Life-Course Implications of U.S. Public Policies (US Public Policy) 2020053724, 2020053725, 9780367897598, 9780367897604, 9781003020912

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This timely collection by Janet Wilmoth and Andrew London assembles an impressive cast of social scientists to illuminate how American policies and programs create, perpetuate, or otherwise seek to offset inequalities in distinct periods of life and across the life course. In making these processes more visible, the authors invite us to reimagine policies and programs and intervene into the social world in order to improve the health and well-being of individuals, families, and populations. Richard A. Settersten, Jr., Barbara E. Knudson Endowed Chair and Professor of Human Development and Family Sciences, Oregon State University Life-Course Implications of U.S. Public Policies, edited by Janet M. Wilmoth and Andrew S. London, draws attention to the manifold ways life-course research and policy can and should inform public policy. Its eleven chapters cover rapidly growing societal problems and needs, coupled with markedly insufficient extant policy responses, across a wide range of domains, including food and nutrition, health, housing, and immigration. The selections highlight escalating requirements for innovative programs and policies directed to issues that arise throughout the life course, from juvenile delinquency to long-term care of the elderly and grandparent care work. This comprehensive, highly accessible and engaging collection is a must read for scholars of the life course and for social policy makers. Jeylan Mortimer, Professor of Sociology, University of Minnesota This volume is a fantastic intersection between policy, life-course concepts, and leading-edge theoretical and empirical research. It is both timely and accessible, and therefore highly valuable to a broad range of readers in multiple disciplines across both academic and applied contexts. Miles G. Taylor, Professor of Sociology, Florida State University

LIFE-COURSE IMPLICATIONS OF U.S. PUBLIC POLICIES

There is a complex set of public policies and associated programs that constitute the social safety net in the United States. In Life-Course Implications of U.S. Public Policies, the authors encourage others to systematically consider the influence of policies and programs on lives, aging, and the life course, and how the consequences might vary by gender, race/ethnicity, sexual orientation, ability, and social class. The volume aims to foster an appreciation of how policy influences connect and condition the life course. Chapters examine issues relating to health, housing, food security, crime, employment, and care work, amongst other issues, and demonstrate how the principles of the life-course perspective and cumulative inequality theory can be used to inform contemporary public policy debates. Life-Course Implications of U.S. Public Policies will be a great resource for students of gerontology, sociology, demography, social work, public health and public policy, as well as policy makers, researchers in think tanks, and advocates, who are concerned with age-based policy. Janet M. Wilmoth is Professor and Chair of Sociology, and Director of the Aging Studies Institute, at Syracuse University. She is affiliated with the Center for Aging and Policy Studies, the Center for Policy Research, and the Lerner Center for Public Health Promotion. Her research examines older adult migration, living arrangements, and health status, and explores how military service shapes various life-course outcomes. Andrew S. London is Associate Dean and Professor of Sociology at Syracuse University’s Maxwell School of Citizenship and Public Affairs. He is affiliated with the Aging Studies Institute, the Center for Aging and Policy Studies, the Center for Policy Research, and the Lerner Center for Public Health Promotion. His areas of specialization are in medical sociology, demography, aging and the life course, veterans, families, poverty, and social welfare.

SOCIETY AND AGING SERIES Madonna Harrington Meyer, PhD, and Jennifer Karas Montez, PhD, Series Editors

For a complete list of all books in this series, please visit the series page at: https://www.routledge.com/Society-and-Aging-Series/book-series/SAS

Later-Life Social Support and Service Provision in Diverse and Vulnerable Populations Understanding Networks of Care Edited by Janet M. Wilmoth and Merril Silverstein Dying in Old Age U.S. Practice and Policy Sara M. Moorman Life-Course Implications of U.S. Public Policies Janet M. Wilmoth and Andrew S. London

LIFE-COURSE IMPLICATIONS OF U.S. PUBLIC POLICIES

Edited by Janet M. Wilmoth and Andrew S. London

First published 2021 by Routledge 52 Vanderbilt Avenue, New York, NY 10017 and by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN Routledge is an imprint of the Taylor & Francis Group, an informa business © 2021 Taylor & Francis The right of Janet M. Wilmoth and Andrew S. London to be identified as the author of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging-in-Publication Data Names: Wilmoth, Janet M. (Janet May) editor. | London, Andrew S., editor. Title: Life-course implications of U.S. public policies / [edited by] Janet M Wilmoth, Andrew S London. Description: 1 Edition. | New York City : Routledge Books, 2021. | Series: Society and aging | Includes bibliographical references and index. Identifiers: LCCN 2020053724 (print) | LCCN 2020053725 (ebook) | ISBN 9780367897598 (hardback) | ISBN 9780367897604 (paperback) | ISBN 9781003020912 (ebk) Subjects: LCSH: Aging–United States. | Aging–Social aspects. | Public administration–United States. | Older people–Care. Classification: LCC HQ1061.L475 2021 (print) | LCC HQ1061 (ebook) | DDC 305.26–dc23 LC record available at https://lccn.loc.gov/2020053724 LC ebook record available at https://lccn.loc.gov/2020053725 ISBN: 978-0-367-89759-8 (hbk) ISBN: 978-0-367-89760-4 (pbk) ISBN: 978-1-003-02091-2 (ebk) Typeset in Bembo by Taylor & Francis Books

To my children, Catherine Jean Durkin and Brian Patrick Durkin, Jr., and all children who will live with the enduring impact of current public policies and social programs. JMW To Beatrice Shopnick, Nana, who lived for 107 years, from 1910 to 2017, and exemplified resilient aging to me and all who knew her. ASL

CONTENTS

List of illustrations Foreword Preface Janet M. Wilmoth and Andrew S. London Acknowledgements List of contributors 1 An Introduction to Life-Course Perspectives on Public Policies Janet M. Wilmoth and Andrew S. London

xi xiii xv xvii xviii

1

2 Process, Policy, and Unintended Consequences: The Life-Course Patterning of Cumulative (Dis)advantage Dale Dannefer and Chengming Han

