to vasoconstriction, rupture or disruption of an atherosclerotic plague in coronary vessels, increased cardiac electrical instability, increased blood clotting, and myocardial ischemia. These pathophysiological changes are driven in large part by stress-­induced increases in sympathetic, HPA axis, and immune system activities (Kivimäki & Steptoe, 2018). Some of the earthquake studies referenced above focused on the immediate effects of the natural disaster on cardiac events, while others demonstrated prolonged increases in heart-­related morbidity and mortality due to extended periods of suffering in remote regions (e.g., Japan earthquake). A closer examination reveals that the timing of the earthquake was a critical variable, with late night–early morning earthquakes (e.g., Ji-Ji, Taiwan) having greater impact on cardiac morbidity and mortality than earthquakes occurring during the daytime (e.g., San Francisco). Imagine the extreme emotional reaction of being awakened from a sound sleep in total darkness with your home or apartment building violently shaking and your sympathetic nervous system increasing from a low level of activity to an extremely high one in a matter of seconds.

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How might an emotionally triggering event lead to a heart attack? Strike et al. (2006) approached this question empirically by studying a group of 34 male patients an average of 15 months after they experienced a heart attack or unstable angina. At this time, patients were stable and medically well managed. Soon after the coronary event, 14 of the patients had reported that an emotionally charged (EC) event triggered their heart attack or chest pain, while the remaining 20 patients (nonemotionally charged—­ NEC) did not report having experienced an emotional event prior to their cardiac event. All patients were brought into the laboratory and exposed acutely to two stressors: a computer-­based color–word interference task and a public speaking task. The color– word interference task typically involves rapid presentation on a computer screen of color words printed in an incongruous color of ink. For example, the word red is printed in yellow ink. The task is to say the color of the ink for each color word as quickly as possible. Blood samples and cardiovascular measures were obtained at rest and at timed intervals following exposure to the stressors. EC patients but not NEC patients displayed enhanced platelet–­leukocyte aggregation during and after exposure to the stressors. EC patients also had greater increases in systolic blood pressure (BP) and cardiac output during and after stress testing compared to NEC patients. These results suggest that individuals who are vulnerable to emotional triggers may react to stressful situations with an increase in platelet activation and more prolonged BP changes that could lead to increased sheer stress on the walls of blood vessels, followed by potential rupture of atherosclerotic plaques.

STRESS‑RELATED DISORDERS AND CARDIOVASCULAR DISEASES Drawing upon the Swedish National Patient Register, Song, Fang, et al. (2019) identified patients who received a diagnosis of a stress-­related disorder such as PTSD, acute stress reaction, adjustment disorder, and other stress reactions between 1987 and 2013 (N = 106,180). These investigators also constructed two control groups: unaffected full siblings of the patients with stress-­related disorders (N = 171,314) and a group of unexposed individuals who were matched to the demographic characteristics of the patient group (N = 1,366,370). During the follow-­up period that lasted as long as 27 years, the incidence of any cardiovascular disease (expressed as cases per 1,000 person-­years) was 10.5, 8.4, and 6.9 in the stress-­related disorder groups, the unaffected full sibling group, and the matched unexposed control group, respectively. Compared to unaffected siblings, those with stress-­related disorders had an increased risk of developing any cardiovascular disorder during the year following the diagnosis (HR = 1.64, 95% CI = 1.45–1.84). A similar pattern was reported for patients with stress-­related disorders compared to matched unexposed controls (HR = 1.71, 95% CI = 1.59–1.83). These results applied equally to males and females and were adjusted for family history of cardiovascular diseases and psychiatric comorbidities. These results demonstrate the profound effects of significant life stressors on the cardiovascular system and strongly suggest that patients should be carefully monitored for disorders of the cardiovascular system, especially in the first year following a stress-­related diagnosis (Song, Fang, et al., 2019).



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THE STRESS OF A CANCER DIAGNOSIS Few things in life are more dreaded or more stressful than receiving news from a physician that you have cancer, especially an aggressive form of cancer with little chance of long-term survival. How will you prepare your loved ones, are your affairs in order, are there things you really want to do before you are no longer mobile? To determine if receiving a cancer diagnosis is a stressful insult to the heart, Fang et al. (2017) conducted a study using Swedish national census and cancer and mortality databases that included slightly more than 6 million people who were born in Sweden and were at least 30 years of age between January 1, 1991 and December 31, 2006. Over the course of the study, more than 543,000 individuals who were cancer-­free died from cardiovascular diseases, an incidence rate of 7.53 deaths per 1,000 participants. Following a diagnosis of cancer (excluding brain tumors), 48,991 individuals died from cardiovascular disease, an incidence rate of 23.1 deaths per 1,000 participants. The highest relative risk of cardiovascular deaths occurred during the first week following a cancer diagnosis, when the incidence rate increased to 116.8 deaths per 1,000 participants (OR = 5.6, 95% CI = 5.2–5.9). Extending out to the first 4 weeks after a cancer diagnosis, the incidence rate for cardiovascular deaths decreased to 65.8 deaths per 1,000 participants (OR = 3.3, 95% CI = 3.1–3.4). More than 1 year after a cancer diagnosis, there was no longer an elevated risk for cardiovascular deaths from most cancer diagnoses, with the exception of lung cancer. To control for shared risk factors among cancer and cardiovascular disease, Fang et al. (2017) employed a case–­crossover design such that participants who received a cancer diagnosis served as their own controls in the 17 4-week periods leading up to the diagnosis versus the 4-week period following the diagnosis. The results revealed that the risk of cardiovascular death was 3.7 times higher following a diagnosis compared to the control period prior to a cancer diagnosis. Deaths due to other disturbances of the cardiovascular system were also elevated (see Table 7.1). These investigators took advantage of the excellent national census and health record systems in Sweden to address the question of how the elevated risk of cardiovascular TABLE 7.1.  Risk of Cardiovascular Death after a Cancer Diagnosis Using a Case–Crossover Design Number of patients who died with a cancer diagnosis Cause of death

Before diagnosis

After diagnosis

Odds ratio (95% CI)

Cardiovascular death

11,988

2,641

3.7 (3.6–3.9)

Heart attack

 3,662

  970

4.5 (4.2–4.8)

Other heart diseases

   554

  134

4.1 (3.4–5.0)

Embolism/thrombosis

   477

  159

5.7 (4.7–6.8)

Stroke

 1,538

  220

2.4 (2.1–2.8)

Note. Odds ratios were adjusted for seasonal variations in cancer diagnosis and cardiovascular deaths. Data are from Fang et al. (2017). Suicide and cardiovascular death after a cancer diagnosis. New England Journal of Medicine, 366, 1310–1318. Copyright © 2017 Massachusetts Medical Society. Used with permission of Massachusetts Medical Society.

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disease plays out following a diagnosis of cancer. There can be little doubt that the period immediately following a cancer diagnosis is profoundly stressful and appears to serve as a trigger for heart attacks and other disturbances of the heart and circulation (Fang et al., 2017).

DEPRESSION AND THE HEART As we discussed in Chapter 6, depression is the second leading cause of disability in the United States and globally. It has a 1-year prevalence of 10–12% and a lifetime prevalence of ∼20%. Depression is also a major risk factor for the development of coronary heart disease, and those individuals with heart disease who are also depressed tend to have a much poorer long-term prognosis. Coronary heart disease, the other half of this dreaded 1–2 punch, remains the leading cause of mortality in the world and increases vulnerability for depression. In fact, the prevalence of depression increases to 15–30% in patients with coronary heart disease, and is two times higher in women than in men. This bidirectional relationship between depression and heart disease sets in motion a downward spiral of poor physical health and poor mental health (Whooley & Wong, 2013). Not surprisingly, when depression and heart disease co-occur, the prognosis for both worsens. One psychosocial factor that is shared in common between depression and heart disease is recurrent activation of stress-­sensitive central and peripheral neural and endocrine pathways (Dhar & Barton, 2016; McCarty, 2020). An immense literature on the comorbidity of depression and heart disease has developed, and many outstanding review articles and meta-­analyses have been issued on this topic (see, for example, Carney & Freedland, 2017; Wholley & Wong, 2013). In the sections that follow, I have included several key studies to illustrate how depression is a prominent risk factor for the development of heart disease and how the occurrence of heart disease increases the risk for depression. Indeed, Dhar and Barton (2016) argued that major depressive disorder should be considered a modifiable risk factor for heart disease just like cigarette smoking, a sedentary life style, hypertension, and hyperlipidemia.

Is Depression a Risk Factor for Coronary Heart Disease? Liu, Hernandez, Trout, Kleiman, and Bozzay (2017) reported on a prospective approach to exploring the toxic combination of depression and heart disease. These investigators analyzed data from the Americans’ Changing Lives study led by the Survey Research Center of the University of Michigan and initiated in 1986 with a nationally representative sample of adults in the 48 contiguous United States. In 1989, 2,846 participants completed assessments of functional social support; body mass index; depressive symptoms over the previous 3-year period; and occurrence of heart disease, hypertension, and diabetes. Follow-­up data were collected in 2001 and the remaining active participants (N = 1,642) were again asked about occurrence of heart disease over the previous year. Social support was found to be an important buffer between participants with depression and a later diagnosis of heart disease. Among participants with lower levels of social support (defined as 1 SD below the mean), depression was a significant risk factor for heart disease even after adjusting for demographic and health measures (OR = 2.07, 95% CI = 1.02–4.07, p < .05). In contrast, depression was not prospectively



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associated with heart disease in participants with higher levels of social support (defined as 1 SD above the mean). A strong system of social support may encourage health-­related behaviors and dampen physiological responses to stress that have adverse effects on the heart and circulatory system. Although this study has many compelling aspects, all health-­related data were based on participants’ self-­reports and no measures of perceived stress were taken. That a significant interaction between low levels of social support and later diagnosis of heart disease was determined makes the finding all the more remarkable (Liu et al., 2017).

Does Coronary Heart Disease Increase the Risk of Depression? There is little doubt that experiencing a heart attack is about as stressful a situation as one can imagine. There is the rush to the hospital emergency room, perhaps by ambulance, and the team of doctors and nurses that descend upon the patient. If one is fortunate and survives the initial scare of the heart attack symptoms, the recovery can also present quite a few life stressors as the inevitable adjustments to a new way of life kick in with a changing diet and a new exercise plan. But what if all these changes become too much and symptoms of depression take hold. Are depressive symptoms to be expected, or do they pose a serious risk for longer-­term survival from the heart attack?

Depression as a Risk Factor A team of researchers in Montreal, led by Dr. Nancy Frasure-­Smith, published an influential article that provided strong evidence that depression is a potent risk factor for death in the 6 months following a heart attack (Fraser-­Smith et al., 1993). This team enrolled 222 patients who experienced heart attacks in a 6-month study relating depression to health outcomes. Interviews were conducted while patients were in hospital and included demographic information and a structured interview regarding symptoms of depression. Additional information on participants was obtained from hospital records. All participants were contacted 6 months after hospitalization to determine survival rates. Twelve patients had died of cardiac complications by the 6-month follow-­up. Strikingly, depression was a significant predictor of mortality, even after controlling for demographic and cardiac-­related variables (HR = 4.29, 95% CI = 3.14–5.44, p < .02).

Large‑Scale Study of Depression as a Risk Factor The prospective report by Frasure-­Smith, Lespérance, and Talajic (1993) was the first to demonstrate that depression has an adverse impact on survival in patients following a heart attack. A more recent large-scale study has extended these initial findings and explored mortality rates among treated and untreated depressed patients following a heart attack. The TRIUMPH study (Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients’ Health Status) enrolled more than 4,000 patients who experienced heart attacks at 24 medical centers across the United States (Smolderen et al., 2017). Three groups of patients were established based on reviews of medical records and screening with the Patient Health Questionnaire–9

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(PHQ-9, scores range from 0 to 27) during admission: (1) no depression evident (PHQ-9 score < 10), (2) untreated depression (PHQ-9 score ≥ 10), and (3) depression treated with antidepressants or counseling (PHQ-9 score ≥ 10). Mortality rates 1 year after the heart attack were tracked for all patients. Patients with untreated depression had significantly higher mortality rates 1 year after a heart attack compared to patients who received treatment for depression and patients without depression, even after adjusting for demographic and clinical variables in the three patient groups (p < .001). These findings emphasize the importance of screening for depression and instituting treatment options (drugs, psychotherapy, exercise regimen, stress management) to increase survival in heart attack patients following discharge from the hospital. These observational data are compelling, but definitive evidence of a connection between effective treatment of depression and enhanced survival following a heart attack awaits large-scale, multi-­center randomized clinical trials. Several review articles have emphasized stress-­induced sympathetic nervous system, HPA axis, and immune activation as shared mechanisms relating to the onset of depression and the occurrence of a heart attack. In particular, the role played by heightened levels of inflammation in both diseases provides new therapeutic targets for treatment of depression and heart disease (Rohleder, 2014; Shao et al., 2020; Whooley & Wong, 2013).

Coronary Heart Disease Leads to Persistent Psychological Distress One criticism that could be leveled at the preceding studies was their complete dependence on a single measure of depression in probing the onset of coronary heart disease or the response to a coronary event. Persistence of depressive symptoms over time may be a critical variable that has been overlooked in many previous studies that explored the links between depression and coronary heart disease. Stewart et al. (2017) tackled this problem head-on by taking a longer view of this critical relationship. In their study, 950 participants from a larger sample of individuals who were enrolled in a study of the effectiveness of a statin on coronary heart disease completed at least four general health questionnaires (GHQ-30) at the start of the study and after 6 months and 1, 2, and 4 years. All individuals were then followed for a median of 12.5 additional years, and mortality from coronary heart disease and other causes was tracked. Over the 4-year assessment period, participants were ranked for levels of distress relating to anxiety and depression based on their scores on the GHQ-30. Participants were categorized as follows: never distressed to mildly distressed (5 < GHQ score < 10), moderately to severely distressed (GHQ score > 10). Persistent distress was defined as a GHQ score > 10 on at least three of the five assessments. Participants with persistent moderate to severe levels of distress over the 4-year assessment period had higher risks of cardiovascular deaths and all-cause mortality (two- to fourfold increase) over the 14-year follow-­up period compared to participants with no distress (ps < .001). These findings point clearly to the persistence of distress over a long period of time as a key contributor to mortality, and they are consistent with long-term distress contributing to allostatic load (Stewart et al., 2017). Persistent levels of distress should be measured and considered in designing behavioral interventions to improve well-being in patients at high risk of mortality from coronary heart disease.



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Summary For the past 30 years, compelling evidence suggests that symptoms of depression result in reduced survival from a heart attack. In addition, treatment of depression reduces the risk of death from a heart attack. Finally, long-term, persistent levels of distress lead to increases in allostatic load and an increased risk of death from coronary heart disease as well as other causes of mortality. Taken together, these findings emphasize the need to address levels of psychosocial stress in patients diagnosed with coronary heart disease and in patients recovering from heart attacks (Vaccarino et al., 2020).

WORK‑RELATED STRESSORS AND THE HEART Adults throughout the world spend a great deal of time spanning many decades in work-­related activities, including commuting from their homes to places of employment. In addition, with increased access to smartphones and wireless technology, many individuals are involved in work projects through texts, emails, and teleconferences during evenings and weekends and even during vacations. During the COVID-19 pandemic, many individuals worked from home, and the challenges associated with telecommuting have been widely discussed. Work-­related stressors comport nicely with the concept of allostatic load, as summarized in Chapter 1. To combat the intrusion of work-­related activities on leisure time, in 2017 the French government passed a law that introduced the right of employees to disconnect from all digital devices during their personal time. The details of implementation were vague, but the intent was clear: to reduce levels of stress on workers. On top of time demands, add a tendency for workers to have less job security while dealing with stagnant wages. It’s easy to see how the contemporary pressures and insecurities associated with work might increase levels of allostatic load and in turn place individuals at greater risk for development of coronary heart disease.

Demand–Control Imbalance Demand–­control imbalance (DCI; better known as job strain) refers to the stress associated with a job that places significant psychological demands on an employee but allows that person little or no control over task assignments or input on work-­related decisions. Many differences of opinion exist on the impact of work stress on cardiovascular disease, with some researchers favoring significant adverse effects of work stress, and others suggesting the impact of work stress is negligible (Kivimäki & Kawachi, 2015). To tackle this important issue, Kivimäki et al. (2012) combined individual data from 13 European cohort studies initiated between 1985 and 2006 that were part of what is known as the Individual-­Participant Data Meta-­A nalysis of Working Populations (IPDWork) consortium. Some of the findings were previously published, and some were unpublished. The combined dataset included 197,473 participants, with approximately equal numbers of men and women with an average age of 42 years. Fifteen percent of participants (30,214) reported significant job strain on an initial questionnaire. After a follow-­up period that averaged 7.5 years, there were 2,358 diagnoses of coronary heart disease. After adjusting for sex and age, the hazard ratio for participants with job strain

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versus no job strain was 1.23 (95% CI = 1.10–1.37). These findings point to a modest but consistent effect of job strain on elevated risk for coronary heart disease.

Effort–Reward Imbalance Imagine a job where you are expected to work long hours, the workload never lets up, and the pace of work expected is unreasonably high. Now combine these measures of effort with an absence of rewards or incentives such as salary increases, special recognition, opportunities for promotion, or increased job security. These characteristics are the essential features of the effort–­reward imbalance (ERI) model of work stress. The literature suggests that jobs that have high effort but low rewards are associated with increased risk of coronary heart disease and cardiovascular-­related mortality. One major prospective study has tackled this important question by establishing a consortium across 11 cohort studies in six European countries (Denmark, France, Finland, Germany, Sweden, and United Kingdom) to explore associations between work-­ related psychosocial measures and disease outcomes (IDP-Work consortium) (Dragano et al., 2017). The study population included 90,164 participants (mean age = 45 years, 61% female) without coronary heart disease at the start of the individual studies (beginning in 1985–2005). All participants completed questionnaires relating to job strain and ERI at baseline and were followed for an average of 9 years, 8 months, with data collected on heart attacks and mortality from coronary heart disease. At the beginning of the study, 32% of participants reported ERI associated with their jobs, 16% reported job strain but not ERI, 10% reported both, and 62% reported neither. Over the course of the study, there were 1,078 coronary events. After adjusting for demographic variables and coronary heart disease risk factors, the results indicated that the effects of ERI or job strain on coronary heart disease were modest (HR = 1.16, 95% CI = 1.01–1.34) and that the combined effects of both stressors on coronary heart disease were additive (HR = 1.41, 95% CI = 1.12–1.76). These findings of a significant association between work stress and risk of coronary heart disease are all the more remarkable given that all study participants worked in European countries where occupational safety and health standards are at high levels, attention is given to reducing workplace stress levels, and strong social welfare policies have been put in place to protect workers. It remains to be seen whether the impact of ERI and/or work stress on coronary heart disease risks are of greater impact in countries that lack these well-­ established labor protection and social welfare policies (Dragano et al., 2017).

Shift Work Shift work places significant demands on workers and their loved ones given the constantly changing schedules and the alterations in sleep–wake cycles. In some instances, shift work also includes weekend work hours. In many sectors of our nation, work-­ related activities continue nonstop 24 hours per day, 7 days per week. Consider hospital workers, first responders, fulfillment center and call center staff members, manufacturing plants, and transportation workers as a few of the many areas that almost never shut down. In a meta-­analysis of 21 studies that included over 170,000 participants, Torquati et al. (2018) reported that shift workers had a 17% greater risk of any cardiovascular



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disease event compared to controls who worked standard day shifts. Further, the risk of coronary heart disease morbidity (HR = 1.26, 95% CI = 1.10–1.43) and coronary heart disease mortality (HR = 1.18, 95% CI = 1.06–1.32) were both elevated in shift workers compared to day workers. The longer an individual continued with shift work beyond the first 5 years, the greater the risk of experiencing cardiovascular disease-­ related events.

Loss of Job Economic downturns, which seem to come out of nowhere, can place job security at risk for even the most valuable employees. Organizations in many sectors of national economies have operating budgets that are largely connected to employee pay and benefits. Thus, during a steep economic downturn, the quickest way to cut operating costs is unfortunately to furlough or terminate employees. Think back to the rapid economic downturn that occurred during the COVID-19 pandemic in early 2020. Tens of thousands of employees were furloughed or terminated from businesses large and small, including colleges and universities, as quarantine orders and travel restrictions were issued. Clearly, loss of one’s job is not a remote possibility: it is all too real even under the best of economic circumstances. To address these important issues, Virtanen et al. (2013) combined data from four published studies and 13 IDP-Work studies conducted in the United States and six European countries to yield a meta-­analysis dataset of almost 175,000 participants. Participants completed an assessment of job insecurity (one question or a series of questions, depending on the study methodology) and were followed for an average of 9.7 years, with records made of fatal and nonfatal heart attacks. Across these 17 studies, job insecurity was reported by 16% of participants, many of whom were in low-­paying jobs and tended to be less physically active, with more cases of hypertension and hypercholesterolemia. There were 1,892 cases of coronary heart disease over the course of the studies, and high job insecurity was associated with a higher incidence of coronary heart disease among men and women combined (HR = 1.32, 95% CI = 1.09–1.59), with women being at slightly higher risk than men.

Summary Work can be a blessing or a curse. For many, work is rewarding, challenging, and exciting, and it offers opportunities to enhance the success of one’s employer and to benefit personally from that success. For others, work is a means to an end—a way to earn a modest salary in a job that is a dead-end with no hope of promotion, little job security, no on-the-job training, and no prospects for assuming responsibilities or benefiting from the success of the employer. As we have seen, job strain, effort–­reward imbalance, shift work, and job insecurity contribute modestly to risk of an acute heart attack. These risks do have consequences, and some companies and national governments have taken steps to reduce workplace stressors, address effort–­reward imbalances in creative ways, enhance opportunities for training and advancement, and enhance the quality of life for their employees. Employers receive returns on these investments by having a more dedicated and productive workforce that is committed to the long-term success of the company (Marmot, 2004).

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BELIEFS ABOUT STRESS AND THE HEART Nabi et al. (2013) were interested in the long-term impact of beliefs that stress affects one’s health. To address this important research question, these investigators made use of data from the Whitehall II study of British civil servants. Begun in 1985 with more than 10,000 participants aged 35–55 years old, this prospective study included periodic data collection via mailed questionnaires and clinic visits. In Phase 3 (1991–1993), the following question was added to the larger mailed questionnaire: “To what extent do you feel that the stress or pressure you have experienced in your life has affected your health?” Responses included (1) not at all, (2) slightly, (3) moderately, (4) a lot, or (5) extremely. Participants were followed until Phase 9 (2007–2009), for a maximum period of 18.3 years. A complete dataset was available for 7,268 participants, of whom 8% (N = 584) responded “a lot” or “extremely” to the question about stress affecting health. There were 352 coronary deaths or nonfatal heart attacks over the course of the study. After adjusting for biological and behavioral risk factors (including perceived levels of stress), there was an increased risk of coronary heart disease among those individuals who responded a lot or extremely to the key question regarding stress effects on health (HR = 1.49, 95% CI = 1.01–2.22). Nabi et al. (2013) concluded that behavioral interventions designed to alter the belief that stress has a significant impact on personal health could be an effective strategy for reducing the risk of coronary heart disease in this cohort of patients. Perhaps a more effective intervention would be to provide strategies for managing life stressors more effectively.

BRAIN RESPONSES TO STRESS Psychosocial stressors exert deleterious effects on the cardiovascular system via activation of brain circuits that control autonomic, endocrine, and immune activities (McCarty, 2020). In an elegant prospective study, Tawakol et al. (2017) enrolled 293 participants from a larger group of more than 6,000 patients who were screened for cancer over a 3-year period (2005–2008). All participants were at least 30 years old, had been cancer free for at least 1 year, and had no history of immune dysfunction. Individuals were included in a functional magnetic resonance imaging (fMRI) study and an 18F-­f luorodeoxyglucose (18F-FDG) study to measure brain neuronal activity and tissue metabolic activity, respectively. Over the follow-­up period (median = 3.7 years), 22 participants experienced 39 cardiovascular disease events (e.g., heart attack, unstable angina, stroke, heart failure). Interestingly, fMRI-based activity in the amygdala under resting conditions, an important component of the brain’s stress circuitry, was significantly associated with cardiovascular disease events even after adjusting for other standard risk factors (HR = 1.61, 95% CI = 1.21–2.14). This relationship was not apparent for other brain areas, including the cerebellum and the cerebral cortex. Amygdala activity also correlated with metabolic activity in bone marrow and spleen and uptake of 18FFDG in arteries, an index of inflammation. Activation of the amygdala also increases sympathetic nervous system activity, which directly affects levels of arterial inflammation and atherosclerosis. These investigators suggested that efforts to reduce levels of psychosocial stress might dampen the negative effects of the amygdala–­sympathetic–­ immune axis and reduce cardiovascular disease risk (Tawakol et al., 2017).



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THE PROTECTIVE EFFECT OF SOCIAL NETWORKS The Nurses’ Health Study was launched in 1976 with more than 120,000 female nurses who were 30–55 years of age at the time. Women were followed every 2 years with a mailed questionnaire regarding health risks and outcomes. Beginning in 1992 and continuing every 4 years, new information was collected on social networks and their impact on coronary heart disease, and 1992 served as the baseline year for a study by Chang et al. (2017). There were 76,362 participants (mean age = 58 years) after exclusions for preexisting conditions and advanced age, and they were followed for fatal and nonfatal heart attacks until May 2014. After adjusting for demographic and health-­related behaviors, participants with the highest social integration scores were less likely to develop a fatal heart attack compared to those participants with the lowest social integration scores (HR = 0.68, 95% CI = 0.51–0.92). For nonfatal heart attacks, those participants with higher social integration scores also had higher levels of health-­ promoting behaviors (nonsmoking and regular exercise) that reduced their risk compared to participants with the lowest scores for social integration. This study emphasized the importance of psychosocial well-being as an important contributor to physical health and as an inhibitor of biological pathways that promote coronary heart disease (Chang et al., 2017).

STRESS‑TARGETED INTERVENTIONS FOLLOWING A HEART ATTACK If psychosocial stressors play a critical role in the occurrence of acute heart attacks, is it a good idea to have post-heart attack patients return to dealing with this plethora of stressors in the weeks and months following discharge from the hospital? If post-heart attack patients continue to experience high levels of stress, there is an increased risk of readmission to the hospital (de Albuquerque et al., 2020). As we will see in the next several studies, behavioral interventions have been developed to supplement standard cardiac rehabilitation programs, with an emphasis on developing strategies to aid patients in more effectively managing psychosocial stressors (Chauvet-­Galinier & Bonin, 2017).

Karolinska University Intervention In this study, 237 women (mean age = 62 years) who were treated at the Karolinska University Clinics for acute heart attacks, coronary artery bypass surgery, or placement of a stent(s) to open partially occluded coronary vessels were recruited to participate in a psychosocial intervention program to improve recovery. Four months after discharge from the hospital, participants were randomly assigned to the group-based psychosocial intervention (N = 112) or to a control group receiving usual care (CON, N = 125). The psychosocial intervention involved groups of four to eight women who met 20 times over a 1-year period to discuss cardiovascular risk factors, relaxation techniques, cognitive restructuring, coping with stress at home and at work, self-care, and medical compliance. The group members benefited from social bonding and mutual support and encouragement over the 1-year period of meetings. All participants were followed for an average of just over 7 years from the start of the intervention. During this time,

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25 control participants (20%) but only 8 psychosocial intervention participants (7%) died, pointing to a significant protective effect of the intervention even after controlling for use of medications (p < .01). These results could not be explained by differences between groups in demographic factors, acuity of initial diagnosis, risk profiles, or drug regimens. In addition, women in the two groups exhibited similar levels of life stressors at the start of the intervention. The mechanisms to explain this dramatic increase in survival in women in the psychosocial intervention group remain to be explored, but might include reduced levels of inflammation, sympathetic nerve activity, coagulation, and atherosclerosis (Orth-Gomér et al., 2009).

Duke University Intervention We have already seen that stressors can serve as triggers to increase the probability of an acute heart attack in susceptible individuals. What can be done to improve health outcomes for individuals who have experienced a significant cardiac event? A remarkable intervention study led by James A. Blumenthal of Duke University addressed this issue by incorporating a well-­developed stress management module within a standard cardiac rehabilitation program for patients with coronary heart disease. As we will see, a focus on stress management during cardiac rehabilitation enhanced survival significantly following an initial diagnosis of coronary heart disease (Blumenthal et al., 2016). Participants in this study were evaluated for levels of stress, traditional cardiovascular risk factors, and coronary heart disease biomarkers, and they were then randomly assigned to either comprehensive cardiac rehabilitation (N = 75) or cardiac rehabilitation plus stress management training (N = 76). A third group declined to participate in cardiac rehabilitation; individuals were randomly selected from this larger group (N = 75) and followed clinically. Cardiac rehabilitation was delivered over a 12-week period and involved aerobic exercise three times per week, education about coronary heart disease and nutrition, and two classes on stress. Stress management sessions were presented in 12 weekly 1.5-hour sessions in small groups of four to eight participants. The stress management sessions were structured based on a cognitive-­behavioral model, with life stressors presented as an imbalance between high demands and low coping resources. Emphasis was also placed on cognitive appraisal processes, anger management, effective problem solving, and related topics. Patients were followed for a median of 3 years, 2 months, and a maximum of 5 years, 3 months. The results clearly indicated that the cardiac rehabilitation plus stress management group had greater reductions in self-­reported stress levels compared to the cardiac rehabilitation only group, indicating the effectiveness of the stress management intervention. Reductions in stress levels in this group were attended by significant reductions in adverse cardiac-­related events compared to the cardiac rehabilitation group, including heart attacks, cardiac or peripheral vascular treatment, strokes, or unstable angina. Both groups receiving cardiac rehabilitation had significantly lower adverse event rates compared to the group that refused all treatment. As impressive as these results are, the sample sizes were quite small and were drawn from only two sites. In addition, the participants volunteered to be involved in the study and may have been more motivated to engage in the program than typical recovering patients. The stress measure was a composite of several other measures, and this aspect



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of the study could definitely be improved. In spite of these concerns, these results are sufficiently promising to warrant a multi-­center study with significantly larger sample sizes (Blumenthal et al., 2016).

Summary Nearly 50% of American adults have some form of cardiovascular disease, including coronary heart disease, heart failure, stroke, and hypertension. The majority of affected adults have hypertension, with cutoff values recently set at lower levels (Table 8.1) (Benjamin et al., 2019). Many adults with cardiovascular disease deal with psychosocial stressors on a daily basis. Given these extremely large numbers of affected individuals, small-group stress management workshops simply cannot handle this level of demand. When a physician is concerned about an individual patient’s stress levels or when someone feels the need for support in dealing with life stressors, web-based stress management programs offer an affordable and scalable solution (Chinnaiyan, 2019). In addition, when policymakers recognize the critical role of psychosocial stressors in the etiology of cardiovascular disease and other chronic conditions, changes may be made in areas that directly contribute to levels of stress for many adults (e.g., working hours and conditions, availability of childcare, opportunities for training and advancement, better public transportation, affordable housing) (Marmot, 2004).

STRESS AND HYPERTENSION One of the most frequently measured physiological variables in all of medical practice is blood pressure (BP). The first documented measurement of BP was reported by the English clergyman and scientist Stephen Hales (1677–1761), who built on the earlier findings of William Harvey regarding the heart and its role in the recirculation of blood (refer to Chapter 1). Noninvasive methods for measuring BP were first introduced in the mid-19th century and employed mercury manometers. The modern-­day sphygmomanometer for measuring BP noninvasively in humans is a relatively recent invention, appearing in various forms at the end of the 19th and the beginning of the 20th centuries (Booth, 1977). BP reflects the pressure of blood being forced through arteries by the contraction of the heart. Systolic BP (SBP) is the pressure in arteries when the heart contracts, and diastolic BP (DBP) is the pressure in arteries when the heart relaxes. The units of BP measurement are in mm of mercury (mmHg) and are reported as SBP/DBP. In 2018, the American College of Cardiology and the American Heart Association published major changes in clinical practice guidelines regarding resting BPs of adults (Whelton & Carey, 2018). As summarized in Table 7.2, normal adult BPs were set at an SBP of less than 120 mm Hg together with a DBP of less than 80 mm Hg. There are also categories for elevated BP and two levels of hypertension. These new guidelines will quickly be incorporated into clinical research protocols for studying risk factors for elevated BP and for hypertension. However, much of the existing literature will have prior thresholds for hypertension; this should be kept in mind as you consider the next series of studies of psychosocial effects on BP regulation.

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S t r e ss , H e a lt h , a n d B e h av i o r TABLE 7.2.  American Heart Association Guidelines for Normal and Elevated Blood Pressure and for Hypertension BP category

SBP

DBP

Normal

< 120 mm Hg

and

< 80 mm Hg

Elevated

120–129 mm Hg

and

< 80 mm Hg

Hypertension Stage 1 Stage 2

130–139 mm Hg ≥ 140 mm Hg

or or

80–89 mm Hg ≥ 90 mm Hg

Note. Values are presented for systolic (SBP) and diastolic blood pressure (DBP) in mm Hg for adults based on two or more BP determinations on two or more occasions. Details are provided in Whelton and Carey (2018).

A recent meta-­analysis of 48 randomized clinical trials of pharmacological BP-­ lowering medications versus placebo or other classes of BP-­ lowering medications revealed that a 5-mmHg reduction in basal BP resulted in a 10% reduction in risk of cardiovascular events, even when starting BPs were in what would have been considered the normal or high-­normal range. These findings were true for patients without a history of cardiovascular disease and for patients with a prior history of cardiovascular disease (Blood Pressure Lowering Treatment Trialists’ Collaboration, 2021). The World Health Organization estimates that more than 1.1 billion people in the world have hypertension (World Health Organization, 2021). In the United States alone, 50% of adults (108 million people) have hypertension. Although BP is easily measured, many people with hypertension remain undiagnosed, and as a result, their health status is placed at significant risk. There are several highly effective drugs for the treatment of hypertension, but many individuals who would benefit from these drugs are unaware that they need them or cannot afford them due to lack of prescription drug benefits or high co-pays. Hypertension develops over many years, and there are no overt signs that signal that BP is gradually increasing—­these are the slow and silent features of hypertension. As BP increases, the elasticity of blood vessels is diminished and may reduce the delivery of oxygenated blood to various tissues, including the heart. Elevated BP is a significant risk factor for heart and kidney disease and stroke; this is the deadly feature of hypertension. There are several risk factors for hypertension, including tobacco use, elevated intake of salt and fat in the diet, lack of regular exercise, and being overweight. Another important risk factor that is the focus of this section is psychosocial stress.

Baseline BP Measurements Imagine you are a single mother with two children and you have your yearly medical check-up scheduled for today at 10:00 A.M. You have canceled two previous visits because one of your children was sick, you have used up all of your personal time off from work, and it is only October. You are successful in getting your children out of bed, dressed, and fed in record time. You take them into their school, and they are happy to be back with their friends. You return to your car and turn the key and nothing



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happens—­dead battery. You remain calm and order an Uber, but there is a delay due to a major traffic jam leading into the city center. You arrive for your doctor’s appointment 20 minutes late, and the receptionist is less than welcoming. You are finally taken into an examining room, and you notice a text from your coworker: “Where are you? Our meeting starts in 10 minutes.” You realize you did not request time off for your appointment. At that moment, your nurse comes in to measure your BP and heart rate. You feel as if your head is going to explode as the cuff is inflated around your arm. This is one of many scenarios that plays out each day when adults go for clinic appointments with their doctors. Not all of these appointments are accompanied by racing around at home and traffic jams and sick children. But this level of chaos can affect baseline BP measurements at the point of care.

White‑Coat Hypertension Pickering et al. (1988) coined the term white-coat hypertension to describe individuals who have elevated BPs in a clinical setting but normal BPs at other times as measured by continuous ambulatory BP monitoring for 1 day. The white coat phenomenon was most evident when male physicians measured BPs and much less so when nurses or technicians measured BP. Of 292 patients with untreated borderline hypertension included in the report by Pickering et al. (1988), 21% had ambulatory daytime BPs that were within the normotensive range. Patients with white coat hypertension tended to be younger females who weighed less and had been diagnosed with hypertension for a shorter period of time than patients with stable hypertension. Patients with white coat hypertension did not appear to have greater levels of anxiety when they came into the clinic, and their BPs were consistently elevated over multiple clinic visits and did not display habituation. The authors suggested that the elevated BP levels may be explained by a classically conditioned response to stimuli associated with the first clinic visit that activates a pressor response on subsequent clinic visits.

Masked Hypertension The flip side of white coat hypertension is masked hypertension, which occurs when a patient has normal BP in the clinic setting but elevated BP based on ambulatory daytime BP monitoring or home BP monitoring. Anstey et al. (2017), in a review of the literature on masked hypertension, estimated that the prevalence of this phenomenon in population-­based studies ranged from 15–30% of adults with normal clinic BPs. In the United States, masked hypertension has a prevalence of 11–16%, with some variations among racial groups. Prior studies have documented that target organ damage (e.g., left ventricular hypertrophy and carotid artery arteriosclerosis) is as severe in patients with masked hypertension as in patients with hypertension based on clinic and ambulatory BP measurements. Given the millions of normotensive individuals in the United States, it is simply impractical to measure ambulatory or home BPs to screen for masked hypertension. Masked hypertension does tend to be more common in individuals who have poor scores on many of the standard risk factors for hypertension (history of smoking, higher BMI, less healthy diet, lower activity levels, etc.). It is possible that patients with masked hypertension are more relaxed in the clinic setting but more consistently reactive to the

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day-to-day stressors that they encounter in their lives. One way to identify such individuals is through wearable devices (e.g., smartwatches) that measure BP during the day and night.

Impact of Psychosocial Stressors on BP So many studies have examined the effects of psychosocial variables on BP regulation that it would be impossible to provide a summary of even a significant percentage of them (Sparrenberger et al., 2009; Spruill, 2010). Instead, in the sections that follow, I will provide overviews of some important and well-­designed studies to illustrate the effects of various psychosocial stressors on BP levels in adults.

Hostile and Impatient The Coronary Risk Development in Young Adults (CARDIA) study was a multi-­center prospective study of 3,308 young adults (18–30 years of age at the start of the study in 1985–1986), with five follow-­up data collections through 2001. Efforts were made at each data collection site to recruit and retain up to year 15 a participant sample balanced by sex (56% female) and race (44% African American). Five psychosocial measures were taken: (1) hostile attitudes in Years 0 and 5, (2) time urgency/impatience and achievement striving/competitiveness in Year 0, and (3) depression and anxiety in Year 5. The incidence of hypertension in year 15 (defined as SBP ≥ 140 mm Hg, DBP ≥ 90 mm Hg or taking antihypertensive medication) was 15%, up slightly from 13.6% in Year 5. After adjusting for standard risk factors for hypertension, both hostility and time urgency/impatience were significantly associated with development of hypertension in Year 15. Those scoring highest for hostility had an adjusted odds ratio of 1.84 (95% CI = 1.33–2.54) compared to the lowest scoring group. Those scoring highest for time urgency/impatience had an adjusted odds ratio of 1.84 (95% CI = 1.29–2.62) compared to the lowest scoring group. In addition, there was a dose–­response relationship for hostility and time urgency/impatience on hypertension, with incidence of hypertension increasing with each quartile increase in the two behavioral measures. Measures of achievement striving/competitiveness, depression, and anxiety did not have significant effects on the development of hypertension in Year 15. There are several limitations in the design of this study. Behavioral measures were taken at different times, and there were inconsistencies across measures. In addition, measures of BP were a single time for each follow-­up data collection rather than multiple measures at each follow-­up or ambulatory monitoring of BP. Finally, the study was underpowered to determine race- and sex-­specific risk estimates. In spite of these limitations, this important study demonstrated a clear impact of psychosocial factors on the development of hypertension (Yan et al., 2003).

Job Strain A quantitative meta-­analysis of 22 cross-­sectional studies of job strain and ambulatory SBP and DBP was reported by Landsbergis, Dobson, Koutsouras, and Schnall (2013). Their findings indicated that job strain was associated with increases in SBP (3.43 mm Hg) and DBP (2.07 mm Hg). In men, there were significant associations between job



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strain and ambulatory BPs measured at work, at home, and while asleep. In women, however, the only significant association was between job strain and SBP at work. All data for men and women were adjusted for standard risk factors for hypertension. There was also evidence in support of a dose–­response relationship between increasing levels of job strain and increasing levels of ambulatory BP. Interventions to address the adverse effects of job strain on workers would require large-scale interventions by workplace managers and by regulatory authorities, and these efforts are unlikely to occur (Landsbergis et al., 2013).

Social Isolation and Loneliness Individuals who are socially isolated have few relationships with others and infrequent social contacts. In contrast, loneliness reflects a subjective feeling of being alone due to a mismatch between one’s desired level of social contacts versus the actual level. Loneliness can have serious negative effects of overall physical and mental health and increases the risk of all-cause mortality (Holt-­Lunstad, 2021). In a prospective study of a diverse group of male and female adults who were 50–68 years old, Hawkley, Thisted, Masi, and Cacioppo (2010) reported that those participants with the highest starting levels of loneliness as measured by the revised UCLA Loneliness Scale displayed the greatest increases in SBP over the 4-year study period (p < .05). Importantly, the effects of loneliness on SBP persisted after adjusting for previous health conditions; levels of depression, hostility, social support, and perceived stress; medications; and cardiovascular risk factors.

Depression In the report by Yan et al. (2003) summarized above, depression scores did not exert a significant influence on BP levels in the CARDIA study. A more detailed study of the effects of depression on BP was summarized by Patten et al. (2009) based on their analyses of data from the Canadian National Population Health Survey of 12,270 individuals who did not report a diagnosis of high BP or the use of antihypertensive medications at the initiation of the study in 1994. Over a 10-year follow-­up period with assessments at 2-year intervals, participants with and without major depression (based on the Composite International Diagnostic Interview Short Form) were compared for incidence of elevated BPs. After adjusting for age and other risk factors, the chance of developing high BP was increased in participants with major depression (HR = 1.6, 95% CI = 1.2–2.1). An obvious concern in the clinical management of patients is that depression may exacerbate some risk factors for hypertension, including perceived levels of stress, weight gain, reduced exercise, increased tobacco use, and increased intake of alcohol (Patten et al., 2009).

Summary In this brief overview of psychosocial factors and hypertension, an individual psychosocial factor was the focus of each study. In reality, individuals face a shifting tide of psychosocial stressors over time, and some periods are worse than others. What is clear from these and many other studies is that a range of life stressors can impact

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BP regulatory systems and lead to progressive increases in resting BPs that approach or exceed levels that meet the criteria for hypertension. Hypertension is a significant risk factor for heart attacks, stroke, kidney disease, and other medical conditions that increase morbidity and mortality. Providing at-risk individuals with strategies to manage psychosocial stressors more effectively could increase quality of life for many adults.

STRESS‑TARGETED INTERVENTIONS AND HYPERTENSION Given the impact of psychosocial stressors on BP levels, it would appear that behavioral interventions to enhance stress management skills in patients with elevated BPs would be an effective therapeutic approach to manage hypertension. Following are the results of two stress management interventions that demonstrate the promise of this approach.

Not Quite Personalized Stress Management Linden, Lenz, and Con (2001) conducted a small intervention trial with 60 male and female participants (mean age = 55 years) whose BPs exceeded 140/90 mm Hg. Participants were randomly assigned to an immediate stress management program or to a wait-list control group. Eventually, participants in the wait-list control group were offered entry into the stress management program. To the extent possible, the stress management program was delivered in 10 weekly 1-hour sessions and was somewhat tailored to the needs of each participant based on an intake interview with a therapist. BP was measured by an ambulatory BP monitoring device prior to and at the end of the stress management program and at a 6-month follow-­up. A total of 36 participants in the stress management program were available for the 6-month follow-­up. Compared to wait-list controls, participants immediately following completion of the stress management program had greater reductions in ambulatory SBP (–6.1 vs. +0.9 mm Hg) and DBP (–4.3 vs. 0.0 mm Hg). A similar pattern was true at the 6-month follow-­up for ambulatory SBP (–12.5 mm Hg) and DBP (–9.9 mm Hg) in participants who completed the stress management program. The results of this study are intriguing, but the sample sizes were quite small and precluded detecting meaningful changes in psychosocial measures. The sustained decreases in ambulatory BPs were substantial given the modest level of stress management training and warrant follow-­up studies with larger numbers of participants (Linden et al., 2001).

Stress Management in the Workplace Stress reduction interventions may be ideally suited for implementation in a workplace setting because of greater access by employees during normal working hours. Employers have placed greater emphasis on wellness programs in workplace settings in recent years; adding a stress management program would be consistent with this emphasis on employee well-being. Clemow et al. (2018) presented the effects on BP of 10 weekly 1-hour cognitive-­behavioral coping skills training sessions for groups of 8–10 participants per site. Controls received information about the management of hypertension, but they did not meet in small groups. Following initial BP screening of employees at an academic medical center, individuals were identified with SBPs/DBPs in the following



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range: ≥ 140/90 mm Hg and < 180/110 mm Hg. Forty-one controls and 40 participants in the intervention group completed the 10-week program. The mean age of all participants was approximately 48 years, and more than 70% were female. The mean number of intervention sessions completed was 8.1 out of 10. Two months after the final intervention sessions, mean SBP in controls decreased modestly (–1.7 mm Hg), while in the intervention group, SBP decreased significantly (–9.1 mm Hg). DBP changes were similar in controls and intervention group participants. Although this study included a relatively small sample size and automated BP measures were not confirmed with ambulatory BP measures, the results are encouraging and point to workplace interventions for delivering a standardized cognitive-­behavioral intervention as a promising avenue for behavioral modification of elevated BP (Clemow et al., 2018).

CONCLUSIONS Cardiovascular diseases, especially heart attacks and hypertension, have retained their ranking as the number one cause of morbidity and mortality in the world. In this chapter, we have explored multiple connections between real-life stressors and disability and death, with a focus on heart attacks and high BP. Intense stressors can precipitate the onset of a heart attack, as has been documented in many studies, ranging from experiencing an earthquake, a terror attack, or a disappointing defeat of a favorite sports team as well as being diagnosed with cancer and/or depression. Hypertension tends to affect individuals over a longer timescale, and many individuals are unaware that they have sustained elevations in BP for many years. An encouraging aspect of the research on psychosocial stressors and cardiovascular diseases is the apparent effectiveness of interventions to reduce perceived levels of stress in patients. These interventions have been tested in patients following a heart attack as well as in patients with sustained elevations in BP. A future challenge is to develop scalable interventions through web-based or smartwatch platforms, given the overwhelming number of individuals who have been diagnosed with coronary heart disease or hypertension (Hughes, Serber, & Kuhn, 2022).

CHAPTER 8

Stress and Diabetes

T

here are three primary types of diabetes: type 1 diabetes (insulin-dependent or juvenile onset; T1D), type 2 diabetes mellitus (non-insulin-dependent; T2DM), and gestational diabetes (GDM). The focus of this chapter will be solely on the relationship between stressful life events and the onset and progression of T2DM, which accounts for approximately 90% of all cases of diabetes. I will not present findings on stress and T1D or GDM; however, the interested reader may wish to consult the relevant literature, including these references for T1D (e.g., Hagger, Hendrieckx, Sturt, Skinner, & Speight, 2016; Jaser, Patel, Xu, Tamborlane, & Grey, 2017; Korczak, Pereira, Koulajian, Matejcek, & Giacca, 2011; Sharif et al., 2018) and these references for GDM (Braig, Logan, Reister, Rothenbacher, & Genuneit, 2020; Daniells et al., 2003). Diabetes is a chronic disease that exacts a heavy toll on quality of life, health care costs, and morbidity and mortality in countries around the globe (Pillon, Loos, Marshall, & Zierath, 2021). The International Diabetes Federation (IDF), using an agestandardized range of 20–79 years of age, estimated that 463 million people worldwide were living with diabetes in 2019, representing a prevalence of 9.3%. This represents an increase of more than 200% compared to data from 2000. Of great concern is the fact that 50% of people who have diabetes are not even aware they have the disease. An additional 374 million people have impaired glucose tolerance (7.5%), a risk factor for later development of T2DM. By 2030, the IDF estimates that 578 million people will have diabetes, with the global prevalence increasing to 10.2%. Data on prevalence of diabetes in the United States are just as sobering. In 2019, 31 million Americans had diabetes (7.2 million were undiagnosed), with a projected increase to 34.4 million by 2030 (11% increase) (Saeedi et al., 2019; Wang et al., 2021). In 2019, diabetes was the cause of approximately 4.2 million deaths, or 11.3% of all deaths globally. More than 45% of these deaths occurred in people under the age of 60, with more diabetes-associated deaths in women than men. In the United States in 2017, more than 83,000 death certificates listed diabetes as the underlying cause of death. In 270,000 other cases, diabetes was listed as a contributor to death. The connections 154



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between T2DM and morbidity and mortality are related in part to the increased risk of various cardiovascular and kidney diseases in individuals with T2DM. Globalization, economic development, urbanization, and aging of the population have combined to elevate T2DM as an international public health crisis. As income levels increase and more people move into urban areas, there is a corresponding reduction in physical activity; increased intake of a diabetogenic diet rich in processed meats, fats, and refined grains and sugars (especially sweetened beverages); and higher levels of obesity.

WHY IS REGULATION OF BLOOD GLUCOSE SO IMPORTANT? As we saw in Chapter 1, Walter B. Cannon appreciated the critical role played by epinephrine in stimulating glucose release from the liver into the circulation during exposure of animals and humans to acute stressors. Glucose provides energy to skeletal muscles during fight-or-­f light challenges, and it is the energy source preferred by the brain. But too much glucose over long periods of time can be damaging to blood vessels and peripheral nerves, and can increase the risks of eye, heart, and kidney diseases, atherosclerosis, and stroke (Figure 8.1).

FIGURE 8.1.  Regulation of blood glucose by the actions of the pancreatic hormones, insulin and glucagon. Blood glucose levels are also affected by cortisol (CORT) and epinephrine (EPI) from the adrenal gland. Excess glucose is stored in the liver as glycogen.

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Blood glucose is typically maintained within relatively narrow limits in healthy individuals. Key components of the regulatory processes are insulin and the counterregulatory hormones (glucagon, epinephrine, cortisol, and growth hormone), which store excess glucose during times of plenty and maintain adequate levels of glucose in blood during fasting. In addition, sympathetic, parasympathetic, and sensory nerve fibers that innervate the pancreas, liver, and fat cells also contribute to glucoregulatory processes (Lin, Scott-­Solomon, & Kuruvilla, 2021). When these tightly controlled regulatory processes are dysregulated, morbidity and mortality increase over time.

Factors Influencing Blood Glucose Levels Insulin is a peptide hormone produced by b cells of the endocrine pancreas. The primary stimulus for insulin secretion is an elevation in circulating levels of glucose, especially following ingestion of a meal. Insulin binds to its membrane-­bound receptor on target cells, resulting in intracellular phosphorylation of a series of enzymes and other proteins. In addition, the insulin-­receptor complex is internalized where it may be degraded or recycled back to the cell membrane. Insulin also down-­regulates its membrane-­bound receptor by decreasing rates of synthesis and increasing rates of degradation. Finally, intracellular insulin binds to elements in DNA to regulate gene transcription. Glucose is a water-­soluble molecule and is unable to cross the membranes of target cells or the blood–brain barrier without facilitated transport made possible by glucose transporter molecules embedded in the plasma membrane. When nutrient availability exceeds an individual’s metabolic needs, the actions of insulin ensure that excess nutrients are stored as (1) glycogen in liver cells, (2) fat in adipose cells, or (3) protein in muscle cells. These actions of insulin during times of plenty have certainly been subject to positive selection pressure over evolutionary time, as food availability was not always guaranteed for most animal species, including humans. But storage of excess nutrients is a double-­edged sword, with one edge favoring survival and the other edge leading to increased morbidity and mortality. Among insulin’s many actions on target cells are the following:

• Increases glucose transport into muscle and fat cells by stimulating the insertion of glucose transporters into the cell membrane.

• Enhances the synthesis of glycogen from glucose in liver and muscle cells while inhibiting the breakdown of glycogen. • Inhibits the synthesis of glucose. • Increases the storage of fatty acids and inhibits their breakdown. • Increases amino acid and protein uptake into target cells and inhibits breakdown of proteins.

Collectively, these effects of insulin on target tissues are designed to enhance the storage of energy sources in the form of glycogen, fats, and proteins. If limited food availability occurs at some point in the future, these stored forms of energy are rapidly mobilized to maintain relatively stable levels of circulating glucose to support energy needs of the brain, muscles, and other tissues. Table 8.1 summarizes the normal range for blood glucose after an overnight fast as well as 2 hours following an oral glucose tolerance test in healthy individuals, in



Stress and Diabetes 157 TABLE 8.1.  Regulation of Glucose Levels in Healthy Individuals and Individuals with Prediabetes and T2DM Based on Standards Established by the American Diabetes Association Measure

Healthy controls

Prediabetics

T2DM

Blood glucose (mg/dl)

70–99

100–125

> 125

Blood glucose (mg/dl) after oral glucose tolerance test

< 140

140–199

> 199

HbA1c (%)

< 5.7

5.7–6.5

> 6.5

Note. T2DM, type 2 diabetes mellitus; HbA1c, glycated hemoglobin.

prediabetics, and in individuals with T2DM. As blood glucose levels increase, the percentage of hemoglobin molecules that are chemically linked to glucose increases. The lifespan of a typical red blood cell is 4 months, but this length of time varies, so that levels of glycolated hemoglobin (HbA1c) reflect how well an individual has regulated glucose levels in the preceding 2–3 months. However, HbA1c levels may represent an over- or underestimate of actual glucose levels measured by continuous glucose monitoring and should be interpreted with caution (Beck, Connor, Mullen, Wesley, & Bergenstal, 2017).

The Ups and Downs of Blood Glucose Insulin plays an essential role in removing glucose from the circulation. It is so effective, in fact, that too much insulin can result in loss of consciousness because of the precipitous drop in glucose availability for the brain. There are several counterregulatory mechanisms for elevating blood glucose levels so that critical tissues, including the brain, receive adequate levels of glucose even during times of limited nutrient availability. These include the following:

• Alpha cells of the endocrine pancreas synthesize and release glucagon, a peptide hormone that is secreted when blood glucose levels decrease. In addition, glucagon is secreted following ingestion of protein. The primary actions of glucagon are to enhance the breakdown of glycogen to glucose, inhibit the formation of glycogen from glucose, and increase blood fatty acid levels. • Epinephrine is released from the adrenal medulla during exposure to stressful stimuli and increases the breakdown of glycogen to glucose in the liver. The effects of epinephrine on glycogenolysis in liver cells are mediated by b2-adrenergic receptors. • Cortisol stimulates the synthesis of glucose from noncarbohydrate sources (gluconeogenesis) by increasing the breakdown of protein in muscle cells and inhibiting new protein synthesis. In addition, cortisol stimulates the breakdown of fats, providing additional glycerol for the synthesis of glucose in the liver. Finally, cortisol reduces the utilization of glucose by tissues and decreases the sensitivity of fat cells to insulin. Taken together, these multiple actions of cortisol play an essential role in survival during times of limited food availability.

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• Growth hormone (GH) released from the anterior pituitary gland also has an impact on regulation of glucose metabolism. Growth hormone increases gluconeogenesis and glycogenolysis in the liver and decreases glucose uptake into fat cells. In addition, growth hormone reduces the sensitivity of peripheral target tissues to the effects of insulin (refer to Figure 8.1). T2DM Pathophysiology In T2DM, insulin receptors in target tissues are downregulated, such that normal levels of insulin released from pancreatic b cells are no longer sufficient to produce the desired metabolic effects. In such instances, blood glucose levels remain elevated, sometimes dangerously so, during fasting as well as following ingestion of a meal. Over time, high levels of glucose in blood can result in damage to small blood vessels, arteries, and nerve cells. Collectively, these vascular and neural complications can lead to kidney damage, impaired vision, cardiovascular disease, and damage to neurons innervating the feet and hands. The damage to peripheral nerves is associated with impairments in sensory function and wound healing, which may result in amputations (Forbes & Cooper, 2013). If obese patients and individuals with a first-­degree relative with T2DM are followed longitudinally, they display an initial state of insulin resistance that is compensated for by elevated secretion of insulin from pancreatic b cells. Over time, insulin resistance in target tissues remains elevated but pancreatic b cells are unable to sustain the hypersecretion of insulin. When T2DM is finally diagnosed, blood glucose levels are consistently elevated and pathological changes are already underway. During the development of obesity, excess fat accumulates in subcutaneous tissues, especially in the abdomen. As the capacity of subcutaneous tissues to store fat is reached, fat is shunted to other tissues, including the liver, pancreas, muscle, and pericardium. Accumulation of excess fat in these tissues may precede a diagnosis of T2DM by many years and contributes to a further decline in sensitivity to insulin (Zaccardi, Webb, Yates, & Davies, 2016). An emerging area of research concerns the effects of gut signaling molecules and the gut microbiome on glucose regulation. Details of these gut regulatory circuits are presented in Chapter 9.

METABOLIC SYNDROME Metabolic syndrome is typically defined as a complex of the following cardiovascular and T2DM risk factors:

• Abdominal obesity • Insulin resistance • Elevated BP • Elevated blood triglycerides • Reduced HDL (good) cholesterol Although the metabolic syndrome started as a disorder more frequently diagnosed in developed countries, it is now an issue of global concern, with greater increases in urban areas of developing countries than in their developed counterparts. An unhealthy



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combination of factors interacts with genetic susceptibility to increase the risk of the metabolic syndrome, including a sedentary lifestyle, a high-­ calorie–­ low-fiber diet, and smoking. Of special concern in developing countries and in many communities in the United States is the aggressive marketing and increased availability of relatively inexpensive, high-­calorie fast-food choices, including sugar-laden drinks (Christian & Gereffi, 2010). There are clear indications that the prevalence of the metabolic syndrome increases with age in adults. However, given the increasing rates of obesity in children and adolescents, the metabolic syndrome may also be present, though largely undiagnosed, in children. Nondiabetic individuals with the metabolic syndrome also displayed increased risk for all-cause mortality as well as mortality from cardiovascular disease and stroke (Grundy, 2016). The prevalence of metabolic syndrome globally is difficult to estimate given differing national and regional definitions. One reasonable estimate is that metabolic syndrome is about three times more prevalent than T2DM. If this relationship holds true, there are more than 1.75 billion people globally with metabolic syndrome. This staggering figure will be a major public health challenge for many developed and developing nations in the coming decades (Saklayen, 2018). Unfortunately, there is no magic pill to cure the metabolic syndrome. Rather, the challenge for individuals who fall into this diagnostic category is to commit to major changes in lifestyle and behavior that must be maintained throughout one’s lifetime. These changes include strict regulation of caloric intake, with reduction in saturated fats and carbohydrates combined with a modest initial goal of reducing body weight by 10%. A regular program of physical activity is also an essential component for successfully managing risk factors associated with metabolic syndrome. A statin is useful in reducing circulating low-­density lipoproteins (LDLs) and decreasing the risk of cardiovascular disease. Finally, a compelling argument has been made that nutritional management of metabolic syndrome will be more effective if treatments are personalized and take into account specific risk gene variants present in each patient (de Toro-­ Martin, Arsenault, Després, & Vohl, 2017). Some individuals who are obese have a lower risk of developing cardiovascular or diabetic complications. Individuals who exhibit metabolically “healthy” obesity tend to maintain normal levels of insulin sensitivity and pancreatic b cell function, reduced fat deposition in the viscera and liver, and higher fat deposition in the legs. In spite of their relatively healthy state, metabolically obese individuals are still at higher risk of medical complications than healthy controls and should be encouraged to reduce their body weight as part of a long-term plan to improve health and well-being (Blüher, 2020).

CONTRIBUTIONS OF GENES AND ENVIRONMENT TO T2DM In a classic study, Schultz et al. (2006) designed an experiment to test the theory that T2DM results from an interplay between genetic susceptibility and a lifestyle associated with unfavorable environmental factors. They were impressed by the starkly different health outcomes of Pima Indians from the Sierra Madre Mountains of Sonora state in the northwestern portion of Mexico versus those members of this ethnic group who live on the Gila River Indian Reservation south of Phoenix. Genetic analyses have shown that Mexican and U.S. Pima Indians are closely related and share a common gene pool

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that is distinct from other Native American groups. In this study, T2DM was confirmed by an oral glucose tolerance test, and participation rates in the three groups were substantial. Pima Indians living in Mexico have low rates of T2DM, but Pima Indians living in Arizona have the world’s highest rates of T2DM. The strikingly higher rates of T2DM in U.S. Pima Indians appear to result from an interaction of genetic risk factors with a toxic combination of environmental factors, including a significant reduction in regular physical activity at work and during leisure activities and a diet that is much higher in fat and lower in fiber. These changes in lifestyle and diet are reflected in the elevated body mass indexes (BMIs) of U.S. Pima Indians. These findings provide powerful support for the view that a strong genetic predisposition to develop T2DM can be managed with rigorous attention to diet and levels of physical activity that are characteristic of Pima Indians living in Mexico (Schultz et al., 2006). As we will see in the sections that follow, psychosocial stressors also appear to be critical and largely modifiable risk factors that contribute to the pathophysiology of T2DM.

STRESS AND T2DM In the sections that follow, I will provide evidence that stress plays an important role in the etiology of T2DM by highlighting key studies in several areas. To begin, I will summarize a study comparing responses to acute stressors in healthy controls and individuals with T2DM under highly controlled laboratory conditions. Next, a series of studies will be presented relating the impact of life stressors and work stress on the development of T2DM. I will then discuss the bidirectional relationship between depression and T2DM and their combined influence on heart disease. Finally, I will provide three examples of intervention studies designed to reduce stress and improve health outcomes in individuals with T2DM.

A Laboratory Study of Stress and T2DM Steptoe et al. (2014) tested the hypothesis that individuals with T2DM have disruptions in regulation of multiple stress-­responsive neural, endocrine, and immune systems associated with an increase in allostatic load. They recruited adult males and females with a confirmed diagnosis of T2DM (N = 140) from clinics in the London area who were free from coronary heart disease, allergies, inflammatory diseases, and mood disorders. Healthy controls (N = 280) were matched on age, sex, and income level and had an HbA1c of ≤6.5% with no evidence of impaired glucose tolerance. Participants were brought into the laboratory and exposed to two 5-minute stressors, a computer-­based version of the Stroop color–word task and a mirror-­drawing task. Subjective ratings of stress increased significantly from baseline to the time following exposure to the two stressors, but the increase between diabetics and controls was similar. Several physiological, endocrine, and immune parameters differed between diabetics and controls under baseline conditions and following exposure to the two stressors. Systolic blood pressure (SBP) responses to the stressors were blunted in diabetics compared to controls, but the rate of recovery of SBP toward baseline was reduced in diabetics up to 75 minutes poststress. For diastolic blood pressure (DBP), baseline values



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were lower, the responses to the stressors were blunted, and the recovery to baseline was reduced in diabetics compared to controls. Baseline heart rates of diabetics were higher than controls, and diabetics displayed blunted responses to the stressors and slower rates of recovery of heart rates toward baseline values relative to controls. Salivary cortisol levels were significantly higher at baseline in diabetics compared to controls. Following exposure to the stressors, salivary cortisol levels decreased in diabetics but increased in controls. Plasma IL-6 levels were also higher at baseline in diabetics, and levels increased immediately following stressor exposure. However, plasma IL-6 levels were diminished at 45 minutes and 75 minutes poststress in diabetics relative to controls. At all timepoints, salivary cortisol and plasma IL-6 levels were higher in diabetics compared to controls. The reverse was true for total cholesterol levels, with controls exhibiting higher mean levels at all sampling timepoints. For diabetics, the increase in total cholesterol following stressor exposure was reduced relative to controls, as was the rate of recovery toward baseline levels. Finally, a battery of behavioral measures revealed that diabetics reported more depressive symptoms, higher levels of hostility, more financial strain, less social cohesion in their immediate neighborhoods, a reduced sense of control over their lives, and less optimism compared to healthy controls. Diabetics were more likely to be separated, divorced, or widowed than controls. Diabetics did not differ from controls in levels of social support or in their frequency of providing care for aging or disabled family members. This laboratory experimental study is noteworthy for quantifying cardiovascular, neuroendocrine, immune, and psychosocial parameters obtained following an acute stressor and for drawing on the concept of allostatic load to interpret how stress might influence the development of T2DM. These investigators provided evidence consistent with disruptions in multiple neural, endocrine, and immune parameters under basal conditions and reactivity and recovery following exposure to acute stressors as described by McEwen (1998) for allostatic load. In addition, this report emphasized the need to consider how stress-­responsive neural, endocrine, and immune systems might contribute to the hallmark features of T2DM, elevations in blood glucose and reductions in insulin sensitivity. However, the cross-­sectional design of the experiment precludes an assessment of cause and effect, and disruptions in stress responses could precede the onset of T2DM or could be a consequence of the onset of the disease. In addition, participants were only exposed to the two stressors on one occasion, and surprisingly, glucose and insulin levels were not measured. In spite of these concerns, this study represents a major step forward in understanding the role of life stressors in the pathophysiology of T2DM, and it suggests new avenues for biobehaviorally based treatments (Steptoe et al., 2014).

Life Stressors and T2DM Kobe, Japan, Earthquake of January 17, 1995 This magnitude 7.2 earthquake, described in Chapter 7, resulted in significant loss of life and widespread damage to property. Given the dramatic and unexpected rise in stress levels during and after the earthquake, a group of investigators sought to quantify the impact of this high level of stress on glycemic control in individuals previously

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diagnosed with T2DM (Inui et al., 1998). To quantify glycemic control, these investigators measured blood levels of HbA1c in 157 diabetic outpatients in Kobe and compared their results with a group of 277 diabetic outpatients in Osaka, where damage from the earthquake was minor. HbA1c levels were measured approximately 2 months after the earthquake and were compared to values obtained prior to the earthquake. Scores on the General Health Questionnaire (GHQ) were employed as a measure of psychosocial stress. The results of this study indicated that GHQ scores and HbA1c levels 2 months after the earthquake were significantly higher in diabetics from Kobe compared to diabetics from Osaka. In a separate group of T2DM outpatients in Kobe followed immediately before and each month after the earthquake, HbA1c levels peaked in April and May and then started a slow return to pre-­earthquake levels. These results on stress-­related disturbances in glycemic control in diabetics are consistent with similar research summarized in Chapter 7 on increased rates of myocardial infarction following the Kobe earthquake.

Prospective Study of Swedish Men This study examined the effects of life stressors on the development of T2DM in a sample of Swedish men (Novak et al., 2013). This sample of participants was derived from the Primary Prevention Trial Study, which collected data on all men living in Gothenburg, Sweden, in 1970 who were born between 1915 and 1925 (with the exception of 1923). Baseline screening of all participants took place between January 1970 and March 1973 and included a mailed questionnaire that assessed perceived stress levels in a single item. Stress was defined as “feeling tense, irritable or filled with anxiety, or having sleeping difficulties as a result of conditions at work or at home.” Possible responses on a 6-point scale were (1) never experienced stress, (2) some periods of stress, (3) several periods of stress in the past year, (4) several periods of stress in the past 5 years, (5) permanent stress in the past year, and (6) permanent stress over the past 5 years. Other standard risk factors for cardiovascular disease and T2DM were also measured. All participants were followed until December 31, 2008, or death, and those with a diagnosis of T2DM were identified using International Classification of Diseases codes on death registries or health records. Over the 35-year follow-­up period with this cohort, 899 out of 6,828 men (13.2%) received a primary or secondary diagnosis of T2DM. The initial assessment revealed that 16% of participants reported permanent stress related to conditions at work or home (ratings 5 and 6). After adjusting for age and competing risk of death, the estimated 35-year conditional probability of T2DM associated with permanent stress was 43%, compared with 31% for those with periodic stress (ratings 3 and 4) and 31% with little or no stress (ratings 1 and 2). After adjusting for age and standard risk factors, participants with stress ratings of 5 or 6 had a significantly higher risk of T2DM (HR = 1.45, 95% CI = 1.20–1.75) compared to those with stress ratings of 1 or 2 [HR = 1.00] and stress ratings of 3 or 4 (HR = 1.09, 95% CI = 0.94–1.27). This study had several strengths, including a large sample size with a 35-year follow-­up and reliance on national health and death registries for details on medical diagnoses and causes of death. A major limitation was that the sample was made up exclusively of males. In addition, a more fine-­grained assessment of stress levels at several



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intervals would have been preferred. However, the findings pointed to a strong relationship between life stressors over a 35-year period and the later incidence of T2DM.

Health and Retirement Study The Health and Retirement Study (HRS) includes a representative sample of approximately 20,000 Americans 50 years of age or older as well as their spouses or partners. Participants are interviewed every two years and asked a range of questions relating to health status, cognitive functioning, financial planning, and employment status. In this study examining the contribution of stressful life events to the onset of T2DM, data were collected from the 2006–2014 interviews and included a 17-item questionnaire that was completed and returned by mail. The interview inquired about stressful life experiences (11 questions related to lifetime stressors and 6 questions related to stressors experienced over the previous 5 years). A total of 7,956 individuals were included in the study who were initially interviewed in 2006 or 2008, had not received a diagnosis of T2DM, and completed the stressful experiences questionnaire (Smith et al., 2020). From 2006 to 2014, 833 (10.5%) of the participants were diagnosed with T2DM. In general, there was a progressive increase in cases of T2DM as frequency of lifetime or recent stressful events increased. There were significant associations between lifetime stress scores, recent stress scores, and combined stress scores and risk of developing T2DM. These findings emphasize the importance of considering the impact of proximal and distal stressors in the development of T2DM, especially those stressors that occur in middle age (> 50 years of age) (Table 8.2). The findings of this prospective study demonstrate clearly that standard risk factors and stressful life events interact with genetic susceptibility in a dynamic fashion over many decades to result in a diagnosis of T2DM. The study results were derived from a large sample of individuals who had not yet been diagnosed with T2DM. It would have been desirable to include relevant biomarkers associated with the development of T2DM and to have a longer follow-­up period, as some individuals in the study were only tracked for 6 years (2008–2014). However, these findings point to a significantly increased risk of T2DM in individuals exposed to life stressors and suggest that interventions to improve management of life stressors may be beneficial in delaying or preventing the development of T2DM (Smith, Miles, et al., 2020). TABLE 8.2.  Adjusted Hazard Ratios and 95% Confidence Intervals for the Association between Diagnoses of T2DM and Stress Measures from the Health and Retirement Study (2006–2014) Stress measure

HR (95% CI)

Significance

Lifetime stress score (range 0–11)

1.05 (1.00, 1.09)

p < .04

Recent stress score (range 0–6)

1.23 (1.12, 1.36)

p < .0001

Lifetime + recent stress scores (range 0–17)

1.06 (1.03, 1.11)

p < .0011

Note. T2DM, type 2 diabetes mellitus; HR, hazard ratio; CI, confidence interval. All data were adjusted for sex, race, marital status, comorbidity index, BMI, smoking status, and retirement status. Data are summarized from Smith et al. (2020) and used with permission of the publisher.

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Summary The complex relationship between life stressors and T2DM was illustrated in these three studies. The first study demonstrated a transient disruption in glycemic control among diabetic patients following the Kobe earthquake of 1995. The second prospective study of Swedish men was notable for its 35-year follow-­up period, and the results clearly pointed to a significant association between high levels of stress at home and at work and the development of T2DM. Finally, the HRS findings emphasized the long timeline during which stressful life experiences interact with a susceptible genotype over many years to ultimately result in a diagnosis of T2DM.

Work Stress and T2DM Whitehall II Study This prospective study probed the relationship between work-­related stressors and the development of T2DM in more than 10,000 male and female civil servants working in London, United Kingdom (Kumari, Head, & Marmot, 2004). Baseline data were collected between 1985–1988 and follow-­up data were collected in 1989, 1992–1993, 1995, and 1997–1999, with glucose tolerance tests administered during 1992–1993 and 1997–1999. A battery of questionnaires was administered to quantify psychosocial stress measures, and data were collected on standard risk factors for T2DM (e.g., BMI, BP, levels of exercise, amount of smoking). The average length of follow-­up was 10.5 years for 8,386 participants who made it through to the final assessments in 1997–1999. There was a social gradient in the incidence of T2DM for British civil servants such that those in lower-level clerical jobs had higher rates of T2DM than those in higher-­ level executive and administrative positions. The effects of effort–­reward imbalance, a major work-­related stressor, had a significant effect on prevalence of T2DM in male civil servants (OR = 1.71, 95% CI = 1.0–2.8) but not in females after controlling for standard risk factors. This Whitehall II study included a significant number of male and female participants who were followed for an average of slightly more than a decade. T2DM was diagnosed by an oral glucose tolerance test, which may have picked up undiagnosed cases of the disease in some participants. The concept of effort–­reward imbalance has been important in understanding the health effects of job-­related stressors (Siegrist, 1996). These results for T2DM are generally consistent with the results for cardiovascular diseases as reported in Chapter 7.

Swedish National Study A study by Pan, Xu, Mangialasche, Fratiglioni, and Wang (2017) took a broader view of work-­related psychosocial stressors in their prospective study of 2,713 participants (≥ 60 years of age, mean age = 73 years) from the larger Swedish National Study on Aging and Care in Kungsholmen (SNAC-K) who had not received a diagnosis of T2DM at the start of data collection. A participant was defined as having T2DM based on an HbA1c value ≥ 6.4%, self-­reported use of diabetic medicines, or a diagnosis of T2DM in the participant’s medical records. Work stress was assessed by an interview at baseline regarding job control, job demands, and job support for the five longest-­held jobs



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over the participant’s career. Additional measures of health status, medical history, and hours per week spent doing household chores were also obtained. Over the course of this study, 154 participants developed T2DM. Elevated work stress was associated with a diagnosis of T2DM in the 60-year-old cohort for female participants (OR = 6.18, 95% CI = 1.22–31.26), but not for males. If the added stress of household chores was factored in, a more pronounced risk of T2DM was evident in female participants who were 60 years old at baseline after adjustment for lifestyle and medical risk factors (OR = 9.45, 95% CI = 1.17–76.53). Work stress experienced prior to age 40 appeared to exert a greater effect than work stress experienced after age 40. These findings point to another source of psychosocial stress that elevates the risk for development of T2DM in females. One concern about this study was the much smaller sample size of male participants who were 60 years of age at baseline (Pan et al., 2017).

IPD‑Work Consortium The Individual-­Participant Data Meta-­A nalysis of Working Populations (IPD-Work) Consortium was described in the previous chapter and has been an important source of information on the health risks associated with work-­related stressors. Data were pooled from 124,808 T2DM-free participants from 13 European cohort studies (Nyberg et al., 2014). There were 3,703 cases of T2DM over a follow-­up period that averaged 10.3 years. After adjusting for age, SES, and standard risk factors, job stress was associated with a significantly higher risk of diagnosis of T2DM (HR = 1.11, 95% CI = 1.00–1.23), with no differences between male and female participants. Based on the way in which T2DM varied across the national samples, it is likely that the results underestimated the actual frequency of cases of T2DM. In addition, work stress was measured with a single questionnaire that did not take into full account the various conceptualizations of work-­related levels of psychosocial stress. In spite of these concerns, this remains a powerful set of findings and strengthens the link between work stress and the incidence of T2DM.

Summary While there is clear evidence of an association between job stress or strain and long working hours on the development of T2DM, there are also some inconsistencies in the literature. Some studies have found that this association was only evidenced in males, while others have found the association only in females. In addition, SES may be a moderating variable in explaining this relationship. Many studies of job-­related stressors and their impact on health outcomes have been conducted in European countries where the issue has received significantly greater attention and funding compared to the United States.

Depression and T2DM: A Bidirectional Relationship Nurses’ Health Study In Chapter 7, I provided evidence that a bidirectional relationship exists between depression and heart disease. A similar relationship exists between depression and T2DM

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in women as reported by Pan et al. (2010). Data were generated from a subset of participants from the Nurses’ Health Study, a cohort study that started in 1976 with the recruitment of 121,700 female registered nurses who were at that time 30–55 years of age. The cohort was followed every 2 years, and response rates to mailed questionnaires were > 90%. A baseline was established with the 1996 questionnaire using a sample of 65,381 participants who were followed every 2 years through 2006. Depression was identified based on self-­reported symptoms of depression using the 5-item Mental Health Index (MHI-5), use of antidepressants, or a diagnosis of depression by a physician. T2DM was defined based on standard metrics for resting or fasting blood glucose levels or use of diabetes medications, including insulin. The results provided convincing evidence of a bidirectional relationship between T2DM and depression. Over the 10-year follow-­up period, participants with greater levels of depression displayed an increased risk of developing T2DM. Those who used antidepressants were at the highest relative risk of developing T2DM. In addition, participants with T2DM displayed an increased risk of developing depression. Those who depended on insulin therapy to regulate blood glucose levels were at the highest relative risk of developing depression. This bidirectional relationship was evident after adjusting for age, marital status, BMI, and a range of lifestyle variables. The authors concluded that interventions that promote weight management and a regimen of regular physical activity should be encouraged to reduce the risk of developing both of these diseases that contribute to the morbidity and mortality of middle-­aged and older women (Pan et al., 2010).

English Longitudinal Study of Ageing The English Longitudinal Study of Ageing (ELSA) is a population-­based sample of people living in communities in England who were ≥ 50 years old when baseline measures were obtained in 2002–2003. Face-to-face interviews were then conducted every other year. In addition, a nurse visited each participant in 2004–2005 and again in 2008–2009, and blood samples were collected for measurement of HbA1c. Depressive symptoms were quantified using the 8-item Center for Epidemiological Studies Depression Scale. Over the follow-­up period, the results indicated a dose–­response relationship between increases in symptoms of depression and incident cases of T2DM. There was also a significant association between diagnosed cases of T2DM and future risk of elevated scores for depression in participants 50–64 years of age but not in older participants. These results confirmed the bidirectional relationship between depression and T2DM in a large sample that included older males as well as females (Demakakos, Zaninotto, & Nouwen, 2014).

An Unholy Trinity We have now established a bidirectional relationship between T2DM and depression, and from the previous chapter, we discovered a bidirectional relationship between coronary heart disease (CHD) and depression. Might these two bidirectional relationships interact such that we end up with a three-way relationship connecting these three devastating chronic diseases (Figure 8.2)? Cummings et al. (2016) explored this pattern of interactions through studies of participants enrolled in the Reasons for Geographic and



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FIGURE 8.2.  Exposure to psychosocial stressors increases the risk of developing major depressive disorder (MDD), type 2 diabetes mellitus (T2DM), and cardiovascular disease (CVD). Each of these diseases increases the risks associated with the other two, creating an unholy trinity.

Racial Differences in Stroke (REGARDS) study, a population-­based, prospective, longitudinal cohort study of participants with the following characteristics: > 45 years of age, 45% male and 55% female, 41% Black and 59% White, and 55% from the southeastern United States and 45% from the remainder of the continental United States. The southeastern United States has a high rate of strokes relative to the rest of the country. After excluding individuals with a history of stroke or heart disease, there were 22,003 participants in the study cohort. At baseline, participants received an in-home physical examination and T2DM, depression, and perceived stress levels were determined using validated measures. Over a median follow-­up period of 5.95 years, the incidence of cardiovascular disease, including stroke, myocardial infarction, coronary heart disease, and deaths from cardiovascular disease, was determined during interviews with participants every 5 months and from hospital records. The results indicated that elevated levels of perceived stress and/or symptoms of depression were more prevalent in participants with T2DM than in nondiabetics (37 vs. 30%; p < .001). In fully adjusted models, those participants who reported either elevated perceived stress or depressive symptoms exhibited an increased incidence of stroke (HR = 1.57, 95% CI = 1.05–2.33) and death from cardiovascular complications (HR = 1.53, 95% CI = 1.08–2.17) in subjects with T2DM but not in those without diabetes. The combination of elevated perceived stress levels and depressive symptoms in subjects with T2DM was associated with a higher incidence of death from cardiovascular complications (HR = 2.15, 95% CI = 1.33–3.47) than either comorbidity alone and higher than in those with both elevated stress and depressive symptoms but without T2DM (HR = 1.27, 95% CI = 0.86–1.88). This excellent study demonstrated the powerful interactions between T2DM, depression, and perceived stress levels in increasing the risk of cardiovascular-­related morbidity and mortality, especially in individuals living in an area of the United States with a high incidence of strokes. These investigators suggested greater attention to detailed behavioral assessments and coordination of care in primary care settings where the majority of patients with T2DM are managed (Cummings et al., 2016).

Summary Patients with T2DM must remain ever vigilant as they attempt to control their blood glucose levels. This is a significant challenge, dare I say a stressor, under the best of conditions, but when one adds to this situation major depressive disorder as a comorbidity, then it becomes even more challenging. In addition, recent evidence has identified

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biomarkers of insulin resistance as a significant risk factor for the development of depression (Watson et al., 2021). Individuals who were comorbid for T2DM and depression exhibited suboptimal adherence to treatments for their diabetes, and they also displayed less effective glycemic control (Hackett & Steptoe, 2017). Given the compelling evidence of a bidirectional relationship between T2DM and depression, one can view each of these diseases as a stressor that increases susceptibility to the second disease. When T2DM and depression co-occur, the resulting increase in allostatic load makes the onset of cardiovascular complications more likely. Joseph and Golden (2017) have summarized evidence that a common biological pathway that connects stressful life experiences, T2DM, and depression is the HPA axis through disturbances in patterns of cortisol release.

STRESS‑TARGETED INTERVENTIONS FOR T2DM T2DM is a chronic disease that unfolds over several decades and is typically diagnosed in later life. Multiple lines of evidence discussed earlier in this chapter point to life stressors as important mediators of T2DM through their sustained impact on stress-­ responsive neural, endocrine, and immune systems. If this series of findings is accurate, then it follows that interventions designed to lessen the negative effects of stress should improve glycemic control in individuals with T2DM. Several studies highlighted below explored behavioral interventions to improve glycemic control in T2DM.

Duke University Stress Management Study This year-long study was designed to determine if a group-based stress management training program could improve glycemic control in individuals with T2DM (Surwit et al., 2002). Adult male and female participants were recruited and randomly assigned to a stress management group (SM; N = 38) or an educational control group (EC; N = 34). At baseline, all participants provided blood samples for measurement of HbA1c; body weight was measured, daily diet was assessed, and the following questionnaires were completed: Spielberger State–Trait Anxiety Inventory (STAI), Perceived Stress Scale, General Health Questionnaire, and the Duke Activity Status Index. During the initial 2 months of the study, participants were required to attend five weekly small-group sessions that included general information on diabetes (EC group) or stress management training plus general information on diabetes (SM group). The SM training included progressive muscle relaxation through use of audiotapes, use of cognitive and behavioral techniques to recognize and reduce stress levels, and information on the negative effects of stress on health. In spite of random assignment, SM participants had higher HbA1c levels and higher daily caloric intake at baseline compared to EC participants. All other baseline measures were similar between the two groups. Of critical importance to this study was the change in HbA1c levels over a 1-year follow-­up. SM participants displayed a significant reduction in HbA1c levels, whereas participants in the EC group had a slight increase. These changes were most evident at the 1-year follow-­up but not at earlier timepoints. Additional analyses revealed that the improvement in glycemic control with SM could not be explained by changes in diet or levels of physical activity. In addition, the SM



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training was not as effective in participants who had higher scores for trait anxiety. Thus, this early study demonstrated clear benefits of a stress management training program on glycemic control in participants with T2DM. Delivering SM training in a smallgroup setting is a cost-­effective way of improving management of blood glucose levels in diabetics (Surwit et al., 2002). Although modest in terms of sample size and range of dependent variables measured, this study served as a proof-of-­concept that interventions to reduce stress may be effective for improving glycemic control in diabetic patients.

Latino Stress Management Study A more recent study examined the effectiveness of using a community-­based health worker to deliver stress management training in a Latino community in Hartford, Connecticut (Wagner et al., 2016). The design of the experiment was somewhat similar to the earlier report by Surwit et al. (2002), with random assignment of participants to a diabetes education group (EC group; N = 46) or diabetes education plus stress management training group (SM group; N = 61). This is an important ethnic group to study given that Latinos are twice as likely as non-­Latino Whites to develop T2DM and they more frequently develop complications requiring hospitalization. All participants had been diagnosed with T2DM for at least 6 months, and their most recent HbA1c value was ≥ 7.0%. At the beginning of the study, all participants were included in a 2.5-hour session on basic education about diabetes and self-care. After this introductory session, the SM group participated in eight group sessions over 8–10 weeks that covered cognitive-­behavioral skills, mindfulness training, and progressive muscle relaxation techniques. All sessions and training materials were presented in Spanish by the same instructor. Measures were obtained for HbA1c, urinary cortisol, and a battery of psychosocial questionnaires. The study concluded approximately 14 weeks after the last SM group session when a blood sample was obtained for measurement of HbA1c (Wagner et al., 2016). The results of this study were promising in some respects but disappointing in others. The SM group displayed significant improvements in symptoms of depression and anxiety and self-­reported health status. However, adherence to the SM training sessions was highly variable, with only 18% of participants attending all eight sessions. The mean number of sessions attended was 4.5. Although HbA1c levels were not reduced with SM training, there were indications of a dose–­response relationship, with greater decreases in HbA1c levels with each additional SM session attended. This study was noteworthy in that it targeted a high-risk population and utilized a bilingual community health worker to deliver all SM training sessions in the preferred language of the participants. Unfortunately, it suffered from poor attendance at the SM training sessions and a small sample size. In addition, the study duration was quite brief relative to the 1-year intervention study by Surwit et al. (2002), with psychosocial measures obtained within 2 weeks after the final SM session and the final measure of HbA1c obtained just 3 months later.

Dutch Reverse Diabetes2‑Now Intervention Pot et al. (2020) developed a multicomponent lifestyle intervention—­Reverse Diabetes2-Now (RD2N)—delivered by a multidisciplinary team that included information

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on health, nutrition, and lifestyle. Although the program did not have a sole focus on stress reduction, such information was included in the lifestyle section. Participants were recruited in waves of 20 per location per month. Participants were screened for age (18–75 years), BMI (25–41 kg/m 2) and motivation to take part in the program. The intervention was delivered over a 6-month period, with an option for additional follow­up sessions, and often included family members and close friends to enhance adherence to the program. There was an initial 2-day meeting, with 1-day follow-­up meetings after 1, 3, and 6 months. At baseline, all participants were taking a glucose-­lowering medication, but none was using an insulin pump or reported significant comorbidities. Questionnaires were completed online with encouragement from instructional team members, and participants were encouraged to communicate regularly with others in their small groups. Of 438 individuals originally recruited to participate in this intervention project, only 234 (53%) provided data on HbA1c at baseline and at 24 months. After 24 months, glucose-­lowering medication use was reduced in 67% of responders, with 28% not using any medication while 71% who were using insulin to control blood glucose had ceased administering it. HbA1c levels gradually decreased from baseline but were similar to baseline levels at the 24-month follow-­up. Other significant improvements at 24 months included the following: lower values for triglyceride levels, total cholesterol/ HDL, BMI, and waist circumference as well as higher HDL levels. In addition, self-­ reported measures of perceived health status and quality of life improved while fatigue decreased. Several strengths were evidence in this study. Sample sizes were greater than in the previous two studies, and participants were followed up for a longer period of time (2 years). A multidisciplinary team delivered the program over a different timescale. Although many key health and behavioral metrics were changed in a favorable direction over the 2-year study, HbA1c levels did not improve. There were also several weaknesses in this study. Of major concern was the absence of a control group to compare to the participants who received the intervention training. In addition, almost one-half of the individuals who were originally recruited dropped out of the study.

Summary The three studies described above capture many of the challenges as well as the opportunities in targeting stress reduction for the improvement of T2DM. An area that has received little attention thus far is introducing stress management training for individuals, especially teens and young adults, who are prediabetic as a way to reduce the probability that they go on to develop T2DM with its attendant health risks. Several improvements to stress management interventions should be considered in the design of future studies: 1.  Put into place longer follow-­up periods after stress management interventions (at least 2 years) to determine the beneficial effects on key metrics associated with T2DM. 2.  Develop more effective approaches to enhance adherence to stress management classes, including formation of online communities of participants and other forms of virtual communication with trainers.



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3.  Add more workshops or online sessions as a “booster shot” to sustain the beneficial effects of stress management. 4.  Develop apps to guide and encourage individuals as they work to manage their stress levels more effectively and improve their glycemic control. These apps could also be updated with a given individual’s blood glucose measures and other data to inform automated, personalized coaching as well as provide reminders and alarms (Baptista et al., 2019). 5.  Continue to consider measurements of HbA1c as the gold standard for determining the effectiveness of stress management interventions. 6.  Employ behavioral interventions to reduce stress as part of the standard of care for patients with T2DM and routinely offer these behavioral services in primary care clinics and for services covered by health care plans.