17

3 Structural Sexism and Life-Course Health: Implications for Public Policy Patricia Homan

31

4 Wealth Policy as Health Policy: A Population Aging and Racial Equity Perspective Courtney Boen

41

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Contents

5 Understanding the Role of Housing Policy in Life-Course Health: HUD Rental Assistance and Health Outcomes for Children and Adults Andrew Fenelon 6 U.S. Food and Nutrition Policy Across the Life Course Colleen M. Heflin

52 64

7 Crime and Delinquency Over the Life Course: Adolescence, Peers, and Policy Jason P. Robey and Michael Massoglia

74

8 Immigration Policies and the Health of the Older Foreign-Born in the United States Zoya Gubernskaya

87

9 The Future of Long-Term Care in the Latino Population: Where Will the Burden Fall? Jacqueline L. Angel and Sunshine M. Rote

100

10 How Social Policies Affect Grandparent Care Work Madonna Harrington Meyer and Amra Kandic

114

11 Social Policies for Older Workers Debra Street and Áine Ní Léime

124

Index

137

ILLUSTRATIONS

Figures

3.1 A conceptual framework for understanding the relationships among structural sexism, public policies, and health 4.1 Long-term wealth and biological age 4.2 Racial wealth inequality among children and older adults 4.3 The socioeconomic determinants of black–white disparities in biological age 5.1 Predicted Strengths and Difficulties Questionnaire (SDQ) score for children (ages 2–17) by rental assistance status 5.2 Percent reporting fair/poor health and serious psychological distress among adults (ages 18+) by rental assistance status 6.1 Household food insecurity by age 8.1 Top countries of origin of foreign-born age 65 and over in the United States: 2016 IPUMS American Community Survey 8.2 Foreign-born age 65 and over by duration of stay in the United States and by year of migration: 2016 IPUMS American Community Survey 8.3 Predicted probability of functional difficulties by age at migration, citizenship, and timing of naturalization: Foreign-born age 65+, 2016 IPUMS American Community Survey

35 45 46 48 58 59 66

89

90

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xii List of illustrations

Tables

1.1 Social safety net in the United States 1.2 Settersten’s (2003) framework for analyzing the intersection between human development and social policy 3.1 Conceptual overview of domains in which macro-structural sexism occurs 9.1 Caregiving experiences by race/ethnicity (%)

4 11 33 105

FOREWORD

According to Forrest Gump’s mama, “Life was like a box of chocolates. You never know what you’re gonna get.” Mama was right. However, that uncertainty can be tamed with public policies. In fact, no two people experience life in the same way. Some are raised poor and others wealthy. Some of those raised poor will rise to middle class, while others will never escape the poverty of their childhood. Some have extended families and social networks that buffer against the vicissitudes of life; many others traverse life with fragile social and economic supports. Some retire from long careers and travel the globe; many others retire early to stay home and help raise grandchildren. By older age, people have accumulated vastly different experiences from one another. As a consequence, their social and economic well-being and health vary greatly. Why do these differences and inequalities emerge? Why do they grow over the life course? Why are they larger in the United States than other high-income countries? Are they inevitable and immutable? If not, how can public policies prevent or ameliorate them? Have public policies had a hand in creating them? These questions and more are addressed in Life-Course Implications of U.S. Public Policies, edited by Janet M. Wilmoth and Andrew S. London. The origins of this manuscript lie in a session of “flash talks” at the 2019 American Sociological Association Conference in New York City. Those talks resulted in these 11 engaging chapters. Taken together, they reveal how aging and the life course of individuals and families in the United States are inextricably linked to public policies. At the conference and in this volume, Wilmoth and London assembled expert scholars from sociology, demography, gerontology, and public policy who bring deep knowledge and innovative perspectives on the topic.

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Foreword

The chapters paint a clear picture of the importance of public policies on aging and the life course. For starters, public policies affect everyone. They affect lowincome adults (e.g., housing vouchers) as well as middle- and high-income adults (e.g., mortgage interest deductions). Public policies touch every age group. They affect children (e.g., the Supplemental Nutrition Assistance Program, also known as SNAP), adolescents (e.g., compulsory schooling), working-age adults (e.g., paid leave or the lack thereof), and retirees (e.g., Medicare). Public policies can attenuate inequalities (e.g., the Earned Income Tax Credit), but they also can exacerbate them (e.g., low minimum wage). The authors illustrate how public policies impact all of our lives and those of our families and communities. Too often, these universal effects are underappreciated. The chapters also illuminate the far-reaching and often unintended effects of public policies on aging across the life course. For instance, even though many policies target a particular age group, they affect people of all ages in the recipients’ lives. One example is paid family leave. In addition to helping working-age recipients stay economically afloat, paid family leave can improve their infants’ health and avoid pressure on grandparents to provide caregiving. The effects of public policies also can reverberate across generations. As an example, food security policies such as SNAP benefit the growth, development, and health of children who receive the food. These healthy children, as adults, are then more likely to have healthy children of their own. Despite the potential to prevent or ameliorate inequalities in aging and the life course, U.S. public policies have fallen short. According to the authors, the reasons are complex. Many policies are designed in piecemeal fashion, creating gaps in coverage. Many others rely on means-testing, which often incurs high administrative costs and excludes a sizable portion of the population. In sum, the chapters show that public policies are potentially powerful levers for reducing inequality across the life course and improving population wellbeing—today, tomorrow, and for generations to come. For policy makers seeking a recipe for a thriving and healthy U.S. population, these chapters provide the key ingredients. Jennifer Karas Montez

PREFACE Janet M. Wilmoth and Andrew S. London

This edited volume was inspired by an invited panel that we organized for the 2019 annual meeting of the American Sociological Association. This Section on Aging and the Life Course (SALC) session featured a series of five-minute flash talks on U.S. public policy debates in relation to various life-course stages. Then, because flash talks are short, we presided over an extended exchange between audience members and panelists. The engaging presentations and lively discussion generated a palpable buzz in the room. The feedback we received from panelists and audience members alike convinced us that the field would benefit from a book that succinctly outlined major policy debates and closely coupled them to the cutting edge of aging and life-course scholarship. The panelists who participated in that 2019 SALC session graciously agreed to contribute brief chapters to this edited volume. Each chapter explores contemporary public policy issues in relation to specific segments of the life course and processes of cumulative inequality across the life course. Central questions motivating the chapters include:   

How does policy shape cumulative (dis)advantage processes and outcomes during childhood and adolescence, young adulthood, middle adulthood, and older adulthood? What are the life-course implications of federal and state policies in various domains, including health and health care, work and retirement, crime, families and caregiving, housing, food security, and immigration? How do race, class, and gender influence how policies are shaped, social programs are taken up, and efforts to intervene influence different stages of the life course?