CONCLUSIONS The research summarized in this chapter makes a strong case for prior or recent stressful life experiences being a critical factor in the etiology of T2DM (Kivimäki et al., 2023; Mishra, 2022). These stressful life experiences are many and varied, including stressors at work and at home as well as concerns about financial security and health challenges. Diabetics respond in a different manner than healthy controls when exposed to minor stressors in the laboratory and they display significant disruptions in glycemic control following the intense stress associated with a major earthquake. Morbidity and mortality increase for diabetics who develop comorbid depression and for depressive patients who develop comorbid T2DM. This bidirectional relationship between T2DM and depression contributes to a downward spiral due to the increased risk of cardiovascular disease. Given the significant global burden of disease associated with T2DM, it is surprising that behavioral interventions that seek to reduce the impact of stress on diabetics have not received more attention. Even more concerning is the lack of research on interventions that target prediabetic individuals with the goal of blocking the continued disruptions in glycemic control that lead to T2DM. We can hope that more effective behavioral interventions will be developed and tested widely in the coming years.

CHAPTER 9

Stress and the Gastrointestinal System

T

here are many ways in which we forge links through our everyday expressions between stress and the gastrointestinal (GI) tract. For example, you might say you have butterflies in your stomach as you prepare for your first game of the season. Or you might tell a close friend your abdomen is tied up in knots as you think about a first date with someone you are really interested in. Or you might say that you can feel something ominous in your gut. Our challenge in this chapter is to explore how stressful stimuli can alter GI function and examine the pathways of communication between the GI tract and the brain. We will also investigate the importance of the microbiota (bacteria, fungi, and viruses) of the GI tract and how these resident microbes add another layer of complexity onto the signaling pathways between the gut and the brain. Finally, we will consider how stress exacerbates symptoms related to disorders of the GI tract and take a look at how stress management interventions might improve outcomes. In this chapter, we will be discussing issues that have a decidedly negative impact on the quality of life of millions of people globally; stressful life events have been shown to be a key element in their onset and progression. Research on connections between the GI system and the brain has been a topic of intense interest over the past two decades and has revealed new lines of communication along the gut–brain axis. One interesting outcome of research on gut–brain communication is the development of psychogastroenterology as a subspecialty area within gastroenterology for clinical and health psychologists. We will discuss the importance of this subspecialty when we examine behaviorally based interventions for disorders of gut–brain interaction.

THE MICROBIOME–GUT–BRAIN AXIS Research on the microbiome– gut–brain axis has progressed at a dizzying pace over the past two decades (Cryan et al., 2019). These findings have important implications for 172



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understanding how psychosocial stressors can adversely affect GI function and even lead to the onset of GI-­related diseases such as peptic ulcer disease, inflammatory bowel disease, and irritable bowel syndrome. To develop a deeper understanding of these connections between stress and diseases of the GI system, we need to have a basic understanding of the components of the microbiome–­gut–brain axis. In the sections that follow, I will provide an overview of the microbial, neural, endocrine, and immune signaling pathways that contribute to the homeostatic regulation of the GI system and, on occasion, push it into a state of dysregulation (Figure 9.1).

The Enteric Nervous System The enteric nervous system (ENS) is the largest and most complex unit of the autonomic nervous system (ANS). The total number of enteric neurons in humans ranges from 400 to 600 million cells, a number that exceeds the sum of all sympathetic and parasympathetic ganglion cells combined and is approximately equal to the number of neurons in the spinal cord. Because most ENS neurons lack direct innervation from the

FIGURE 9.1.  Bidirectional communication between the gut microbiome and the brain to form the microbiome–­gut–brain axis. The vagus nerve (solid line) provides bidirectional communication between the brain and peripheral tissues, including the gastrointestinal (GI) tract. The sympathetic nervous system (SNS) (dotted line) projects to the GI tract. Microbiome-­derived signaling molecules, including short-chain fatty acids (SCFAs) and immune signaling molecules and neurons of the enteric nervous system (two such neurons are shown) contribute to this highly complex system.

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central nervous system (CNS), the ENS is neither sympathetic nor parasympathetic; rather, it constitutes a third distinct autonomic subdivision that also receives input from the sympathetic and parasympathetic subdivisions. A unique feature of the ENS is its ability to regulate GI function in the absence of CNS input. Although the ENS can function independently, the ENS and CNS normally engage in bidirectional communication to optimize GI function. Intrinsic ENS neural systems are largely responsible for the detailed patterns of GI motor and secretory activities, such as peristalsis and fluid and electrolyte secretion. The ENS also communicates with many other cell types, including intestinal epithelial, endocrine, and immune cells, to influence various physiological responses of the GI tract. Among the important functions regulated in part by the ENS are determining the muscular contractions of the GI tract, controlling gastric acid secretion, regulating movement of fluid across the gut epithelium, changing local patterns of blood flow, modifying nutrient handling, and interacting with the intrinsic cells of the immune and endocrine systems of the gut. The ENS also contributes to maintenance of the integrity of the epithelial barrier between the lumen and epithelial cells of the intestinal wall (Furness, 2012; Rao & Gershon, 2018). Neuronal communication along the microbiome–­gut–brain axis involves ANS and ENS pathways that regulate important functions that occur throughout the GI tract. One of the most important of these neural pathways is the vagus nerve, which provides bidirectional communication between the CNS and all visceral organs through a mix of 80% afferent and 20% efferent nerve fibers. The afferent fibers of the vagus nerve are the main neural conduit connecting the GI tract to the nucleus of the solitary tract in the brainstem and higher emotion-­regulating networks in the mammalian brain (Wilmes et al., 2021). Vagal afferents contain a wide array of receptors for the detection of various gut hormones, neurotransmitters, and bacterial metabolites. Although it does not appear to interact with the gut microbiota directly, evidence suggests that the vagus nerve can sense microbial signals in the form of bacterial metabolites, or be influenced via microbiota-­mediated modulation of enteroendocrine and enterochromaffin cells in the gut epithelium. For example, gut bacteria produce short-chain fatty acids that regulate physiological intestinal functions, including motility, secretion and inflammation, through free fatty acid receptors. In addition, other receptors on vagal nerve fibers such as those for serotonin (5-HT3 and 5-HT4 receptors) and other gut peptides may also facilitate these signaling pathways. The ENS works in concert with the CNS through integrative neural pathways that pass through sympathetic ganglia and the gastroenteropancreatic endocrine system. In the small and large intestines, the ENS contains full reflex pathways that are essential to direct the movements of these parts of the digestive tract and to control fluid movement between the gut lumen and body compartments. The control of fluid transport represents a prime example of close integration between the CNS (via sympathetic pathways) and the ENS (Furness, 2012).

Endocrine Signaling Pathways Endocrine signaling within the microbiome–­gut–brain axis involves two major systems, one external to the GI tract and one internal to the GI tract. The external component is represented by the HPA axis and the regulation of cortisol levels in the circulation. In contrast, the endocrine system of the digestive tract, called the gastroenteropancreatic



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endocrine system, is an extensive network of approximately 30 endocrine cell types that secrete more than 100 signaling molecules. The contents of the lumen of the small intestine are detected by receptors on enteroendocrine cells, which release signaling molecules from their basolateral surfaces to activate enteric, vagal, and spinal sensory neurons. A good example of neural and endocrine integration in the GI tract is the control of gastric acid secretion. The primary endocrine hormones involved in control of acid secretion are gastrin released from antral G-type enteroendocrine cells, histamine released from enterochromaffin-­like cells, and somatostatin released from gastric mucosal D cells. However, the parietal cells are influenced both directly and indirectly by cholinergic neurons with cell bodies in the ENS, and gastrin release is controlled by gastrin-­releasing peptide, a transmitter released from enteric neurons that innervate G cells (Furness, 2012; Moran, Leslie, Levison, & McLaughlin, 2008).

GI Immune Responses In the gut, an intact immune system is critical for maintaining the careful balance between homeostatic tolerance of commensal organisms and the simultaneous protection of the body against pathogenic microbial invasion. In addition, immunity also serves a critical role in mediating communication between the gut microbiota, the ENS, and the CNS. Toll-like receptors (TLRs) and peptidoglycans (PGNs) mediate the immune response to microbes by acting as sensors of microbial components. An intact gut barrier also prevents the inappropriate activation of immune cells and the development of systemic immune activation. Diet-­induced changes in the gut microbiome can lead to a compromised mucus layer, allowing access of luminal microbes to extensions of dendritic cells and resulting in activation of these cells by both pathogens and commensals. This local immune activation can lead to increased permeability of the epithelial tight junctions that further compromise the intestinal barrier. The diet-­induced release of immune mediators into the systemic circulation is referred to as metabolic endotoxemia, which can lead to immune activation in different organs, including the CNS. Macrophages are present throughout the gut, where they play an essential role in the reparative response to intestinal injury. An important topic in the context of inflammation within the microbiome–­gut– brain axis is the integrity of the intestinal barrier. Changes in intestinal permeability create a passage for bacteria and their products from the lumen to make contact with the ENS and immune cells and enter the systemic circulation, which can evoke an immune response. Increased intestinal permeability is associated with low-grade inflammation, a feature of some GI diseases (Cerf-­Bensussan & Gaboriau-­Routhiau, 2010).

The Gut Microbiome A unique combination of different populations of organisms inhabits our gut, mainly bacteria but also archaea, viruses, and protozoa, with a rough estimate of 1014 cells, outnumbering the human cells in our bodies by a factor of 10. While bacterial profiling and its understanding have become easier during the last decade, analyses of the mycobiome and the virome are still in their infancy. Even though the gut microbiota differ greatly between subjects in makeup and structure, it still appears on the whole to be functionally equivalent and necessary for proper development of the host. The two

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more prominent phyla are Firmicutes and Bacteroides, accounting for at least three-­ quarters of the gut microbiome in healthy humans. This diverse microbial community contributes to important metabolic and physiological functions that benefit the host and contribute to homeostatic balance throughout life. Mammals, including humans, have coevolved to exist with their gut microbiota largely in a mutualistic relationship. These organisms participate in the conversion of nondigestible carbohydrates (dietary fiber) to short-chain fatty acids, play a role in bile acid metabolism, provide a barrier against pathogenic bacteria, and modulate the innate and adaptive immune systems. In turn, the host provides a unique, nutrient-­rich niche that is maintained at a relatively constant temperature. Alterations in gut microbiota (dysbiosis) can arise as a consequence of GI diseases, following acute exposure to stress, or as a result of various drug therapies (Bastiaanssen et al., 2021). All major chronic disorders of the gut, specifically inflammatory bowel disease, irritable bowel syndrome, and coeliac disease, are associated with dysbiosis (Carabotti, Scirocco, Maselli, & Severi, 2015; Wilmes et al., 2021). In addition, disturbances in the gut microbiome place individuals at greater risk of the onset of depressive symptoms (Eustis, McCall, Murphy, & Wirth, 2022).

Communication along the Microbiome–Gut–Brain Axis A pattern of bidirectional communication between dietary constituents, the gut microbiome, and the vagus nerve has been described. Enterochromaffin cells contain more than 90% of the body’s serotonin (5-HT), and 5-HT synthesis and release in these cells are modulated by short-chain fatty acids produced by spore-­forming Clostridiales. These microbes increase their stimulatory actions on enteroendocrine cells with increased dietary tryptophan availability. Enterochromaffin cells also communicate with vagal afferent nerve fibers through synaptic connections formed by neuropod-­like extensions. On the other hand, the ANS can activate enterochromaffin cells to release 5-HT into the gut lumen, where it can be taken up by serotonin transporter-­like mechanisms and influence gut microbial function (De Palma, Collins, Bercik, & Verdu, 2014; Margolis, Cryan, & Mayer, 2021). The various components of the GI system are sensitive to psychosocial and physical stressors through the signaling molecules of the three primary stress effector systems, the HPA axis, the sympathetic–­adrenomedullary system, and the immune system. Activation of these stress effector pathways can lead to significant alterations in GI function, including alterations in gut barrier permeability, mucosal transport, GI motility, and composition of the gut microbiota (Molina-­Torres, Rodriguez-­A rrastia, Roman, Sanchez-­Labraca, & Cordona, 2019). If high-­stress levels are sustained, pathological changes in the GI tract may occur; these pathologies will be discussed in greater detail in the sections that follow.

PEPTIC ULCERS AND STRESS In his early research on stress and the general adaptation syndrome, Selye (1936) described erosions in the stomach and proximal portion of the small intestine following exposure of laboratory rats to intense stressors over extended periods of time. These



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initial findings in laboratory rats foreshadowed a connection between stress and peptic ulcers (Fink, 2017). For many years, peptic ulcers of the stomach, duodenum, and the proximal end of the small intestine were thought to be a consequence of high levels of psychosocial stress associated with urbanization beginning in the late 19th century and continuing well into the 20th. However, a major discovery by Australian physicians Barry J. Marshall and J. Robin Warren revealed that a bacterium, later identified as Campylobacter pyloridis, was responsible for many cases of peptic ulcer disease (Marshall & Warren, 1984). Dr. Marshall, a gastroenterologist, famously went the extra mile in his research and drank a solution containing the bacterium cultured from a patient with peptic ulcer disease to firmly establish a connection between the bacterium and peptic ulcer disease, which he developed approximately 10 days later (Marshall, Armstrong, McGechie, & Glancy, 1985). The ulcer-­causing bacterium was renamed Helicobacter pylori in 1989 during a major taxonomic reclassification. Marshall and Warren shared the Nobel Prize for Physiology or Medicine in 2005 for their groundbreaking discovery. In addition to H. pylori, other risk factors contributing to the pathogenesis of peptic ulcers include smoking and chronic use of nonsteroidal anti-­inflammatory agents (NSAIDs) such as ibuprofen as well as high doses of aspirin. With the discovery of H. pylori as an etiologic agent in the 1980s, research relating to connections between stress and peptic ulcer disease came to a screeching halt. After all, many argued, peptic ulcer disease was really just an infectious disease that targeted the mucosal lining of the stomach and small intestine. Some national health services, including the Centers for Disease Control and Prevention in the United States, distributed educational materials to physicians to put an end to any lingering beliefs of their patients who might assume a link between stress and peptic ulcers. Current estimates of the lifetime prevalence of peptic ulcer disease in the general population vary from 5 to 10%, and the yearly incidence is in the range of 0.1–0.3% per year. The prevalence and incidence of peptic ulcer disease are probably even lower than these estimates in high-­income countries, as recent trends suggest pronounced decreases in incidence, rates of hospital admissions, and mortality associated with peptic ulcer disease over the past 20–30 years. Of note, there has also been a trend of decreasing prevalence of H. pylori infections over the same time period. Currently, approximately 20% of cases of peptic ulcer disease are negative for H. pylori infection, NSAID use, and aspirin use. Regarding the theme for this chapter, life-­threatening stressors such as the Great East Japan earthquake of 2011 were followed by an increased incidence of several diseases, including peptic ulcer disease. Might stress have played a role in the aftermath of this natural disaster? Epigastric pain is the primary symptom of peptic ulcer disease, combined with feelings of fullness, bloating, and nausea. The most serious complications of peptic ulcers include bleeding, perforation, and gastric outlet obstruction. Endoscopic examination differentiates between an erosion (mucosal break less than 5 mm in diameter) and an ulcer (mucosal break greater than 5 mm in diameter). In patients younger than 50–55 years of age, a test-and-treat strategy is typically followed, often employing a breath test and stool antigen test to detect the presence of H. pylori. A major concern after an initial diagnosis of peptic ulcer disease is prevention of recurrence. First-line therapy often includes a proton pump inhibitor to reduce gastric acid secretion plus a combination of two to three antibiotics based on the profile of antibiotic-­resistant H. pylori strains in the local area. In most instances, peptic ulcers resolve after 6–8 weeks

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of treatment with a proton pump inhibitor (Lanas & Chan, 2017; Malferheiner, Chan, & McColl, 2009).

A Continuing Role for Stress Is there more to the stress–­peptic ulcer connection than meets the eye, even after the discovery of the disease-­causing bacterium, H. pylori? Consider these clinical observations summarized by Levenstein (2000):

• More than 80% of patients with H. pylori infections never develop a peptic ulcer. • The majority of NSAID users never develop a peptic ulcer. • Up to 20% of patients with peptic ulcers are negative for H. pylori infections and do not take NSAIDS or aspirin.

Levenstein argued that peptic ulcer disease matches well with the biopsychosocial model of disease originally proposed by Engel (1977). She also pointed to socioeconomic status (SES) as a confounding variable that shapes the course of peptic ulcer disease in many individuals (Figure 9.2). Included below are the results of some more recent studies that have explored these complex interrelationships between psychosocial and major life stressors and the risk of peptic ulcer disease.

FIGURE 9.2.  A model postulating behavioral and psychophysiological mechanisms that may link psychosocial stress with peptic ulcer. NSAIDs, nonsteroidal anti-­ inflammatory drugs. Redrawn from Levenstein et al. (2000) and used with permission of the publisher.



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Peptic Ulcers in Danes In a prospective population-­based cohort sample of Danish adults without ulcers, Levenstein, Rosenstock, Jacobsen, and Jorgensen (2015) examined the relationship between incidence of peptic ulcers and ratings of psychosocial life stressors. At study inception in 1982–1983, medical histories, blood samples, and behavioral measures were obtained from 3,379 adults who were part of the World Health Organization-­sponsored study on Monitoring Trends and Determinants in Cardiovascular Disease (MONICA). Follow­up data were collected in 1987–1988 (N = 2,809) and again in 1993–1994 (N = 2,410). Ulcer diagnoses (N = 67) were confirmed by radiological and endoscopic studies and required a break in the gastric mucosa. Participants’ medical records in the Danish National Patient Register were also reviewed. The results revealed that participants with the highest third of stress scores displayed significantly higher rates of peptic ulcers (3.5%) compared to participants with the lowest third of risk scores (1.6%). The association between the stress index score and risk of peptic ulcer was significant even after adjusting for presence of antibodies for H. pylori, alcohol consumption, sleep duration, SES, smoking behavior, level of exercise, and use of NSAIDs (OR = 1.11, 95% CI = 1.01–1.23, p < .04). In addition, risk of peptic ulcers related to stress levels was similar for participants who were H. pylori seropositive, H. pylori seronegative, and H. pylori seronegative plus nonusers of NSAIDS. Additional analyses revealed that stress levels, low SES, H. pylori seropositivity, smoking, and regular use of nonsteroidal anti-­inflammatory drugs were each significantly associated with risk of peptic ulcers. These investigators concluded that life stressors as measured at baseline in an adult population free of ulcers increased the risk of developing peptic ulcers over a 10- to 11-year follow-­up, in part by affecting health risk behaviors (Levenstein et al., 2015).

Peptic Ulcers in Swedes The sample for this study (N = 233,093) included all males born in Sweden between 1952 and 1956 who participated in mandatory assessments for conscription into the Swedish military from 1969 to 1976 and who were free of inflammatory bowel disease prior to follow-­up data collection from 1985–2009 using the National Patient Register (Melinder, Udumyan, Hiyoshi, Brummer, & Montgomery, 2015). All participants completed assessments at conscription that included a measure of stress resilience combined with an in-­person interview (range of scores = 1–9). Scores of stress resilience were grouped as follows: low (scores 1–3), moderate (scores 4–6), or high (scores 7–9). High-­ stress resilience included the ability to adapt effectively to psychosocial stressors and the resolve to continue with assigned tasks under adverse conditions. Over the course of the follow-­up period, 2,259 cases of initial peptic ulcer disease were diagnosed. Lower stress resilience scores measured in adolescence were associated with a higher risk of peptic ulcer disease later in life. Compared to participants with high-­stress resilience scores, those participants with moderate (HR = 1.23, 95% CI = 1.09–1.38) and low stress resilience scores (HR = 1.84, 95% CI = 1.61–2.10) were at greater risk for developing peptic ulcer disease even after adjusting for household crowding, parental SES, and adolescent cognitive parameters measured at conscription. In addition, data on acute appendicitis were included as a “disease control,” and no association between stress resilience scores and risk of appendicitis was found.

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The results of this study clearly point to a connection between low stress resilience and risk of peptic ulcer disease. However, some shortcomings in the design of this study and data collection for it should be kept in mind. Obviously, all participants were male, a fact that should be considered in the design of future studies. Stress resilience was only measured at one timepoint during late adolescence, and these researchers assumed that this was a stable trait over the lifespan, which may or may not be true. In addition, cases of peptic ulcer disease may have been underestimated because some participants were diagnosed and treated with antibiotics by primary care physicians. There were also no measures of stressful events, which may have also underestimated the strength of the association between susceptibility to stress and peptic ulcer disease. Information on smoking history was not collected, and most importantly, no measures of H. pylori infections were obtained. In spite of these limitations, the results of this study clearly suggest that stress management should be added to any comprehensive plan for managing patients with peptic ulcer disease (Melinder et al., 2015).

Depression and Peptic Ulcer Disease Kim, Min, Oh, and Choi (2020) capitalized on two large cohort studies to explore the possibility of a bidirectional relationship between depression and peptic ulcer disease. The Korean National Health Insurance Service–­National Sample Cohort (NHIS-NSC) from 2002–2013 was used to generate participants for this two-part study. In the first part, 30,306 clinically depressed patients were matched 1:4 with 121,224 controls who were similar in age, sex, income, and area of residence. The key outcome measure in this study was a diagnosis of peptic ulcer disease. In the second part of the study, 127,590 peptic ulcer patients were matched 1:1 with 127,590 controls who were similar in age, sex, income, and area of residence. The key outcome measure is this study was the incidence of major depression. The results are summarized in Table 9.1. In the first study, 8.9% (2,703/30,306) of depressed patients and 7.3% (8,896/121,224) of individuals in the control group had peptic ulcers (p < .001). In the second study, 6.4% TABLE 9.1.  Hazard Ratios and 95% Confidence Intervals for the Association between Depression and Peptic Ulcer Disease (Study 1) and the Association between Peptic Ulcer Disease and Depression (Study 2)

Study 1 (depression → peptic ulcer disease) Depressed Controls

Stratified model HR (95% CI)

Adjusted model HR (95% CI)

1.24 (1.19–1.30)* 1.00

1.14 (1.09–1.19)* 1.00

1.84 (1.78–1.91)* 1.00

1.68 (1.62–1.74)* 1.00

Study 2 (peptic ulcer disease → depression) Peptic ulcer disease Controls

Note. HR, hazard ratio; CI, confidence interval. Stratified model: Data were adjusted for age, sex, income, and area of residence. Adjusted model: Reflects the Charlson Comorbidity Index calculated without peptic ulcer. Data are from Kim, Min, et al. (2020). *p < .001.



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(8,144/127,590) of peptic ulcer patients and 3.5% (4,515/127,590) of individuals in the control group were diagnosed with depression (p < .001). These results clearly point to a bidirectional relationship between depression and peptic ulcer disease. Both of these diseases bring with them significant amount of stress to individuals, increasing the risk that an individual with one disease will in time be diagnosed with the other (Kim, Min, et al., 2020).

Summary Simplicity is appealing but often misleading. Prior to the 1980s, peptic ulcer disease was thought to be due to stress—­end of story. After the discovery of H. pylori in the 1980s, peptic ulcer disease was shown to result from an infectious agent—end of story. Thanks to the excellent work of Levenstein and others, the pathophysiology of peptic ulcer disease is now considered appropriately complex, with contributions from psychosocial stressors, H. pylori infections, excessive use of NSAIDS, and smoking, and with moderation of these risk factors by socioeconomic status (refer to Figure 9.2) (Levenstein, Ackerman, Kiecolt-­Glaser, & Dubois, 1999).

INFLAMMATORY BOWEL DISEASES Inflammatory bowel diseases (IBDs) are chronic inflammatory diseases of the GI tract that are usually characterized as one of two major subtypes: Crohn’s disease or ulcerative colitis. Current data indicate that approximately 1.5 million adults in the United States suffer from IBDs. In spite of sustained research efforts over the past several decades, the pathophysiological mechanisms underlying these two conditions are incompletely understood. Until recently, IBDs were associated with Westernized societies, including the United States, Canada, the countries of Western Europe, Australia, and New Zealand. However, over the past 25 years the incidence of IBDs in emerging economies in Asia, Africa, and South America has increased substantially (Ng et al., 2017). In the following sections, I will provide an overview of Crohn’s disease (CD) and ulcerative colitis (UC), followed by a discussion of the role of psychosocial stress in the pathophysiology, progression, and management of IBDs.

Crohn’s Disease Although the exact cause of CD is at present unknown, it is clear that genetic, immunologic, and environmental risk factors contribute to the development and progression of the disease. The peak incidence of CD occurs between the second and fourth decades of life and with approximately equal frequency in males and females. Individuals with CD must contend with chronic and at times severe abdominal pains, bouts of diarrhea with passage of blood or mucus, and possibly intestinal obstructions requiring surgery. Up to 50% of CD patients required surgery to repair bowel damage in the 20 years following their initial diagnosis. The underlying pathology of CD involves what are referred to as “skip lesions” that are interspersed with normal mucosal tissue in the GI tract. This patchy distribution of lesions leads to a “cobblestone” appearance in the mucosa of the colon. These

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lesions can occur anywhere within the GI tract, and the resulting inflammatory activity is transmural, involving all layers of the intestinal wall. The production of mucus by goblet cells is the first line of defense between the contents of the GI tract and the wall of the intestine. Mucous production appears to be impaired in CD, together with a breakdown in the tight junctions between adjacent epithelial cells that form the inner lining of the GI tract, such that the intestinal wall becomes leaky. The breakdown of the GI barrier allows antigens from the lumen to gain access to the high density of immune cells in the lamina propria, initiating a cycle of inflammatory responses. In addition, Paneth cells dispersed in the inner layer of the GI tract are also compromised in CD, such that their secretion of antimicrobial peptide granules into the mucous layer and the lumen of the GI tract is compromised. There are also disruptions in the gut microbiota in CD, resulting in a decrease in diversity of commensal microbes (Roda et al., 2020). There is a strong genetic underpinning to CD, with high rates of concordance for the disease in monozygotic twins (35–50%) and increased risk of developing the disease in individuals with a first-­degree relative who has CD. Jewish descent is an independent risk factor for CD, with Ashkenazi Jews having the highest prevalence of CD compared to other ethnic groups. Results from genome-­wide association studies have identified many susceptibility loci for CD, including genes associated with immune function. However, the currently identified risk gene variants only account for approximately 20% of the heritability of CD.

Ulcerative Colitis Ulcerative colitis (UC), a chronic disease of unknown etiology, is limited to the colon and is characterized by inflammation of the mucosal layer beginning in the rectum and extending up into the colon in a continuous fashion, with superficial damage to the bowel wall. Ulcerations, blood and/or mucus in the stool, diarrhea, and increased frequency and urgency associated with bowel movements are the most common symptoms of UC. A toxic combination of altered GI immune responsiveness, dysregulated gut microbiota, risk genes, and environmental factors appear to join forces and result in a diagnosis of UC. Based on endoscopic examination, inflammation of the mucosa of the colon increases in a proximal to distal pattern, with an abrupt transition to normal mucosa in the proximal colon. Approximately 20–25% of UC patients eventually require surgery even if they have benefited from medical management to control the progression of the disease (Kobayashi et al., 2020).

Psychosocial Stressors and IBDs Given that the course of IBDs is characterized by periods of remission alternating with flares of active disease and disabling symptoms of abdominal pain, diarrhea, and weight loss, there has been speculation for many years that psychosocial stressors might contribute to an acute onset of symptoms (for a review of early studies, see Gerbert, 1980). Summarized below are results from longitudinal clinical studies that explore the impact of psychological variables on flares of IBD or diagnosis of these diseases within a larger biopsychosocial model of health and disease.



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Stress and IBD Flares One of the significant challenges that faces patients with IBD is the occurrence of disabling flares of symptoms, including frequent bowel movements, nausea and vomiting, diarrhea, bloody stools, and severe abdominal pains. Psychosocial stressors are one of several environmental factors that can promote and/or exacerbate the onset of a flare in CD as well as UC. Other potential triggers of IBD flares include use of NSAIDS and antibiotic medications, development of infections, and smoking. To examine the role of these suspected triggers in IBD flares, Bernstein et al. (2010) conducted a prospective study of 704 patients drawn from the University of Manitoba IBD Research Registry who were asked to complete surveys received through the mail every 3 months for a year to determine whether suspected triggers were associated with a subsequent flare of IBD symptoms. A flare was defined as a change from an inactive to an active disease state across two consecutive 3-month periods. The primary outcome measures in this study were scores on the Manitoba Inflammatory Bowel Disease Index (MIBDI) adapted for the 3-month interval of the surveys. The baseline survey at the beginning of this study was completed by 704 participants, and 552 participants completed all five surveys. The average age of participants was 52 years (60% females), and the mean duration of their IBD was 22 years, with 62% diagnosed with CD and 38% with UC. Over the 12-month study period, 174 participants experienced a flare, while 209 participants did not. Major stressful life events, negative mood state, and elevated perceived stress levels were significantly associated with IBD flares. Based on multivariate logistic regression analyses, only elevations in perceived stress levels were significantly associated with flares (HR = 2.40, 95% CI = 1.35–4.26). Flares were not associated with use of NSAIDS or antibiotics or other demographic or health-­related variables. These results strengthen the connection between how an individual perceives the levels of stressful stimuli in his or her daily life and the flares of symptoms associated with IBD. These investigators concluded that stress management interventions at the time of initial diagnosis for some patients with high levels of perceived stress might serve as an important addition to traditional medical management in controlling the course of IBD (Bernstein et al., 2010).

Nurses’ Health Study Drawing on the statistical power of the Nurses’ Health Study, Anantharishnan et al. (2013) examined prospectively the relationship between depression and psychosocial stressors and incidence of CD and UC. Study participants included 152,461 female registered nurses who completed a health-­related quality of life survey in 1992–1993 and at that time were free of IBD and cancer. Self-­reported depressive symptoms were assessed in 1992–1993, 1996–1997, and 2000–2001 with the 5-item Mental Health Index (MHI-5), which quantifies psychological distress on a scale of 0–100. Individuals with MHI-5 scores of 0–52 were categorized as depressive, while those with scores of 86–100 were included in the referent group. At baseline, the median age of participants was 45 years, and the median MHI-5 score was 76. During the study, 170 cases of CD and 203 cases of UC were confirmed by a gastroenterologist’s review of the participants’ medical records. There was a significant linear trend of increased risk for CD, with decreasing scores on the MHI-5 (Table 9.2).

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TABLE 9.2.  Relationship between MHI-5 Scores and Incidence of Crohn’s disease (CD) in Participants from the Nurses’ Health Study MHI-5 score

86–100

76–85

53–75

0–52

Person-years of follow-up

478,480

616,292

516,500

175,798

No. of diagnoses

33

57

53

27

Incidencea

7

9

10

15

1.0

1.38 (0.90–2.13)

1.59 (1.02–2.48)

2.36 (1.40–3.99)c

CD

HR (95% CI)b

Note. MHI-5, the five-item version of the Mental Health Index to measure psychological distress. Data were originally presented by Anantharishnan et al. (2013) and are used with permission of the publisher. a Incidence of CD was expressed as number of diagnoses per 100,000 person-years. b Hazard ratio (HR, with 95% confidence interval [CI]) was adjusted for age, race, smoking history, BMI, contraceptive use, use of over-the-counter pain medications, and so on. Those individuals with an MHI-5 score of 86–100 were assigned an HR score of 1.0 and defined as the referent group. c p < .001 for the negative linear trend of increasing incidence of CD with decreasing MHI-5 scores.

The effect sizes for MHI-5 scores were comparable to effect sizes for smoking, a well-­ established risk factor for CD. These investigators suggested that their results were consistent with an interaction between depressive symptoms, immune dysregulation, and CD symptom onset and were consistent with a biopsychosocial model of CD. In contrast, MHI-5 scores were not associated with an increased risk of UC (HR = 1.07, 95% CI = 0.63–1.83). This study had a number of notable strengths, including a large sample of participants who were disease-­free at the start of data collection and were followed for one decade, and each reported case of CD and UC was also confirmed by an experienced gastroenterologist. Limitations of this study included participants who were all female and mostly Caucasian, and the age range of the participants, which was well past the higher risk period for onset of CD and UC. The only psychosocial measure in this study was the MHI-5, but it is well validated, having been administered on three occasions over the 10-year period of the study.

Telemedicine Study of Stress and IBD Flares Wintjens et al. (2019) drew on the myIBDcoach telemedicine study cohort to examine the influence of psychosocial and other stressors on flares of IBD symptoms. Over a 1-year period, participants (N = 417) reported on disease flares and psychosocial measures through the secure myIBDcoach web portal. The web portal included monthly monitoring modules, questions relating to IBD symptoms, medication usage, smoking status, adherence to prescribed treatments, and questionnaires relating to psychosocial well-being. Of the 417 patients who were included in this study, 49 developed a flare of disease symptoms over the study period. Disease flares were determined based on symptoms reported by the participants and clinical assessments by a gastroenterologist. The mean time from inclusion in the study to a disease flare was approximately 6 months.



Stress and the Gastrointestinal System 185

Measures of anxiety, depression, and fatigue were not associated with symptom flares. However, the occurrence of stressful life events was significantly associated with IBD symptom flares over the next 3 months (HR = 1.81, 95% CI = 1.04–3.17). If only novel perceived stress levels were factored in, the association with IBD symptom flares was even more compelling (HR = 2.92, 95% CI = 1.44–5.90). Unfortunately, the psychosocial measures employed in this telemedicine study were unusually brief to increase participant adherence to regular reporting through the web portal and cannot be compared directly to more established psychosocial questionnaires. These investigators concluded that psychosocial monitoring of IBD patients and interventions to enhance coping strategies may reduce the occurrence of disease flares (Wintjens et al., 2019).

A Swedish Cohort Study of Stress and CD The sample for this study (N = 239,591) included all males born in Sweden between 1952 and 1956 who participated in mandatory assessments for conscription into the Swedish military as described above. All participants were confirmed to be free of IBD prior to follow-­up data collection from 1970 to 2009 using the National Patient Register (Melinder, Udumyan, Hiyoshi, Brummer, & Montgomery, 2017). All participants completed assessments at conscription that included a measure of stress resilience combined with an in-­person interview (range of scores = 1–9). Scores of stress resilience were grouped as follows: low (scores 1–3), moderate (scores 4–6), or high (scores 7–9). High-­stress resilience included the ability to adapt effectively to psychosocial stressors and the resolve to continue with assigned tasks under adverse conditions. An inpatient or outpatient diagnosis of CD at least 4 years after conscription was the primary outcome measure in this study. Over the course of this study, 938 men were diagnosed with CD. Those individuals with low to moderate stress resilience scores in late adolescence were significantly more likely to develop CD compared to those with high-­stress resilience scores, even after adjusting for socioeconomic, demographic, and various health risk factors (Table 9.3). Possible mechanisms that were advanced to explain these findings included pro-­ inflammatory responses to recurring psychosocial stressors and disruptions in the integrity of the intestinal barrier. Weaknesses of this study included a study population made up exclusively of males and a lack of information on smoking behavior, diet, and stress coping mechanisms (Melinder et al., 2017). TABLE 9.3.  Relationship between Stress Resilience Measured at Conscription for Military Service and Subsequent Diagnosis of CD Beginning at Least 4 Years after Conscription in Swedish Males Stress resilience

Cases/total sample

Unadjusted HR (95% CI)

Adjusted HR (95% CI)

Low

225/50,965

1.54 (1.26–1.88)

1.39 (1.13–1.71)

Moderate

547/130,994

1.43 (1.20–1.70)

1.36 (1.14–1.62)

166/57,632

Reference score 1.00

Reference score 1.00

High

Note. HR: hazard ratio and 95% confidence interval (95% CI). Adjusted HR: adjusted for BMI, parental socioeconomic index, appendicitis before age 20, region of residence, etc. Data were originally reported by Melinder et al. (2017).

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Psychosocial Stress and UC Bitton et al. (2003) examined the relationship between psychosocial stressors and relapse in UC. Patients (N = 60, of whom 37 were female, with an overall median age of 39 years) with well-­documented UC were recruited to participate in a prospective, longitudinal study. Patients had to be in clinical remission for at least 1 month based on normal bowel activity without rectal bleeding and confirmed by an endoscopic examination. At the baseline interview, each participant completed questionnaires relating to psychological distress, perceived stress, and stressful life events. These included the Psychiatric Epidemiology Research Interview (PERI) Life Events Scale, an instrument that assesses 102 positive and negative life events experienced during the past month. Participants were also instructed to promptly report any flares in symptoms. Patients were seen in clinic every 3 months for up to 1 year if they remained in remission or less if they experienced a recurrence of UC symptoms. The average amount of time from study onset to relapse of symptoms was 202 days (N = 22 participants). After adjusting for age, gender, and number of prior UC relapses, a statistically significant association was detected between PERI scores and time to relapse (p < .02, HR = 1.26 per event, 95% CI = 1.04–1.53). These findings suggest that greater numbers of stressful events were associated with an increased risk of relapse of UC symptoms. The authors situated their results within a biopsychosocial model of disease and suggested that monitoring of stressful life events could be helpful in stratifying patients to recommend psychosocial interventions for some. This study had a number of strengths in that it followed patients longitudinally and employed several measures to determine active cases of UC. In addition, multiple psychosocial measures were taken in advance of flares of symptoms. Unfortunately, the study included a limited number of patients, reducing the statistical power of the study (Bitton et al., 2003).

STRESS‑TARGETED INTERVENTIONS FOR IBD The studies reviewed above and many related studies that were not discussed have suggested that targeted psychosocial interventions could be beneficial in the overall management of IBD patients. In a set of guidelines representing the official practice recommendations of the American College of Gastroenterology for management of adult patients with CD, the authors concluded: Perceived stress, depression, and anxiety, which are common in IBD, are factors that lead to decreased health-­related quality of life in patients with Crohn’s disease, and lead to lower adherence to provider recommendations. Assessment and management of stress, depression, and anxiety should be included as part of the comprehensive care of the Crohn’s disease patient (strong recommendation, very low level of evidence). (Lichtenstein et al., 2018, p. 495)

Similar practice recommendations of the American College of Gastroenterology for management of adult patients with UC also indicated a need to address comorbid anxiety and depression in UC patients as part of an overall strategy for patient management (Rubin, Ananthakakrishnan, Siegel, Sauer, & Long, 2019).



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If psychosocial stressors are among the environmental triggers for development of IBDs as well as onset of flares when symptoms recur, then it follows that interventions that enhance stress management and contribute to development of coping skills may play a beneficial role in patient management. Unfortunately, this vital area of research has not received the attention it deserves from behaviorally oriented researchers interested in IBDs. To capture the current state of knowledge, several stress management interventional studies will be discussed in the following sections.

Psychotherapy and IBD Deter et al. (2007) examined the effects of extended psychotherapy on health care utilization in CD patients. At the beginning of the 2-year study, CD patients were randomly assigned to a standard-­of-care control group (N = 26) or a psychotherapy + standard-­ of-care experimental group (N = 43). Psychotherapy consisted of a combination of psychotherapy sessions and relaxation treatments delivered over a 1-year period (total of 30 hours). These therapy sessions were intended to enhance participants’ coping skills and to reduce psychological distress related to CD. The results indicated that participants who received psychotherapy displayed a significantly greater decrease in days as an inpatient in a hospital as well as in number of sick leave days taken. In spite of the decreased utilization of health care resources, participants in the two groups did not differ in psychological measures (symptoms of depression and anxiety) or in the course of their illnesses. This study included a “high dose” of psychological interventions and over an extended period of time relative to similar studies. This is not the kind of intervention that could be brought to scale such that it would be available to large numbers of IBD patients.

Stress Management and IBD Participants with documented diagnoses of CD (N = 56) and UC (N = 58) were recruited for a study examining the effects of stress management psychotherapy on the course of illness and illness-­specific quality of life (Boye et al., 2011). Participants were randomly assigned to standard medical care or stress management + standard medical care. The stress management intervention consisted of three group sessions and six to nine private sessions, together with one to three booster sessions at 6- and 12-month follow-­ups. The intervention consisted of psychoeducational information on stress effects on the body, methods for coping with a chronic disease, problem-­solving skills training, relaxation methods, and cognitive-­behavioral therapy-­based approaches to improving coping with disease symptoms. Home-based assignments were also included as part of the intervention. Gastroenterologists who were unaware of participants’ treatment groups assessed disease activity at baseline and 3, 6, 12, and 18 months later. Samples were collected at each assessment point for measurement of fecal calprotectin (FC) and plasma C-­reactive protein (CRP), and an IBD quality-­of-life questionnaire was completed at 6, 12, and 18 months. The stress management intervention had no significant effects on the course of IBD or on the frequency of relapse in this study. However, there was a significant improvement in IBD quality of life at 18 months in those who received the stress management intervention. This improvement in IBD quality of life was limited to UC patients. These

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largely negative findings are disappointing given the strong indications that psychosocial stressors are involved in the onset and recurrence of IBDs.

Targeting Inflammation through Mindfulness Mucosal inflammation is a key pathophysiological feature of IBDs, and the level of inflammatory activity may be increased by psychosocial stressors. To address this possible connection between psychosocial stress levels and inflammation in patients with IBD, González-Moret et al. (2020) conducted a randomized controlled trial (∼2:1 ratio) to evaluate the impact of a mindfulness-­based intervention + standard medical management (N = 37) versus standard medical management alone (N = 20) on inflammatory biomarkers in IBD patients who had been free of symptoms for the previous 3 months. The mindfulness intervention involved a combination of four Internet-­based therapy sessions and four in-­person support sessions delivered over an 8-week period. These sessions involved information about and training in mindfulness, managing stressors, and guided meditation. The final session prepared participants to continue practicing the skills they had learned during the eight sessions. Measures of inflammatory biomarkers were taken at baseline and 6 months later. The measures included fecal calprotectin, CRP, and cortisol levels in hair samples. Calprotectin is a protein released by activated neutrophils and other immune cells during inflammation of the GI tract and is used clinically to assess levels of inflammation of the GI tract in patients with IBD. The results of this study revealed clear-cut benefits of the mindfulness intervention on inflammatory biomarkers. Compared to baseline levels, fecal calprotectin levels at 6 months decreased by 35% in the mindfulness group but increased by 123% in controls (p = .03), while CRP levels increased by 26% in the mindfulness group but increased by 113% in controls (p < .05). Hair cortisol levels did not differ between the two groups. These encouraging results suggest that levels of key inflammatory markers can be reduced in IBD patients who receive mindfulness training and related instruction. Unfortunately, no IBD outcomes, stress and coping measures, or quality-­of-life measures were included in this study that had a relatively small number of participants. However, the results are certainly promising enough to warrant follow-­up studies.

Acceptance and Commitment Therapy and IBD Wynne et al. (2019) developed a behavioral intervention to improve outcomes in IBD patients with CD and UC, with a particular focus on decreasing their levels of psychosocial stress. Eligibility for the study was defined as a perceived stress score ≥ 5 (range 1–10) or a quality-­of-life score > 80 (range 0–400), with higher scores reflecting a poorer quality of life. For the randomized controlled trial, IBD patients were randomly assigned to a control group that received standard medical care for IBD or to an intervention group that received acceptance and commitment therapy (ACT) together with standard medical care for IBD. ACT, which encourages patients to embrace positive life values and to accept adverse experiences as a normal part of life, was delivered in eight weekly, 90-minute sessions in groups of 14–16 participants. It overlaps with but is distinct from cognitive-­behavioral therapy and holds promise for applications in chronic diseases such as IBD (Graham, Gouick, Krahé, & Gillanders, 2016). Participants were evaluated at baseline, after the 8-week ACT intervention, and 3 months after



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the intervention. Unfortunately, 35% of participants dropped out of the study, leaving 42 participants in the control group and 37 participants in the ACT group. The impact of ACT was quite impressive relative to baseline stress levels, with a 39% decrease measured at 8 weeks and a 45% decrease at 20 weeks (p < .01). In contrast, participants in the control group displayed 8 and 11% decreases in stress levels at 8 and 20 weeks, respectively (ps > .20). Those receiving ACT also displayed significant decreases in perceived stress levels and significant improvements in depression scores and overall well-being but not in levels of anxiety. Finally, objective measures of IBD (e.g., levels of CRP and fecal calprotectin) were not affected by ACT. These encouraging findings must be tempered by the high dropout rate among participants in both the control and treatment groups. Thus, the final sample sizes were modest, and all participants were drawn from a single medical center in Ireland. In spite of these limitations, this study clearly points the way toward including psychological interventions such as ACT for targeting stress reduction and improving treatment outcomes for IBD patients (Wynne et al., 2019).

Summary The four studies summarized above convey a hopeful message regarding strategies for controlling psychosocial stressors for the benefit of IBD patients. Several stress reduction procedures were employed, and it may be that the exact approach taken should be personalized in some fashion to the individual patient. We are in the early stages of incorporating psychosocial interventions into the routine clinical care of patients with CD and UC. Time and effort and additional studies will be required to convince some gastroenterologists of the benefits of stress management interventions for their patients. A concerted effort will also be required to educate IBD patients about the potential benefits of psychosocial interventions. The end goal is simple—­improving patient care and outcomes and enhancing quality of life by targeting real-life stressors (Kredentser, Graff, & Bernstein, 2021).

IRRITABLE BOWEL SYNDROME Individuals with irritable bowel syndrome (IBS) experience chronic, recurring episodes of abdominal pain and discomfort as well as alterations in bowel habits. Patients with IBS are categorized into four major subtypes depending on their predominant stool patterns: IBS with constipation (IBS-C), IBS with diarrhea (IBS-D), IBS with mixed bowel habits (IBS-M), and unclassified IBS (IBS-U). IBS is one of several disorders of gut–brain interaction that is diagnosed based on a set of symptoms experienced by patients and referred to as the Rome IV criteria (Table 9.4). The etiology of IBS is complex, involving risk genes, the gut microbiome, GI infections, inflammatory responses, and psychosocial stressors, but it is incompletely understood (Hanning et al., 2021). The global prevalence of IBS is approximately 10%, but most of the relevant published studies were based on Rome III criteria. More recent estimates of the global prevalence of IBS using the more restrictive Rome IV criteria ranged from 3.8 to 4.1%, with females having higher rates of IBS than males, and younger people more likely to be diagnosed than adults greater than 50 years of age. There were also significant variations between countries in

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• Recurrent abdominal pain on average at least 1 day per week in the

last 3 months, associated with two or more of the following criteria: 1.  Related to defecation 2.  Associated with a change in frequency of stool 3.  Associated with a change in form (appearance) of stool

• Criteria must be fulfilled for the last 3 months, with symptom onset at least 6 months prior to diagnosis.

Note. Reproduced with permission of the Rome Foundation. Copyright © 2016 Rome Foundation, Inc. All Rights Reserved.

the prevalence of IBS, with higher rates in the United States, Russia, and Australia and lower rates in India, Canada, Mexico, Brazil, and most of Western Europe. As developing nations shift to a more Westernized diet and lifestyle, there is the potential for an increase in the prevalence of IBS worldwide (Black & Ford, 2020; Oka et al., 2020; Sperber et al., 2021). IBS patients frequently display comorbidity for other diseases of the gut–brain axis as well as chronic pelvic pain, fibromyalgia, and chronic fatigue syndrome. In addition, these patients may also be diagnosed with an anxiety disorder and/or depression. In considering the global burden of IBS, patients have reported a reduced quality of life, loss of freedom due to worries about access to a bathroom, and a lack of understanding of their difficulties by partners, family members, and friends. IBS patients also expend significant amounts of money for treatment of their symptoms. Finally, symptoms of IBS often compromise patients’ abilities to function effectively in their jobs and may lead to excessive absences from their places of employment (Black & Ford, 2020).

Psychosocial Stressors and IBS Psychosocial stress has for many years been advanced as a key factor in the etiology of IBS (Chang, 2011; Drossman et al., 1988; Mayer, Naliboff, Chang, & Coutinho, 2001; Pellissier & Bonaz, 2017). Several reports have noted strong associations between stressful or traumatic experiences in early life and the development of IBS in adolescence or adulthood. In addition, chronic exposure to one or several chronic psychosocial stressors increases the likelihood of a diagnosis of IBS, in part due to greater and more prolonged physiological responses of the gut–brain axis to stress. The three studies highlighted next examine the effects of various stressors on IBS patients.

Exposure to Laboratory Stressors Kennedy, Cryan, Quigley, Dinan, and Clarke (2014) compared the physiological and behavioral responses of female IBS patients (N = 13) and age-­matched healthy female controls (N = 15) to the Trier Social Stress Test (TSST). Measures were taken of salivary cortisol, salivary CRP, skin conductance levels, GI symptoms, mood, and self-­reported stress levels before and at timed intervals following the TSST protocol. IBS patients



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displayed prolonged cortisol responses to stress compared to controls, even though baseline levels were similar between the two groups.

Perceived Stress and IBS Parker et al. (2019) took a comprehensive approach to assessing how IBS patients experience stressors in early life as well as adulthood and how these experiences may influence the onset, severity, and recurrence of symptoms of IBS. IBS patients (N = 129) and healthy controls free of gastrointestinal disorders (N = 108) were recruited and asked to complete a series of questionnaires relating to life events, adverse childhood experiences, severity of IBS symptoms, and quality of life given symptoms of IBS. Subsets of the two groups were brought into the laboratory and given a challenge dose of corticotropin-­ releasing factor (CRF), and blood samples were collected for measurement of ACTH and cortisol. This study revealed that IBS patients experienced a similar number of stressful life events in adulthood compared to controls, but they perceived these events as more stressful or negative. Early life stressors interacted with adult stressful experiences to increase the likelihood of developing IBS. In IBS patients, negative perceptions of life stressors in adulthood were associated with enhanced severity of symptoms and reduced quality of life. Finally, IBS patients displayed a pattern of dysregulation of the HPA axis consistent with a greater level of allostatic load over the lifespan (Parker et al., 2019).

Posttraumatic Stress Disorder Ng et al. (2019) were intrigued by a possible connection between symptoms of hyperarousal and hypervigilance characteristic of posttraumatic stress disorder (PTSD) and the development of IBS. They conducted a systematic review and meta-­analysis to explore the association between PTSD and IBS. Eight published studies met their inclusion criteria and included approximately 650,000 participants, most of whom were U.S. military veterans. They found a highly significant association between PTSD and IBS (OR = 2.80, 95% CI = 2.06–3.54). The hyperarousal and enhanced stress responses of patients with PTSD could influence the visceral hypersensitivity of the GI tract, predisposing individuals to develop symptoms associated with IBS.

STRESS‑TARGETED INTERVENTIONS FOR IBS Internet‑Based Delivery Platforms An Internet-­based platform for delivery of behavioral interventions for IBS patients is appealing because it can be delivered asynchronously, it is much more cost effective than in-­person intervention sessions, and it eliminates required trips away from home for individuals who may have worries about flares of their GI-­related symptoms and access to a bathroom. Ljótsson et al. (2011) designed a clinical study to compare the effectiveness of exposure-­based cognitive-­behavioral therapy (EB-CBT) and a more traditional stress management program (SM). Some critical features of these 10-week programs include:

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• EB-CBT. This program was designed to tackle head-on the GI-­specific anxiety symptoms that are thought to be critical in maintaining and even amplifying the symptoms of IBS. A focus on controlling symptoms and having easy access to a bathroom may set up a vicious cycle of being more aware of IBS-­related symptoms, thereby increasing the severity of the symptoms. The EB-CBT program encouraged participants to accept their beliefs and feelings regarding IBS and to engage with aversive stimuli and limitation of activities, with an overall goal of improving quality of life. Specifically, participants were encouraged to engage in activities known to provoke symptom onset, reduce or eliminate behaviors designed to control symptoms, and enter situations where symptoms would be undesirable, such as in meetings or on public transportation. These components of the program were a great deal to ask of participants, but they were presented in an open and supportive manner. • SM. In contrast, the SM program represented an effective control condition, for it was delivered in a therapeutic manner and it included strategies for reducing the impact of daily life stressors thought to play a role in IBS. However, it did not overlap with the critical elements of the EB-CBT intervention. The effectiveness of the EB-CBT and SM interventions in this study were gauged by the IBS version of the Gastrointestinal Symptom Rating Scale (GSRS). Immediately after the interventions and at the 6-month follow-­up, both groups displayed significant improvements in scores on the GSRS, but the improvements were significantly greater in the EB-CBT group. A similar pattern of results was evident for measures of IBS-­related quality of life. These investigators suggested that exposure exercises as contained in the EB-CBT program may be more effective in treating IBS symptoms than stress and symptom management interventions. They also cautioned that this program requires a great commitment from patients and may only work well for a select subset. Use of an Internet-­based delivery platform allows clinicians to reach many more patients at scale and in a cost-­effective manner (Ljótsson et al., 2011).

Therapy at Home for IBS Lackner et al. (2018) conducted a randomized controlled trial to determine the effectiveness of cognitive-­behavioral therapy (CBT) administered in a largely home-based program or in a clinical setting compared to an educational program on symptoms associated with IBS. IBS patients with moderate to severe symptoms were recruited, followed for a 4-week baseline period, and randomly assigned to one of three groups: (1) standard CBT (S-CBT; N = 146) delivered in 10 weekly sessions with a therapist, (2) modified CBT (M-CBT; N = 145) delivered in four face-to-face sessions over a 10-week period, but with extensive supplemental home-based study materials, or (3) an educational program (ED; N = 145) that was equivalent to the M-CBT program in time and contact with health professionals but that focused on education, support, and personal reflection related to IBS without any mention of CBT-­related approaches. Participants were predominantly female (80%) and non-­Hispanic White (89%). The results of this study revealed that a program involving M-CBT was significantly more effective than the ED program in achieving moderate to substantial improvement in symptoms associated with IBS based on patient ratings as well as assessments



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by gastroenterologists who were not aware of assignment to treatment groups. These results indicated that the M-CBT and S-CBT programs were comparable in their beneficial effects on symptoms in IBS patients. These results were consistent immediately after and were maintained up to 6 months following the end of the CBT programs. Using an educational control group was important in that it allowed for comparable time spent with a health professional, and it provided valuable information on managing IBS symptoms. The magnitude of the improvements observed for the CBT groups compared well with standard dietary and pharmacological treatments. A consideration for the future would be how to maximize the timing of CBT booster sessions well after training periods through brief online sessions or through the use of mobile apps to maintain the beneficial effects of symptom relief (Lackner et al., 2018).

Summary IBS is a source of significant distress for many patients, and this issue must be tackled directly for positive benefits to be realized. The two studies summarized above provide support for use of Internet-­delivered behavioral treatments to reduce the impact of IBS-­ related symptoms on patient quality of life. In both instances, the investigators employed a modification of CBT as the intervention, and significant benefits were reported. Other approaches, including mindfulness-­based stress reduction, have also shown positive benefits for IBS patients (Zernicke et al., 2013) and have been encouraged as part of an overall treatment plan for patients with IBS (Vasant et al., 2021). Black et al. (2020) conducted a meta-­analysis of 41 randomized controlled trials of behavioral interventions with IBS patients (N = 4,072 participants) using a variety of treatment approaches. Based on analyses of relative risk (RR), the most effective interventions included self-­administered or minimal contact CBT (RR = 0.61; 95% CI = 0.45–0.83), face-to-face CBT (RR = 0.62; 95% CI = 0.48–0.80), and gut-­directed hypnotherapy (RR = 0.67; 95% CI = 0.49–0.91) (Whorwell, Prior, & Faragher, 1984). The take-home message from this meta-­analysis is that a variety of behavioral interventions was consistently superior to routine medical management in reducing IBS symptoms. Unfortunately, many IBS patients are unwilling to commit to such therapies or are not encouraged to do so by their physicians.

CONCLUSIONS Advances in the study of the microbiome–­gut–brain axis have given us a deeper understanding of the interconnections between stress and the GI system. The microbiome–­ gut–brain axis involves dynamic bidirectional channels of communication between the brain and the GI system through signaling molecules released by the gut microbiota and centrally directed alterations in the autonomic nervous system and the HPA axis. The GI system is regulated in part by the autonomic nervous system, but it also has its own enteric nervous system. In addition, multiple types of endocrine and immune cells are interspersed along the gut wall, influenced by signaling molecules released from microbiota in the gut lumen. Psychosocial stressors have a significant impact on the symptoms of patients with peptic ulcers, IBD, and IBS, and may play a critical role in increasing the frequency and

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severity of disease flares. These GI diseases are often disabling and life-­altering, and effective interventions have been shown to result in more effective disease management and improvements in quality of life. Because of the encouraging responses of patients with GI disorders to psychosocial interventions, a biopsychosocial approach has shown promise in providing personalization of treatment for patients with a variety of GI disorders. This model of care requires the co-­location of specialists, including clinical and health psychologists, to provide an integration of services for patients with GI disorders. Among the services would be an evaluation of comorbid psychological disorders, including depression and anxiety, as well as a consideration of the level of perceived life stressors. An integrated treatment plan would include interventions to address comorbidities and develop coping skills for more effective management of life stressors (Mikocka-­Walus, Turnbull, Holtmann, & Andrews, 2012).

CHAPTER 10

Stress and Cancer

A

diagnosis of cancer is one of the most dreaded things patients will hear from their physicians. Unfortunately, cancer will touch most of us at some point in our lives either directly or through a close friend or loved one who is diagnosed with cancer. In this chapter, we will explore the interconnections between psychosocial stressors and cancer and consider whether stress management interventions improve the prognosis of cancer patients. Cancer is a bewildering combination of tumor types and affected tissues in the body. At its most basic level, however, cancer is a disorder of the cell cycle, involving a state of uncontrolled cell division as well as a failure of some cells to die off when their appointed time comes. In an attempt to bring order to the chaos of cancer, Hanahan and Weinberg (2011) published an influential review article on the six hallmarks, two emerging hallmarks, and two enabling characteristics of cancer to focus attention on identifying promising targets for the development of new cancer therapeutics (Table 10.1). As we will see later in this chapter, these hallmarks and enabling characteristics may be affected by psychosocial stressors through the responses of the sympathetic– adrenomedullary system, the HPA axis, and the immune system.

HISTORICAL CONNECTIONS BETWEEN STRESS AND CANCER The first written record of cancer appeared in an Egyptian papyrus that has been dated to the 17th century B.C.E. This papyrus, known as the Edwin Smith papyrus after the Englishman who acquired the artifact in Luxor in 1862, was translated in 1930. It is actually a rough transcription of a much older collection of writings from around 2500 B.C.E. that has been attributed to the celebrated Egyptian physician, Imhotep. Included in these 48 case studies was a description of a woman with a “bulging mass in the breast” for which there was no treatment. This is one of the few references to cancer in an ancient medical text because people living in those times had relatively short 195

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TABLE 10.1.  The Six Hallmarks, Two Emerging Hallmarks, and Two Enabling Characteristics of Cancer Hallmarks 1.  Sustained proliferation: dysregulation of growth-promoting signals leads to uncontrolled cell division. 2.  Lack of response to growth-inhibiting signals: this includes an inability of tumor suppressor genes to stop cell division. 3.  Resisting programmed cell death (apoptosis): genes and signaling pathways that normally allow cells to die are suppressed or inactivated. 4.  Achieving immortality: cancer cells can replicate even after many generations of growth. 5.  Promotion of angiogenesis: this process provides blood vessels that support tumor growth with a source of nutrients and a means to eliminate waste products. 6.  Metastasis and invasion of other tissues: cancer cells may migrate from their original site of development and invade and colonize other tissues. Emerging hallmarks 1.  Reprogramming energy metabolism: cell growth and rapid rates of cell division require substantial levels of energy. Cancer cells undergo a metabolic switch to depend on metabolism of glucose rather than mitochondrial oxidative phosphorylation. 2.  Evading immune detection: cancer cells may develop the ability to avoid detection by various components of the immune system. Enabling characteristics 1.  Genome instability: this problem results in the generation of random mutations, including chromosomal rearrangements, that contribute to hallmark capabilities. 2.  Tumor-promoting inflammation: various immune cells infiltrate some tumors to create an inflammatory state that contributes to hallmark capabilities.



Note. Based on Hanahan and Weinberg (2011).

lifespans and, above all else, cancer is a disease that increases in frequency with age (Mukherjee, 2010). Let’s fast-­forward to about 400 B.C.E. and consider the writings of the Greek physician Hippocrates and his followers, who believed that cancer was one of many diseases that arose from an imbalance of the four humors, blood, phlegm, black bile, and yellow bile. Black bile was especially problematic as a cause of cancer. Some 600 years later, Galen of Pergamon observed that women who had a melancholic disposition were more likely to develop breast cancer because of an excess of thick black bile. Over the course of his professional life, Galen wrote more than 100 notes relating to cancer, and these notes were later translated from Greek into Latin and were widely distributed and highly influential for a millennium (Hajdu, 2011). These early connections between breast cancer and depression will be explored in greater detail as we progress through this chapter.

CANCER AND THE GLOBAL BURDEN OF DISEASE Global cancer statistics present a grim picture that faces many countries in the world in spite of advances in the detection and treatment of cancers that have been developed



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over the past several decades. In 2017, global estimates indicate that there were 24.5 million incident cases of cancer, 9.6 million deaths, and 233.5 million disability-­adjusted life-years (DALYs). Between 2007 and 2017, incident cases of cancer increased by 33%, with the smallest increases occurring in the most developed countries. Fifty-one percent of all incident cases of cancer occurred in highly developed nations, but only 30% of deaths and 24% of DALYs (Global Burden of Disease Cancer Collaboration, 2019). In the United States, approximately 1.9 million incident cases of cancer were diagnosed, and more than 608,000 people died of cancer in 2021. Cancer is the second-­ leading cause of death in the United States, topped only by heart disease. The risk of cancer increases with advancing age, and more than 80% of all incident cases of cancer are diagnosed in individuals greater than 55 years of age. The age-­adjusted cancer death rate peaked in 1991 at 215 cancer deaths per 100,000 people. By 2015, the rate had decreased to 149 deaths per 100,000 due in large measure to reductions in smoking and improvements in early detection and treatment. Table 10.2 summarizes estimates for 2021 of the leading causes of incident cases of cancer and deaths for males and females in the United States (Siegel, Miller, Fuchs, & Jemal, 2021).

PSYCHOSOCIAL STRESSORS INCREASE THE RISK OF DEVELOPING CANCER On the surface, this seems like a relatively straightforward statement. However, if one steps back and considers the significant challenges of developing a research design to address this issue, the task is anything but straightforward. Some of the many issues that must be tackled include: how does one measure stress levels, how frequently should stress levels be measured, are cross-­sectional or prospective studies more likely to provide definitive results, what sample size is required to provide sufficient statistical power,

TABLE 10.2.  Estimates for 2021 of the Top Five Incident Cases of Cancer by Type and the Five Leading Causes of Cancer Deaths for Males and Females in the United States Type of cancer Prostate Lung and bronchus Colon and rectum Urinary bladder Melanoma of the skin

Males, incident cases 248,530 119,100  79,520  64,280  62,260

Deaths Lung and bronchus Prostate Colon and rectum Pancreas Liver/bile duct

Type of cancer Breast Lung and bronchus Colon and rectum Uterine Melanoma of the skin

Females, incident cases 281,550 116,660  69,980  66,570  43,850

Deaths  69,410  34,130  28,520  25,270  20,300

Lung and bronchus Breast Colon and rectum Pancreas Ovary

Note. Data are from the Centers for Disease Control and Prevention.

 62,470  43,600  24,460  22,950  13,770

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and can stress effects be disentangled from the many other factors that influence rates of cancer diagnosis? Several studies are presented below that tackled these challenges and provided some interesting insights relating to this important matter.

Work Stress and Cancer in Europe In one of these studies, Heikkilä et al. (2013) reported the results of a meta-­analysis of 12 independent studies conducted in six European countries from 1985 to 2008. These studies were part of the Individual Participant Data Meta-­A nalysis in Working Populations (IDP-Work) Consortium. At the beginning of the study, participants (N = 116,056) who were free from cancer completed baseline questionnaires relating to health and lifestyle factors and job strain, defined as a combination of high demand and low control at work. Over a median follow-­up period of 12 years, incident cancers were ascertained from local and national health registers. Over the course of the study, 5,765 incident cases of cancer were diagnosed in study participants. High job strain was not associated with overall risk of a cancer diagnosis (HR = 0.97, 95% CI = 0.90–1.04), and the same held true for several types of frequently occurring cancers (i.e. colorectal, lung, breast, and prostate cancers). One could argue that the impact of job strain on cancer must play out over a longer period of time, but other reports using similar methodologies have noted a significant impact of job strain on heart disease and diabetes as noted in Chapters 7 and 8, respectively.

PTSD and Risk of Cancer: A Nationwide Cohort Study In this study, Gradus et al. (2015) examined the impact of exposure to a traumatic stressor followed by the development of PTSD on later diagnosis of cancer. The study population included all Danish-­born residents of Denmark who received a diagnosis of PTSD within the Danish hospital system and who had not been diagnosed with cancer during the year following the PTSD diagnosis (N = 4,131). No significant association between PTSD and a later diagnosis of various types of cancer was determined (Standardized incidence ratio = 1.00, 95% CI = 0.88–1.20).

Stress and Risk of Cancer in Japan Song et al. (2017) analyzed data from a large population-­ based cohort study, the Japan Public Health Center-­Based Prospective Study (JPHC study), with initial enrollment of participants aged 40–69 years (mean age = 53 years and approximately equal numbers of males and females) occurring between 1990 and 1994. All participants completed an initial questionnaire relating to medical conditions and lifestyle issues and were encouraged to complete a follow-­up questionnaire 5 years later. Participants who answered the question “How much stress do you have in your daily life?” on the baseline questionnaire and were cancer-­free at that time were included in the analyses (N  =  101,708). Diagnoses of cancer were noted through cancer registers or through local hospital records. Over a mean follow-­up time of approximately 17 years, 17,161 participants were diagnosed with cancer. The association between perceived stress levels at baseline (low,



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medium, or high) and incidence of cancer was modest and was not maintained after adjusting for other relevant cancer risk factors, including BMI, diet, smoking, level of physical activity, and family history of cancer. However, longitudinal data on perceived stress levels revealed a modest but significant increase in cancer risk for all participants who reported experiencing medium or high levels of stress compared to the reference group with low stress levels, even after adjusting for relevant cancer risk factors. This effect of perceived stress levels was evident in males but not females (see Table 10.3). Further analyses indicated that participants who reported consistently high levels of perceived stress had an 11% excess risk of cancer compared to participants with consistently low levels of perceived stress. This association was limited to high-­stress males, who had a 19% excess risk of cancer compared to males with low levels of perceived stress. In addition, an association between long-term perceived stress levels and a cancer diagnosis was limited to participants without a family history of cancer and was more likely to occur in participants who smoked or drank alcohol and were classified as obese based on their BMIs. These findings were strongly associated with diagnoses of cancers of the liver and prostate (HRs = 1.33 and 1.28, respectively). One obvious concern about this study is that perceived stress levels were reflected in a single question and quantified as low, medium, or high. However, the simplicity of this measure and the fact that 78% of the initial group of participants responded to the same question at the 5-year follow-­up were significant strengths, permitting an analysis of the effects of changing patterns of perceived stress over time. Male participants who maintained consistently high levels of perceived stress were at a 10–20% excess risk of a cancer diagnosis (Song et al., 2017).

Stressful Life Events and Breast Cancer Risk Fischer, Ziogas, and Anton-­Culver (2018) employed a case–­control design to explore the relationship between the perception of stressful life events and occurrence of breast cancer. Women with breast cancer were recruited from the Cancer Surveillance Program of Orange County, California (N = 664), and cancer-­free women who served as controls were recruited from the same area (N = 203). All participants completed a detailed epidemiological risk factor questionnaire that also included questions related to experiences with stressful life events. All participants with breast cancer completed the TABLE 10.3.  Effects of Perceived Stress Levels on Risk of a Cancer Diagnosis in Participants in the Japan Public Health Center-Based Prospective Study Perceived stress levels Low Medium High p value for trend

Total sample

Males

Females

Reference 1.04 (1.01–1.09) 1.06 (1.00–1.11)

Reference 1.07 (1.02–1.13) 1.10 (1.03–1.18)

Reference 1.01 (0.95–1.08) 1.02 (0.93–1.10)

p = .048

p = .002

p = .700

Note. Data are expressed as hazard ratios with 95% confidence intervals and reflect adjustments for known cancer risk factors. Significance levels for a trend of increasing risk of a cancer diagnosis with increasing levels of perceived stress are also included. Data are from Song et al. (2017).

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questionnaire within 3 years of their initial diagnosis. Stressful life events were selected from the original report of Holmes and Rahe (1967) and were modified to include information about their perceived stressful nature. Participants with breast cancer rated stressful life events that occurred prior to receiving a breast cancer diagnosis. Cumulative life events perceived as stressful were associated with an increased risk of breast cancer in a dose–­response relationship (OR = 1.63, 95% CI = 1.00–2.66, p = .045). In contrast, life events perceived as nonstressful did not have a significant impact on breast cancer risk. Previous personal illness was significantly associated with increased risk of breast cancer, whether the illness was perceived as stressful (OR = 2.84, 95% CI = 1.96–4.11) or not (OR = 3.47, 95% CI = 1.34–8.94). Those who were most sensitive to stressful life events included younger women, women who had not given birth previously, and women who delayed having children until later ages (Fischer et al., 2018).

Social Integration and Marital Status Influence Risk of Ovarian Cancer Using data from the Nurses’ Health Study, Trudel-­Fitsgerald et al. (2019) examined the effects of social integration and marital status on risk of ovarian cancer. Women enrolled in the Nurses’ Health Study completed the Berkman–­Syme Social Network Index and reported their marital status every 4 years beginning in 1992 (N = 72,206), and they were followed over the next 20 years. Estimates of hazard ratios and 95% confidence intervals were determined for risk of ovarian cancer in lagged analyses where psychosocial indicators were assessed 4–8 years (N = 436 cases) and 8–12 years (N = 306 cases) before diagnosis to account for the effects of prediagnostic symptoms on psychosocial measures. Social isolation was associated with an increased risk of ovarian cancer 8–12 years later (HR = 1.51, 95% CI = 1.07–2.13), but not 4–8 years later. Compared to married women, risk of ovarian cancer was significantly greater in widows (HR = 1.57, 95% CI = 1.15–2.14) but not in women who were separated/divorced (HR = 1.13, 95% CI = 0.74–1.72). These findings indicate that risk of ovarian cancer was higher in women who were socially isolated or had lost their spouses. These effects were especially evident when these psychosocial stressors were experienced a decade before diagnosis or were sustained over a long period of time. These findings are powerful in that they were drawn from a large sample of women who were followed prospectively.

Summary The five studies summarized above capture some of the challenges of designing experiments to determine if exposure to stressful life events serves as a risk factor for cancer. In spite of these challenges, a consensus has emerged that chronic life stressors result in high levels of allostatic load, which are translated into disturbances in neural, endocrine, and immune systems that facilitate the induction and progression of cancer. These disturbances include enhanced b-adrenergic signaling to promote tumor growth and elevated levels of inflammation that lead to decrements in immune surveillance, with a corresponding increase in the survival of cancer cells (Antoni et al., 2006; Cui et al., 2021; Dai et al., 2020; Mravec, Tibensky, & Horvathova, 2020a; Sephton & Spiegel, 2003; Zhang, Pan, Chen, Jiang, & Huang, 2020).



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THE IMPACT OF PSYCHOSOCIAL STRESSORS AND LEVELS OF SOCIAL SUPPORT ON MORBIDITY AND MORTALITY FOLLOWING A DIAGNOSIS OF CANCER Receiving a diagnosis of cancer is one of life’s most stressful experiences. Will my cancer lead to an early death? How will my family cope with the news of my diagnosis? Will my career be adversely affected? How will I tell my children? Can I handle the difficulties associated with surgery, radiation treatment, and chemotherapy? These and other immediate concerns and challenges may be overwhelming for some patients, resulting in dramatic elevations in levels of psychosocial stress. In this section, we will explore the impact of levels of stress and coping on clinical outcomes and survival in cancer patients.

Psychosocial Factors and Cancer Outcomes: A Meta‑Analysis Pinquart and Duberstein (2010) identified 87 published reports relating to the impact of perceived social support, social network size, and marital status on rates of cancer survival. The combined sample size from these 87 published reports was 10,795,137 participants, with a mean age of 66 years. In the combined sample, 57% were women, 87% were married, and 14% were members of ethnic minority groups. The average time between assessment of social network characteristics and survival was approximately 7 years. Having higher levels of perceived social support, belonging to a larger social network, and being married were associated with decreases in relative risk for mortality of 25, 20, and 12%, respectively. Additional analyses revealed that never married participants had higher mortality rates than widowed and divorced/separated participants. Connections between social network measures and mortality were greater in younger participants, and associations of marital status with mortality were stronger in studies with shorter time intervals and in early-stage cancers. The impact of social support varied by type of cancer, with stronger associations of social support observed in studies of patients with leukemia and lymphomas and stronger associations of network size observed in studies of women with breast cancer. The impact of measures of social support was of obvious clinical significance; however, most individual studies have failed to detect these effects because they have not been sufficiently powered. A somewhat surprising finding was the lack of gender differences in associations of perceived social support, network size, and marital status with mortality from cancer. The findings of this important meta-­analysis point to the development of interventions in newly diagnosed cancer patients that would enhance their social networks and hopefully improve their clinical outcomes and increase their survival (Pinquart & Duberstein, 2010).

Social Support and Ovarian Cancer Social support has been shown to have beneficial effects on health through direct effects as well as indirectly by providing a buffer against the negative effects of psychosocial stressors. Earlier research revealed that levels of social support were associated with variations in disease-­related biomarkers in patients with ovarian cancer. However, the

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clinical relevance of variations in levels of social support on patient outcomes was not investigated. To address this important issue, a prospective study of women diagnosed with ovarian cancer was conducted that focused on the impact of social support on long-term survival. Two types of social support were assessed: social attachment, a type of emotional social support that reflects connections with others, and instrumental social support, a type of support that reflects the availability of assistance during times of need. Patients were prospectively recruited during a presurgical clinic visit, and they completed the Psychosocial Provisions Scale and a questionnaire on demographic factors. They were also assessed for depression. One hundred sixty-eight patients with histologically confirmed epithelial ovarian cancer were recruited from three medical centers and were followed from the date of surgery for an average of 2.73 years. At the time of diagnosis, 71% of women had advanced-­stage ovarian cancer and 86% had a high-grade tumor. At the end of the follow-­up period, 103 women were still alive (61%). After adjusting for disease stage, grade, histology, residual disease, and age, greater levels of social attachment were associated with a lower likelihood of death (HR = 0.87, 95% CI = 0.77–0.98, p < .018). The median survival time for patients with low social attachment scores was 3.35 years (95% CI = 2.56–4.15 years). In contrast, 59% of patients with high social attachment scores were still alive after 4.70 years. No significant association was found between instrumental social support and survival, including after adjustment for covariates. Social attachment was associated with a significant survival advantage for patients with ovarian cancer. The authors suggested that high levels of social attachment functioned as a stress buffer, reducing the activities of the sympathetic nervous system and the HPA axis. In addition, the results underscored the importance of screening for deficits in the social environment and emphasized the value of providing social support following surgery and adjuvant treatment (Lutgendorf et al., 2012). Adjuvant treatment includes chemotherapy, radiation therapy, hormone therapy, and immunotherapy and is intended to reduce the risk of cancer recurrence.

Psychosocial Stress and Chronic Lymphocytic Leukemia Chronic lymphocytic leukemia (CLL) is the most prevalent leukemia in adults, with more than 15,000 new diagnoses and 5,000 deaths in the United States each year. Most patients are asymptomatic when diagnosed and are usually referred after an elevated white blood cell count is detected during a routine annual check-up (Nabban & Rosen, 2018). Andersen and coworkers (Andersen et al., 2018) examined correlations between psychosocial stressors and disease-­specific, negative prognostic cellular, cytokine, and chemokine markers in patients with CLL. A single-­group, observational design was used. Patients with relapsed/refractory CLL (N = 96) who were entering a Phase II clinical trial of an experimental therapy, ibrutinib (Imbruvica), were studied. Before the first dose of the drug, patients completed a self-­report measure of stress (the Impact of Event Scale), and blood was drawn for measurement of absolute lymphocyte counts and levels of cytokines and chemokines. Multiple linear regression models tested stress as a concurrent predictor of absolute lymphocyte counts; of cytokines (tumor necrosis factor alpha [TNF-a], a proliferation-­ inducing ligand [APRIL], B-cell activating factor [BAFF], interleukin 6 [IL-6], IL-10, IL-16, and vascular endothelial growth factor [VEGF]); and of the chemokine C-C



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motif ligand 3 (CCL3). After adjusting for demographic variables, comorbidities, CLL genetic risk, and correlates of inflammation, stress predicted higher absolute lymphocyte counts (p < .05) and higher levels of TNF-a (p < .05), IL-16 (p < .01), and CCL3 (p < .05). Levels of stress were not associated with measures of APRIL, BAFF, IL-6, IL-10, or VEGF. These findings demonstrate that levels of psychosocial stress are associated with enhanced levels of cellular, cytokine, and chemokine markers associated previously with progression of disease in CLL. Stress appears to influence cancer cell proliferation and survival by upregulating immune and inflammatory processes.

Psychosocial Influences on Ovarian Cancer as Revealed by Exosomal Analyses A major challenge for psycho-­oncology is to understand how psychosocial factors experienced by patients are translated into molecular changes in the tumor microenvironment that affect cancer progression and patient outcomes. To confront this challenge, researchers have turned their attention to exosomes, small extracellular vesicles released from most cell types in the body. Exosomes are highly heterogeneous and consist of a lipid bilayer containing all of the normal constituents of a cell, including proteins, lipids, RNA, and DNA. Once released from their cells of origin, exosomes have the ability to fuse with the plasma membrane of recipient cells and inject their contents into the cytoplasm of the receiving cell. This provides a novel means of cell-to-cell communication that lacks the specificity of receptor-­based neural or hormonal signaling (Pegtel & Gould, 2019). Human blood is estimated to contain 2 x 1015 exosomes, and this number doubles for cancer patients. Exosomes produced by tumors appear to promote further development of the tumor as well as metastatic spread to other locations in the body. Circulating exosomes have also been used as a “liquid biopsy” to detect, diagnose, and treat certain cancers. Exosomes shed from tumors contain a variety of tumor-­specific antigens that are characteristic of the cells of origin. In addition, exosomes provide a useful biomarker to track how psychosocial stressors impact the progression of tumors (Kalluri, 2016). A study by Lutgendorf et al. (2018) examined exosomal profiles from patients with low or high levels of social support for epithelial mesenchymal transition (EMT) polarization and gene expression related to inflammation and b-adrenergic signaling. Exosomes were isolated from plasma samples obtained from 40 women before primary surgical resection of Stage III and IV ovarian cancer at three academic medical centers. Samples were selected for analysis on the basis of extremes of low and high levels of social support. Following isolation of exosomes and RNA extraction, a microarray analysis of the transcriptome was performed. Primary analyses identified significant upregulation of 67 mesenchymal-­characteristic gene transcripts and downregulation of 63 epithelial-­characteristic transcripts in patients with low social support; this demonstrated increased EMT polarization (p < .0002). Secondary analyses using promoter sequence bioinformatics supported a priori hypotheses linking low social support to (1) increased activity of cyclic adenosine monophosphate response element binding protein (CREB)/activating transcription factor (ATF) family transcription factors that mediate the b-adrenergic response to catecholamines via the cyclic adenosine monophosphate/ protein kinase A signaling pathway (mean fold change for CREB: 2.24 ± 0.65; p < .002; mean fold change for ATF: 2.00 ± 0.55; p < .005) and (2) increased activity of

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the pro-­inflammatory nuclear factor kB/Rel family of transcription factors (mean fold change: 2.10 ± 0.70; p < .02). These findings suggest the possibility of leveraging exosomes as a noninvasive assessment of biobehavioral factors to inform personalized treatment approaches in cancer patients.

Stress and Social Support in Prostate Cancer Patients Jan et al. (2016) utilized data from the National Prostate Cancer Registry to examine interactions among perceived stress, social support, disease progression, and mortality in a retrospective population-­based cohort of men with prostate cancer. The study surveyed 4,105 Swedish men treated for nonmetastatic prostate cancer regarding perceived stress, grief, sleep habits, and levels of social support. Over a mean follow-­up period of 51 months following completion of the questionnaires, 127 men died of prostate cancer and 276 men died from other causes. Men with the highest levels of perceived stress had a significantly increased rate of prostate cancer-­specific mortality compared with men with low stress levels (HR = 1.66, 95% CI = 1.05–2.63). Men with high-­stress levels also experienced a higher frequency of grieving and sleep loss. They had fewer people to confide in and felt unable to discuss their problems with partners, friends, or family members. These findings add to the area of psychosocial quality of life research in men with prostate cancer and have important implications for designing interventions to improve quality of life in men with prostate cancer.

PSYCHOSOCIAL STRESSORS PROMOTE CANCER METASTASIS Primary tumors consist of a heterogeneous mixture of cell types that contain a profile of genetic changes that permit some of these cells to escape from the primary tumor, move into the lymphatic and circulatory systems, and form secondary tumors in other parts of the body. This process of metastasis is responsible for up to 90% of all cancer deaths, and understanding the steps involved in this complex pathway of cancer cells leaving the primary tumor and forming secondary tumors is a major challenge for cancer biologists. Another less-­studied facet of metastasis is the potential role of psychosocial stressors in promoting the formation of secondary tumors (Chiang & Massagué, 2008; Steeg, 2016). In this section, we will take a look at research relating to the ways in which biological responses to stressful stimulation may exacerbate metastatic processes (Figure 10.1). Stressful stimuli have been shown to modulate cancer progression through release of the catecholamines, norepinephrine and epinephrine, from the sympathetic–­adrenal medullary system. Extensive research on cancer cells maintained in vitro and studies of animal models indicate that catecholamine signaling through a- and b-adrenergic receptors exerts many favorable effects on cancer progression, including enhanced proliferation and survival of cancer cells, increased formation of blood vessels to support tumor growth (angiogenesis), downregulation of the immune system, upregulation of inflammation, and facilitation of movement of cancer cells from the tumor microenvironment into adjacent tissues (Conceição, Sousa, Paredes, & Lamghari, 2021). Unfortunately, translating these basic research findings into clinical practice is not a simple matter, and more extensive studies with patients having a variety of cancers is required.



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FIGURE 10.1.  Stressors activate the sympathetic nervous system (SNS) and the hypothalamic–­ pituitary–­adrenocortical (HPA) axis, resulting in the release of cortisol (CORT) from the adrenal cortex and epinephrine (EPI) from the adrenal medulla. Both of these hormones are delivered by the circulation to a developing tumor, where they promote metastatic processes.

This remains an active area of research, and the coming years will hopefully bring new breakthroughs in treatment (Cole, Nagaraja, Lutgendorf, Green, & Sood, 2015).

Beta‑Blockers and Breast Cancer. In a proof-of-­concept study, Powe et al. (2010) followed 466 consecutive female patients with operable breast cancer for more than 10 years. Three subgroups of patients were formed: (1) women with hypertension who were treated with beta-­blockers for at least 1 year prior to a breast cancer diagnosis (N = 43), (2) women with hypertension who were treated with other antihypertensive medications for at least 1 year prior to a breast cancer diagnosis (N = 49), and (3) women with breast cancer but without hypertension, who served as a control group (N = 374). These groups were similar in terms of age; primary tumor size, type, and stage; and extent of vascular invasion. Those women who received beta-­blockers prior to being diagnosed with breast cancer were less likely to develop metastases (p < .03) and experience tumor recurrence (p < .01) and had a longer cancer-­free period (p < .01) than controls. In addition, women who received beta-­ blockers had a dramatic 71% reduction in breast cancer mortality after 10 years (HR = 0.29, 95% CI = 0.119–0.715).

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This study raises some concerns. The sample size was modest, and the investigators did not make any distinctions between the type of beta-­blocker that was prescribed. However, the results were strongly suggestive of an effect of beta-­blockers on metastatic processes and survival following a breast cancer diagnosis. A major need going forward is a series of randomized clinical trials of beta-­blockers that center on rates of cancer recurrence and patient survival. Other research involving beta-­blockers and cancer have appeared since this original study. Childers, Hollenbeak, and Cheriyath (2015) conducted a meta-­analysis of published studies on beta-­blockers and breast cancer outcomes that encompassed research published between 2010 and 2013. They concluded that the use of beta-­blockers significantly reduced the risk of death in women diagnosed with breast cancer (HR = 0.50, 95% CI = 0.32–0.80). Baek, Kim, Kim, Kim, and Park (2018) drew a similar conclusion in a population cohort study of women with ovarian cancer. Those women who were taking beta-­blockers had better survival outcomes compared to those women who did not take beta-­blockers. Finally, Na et al. (2018) conducted a large-scale meta-­analysis of all research on beta-­blockers and cancer published up to September 2017. The combined sample size was slightly greater than 319,000 patients. There was no evidence of a favorable effect of beta-­blockers on overall cancer outcomes for the pooled sample of patients. However, there was evidence of improved survival in patients with ovarian and pancreatic cancer and melanoma who were taking beta-­blockers.

Social Well‑Being Reduces Expression of Genes Related to Inflammation and Metastasis Jutagir et al. (2017) explored the relationship between social well-being and genes related to inflammation and metastasis in women who had surgery for breast cancer. Social well-being concerns the subjective feeling of being close to, supported by, and satisfied with interactions with family and friends. High levels of social well-being have been linked to improved adaptation and longer survival following a breast cancer diagnosis. This experiment tested whether greater self-­reported levels of social well-being were associated with lower levels of pro-­inflammatory and pro-­metastatic leukocyte gene expression following surgery for nonmetastatic breast cancer. Fifty women diagnosed with nonmetastatic (0–III) breast cancer were enrolled 2–8 weeks after surgery and prior to adjuvant therapy. Leukocyte gene expression for specific pro-­inflammatory (cytokines, chemokines, and their receptors and COX-2) and pro-­metastatic genes (e.g., MMP9, LMNA) were quantified from microarray analyses. Data analyses controlled for age, stage of disease, days postsurgery, education, and BMI. The results indicated that higher levels of social well-being were associated with less leukocyte pro-­inflammatory and pro-­metastatic gene expression (ps < .05). In contrast, self-­reported levels of emotional, physical, and functional well-being did not correlate with patterns of leukocyte gene expression (ps > .05). Higher levels of social well-being remained significantly associated with less leukocyte pro-­inflammatory and pro-­metastatic gene expression even after controlling for depressive symptoms. These findings have important implications for understanding biobehavioral mechanisms linking social resources to health-­relevant biological processes in breast cancer patients undergoing primary treatment. In addition, the results have important implications for the design of behavioral interventions in women prior to and following surgery for



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breast cancer. Such interventions, if successful, have the potential to reduce the prevalence of metastases and increase survival times following a diagnosis of breast cancer (Jutagir et al., 2017).

Stress Activates Dormant Cancer Cells In an impressive series of experiments employing cancer patients and mouse models, Perego et al. (2020) tackled the challenging question of why some tumors recur following successful surgical removal of the primary tumor or after a favorable response to chemotherapy and/or radiation therapy. I will limit my discussion to several key components from this wide-­ranging series of experiments. Initial experiments revealed that several stress-­signaling molecules, including norepinephrine and epinephrine, caused a significant release of S100A8/A9 complexes from polymorphonuclear neutrophils (PMNs) by stimulation of b2-adrenergic receptors. S100A8/A9 proteins are low-­molecular-­weight intracellular calcium binding proteins produced by neutrophils and macrophages that are involved in pro-­inflammatory processes. Stressful stimulation of healthy mice also caused a significant increase in circulating levels of S100A8/A9. Next, mice that contained dormant cancer cells were subjected to restraint stress each day for 3 weeks, which resulted in substantial increases in plasma norepinephrine. Unstressed mice served as controls. Following intravenous administration of PMNs, 71% of stressed mice but only 18% of control mice exhibited increased growth of dormant cancer cells in lung and liver (ps < .02). In addition, the survival of stressed mice was greatly reduced compared to control mice. Pretreatment with a b2-receptor antagonist greatly reduced activation of dormant cancer cells and increased the survival rates of stressed mice. A second experimental approach involved using mice with experimental tumors that were surgically removed, followed by treatment with a chemotherapy drug. After 1 week, mice were stressed daily for 3 weeks; at the end of this period, 100% of stressed mice had large tumors in the lungs, but none of the unstressed mice exhibited any signs of lung tumors. Only 17% of knockout mice that lacked the gene for S100A9 showed evidence of tumors following stress, further connecting S100A8/A9 signaling to the recurrence of tumors. To demonstrate the relevance of these findings for stress and tumor recurrence in mice, these investigators examined circulating levels of S100A8/A9 in patients who underwent complete surgical removal of Stage I–II non-small-cell lung cancer. Blood samples were collected 3 months after surgery, and patients were tracked for any recurrence of tumors; 33 months postsurgery was considered an early recurrence (N = 17 of 80 patients). Eleven of 35 patients (31%) with serum concentrations of S100A8/A9 greater than 2500 ng/ml had early recurrence of cancer, while only 6 of 45 patients (13%) with serum concentrations of S100A8/A9 less than 2500 ng/ml had early recurrence of cancer (p < .05). Overall, patients with high serum concentrations of S100A8/ A9 had significantly shorter recurrence-­free survival than patients with lower levels (p < .03). Finally, in a subset of samples, there was a significant positive correlation between serum concentrations of norepinephrine and S100A8/A9 (p < .04). The results reported by Perego et al. (2020) are well worth a careful review. Their experiments in mouse models and in postoperative cancer patients point to a link between stress hormones (norepinephrine and epinephrine) → stimulation of b-adrenergic

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receptors on neutrophils → synthesis and release of pro-­inflammatory S100A8/A9 proteins → reactivation of dormant cancer cells. These findings further strengthen connections between stress and cancer recurrence, and they suggest new stress-­associated targets for the prevention of metastasis following surgery or chemotherapy.