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Preface



What are the most pressing policy issues that life-course scholars should consider? What kinds of data needs exist? How might a greater appreciation of the linked lives principle of the lifecourse perspective influence how policies and social programs are conceived, implemented, and evaluated?



Through this edited volume, we are encouraging others to systematically consider the influence of public policies and social programs on lives, aging, and the life course. Public policies include all types of government policies. Some might be explicitly social in that they aim to meet human needs for security, education, work, health, and well-being. Others, while not primarily social in nature, still could have social implications. Public policies often are narrowly focused and targeted legislative or regulatory guidelines. Yet, sometimes they affect women more than men, or vice versa, or have consequences that vary by age, race/ethnicity, sexual orientation, ability, and social class. The effects of public policies often are channeled through the social programs they instantiate. For example, the Medicare program is a manifestation of health policy. Social programs can have short- and long-term effects, contribute to dynamic processes of inequality, vary in relation to personal history and historical timing, and spill over into the lives of others. All of these potentialities require explicit examination by life-course scholars. Additionally, we hope this volume will achieve two other related goals. First, we strive to foster an appreciation of how public policy influences connect with one another and condition the life course. The life-course principle of life-long development suggests that one domain of policy and its associated ground-level programs can affect the outcomes of other policies and programs taken up in a later stage of the life course. For example, child development policies that govern ground-level programs like Head Start could condition the effects of education and work-force development policies and programs targeted to adolescents and young adults. Second, and perhaps most important, we hope to demonstrate how the principles of the life-course perspective and cumulative inequality theory can be used to inform contemporary public policy debates and lead to social programs that are more responsive to the needs of individuals across the life course.

ACKNOWLEDGEMENTS

This edited volume would not have been possible without the contributions of many. Our work was supported by the Appleby–Mosher Fund for Faculty Research from the Maxwell School of Citizenship and Public Affairs at Syracuse University. We are grateful to the authors for their collaboration, excellent work, insights, and timely revisions. We also thank the series editors, Madonna Harrington Meyer and Jennifer Karas Montez, for their unwavering and enthusiastic support for this project. Jeylan Mortimer, Miles Taylor, and two anonymous reviewers provided comments on each chapter. Their constructive, wise suggestions helped to elevate specific themes in our overview that the authors threaded throughout the volume. We are grateful to them for their engagement and thoughtful guidance; the volume is improved as a consequence. We also thank Richard Settersten for his insightful suggestions on our chapter. At Routledge, Tyler Bay and Charlotte Taylor have been incredibly supportive, and patient, as many of us grappled with the challenges of getting things done during a pandemic. We appreciate the support of Richard Cook and Jeffrey Boys, at Book Now, who provided editorial and production assistance. We also thank Yooumi Lee for her assistance with formatting and Eric Ferguson for his assistance with copy-editing and indexing. Finally, we would like to thank our respective spouses—Brian Durkin and Alan Curle—for supporting us in doing this work that we both love to do. Janet M. Wilmoth and Andrew S. London

CONTRIBUTORS

Jacqueline L. Angel is the Wilbur J. Cohen Professor of Public Affairs and Professor of Sociology at The University of Texas at Austin. Her research examines health and retirement issues in the U.S., with a focus on older minorities, immigration processes, and the impact of social policy on the Hispanic population and Mexican-American families. She is involved in several NIH/NIA projects, including a longitudinal study of older Mexican Americans (H-EPESE) since its inception in 1992 and for the past two decades a Conference Series on Aging in the Americas. Angel is author/coauthor/co-editor of numerous publications, such as The Politics of a Majority-Minority Nation: Aging, Diversity and Immigration (2019); Latinos in an Aging World (2015); “Medicaid Use among Older Low-Income Medicare Enrollees in California and Texas: A Tale of Two States” (2019) and “Institutional Context of Family Eldercare in Mexico and the United States” (2016). Courtney Boen is an Assistant Professor and Axilrod Faculty Fellow in the Department of Sociology at the University of Pennsylvania. She is also a Research Associate in the Penn Population Studies Center and Population Aging Research Center, an Affiliate in the Center for the Study for Ethnicity, Race, and Immigration, and a Senior Fellow in the Leonard Davis Institute for Health Economics at the Penn. Dr. Boen’s research focuses on the social determinants of population health inequality, with particular attention to the social factors producing racialethnic, immigrant-native, and socioeconomic health inequities across the life span. Her work aims to improve scientific understanding how macro-level systems of social inequality shape micro-level biophysiological processes to produce health disparities from birth through late life. Her research has been published in a number of outlets, including the Journal of Health and Social Behavior, Social Science