Summary The three studies highlighted in this section and many other reports confirm that physiological responses to psychosocial stressors can promote the spread of some cancers or activate dormant cancer cells that have spread from the primary tumor. These findings have also led to possible new therapeutic approaches to slowing metastatic processes by repurposing drugs that block b-adrenergic receptors (e.g., propranolol) that have previously been shown to be safe and effective in treating other conditions. There are many excellent reviews on the connections between stress and metastasis, and the overall findings are quite compelling (see, e.g., Liu, Sood, Jenewein, & Fagundes, 2020; Moreno-­ Smith, Lutgendorf, & Sood, 2010; Mravec et al., 2020; Shi, Liu, Yang, & Guo, 2013; Zhang et al., 2020).

DEPRESSION AFFECTS CANCER MORBIDITY AND MORTALITY It is not uncommon for patients to develop symptoms of depression after receiving a diagnosis of cancer. Although these patients may not meet the criteria required for a diagnosis of major depressive disorder, these depressive symptoms may impact the progression of cancer and increase mortality. Several factors have been advanced to explain the negative impact of depressive symptoms on cancer patients: 1.  The onset of depressive symptoms may be associated with disruptions in stress-­ responsive neuroendocrine and immune system function that could facilitate the development and spread of particular cancers. 2.  Depressed patients may be less likely to adhere to treatment protocols or recommendations by physicians to maintain health-­promoting behaviors such as regular exercise and a healthy diet. 3. Depressive symptoms overlap with some of the side effects of cancer and its treatment, and may result in greater severity of symptoms. 4.  Depressive behaviors reduce the likelihood that cancer patients will maintain or expand their social support networks that are critical for positive outcomes. 5.  Depressive behaviors make it less likely that cancer patients will form effective bonds with members of their health care team that are critical for positive treatment outcomes (Spiegel & Giese-Davis, 2003). Included below are selected studies using a variety of methodologies that address the relationship between depressive symptoms and cancer. As you will see, these findings



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lead quite naturally to intervention studies that seek to lessen the negative effects of depression on cancer outcomes.

Depression and Cancer‑Related Mortality Pinquart and Duberstein (2010) conducted a meta-­analysis of 76 prospective studies with a combined sample size of 176,863 participants to determine the relationship between depression and cancer mortality. Average age of participants was 65 years, 72% were female, and 49% were married. The 76 studies that met inclusion criteria were heterogeneous in terms of types of cancers that were studied, stage and severity of the disease, and methods for assessing depressive symptoms. Results of the meta-­analysis revealed a significant association between depressive symptoms and elevated risk of mortality from cancer (RR = 1.17, 95% CI = 1.12–1.22). A similar result was reported for those studies that adjusted for other relevant demographic and health-­related variables (RR = 1.22, 95% CI = 1.14–1.30). These results are consistent with earlier meta-­analyses (Chida, Hamer, Wardle, & Steptoe, 2008; Satin, Linden, & Philipps, 2009) but included a much larger combined sample size. Onset of depression includes a strong undercurrent of stress-­related changes in neural, endocrine, and immune responses that may alter the tumor microenvironment in such a way as to promote metastasis. Studies that have addressed these possibilities will be discussed in the following section.

Depression in Patients with Metastatic Breast Cancer Some cancer treatments are known to have significant immunosuppressive effects. In addition, psychological distress and depression, which often accompany a diagnosis of and treatment for cancer, may also suppress endocrine systems and immune function. Cell-­mediated immunity is critical for defense against a range of pathogens to which cancer patients may be particularly susceptible as well as to some tumors. A study by Sephton et al. (2009) explored relationships among depressive symptoms, cortisol secretion, and cell-­mediated immune responses in 72 women with Stage IV metastatic breast cancer. Depressive symptoms were assessed with the Center for Epidemiologic Studies Depression Scale. Saliva was sampled throughout the day over a 3-day period to obtain a physiologic index of diurnal cortisol concentrations and circadian rhythmicity, which are related to breast cancer survival. Cell-­mediated immune responses to specific antigens were measured following intradermal administration of seven commonly encountered antigens to the surface of the forearm (tuberculin, tetanus, diphtheria, Streptococcus, Candida, Trichophyton, and Proteus). Forty-eight hours later, induration responses (swollen inflamed areas on the skin) were measured across 2 diameters at right angles, and the average measure (mm) was recorded. Induration responses to a control solution were subtracted from the antigenic responses. Induration responses > 2 mm were considered to be positive responses. After adjusting for relevant medical and treatment variables, the findings revealed that women who reported more depressive symptoms displayed suppressed immune responses to an antigenic challenge, as measured by lower average induration size. Women with higher mean diurnal cortisol concentrations also showed suppressed immune responses, as indicated by a decreased number of antigens to which positive

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reactions were obtained. This study highlights the interrelationships among depression, HPA responses to stress, and immune function in patients with metastatic breast cancer.

Depression and Pro‑Inflammatory Cytokines in Breast Cancer Patients Depressive symptoms and pro-­inflammatory responses may promote the progression of breast cancer and result in less favorable clinical outcomes. Prior research has shown that depression is associated with increased circulating levels of pro-­ inflammatory markers in healthy individuals as well as in patients with cancer. A study by Bouchard et al. (2016) examined relationships between depressive symptoms and inflammation in women with early-stage breast cancer before beginning adjuvant treatment. Women (N = 89, mean age = 50) with Stage 0–III breast cancer were recruited approximately 4 to 8 weeks after surgery (lumpectomy or mastectomy). Depressive symptoms were assessed using the Hamilton Rating Scale for Depression, and blood samples were collected to quantify circulating levels of IL-1b, IL-6, and TNF-a. Thirty-­six (40%) of 89 patients showed elevated levels of depressive symptoms and, in adjusted models, had marginally higher levels of IL-1b and IL-6 and significantly higher levels of TNF-a compared to women with low depressive symptoms. Across the range of depressive symptoms, higher levels of depressive symptoms were related to greater levels of IL-1b (p = .006) and TNF-a (p = .003). These findings have implications for psychosocial and biological interventions concurrently targeting depression and inflammation to improve breast cancer outcomes, especially through reduced tumor growth and metastasis (Bouchard et al., 2016).

Changes in Stress, Depressive Symptoms, and Immune Function over a 5‑Year Period Andersen, Goyal, Westbrook, Bishop, and Carson (2016) addressed an important gap in the literature by examining trajectories of stress, depressive symptoms, and immune function over a 5-year period in breast cancer survivors. Women (N = 113, average age 51 years) were recruited following diagnosis and surgical treatment for breast cancer and while awaiting adjuvant therapy. They completed self-­report measures of stress and depressive symptoms and provided blood samples for assays of natural killer cell cytotoxicity and T-cell formation. Assessments were repeated every 4 to 6 months for 5 years, for a total of 12 assessments over the course of the study. Stressors associated with cancer displayed two distinct phases of decline, with the change point being 12 months. After the 12-month point, trajectories of change became more variable, with some patients continuing a slow decline and others maintaining levels of stress. In contrast, a steep decline in depressive symptoms occurred by 7 months, with stable, low levels out to 5 years in many patients. Some patients experienced a rebound in levels of depressive symptoms that should be addressed with targeted treatments. Natural killer cell cytotoxicity exhibited a steady upward trajectory through 18 months, and these high levels were maintained. However, there was no consistent pattern of change over the 5-year period for T-cell formation. These findings are consistent with the need for provision of psychological support services for those women who are newly diagnosed with breast cancer, as well as for survivors out to 5 years postsurgery.



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Careful attention to levels of cancer-­related stressors and depressive symptoms could substantially improve outcomes for breast cancer survivors (Andersen et al., 2016).

Stress Moderates Inflammation‑Mediated Depressive Symptoms in Cancer Patients Stress precipitates depressive episodes, and there is compelling evidence that the stress–­ depression connection is mediated by increased susceptibility to inflammation-­induced depressive symptoms in susceptible individuals (Kiecolt-­Glaser, Derry, & Fagundes, 2015; Miller & Raison, 2016). A study by Manigault et al. (2021) examined the moderating role of psychosocial stress levels on the association over time between inflammation and depressive symptoms in women with breast cancer. Participants recently diagnosed with early-stage breast cancer (N = 187, mean age = 56 years) were enrolled typically following surgery (lumpectomy or mastectomy) and before starting adjuvant/neoadjuvant treatment. Blood draws and self-­reported depressive symptoms were obtained pretreatment, posttreatment, and at 6, 12, and 18 months following treatment. Circulating levels of CRP were used as a measure of inflammation. Measures of psychological stress, including cancer-­related stress, general stress perceptions, and childhood stress levels, were obtained pretreatment. The results revealed that stress moderated the association between CRP levels and depressive symptoms, such that higher levels of CRP were associated with elevated depressive symptoms, but only among women who reported high levels of cancer-­ related stress (p = .002) and perceived stress (p = .044). In contrast, childhood stress effects were not significant. In addition, elevated levels of CRP were associated with clinically significant depressive symptoms (OR = 1.64, p < .001) among women who reported high cancer-­related stress levels. These findings were independent of age, BMI, race, and other cancer-­related covariates. Stress was found to heighten sensitivity to inflammation-­associated depressive symptoms over a 2-year period, with much stronger effects for perceived stress responses to a concurrent life event. Individuals who are most distressed following a major life event may exhibit the greatest risk for inflammation-­ induced depression. These individuals may require careful monitoring and targeted interventions to address depressive symptoms and improve overall treatment outcomes.

Summary The results of these five reports on the interrelationship between psychosocial stressors, depressive symptoms, and levels of inflammation in patients recovering from a cancer diagnosis and treatment have important implications for the management of cancer patients. In a meta-­analysis, depressive symptoms were shown to increase the risk of mortality from cancer. In women recovering from breast cancer, higher levels of depressive symptoms were associated with reduced immune responses to an antigenic challenge. Depressive symptoms were also positively correlated with levels of inflammation in women treated for breast cancer. Finally, higher levels of inflammation were associated with elevations in depressive symptoms in women who experienced high levels of cancer-­related stress and perceived stress. Taken together, these results provide strong support for personalized care in cancer patients, with specific interventions to address stress-­related disturbances in the HPA axis, elevated levels of inflammation, and increases in depressive symptoms.

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STRESS‑TARGETED INTERVENTIONS FOLLOWING A CANCER DIAGNOSIS Targeted interventions to improve stress management skills in patients with a variety of diseases have been shown to improve overall treatment outcomes. In the sections that follow, I provide strong evidence for the beneficial effects of psychological interventions designed to improve stress management and reduced depressive symptoms in cancer patients (Barrera & Spiegel, 2014; Rodin, 2018).

A Psychological Intervention to Enhance Survival in Metastatic Breast Cancer Spiegel, Bloom, Kraemer, and Gottheil (1989) reported on an early effort to develop a psychological intervention designed to enhance survival of women diagnosed with metastatic breast cancer. The year-long intervention consisted of weekly group therapy sessions with self-­hypnosis for pain. The program emphasized enjoying life, improving communication with family members and health care providers, confronting fears about death and dying, and controlling pain and other symptoms associated with cancer. The intervention did not discuss or target enhanced survival following the cancer diagnosis. Both the treatment (N = 50) and control groups (N = 36) received routine oncological care. At the 10-year follow-­up, only 3 of the 86 original patients were alive, and death records were reviewed for the other 83. Survival from the time the intervention was launched was an average of 36.6 months in the intervention group compared with 18.9 months in the control group (p < .001). Survival plots pointed to a divergence in survival between treatment and control groups beginning at 20 months after entry into the study, or 8 months after the intervention ended. The authors suggested that neuroendocrine and immune system changes may represent a critical link between this extended psychological intervention and cancer progression.

Enhancement of Breast Cancer Survival after an Intervention to Reduce Stress The question of whether psychosocial stressors present a risk for cancer progression has been challenging to address. Andersen et al. (2008) conducted a randomized clinical trial to determine if a psychological intervention to reduce stress levels in recently diagnosed cancer patients would improve survival. A total of 227 patients who were surgically treated for regional breast cancer participated. Before beginning adjuvant cancer therapies, patients were assessed with psychological and behavioral measures, had a health evaluation, and had their blood sample drawn. Patients were randomized to psychological intervention plus assessment or assessment-­only study arms. The intervention was conducted by a psychologist in small groups, and it included strategies to reduce stress, improve mood, alter health behaviors, and maintain adherence to cancer treatment and care. Earlier studies demonstrated that, compared with the Assessment arm, the Intervention arm resulted in improvements across all of the secondary outcomes. Immunity was also enhanced. After a median of 11 years of follow-­up, disease recurrence was reported in 62 of 212 (29%) women, and death was reported for 54 of 227 (24%) women. Using the Cox



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proportional hazards analysis, a multivariate comparison of survival was conducted. As predicted, patients in the Intervention arm were found to have a reduced risk of breast cancer recurrence (HR = 0.55; p < .034) and death from breast cancer (HR = 0.44; p < .016) compared with patients in the Assessment only arm. Follow-­up analyses also demonstrated that Intervention patients had a reduced risk of death from all causes (HR = 0.51; p < .028). Psychological interventions as delivered in this study may improve survival in breast cancer patients.

Cognitive‑Behavioral Stress Management and Breast Cancer Outcomes Nonmetastatic breast cancer patients often experience psychological distress, which may influence disease progression and survival. Cognitive-­behavioral stress management (CBSM) improves psychological adaptation and lowers distress during breast cancer treatment and long-term follow-­up. Stagl et al. (2015) examined whether breast cancer patients randomized to CBSM had improved survival and reduced recurrence of cancer 8–15 years following enrollment in the study. From 1998 to 2005, women (N = 240, average age = 50 years) 2–10 weeks postsurgery for nonmetastatic Stage 0–IIIb breast cancer were randomly assigned to a 10-week, group-based CBSM intervention (n = 120) or a 1-day psychoeducational seminar that served as the control condition (n = 120). In 2013, 8–15 years poststudy enrollment (11-year median), recurrence and survival data were obtained. CBSM was delivered in 90-minute sessions once per week for 10 weeks and was designed to enhance coping and adaptive mechanisms and reduce stress levels and negative mood states. Women in the control condition received general information about breast cancer care and health-­related issues. After controlling for demographic and medical risk factors, group differences in all-cause mortality, breast cancer-­specific mortality, and the disease-­free interval were determined. Compared to women in the control group, women in the CBSM group displayed a reduced risk of all-cause mortality (HR = 0.21; 95% CI = 0.05–0.93, p = .040). Limiting analyses to women with invasive disease revealed significant effects of CBSM on breast cancer-­related mortality (HR = 0.08, 95% CI = 0.01–0.49, p = .006) and disease-­free interval (HR = 0.24, 95% CI = 0.07–0.82, p = .011). CBSM interventions delivered following breast cancer surgery may provide long-term health benefits for nonmetastatic breast cancer patients, in addition to previously established psychological benefits. These findings represent an important contribution to the limited body of research relating to improved outcomes following psychosocial interventions following surgery for nonmetastatic breast cancer. There is a pressing need to replicate these basic findings in varied settings and with a diverse patient population and to examine CBSM-­ influenced changes in physiological systems, health behaviors, and levels of treatment adherence.

Targeting CBSM in Breast Cancer Patients CBSM improves adaptation to primary treatment for breast cancer, as shown by reductions in distress and increases in positive affect. It is likely that all breast cancer patients may not have need for psychosocial interventions, so that identifying those most likely to

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benefit would represent an important step toward personalized biobehavioral treatment plans for cancer. In a secondary analysis of a previous randomized trial as described above (Stagl et al., 2015), Wang et al. (2018) determined whether baseline levels of cancer-­related distress moderated CBSM effects on adaptation over 12 months. They hypothesized that patients experiencing the greatest cancer-­specific distress in the weeks after surgery would show the greatest CBSM-­related moderating effects on distress and affect. The results revealed that CBSM interacted with initial cancer-­related levels of distress to influence levels of distress and affect. Follow-­up analyses showed that those with higher levels of initial distress benefited significantly from CBSM compared to controls. No differential improvement in affect or intrusive thoughts occurred in women with low initial levels of cancer-­specific distress. Identifying patients most in need of a CBSM intervention in the period after surgery may optimize cost-­effective psycho-­oncology care and contribute to personalized delivery of behavioral support services.

An Internet‑Based Intervention for Ovarian Cancer Research on psychosocial group-based interventions for patients with ovarian cancer has been limited. Drawing from elements of CBSM, mindfulness-­based stress reduction (MBSR), and acceptance and commitment therapy (ACT), Kinner et al. (2018) developed an Internet-­based group intervention designed specifically to meet the needs of ovarian cancer survivors. The Internet-­based platform facilitated home delivery of the psychosocial intervention to a group of cancer survivors for whom attending face-toface programs would be difficult given their physical limitations and the small number of ovarian cancer survivors at any one treatment site. The aim of their study was to develop, optimize, and assess an Internet-­based group stress management intervention for ovarian cancer survivors delivered via a tablet or laptop. In total, 9 ovarian cancer survivors provided feedback during usability testing. Subsequently, 19 survivors participated in five waves of field testing of the 10-week group intervention led by two psychologists. The group met weekly for 2 hours via an Internet-­based videoconference platform. Structured interviews and weekly evaluations were used to elicit feedback on the website and intervention content. Before and after the intervention, measures of mood, quality of life, perceived stress, sleep, and social support were obtained. In the field trial (N = 19), across five groups, the 10-week intervention was well attended. Perceived stress levels (p = .03) and ovarian cancer-­specific quality of life (p = .01) both improved significantly during the course of the intervention. Trends toward decreased distress and greater well-being were also noted. Qualitative interviews revealed that the most common obstacles participants experienced were technical issues and the time commitment for practicing the techniques taught in the program. Participants reported that the intervention helped them to overcome a sense of isolation and that they appreciated the ability to participate in the intervention from their homes. An Internet-­based group intervention tailored specifically for ovarian cancer survivors is a major step forward in delivering psychological services to these patients. Preliminary psychosocial outcomes indicate decreases in perceived stress and improvements in ovarian cancer-­specific quality of life following the intervention. A randomized clinical trial is needed to demonstrate the efficacy of this promising intervention for ovarian cancer survivors.



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Summary The five studies described above and related reports have acknowledged the highly stressful nature of receiving a diagnosis of and undergoing treatment for cancer. Life stressors and cancer-­specific stressors have been shown to negatively affect health outcomes and mortality rates. In contrast, psychosocial interventions that mitigate these adverse effects improve health outcomes and reduce mortality rates. Reducing neuroendocrine and immune responses to stress appear to play a key role in decreasing growth-­ promoting stimuli of the tumor microenvironment and reducing metastatic processes. Psychosocial interventions have an important role to play in comprehensive treatment plans for cancer patients, and the research on their high level of effectiveness is impressive (Antoni, 2013; Antoni & Dhabhar, 2019; Barrera & Spiegel, 2014; Gosain, Gage-­ Bouchard, Ambrosone, Repasky, & Gandhi, 2020; Mohan, Huybrechts, & Michels, 2022). Many of the intervention studies to date have involved cohorts of breast cancer patients. In the future, research studies should expand to include other types of cancers (e.g., lung, prostate, kidney, GI) and interventions that are designed specifically to address a particular type of cancer and the unique challenges presented to these patients during diagnosis, treatment, and recovery. Internet-­based delivery platforms could also make psychosocial interventions more widely available to patients, and early indications provide a hopeful sign of their effectiveness and ease of delivery to remote areas.

CONCLUSIONS This chapter was organized around five issues regarding connections between stressful stimulation and cancer. Evidence was presented that under some conditions, high levels of perceived stress or low levels of social support serve as risk factors for the development of some types of cancer. However, some studies, including those with large sample sizes, have failed to detect such a relationship. High perceived stress levels associated with receiving a cancer diagnosis or undergoing surgical removal of a tumor contribute to less favorable outcomes in cancer patients, including higher mortality rates. Cancer metastasis also benefits from high levels of perceived stress. Patients with depressive symptoms exhibit poorer long-term outcomes following a diagnosis of cancer. Connections between high levels of perceived stress and a cancer diagnosis have naturally led to the design of behavioral and pharmacological interventions to reduce stress levels and improve health outcomes. In addition, provision of psychosocial support services has now become a routine component of treatment plans for cancer patients, including interventions to promote resilience (Pirl et al., 2020; Seiler & Jenewein, 2019). Two stress-­responsive systems appear to be closely linked to cancer-­promoting processes. b-adrenergic receptors within the tumor microenvironment are stimulated by norepinephrine released from sympathetic nerve terminals and epinephrine released from the adrenal medulla, both of which promote tumor development and metastasis. In addition, stress-­induced disruptions in the immune system and elevations in levels of inflammation also promote the development of cancer cells. Finally, symptoms of depression often go hand in hand with the progression of some cancers, and this relationship often results in a poorer prognosis for affected patients.

C H A P T E R 11

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F

or most of our existence as a species, humans have lived in small, widely dispersed nomadic groups of 50–100 individuals. For the most part, these early hominids suffered from infectious diseases that were similar to those of overlapping primate populations. With the advent of agriculture and a relatively stable source of food production about 10,000 years ago, conditions were optimized to support the emergence of modern infectious diseases that can only be sustained by densely populated human groups living in large towns and cities (Wolfe, Dunavan, & Diamond, 2007). In the 21st century, we have already experienced the emergence of four viral outbreaks that have attracted international attention from public health officials (Table 11.1). The most recent of these viruses, COVID-19, quickly attained pandemic status by the World Health Organization and resulted in more than 4.5 million deaths worldwide 2 years after the virus was first detected in Wuhan, China. In spite of the rapid development of several highly effective vaccines, public health officials must deal with vaccine hesitancy among some groups and the relative lack of vaccine availability in the poorest countries. In the United States, COVID-19 has exposed schisms in our society that relate to racial and economic disparities of long standing. These issues will be discussed in greater detail in Chapter 12. In this chapter, we will explore some of the ways in which psychosocial stressors affect susceptibility to infectious diseases and impact the effectiveness of vaccines in triggering an immune response. Many of these studies were inspired by the emergence of a new scientific discipline, psychoneuroimmunology, that explores connections between behavior, the brain, the neuroendocrine system, and the immune system. A central facet of this interdisciplinary field of inquiry is the powerful influence exerted by stressful stimulation on the brain–neuroendocrine–immune axis (Kiecolt- Glaser, McGuire, & Robles, 2002). 216



Stress and Infectious Diseases 217 TABLE 11.1.  Four Emerging Viruses of the 21st Century and Their Spread Year

Virus

Countries affected

Outcome

2003

Severe acute respiratory syndrome-associated coronavirus (SARS-CoV)

China, other Asian countries, Europe, Canada, United States. Transmission via aerosols from person-to-person. High mortality.

Successfully contained, no new cases since 2003

2009

H1N1 “swine flu” strain of influenza A virus

Spread to countries around the world as a seasonal flu.

Pandemic status by WHO

2013

Middle East respiratory syndrome-associated corona virus (MERS-CoV)

Emerged in Saudi Arabia and spread to 27 other countries, including the United States, still occur. Transmission requires close contact.

Successfully contained, but some cases still occur

2019

Severe acute respiratory syndrome-associated coronavirus2 (SARS-CoV-2)

Emerged in China and rapidly spread throughout the world. Transmission via aerosols from person to person.

Pandemic status by WHO

Note. Based on information provided by the World Health Organization.

HERPES ZOSTER Herpes zoster, more commonly known as shingles, results from reactivation of varicella-­ zoster virus that lies dormant in the spinal dorsal root and cranial sensory ganglia following a primary infection of chickenpox that typically occurs in childhood. Approximately 98% of adults in the United States are infected with the varicella zoster virus that causes chicken pox. Shingles is a painful rash that develops on one side of the face or body. The rash consists of blisters that usually scab over within 7–10 days and resolve within 2–4 weeks. Direct contact with the fluid from the blisters can spread the varicella-­zoster virus to others who have never had chicken pox or been vaccinated. If this occurs, those infected individuals will develop chicken pox and not shingles (Johnson, 2010). Approximately 1 million cases of shingles are diagnosed in the United States each year (3–4 cases per 1,000 adults). The incidence of shingles is greater in women than men and increases with age, such that 50% of unvaccinated 85-year-old adults can be expected to develop the disease. A dreaded complication of shingles is postherpetic neuralgia, or pain, that may continue for months or years after the rash clears up. At times, the pain can be debilitating and interfere with normal daily activities and lead to depression and loss of employment. This severe complication, which is more common in older individuals, has been reported in 10–50% of adults with shingles and often requires hospitalization (Cohen, 2013; Johnson, 2010; Johnson & Rice, 2014). A major advance in prevention of herpes zoster in the United States occurred in 2008 with the recommendation by the Centers for Disease Control and Prevention of a single-­use vaccine for adults age 60 and older (Harpaz, Ortega-­Sanchez, & Seward, 2008).

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Stress Levels and Shingles in Japan The Shozu Herpes Zoster (SHEZ) study began in Shozu, Japan, in December 2008 with the recruitment of participants who were residents of the area and were at least 50 years of age. This population-­based prospective study was motivated by an earlier laboratory study in mice demonstrating that stress-­induced increases in circulating glucocorticoids in the early stages of an infection with herpes simplex virus-1 suppressed the subsequent antiviral immune response even after the stressor was terminated (Elftman et al., 2010). Armed with these basic research findings, Takao et al. (2018) examined the impact of psychosocial stressors on the incidence of herpes zoster and postherpetic neuralgia in the SHEZ study. Participants (N = 12,359, 55% female) completed a detailed health questionnaire that included questions on prior diseases, lifestyle, exercise habits, perceived mental stress, major life events, and having a sense of purpose in life. During a 3-year follow­up between December 2008 and November 2012, incident cases of herpes zoster and postherpetic neuralgia were diagnosed in 400 and 79 participants, respectively. Hazard ratios of incident HZ and PHN expressed the impact of psychosocial factors on herpes zoster after adjusting for age, sex, prior history of herpes zoster, other co-­morbid conditions, and lifestyle issues. The results of this study revealed that males with high levels of mental stress were twice as likely to be at risk for incident herpes zoster infection (HR = 2.22, 95% CI = 1.05–4.66). In contrast, the risk of incident herpes zoster was approximately 60% lower in men and women who reported a high sense of purpose in life (HR = 0.54, 95% CI = 0.30–0.96). Men and women who experienced negative life events during the previous year had a twofold higher risk of incident postherpetic neuralgia (HR = 2.15, 95% CI = 1.33–3.47). The results of this population-­based prospective study of older Japanese men and women indicate that psychosocial stressors have an impact on the occurrence of herpes zoster and postherpetic neuralgia. Previous findings from the SHEZ study noted that participants with lower cell-­mediated immune responses to varicella antigen were 3.6 times more likely to develop herpes zoster than participants with higher levels of immunity (Asada et al., 2013). It is tempting to speculate that prolonged exposure to psychosocial stressors results in activation of the HPA axis, with alterations in cortisol signaling leading to decreases in cell-­mediated immunity. These reductions in cell-­mediated immunity, especially in older individuals, would increase the likelihood of an episode of shingles.

Stress and Depressive Symptoms and Shingles in France Lasserre et al. (2012) coordinated with family physicians throughout France to assemble a sample of patients aged 50 years and older who were diagnosed with herpes zoster (N = 250 cases) and a group of controls without the disease who were matched by age and sex (N = 500). In an extensive telephone interview within 2 days of diagnosis, each participant provided the following information: demographic and lifestyle data, family history of herpes zoster, score on the Hamilton Anxiety Depression Scale, and significant life events over the previous 6 months.



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The results revealed that a family history of herpes zoster in at least one relative was significantly associated with cases of herpes zoster (OR = 2.29, 95% CI = 1.63–3.22, p < .001). In addition, a depression score ≥ 8 was significantly associated with herpes zoster cases relative to controls (OR = 2.21, 95% CI = 1.51–3.23, p < .001). Finally, the occurrence of significant negative life events was greater in patients with herpes zoster compared to controls, and this difference was significantly associated with the disease (OR = 2.55, 95% CI = 1.36–4.48, p < .001). These findings provide additional information on the connections between psychosocial stressors, depressive symptoms, and the onset of herpes zoster. The authors suggested that reduced immune responses might have contributed to these differences between patients and matched controls, although this could not be confirmed (Lasserre et al., 2012).

UPPER RESPIRATORY INFECTIONS Symptoms of the common cold are all too familiar to most Americans. Upper respiratory infections are typically accompanied by nasal congestion, sneezing, a sore throat, and a cough. The illness is typically transient and is often caused by rhinoviruses, coronaviruses, and influenza viruses. The common cold follows a distinct seasonal pattern in the northern hemisphere, with the onset of cough and cold season beginning in the fall and continuing into the winter months, with a dropoff beginning the following spring. Transmission of cold viruses can occur by several means, including hand contact with secretions from an infected individual or from surfaces that contain these secretions, small particle aerosols from an infected individual, or direct contact with large particle aerosols when an infected individual sneezes. The incubation period varies by type of virus, ranging from a half-day up to 7 days. The severity of cold symptoms peaks within 2–3 days after infection, but symptoms may persist for as long as a week. Each year in the United States, millions of people develop cold symptoms, with adults having two to three colds each year and children less than 10 years of age having three to six colds per year. The common cold results in millions of lost days from work and absences from school each year, and there is no end in sight (Heikkinen & Järvinen, 2003). Only a portion of individuals who are exposed to upper respiratory viruses actually go on to develop symptoms of disease. One explanation that has been advanced to explain this variability in response to infectious upper respiratory viruses is the negative impact of psychosocial stressors on immune parameters. These effects appear to be mediated directly by neural and hormonal effects on immune cells and indirectly by stress-­induced increases in health risk behaviors such as smoking, poor diet, lack of exercise, and drug and alcohol use.

Meta‑Analysis of Psychological Stress and Upper Respiratory Infections To address these possibilities, Pedersen, Zachariae, and Bovbjerg (2010) conducted a systematic review and meta-­analysis of 27 prospective studies that examined the association between psychological stress and subsequent upper respiratory infection in a combined sample of 8,110 participants. The results revealed a significant overall main effect of psychological stress on the risk of developing an upper respiratory infection.

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Additional analyses revealed that the development of infections was not affected by the type of stressor, how infection was measured, if the studies utilized natural exposure to the pathogen or experimental exposure to the pathogen, or if the study controlled for immunity resulting from preexposure to the infectious agent. These investigators suggested that Interleukin-6 (IL-6) may mediate the effects of psychosocial stressors on susceptibility to upper respiratory infections, but this possibility must await further studies (Pedersen et al., 2010).

Stress‑Induced Changes in Glucocorticoid Receptors Promote the Common Cold For many years, Sheldon Cohen of Carnegie Mellon University and his collaborators have explored the impact of psychosocial stressors on the development of the common cold (Cohen et al., 1991). One experimental design they have developed involves recruiting healthy volunteers, who are then quarantined and later infected with a common cold virus (a rhinovirus). In a landmark study, Cohen et al. (2012) demonstrated that psychosocial stressors that produced long-term threat resulted in decreased glucocorticoid receptor (GR) sensitivity, which has been linked to a failure to downregulate pro-­ inflammatory cytokine responses to cold viruses. The inability of cortisol to effectively downregulate pro-­inflammatory cytokine production resulted in enhanced signs and symptoms of a cold virus infection. Participants in these two experiments (N = 276, mean age 29 years, 55% female) were recruited through local advertisements and were compensated for their time. In the first experiment, participants completed a medical examination to confirm they were in good health. They returned to the laboratory several weeks later and completed a life stress questionnaire; they also provided blood samples for measurement of cortisol, viral antibodies, and blood cell analyses. They were then quarantined in individual rooms and were examined carefully for evidence of an upper respiratory infection. If cleared for participation, individuals received nasal drops of a low infectious dose of one of two rhinoviruses and remained quarantined for 5 days. During that time, they completed nasal washes for isolation of virus, and signs and symptoms of the common cold were noted. The second experiment involved a subset of the original participants (N = 79) who followed the same protocol, but with measures of the pro-­inflammatory cytokines IL-1b, IL-6, and TNF-a in nasal secretions following administration of nasal drops containing a rhinovirus. The results of these experiments were quite striking. In experiment 1, 167 participants did not develop signs and symptoms of a cold following the viral challenge, while 109 participants did develop symptoms of a cold. Those participants who experienced significant life stressors in the previous month exhibited reduced glucocorticoid receptor sensitivity, as reflected in their neutrophil to lymphocyte ratios. These same individuals were at increased risk of developing a cold following the viral challenge. As predicted, plasma levels of cortisol did not predict which participants would develop signs and symptoms of a cold (OR = 1.27, 95% CI = 0.20–7.94). In the second experiment, those participants with decreased glucocorticoid receptor sensitivity produced greater quantities of pro-­inflammatory cytokines in their nasal passages following a viral challenge. Taken together, the findings from these two experiments indicate that recent exposure to significant life stressors leads to reduced glucocorticoid receptor sensitivity, which



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disrupts local regulation of pro-­inflammatory cytokines by cortisol. Increased production of pro-­inflammatory cytokines in the nasal passages leads to the typical signs and symptoms of an upper respiratory infection. These investigators suggested that stress-­ induced decreases in glucocorticoid receptor sensitivity may also play an important role in the onset and progression of other diseases as well (Cohen et al., 2012).

HUMAN IMMUNODEFICIENCY VIRUS The first official mention in the United States of what was to become known as human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) appeared in the June 5, 1981, issue of Morbidity and Mortality Weekly Report, which included a brief summary of clinical findings from five young gay men who had developed an unusual series of infections and had abnormal ratios of lymphocyte subgroups (Centers for Disease Control and Prevention, 1981). A great deal of early speculation suggested that this unknown pathogen, probably a virus, was limited to gay men, intravenous drug users, Haitians, and recipients of blood transfusions. The list soon expanded to include Africans. Needless to say, many of our national leaders did not display appropriate levels of compassion or concern about this new disease or those who became infected because of homophobia and xenophobia (Sepkowitz, 2001). The term acquired immune deficiency syndrome was first used by the CDC in September, 1981 and represented one small step away from the rampant discrimination and stigma directed against groups that were at high risk for HIV (Centers for Disease Control and Prevention, 1981b). The following month, however, additional cases in five women were reported, and in one of the women it was confirmed that her only exposure to HIV was through heterosexual sex (Sepkowitz, 2001). Major research breakthroughs were reported in 1983 with the isolation of the virus and confirmation that it caused HIV/AIDS (Barré-Sinoussi et al., 1983; Gallo et al., 1983). Studies have documented three primary means of transmission of HIV: (1) unprotected sexual contact with an infected person, (2) bloodborne transmission through blood or blood products, and (3) transmission from mother to child during pregnancy, delivery, and lactation. We now take for granted the careful testing of blood donors for HIV, safety precautions among health care personnel to prevent needle stick injuries and potential transmission of HIV from blood and body fluids, public information campaigns that promote safe sexual practices, and efforts to provide intravenous drug users with clean needles. These and many other efforts to prevent transmission of HIV have met with great success; however, in the United States in 2019 there were 36,801 newly diagnosed cases of HIV and 15,815 deaths reported among individuals diagnosed with HIV. Most cases of HIV now result from heterosexual transmission (Centers for Disease Control and Prevention, 2021). At present, HIV/AIDS remains a serious infectious disease, but substantial progress has been made in understanding the course of the disease and in developing effective treatments. A critical biomarker of the progression of HIV-AIDS is the concentration of CD4+ T helper cells in blood. CD4 is a glycoprotein found on the cell membrane of immune cells, including T helper cells, monocytes, and dendritic cells. CD4+ T helper cells play a critical role in assisting B cells to produce antibodies and CD8 T cells to kill virally infected cells (Soghoian et al., 2012).

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Following contraction of the virus, an individual may develop flu-like symptoms 2–4 weeks later. Symptoms include a low-grade fever, swollen lymph nodes, headache, fatigue, a sore throat, and a rash. Infected individuals may develop opportunistic infections at this stage as well. Given the nonspecific nature of these symptoms, many individuals are misdiagnosed soon after infection. The second stage of HIV infection involves very low levels of viral replication, and individuals are mostly asymptomatic during this period, which may last up to a decade in those who do not receive medication. The move into the third stage involves an increase in viral load and a decrease in CD4+ T helper cell count below 200 cells per µl. At this stage, individuals have AIDS and are at increased risk of opportunistic infections, and they are highly infectious (Table 11.2). Untreated individuals with AIDS can survive for up to 3 years (De Cock, Jaffe, & Curran, 2012). The standard of care for patients with HIV now involves a highly active anti­ retroviral therapy (HAART), a cocktail of drugs that prevents viral replication, maintains immune function, and prevents opportunistic infections. HAART is so effective that physicians now work with their HIV patients to manage a chronic disease with significant longevity rather than prepare for progression to AIDS and death (Deeks, Lewin, & Havlir, 2013). Hope remains that a highly effective vaccine to prevent HIV infections will be developed in the not-too-­distant future (Pavlakis & Felber, 2018). In the next section, I have summarized several studies that highlight connections between psychosocial stress and the progression of HIV in patients. In addition, targeted behavioral interventions to reduce the impact of psychosocial stressors and improve their management in HIV patients are included. As HAART has been made available to HIV-­infected individuals, it has become clear that there is a powerful interaction between HIV, psychosocial stressors, and inflammation. Individuals living with HIV have higher lifetime rates of depression and PTSD, both of which can be brought on by exposure to high levels of stress. In addition, circulating levels of pro-­inflammatory molecules (IL-6, TNF-a, and CRP) are elevated in response to stressful events and complicate the medical management of patients with HIV infections (Valdez, Rubin, & Neigh, 2016).

TABLE 11.2.  Classification of the Stages of HIV Infections as Developed by the Centers for Disease Control and Prevention Acute retroviral syndrome: This illness has symptoms like those of mononucleosis. It often develops within a few days of infection with HIV, but it also may occur several weeks after the person is infected. The symptoms can range from mild to severe and usually disappear on their own after 2 to 3 weeks. But many people do not have symptoms, or they have such mild symptoms that they don’t notice them. Stage 1 (HIV infection): There are no AIDS-related conditions, and the CD4+ cell count is at least 500 cells per microliter, or the percent of CD4+ cells is at least 29% of all lymphocytes. Stage 2 (HIV infection): There are no AIDS-related conditions, and the CD4+ cell count is 200–499, or the percent of CD4+ cells is 14–28% of all lymphocytes. Stage 3 (AIDS): The CD4+ cell count is lower than 200, the percent of CD4+ cells is less than 14% of all lymphocytes, or an AIDS-related condition is present.



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Prospective Studies of HIV in Men These important studies (Evans et al., 1997; Leserman et al., 1999) were the first to employ a prospective design to address the role of severe psychosocial stressors in the progression of HIV pathophysiology. The first study was motivated by clinical observations of the heterogeneous nature of HIV disease progression, and some of this variance in disease progression might be explained by exposure of HIV-­positive individuals to significant life stressors. As detailed in the second report (Leserman et al., 1999), 82 HIV-­positive homosexual men were enrolled in this study and were without clinical symptoms at the beginning of a 66-month study period. Participants (mean age = 30 years, 79% White) were selected after screening for drug and alcohol use, comorbid diseases, medications that affect the immune system, and ongoing bacterial or viral infections. Every 6 months from study onset, participants underwent comprehensive medical and psychiatric assessments and completed a battery of psychosocial assessments. These tests included measures of depression and experiences with stressful life events. A measure of social support was taken on a yearly basis. This interview-­based methodology for assessing stressful life events was a modification of the Psychiatric Epidemiology Research Interview and included a list of 111 stressors ranging from trouble with a superior at work to death of a close friend or family member to financial difficulties. For each stressor endorsed by a participant, the interviewer focused on the context and severity of the experiences. No references to HIV disease progression were included among the list of stressors. In addition, exposure to severe stressors was determined every 6 months and only those stressors that occurred prior to disease progression were included in the analyses. For example, if a participant’s first evidence of disease progression occurred between the 24-month and the 30-month assessments, severe stress exposure per unit of time was calculated for the first 24 months only. During the course of the study, 27 participants progressed to a diagnosis of AIDS in an average time of 2.6 years. Over the 5.5-year duration of this study, eight participants died of AIDS-­related causes. Using a proportional hazard survival method (where survival was a proxy for absence of progression to AIDS) and with median scores of psychosocial measures used to divide participants into two groups, the findings clearly pointed to a significant effect of each of the four psychosocial variables on the progression to symptoms of AIDS (Table 11.3). Expressed in a different manner at the TABLE 11.3.  Effects of Psychosocial Variables on the Risk of a Diagnosis of AIDS in a Group of HIV-Positive Homosexual Men HR (95% CI)

p value

1.21 (1.07–1.36)

.002

3.96 (0.80–19.57)

.090

Depressive symptoms

1.30 (1.07–1.58)

.008

Satisfaction with social support

0.37 (0.22–0.63)

.0002

Psychosocial measure Stressful life events Diagnosis of major depression

Note. Regression models for the four psychosocial variables were adjusted for the number of retroviral medications used, age, level of education, race, CD4+ cell count, and tobacco use. Data are presented as hazard ratios (HRs) with 95% confidence intervals (CIs). Data are from Leserman et al. (1999) and are used with permission of the publisher.

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66-month endpoint of the study, participants below the median for stressful life events had a 28% higher probability of being free from AIDS compared to those above the median. For participants below the median for depressive symptoms, there was a 39% higher probability of being free of AIDS. Finally, for those above the median on social support, there was a 40% higher probability of being free of AIDS. When the psychosocial measures were combined into a single regression model, depressive symptoms were no longer significant contributors to the onset of AIDS. These two studies were conducted against a backdrop of suspected involvement of psychosocial stressors in the pathophysiology of HIV infections. Up to the time when these studies were conducted, however, the literature on stress and HIV progression was inconsistent and suffered from concerns regarding the imprecise assessment of psychosocial stressors. These results clearly pointed to severe life stressors as a significant risk factor for disease progression in asymptomatic HIV-­positive men, such that exposure to two moderate-­intensity stressors resulted in a twofold greater risk of progression to AIDS. These findings are consistent with the view that exposure to life stressors alters immune function and disease progression in HIV+ men (Evans et al., 1997; Leserman et al., 1999).

Meta‑Analysis of Stress and Coping in Women with HIV/AIDS McIntosh and Rosselli (2012) conducted a meta-­analysis of 40 research articles published between 1997 and 2011 that explored the impact of stress and coping mechanisms on health outcomes in adult females living with HIV/AIDS in the United States (N = 7,602, mean age = 36 years). The sample was made up of 67% African American women, 19% Hispanic women, 5% White women, and 9% women from other racial/ ethnic groups. A particular motivation for this meta-­analysis was to investigate possible psychosocial contributions to differences in HIV/AIDS disease progression. The time frame covered by this meta-­analysis was marked by the general availability of antiretroviral medications to manage the disease. The findings revealed that poor mental health outcomes were associated with psychosocial stress and symptoms related to HIV/AIDS. Significant effects were also observed with functional impairment, though to a lesser extent. Coping by avoidance and social isolation predicted more severe mental health challenges. Spirituality and positive reappraisal predicted greater psychological adaptation than did social support seeking. Despite advancements in the antiretroviral treatment for women, HIV/AIDS symptoms and acute and/or chronic psychosocial stressors pose the same threat to behavioral and mental health. In the face of these stressors, positive reframing appears to promote psychological adaptation in a way that may lead to positive health outcomes for women living with HIV/AIDS (McIntosh & Rosselli, 2012).

Stress‑Targeted Interventions in HIV/AIDS Consistent evidence has accumulated regarding the deleterious effects of exposure to psychosocial life stressors on HIV disease progression. Several research groups have developed stress management interventions specifically for HIV-­positive individuals in the hope that more effective management of life stressors would slow disease progression.