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and Medicine, Proceedings of the National Academy of Sciences, The Journals of Gerontology, Biodemography and Social Biology, the Journal of Aging and Health, Cancer Epidemiology, Biomarkers, and Prevention, and the American Journal of Preventive Medicine. Dr. Boen received her PhD in sociology from the University of North Carolina at Chapel Hill and her MPH from Tufts University. Dale Dannefer is Selah Chamberlain Professor and Chair of the Department of the Sociology at Case Western Reserve University. He received his Ph.D. from Rutgers University and has been a fellow at the Max Planck Institute for Human Development and Education in Berlin, at the Andrus Gerontology Center, and in the Department of Sociology at Yale University. His recent publications include Age and the Reach of Sociological Imagination (Routledge, forthcoming), “Systemic and Reflexive: Foundations of Cumulative Dis/Advantage and Life Course Processes” (Journals of Gerontology Social Sciences, 2020) and “With the Wind at Their Backs” (Annual Review of Gerontology and Geriatrics, 2020). Andrew Fenelon is an Assistant Professor of Public Policy, Sociology, and Demography at Penn State University and an associate faculty member of the Population Research Institute. He is a sociologist and demographer studying health disparities, population health, and housing policy. Dr. Fenelon’s current research addresses the effects of HUD housing assistance programs on health, well-being, and neighborhood attainment across the life course, and highlights the role of stable and affordable housing as a social determinant of health. His work has appeared in a number of academic journals including JAMA, Journal of Health and Social Behavior, and Demography, and he currently serves as the Secretary of the Interdisciplinary Association for Population Health Science (IAPHS). Zoya Gubernskaya is an Associate Professor of Sociology at the University at Albany, the State University of New York. Her research interests are at the intersection of sociology and demography of immigration, family, aging and health. One strand of her research focuses on health and well-being of older immigrants in the United States. The second strand of her research explores changes in intergenerational relations over time and across different countries. Zoya’s research articles appeared in peer-reviewed sociology and interdisciplinary journals, such as Demography, Journal of Marriage and Family, Journal of Health and Social Behavior, and Journal of Gerontology: Social Sciences. Chengming Han is a sociology Ph.D. candidate in Case Western Reserve University. Chengming’s research involves social changes and urban-rural inequalities in China, health disparities among minorities and immigrants in the U.S., aging and the effects of social changes and policies on the life-course outcomes. Before the Ph.D. program, Chengming was a volunteer teacher for migrant children, and published articles on the reproduction of the disadvantages

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of migrant children, migrant worker neighborhoods, and educational policies for migrant children. She also has published research on journal and conference papers on oral health disparities in the U.S., urban-rural inequalities, and migrant workers in China. At present, Chengming is engaged in her dissertation which focuses on the social changes in China since 1949 and the life-course health of the PRC (People’s Republic of China) cohort. Chengming’s future research plan involves comparative studies of social policies and the life course in China, USA, and Canada. Madonna Harrington Meyer is University Professor at Syracuse University. She is professor of sociology at the Maxwell School of Public Affairs and Meredith Professor of Teaching Excellence. She is senior research associate at the Center for Policy Research, Faculty Affiliate at the Aging Studies Institute, and Faculty Research Affiliate at the Lerner Center. She is co-author, with Ynesse Abdul-Malak, of Grandparenting Children with Disabilities (2020). She is co-editor, with Ynesse Abdul-Malak of Grandparenting in the United States (2016). She is coeditor with Elizabeth Daniele of Gerontology: Changes, Challenges, and Solutions (2016). She is author of Grandmothers at Work: Juggling Families and Jobs (2014), winner of the Gerontological Society of America’s Kalish Book Award. She is co-author with Pamela Herd of Market Friendly or Family Friendly? The State and Gender Inequality in Old Age (2007), which also won the Gerontological Society of America’s Kalish Book Award. She is editor of Care Work: Gender, Labor, and the Welfare State (2000). Her work appears in American Sociological Review, Journal of Health and Social Behavior, Gender & Society, and Social Problems. In 2016 she was named winner of the American Sociological Association (ASA) Section on Aging and the Life Course (SALC) Matilda White Riley Distinguished Scholar Award. Colleen Heflin is Professor of Public Administration and International Affairs and Senior Research Associate in the Center for Policy Research at Syracuse University. Dr. Heflin received her PhD from the University of Michigan. Heflin’s primary research interests include social policy, food and nutrition policy and social demography. Dr. Heflin’s research has appeared in leading journals such as the American Sociological Review, Social Problems, Health Affairs, and the Journal of Policy Analysis & Management. In 2014, her paper on community social capital was awarded the W. Richard Scott Award for Distinguished Scholarship from the American Sociological Association. Dr. Heflin’s research has been funded by the National Institutes of Health, U.S. Department of Health and Human Services, the U.S. Department of Agriculture, the Robert Wood Johnson Foundation and the Russell Sage Foundation. Patricia Homan is an Assistant Professor of Sociology at Florida State University. She is also an Associate at FSU’s Pepper Institute on Aging and Public

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Policy and a Research Affiliate of the FSU Center for Demography and Population Health. Her research explores how gender, socioeconomic, and racial inequalities in American society shape the health and well-being of the population and of individuals as they age. Her recent work has been published in American Sociological Review, Social Forces, Social Science & Medicine, and The Journals of Gerontology: Series B. Amra Kandic, MA, is a PhD student in the Department of Sociology at Syracuse University. Her research interests include aging, immigration, and social policy. She holds a MALS degree in globalization from Dartmouth College and a MA degree in sociology from Syracuse University. Andrew S. London is the Associate Dean for Administration and Research, and a Professor of Sociology, in the Maxwell School of Citizenship and Public Affairs at Syracuse University. London is a Faculty Associate in the Aging Studies Institute, and a Faculty Affiliate in the Center for Aging and Policy Studies, Center for Policy Research and the Lerner Center for Public Health Promotion. London is a Sociologist and Demographer who specializes in studying the health, care, and well-being of stigmatized and vulnerable persons and populations. He has published approximately 90 peer-reviewed articles and book chapters, and two edited volumes, that focus on persons living with HIV/AIDS, caregivers, welfare-reliant and working poor women, children living in poverty, the formerly incarcerated, LGBT (lesbian, gay, bisexual, transgender)-identified persons, racial/ethnic minorities, immigrants, older adults, and adults living with Attention Deficit Hyperactivity Disorder (ADHD). For the past 15+ years, much of his research has focused on the life-course consequences of military service for health, disability, mortality, social program participation, marriage/divorce, and health behaviors (e.g., smoking, drinking, sexual behavior). In his research, teaching, and advocacy work, he is particularly concerned with how social factors, policies, programs, and institutions can mitigate or exacerbate vulnerability, disadvantage, and social exclusion across the life course. Michael Massoglia is a Professor of Sociology at the University of WisconsinMadison. His work focuses on the social consequences of the expansion of the penal system, the relationship between the use of legal controls and demographic change in the United States, and patterns and consequences of criminal behavior over the life course. Current research projects examine historical variation in U.S. criminal deportations as well as the relationship between incarceration and neighborhood attainment and racial composition. Mike teaches classes on criminology, delinquency, and deviance. Jennifer Karas Montez is a Professor of Sociology, the Gerald B. Cramer Faculty Scholar in Aging Studies, Director of the Center for Aging and Policy

xxii List of contributors

Studies, and Co-Director of the Policy, Place, and Population Health Lab at Syracuse University. Her research investigates trends and disparities in population health since the 1980s and the growing influence of U.S. state policies and politics on those outcomes. Her research on these topics has been featured in outlets such as the New York Times, BBC, NPR, and CNN; and it has been funded by the National Institute on Aging, Robert Wood Johnson Foundation, Carnegie Corporation, and National Science Foundation. Montez received her PhD in Sociology from the University of Texas at Austin. Áine Ní Léime is a senior researcher and Deputy Director at the Irish Centre for Social Gerontology at NUI Galway. Her research focuses on the social aspects of ageing and more recently have concentrated more specifically on gender, ageing, employment, pensions and extended working life policy She is a former Marie-Sklodowska Curie International Outgoing fellow (2015–2018) and spent two years at Case Western Reserve University in Cleveland, Ohio conducting a qualitative project entitled Gender, Older Workers and the Lifecourse (GENDOWL), comparing the work-life experiences of older workers in Ireland and the U.S. She is currently Principal Investigator for the Irish strand of an EUfunded project, Dynamics of Accumulated Inequalities for Seniors in Employment (DAISIE) 2018–2021) a cross-national project on older workers. She has been awarded a Science Foundation Ireland, Public Service Fellowship on the Costs of Discrimination and the Benefits of Diversity in the Workplace (2020– 2022). She is a Fellow of the Gerontological Society of America (FGSA). Her teaching is in the area of gender and work, social policy and ageing. Jason Robey is a PhD student in the Department of Sociology at the University of Wisconsin-Madison. He is also affiliated with the Center for Demography and Ecology. His research focuses on crime, delinquency, incarceration, immigration, and inequality. Jason’s work has been published in the Proceedings of the National Academy of Sciences (PNAS), the Oxford Research Encyclopedia of Criminology, and two edited volumes. Prior to joining the University of Wisconsin-Madison, Jason worked at the University of Minnesota Law School as a Research Associate with the Robina Institute of Criminal Justice, where his work focused on the role of probation and parole supervision in the criminal justice system. Sunshine M. Rote is an Associate Professor in the Kent School of Social Work at the University of Louisville. Dr. Rote’s research examines the role of social relationships for psychological well-being and cognitive health of diverse older adult and their family caregivers. Debra Street is Professor of Sociology at the State University of New York at Buffalo. Author of 80+ articles, book chapters, and working papers; a

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monograph; and co-editor of three books, Street researches the challenges presented by aging societies, particularly those associated with gender, health, and income security over the life course and the experiences of older workers in contemporary labor markets. She is a Fellow of the Gerontological Society of America, an elected member of the National Academy of Social Insurance, former Senior Research Fellow at King’s College, London and recipient of the UB Gender Institute Janice L. Moritz Distinguished Lecturer award. Street’s research has been funded by the National Science Foundation, the National Institute on Aging, The International Council for Canadian Studies, and the Robert Wood Johnson Foundation. Professor Street is also an award-winning teacher, the recipient of the SUNY Chancellor’s Award for Excellence in Teaching (2014) and the annual award for Outstanding Contributions to International Education (2016) from the Council on International Studies and Programs. Janet M. Wilmoth has a Ph.D. in Sociology and Demography, with a minor in Gerontology, from the Pennsylvania State University. She is a Chair and Professor of Sociology, Director of the Aging Studies Institute, Primary Leader of the Aging Health and Neuroscience Cluster, and a Faculty Affiliate in the Center for Aging and Policy Studies, the Center for Policy Research, and the Lerner Center for Health Promotion at Syracuse University. Her research utilizes quantitative methods to understand later-life well-being from a life-course perspective. She has over 70 publications in the areas of older adult migration and living arrangements, health status, financial security, and the influence of military service on various life-course outcomes. She also co-edited Gerontology: Perspectives and Issues, 3rd and 4th Edition, Life Course Perspectives on Military Service, and LaterLife Social Support and Service Provision in Diverse and Vulnerable Populations: Understanding Networks of Care.

1 AN INTRODUCTION TO LIFE-COURSE PERSPECTIVES ON PUBLIC POLICIES Janet M. Wilmoth and Andrew S. London

Social, economic, and health inequalities are persistent features of life in the United States. These inequalities are rooted in social structures that variably influence childhood experiences and compound (dis)advantage as individuals transition into adulthood, move through mid life, and segue to later life. The experience of inequality differs along intersecting axes of socially constructed categories, including race, ethnicity, immigrant status, class, gender, ability, and sexual orientation. Through various mechanisms, it contributes to increasing heterogeneity within birth cohorts (i.e., groups defined by specific birth years) as they age through the life course. As a result, certain groups arrive at later life with substantially fewer resources than others, which influences their capacity to cope with the challenges of aging. Variation across cohorts in these cumulative inequality processes is produced by the unique historical experiences their members encounter at critical life stages (Ferraro, Shippee, and Schafer 2009). These historical macro-level social forces include economic cycles, demographic changes, political regimes, periods of war and peace, technological changes, pandemics, and cultural shifts. As the modern welfare state developed in the twentieth century, the U.S. federal government increasingly developed public policies based on legislative and regulatory guidelines that were typically implemented through ground-level programs at the state and local levels. These policies and programs were designed to promote population health and well-being by addressing macro-level social forces that directly and indirectly shaped life-course processes and outcomes. An early example of this is President Franklin Roosevelt’s “New Deal,” which was implemented in the 1930s as the nation struggled to recover from the Great Depression. The New Deal was bolstered by the post-World War II economic boom, which was in part made possible by the Servicemen’s Readjustment Act