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Cognitive‑Behavioral Stress Management Intervention HIV-­positive individuals may also harbor coinfections of the Epstein–­Barr virus (EBV), the cause of infectious mononucleosis. EBV infections are of significant concern because this virus has been shown to enhance HIV replication, reduce levels of CD4+ T helper cells, and accelerate HIV disease progression. Psychosocial stressors also appear to affect EBV and HIV disease progression. Psychosocial stressors are a major concern in the management of patients with HIV, given the challenges they face in confronting the social stigma of being HIV-­positive, the social isolation that often accompanies a diagnosis of HIV, and management of a chronic disease. Given the research findings that link EBV, HIV, and stress levels, Carrico et al. (2005) examined the effects of a 10-week group-based cognitive-­behavioral stress management (CBSM) intervention on distress, dysphoria, perceived social support, and herpes virus immunoglobulin G (IgG) antibody titers during the 6–12 months following the intervention. Of those who were initially randomized, 49 HIV-­infected male participants (mean age = 35 years) were followed during the 6- to 12-month period after randomization to either a 10-week CBSM group (N = 31) or a modified wait-list control group (N = 18). Measures of distress, dysphoria, and social support and blood samples for measurement of herpes virus IgG titers were obtained under basal conditions, immediately following CBSM, and at 6- to 12-month follow-­up appointments. Participants in the CBSM group displayed persistent decreases in dysphoria and increases in reliable alliance support throughout the follow-­up period. In contrast, participants in the control group did not report changes in these behavioral measures. Participants in the CBSM group maintained previously observed intervention effects on dysphoria, reliable alliance support, and EBV antibody titers. Intervention-­related changes in EBV antibody titers were unrelated to changes in lymphocyte subsets (i.e., CD4+, CD8+, and CD4+:CD8+) or changes in measures of dysphoria and social support over the course of the 12-month follow-­up. These findings indicate that HIV-­infected men participating in the CBSM intervention maintained better psychosocial status and immunological control of latent EBV infection up to 1 year after completion of the CBSM intervention (Carrico et al., 2005).

Comparison of Three Stress Interventions Stress-­ induced immunosuppression may enhance disease progression in individuals with HIV infections. Stress management interventions may have favorable effects on HIV-­positive individuals by enhancing immune function. However, the nature of effective stress management interventions has yet to be determined. To address this lack of head-to-head comparisons of various stress management interventions, McCain et al. (2008) conducted a randomized clinical trial to test the effects of three different 10-week stress management interventions: (1) cognitive-­behavioral relaxation training (N = 65), (2) focused tai chi training (N = 62), and (3) spiritual growth (N = 68) compared to a wait-­listed control group (N = 52). Participants were males and females with an average age of 42 years, and 75% were African Americans. Compared to wait-­listed control participants, those in the cognitive-­behavioral relaxation and the tai chi groups employed less emotion-­focused coping, and all treatment groups displayed enhanced lymphocyte proliferative responses in vitro. Despite the modest effects of the interventions on

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psychosocial functioning, intervention-­related effects on immune function have important clinical implications for individuals with HIV infections (McCain et al., 2008).

VAGINAL INFECTIONS Sympathetic–­adrenal medullary, HPA axis, and immune responses to recurring psychosocial stimuli may disrupt the vaginal microbiome and increase the risk for genitourinary tract infections. Stress-­related hormones are risk factors for several infections, including genitourinary tract infections. In particular, cortisol-­induced inhibition of vaginal glycogen deposition may play a key role in the initiation of vaginal infections. In their detailed review, Amabebe and Anumba (2018) provided an overview of the vaginal microbiome under normal conditions and following exposure to stressors. In sexually mature females, the vaginal microbiome is dominated by Lactobacillus species, which produce significant quantities of lactic acid and hydrogen peroxide that maintain the vaginal environment at acidic levels (pH 3.5–4.5). This acidic microenvironment contributes in part to an inhibition of the growth of potentially pathogenic resident bacteria, including Streptococcus and Staphylococcus species. The proliferation of Lactobacillus bacterial species is dependent on elevated glycogen levels in vaginal epithelial cells, which in turn require elevated levels of estrogen. Glycogen is metabolized by a-amylase to yield lower molecular weight carbohydrates that are then metabolized by Lactobacilli. Stress-­induced release of cortisol inhibits the maturation of the vaginal epithelium and the accumulation of glycogen, leading to a decrease in resident Lactobacilli and lower levels of lactic acid and hydrogen peroxide production. These changes lead to an accumulation of anaerobic bacteria associated with bacterial vaginosis. Pro-­ inflammatory responses within vaginal tissue are further supported by cortisol as well as norepinephrine release (Amabebe & Anumba, 2018). Two studies highlighted in the next section explore the relationship between psychosocial stress and bacterial vaginosis in a prospective longitudinal study.

Psychosocial Stress and Vaginosis Nansel et al. (2006) examined the impact of psychosocial stressors on bacterial vaginosis in a group of nonpregnant women. Participants for this study (N = 3,614) were between 15 and 44 years of age and were recruited during routine health care visits at 1 of 14 clinics in the vicinity of Birmingham, Alabama. Assessments were conducted quarterly for 1 year and included a standardized pelvic examination, an assessment of clinical symptoms, and an extensive self-­report interview. Psychosocial stress was associated with an overall prevalence of bacterial vaginosis (OR = 1.10, 95% CI = 1.01–1.20) and an increased incidence of the infection (OR = 1.29, 95% CI = 1.12–1.48). The association between stress and the incidence of bacterial vaginosis was not changed significantly by controlling for behavioral and demographic characteristics and related risk factors.

Psychosocial Stress and the Vaginal Microbiome The vaginal microbiome provides the first line of defense against urogenital infections primarily through the protective actions of Lactobacillus species. Perceived stress



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increases susceptibility to infections through several mechanisms, including suppression of immune function. Turpin et al. (2021) investigated whether stress was associated with deleterious changes to the vaginal microbiome in a subsample of 572 women in the Longitudinal Study of Vaginal Flora, sampled from 1999 through 2002. They noted that participants who exhibited a five-unit increase in the Perceived Stress Scale had greater risk (HR = 1.40, 95% CI = 1.13–1.74) of developing molecular bacterial vaginosis, a state with low Lactobacillus abundance and the appearance of a diverse array of anaerobic bacteria. These findings suggest that psychosocial stress is associated with transitions in vaginal microbiota composition and create opportunities to explore mechanisms associated with stress-­induced bacterial vaginosis.

STRESS AND LIFE‑THREATENING INFECTIONS Stress-­related psychiatric disorders, including PTSD, acute stress reactions, and adjustment disorders, result in significant alterations in the HPA axis and in immune parameters. Some reports have also suggested links between PTSD and increased risk of infectious diseases. Song, Fall, et al. (2019) were interested in exploring connections between stress-­related psychiatric disorders and susceptibility to life-­threatening infections. These investigators took advantage of the national health care databases available in Sweden to pursue this research question using a sibling-­matched cohort design. They identified all individuals in Sweden who were diagnosed with stress-­related psychiatric disorders from 1987 to 2013 (N = 144,919) and compared them to two groups of controls: 184,612 full siblings from 71% of those with a stress-­related disorder and 1,449,190 individuals from the general population of Sweden who were not diagnosed with a stress-­related psychiatric disorder. Ten individuals from the general population were matched to each individual with a stress-­related disorder based on sex, year of birth, and county of birth. The focus of this study was on records from the Swedish National Patient Register of a first inpatient or outpatient visit, where the primary diagnosis was of a severe infection with a high mortality rate, including sepsis, endocarditis, and meningitis or other central nervous system infections, and deaths from these infections or infections of any origin from the Cause of Death Register. After controlling for multiple confounding variables, hazard ratios were estimated for these life-­threatening infections. The mean age at diagnosis of a stress-­related disorder was 37 years (55,541, 62% women). During a mean follow-­up of 8 years, the incidence of life-­threatening infections per 1,000 person-­years was 2.9 in individuals with a stress-­related disorder, 1.7 in siblings without a stress-­related disorder, and 1.3 in matched individuals from the general population. Compared with full siblings and controls from the general population, individuals with a stress-­related disorder were at elevated risk of life-­threatening infections, and this risk was increased even further for those with a diagnosis of PTSD. Stress-­related disorders were associated with all life-­threatening infections that were tracked, with the highest relative risk observed for meningitis. Use of selective serotonin reuptake inhibitors in the first year after diagnosis of a stress-­related disorder resulted in reduced risk of serious infection at a later date. These results provide evidence of a strong association between clinically diagnosed stress-­related psychiatric disorders and later risk of life-­threatening infections. This relationship held even after controlling for many demographic variables and medical

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and psychiatric comorbidities. Results consistent with these findings were reported by Jiang et al. (2019) for increased risk of a variety of infections in individuals diagnosed with PTSD in a population-­based cohort study in Denmark. A possible connection between stress-­related psychiatric disorders and downregulation of immune responses may provide a mechanism to explain in part the increased susceptibility to serious infections.

STRESS AND VACCINE CHALLENGE STUDIES Cohen and his colleagues have advanced our understanding of how psychosocial stressors affect susceptibility to viral infections through their landmark studies of participants in challenge tests with cold viruses that were described above (Cohen, 2020). However, many individuals do not raise their hands when asked if they would be willing to quarantine for almost a week, have researchers spritz viruses into their nasal passages, and wait to develop symptoms of a nasty cold. As an alternative to this experimental approach, vaccine challenge studies provide a host of advantages to investigators interested in studying the effects of stress on susceptibility to disease. In particular, many people receive vaccinations to protect against a range of pathogens, including measles, mumps, rubella, seasonal flu, hepatitis, pneumonia, and shingles, to name a few. Vaccines typically contain live, attenuated, modified, or killed pathogens and when administered, stimulate an immune response and the production of antibodies. Vaccine challenge studies provide researchers with an opportunity to study the impact of psychosocial stress on antibody production without the need for a prolonged quarantine or inducements for participation.

Stress and Antibody Production in Medical Students Glaser et al. (1992) were the first group to conduct a vaccine challenge study and link the results to levels of psychosocial stress and anxiety. Working with a group of healthy second-­year medical students (N = 25 males and 23 females), they administered a three-dose regimen of a vaccine for hepatitis B, with the first two doses separated by 1 month (mid-­November and mid-­December) and the third dose, a booster shot, given at 6 months (mid-May). Each vaccine injection was timed to coincide with the last day of a 3-day series of medical school exams that enhanced stress levels in participants. Blood samples were collected prior to each vaccine injection for measurement of antibodies to hepatitis B antigen. In addition, participants completed the Profile of Mood States instrument before each inoculation, and the Perceived Stress Scale was completed at the second and third inoculations. Finally, a scale to measure social support was administered 1 month prior to the third inoculation. None of the participants was antibody-­positive at the time of the first inoculation. Between the first and second inoculations, 12 of 48 individuals who tested positive for antibodies to hepatitis B had lower scores for anxiety and perceived levels of stress compared to those who did not seroconvert. Also, those participants who reported greater sources of social support displayed stronger immune responses to the third inoculation, as reflected in higher antibody titers and enhanced blastogenic responses to hepatitis B surface antigen.



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The results from this early experiment with a relatively small group of participants confirmed a strong link between elevated levels of psychosocial stress and immune responses to a hepatitis B vaccine challenge. The relatively mild and predictable levels of stress associated with scheduled exams in second-­year medical students exerted an impact on the immune responses to the hepatitis B vaccine challenge. In individuals who experience high levels of stress resulting from their employment, family commitments, or other sources, it is conceivable that immune responses to a vaccine might be compromised to an even greater extent than was observed in the medical student participants (Glaser et al., 1992).

Affective Style Influences Antibody Responses to Vaccine Administration Mounting evidence points to an association between psychosocial stressors and peripheral immune function. However, the mechanisms by which stressful experiences are processed within brain circuits and influence immune responses are poorly understood. Research reported by Rosenkranz et al. (2003) addressed this challenge by focusing on relationships between affective style, well-being, and immune responses. Participants (N = 52, of whom 24 were females) who were 57–60 years old were recruited for this study. Negative and positive affect was elicited by using an autobiographical writing task. Participants were asked to recall a joyful or exceptionally happy event (positive affect), and later were asked to recall an intensely sad, fearful, or anger-­provoking event (negative affect). Participants were asked to recall their positive or negative experiences for approximately 1 minute each and then to write about their positive and negative experiences for 5 minutes each. Electroencephalography (EEG) and affect-­modulated eye­blink startle responses were obtained under basal conditions, during the recollection of positive or negative events, and for 3 minutes after completion of each autobiographical writing task. Responses of participants to an influenza vaccine challenge were tracked by measuring antibody levels in blood samples prior to the inoculation and at 2, 4, and 26 weeks after inoculation. Higher levels of right-­prefrontal electroencephalographic activation and greater magnitude of the startle reflex were associated with reduced immune responses. Three physiological correlates of negative affective style were associated with reduced immune responses 6 months following inoculation. These included greater relative right-­ prefrontal EEG activation under baseline conditions and following induction of negative affect and a larger relative magnitude of the eyeblink startle response following induction of negative affect. These findings could not be explained by differences in pre-­inoculation antibody titers. These data are consistent with the view that individuals with a more pronounced negative affective style mount a weaker immune response to vaccination and therefore may be at greater risk for illness than those with a more positive affective style (Rosenkranz et al., 2003).

Daily Stressors and Antibody Responses A study by Miller et al. (2004) addressed several important questions regarding the impact of exposure to daily life stressors on the antibody response to an influenza vaccine. Participants in this study (N = 83, 55% female) were college freshmen who agreed to engage in ambulatory monitoring for 3 days before and 10 days following

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administration of an influenza vaccine. Each day at 1, 4, 9, and 11 hours after expected waking time, participants noted their stress levels and health-­related behaviors (smoking, alcohol use, activity levels, sleep patterns) on a hand-held computer. On days 2–6 of the 13-day assessment period, saliva samples were collected for measurement of cortisol. Blood samples were collected for measurement of antibody titers on day 3 of the monitoring period, just before the vaccine was administered and 1 and 4 months later. Higher self-­reported stress levels during the 13-day monitoring period were associated with diminished antibody responses to the influenza vaccine. Stress ratings on the first 3 days of the monitoring period did not affect the antibody responses to the vaccine. However, the 10 days after vaccine administration appeared to be a time when daily stress levels could influence the trajectory of the long-term antibody response. Levels of cortisol in blood, alcohol consumption, activity levels, and smoking did not appear to influence the relationship between daily life stressors and antibody responses to the influenza vaccine. Loss of sleep and daily experiences of stress combined to inhibit antibody responses to the vaccine. These findings provide important insights into the pathways through which daily stress exposure affects humoral responses to the influenza vaccine and increases vulnerability to infectious diseases. Behavioral interventions to reduce perceived levels of stress could be implemented prior to and in the days following vaccine administration in individuals known to be experiencing high levels of stress to ensure a robust antibody response to vaccine administration. In this regard, one study that employed a mindfulness meditation intervention for 8 weeks did report enhanced humoral responses to administration of an influenza vaccine (Davidson et al., 2003). Daily stressors may exert influences on the antibody response to vaccine administration well beyond the 10-day period in this study. In future experiments, it would be useful to monitor daily stress levels for a longer period of time to gauge the window of time following vaccine administration when antibody responses are sensitive to daily levels of stress (Miller et al., 2004).

STRESS EFFECTS ON WOUND HEALING This topic begins with a look back at the forces of evolution that have contributed to the regulation of immune system responses to stress in modern humans. As Miller and Raison (2016) have argued so convincingly, our early human ancestors evolved in a pathogen-­rich environment. Given that the risk of infection was high, there was a selection bias favoring those individuals who displayed immune responses prior to a threatening situation. This preemptive immune response could increase the probability of survival following an encounter with a predator, a dangerous hunting foray, or a conflict with an aggressive member of a neighboring social group. In each of these cases, the anticipatory immune activation could have increased survival from a serious wound and subsequent infections. Even if the immune activation turned out to be a false alarm, the risks were great enough that the low threshold for activation of inflammatory responses resulted in a net benefit (Miller & Raison, 2016). Kiecolt-­Glaser et al. (1995) were the first researchers to report that the chronic stress of providing continuing care to a loved one with dementia resulted in a delay in healing of a punch biopsy on the forearm compared to matched controls with no



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responsibilities for providing care. Indeed, wound healing took 24% longer in caregivers compared to controls. Since this initial report, the negative impact of life stressors on wound healing has been consistently demonstrated using a range of methodologies (refer to Gouin & Kiecolt-­Glaser, 2011, for a summary). Some of these experimental strategies will be highlighted in the studies that are presented below. In addition, an intervention to reduce levels of stress and enhance wound healing will be presented.

Stress Levels and Wound Healing in Diabetics Foot ulcers are a major complication of poorly managed type II diabetes and result in lower limb amputations in a significant percentage of diabetic patients, especially those with peripheral neuropathy. Foot ulcers are caused by chronically high blood glucose levels, poor circulation to the extremities, nerve damage that leads to a lack of sensation in the feet, and irritation to the feet from abnormal gait and injuries. Poor healing and lack of prompt attention to foot ulcers lead to an increased risk of amputation in diabetic patients (Jeffcoate & Harding, 2003). High levels of psychosocial stress may impede healing of foot ulcers in diabetic patients and increase the chances of infection of the ulcerous tissue. With these concerns in mind, Razjouyan et al. (2017) examined the effects of stress on rate of healing of foot ulcers in diabetic outpatients. These investigators employed a wearable sensor to measure heart rate variability and utilized this measure as a physiological marker of stress. Diabetic patients with foot ulcers (N = 25, mean age = 59 years) were recruited during visits to a diabetes clinic in Doha, Qatar. Heart rate variability was measured for 10–15 minutes while waiting for a fresh wound dressing to be applied. Wound size was measured during two consecutive clinic visits spaced approximately 3 weeks apart. Participants were then categorized as slow-­healing or fast-­healing based on changes in wound size. The rate of ulcer healing was 80% greater in fast-­healers compared to slow-­healers. Rate of ulcer healing was significantly correlated with both vagal tone (r = –.71, p = .001) and stress responsiveness (r = .71, p = .001) as extracted from the frequency domain of the electrocardiogram. No between-­group differences were observed for perceived stress levels, depressive symptoms, quality of life, fear of falling, pain levels, or standard clinical measures (BMI, HbA1c, or years since first diagnosis of diabetes). These findings revealed a significant association between heart rate variability parameters and the rate of wound healing in type 2 diabetic patients with foot ulcers. Of particular note is the possible contribution of elevated vagal tone in enhancing the rate of wound healing. The primary concern with this study is the small sample size, but the results were quite clear. There is a great benefit in identifying diabetic patients who are slow to heal so that they can be provided with stress management interventions and other medical and psychosocial support to avoid the necessity of lower limb amputations (Razjouyan et al., 2017).

Stress and Wound Healing in Living Kidney Donors One of many factors required for proper wound healing is a functioning immune system that responds appropriately to tissue injury. Indeed, inflammatory responses play an essential role in this cascade of cellular and molecular changes that lead to wound

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healing. One early element of this cascade involves signaling by cytokines and chemokines (e.g., IL-1b, TNF-a, IL-8) to prevent infection and stimulate the recruitment of phagocytes and other immune cells to the site of the injury. Thus begins the complex process of tissue regeneration and capillary repair (Gouin & Kiecolt-­Glaser, 2011). The link between psychosocial stress and wound healing is thought to be mediated by effects of the HPA axis and the sympathetic nervous system on the inflammatory response. Maple et al. (2015) studied the effects of psychosocial stress and personality characteristics on the rate of healing of surgical incisions. Participants in their study were living kidney donors (N = 52) who were free of any significant medical or psychological comorbidities. One to 2 weeks prior to a hand-­assisted laparoscopic nephrectomy, participants completed the Perceived Stress Scale, the Life Orientation Test–­Revised Version, and the Ten-Item Personality Inventory. Patients were admitted to the hospital on the day of surgery, and the procedure for removal of the donor kidney involved three incisions. Two incisions were small (5–10 mm) and lateral to the midline to allow for insertion of the laparoscopic instrument and the camera. The largest incision (7′–10 cm) was in the midline and allowed the surgeon to insert his or her hand and extract the donor kidney. Following surgery, the incisions were closed with surgical glue to facilitate monitoring of wound healing by high-­resolution ultrasound. This method for monitoring wound healing provided a detailed image of the layers of skin and the size of the wound, and the fluid content of the surgical incision could be quantified. Ultrasound scans of the surgical incisions were performed on the first 3 days postoperatively and 10–20 days following discharge from the hospital. Those living kidney donors with higher levels of perceived stress and lower scores for optimism and conscientiousness exhibited slower rates of healing of their surgical incisions as reflected in size of incision and fluid content. In contrast, those kidney donors who scored high on optimism, conscientiousness, and emotional stability displayed enhanced rates of healing of their surgical incisions. Given that organ donors are carefully screened for preexisting medical conditions prior to surgery, the results of this study were likely not influenced by variations in underlying medical issues among the participants. This study also highlighted the value of high-­resolution ultrasound to track the rate of wound healing in surgical patients (Maple et al., 2015).

A Stress‑Targeted Intervention to Enhance Wound Healing Broadbent et al. (2012) took the next logical step and examined whether a behavioral intervention to reduce stress levels in surgical patients could accelerate wound healing. Participants in this randomized controlled trial (N = 60, of whom 45 were female, mean age = 51 years) were scheduled for elective laparoscopic surgery to remove the gallbladder. Participants were randomly assigned to receive standard care or standard care plus a 45-minute intervention with a health psychologist that included information on deep breathing, muscle relaxation, and guided imagery. In addition, participants were provided with CDs for listening at home for 3 days before and 7 days after surgery. Before and after surgery, participants completed the Perceived Stress Scale. To quantify wound healing, two flexible plastic tubes (20 cm) were inserted in the subcutaneous layer of the abdominal wall and secured externally with sutures. These tubes were removed 7 days after surgery, and levels of hydroxyproline were quantified as a measure of collagen deposition and wound healing.



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Participants in the stress intervention group exhibited a significant reduction in levels of perceived stress compared with participants in the standard care control group (p = .048). In addition, participants in the stress intervention group had higher levels of hydroxyproline deposition in their subcutaneous plastic tubes compared to controls (p = .03). No infections were reported as a result of the placement of subcutaneous plastic tubes. Levels of perceived stress before and after surgery were not correlated with levels of hydroxyproline (ps > 0.05). A brief psychological intervention prior to surgery can reduce stress levels and improve wound healing in elective surgical patients. Future research studies could be devoted to optimizing the timing and characteristics of the psychological intervention in a much larger sample of participants. Psychological interventions that are designed to reduce stress and anxiety levels in patients before and immediately after major surgery may be advantageous to enhance healing of the incision(s) and reduce infections in patients at risk of poor healing (Broadbent et al., 2012).

THE COVID‑19 PANDEMIC At the end of 2019, Wuhan, a city of more than 10 million residents in east-­central China, experienced an outbreak of a novel coronavirus that spread rapidly among the population, killing almost 2,000 individuals and infecting more than 70,000 others in the first 50 days of the outbreak (Shereen, Khan, Kazmi, Bashir, & Siddique, 2020). The virus was labeled severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the disease it causes has been referred to as COVID-19. On March 11, 2020, the World Health Organization officially declared COVID-19 a pandemic (World Health Organization, 2020). Within 18 months after first being detected, SARS-CoV-2 had spread to most areas of the world, exacting a devastating toll of severe illness (> 200 million cases) and death (> 2 million confirmed deaths) and precipitating a global economic calamity. With unprecedented speed, laboratories around the globe raced to develop vaccines and therapeutics, with 18 vaccines approved for emergency use in at least one country, and some others fully approved. Many other vaccines and drugs to treat COVID-19 are in various stages of preclinical or clinical testing. By mid-2021, more than 3 billion doses of vaccines had been administered worldwide, mostly in high-­income countries (Ndwandwe & Wiysonge, 2021). From discussions earlier in this chapter, it has become evident that the efficacy of vaccines depends on the nature of the vaccine as well as the characteristics of those who are vaccinated. As Madison, Shrout, Rennal, and Kiecolt-­Glaser (2021) have discussed, the immune response to a vaccine can be impaired by a variety of psychosocial factors, including levels of stress, depressive symptoms, loneliness, and risky behaviors such as smoking, lack of exercise, and a poor diet. An additional concern in the rollout of the COVID-19 vaccines has been the compromised immune responses of older individuals, especially among individuals who reside in nursing homes. Some of the challenges that have accompanied the COVID-19 pandemic are the high levels of stress, depression, and anxiety associated with restrictions in movement resulting from quarantines and school closures, combined with lack of child care, financial concerns, fear for the safety of loved ones, and loneliness. For example, Holman,

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Thompson, Garfin, and Silver (2020) surveyed a nationally representative sample of Americans between March 18 and April 18, 2020, at a time of increasing COVID-­ related illness and death. Their findings revealed that levels of acute stress and depressive symptoms increased significantly during the pandemic. In addition, health care and other frontline workers have had to report to work even when the risk of infection with COVID-19 was high (Pfefferbaum & North, 2020; Van Bavel et al., 2020). How might elevated levels of chronic stressors associated with the COVID-19 pandemic affect responses to the various vaccines that are now available? As Madison et al. (2021) have noted, high levels of distress associated with the COVID-19 pandemic have resulted in increases in symptoms of anxiety and depression, which can impair the immune system’s innate and adaptive responses to a vaccine. In addition, elevated levels of stress around the time of vaccination increase the frequency and severity of side effects of the vaccine. Even a modest increase in side effects of vaccine administration could reduce the likelihood that others would seek out the vaccine, given how rapidly bad news spreads on social media. Other factors related to levels of stress also tend to have a negative impact on vaccine effectiveness, including social isolation, loss of employment, and bereavement. In addition, lifestyle changes that frequently occurred during the pandemic included reduced physical activity, increased smoking and alcohol intake, lack of a healthy diet, and alterations in sleep patterns (Cohen, 2020; Madison et al., 2021). Thus, the COVID-19 pandemic created the perfect storm of behavioral changes that collectively has been shown to increase risk of infection and reduce vaccine effectiveness. Some of the breakthrough infections in fully vaccinated individuals may be explained, at least in part, by high levels of exposure to these stressors and lifestyle changes. An obvious question that derives from these findings is what can be done to optimize vaccine effectiveness in highly stressed and vulnerable individuals. Public health messaging has the potential to instill calm and confidence in individuals who are considering receiving the COVID-19 vaccine, and the subtle signals that are conveyed at vaccination sites also have a role to play. Health care personnel who assist with obtaining background information from patients as they arrive at a vaccination site and those who deliver shots can reduce stress levels and increase resilience by their demeanor and their positive attitudes. The same can be said for the physical environment of the vaccination site. Is the vaccination site located in a crowded windowless basement room or in a bright and cheerful location? Ongoing studies of vaccine effectiveness will address some of these issues, and relevant findings can inform national strategies governing responses to the next global pandemic.

CONCLUSIONS For much of our existence as a species, humans have been at high risk of serious illness and death from various infectious agents. At the beginning of the 20th century, pneumonia, tuberculosis, influenza, gastrointestinal infections, and diphtheria were among the leading causes of death in the United States. The life expectancy at that time was approximately 47 years. With the development of antibiotics and antiviral drugs as well as effective vaccines against pneumonia, influenza, and other infectious agents, life expectancy increased by the year 2000 to approximately 77 years, and the leading



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causes of death were no longer infectious agents but chronic diseases such as cardiovascular disease and cancer. However, recent experiences with the HIV/AIDS pandemic and the COVID-19 pandemic have provided some hard lessons about our continuing vulnerability to infectious agents that our immune systems have never been exposed to. In this chapter, we have explored the ways in which stressful life events can impact our susceptibility to infections, from the common cold to shingles to HIV. Negative effects of stress were also apparent in processes related to wound healing and recovery from life-­threatening infections. Consistent with findings presented in earlier chapters, behavioral interventions to reduce the negative effects of psychosocial stressors and enhance coping mechanisms boosted immune function and resistance to new infections or slowed the progression of existing infections (Schneiderman, McIntosh, & Antoni, 2019). Finally, vaccine challenge studies have provided compelling evidence that high levels of stress prior to and immediately following vaccine administration can reduce the immune response to the vaccine. These findings have special relevance for the COVID19 vaccines and those who receive them.

CH A P TER 12

Systemic Racism as a Stressor

O

n May 25, 2020, George Floyd, a 46-year-old African American man, was murdered after being arrested on suspicion of passing a counterfeit $20 bill at Cup Foods grocery store in Minneapolis, Minnesota. Four police officers arrived on the scene to arrest Mr. Floyd. One of them, Officer Derek Chauvin, kept his knee on Mr. Floyd’s neck and back for 9 minutes and 29 seconds. On several occasions during his restraint while lying face-down in the street with his hands cuffed behind him, Mr. Floyd could be heard telling the police officers that he could not breathe. During the final 2 minutes of restraint, Mr. Floyd lay motionless in the street and did not have a pulse. Following an autopsy, Mr. Floyd’s death was ruled a homicide due to asphyxia resulting from neck and back compression. Officer Chauvin, who is White, was later charged with murder, found guilty by a jury, and sentenced to 22.5 years in prison. In February 2022, the other three officers who were involved were found guilty in federal court of violating Mr. Floyd’s civil rights. The tragic death of George Floyd sent reverberations around the world in large part because his slow and painful murder was recorded on the cell phone of Ms. Darnella Frazier, a high school junior who walked to the grocery store while Mr. Floyd was being restrained. She recorded Floyd’s murder and posted the video on Facebook early the next morning. Without her video, there would have been no way to dispute the initial police accounts of Mr. Floyd’s death. In the days and weeks that followed, major demonstrations erupted in many cities and towns throughout the United States and around the globe protesting police brutality directed toward people of color. Floyd’s death in many ways was the spark that ignited passions that had been kept just below the surface through so many previous deaths of people of color at the hands of the police. During the summer of 2020 and continuing to the present, elected officials at all levels, business leaders, college and university presidents, and community leaders have committed to enhanced policies to support equity, diversity, and inclusion within their spheres of influence and in their communities. But these problems at the intersection of race, poverty, and inequity have persisted for generations in spite of the best efforts of some and the policies enacted by others. Although these commitments to address 236



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structural racism in our society do appear to be gaining traction, only time will tell if these efforts can be sustained and result in meaningful improvements in the lives of African Americans and other minorities. In this chapter, we will consider the ways in which racial inequities in their various forms constitute a powerful source of psychosocial stress and result over time in increasing levels of allostatic load. These elevations in allostatic load have been shown to contribute to higher levels of morbidity and mortality in ethnic minorities in the United States, especially African Americans. We continue to experience many indirect effects of the legacy of slavery, a stain on the fabric of this nation that may never be washed away.

RACISM IN MEDICAL RESEARCH: THE TUSKEGEE SYPHILIS STUDY To set the context for this chapter on racism as a stressor that exerts adverse effects on health, it is important to reflect on the decades-­long tragedy of the Tuskegee Syphilis Study and its reverberations to the present. The Tuskegee Syphilis Study had its origins in the extraordinary philanthropic efforts of Julius Rosenwald, one of the original partners in the Sears, Roebuck & Company that was headquartered in Chicago, Illinois. Rosenwald, the son of Jewish immigrants from Germany, dedicated much of his great fortune to improving the lives of African Americans in southern states as well as those who moved north during the Great Migration. He partnered with Booker T. Washington to address the needs of African Americans in the South and provided significant financial support as a member of the Board of Directors of the Tuskegee Institute from 1912 until his death in 1932. Over the last 20 years of his life, he underwrote the costs of more than 5,000 schools, homes for teachers, and shops in African American communities in the South. He also provided financial support for the construction of 25 YMCAs for African Americans in Chicago, New York, and other cities in northern states (Jones, 1981).

Involvement of the U.S. Public Health Service In 1932, the medical director of the Rosenwald Fund approached officials in the U.S. Public Health Service to express concern over the health and welfare of African Americans in the rural South. At that same time, the Public Health Service had recently completed a study of the prevalence of syphilis in Mississippi, and the results revealed that 25% of adults tested positive. The Rosenthal Fund provided support for medical treatment of these individuals. Based on this successful early collaboration, Public Health Service officials proposed an expansion of syphilis demonstration projects in counties in five southern states with support from the Rosenwald Fund. After documenting the high prevalence of syphilis in these localities, the onset of the Great Depression wiped out much of the value of the Rosenwald Fund, and there was a lack of financial support available to underwrite treatment for those individuals with syphilis (Jones, 1981; Thomas & Quinn, 1991).

When Things Went Terribly Wrong Given the lack of funding for treatment programs at the time, a physician with the Public Health Service, Dr. Taliaferro Clark, recommended an experiment limited to Macon

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County, Alabama, that would follow 399 untreated African American men with syphilis and 201 uninfected African American controls until they died. During the course of this study, it is now clear that the men who volunteered were given the distinct impression that they were receiving free medical treatment for “bad blood,” a local expression for syphilis and other ailments. Concerted efforts were made to enlist the collaboration of Tuskegee Institute physicians and nurses and local churches to bolster support for the study. An African American public health nurse in Macon County, Ms. Eunice Rivers, was involved with the project for the entire 40-year period and formed trusting relationships with all of the men to ensure a high level of cooperation. She was also a co-­author on several of the published studies that resulted from the ongoing experiment (Brandt, 1978; Thomas & Quinn, 1991). It is difficult to fathom that public health physicians involved in this study did not inform the men in the Tuskegee Syphilis Study about the nature of their disease and its mode of transmission through sexual contact. As penicillin became available for the treatment of syphilis in the mid-1940s and was the standard of care by 1951, extreme efforts were taken to withhold penicillin from these men so that the “experiment” could run its course. Families of men who died were incentivized with direct financial support, including burial expenses, to agree to have autopsies performed (Thomas & Quinn, 1991).

Shining a Light on Unethical Behavior Concerns about the Tuskegee Syphilis Study were first raised in 1967 by Peter Buxtun, a Public Health Service staff member involved in venereal disease studies in San Francisco. As a direct result of Buxtun’s persistence, the Centers for Disease Control convened a review panel in 1969 to discuss the Tuskegee study. Surprisingly, this review panel recommended that the Tuskegee Syphilis Study continue without any medical treatment provided to the men. The situation drew national attention when Buxton shared his concerns with a reporter with the Associated Press, and an article appeared in the Washington Star on July 25, 1972, with all of the salacious details of the Tuskegee Syphilis Study and the failure of institutions of government to protect the men who were involved. Senator Edward Kennedy convened congressional hearings in 1973 that resulted in a complete overhaul of federal regulations governing the protection of human subjects (participants) in research. In addition, the U.S. government settled a class-­action law suit and agreed to pay $10 million to the men in the study (Thomas & Quinn, 1991). The Tuskegee Syphilis Study will go down in infamy as the longest experiment in history in which medical treatment was intentionally withheld from human participants. The reverberations from this ethical debacle continue to the present. Even superficial knowledge of the Tuskegee Syphilis Study created long-­lasting fears in the African American community about deeply rooted racial prejudice in the medical community and led to widespread distrust of the motivations of medical research. This lack of trust among African Americans led to challenges for public health officials during the rollout of needle exchange programs designed to prevent the transmission of HIV to drug users in the 1980s (Fairchild & Bayer, 1999; Thomas & Quinn, 1991). More recently, echoes of Tuskegee were heard when pharmaceutical companies encountered difficulties in recruiting African American volunteers to test COVID-19 vaccines. Once



Systemic Racism as a Stressor 239

vaccines received emergency use authorization to prevent COVID-19 infections, the African American community expressed considerable concern about vaccine safety, and many initially refused to receive the vaccine (Warren, Forrow, Hodge, & Truog, 2020).

RACIAL INEQUITIES AND ALLOSTATIC LOAD McEwen and Stellar (1993) introduced the concept of allostatic load to address some of the shortcomings of Selye’s overly broad conception of stress (see Chapter 1). This concept is especially useful when considering the insidious and pervasive effects (“wear and tear”) of systemic racism on the health and well-being of people of color. Several algorithms have been developed to compute allostatic load scores in individuals based on a range of biomarkers relevant to physiological regulation. Regardless of ethnicity, elevated allostatic load scores are associated with increased incidence of cardiovascular disease and all-cause mortality (Borrell, Dallo, & Nguyen, 2010). Allostatic load scores capture the slowly unfolding but persistent effects of systemic racism on neural, endocrine, and immune parameters critical for homeostatic regulation (Figure 12.1). The stressors that affect the health status of African Americans begin during the prenatal period and continue throughout life, resulting in elevations in allostatic load and increased risk for chronic diseases, including diabetes, cardiovascular diseases, and mental disorders. A related concept specific to racial disparities in health outcomes is the weathering hypothesis that Geronimus (1992) first introduced based on her studies of racial

Inadequate Access to Health Care Frequent Trauma Exposure

Lack of Educational Achievement

Legacy of Structural Racism

Daily Experiences with Discrimination

Social Community Disadvantage Disadvantage

Maternal Reduced Perinatal Exposure to Birthweights Complications Discrimination

FIGURE 12.1.  The mosaic of stressors that contributes to the impact of structural racism on the health status of African Americans. These stressors begin during the prenatal period and continue throughout life, resulting in elevations in allostatic load and increased risk for chronic diseases, including diabetes, cardiovascular diseases, and mental disorders.

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inequalities in the health of women and infants. The weathering hypothesis posits that chronic exposure to discrimination and economic disadvantage in minority populations is associated with an accelerated decline in health outcomes. Her focus later expanded to tests of the weathering hypothesis by examining differences in the morbidity and mortality of African Americans and White Americans based on allostatic load scores, as will be discussed in the next section (Geronimus, Micken, Keene, & Bound, 2006). A recent systemic review by Forde, Crookes, Suglia, and Demmer (2019) found evidence in favor of the weathering hypothesis as an explanation for racial differences in health outcomes.

Testing the Weathering Hypothesis Geronimus et al. (2006) utilized data collected between 1999 and 2002 from the National Health and Nutrition Examination Survey (NHANES) to compute allostatic load scores for African American and White American men and women who were 18–64 years of age at the time of data collection. A critical issue in this study was to determine whether African Americans experienced health deficits at early ages consistent with the weathering hypothesis. African American and White participants were divided into the following age cohorts: 18–24, 25–34, 35–44, 45–54, and 55–64 years of age. The participant pool across age cohorts and racial groups was 6,586 individuals. Allostatic load scores were based on the following 10 measures: systolic and diastolic blood pressure; body mass index; and blood levels of hemoglobin-­A1c, albumin, creatinine clearance, triglycerides, C-­reactive protein, homocysteine, and total cholesterol. The results demonstrated that African American males and females had higher allostatic load scores compared to Whites at all ages, and the differences between races increased with increasing age. Importantly, these differences in allostatic load scores persisted after controlling for income levels. In addition, African American women had higher allostatic load scores than African American men across all age levels, and this difference was especially evident in African American women with significant economic resources. Geronimus et al. (2006) suggested that elevated allostatic load scores in African Americans reflect the chronically high-­stress levels of living and working in a race-­ conscious society. In addition, the data from this study were consistent with the weathering hypothesis in that African Americans showed evidence of poor health at earlier ages compared to Whites, and this differential was approximately 10 years.

Allostatic Load and Morbidity and Mortality in African Americans Differences in mortality between African Americans and non-­Hispanic Whites persist even after adjustment for differences in socioeconomic status (SES) and behaviors relevant to health (smoking, exercise, diet, alcohol intake). Duru, Harawa, Kermah, and Norris (2012) hypothesized that differences in allostatic load scores driven by chronic exposure to racial inequities might explain in part the differences in mortality that have been documented between African Americans and Whites. These investigators made use of the third wave of data collection for NHANES from 1988 to 1994 and determined participant deaths through 2006. The NHANES sample included 1,888 African American males and females and 2,627 White males and females. Allostatic load scores were computed for all participants using 10 biomarkers,



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including blood pressure, HbA1c, albumin levels, triglycerides and total cholesterol, C-­reactive protein, glomerular filtration rate, and waist to hip ratio. Unfortunately, no measures of HPA axis activity or immune markers were obtained in the NHANES study. African American men and women had higher allostatic load scores than White men (2.5 vs. 2.1, p < .01) and women (2.6 vs. 1.9, p < .01), respectively. Mortality related to cardiovascular disease and type II diabetes was significantly higher in African Americans compared to Whites. The magnitude of this racial disparity for women was decreased after adjustment for a range of risk factors, and it was reduced even further after adjusting for allostatic load scores. A similar pattern was observed for noninjury-­ related mortality in women. Data for African American and White males revealed that disparities in mortality were reduced but remained significantly different even after adjustment for allostatic load scores (Table 12.1). Higher allostatic load scores explain in part the higher mortality rates of African Americans compared to Whites after adjusting for SES and health-­relevant behaviors. These findings underscore the importance of chronic race-based stressors as a pervasive negative influence on allostatic load scores and in turn, on the morbidity and mortality of African American men and women in the United States. Ongoing efforts to reduce health care inequities and eliminate structural racism in policies at the local, state, and federal levels that affect the lives of African Americans will hopefully contribute to continuing reductions in allostatic load scores and racial differences in morbidity and mortality (Duru et al., 2012).

Mediators of Higher Allostatic Load Scores in African Americans Building on the earlier findings reported by Duru et al. (2012) and others on racial differences in allostatic load scores, Tomfohr et al. (2016) examined mediators that might contribute to the higher allostatic load scores of adult male and female African Americans (N = 75) compared to Whites (N = 101). African American and White participants TABLE 12.1.  Disparities between African Americans and Whites in Cardiovascular/ Diabetes-Related Mortality and Non-Injury-Related Mortality Comparisons 1

2

3

Cardiovascular/diabetes-related mortality Males

2.24 (1.59–3.16)

1.93 (1.27–2.92)

1.55 (1.04–2.32)

Females

2.00 (1.31–3.06)

1.63 (0.96–2.75)

1.15 (0.70–1.88)

Non-injury-related mortality Males

2.11 (1.61–2.76)

1.54 (1.10–2.17)

1.39 (1.00–1.92)

Females

1.66 (1.27–2.17)

1.43 (1.00–2.04)

1.26 (0.90–1.78)

Note. Comparison 1: no adjustments in mortality data. Comparison 2: adjustments for socioeconomic status and health risk behaviors. Comparison 3: addition of allostatic load scores to adjustments in Comparison 3. Data are presented as hazard ratios (HRs) with 95% confidence intervals (CIs). White participants represent the reference group for the three comparisons with an HR set at 1.00. Data are from Duru et al. (2012) and are used with permission of the publisher.

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were admitted to a clinical research unit for a 2-night stay. Questionnaires were provided to participants upon arrival and were collected at discharge. Blood samples were collected the next morning from an intravenous catheter that was inserted the previous day. Overnight urine samples were also collected from each participant. Measures taken from each participant included lifestyle and demographic data; experiences with discrimination; levels of hostility, anger, and depression; subjective sleep quality; and several biomarkers (blood levels of cholesterol, IL-6, and C-­reactive protein; blood pressure; and fasting levels of glucose and urinary levels of norepinephrine, epinephrine, and cortisol). An allostatic load score was determined for each participant using 11 biomarkers. African Americans had significantly higher allostatic load scores compared to Whites. Serial mediation analyses pointed to a pathway whereby African Americans experienced greater levels of discrimination → increased anger + decreased sleep quality → higher allostatic load scores. These variables fully accounted for the relationship between race and allostatic load scores (p < .05). Although this study had a modest sample size, it did include males and females as well as a wide range of biomarkers for the determination of allostatic load scores. This study of young adults shines a bright light on personal experiences with discrimination as a key life stressor that drives increases in expression of anger and disrupts quality of sleep. These changes in turn exert a decidedly negative effect on a range of biomarkers related to health outcomes. The anger measurement used in this study captures feelings of being mistreated and the need to remain on high alert at all times simply because of the color of one’s skin. Internalized anger also contributes to disruptions in perceived quality of sleep that adds to the physiological dysregulation characteristic of higher allostatic load (Tomfohr, Pung, & Dimsdale, 2016). Finally, Goosby, Straley, and Cheadle (2017) have emphasized the importance of stress-­induced disruptions in sleep in their model of the ways in which racial discrimination increases cardiometabolic risk.

The Nashville Stress and Health Study The late R. Jay Turner (1934–2018), Professor of Sociology and a former colleague of mine at Vanderbilt University, designed the Nashville Stress and Health Study to explore the impact of socioeconomic measures on the health status of African American (N = 575) and White American (N = 598) participants who were 22–68 years of age. Each participant completed a nearly 3-hour in-­person interview and provided urine and blood samples for later analyses. In addition, a technician took several blood pressure measurements as well as waist, hip, height, and body weight measures. Allostatic load scores were derived from the following measures: epinephrine and norepinephrine in urine, plasma levels of cortisol and dehydroepiandrosterone sulfate, systolic and diastolic blood pressure, total cholesterol, high-­density lipoproteins, HbA1c, and waist-tohip ratio (with appropriate adjustments for participants who were taking antihypertensive and statins to reduce cholesterol levels). Consistent with other studies, allostatic load scores of African American males and females in the Nashville study were significantly higher than scores for White males and females (ps < .001). In addition, their findings challenged the notion that racial differences in health outcomes could be explained in large measure by differences in



Systemic Racism as a Stressor 243

socioeconomic variables. Rather, Turner, Brown, and Hale (2017) suggested that racial differences in health are grounded in social context and experience, including experiences of racism and discrimination. More recently, DeAngelis (2022) conducted further analyses on the Nashville Stress and Health Study dataset but added information from neighborhood-­level census data. His findings revealed that African Americans who lived in poorer neighborhoods in the Nashville metropolitan area had higher levels of stress hormones compared to African Americans who lived in predominantly White neighborhoods. But there were costs associated with moving into higher status neighborhoods, given that African Americans residents of these neighborhoods reported higher levels of perceived discrimination. The net result was that African Americans who lived in high-­status neighborhoods experienced chronic body pain and higher levels of goal-­striving stress, which in turn resulted in higher levels of stress hormones and blood pressure. Thus, what should be a sign of success for African Americans may revert to a negative in that the higher stress levels associated with living in a high-­status neighborhood cancel out the health benefits that would be expected (DeAngelis, 2022).

Allostatic Load in Mexican Immigrants Immigrants to the United States from Mexico also experience racial discrimination as they attempt to assimilate into the majority culture, resulting in an “unhealthy assimilation.” Data suggest that Mexican immigrants are healthy upon arrival in the United States, but their health status declines with increasing time in their new country. Kaestner et al. (2009) were interested in whether the cumulative impact of exposure to repeated or chronic stressors related to discrimination, as measured by allostatic load, underlies the unhealthy assimilation effects often observed for immigrants living in the United States. They analyzed data collected from 1988 to 1994 from the NHANES to estimate the odds of having a high allostatic load score among Mexican immigrants, stratified by adult age group, according to length of residence in United States, and controlling for demographic, socioeconomic, and health input covariates. Their data indicate that 45- to 60-year-old Mexican immigrants have lower allostatic load scores upon arrival than U.S.-born Mexican Americans, non-­Hispanic Whites, and non-­Hispanic African Americans, and that this health advantage decreases with increasing time of residence in the United States. These group differences remained even after controlling for health-­related behaviors and health care utilization. Data from this study support the view that repeated or chronic physiological adaptation to discrimination-­ related stressors contributes to the unhealthy assimilation effect observed for Mexican immigrants to the United States (Kaestner et al., 2009).

BEHIND FROM THE BEGINNING In this section, we will explore how allostatic load associated with racial inequities negatively impacts African American mothers and their babies. The statistics on birth outcomes for African American mothers and their babies are alarming and have been resistant to change in spite of intensive interventions. African American women are more than 50% more likely to have a preterm birth (prior to 37 weeks’ gestation) and

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are almost twice as likely to have a low-­birthweight baby (< 2,500 grams) compared to White women. In addition, the perinatal mortality rate is 3.5 times higher and the mortality rate in the first year after birth is 2.3 times higher for African American babies compared to White babies. These alarming differences in birth outcomes for African American and White women and their babies cannot be explained solely on the basis of socioeconomic differences (Alhusen, Bower, Epstein, & Sharps, 2016; Leimert & Olson, 2020; Patterson, Becker, & Baluran, 2022). In the studies highlighted below, we will explore the role played by racial discrimination and other racially motivated psychosocial stressors on birth outcomes in African American women.

Lower Birthweights in African American Babies A landmark study by David and Collins (1997) explored racial differences in the birthweights of African American women, women born in Africa who immigrated to the United States, and White women living in Illinois who delivered between 1980 and 1995. Their investigation revealed that mean birthweights of babies born to White women and West African-­born Black women were more similar to each other than to the mean birthweight of babies born to African American women (Table 12.2). Indeed, the distribution of birthweights for babies born to African-­born mothers approximated the distribution of birthweights of babies born to White mothers. In contrast, the distribution of birthweights for babies born to African American women was shifted to the left and was lower than that of women in the other two groups. These findings did not support previous suggestions that differences in birthweights between African American and White babies were strongly genetically determined.

Racial Discrimination and Premature Births Collins, David, Handler, Wall, and Andes (2004) hypothesized that lifetime exposure to racial discrimination in African American women is associated with adverse pregnancy outcomes. To test this hypothesis, they conducted a case–­ control study TABLE 12.2.  Birthweights of Babies Born in Illinois between 1980 and 1995 to African American Women, African Women Who Had Emigrated to the United States, and White Women Variable

African American

African-born

White

Number of births

43,322

3,135

44,046

Mean birthweight (g)

3,089

3,333

3,446

Low-birthweight infants (%) (less than 2,500 g at birth)

13.2

7.1

4.3

3.1 (2.9–3.2)

1.6 (1.4–1.9)

1.0

Relative risk of a low-birthweight baby (95% CI)

Note. Data are from David and Collins (1997). Differing birth weight among infants of U.S.-born blacks, African-born blacks, and U.S.-born whites. New England Journal of Medicine, 337, 1209–1214. Copyright © 1997 Massachusetts Medical Society. Reprinted with permission from Massachusetts Medical Society.



Systemic Racism as a Stressor 245

of African American women (N = 104) who delivered very-low-­birthweight, preterm infants ( 37 weeks’ gestation). The infants of some of the control mothers were admitted to the neonatal intensive care unit and were placed on a ventilator. Trained African American interviewers collected demographic information and lifetime and pregnancy-­specific experiences with racism from each mother who agreed to participate in the study. Domains of interest for personal experiences with racism included when at work, applying for a job, or at school, obtaining medical care, and seeking service at a restaurant or a store. The results revealed that mothers of very-low-­birthweight infants reported the highest level of significant racial discrimination when seeking a job and when at work. The odds ratio of having a very-low-­birthweight infant after experiencing racial discrimination in one or more of the domains was 1.9 (95% CI = 1.2–3.1), and the odds ratio in three or more domains was 3.2 (95% CI = 1.5–6.6). Instances of perceived discrimination during pregnancy were not associated with having a very-low-­birthweight infant. These findings were consistent when mothers of very-low-­birthweight infants were compared to mothers with an infant on a ventilator and with mothers of infants in the regular newborn nursery. This study provided strong evidence that lifelong experiences of mothers with racial bias and discrimination prior to becoming pregnant increased their risk for delivering a premature infant. Surprisingly, experiences with racial discrimination during pregnancy did not affect premature births. These findings point to the accumulated stress of perceived instances of racial discrimination as a risk factor for premature delivery in African American mothers (Collins et al., 2004).

Racial Discrimination and Preterm and Low‑Birthweight Deliveries Mustillo et al. (2004) examined the effects of self-­reported experiences of racial discrimination on differences between African American and White women in preterm ( .30). These findings clearly demonstrated that trait resilience is independently associated with health-­related quality of life in employed patients 1 year following hospitalization for a heart attack. However, resilience did not moderate the negative consequences of work-­related stress on health-­ related quality of life. Further studies are needed to confirm the results of the present trial and should include a more diverse patient population.



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Cancer Two studies are presented next, one involving men diagnosed with prostate cancer and the other involving women diagnosed with breast cancer. Both studies were designed to investigate the impact of prior exposure to stress as a means of enhancing resilience and being able to confront the challenges associated with a cancer diagnosis. The underlying theory behind these two studies is that experience with moderate, time-­limited stressors provides an individual with opportunities to develop effective coping strategies and a sense of mastery that can be called into play later in life. In contrast, exposure to severe, prolonged stressors or traumatic experiences tends to overwhelm individuals and does not enhance resilience. These stress-­buffering effects have been referred to as toughening, steeling, or stress inoculation (Dienstbier, 1989; Meichenbaum & Novaco, 1985; Rutter, 2006).

Resilience and Prostate Cancer Outcomes Sharpley, Christie, and Bitsikal (2021) examined the possibility of a “buffering” effect of psychological resilience (PR) on symptoms of depression in prostate cancer patients. In addition, they examined any effects that past or current treatment may have had on levels of psychological resilience in patients as a test of the “steeling” hypothesis of past adversity upon future resilience. Prostate cancer patients (N = 576) were recruited from cancer treatment centers in Queensland, Australia. All participants had prostate cancer limited to the primary site. Each participant completed the CD-RISC, the Patient Health Questionnaire–9 to assess symptoms of depression, and a general questionnaire regarding demographic variables and prior experience with cancer. Participants had the following characteristics: 69% were married or lived with a partner, 34% had surgery, 15% received radiotherapy, 39% received a combination of treatments, and the average time since diagnosis of prostate cancer was 19 months. As expected, there was a significant inverse correlation between resilience levels and depression scores in these prostate cancer patients (p < .001). In addition, some past and current cancer-­related treatments were significantly associated with resilience scores, suggesting that prior adverse experiences may have produced a steeling effect that persisted over time. The results of this study are interesting but certainly require replication with a larger sample of patients who are clearly defined by their course of treatment for prostate cancer. Ideally, participants should be recruited closer to the time of initial diagnosis of prostate cancer. If the steeling effect is confirmed in subsequent studies, it would open up possibilities for developing targeted interventions to increase resilience in prostate cancer patients soon after their initial diagnosis to improve their prognoses (Sharpley et al., 2021).

Resilience and Breast Cancer Outcomes Dooley, Slavich, Moreno, and Bower (2016) tested the hypothesis that prior exposure to moderate, yet manageable, levels of stress influence levels of resilience at diagnosis and during treatment for breast cancer. They recruited 122 breast cancer survivors and examined the relationship between lifetime stress exposure prior to breast cancer diagnosis and later psychological functioning during treatment. Participants had the following characteristics: mean age of 59 years, 79% were White, 64% were married or living

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with a partner, 78% were college graduates, and the mean time since breast cancer diagnosis was 2.2 years. Lifetime acute and chronic stress was assessed using the Stress and Adversity Inventory (STRAIN), a structured, online stress assessment questionnaire that includes 96 types of acute and chronic stressors (Toussaint, Shields, Dorn, & Slavich, 2016). Psychological functioning was assessed using the 7-item intrusions subscale of the Impact of Events Scale, which measures cancer-­related intrusive thoughts (Horowitz, Wilner, & Alvarez, 1979). Participants also completed questionnaires on positive and negative affect. Surprisingly, no measures of resilience were obtained from the participants. This study indicated that prior acute stress exposure was associated with cancer-­ related intrusive thoughts in a quadratic fashion (p = .016); participants reporting moderate acute stress levels experienced fewer intrusive thoughts than those with low or high acute stress levels. A similar relationship emerged between acute stress exposure and positive affect (p = .009), such that individuals with moderate exposure to acute stress reported the highest levels of positive affect. In contrast, exposure to acute and chronic stress levels were related to negative affect in a positive, linear fashion (ps < .05). These investigators concluded that moderate stress exposure was associated with indications of psychological resilience among breast cancer survivors; this conclusion suggested that prior stress exposure may facilitate adjustment to the many challenges associated with breast cancer diagnosis and treatment. Future studies should include assessments of psychological resilience in a more diverse group of study participants to confirm these suspected relationships between prior stress exposure and enhanced resilience closer to when the initial diagnosis of breast cancer occurs.

Irritable Bowel Syndrome Parker et al. (2021) extended earlier findings from their laboratory on resilience in patients with irritable bowel syndrome (IBS) by recruiting a nationally representative sample of participants from all 50 states to complete an online survey containing questionnaires relating to demographics, diagnosis of IBS or other gastrointestinal (GI) conditions, symptom severity, psychological symptoms, resilience using the CD-RISC score and the Brief Resilience Scale, and adverse early-life events. IBS was defined as having a physician diagnose IBS and/or meeting Rome criteria for diagnosing disorders of gut–brain interactions without comorbid GI disease. The chronic GI conditions group included those with inflammatory bowel disease, celiac disease, and/or microscopic colitis. All other participants were included in the general population group. Resilience scores were lower in participants diagnosed with IBS (N = 820) than in participants in the general population (N = 1,026; p < .001) and were associated with heightened IBS symptom severity (p < .05). Exposure to adverse early life events was associated with a diminished ability to bounce back from adversity in individuals with IBS and in participants from the general population (p < .001). Resilience scores were similar in participants with IBS compared to participants with other chronic GI conditions (N = 95) that involve similar symptoms. Levels of resilience were lower in IBS patients compared to participants from the general U.S. population; however, lower levels of resilience do not appear to be specific to IBS, as similar findings were obtained for individuals diagnosed with comparable GI conditions. Interventions designed to enhance resilience following an initial diagnosis



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may contribute to improved symptom management and reduced health care utilization in IBS patients (Parker et al., 2021).

Metabolic Syndrome A study by Lehrer, Steinhardt, Duboisa, and Laudenslager (2020) explored the moderating effects of psychological resilience on the association between perceived stress and the metabolic syndrome. Participants for this study included a diverse group of adults (73 White, 86 Hispanic, and 69 African American), of whom 68% were female, and the mean age was 45 years. Participants completed the Perceived Stress Scale and the Brief Resilience Scale and had measures taken of blood pressure, blood levels of glucose and lipids, and waist circumference. In addition, a 3-cm length of hair measured from the scalp was taken for later measurement of cortisol concentration as a cumulative measure of HPA axis activity. A sex- and ethnicity-­specific cardiometabolic risk score was computed for each participant. Psychological resilience moderated the association between perceived stress levels and hair cortisol concentration (p = .043), such that the association of perceived stress and hair cortisol concentration decreased as resilience scores increased. Resilience scores also moderated the indirect association between perceived stress levels and cardiometabolic risk scores via hair cortisol, such that higher levels of perceived stress were associated with higher cardiometabolic risk scores only for participants who had Brief Resilience Scale scores that were ≤ 3. Brief Resilience Scale scores were also associated with lower cardiometabolic risk scores (p = .014) independent of perceived stress levels and hair cortisol concentration. The Metabolic Syndrome is a well-­traveled gateway to Type II diabetes, cardiovascular disease, and stroke. These findings suggest that psychological resilience may serve as both a stress buffer and a direct determinant of cardiometabolic health. These results extend the research literature on psychological resilience and its impact on measures of retrospective HPA axis function using hair cortisol content and components of the Metabolic Syndrome in a diverse sample of participants (Lehrer et al., 2020).

Overall Health and Aging Ezeamama et al. (2016) explored the impact of indicators of resilience on patterns of health care utilization and self-­ratings of overall health by analyzing data from the Health and Retirement Survey. This survey follows a representative sample of adults in the United States who are over the age of 50, with data collections every 2 years and with a response rate greater than 80%. This study of resilience and health care utilization included a sample of 4,562 adults 50–70 years of age (58% female) who were surveyed in 2010. Data are presented as odds ratios (ORs) and 95% confidence intervals (CIs) for high versus low resilience in relation to health care utilization and self-­reported health improvements over a 2-year period. Health-­related variables included the following: hospitalization (yes or no), number of doctor visits (< 20 contacts vs. ≥ 20 contacts), and self-rated health status compared to 2 years ago (better vs. worse). Resilience indicators included cumulative lifetime adversity (0, 1–2, 3–4, or 5 or more adverse events), social support, global mastery, and domain-­specific mastery (in health, social life, and finances).

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The major findings of this study are summarized in Table 13.1. Over the 2-year period of the study, 22% of respondents were hospitalized at least once and 15% had ≥ 20 doctor visits, while 12% experienced improvements in self-­reported health. Surprisingly, high levels of social support did not impact measures of health care utilization or self-­reported health. For respondents with high versus low health mastery or high versus low financial mastery, the odds of hospitalization and having ≥ 20 physician visits over the previous 2 years decreased while the odds of improvements in self-­reported health increased for those with high versus low health mastery. In addition, the odds of hospitalization increased progressively with increases in cumulative lifetime adversity. Other factors that affected health care utilization included level of physical activity, body mass index, comorbid health conditions, and difficulty sleeping. In this sample of adults approaching or already in retirement, resilience measures as defined in this study predicted lower health care utilization and improvements in self-­reported health status. A major concern of this study was the lack of specificity in many of the resilience-­related measures, including social support. In addition, some of the measures were presented as categorical (i.e., yes or no responses), and this approach may have limited the ability to detect changes in the dependent variables. These investigators defined resilience as a dynamic, multidimensional, and developmental process as opposed to a stable personality trait (Bonnano, 2012). Viewing resilience as malleable, rather than fixed, has important implications for developing targeted interventions to enhance resilience in high-risk individuals. They argued for incorporating formal screening tools for traumatic and stressful life events during routine health care appointments (Ezeamama et al., 2016). TABLE 13.1.  Effects of Lifetime Stressors and Resilience Factors on Health Care Utilization and Self-Rated Health Status Based on Data from 50- to 70-Year-Olds Involved in the 2010 Health and Retirement Study Health care utilization Stress/resilience factors

≥ 20 doctor visits

Hospitalization

SRH status

1.00

1.00

1.00

Lifetime adversity 0 1–2

1.34 (1.04–1.73)

1.25 (1.01–1.55)

0.86 (0.70–1.07)

3–4

1.59 (1.21–2.10)

1.80 (1.42–2.68)

1.11 (0.86–1.43)

5+

2.18 (1.60–2.97)

2.42 (1.85–3.17)

1.34 (0.96–1.89)

0.89 (0.75–1.06)

0.99 (0.85–1.15)

1.29 (1.02–1.62)

Global mastery High versus low Domain-specific mastery High versus low health

0.53 (0.45–0.63)

0.75 (0.64–0.86)

1.49 (1.17–1.88)

High versus low social life

1.01 (0.87–1.20)

1.01 (0.87–1.17)

1.02 (0.82–1.27)

High versus low finances

0.83 (0.70–0.98)

0.84 (0.73–0.97)

1.10 (0.87–1.39)

Note. SRH, stress-related health. Data are presented as odds ratios (ORs) and 95% confidence intervals (CIs). Values in bold indicate significant confidence intervals (ps < .05). Data are from Ezeamama et al. (2015) and are used with permission of the publisher.



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Resilience to Systemic Racism Jackson, Jackson, and Jackson (2018) viewed resilience to systemic racism from a multigenerational perspective. They argued that legacy African Americans (those descended from enslaved ancestors) endured 250 years of slavery and 150 years of systemic racism and discrimination, a span of approximately 16 generations. Over this period of time, resilience has been bolstered in individuals through adaptations designed to buffer the effects of race-based stressors through the positive impact of families, local communities, and religious institutions. These resilient qualities have the potential to counterbalance in part the transgenerational transmission of trauma through epigenetic changes in DNA associated with 16 generations of deprivation.

STRESS‑TARGETED INTERVENTIONS TO ENHANCE RESILIENCE In Chapters 4–12, I included sections on stress-­targeted intervention to address specific mental disorders or medical diagnoses. In this section, I pivot 180 degrees and address the possibility of developing stress-­targeted approaches to enhance resilience levels. This exciting and relatively new area of research may hold great promise for the future.

Systematic Review and Meta‑Analysis of Interventions to Enhance Resilience Joyce et al. (2018) conducted a systematic review and meta-­analysis of training programs and interventions to promote resilience. Following an exhaustive literature review, 437 publications were retrieved, and 111 peer-­reviewed articles were examined carefully. Seventeen published studies met the inclusion criteria, and 11 randomized controlled trials were included in the meta-­analysis. Three types of interventions were examined, including cognitive-­behavioral therapy, mindfulness, and a combination of the two. A meta-­analysis found a moderate positive effect of resilience interventions (standardized mean difference = 0.44, 95% CI = 0.23–0.64), with further analyses indicating that the three types of interventions were equally effective. The studies included in this meta-­analysis quantified the benefits of resilience interventions as an increase in any of several questionnaire-­based measures of resilience, including the CD-RISC, the Brief Resilience Scale, and the 14-item Resilience Scale. Unfortunately, none of the studies included a real-world test of the effectiveness of the resilience training on one’s ability to bounce back from an adverse experience. The authors suggested that these intervention programs may be of great benefit to highrisk professions, including health care workers, first responders, and military personnel (Joyce et al., 2018).

Mindfulness and College Students The transition from high school to college, especially for those students who leave home and live on campus or in off-­campus housing, represents a significant and potentially stressful transition from adolescence to adulthood. Many colleges and universities are also attempting to meet the increasing demands of undergraduates for mental health

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services. Some research groups are interested in developing interventions to improve the resilience of college students during this stressful time. Galante et al. (2018) conducted a randomized controlled trial at the University of Cambridge (United Kingdom) of an 8-week mindfulness course specially designed for undergraduate or postgraduate students plus mental health services as usual (N = 309) or mental health services as usual as a control group (N = 307). Just over 60% of all participants were female, and just under 50% were between 18 and 21 years of age. Those in the control group were guaranteed spaces in the mindfulness course during the next academic year. Students who were currently experiencing significant levels of anxiety, distress, or depression or who had been diagnosed with a mental disorder were excluded from participating in the study. The primary outcome was self-­reported psychological distress during the 25-day examination period, as measured with the Clinical Outcomes in Routine Evaluation Outcome Measure (CORE–OM), with higher scores indicating more distress. Mindfulness instruction was delivered in eight weekly group-based sessions that lasted 75–90 minutes each. The mindfulness intervention reduced CORE-OM scores during the examination period compared to scores for the control group (p = .001). Further analyses revealed that 57% of controls had CORE-OM scores above an accepted clinical threshold compared to 37% of those in the mindfulness group. On average, six students (95% 4–10) needed to be offered the mindfulness course to prevent experiencing clinical levels of distress. No participants had adverse reactions related to self-harm, suicidality, or a tendency to harm others. These findings indicate that mindfulness training might be an effective component of a comprehensive strategy to provide mental health support services to undergraduate and postgraduate university students. Further comparative effectiveness research, with greater sample sizes and inclusion of controls for nonspecific effects related to weekly contact with course instructors and other participants, will be needed to define a range of additional, effective interventions to increase resilience to stress in university students (Galante et al., 2018).

Psychological Interventions to Foster Resilience in Health Care Professionals Kunzler et al. (2020) reviewed interventions to enhance resilience in health care professionals delivering direct medical care (e.g., nurses, physicians, hospital personnel) and allied health care staff with extensive patient contact (e.g., social workers, psychologists). The systematic review included 44 randomized control trials, with 36 trials conducted in high-­income countries. Thirty-­nine studies focused solely on health care professionals (6,892 participants), including both health care staff delivering direct medical care and allied health care staff. Four studies investigated mixed samples (1,000 participants) with health care professionals and participants working outside of the health care sector, and one study evaluated training for emergency personnel among volunteers (82 participants). Studies were conducted primarily in a hospital setting and included physicians, nurses, and other hospital personnel (37/44 studies). Participants mainly included women (68%) from young to middle adulthood (mean age range = 27–52 years). Most studies investigated group interventions (30 studies) with high training intensity that were delivered face-to-face (29 studies). Of these studies, 19 compared



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a resilience training group (e.g., mindfulness and cognitive-­behavioral therapy) compared to wait-list controls. At postintervention, evidence with a low degree of certainty indicated that, compared to controls, health care professionals receiving resilience training reported higher levels of resilience (standardized mean difference = 0.45, 95% CI = 0.25–0.65; 12 studies, 690 participants), lower levels of depression (standardized mean difference = –0.29, 95% CI = 0.50 to –0.09; 14 studies, 788 participants), and lower levels of stress or perceived stress (standardized mean difference = –0.61, 95% CI = –1.07 to –0.15; 17 studies, 997 participants). There was little or no evidence of any effect of resilience training on anxiety, well-being, or quality of life. Effect sizes were small except for resilience and stress reduction (moderate). Data on adverse effects were available for three studies, with none reporting any adverse effects occurring during the study (very-low-­certainty evidence). For health care professionals, there is little convincing evidence that resilience training results in higher levels of resilience, lower levels of depression, stress or stress perception, and higher levels of certain resilience factors following the intervention. There remains a compelling need for developing highly effective interventions to enhance the levels of resilience and the sense of well-being in health care professionals, especially given the demands that have been placed on frontline health care workers during the COVID-19 pandemic and beyond (Al Maqbali, Al Sinani, & Al Lenjawi, 2021; Kannampallil et al., 2020).

CONCLUSIONS As this relatively new area of research has matured, several features of resilience have come into clearer focus. They include the following:

• Resilience is much more than the absence of psychopathology; rather, it is a characteristic of individuals that is called into play from childhood through old age to adapt to challenging circumstances. • Resilient individuals are capable of adjusting to adverse life stressors and traumatic experiences without suffering from negative mental and physical health outcomes and by rapidly recovering from and moving past the stressful or traumatic event. • Resilient individuals tend to have secure attachments to others, have the capacity to experience positive emotions, and lead a purpose-­driven life. • Research into the genetic and neurobiological foundations of resilience may inform efforts to develop interventions to lessen the negative effects of exposure to severe stressors. Perhaps the greatest challenge facing research in resilience is the issue of measurement. What is the optimal approach to assessing resilience in individuals across the lifespan? At present, there are several widely used questionnaires to measure resilience; they are administered at one point in time and depend on individual responses to a series

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of items. Further research into reliable biomarkers of resilience might allow researchers to track levels of resilience in individuals prospectively as they confront a major stressful life event and recover from it. Looking ahead, it would be desirable to expand resilience research beyond the confines of mental health outcomes into other domains of medicine, including cancer, cardiovascular disease, diabetes, and gastrointestinal disorders. As we have seen in earlier chapters, life stressors affect the course of a variety of diseases, and so it would be helpful to know if resilient individuals have better outcomes following an initial medical diagnosis compared to susceptible individuals. Confirmation of this possibility could have important ramifications for developing targeted interventions to enhance resilience as a means of improving medical outcomes in this age of personalized medicine.

Glossary of Terms

Adaptive immunity: This type of immunity, which is found only in vertebrates, involves an immune response specific to the type of pathogen that is present in the body or the toxins that are produced by the invading bacterium or virus. Lymphocytes are involved in two major types of responses. In antibody responses, B cells secrete antibodies that are specific for a given antigen. When antibodies bind to an antigen, the invading organism is inactivated, and the virus or bacterium is then ingested by macrophages. In cell-­mediated immunity, T cells attack virus-­ infected cells. Adrenergic receptors: These receptors for norepinephrine and epinephrine are located on the outer cell membrane of other neurons or target cells. The two major classes of adrenergic receptors, alpha and beta, differ in their ability to bind norepinephrine and epinephrine as well as a variety of drugs. Adverse Childhood Experiences (ACE) Questionnaire: The ACE Questionnaire includes 10 questions that are answered with yes or no responses and that deal with emotional and physical abuse or neglect and household dysfunction. There is also an international version of the questionnaire. Allostasis: This term was first introduced by Sterling and Eyer (1988) to reflect stability through change of physiological systems. An organism meets perceived and anticipated demands related to stressors by altering internal physiological systems. Allostasis departs from the concept of homeostasis in that some physiological changes reflect anticipation of demands as opposed to merely responding once a disruption to a system has occurred. Sterling and Eyer illustrated this concept using pronounced changes in blood pressure measurements in humans over the course of a day. Allostatic load: This term, first proposed by McEwen and Stellar (1993), reflects the wear and tear on the body of being exposed to chronic intermittent stressors that exceed the individual’s ability to adapt and cope. Increases in allostatic load are associated with increased morbidity and mortality. 279

280

Glossary of Terms

Alpha-­a mylase: This enzyme, produced in the salivary glands, is found in saliva and breaks down starches into simpler sugars. It has been shown to be an accurate biomarker of the activity of the sympathetic nervous system following exposure of humans to laboratory stressors like the Trier Social Stress Test. Anti-­inflammatory cytokines: Just as pro-­inflammatory cytokines stimulate an immune response to a bacterial or viral challenge, anti-­inflammatory cytokines, including, IL-4, IL-6, and IL-10, serve as immunomodulators that limit the potential damage from sustained or excessive release of pro-­inflammatory cytokines. Appraisal: As originally described by Lazarus and Folkman (1984), stress appraisal refers to the process by which individuals evaluate a stressor and determine if it is within or beyond their capacity to cope and endure. B cell: This type of lymphocyte is produced in bone marrow and produce antibodies in response to a bacterial or viral infection. B cells are activated when they bind to an antigen associated with an invading microorganism. After an infection has been cleared, some B cells retain a memory of the foreign antigen and remain in the body. These memory B cells respond to a subsequent infection with a stronger and more rapid production of antibodies to ward off the infection. BMI: Body mass index is calculated by dividing body weight in kilograms (kg) by the square of height in meters (m 2). This simple measure is often employed in clinical studies to categorize individuals as underweight, normal weight, overweight, or obese. BMI does have limitations as a predictor of health status. BPS model: The biopsychosocial model, originally proposed by Engel (1977), posited that biological, psychological, and social factors contribute to an individual’s overall health status and disease risk. This model was developed in reaction to what Engel viewed at the time as an excessive reliance on the biomedical model of disease. Brief Resilience Scale: This scale includes six items, each of which is rated on a 1–5 scale. The total score is divided by the number of items to yield an average resilience score. Low resilience = scores of 1.0–2.99, normal resilience = 3.0–4.3, and high resilience = 4.31–5.0. CD4+ T helper cells: These cells play an important role in the adaptive immune system by releasing cytokines that activate other immune cells such as macrophages and dendritic cells that are involved in clearing the body of infections. Human immunodeficiency virus (HIV) targets CD4+ T helper cells and may reduce their numbers in blood to critically low levels with a resulting increase in opportunistic viral and bacterial infections. When the CD4+ T helper cell count falls below 200 cells per milliliter of blood, an individual has progressed from HIV+ to a diagnosis of AIDS. Connor–­Davidson Resilience Scale: This scale was originally developed by Connor and Davidson (2003) to measure the ability to thrive in the face of adversity. The original scale included 25 items that were rated on a 0–4 scale. A subsequent version reduced the number of items to 10 (Campbell-­Sills & Stein, 2007), and scores on the shorter version were highly correlated with the original longer version. Both versions have achieved high reliability and validity with a variety of populations. Conserved transcriptional response to adversity: This response was originally proposed by Slavich and Irwin (2014), who noted that repeated exposure to social adversity results in an



Glossary of Terms 281

upregulation of pro-­inflammatory innate immune response genes and a downregulation of antiviral innate immune response genes. These transcriptional effects are tied to sympathetic–­ adrenal medullary and cortisol responses to repeated stressors. Coping with stress: When confronted with a stressor, an individual appraises the stressor as either threatening or nonthreatening, and then determines if he or she has the resources to respond to or cope with the challenge effectively. Lazarus and Folkman (1984) indicated that coping processes reflect what an individual thinks or actions that are taken within a specific context and that change over time as the encounter with a given stressor unfolds. They distinguished between problem-­focused coping, in which efforts are made to manage or alter the stressor, and emotion-­ focused coping, in which attempts are made to regulate emotional responses to the stressor. CRP: C-­reactive protein (CRP) is synthesized in the liver and released into blood in response to increases in IL-6. It is used clinically and in research studies as a biomarker of inflammation. CTQ: The Childhood Trauma Questionnaire (CTQ) is a retrospective measure of trauma and abuse that occurred in childhood. It includes five subscales: emotional abuse, physical abuse, sexual abuse, emotional neglect, and physical neglect. Cytokines: Cytokines are a broad family of peptide molecules that act through receptors on cell surfaces to provide a means of communication between cells of the immune system. Cytokines include the interleukins, chemokines, interferons, and tumor necrosis factors. These signaling molecules play critical roles in responses to infection and can be pro-­inflammatory and anti-­ inflammatory in their actions. DALYs: A disability-­adjusted life year (DALY) is a measure of the overall burden of a disease(s) and is expressed as the cumulative number of years lost due to ill health, disability, or premature death. The World Health Organization has used this measure since the 1990s to reflect the overall health of member countries. Dendritic cell: These cells provide a link between the innate and adaptive immune systems. Dendritic cells are found in tissues of the body and enhance an immune response by processing and then presenting antigens on their outer cell membrane that activate naïve T lymphocytes. DHEA-S: Dehydroepiandrosterone sulfate (DHEA-S) is a weak male sex hormone, or androgen, that is produced in the adrenal glands of males and females. Levels of DHEA-S in blood provide a measure of overall activity of the adrenal cortex. DSM-5: The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, was first published by the American Psychiatric Association in 2013, and a text revision (TR) appeared in 2022. It serves as the standard system of classification of mental disorders for health professionals in the United States. ECG: The electrocardiogram (ECG) is a measure of the continuous changes in the electric activity of the heart that is captured using electrodes placed on the skin. Heart rate variability is a measure derived from the ECG (see also under HRV). Effort–­Reward Imbalance Questionnaire: Effort–­reward imbalance (ERI) was originally proposed by Siegrist (1996) to reflect an imbalance between work-­related effort and rewards. When work-­related effort exceeds rewards, levels of stress and adverse health outcomes increase. In addition, overcommitment at work interacts with ERI and also increases the risk of adverse

282

Glossary of Terms

health outcomes. The ERI Questionnaire is a self-­reported measure that includes a long form (22 items) and a short form (16 items); each item is rated using a 4-point Likert Scale. English Longitudinal Study of Ageing (ELSA): ELSA is a population-­based sample of people living in communities in England who were ≥ 50 years old when baseline measures were obtained in 2002–2003. Face-to-face interviews were then conducted every other year. ENIGMA consortium: The Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Consortium includes 50 working groups with more than 1,400 researchers in more than 40 countries who are interested in analyzing brain-­imaging and genomic data to develop a clearer understanding of brain structure, function, and disease processes. Epinephrine: Epinephrine is the primary hormone of the adrenal medulla and was first connected to the fight-or-­f light response by Cannon (1914). Levels of epinephrine in plasma provide a measure of adrenal medullary secretory activity. E-Risk Study: The Environmental Risk Longitudinal Twin (E-RISK) Study probes how environmental and genetic factors contribute to the development of behavior, health, and mental health problems from childhood through adulthood. The study started in 1998 by recruiting a nationally representative 2-year birth cohort of 2,232 same-sex twins born in England and Wales between 1994 and 1995. Assessments have occurred when the individuals were 5, 7, 10, 12, and 18 years old. Blood samples have been collected for genomic analyses. Participant retention has been greater than 90% through age 18. Everyday Discrimination Scale (EDS): This scale was developed by Williams et al. (1997) to measure how frequently individuals experience discrimination in their daily lives. The original scale had nine items, and a tenth was added later. Fight-or-­f light: This term was coined by Walter B. Cannon in 1914 to capture the pattern of physiological responses to a significant life-­threatening stressor. Cannon emphasized the importance of the sympathetic nervous system and the adrenal medulla in redistributing blood flow to the skeletal muscles and increasing levels of glucose in blood to meet the emergency. He placed great emphasis on the emergency function of the adrenal medulla through release of epinephrine in the fight-or-­f light response. GHQ: The General Health Questionnaire (GHQ) provides a self-­reported assessment for detection of mental disorders. The GHQ includes versions with 12 items (GHQ-12) and 28 items (GHQ-28), with the shorter version being preferred as a screening device, particularly in primary care settings. Versions with 30 and 60 items have also been employed. Each item is typically rated using a Likert Scale of 0–3. GWAS: Genome-­wide association studies (GWAS) represent an experimental approach to examining the association between genetic variants and a particular trait of interest, including mental disorders and chronic diseases. These studies typically involve quantifying the frequency of single-­nucleotide polymorphisms (SNPs; see below) in the DNA of individuals with a particular disease or disorder and comparing those results with a group of otherwise healthy controls (the case–­control approach). To achieve appropriate levels of statistical power, sample sizes have ranged from tens of thousands to hundreds of thousands of individuals. The level of statistical significance for comparison of a given SNP between two groups is usually set at 5 × 10 -8 to account for the number of pairwise comparisons that occur in a whole genome study.



Glossary of Terms 283

HbA1c: The hemoglobin A1c blood test provides a measure of one’s average levels of blood glucose over the past 2–3 months. Hemoglobin is the oxygen-­binding protein in red blood cells, and as glucose builds up in the blood, it binds to the hemoglobin protein (glycated hemoglobin). Red blood cells have a lifespan of approximately 3 months. For individuals without diabetes, a normal HbA1c level is between 4.0 and 5.6%. For prediabetics, the levels are 5.7–6.4%, and for diabetics the levels are greater than 6.5%. HDL: High-­density lipoprotein (HDL) absorbs cholesterol and returns it to the liver where it is flushed from the body. This is the “good cholesterol” in that higher levels in blood are associated with reductions in the risk for heart disease and strokes. Levels greater than 60 mg/dL are considered high, and levels below 40 mg/dL are considered low. There are sex differences in recommended levels for adults. Health and Retirement Study: Based at the University of Michigan, the Health and Retirement Study is a longitudinal panel study that surveys a nationally representative sample of approximately 20,000 people every two years using questionnaires and in-depth interviews to address issues relating to aging in America. Blood samples have been collected from some participants to allow genetic measures to be included in the database. Homeostasis: Expanding on the work of the French physiologist, Claude Bernard, in the 19th century, Walter B. Cannon introduce the term homeostasis in the early 20th century to reflect the tendency for critical internal variables (e.g., body temperature, blood pH) to be maintained within limited ranges essential for life. Cannon emphasized the important role of the brain in maintaining homeostatic balance. HPA axis: The hypothalamic–­pituitary–­adrenocortical (HPA) axis is a key stress-­responsive hormonal system involved in the body’s response to acute and repeated stressors. In most studies, the activity of the HPA axis is reflected in measures of plasma levels of ACTH and/or cortisol. In some studies, cortisol has been measured in saliva samples. HRV: Heart rate variability (HRV) is a measure of the beat-to-beat variations in heart rate in milliseconds, usually derived from the electrocardiogram. Factors affecting HRV include sympathetic and parasympathetic nervous system inputs to the heart. Decreased activity of the parasympathetic nervous system or increased activity of the sympathetic nervous system leads to decreases in HRV. High-­frequency activity has been associated with parasympathetic input to the heart, whereas low-­frequency activity has been linked to sympathetic input to the heart. Both of these findings have been called into question. ICD-11: The 11th revision of the International Classification of Diseases (ICD-11) was published by the World Health Organization in 2022. ICD-11 serves as the global standard for notation of diseases and causes of death and other issues related to health care. It includes coding for mental disorders. There are more than 85,000 entities contained within 28 chapters. IL-1b: This interleukin is produced by activated macrophages and plays an important role in inflammatory processes as well as in inducing increases in body temperature. IL-6: This interleukin has both pro- and anti-­inflammatory properties. It is secreted by macrophages in response to microbial antigens, and it also supports the growth of antibody-­producing B cells. In addition, it can serve as an anti-­inflammatory cytokine by limiting the activation of macrophages.

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Glossary of Terms

IMVEST: The Immersive Multimodal Virtual Environment Stress Test (IMVEST) was developed by Rodrigues et al. (2021) using a multimodal virtual environment stress test in which participants are exposed to mental math calculations, environmental challenges, and intense visual and auditory stimuli. A special feature of IMVEST is that the degree of difficulty of mental math can be adjusted based on the performance of an individual participant. In addition, control participants can be exposed to a similar but much less stressful experience. Finally, IMVEST affords an opportunity to deploy similar stressful experiences for participants in multi-­center collaborative experiments. Individual-­Participant-­Data Meta-­A nalysis in Working Populations (IDP-Work) Consortium: Established in 2008 and involving more than 60 researchers, the IDP-Work Consortium uses predefined meta-­analyses of individual participant data from multiple cohort studies across a range of countries, mostly in Europe. The overall goal of the consortium is to provide reliable estimates of the associations between work-­related psychosocial stressors and the risk of chronic diseases, disability, and mortality. Inflammation: Acute inflammation is an adaptive response of the immune system to attack invading bacteria and viruses and to remove dying or damaged cells. In contrast, chronic inflammation is a maladaptive process and is associated with a host of chronic diseases, including heart disease, cancer, Alzheimer’s disease, and type 2 diabetes. Changes in lifestyle can reduce chronic levels of inflammation, including reducing body weight, committing to an exercise routine, reducing alcohol intake, and eliminating smoking. Chronic exposure to stressors can also upregulate chronic inflammatory processes. Innate immunity: This is an evolutionarily older form of immunity in which emphasis is placed on a system of rapid responses and elimination of invading pathogens at the expense of specificity of the immune response. INTERHEART: This international study used a standardized case–­control design to determine underlying causes of acute myocardial infarction by enrolling participants in 52 countries on six continents. Sample sizes included 15,152 individuals who suffered heart attacks, and 14,820 healthy controls were matched to the patients. The primary finding was that nine factors accounted for 90% of myocardial infarctions in men and 94% in women. Included among those factors was exposure to psychosocial stressors. Jackson Heart Study: This study is based in the Jackson metropolitan area of Mississippi and examines the causes of cardiovascular disease in African Americans, with an emphasis on gaining knowledge that will contribute to a reduction in health disparities and result in a strategy to prevent this group of diseases in the future. Male and female participants (N = 5,302) were recruited from 2000–2004 and ranged in age from 35 to 84 years of age, with varying levels of education and income. Job Content Questionnaire: This 49-item questionnaire is designed to assess psychological demands, decision latitude, social support, physical demands, and job insecurity as a means of quantifying psychosocial stress levels associated with the work environment. LDL: Levels of low-­density lipoprotein (LDL) are a major risk factor for heart attacks and strokes. This is the “bad cholesterol,” and a major source of LDLs is diet that is high in saturated fats and cholesterol and low in healthy proteins and fiber. Psychosocial stressors can also result in elevations in LDL. Circulating LDL levels below 100 mg/dL are considered optimal, while levels greater than 160 mg/dL are considered high and may require a cholesterol-­lowering drug (statin).



Glossary of Terms 285

Longitudinal Resilience Assessment (LORA) Study: This study, based in Germany, includes participants (N = 1,191, ages 18–50 years at study entry) who are deep-­phenotyped at study entry and followed for a minimum of 3 years. Participants are tested in the laboratory at 18-month intervals and monitored every 3 months for mental health status as well as exposures to stressors. The goals of this study are to examine individual differences in resilience to life stressors, to operationalize resilience using a dimensional approach, and to explore mechanisms of resilience to everyday life stressors (Chmitorz et al., 2021). Major Experiences of Discrimination Scale (MEDS): As originally described by Williams et al. (1997), the MEDS includes yes or no answers to three questions: (1) Do you think you have ever been unfairly fired or denied promotion? (2) For unfair reasons, do you think you have ever not been hired for a job? (3) Do you think you have ever been unfairly stopped, searched, questioned, physically threatened, or abused by the police? MAST: The Maastricht Acute Stress Test (MAST) was designed to be a simple, quick, and noninvasive procedure for activating peripheral stress effector systems such as the HPA axis and the sympathetic nervous system. The MAST combines features of the Trier Social Stress Test and the Cold Pressor Test. Participants are instructed to immerse their nondominant hand in cold water (2oC) followed by mental arithmetic (serial subtraction of 17 from 2,043), which is socially evaluated. They do not have information on the length of each trial or the total number of trials. Each participant completes five cold immersion trials interspersed with four mental arithmetic trials that vary from 45 to 90 seconds. The entire procedure takes 10 minutes, and details are provided in Smeets et al. (2012). Meta-­a nalysis: This statistical technique is employed to aggregate the results of published reports identified through a systematic review of the literature that meet specific inclusion criteria such that sample sizes and statistical power are increased dramatically. Attempts are made to reduce as much as possible the risk of bias in summary estimates. Data from the selected studies may be individual participant data or aggregate data, often reported in the form of odds ratios or relative risks. Metabolic syndrome: Metabolic syndrome is a cluster of conditions that increase one’s risk for cardiovascular disease and type 2 diabetes. The cluster includes elevations in blood pressure and blood glucose, excess body fat stored around the waist, and elevated cholesterol and triglycerides in blood. The incidence of metabolic syndrome is increasing at an alarming rate both in the United States and across the globe. Lifestyle changes such as eating a healthy diet, getting regular exercise, reducing body weight, and refraining from smoking can improve every component of the syndrome. Midlife in the United States (MIDUS) Study: The MIDUS study began in 1995 with a total of 7,108 participants who were 25–74 years of age. This study was intended to examine the role of psychological, social, and biological factors in age-­related variations in health and well-being as individuals age. A follow-­up wave of data collection began in 2004 and included 4,963 of the original participants. Data on daily stressors, chronic stressors, and major life events were collected from all respondents. MMST: The Mannheim Multicomponent Stress Test (MMST) simultaneously combines cognitive (mental arithmetic), emotional (affective pictures), acoustic (white noise), and motivational stressors (loss of money) in a single 5-minute test session. This stressor protocol does not include a socially evaluated component and does not elicit robust physiological response comparable to the TSST. Details of the testing protocol can be found in Reinhardt et al. (2012).