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of 1944 (commonly known as the “G.I. Bill”), and enhanced by the “War on Poverty” and policies enacted in response to the Civil Rights Movements of the 1960s. Together, these initiatives led to such programs as Medicare and Medicaid, as well as the expansion of a broad social safety net that aimed to level the playing field for, and promoted equality among, Americans who came of age during the middle of the twentieth century. However, the social safety net in the United States lagged behind other welfare states. This is consequential because, as O’Rand (2003:227) notes, “more marketized societies with weaker welfare state structures provide fewer public protections against life-course risks, leading to even more heterogeneity and inequality across the lifespan.” As American politics took a neoliberal turn in the latter two decades of the twentieth century, support for some of these programs began to wane, and initiatives aimed at retrenching and reforming the welfare state were pursued (Quadagno and Street 2006). Holes began to develop in the social safety net as individual responsibility through work became an increasingly important cornerstone of eligibility for, and access to, the social safety net (Scott, London, and Gross 2007). Moreover, as the level of benefits provided decreased, the criteria for qualifying for benefits tightened and the burden of paying for these programs shifted from the federal government to increasingly strained state and local governments. As a result of these shifts, inequality in various domains has been on the rise in the United States for several decades, and the “American Dream” of financial security and upward mobility has become increasingly unattainable, particularly for younger cohorts (Chetty et al. 2017). One life-course manifestation of this phenomenon is the delay in achieving the traditional markers of adulthood that recent cohorts are experiencing, as encapsulated by the new transition to adulthood framework (Settersten and Ray 2010). The current COVID-19 pandemic is making the transition to adulthood even more fraught for the millennial cohort (Settersten et al. 2020). In addition, there is mounting evidence that the pandemic is exacerbating inequalities, as local, state, and federal governments have failed to mount an effective, coordinated policy response, while tax revenues that support social programs are shrinking due to the contraction of the economy. The pandemic has disrupted lives across the board, but certain segments of the population, including older adults, poor and working-class families, women, people of color, individuals with disabilities, and institutionalized individuals are particularly at risk of contracting the disease and experiencing its social, economic, cultural, and psychological consequences (Settersten et al. 2020). Given this state of affairs, it is crucial that life-course scholars have a firm understanding of how public policies and their associated social programs shape cumulative inequality within and between cohorts. In addition, policy makers need to appreciate how their decisions directly and indirectly impact various lifecourse outcomes. Therefore, in this introductory chapter, we aim to set the stage for the chapters that follow by providing an overview of the social safety net in

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the United States and discussing how the core principles of the life-course perspective can be used to understand the short- and long-term implications of public policies. We conclude the chapter with a brief introduction to each of the chapters included in this volume, which individually and collectively address the life-course consequences of specific but interrelated policies and programs.

The Social Safety Net in the United States The social safety net comprises various programs that offer in-kind aid and cash transfers to individuals and families. The goal of these programs is to provide assistance in times of need and protection against life’s uncertainties. These programs also are designed to promote population health and well-being. Countries (and states or regions within countries) with stronger social safety nets have higher life expectancies, fewer health disparities, and less economic inequality (Avendano and Kawachi 2014; Bor, Cohen, and Galea 2017). The strength of the social safety net in any given country depends on the legislative and regulatory policies that govern—and the budgetary priorities that support—the implementation of specific social programs. As shown in Table 1.1, the U.S. social safety net is made up of a patchwork of policies and associated programs that are: administered by federal, state, and local governments; supplemented by employer-provided benefits; and supported by a progressive tax code. While it is beyond the scope of this brief chapter for us to discuss each of these in detail, here we highlight some basic features of key programs and provide some evidence about their use. Social assistance programs (also known as “welfare”) and social insurance programs (also known as “entitlement”) are the foundation of the U.S. social safety net. Social assistance programs that rely on means-testing provide a range of services targeted to individuals and families who meet specific income- and asseteligibility criteria. They offer income, health care, nutritional, housing, educational, and employment support to those who are most in need. Approximately 21% of the population uses at least one of five major assistance programs. The most commonly used programs are Medicaid (15%) and the Supplemental Nutrition Assistance Program (SNAP) (13%), whereas a very small percentage of the population uses housing assistance (4%), Supplemental Security Income (SSI) (3%), and Temporary Assistance for Needy Families (TANF)/General Assistance (GA) (1%) (U.S. Census Bureau 2015a). In addition, most program participation is episodic and short-term. The length of participation is 12 months or less for nearly one-quarter of housing assistance recipients; about one-third of Medicaid, SNAP, and SSI recipients; and about two-thirds of TANF/GA recipients (U.S. Census Bureau 2015b). Children under the age of six years old whose families have incomes below the federal poverty threshold are eligible for Head Start educational programs, which serve over one million children annually (Early Childhood Learning & Knowledge Center 2020). In addition, Healthy Start

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TABLE 1.1 Social safety net in the United States

Type of program

For more information, go to:

Social assistance (aka “welfare”):  Temporary Assistance for Needy Families (TANF)  Supplemental Nutrition Assistance Program (SNAP)  Women, Infants, and Children (WIC)  Child Nutrition  Medicaid  Supplemental Security Income (SSI)  Housing Assistance  Low Income Home Energy Assistance Program  Head Start  Pell Grants  Job Training  Lifeline Social insurance (aka “entitlement” programs):  Social Security  Retirement Benefits  Disability Benefits  Medicare  Unemployment Insurance Tax code:  Child Tax Credit  Child and Dependent Care Credit  Earned Income Tax Credit  Home Mortgage Interest Deduction  Medical Expenses deductions Employment-based benefits:  Private Pension Programs  Health Insurance

https://www.acf.hhs.gov/ofa/programs/tanf/about https://www.fns.usda.gov/snap/supplementalnutrition-assistance-program https://www.fns.usda.gov/wic https://www.fns.usda.gov/cn https://www.medicaid.gov/ https://www.ssa.gov/ssi/ https://www.hud.gov/topics/rental_assistance https://www.acf.hhs.gov/ocs/programs/liheap https://www.acf.hhs.gov/ohs https://studentaid.gov/understand-aid/types/grants/ pell https://www.dol.gov/general/topic/training/adult training https://www.fcc.gov/consumers/guides/life line-support-affordable-communications

https://www.ssa.gov/ https://www.ssa.gov/benefits/retirement/ https://www.ssa.gov/benefits/disability/ https://www.ssa.gov/benefits/medicare/ https://www.dol.gov/general/topic/ unemployment-insurance https://www.irs.gov/taxtopics/tc602 https://www.irs.gov/taxtopics/tc602 https://www.irs.gov/credits-deductions/individuals/ earned-income-tax-credit https://www.irs.gov/pub/irs-pdf/p936.pdf https://www.irs.gov/taxtopics/tc502 https://www.usa.gov/retirement https://www.ncbi.nlm.nih.gov/books/NBK235989/