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National Longitudinal Survey of Youth: This survey is sponsored by the Bureau of Labor Statistics of the U.S. Department of Labor and began in 1979 with 12,686 men and women born between 1957 and 1964 (ages 14–22 in 1979). Participants were interviewed each year from 1979 to 1994 and biennially thereafter. The 2014 interview (Round 26) was conducted with 7,071 men and women 49–58 years of age. Data have been collected on experiences with the labor market and other significant life events. Neighborhood Disorder Scale: This scale was developed by Ross and Mirowsky (1999) to define the concept of disorder, and measure and empirically assess the relationships between perceptions of crime and disorder, order and disorder, and physical and social disorder. The Neighborhood Disorder Scale included 15 items and had high reliability and external validity, and it displayed interesting distinctions and overlaps between physical and social disorder. It also revealed that order and disorder are two ends of a single continuum. NHANES: The National Health and Nutrition Examination Survey (NHANES) is a program of research to assess the health and nutritional status of adults and children in the United States. It began in the early 1960s and since then has been conducted as a series of surveys focusing on different population groups or health topics. In 1999, the survey became a continuous program that has examined a variety of variables related to health and nutrition measurements. The survey draws on a nationally representative sample of about 5,000 people each year. Participants are located in counties across the country, 15 of which are visited each year. There is oversampling of individuals greater than 60 years old, African Americans, and Hispanics. Health interviews are conducted in participants’ homes, while health measurements are performed in specially designed and equipped mobile centers. Findings from the surveys address the prevalence of major diseases and risk factors for diseases, including exposure to stressors. Norepinephrine: This molecule is the primary neurotransmitter of postganglionic sympathetic nerve terminals in the periphery and norepinephrine-­containing neurons in the brain. Norepinephrine is also present in and released from the adrenal medulla during stressful stimulation. Norepinephrine exerts its effects on target cells in the periphery and brain by binding to a- and b-adrenergic receptors. NPY: Neuropeptide Y (NPY) is 36-amino-acid peptide that is co-­localized with norepinephrine in postganglionic sympathetic nerve terminals and in noradrenergic nerve terminals in the brain. It is released in the periphery following sustained stress exposure and has a potent vasoconstrictor effect. NPY has been measured in blood and saliva as a biomarker of stress responses. Nurses’ Health Study: The Nurses’ Health Study is a cohort study that started in 1976 with the recruitment of 121,700 female registered nurses who were at that time 30–55 years of age. The cohort has been followed every 2 years, and response rates to mailed questionnaires have been > 90%. This is a valuable study group for exploring the effects of a variety of factors, including levels of stress, on health and well-being. PGC: Initiated in 2007, the Psychiatric Genomics Consortium (PGC) now includes 800+ investigators from 36 countries who are interested in the genetic basis of psychiatric disorders. By combining datasets from multiple laboratories, the PGC is able to conduct GWAS that have combined sample sizes providing enhanced statistical power to detect small effect sizes of many SNPs for a given psychiatric diagnosis. Foundational principles of the PGC include the benefits of aggregating data across laboratories and adopting an open science approach by making all genome-­wide summary statistics available for widespread use.



Glossary of Terms 287

PSS: The Perceived Stress Scale (PSS) was originally developed by Cohen et al. (1983) and attempts to capture one’s perceived levels of stress over the past month. The original version of the PSS included 14 items, while a shorter version has been developed with only 10 items. The PSS is still used frequently to assess individual perceptions of stress, even though it was developed more than four decades ago. Reasons for Geographic and Racial Differences in Stroke (REGARDS) study: This is a population-­ based, prospective, longitudinal cohort study of participants with the following characteristics: > 45 years of age, 45% male and 55% female, 41% Black and 59% White, with 55% of the cohort from the southeastern United States and 45% from the remainder of the continental United States. The focus of the study is on the etiology of strokes. SNPs: Single-­nucleotide polymorphisms (SNPs) represent the most common type of genetic variation between individuals. Each SNP represents a change in a single nucleotide of DNA. For example, a SNP may replace the nucleotide guanine (G) with the nucleotide adenine (A) in a particular section of the DNA molecule. SNPs occur approximately once in every 1,000 nucleotides, yielding 4–5 million SNPs in one person’s genome. To be classified as a SNP, a single-­nucleotide variant should occur in at least 1% of the population. To date, more than 600 million SNPs have been identified. SNPs are often localized within nucleotide sequences between genes and can be helpful in identifying genes that play a role in specific diseases. GWAS examine the association between various SNPs and complex diseases such as heart disease, cancer, and major depressive disorder. Social Network Index: This index provides a measure of participation in 12 types of social relationships. These include relationships with family members, neighbors and close friends, colleagues from work or volunteer activities, and members of nonreligious or religious groups. One point is given for each type of relationship (possible score of 12) in which respondents speak in person or on the telephone to members of each category at least once every two weeks. Social safety theory: This theory, elaborated by Slavich (2020), places great emphasis on the importance of initiating and maintaining friendly social bonds for humans. Psychosocial stressors put these friendly social bonds at risk and result in increases in morbidity and mortality. Central to the maintenance of these friendly social bonds are brain networks and the immune system. Slavich argues that anticipatory neural-­immune responses to social threat have been conserved over evolutionary time. However, when these neural-­immune response patterns are sustained over significant periods of time, there is an increased risk of inflammation-­related diseases. Socially Evaluated Cold Pressor Test: The Socially Evaluated Cold Pressor Test was developed to elicit a robust HPA axis stress response in laboratory studies (Schwabe et al., 2008). The social evaluation component may involve giving participants unreasonable expectations about how long the average person can keep a hand submerged in ice water, or it may involve videotaping the participant to determine how effective he or she manages the stressor. STARRS: The Army Study to Assess Risk and Resilience in Servicemembers (STARRS) is a broad-based series of studies to inform the development of strategies to reduce suicides by Army servicemembers and add to the knowledge base on risk and resilience factors for suicidal behavior and related psychiatric disorders. Stress and Adversity Inventory: The Stress and Adversity Inventory (STRAIN) was designed to assess an individual’s cumulative exposure to major stressors over the lifespan. These stressors

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included major life events and chronic challenges, such as those occurring during childhood and adolescence. For each stressor that is checked, individuals are asked to rate the severity, frequency, timing, and duration. The questionnaire can be taken online, or it can be administered by an interviewer in a laboratory or clinic. Stress-­in-­Context Questionnaire: The Stress-­in-­Context Questionnaire assesses stress perceptions in specific contexts, such as at home, in one’s neighborhood, in social relationships, at work, and during childhood. Weighting stress perceptions in each of these contexts serves as reminders of the many potential sources of perceived stress from the environment, resulting in a more accurate summative measure. The Stress-­in-­Context Questionnaire may also be more relevant for individuals from low-SES backgrounds or for those exposed to chronic adversity. This questionnaire is highly correlated with the Perceived Stress Scale. Systematic review of the literature: A systematic review of the literature represents an attempt by a team of researchers to address a specific and carefully defined research question. Explicit criteria are formulated in advance of a literature search to provide a guide as to which studies are included and which are excluded. This approach is intended to reduce bias in reporting results. Teaming with a research librarian is often helpful in refining a research strategy and in selecting databases to examine. Systematic reviews may serve as the basis for a meta-­analysis or may be reported independently. Tend-and-­befriend: Originally introduced by Taylor et al. (2000), this theory is the counter to Cannon’s fight-or-­f light response. When females are subjected to stressful stimulation, they focus on providing care for their young, affiliate with social groups to reduce their vulnerability to stressors, and engage in social networks, especially female social networks, to promote the exchange of resources and the sharing of responsibilities. TNF-a: Tumor necrosis factor alpha (TNF-a) is a pro-­inflammatory cytokine produced by macrophages and monocytes during acute inflammatory responses. When macrophages detect an infection, they release TNF-a to signal other immune cells of the infection. This cytokine is also responsible for a varied set of responses within cells, including necrosis and apoptosis (cell death). It also inhibits tumor formation and replication of viruses. TSST: The Trier Social Stress Test (TSST) was developed at the University of Trier in Germany (Kirschbaum et al., 1993) to produce robust and reliable stress responses in a laboratory setting. The original procedure involved two stressors, a socially evaluated public speaking task in front of three evaluators and a mental arithmetic task. There was also the stress associated with preparing the speech. The original version of the TSST has been employed in many studies. There have been modifications to accommodate groups of participants and children, and there is an online version that has worked effectively. 23andMe: 23andMe, Inc., is a publicly held genomics and biotechnology company (Nasdaq: ME) based in Sunnyvale, California, that is best known for its direct-­to-­consumer saliva test for genetic testing for SNPs. With the consent of individual customers, their results can be included in aggregated data used by university-­based and government scientists in studies of inherited disorders. Company scientists also use these aggregated data to explore genetic links with various inherited disorders to identify drug targets for treatment as part of the company’s overall business strategy. UCLA Life Stress Interview: The UCLA Life Stress Interview was developed by Hammen and coworkers to assess chronic, ongoing stressful conditions in major role domains, as well as



Glossary of Terms 289

responses to episodic stressful life events (Hammen et al., 1989). This instrument provides a more fine-­grained analysis of stressors than simple checklists of items, as well as a means of determining objective levels of stressfulness independent of the respondent’s appraisal of or emotional responses to a given stressor. One concern about this instrument is the time commitment required to conduct the interview (usually 30–45 minutes). UCLA Loneliness Scale, Version 3: This is a 20-item scale to measure an individual’s subjective feelings of loneliness and social isolation. Each item is rated on a scale of 1 (never) to 4 (often) (Russell, 1996). Vietnam Era Twin Registry: The Vietnam Era Twin Registry includes 4,774 male–male twin pairs born between 1939 and 1957, both of whom served in the United States military during the Vietnam War. The registry was originally developed to provide the best control group for Vietnam-­exposed servicemen for purposes of studying the long-term health consequences of service in Vietnam. It also includes information on deaths and hospitalizations in the Department of Veterans Affairs hospital system. This registry has also been employed in studies of the genetics of PTSD.

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Index

Note. f or t after a page number indicates a figure or a table. Acamprosate, 85 Acceptance and commitment therapy (ACT) for IBD, 188–189 for ovarian cancer, 214 Acetylcholine Loewi’s research and, 5 metabolism of, 36 ACTH measurement of, 30 role of, 28 Adaptive immunity, characteristics of, 279 Adolescent Skills Training (AST), for preventing depression, 127–128 Adolescents, MDD risk in, 126–127 Adrenal cortex, stress response and, 22–23 Adrenal medulla, activity of, 32–33 Adrenergic antagonists, for AUD treatment, 86 Adrenergic receptors activity of, 33–34, 34t characteristics of, 279 Adrenocorticotropic hormone (ACTH); see ACTH Adverse Childhood Experiences (ACE) Questionnaire, characteristics of, 279 Adverse Childhood Experiences Scale, 63 Adversity, conserved transcriptional response to, characteristics of, 280 Affective style, immune response and, 229 African Americans; see also Systemic racism allostatic load scores in, 241–242 COVID and non-COVID deaths in, 255–256, 256t life expectancy of, 254–255

and maternal and infant impacts of allostatic load, 243–247 mortality from racial inequities versus COVID-19, 256–257 violence and mental health of, 253–254 Aging, resilience and, 273–274, 274t Alarmins, 39 Alcohol abuse, stages of, 75 Alcohol dependence, 76 brain imaging and, 81–82 sex differences and, 82 Alcohol use high-risk, defined, 70 underage, 71 at work, 82–83 Alcohol use disorder (AUD), 68–87 diagnosis of, 71–73, 72t FDA-approved drugs for, 85 gender, class and, 69 genetics of, 73–75 global aspects of, 68–69, 70t health impacts of, 68–69 high-risk for, 70, 74–75 mortality rate and, 69 stress and, 75–84, 76f craving and, 80–81 drinking initiation and, 79–80 drinking maintenance and, 81–83 in early life, 77–78, 77t relapse and, 83–84 stress-targeted interventions for, 84–86 U.S. impacts of, 69–71

329

330 Alcohol Use Disorder Identification Test— Consumption (AUDIT-C), 73–75 Aldosterone, 29 Allostasis characteristics of, 279 defined, 16–17 Allostatic load of African American mothers and babies, 243–247 of African Americans mediators of, 241–242 versus Whites, 240–241, 241t alcohol abuse and, 75 characteristics of, 279 chronic stress and, 26 in Mexican immigrants, 243 quantifying, 17–18, 17f, 18f, 19t racial inequities and, 239–243 T2DM and, 160–161 work-related stressors and, 141 Alpha-amylase characteristics of, 280 salivary, 35–36 Anger, as heart attack trigger, 133 Antibody response daily stressors and, 229–230 stress and, 228–229 Anti-inflammatory cytokines, characteristics of, 280 Army recruits, GWAS and, 267–268 Army Study to Assess Risk and Resilience in Servicemembers (STARRS), 267 Arylhydrocarbon receptor repressor gene (AHRR), PTSD and, 98 Attitude, reorientation of, 11 Autonomic nervous system, 31–36 subdivisions of, 31 parasympathetic nervous system, 36–37 sympathetic nervous system, 31–32, 32t

B B cells, characteristics of, 280 Barker, David J. P., 98 Behavioral measures, 48–67 of early life stressors, 60–62, 62–63 electronic health records, 57–58, 58t laboratory paradigms and, 49–53 major life events and, 63–64 and psychological measures of stress appraisal, 53–57 quantitative analyses of health risks and, 67 smartphone applications and, 64–66 social capital and, 60–62 social isolation and loneliness, 58–59 work-related stressors and, 60 Berle index, 11

Index Bernard, Claude, 3–4, 5 Beta-blockers, stress cardiomyopathy treatment and, 132 Binge drinking, 71 Biological markers, 28–42 autonomic nervous system, 31–36 (see also Autonomic nervous system) epigenetic, 44–47 gene expression biomarkers, 43–44 HPA axis, 28–30, 29f immune system, 37–40 parasympathetic nervous system, 36–37 pro-inflammatory, 40–42 Biological measures, 27–47 biological markers, 28–42 categories of, 27 gene, 42–43 gene expression biomarkers, 43–44 point-of-use sensors, 42–43 questions about, 27–28 Biomarkers epigenetic, 44–47 gene expression, 43–44 pro-inflammatory, 40–42 of resilience, 263–264 Biopsychosocial model characteristics of, 280 of disease, 13, 15–16, 16f Birthweights, African American, 244, 244t Blood glucose regulation diabetes and, 155–158 factors influencing, 156–157, 157t ups and downs of, 157–158 Blood pressure; see also Hypertension baseline measurements of, 148–1150 measurement and guidelines, 147–148, 148t psychosocial stressors and, 150–152 Blumenthal, James A., 146 Body mass index (BMI), characteristics of, 280 Bourdieu, Pierre, 60 Bowditch, Henry P., 4 Bowling Alone: The Collapse and Revival of American Community, 61 Brain health, racism and, 252–254 Brain imaging, alcohol dependence and, 81–82 Brain-imaging studies, of PTSD, 104–105 Breast cancer and 5-year changes in depression, immune function, 210–211 metastatic, depression and, 209–210 pro-inflammatory cytokines and, depression and, 210 psychosocial stressors and, 199–200 resilience and, 271–272 Brief Resilience Scale, 262–263 characteristics of, 280 Broken heart syndrome, 132 Buxtun, Peter, 238



Index 331 C Cancer depression impacts on, 208–211 and global disease burden, 196–197, 197t resilience and, 271–272 stress and, cardiovascular disease and, 137–138, 137t Cancer and psychosocial stress, 195–215 breast cancer and, 199–200 historical connections between, 195–196, 196t impacts of social support, 201–204 on chronic lymphocytic leukemia, 202–203 meta-analysis of, 201 on ovarian cancer outcomes, 201–204 on prostate cancer outcomes, 204 in Japan, 198–199, 199t metastasis and, 204–208, 205f by activation of dormant cells, 207–208 beta-blocker impacts on, 205–206 social well-being impacts on, 206–207 and moderation of depressive symptoms, 211 in ovarian cancer, 200 in PTSD, 198 stress-targeted interventions for, 212–215 CBT stress management, 213–214 and enhancement of breast cancer survival, 212–213 Internet-based for ovarian cancer, 214 in metastatic breast cancer, 212 and work stress in Europe, 198 Cannon, Walter B., 4–6, 8, 9 Cardiomyopathy, stress, cardiovascular disease and, 132 Cardiovascular disease; see also Heart attack; Hypertension beliefs about stress and, 144 and childhood abuse and neglect, 131 depression comorbidity and, 138–141 disability-adjusted life years (DALYs) and, 130 financial stress and, 250–251 and protective effects of social networks, 145 resilience resources and, 269–270 and stress activated by brain circuits, 144 stress and, 130–153 stress cardiomyopathy and, 132 and stress of cancer diagnosis, 137–138, 137t stress-related disorders and, 136 systemic racism and, 250–252 work-related stressors and, 141–143 Cardiovascular/diabetes related mortality, in African American versus White males, 241, 241t Catecholamines, 31 urinary, 35 CD4+ helper cells, characteristics of, 280 Centers for Disease Control and Prevention (CDC), illness focus of, 10 Cerebral cortex, changes in PTSD, 105

Chauvin, Derek, 236 Childhood abuse/neglect, cardiovascular disease and, 131 Childhood Trauma Questionnaire (CTQ), 62–63 AUD and, 78 characteristics of, 281 Cholinergic receptors, functions of, 36 Chronic disease, depression and, 125–126 Chronic lymphocytic leukemia, and impacts of social support, 202–203 Clark, Taliaferro, 237–238 Cognitive appraisal, research on, 20–21 Cognitive processing therapy, for PTSD, 106 Cognitive-behavioral relaxation training, for HIV, 225–226 Cognitive-behavioral stress management (CBSM) for HIV, 225 for ovarian cancer, 214 Cognitive-behavioral therapy (CBT), AUD-specific, 85 Cohen, Sheldon, 220 Coleman, James S., 60 College students, fostering resilience in, 275–276 Connor–Davidson Resilience Scale, 262 characteristics of, 280 Conserved transcriptional response to adversity, 40 characteristics of, 280 Coping, research on, 20–21 Coping with Stress (CWS) characteristics of, 281 for preventing depression, 127–128 Coronary Risk Development in Young Adults (CARDIA), 150 Corticotropin-releasing factor (CRF), 28 AUD changes in, 75–76 Cortisol, 29–30 actions of, 22–23 in blood glucose regulation, 157 epigenetic changes and, 45 measurement of, 30 salivary, 30 COVID-19 pandemic, 216, 233–234 and deaths of African Americans, 255–256, 256t stress and, 143, 233–234 stress cardiomyopathy and, 132 C-reactive protein (CRP) characteristics of, 281 in Japanese women with PTSD, 103 production and measurement of, 41 PTSD and, 102–104 CRHR1 genotype, AUD and, 77–78, 77t Crohn’s disease, 181–182 Cytokines; see also Interleukins (ILs) anti-inflammatory, characteristics of, 280 characteristics of, 281 pro-inflammatory, 24–25

332 D Dale, Henry H., 5–6 Damage-associated molecular patterns (DAMPs), 39 Demand–control imbalance, stress from, 141–142 Demand–control model, 60 Dendritic cell, characteristics of, 281 Depression, 110–129; see also Major depressive disorder (MDD) blood pressure and, 151 and comorbidity with heart disease, 138–141 impacts on cancer morbidity, mortality, 208–211 from infancy through adolescence, 122–123, 124t metastatic breast cancer and, 209–211 theories of, 115–117 immune system and, 116–117 and positive aspects of rumination, 116 socially based, 115–116 twin studies of, 120–122 DHEA-S, characteristics of, 281 Diabetes blood glucose regulation and, 155–158, 155f and comorbid depression, 125 defined, 154 depression and, 165–168 bidirectional relationship of, 166–167, 167f English Longitudinal Study of Ageing and, 166 Nurses’ Health Study of, 165–166 genetic and environmental factors in, 159–160 laboratory study of, 160–161 life stressors and, 161–164 Health and Retirement Study of, 163, 163t Kobe, Japan, earthquake and, 161–162 Swedish Men Study of, 162–163 metabolic syndrome and, 158–159 pathophysiology of, 158 Pima Indian study of, 159–160 prevalence of, 154 stress and, 154–171, 160–168 types of, 154 work stress and, 164–165 Diabetics, wound healing in, 231 Diagnostic and Statistical Manual of Mental Disorders (DSM-III) PTSD in, 88 war-related trauma in, 100 Diagnostic and Statistical Manual of Mental Disorders (DSM-V), 281 alcohol use disorder in, 71, 72t PTSD in, 90, 91t–92t Disability-adjusted life years (DALYs) cardiovascular disease and, 130 characteristics of, 281 Disease biomedical model of, 13 biopsychosocial model of, 13, 15–16, 16f early connections with stress, 10–13 Distress, Selye’s definition of, 8 Disulfiram, 85

Index Drinking relapse statistics on, 85 stress and, 83–84 Drug therapy, for AUD, 85 Duke University Intervention, after heart attack, 146–147 Duke University Stress Management Study, 168–169 Dunedin birth cohort study, 62 Dutch “hunger winter,” 99 Dutch Reverse Diabetes2-Now intervention, 169–170 Dutch Twin Pair study, 266

E Earthquakes acute cardiac events and, 133–134 T2DM and, 161–162 Effort–reward imbalance (ERI), stress from, 142 Effort–Reward Imbalance Questionnaire, 60 characteristics of, 281–282 Electrocardiogram (ECG), characteristics of, 281 Electronic diaries, stress assessment and, 65–66 Electronic health records, 57–58, 58t, 66 racial disparities in, 248 EMIGMA consortium, characteristics of, 282 Engel, George L., 13, 15, 25 English Longitudinal Study of Ageing (ELSA), 166 characteristics of, 282 Epigenetic biomarkers, 44–47 types of, 44–45 Epigenetic changes cortisol-driven, 45 prenatal, 45–46 PTSD and, 97–98 Epigenetic effects on resilience, 268 stress-relevant, 24 Epinephrine, 31, 32t in blood glucose regulation, 157 characteristics of, 282 Epstein–Barr virus (EBV), impacts on HIV, 225 E-Risk Study, characteristics of, 282 E-Risk Twin Study, 264 Eustress, Selye’s definition of, 8 Evolutionary theory, chronic stressors and, 24 Exposure therapy with CBT, for irritable bowel syndrome, 191–192 for PTSD in military personnel, 106–107

F Fight-or-flight response Cannon and, 4–5 characteristics of, 282 in men versus women, 21–22 Financial stress, heart disease and, 250–251 Floyd, George, 236



Index 333 Folkman, Susan, 20–21 Frazier, Darnella, 236

G Galen of Pergamon, 1–3, 196 Gastrointestinal system and stress, 172–194; see also Inflammatory bowel diseases; Peptic ulcer irritable bowel syndrome, 189–191, 190t microbiome–gut–brain axis and, 172–176, 173f communication along, 17t endocrine signaling pathways in, 174–175 enteric nervous system in, 173–174 gut microbiome and, 175–176 immune responses and, 175 peptic ulcers and, 176–181 Gene expression biomarkers, 43–44 General adaptation syndrome (GAS), 6–7, 7f, 9 General Health Questionnaire (GHQ), characteristics of, 282 Genetic factors in alcohol use disorder, 73–75 in Crohn’s disease, 182 in MDD, 111, 113, 121–122 in PTSD, 94–96 Genetic markers, in PTSD, 96 Genome-wide association studies (GWAS) of alcohol-use disorder, 73–74 characteristics of, 282 of CRP, PTSD, 104 of MDD, 111 of PTSD, 94–96 of resilience, 266–268 Gestational hypertension, racial differences in, 246 Glucocorticoid receptor methylation, and PTSD in offspring of Holocaust survivors, 100–101 Glucocorticoid receptors, 28–30 Gold, Philip, 110 Grady Memorial Hospital study, 93 Growth hormone (GH), in blood glucose regulation, 158 Guided imagery, stress and, 80–81

H HAART treatment, for HIV/AIDS, 222 Hales, Stephen, 147 Happy heart syndrome, 132 Harvey, William, 3, 147 Hazard ratio (HR), analyses of, 67 HbA1c, characteristics of, 283 HeadGear, for preventing depression, 128–129 Health, WHO definition of, 10 Health and Retirement Study of T2DM, 163, 163t, 283 Health care professionals, fostering resilience in, 276–277

Health outcomes neighborhoods and, 61–62 racial disparities and, 247–252 social isolation/loneliness and, 58–59 Health psychology, emergence of, 21 Health records, electronic, 57–58, 58t Health risks from stressors, quantitative analyses of, 67 HealthPatch, 42 Heart attack earthquakes and, 133–134 resilience and, 270 soccer and, 134–135 stress and, 133–135 stress-targeted interventions and, 145–147 war/terror and, 135–136 Heart rate variability (HRV) characteristics of, 283 measurement of, 36–37 Hellhammer, Dirk H., 49–50 Herpes zoster infection (shingles), 217–219 French study of, 218–219 Japanese study of, 218 High-density lipoprotein (HDL), characteristics of, 283 Highly active antiretroviral therapy (HAART), for HIV/AIDS, 222 Hippocampus, changes in PTSD, 104–105 Hippocrates, 196 humoral theories of, 2 on melancholia, 110 H1N1 (swine flu), 217t Holmes, Thomas H., 11–12, 13 Holmes–Rahe Stress Inventory (HRSI), 13, 14t limitations of, 54–55, 63–64 Holocaust survivors, offspring of, PTSD risk of, 99–102 Homeostasis versus allostasis, 17 Cannon’s research and, 5, 9 characteristics of, 283 Homophobia, HIV/AIDS and, 221 Hostility, blood pressure and, 150 HPA axis, 28–30 actions of, 22–23 alcohol consumption and, 79 characteristics of, 283 components of, 28, 29f depression and, 110 guided imagery and, 80–81 measured with salivary cortisol, 30 PTSD and, 93 stress-related disorders and, 227–228 Human immunodeficiency virus (HIV), 221–226 homophobia/xenophobia and, 221 meta-analysis in women, 224 prospective studies in men, 223–224, 223t psychosocial stress and progression of, 223–224 stages of, 222, 222t stress-targeted interventions for, 224–226

334

Index

Human immunodeficiency virus (cont.) transmission of, 221–222 treatment of, 222 Hunter, John, 133 Hypertension masked, 149–150 during pregnancy, racial differences in, 246 psychosocial stressors and, 150–152 racial discrimination and, 251–252 stress and, 147–152, 148t stress-targeted interventions for, 152–153 white-coat, 149

I Ibn, Al-Nafis, 2 IL-6, characteristics of, 283 IL-1b, characteristics of, 283 Immersive Multimodal Virtual Environment Stress Test, 51t, 53 Immune response affective style and, 229 to COVID-19, 233–234 stress and, 23 stress-related disorders and, 227–228 Immune system, 37–40 activation of, 37–38 in MDD theory, 116–117 PAMPs and, 38–39 Immunity adaptive, characteristics of, 279 innate, characteristics of, 284 Impatience, blood pressure and, 150 IMVEST, characteristics of, 284 Individual-Participant-Data Meta-Analysis of Working Populations (IPD-Work) Consortium, 165, 284 Infants, African American, birthweights of, 244, 244t Infections, life-threatening, stress-related disorders and, 227–228 Infectious diseases and stress, 216–235 COVID-19 pandemic, 233–234 herpes zoster, 217–219 HIV, 221–226 in life-threatening infections, 227–228 upper respiratory, 219–221 vaccine challenge studies and, 228–230 vaginal, 226–227 viruses of 21st century, 216, 217t wound healing and, 230–233 Inflammation a genomic bias toward, 116 characteristics of, 284 and combat-related PTSD, 104 PTSD and, 102–104 Inflammatory bowel diseases (IBDs), 181–186 Crohn’s disease, 181–182 Nurses’ Health Study of, 183–184, 184t psychosocial stressors and, 182–186

stress-targeted interventions for, 186–189 Swedish cohort study of, 185, 185t telemedicine study of, 184–185 triggers of, 183 ulcerative colitis, 182 Inflammatory markers, interpretation of, 41–42 Innate immunity, characteristics of, 284 Insulin, action of, 156–157 INTERHEART study, 133, 284 Interleukins (ILs) characteristics of, 283 functions of, 40–41 stress responsiveness and, 41 International Classification of Diseases, 11th Revision (ICD-11) alcohol use disorder in, 72 characteristics of, 283 PTSD in, 90, 92t Internet-based interventions for irritable bowel syndrome, 191–192 for ovarian cancer, 214 Irritable bowel syndrome (IBS), 189–193, 190t laboratory stressors and, 190–191 psychosocial stressors and, 190–191 resilience and, 272–273 stress-targeted interventions for, 191–193 exposure-based CBT versus stress management, 191–192 home therapy, 192–193 Internet-based platform for, 191–192

J Jackson Heart Study, characteristics of, 284 James, William, 4 Japan, cancer risk and psychosocial stressors, 198–199, 199t Job Content Questionnaire, 60 characteristics of, 284 Job loss, stress from, 143 Job strain, blood pressure and, 150–151

K Karolinska University Intervention, after heart attack, 145–146 Kennedy, Edward, 238 Kidney donors, stress and wound healing in, 231–232 Kobe, Japan, study of T2DM, 161–162

L Laboratory-based stress paradigms, 49–53, 66 Lactobacillus species, vaginal infections and, 226–227 Latino Stress Management Study, 169 Lazarus, Richard, 20–21



Index 335 Life Events List, 64 Life expectancy, of African Americans versus White Americans, 254–255 Loewi, Otto, 5 Loneliness, blood pressure and, 151 Longitudinal Resilience Assessment (LORA) Study, characteristics of, 285 Low-density lipoprotein (LDL), characteristics of, 284

M Maastricht Acute Stress Test (MAST), 51t, 52–53 characteristics of, 285 Major depressive disorder (MDD), 110–115; see also Depression and at-risk adolescents, 126–127 chronic medical diseases and, 125–126 diagnosis of, 112t–113t genetic aspects of, 111, 113 global burden of disease and, 113–114 overview of, 110–111 personalized prevention programs for, 127–128 and possible positive advantages of, 114–115 risk gene variants for, 111 socioeconomic level and, 114 stress and, 117–120 cognitive model of, 119 cognitive–biological contributions to, 119–120, 120f diathesis–stress theory of, 117–118 intergenerational transmission of, 124–125 kindling theory of, 118–119 stress-targeted interventions for, 126–129 Major Experiences of Discrimination Scale (MEDS), characteristics of, 285 Major life events, stress of, 63–64 Mandela, Nelson, 259 Mannheim Multicomponent Stress Test (MMST), 51t, 52 characteristics of, 285 Marine Resiliency Study (MRS), PTSD and, 96 Mason, John W., 8–9 Matarazzo, Joseph, 21 Maternal morbidity, racial differences in, 246 Matzinger, P., 23 McEwen, Bruce, 16–17, 22–23, 25 Melancholia, 110 Mental health outcomes, resilience and, 269 MERS-CoV, 217t Meta-analysis, characteristics of, 285 Metabolic syndrome characteristics of, 285 diabetes and, 158–159 resilience and, 273 Mexican immigrants, allostatic load in, versus U.S.born Mexican Americans, 243 Middle East respiratory syndrome-associated corona virus (MERS-CoV), 217t

Midlife in the United States (MIDUS) Study, 61, 285 Military personnel, exposure therapy for PTSD in, 106–107 Million Veteran Program, 111 Mindfulness training college students and, 275–276 drinking relapse and, 83–84 IBD and, 188 Mindfulness-based stress reduction (MBSR), for ovarian cancer, 214 Mindfulness-Oriented Recovery Enhancement (MORE), 83–84 Mineralocorticoid receptors (MRs), 28–30 Montreal Neighborhood Networks and Healthy Aging Study, 62 Mortality, racial inequities in, 254–257 MyBPLab app, 43 Mycobacterium tuberculosis, drug-resistant strains of, 12

N Naltrexone, 85 National Health and Nutrition Examination Survey (NHANES) allostatic load data from, 18 characteristics of, 286 weathering hypothesis and, 240 National Institute of Mental Health (NIMH), illness focus of, 10 National Longitudinal Survey of Youth, characteristics of, 286 Neighborhood Disorder Scale, 61 characteristics of, 286 Neuropeptide Y (NPY), 35, 286 Nonspecificity doctrine, 9, 16 Norepinephrine, 31–32, 32t characteristics of, 286 Nucleotide-binding oligomerization domain (NOD)like receptors (NLRs), 38–39 Nurses’ Health Study characteristics of, 286 of IBDs, 183–184, 184t of T2DM, 165–166

O Ovarian cancer and impacts of social support, 201–204 Internet-based CBSM for, 214 psychosocial stressors and, 200

P Parasympathetic nervous system, 36–37 Paroxetine, for PTSD, 105

336

Index

Pathogen-associated molecular patterns (PAMPS), 38 Pattern recognition receptors (PRRs), 38 Peptic ulcer, 176–181 Danish study of, 179 depression and, 180–181, 180t early explanations of, 176–178 role of stress in, 178–181, 178f Swedish study of, 179–180 Perceived Stress Scale (PSS), 54–56, 56t characteristics of, 287 Pima Indian study, 159–160 Plasma catecholamines, 34–35 Point-of-use sensors, 42–43 Police killings, of African Americans, 253–254 Posttraumatic stress disorder (PTSD), 88–109 brain-imaging studies and, 104–105 cancer risk and, 198 cardiovascular disease and, 136 combat-related genetic markers of, 96 inflammation and, 104 cortical volume changes in, 105 diagnosis of, 90, 91t–92t, 93t DSM changes in, 90 epidemiological studies of, 89 genetic overlap with, 95 genetics of, 94–96, 94–98 epigenetic changes, 97–98 genome-wide association studies of, 94–96 transcriptome-wide association studies of, 97 twin studies of, 94 hippocampal volume changes in, 104–105 and history of war trauma, 88 infections and, 227–228 Inflammation and, 102–104 in Japanese women, 103 official recognition of, 88 pharmacotherapy for, 105 and propranolol for trauma memories, 107–108 risk factors for, 88–89, 89t stress-targeted interventions for, 105–109 and transgenerational transmission of trauma, 98–102 Prazosin, for AUD treatment, 86 Preeclampsia/eclampsia, racial differences in, 246 Pregnancy, hypertension during, racial differences in, 246 Premature births, racial discrimination and, 244–246 Pro-inflammatory biomarkers, 40–42 Pro-inflammatory cytokines, 24–25 Prolonged exposure therapy, for PTSD, 106 Propranolol, for trauma memories, 107–108 Prostate cancer and impacts of social support, 204 resilience and, 271 Psychiatric Genomics Consortium (PGC) characteristics of, 286 PTSD and, 94–95 Psychological adjustments, measurement of, 48–49

Psychoneuroimmunology, 216 development of, 23 Psychosis, systemic racism and, 253 Psychosocial factors, TB and, 12 Psychotherapy for IBD, 187 for PTSD, 15–106 Putnam, Robert, 61

R Racial Differences in Stroke (REGARDS) study, 167 Racial inequities, mortality from, 256–257 Rahe, Richard H., 13 Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study, characteristics of, 287 Resilience, 259–278 biomarkers of, 263–264 concepts of, 261 defined, 259 health outcomes and, 269–275 for cancer, 271–272 for cardiovascular disease, 269–270 for heart attacks, 270 for irritable bowel syndrome, 272–273 for mental health, 269 for metabolic syndrome, 273 for overall health/aging, 273–274, 274t measuring, 261–264 molecular and genetic contributions to, 264–268 epigenetic effects, 268 genome-wide association studies of, 266–268 twin studies of, 264–266 neurobiological underpinnings of, 261 versus risk, 260, 260f and stress-targeted interventions for enhancing, 275–277 and systemic racism, 275–277 systems-level approach to, 259–260 Resilience Scale for Adults, 262 Respiratory infections; see Upper respiratory infections Respiratory sinus arrhythmia (RSA), 36 Risk ratios, analyses of, 67 Risk taking, social drinking and, 79 Risky Families Questionnaire, 63 Rivers, Eunice, 238 Rosenwald, Julius, 237 Rumination, positive side of, 116

S Salivary alpha-amylase, 35–36 Salivary cortisol, 30 SARS-CoV, 217t SARS-CoV-2, 217t; see also COVID-19 pandemic



Index 337 Schofield, W., 21 Scottish families, GWAS and, 266–267 Selective serotonin reuptake inhibitors, for PTSD, 105 Selye, Hans, 1 contributions of, 6–9 critiques of, 7–9, 25 legacy of, 9 and nonspecificity doctrine, 9 stress definition of, 7–8 Severe acute respiratory syndrome-associated coronavirus (SARS-CoV-2), 217t Shift work, stress from, 142–143 Shingles; see Herpes zoster infection (shingles) Shozu Herpes Zoster (SHEZ) study, 218 “Sickness behaviors,” 40 Single-nucleotide polymorphisms (SNPs) characteristics of, 287 MDD and, 111, 113 PTSD and, 94, 96, 102–103 Smartphone App, for preventing depression, 128–129 Smartphone applications, stress reduction and, 64–66 Soccer, acute cardiac events and, 134–135 Social capital, health outcomes and, 60–62 Social competition hypothesis of depression, 115 Social drinking, excessive, 79–80 Social isolation, blood pressure and, 151 Social isolation/loneliness, health outcomes and, 58–59 Social Network Index, 59 characteristics of, 287 Social networks, protective effects of, 145 Social Readjustment Rating Scale, 13 Social risk hypothesis of depression, 115–116 Social safety theory, characteristics of, 287 Social signal transduction theory of depression, 117 Social support cancer diagnosis and, 201–204 urban poverty and, 249–250 Social threats, pro-inflammatory cytokines and, 24–25 Socially Evaluated Cold Pressor Test (SEPT), 51–52, 51t characteristics of, 287 Socioeconomic status (SES) and health of African Americans, 242–243 heart attack outcomes and, 251 PTSD risk and, 104 racism and, 257 resilience and, 264 Sperm programming, environmental stimuli and, 46–47 Spiritual growth approach, for HIV, 225–226 STARRS, characteristics of, 287 Stellar, Eliot, 16–17, 25 Stress behavioral measures of (see Behavioral measures) Bernard’s research and, 4 biological measures of (see Biological markers; Biological measures)

cardiovascular disease risk and, 130–131, 131f craving and, 80–81 drinking maintenance and, 81–83 early connections with disease, 10–13 gene expression markers of, 43–44 immune responses and, 23 transgenerational findings on, 24 unified view of, 24–25 Wolff’s research on, 10–11 wound healing and, 230–233 Stress and Adversity Inventory (STRAIN), characteristics of, 287–288 Stress appraisal characteristics of, 280 psychological measures of, 53–57 minor stressors and, 54 Perceived Stress Scale and, 54–56, 56t Stress in Context questionnaire, 57 Stress cardiomyopathy, cardiovascular disease and, 132 Stress field early history of, 1–2, 1–9 Bernard and, 3–4 Cannon and, 4–6 Galen and, 1–3 Harvey and, 3 and revolution in anatomy, 2–3 Selye and, 6–9 later developments in, 10–16 Stress in Context questionnaire, 57 Stress management, for IBD, 187–188 Stress research on appraisal and coping, 20–21 brain-related, 22–23 molecular aspects of, 22–24 social science contributions to, 19–22 Stress responses, laboratory paradigms for, 49–53 Stress-in-Context Questionnaire, characteristics of, 288 Stressors alcohol abuse as, 78 appraisal and coping and, 20–21 AUD and, 75–76 daily, drinking relapse and, 84 depression onset and, 122–123 early life, 62–63 in early life, 122–123, 124t minor, importance of, 54, 55t perceptions of, 11 pro-inflammatory response and, 39–40 TB and, 11–12 work-related, 60 Stress-related disorders cardiovascular disease and, 136 infections and, 227–228 Stress-related variables, wearables for monitoring, 42–43 Stress-responsive systems; see Autonomic nervous system; HPA axis; Immune system

338 Stress-targeted interventions after heart attack, 145–147 for cancer, 212–215 cognitive-behavioral stress management, 213–214 Internet-based, 214 to enhance wound healing, 232–233 for enhancing resilience to systemic racism, 275–277 for health care professionals, 276–277 mindfulness for college students, 275–276 for HIV, comparison of, 225–226 for hypertension, 152–153 for IBD, 186–189 acceptance and commitment therapy, 188–189 mindfulness training, 188 psychotherapy, 187 stress management, 187–188 IBS, 191–193 for MDD, 126–129 for PTSD, 105–109 for reducing impacts of systemic racism, 257 for T2DM, 168–171 Duke University Stress Management Study, 168–169 Dutch Reverse Diabetes2-Now, 169–170 Latino Stress Management Study, 169 Suicide risk, MDD and, 113 Swedish Men Study of T2DM, 162–163 Swedish National Study of T2DM, 164–165 Swine flu (H1N1), 217t Sympathetic nervous system (SNS) depression and, 110 fight-or-flight response and, 23 Systemic racism, 236–258 allostatic load and, 239–243 brain health and, 252–254 cardiovascular disease and, 250–252 health outcomes and, 247–252 hypertension and, 251–252 impacts on mothers and babies, 243–247 and intergenerational transmission of trauma, 247 medical research and, 237–239 Nashville Stress and Health Study and, 242–243 psychosis and, 253 resilience and, 275 and stressors affecting health status, 239, 239f stress-targeted interventions for reducing impacts, 257 weathering hypothesis and, 239–240

T Tai chi training, for HIV, 225–226 Takotsubo syndrome, 132 23andMe, Inc., characteristics of, 288 Tend-and-befriend, characteristics of, 288 Transcriptome-wide association studies, of PTSD, 97

Index Transcutaneous vagus nerve stimulation (VNS), for PTSD, 108–109 Trauma gene expression and, 101–102 intergenerational transmission of, in African American mothers and children, 247 transgenerational transmission of, 98–102 Trauma exposure, brain health and, 252–253 Trauma memories, propranolol for, 107–108 Trauma survivors, children, health risks of, 98–102 Traumatic experiences prevalence of, 89, 89t war and, 88 (see also Posttraumatic stress disorder (PTSD)) Trier Social Stress Test (TSST), 49–50, 50f, 51t AUD and, 76, 80 characteristics of, 288 depression and, 116 Tuberculosis, stress and, 11–12 Tumor necrosis factor alpha (TNF-a), 41, 288 Turner, R. Jay, 242 Tuskegee syphilis study, 237–239 betrayal of subjects of, 237–238 exposure of unethical behavior, 238–239 U.S. Public Health Service and, 237 Twin studies of alcohol-use disorder, 73 of depression, 120–122 of resilience, 264–266

U UCLA Life Stress Interview, 64 characteristics of, 288–289 UCLA Loneliness Scale, 59 characteristics of, 289 Ulcerative colitis, 182 psychosocial stress and, 186 Upper respiratory infections, 219–221 and changes in glucocorticoid receptors, 220–221 meta-analysis of psychological stress and, 219–220 Urinary catecholamines, 35

V Vaccine challenge studies, stress and, 228–230 Vaccine effectiveness, in highly stressed individuals, 234 Vaccine response affective style and response to, 229 psychosocial factors in, 233–234 Vaginal infections, psychosocial stress and, 226–227 Vaginal microbiome, psychosocial stress and, 226–227 Vaginosis, psychosocial stress and, 226 Vasopressin receptors, blockade of, for AUD therapy, 85–86



Index 339 Vesalius, Andreas, 2–3 Vietnam Era Twin Registry, characteristics of, 289 Vietnam Veterans, resilience studies of, 265 Virginia Twin Registry, 264 Voice analysis, assessing stress levels by, 65 von Euler, Ulf S., 6

W Waddington, Conrad H., 44 War trauma, 88; see also Posttraumatic stress disorder (PTSD) War/terror, acute cardiac events and, 135–136 Washington, Booker T., 237 Weathering hypothesis, 239–240

White Americans, life expectancy of, 254–255 Whitehall II Study of T2DM, 164 Wolff, Harold G., 10–11 Work stress, cancer risk and, 198 Workplace drinking in, 82–83 stress management in, 152–153 Work-related stressors, 60 World Health Organization (WHO); see also International Classification of Diseases, 11th Revision (ICD-11) health defined by, 10 Wound healing in diabetics, 231 stress effects on, 230–233 stress-targeted interventions and, 232–233