Life-Course Perspectives on Policy

Type of program

For more information, go to:

 Supplemental Benefits (Vision, Dental, Disability, Life Insurance) & Paid Leave  Family and Medical Leave

https://center-forward.org/work ing-nine-to-five-the-u-s-and-employer-sp onsored-benefits/ https://www.dol.gov/general/topic/workhours/ fmla https://www.fsafeds.com/

 Childcare and Medical Flexible Savings Accounts

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programs, which offer individual- and community-level services that promote child health, are available in over 100 communities with high infant mortality rates in 37 states and the District of Columbia (Escarne et al. 2017). Low-income adults with demonstrated financial need might be eligible for the Federal Pell Grant Program, which pays for postsecondary education. In 2017–2018, there were over 7.1 million Pell Grant recipients, with an average award of $4,031 (U.S. Department of Education 2020). These parental, early-childhood, and earlyadulthood programs might contribute to decreased use of social safety net programs later in life given the importance of education to a range of socioeconomic and health outcomes over the life course. In contrast to social assistance programs, social insurance programs are broadly available to all individuals. The specific criteria that define the access threshold are typically based on work-related credits, contributions to the program over the life course, age, specific medical conditions, and/or being the spouse or child of an eligible individual. Social insurance programs are designed to address needs associated with unemployment, retirement, illness, and disability. Although the unemployment rate had dropped to historically low levels prior to the advent of the COVID-19 pandemic in early 2020, the percentage of the unemployed who receive benefits has been relatively constant. Between 2010 and 2019, the unemployment rate dropped from 10% to 3.5% (U.S. Bureau of Labor Statistics 2020), but the unemployment insurance recipiency rate was consistently less than 30% (U.S. Department of Labor 2019). Nearly 20% of people in the United States receive Social Security benefits as retired workers, disabled workers, or spouses and dependent children of retired, disabled, or deceased workers. Almost 90% of adults aged 65 and older receive Social Security benefits, which are the single largest source of income for a majority of these older adults (U.S. Social Security Administration 2020; see also Street and Ní Léime in this volume). While almost all adults over the age of 65 receive Medicare, some older adult immigrants fall through the cracks and are uninsured due to conflicting priorities at the nexus of immigration and health care policies (Stewart and London 2015). Given that U.S. social programs are not as extensive or generous as other welfare states (see Harrington Meyer and Kandic in this volume), employmentbased benefits are a crucial part of the social safety net. Although employers provide these benefits to attract and retain employees, the government influences

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these benefits through legislation and regulations that require or incentivize employers to provide their employees with private pension programs, health care insurance, family and medical leave, and flexible spending accounts for child care and health care. In 2019, the percentages of civilian workers with employer-provided retirement benefits, medical care benefits, life insurance, and paid sick leave were approximately 70%, 70%, 60%, and 76% respectively (U.S. Bureau of Labor Statistics 2019). It is important to note that these figures do not capture activeduty military personnel and some veterans, who have access to a range of benefits through the Department of Defense and Department of Veterans Affairs. Military service-connected benefits provide an additional layer to the social safety net of those who have served in the military and their family members (Wilmoth, London, and Heflin 2015; Wilmoth, London, and Landes 2020). The impact of these programs on the life course likely was substantial in older cohorts who came of age during World War II, the Korean War, and the Cold War, when military service among men was a normative part of the transition to adulthood (Wilmoth and London 2013). Although women’s participation in the military in these cohorts was structurally limited by policy and practice, these programs indirectly influenced women whose lives were linked to men who served in the military (Wilmoth and London 2021). This demonstrates how systemic discrimination based on characteristics like gender, race/ethnicity, nativity status, ability, and sexual orientation can shape program use and access to resources (see Homan in this volume for a discussion of structural sexism, policy, and the life course). Although often not considered in discussions of the social safety net, a progressive tax system is essential to raising revenues for means-tested and social insurance programs. In addition, the tax code can minimize use of the social safety net by providing credits and deductions that improve the finances of individuals and families (for a discussion of the home mortgage tax credit, see Fenelon in this volume). The United States has a progressive tax system, although it is less progressive than other industrialized countries and has become even less so in recent years (Greenstone and Looney 2012). Still, the U.S. tax code does retain some features that contribute to the social safety net, including: the child tax credit, which benefits all tax filers who have dependent children; the child and dependent care tax credit, which offsets some care costs for eligible earners; and the earned income tax credit (EITC), which benefits workers with low to moderate income. Over 90% of families with children receive the child tax credit (Tax Policy Center 2020a) because it is not means-tested. However, more-targeted and means-tested credits are used less. For example, 12% of families with children benefit from the child and dependent care tax credit (Tax Policy Center 2020b) and less than 20% of tax filers claim the EITC, although there is substantial variation in that percentage across states (Tax Policy Center 2020c; Pomerleau and Borean 2014). The U.S. tax code also allows for deductions, which tend to benefit higher-income taxpayers, who are more likely to

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itemize but less likely to need support from the social safety net. For example, tax filers with an adjusted gross income less than $50,000 make up less than 4% of home mortgage interest deduction claims, while those with incomes above $200,000 constitute 34% of the claims (Eastman and Tyger 2019). More lowand middle-income tax filers claim medical expenses than some of these other kinds of tax credits. In 2014, over 70% of the nearly nine million people who claimed medical expenses earned less than $75,000 (Schwartz and Rowell 2017). As this discussion demonstrates, the social safety net comprises a complex network of policies and programs that are used by large portions of the population. It is important to recognize that the participation rates provided above only offer a snapshot of use at a given time and that lifetime use of social safety net programs is likely to be much higher. To our knowledge, there are no studies that quantify social safety net program use over the life course. Nevertheless, it seems reasonable to surmise that all Americans benefit from the social safety net at some point in their lives and that most Americans benefit from various aspects of it throughout their lives.

Life-Course Perspectives on Public Policy Life-course scholars recognize that public policies helped to create the modern life course by establishing age-based criteria for participation in social programs and social life (Leisering 2002; Settersten 1999). Legislation and regulations established the ages for: entering and leaving school; marrying; working; serving in the military; voting; driving; and consuming controlled substances like cigarettes, alcohol, and now (in some places) marijuana. While relatively few lifecourse scholars explicitly study public policy and social programs, most implicitly take it into account when considering the first principle of the life-course perspective, which recognizes the importance of time and place in lives. Public policies, and their associated programs, are a defining feature of given historical time periods. For example, the 1960s are synonymous with a sea change in policy that was implemented through a broad array of legislation that established many of the programs that are discussed in the chapters of this volume. In a very short amount of time, President Lyndon Johnson’s “War on Poverty” and civil rights legislation passed by Congress laid the foundations for the passage of: the Food Stamp Act of 1964, which made Food Stamps a permanent program; the Economic Opportunity Act of 1964, which established Head Start and other programs; the Elementary and Secondary Education Act of 1965, which subsidized school districts containing a large portion of students living in poverty; the 1965 Social Security Amendments, which created Medicare and Medicaid; the Immigration and Nationality Act of 1965, which abolished the prior county-of-origin quota system in favor of priorities based on reuniting families and attracting skilled labor; the Civil Rights Act of 1964, which addressed segregation and employment discrimination; and the Voting Rights Act of

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1965, which prohibited discriminatory voting practices. These watershed policy initiatives and social programs fundamentally changed the socioeconomic and political landscape for many Americans and provided the members of cohorts coming of age after their passage a more equal, albeit still unequal, footing as they transitioned to adulthood. However, as the subsequent chapters demonstrate, the impact of legislation can vary by race/ethnicity, immigrant status, and gender. In addition, eligibility for programs like Medicaid and SNAP vary across states, which leads to substantial geographic variation in participation and benefits received (for a discussion of SNAP, see Heflin in this volume). Consequently, residents of certain states benefit from a stronger social safety net than others, which has wide-ranging implications for population health and well-being (Montez, Zajacova, and Hayward 2016; Montez, Hayward, and Wolf 2017). The life-course concept of timing highlights the importance of when during the life course individuals experience policy changes or access programs. Policy change or program use that occurs earlier in the life course or is appropriately timed is likely to have a greater impact. Furthermore, the length of time individuals participate in programs and the sequence of program participation also is a salient consideration. For example, low-income children who receive comprehensive education, family, and health services have improved educational and social outcomes through age 20 (Reynolds et al. 2001). As discussed in relation to criminal offending by Robey and Massoglia (in this volume), life-course timing considerations are strongly implicated in theory development and testing, in addition to the translation of scientific knowledge into policies and interventions. The life-course perspective recognizes the role of individual-level agency, which involves the choices people make when faced with a decision. Most policy-based programs involve someone making a decision about enrollment. In some cases, individuals are enrolled in a program by someone else (e.g., parents might enroll their children in Medicaid). Most often, individuals make their own decision about whether to participate in a program. Various programs have specific eligibility criteria that limit participation. However, many factors influence program participation, including: individual-level knowledge of and access to the program; experiences with prior program participation; attitudes toward program participation; concerns about stigma; functional limitations and disabilities that limit the ability to apply or maintain enrollment; language barriers; and expectations regarding program participation. Sometimes, front-line staff and the organization of the system contribute to diversion (Ridzi and London 2006). Collectively, these and other access barriers influence whether individuals seek out information about programs, decide to enroll in them, and choose to stay in them. Even when interventions aim to reduce barriers to access, they often do not overcome all obstacles to participation (Heflin, London, and Mueser 2013). Policies often are explicitly designed to take into account the life-course principle of linked lives, which highlights how the circumstances of one

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person’s life have ripple effects for their significant others. Many social programs make eligibility contingent on family relationships or household membership. For example, spouses and dependent children are able to receive Social Security and some veteran benefits. Other programs, such as TANF, Medicaid, SNAP, and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), base children’s eligibility on family income. Employment-based benefits often extend to a spouse and children, and the benefits delivered through the tax code, such as the mortgage interest deduction, affect the resources available to the entire household. These eligibility criteria reflect the inherent dependence of children on parents and the general interdependence of household members. Finally, the life-course principle of life-long development recognizes that individuals are constantly aging and changing over the course of their lives. The effects of program participation and access to the social safety net can accumulate and condition the effects of other aspects of the social safety net across the life course. Programs designed to meet the needs of individuals at one life-course stage might not adequately serve individuals at different life-course stages. Furthermore, growth and change are ongoing processes that are punctuated by sensitive periods, which set the stage for subsequent developmental stages. Therefore, programs that intervene at developmentally appropriate times might be more effective than those that do not take the developmental stage of the program participants into account.

Public Policy and Cumulative Inequality Life-course scholars, particularly those who are sociologists, recognize that inequalities emerge across the life course through cumulative (dis)advantage processes (see Dannefer and Han in this volume). Specifically, advantages and disadvantages compound over the life course. These compounding processes result in substantial differences in the social, economic, and health characteristics, and lived experiences, of groups that are defined by various socially constructed categories, including gender, race, ethnicity, immigrant status, ability, and sexual orientation. These structurally generated inequalities are transmitted intergenerationally. (Dis)advantage that accumulates over the life course is transmitted to younger generations within families, leading to the reproduction of inequality over historical time (Ferraro et al. 2009). Such compounding and intergenerational processes are rooted in social structure and deeply implicated in the contemporary circumstances of Blacks in the United States (see Boen in this volume). Policies, and their associated social programs, can potentially ameliorate cumulative inequality by rectifying and offsetting the consequences of the historical legacy of discriminatory policies and institutional practices. Policies and programs can be designed to: decrease exposure to risk (e.g., lead paint

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abatement programs for older homes); increase access to opportunity (e.g., grants that support college attendance), health care (e.g., Medicaid, Medicare), or housing (e.g., rental assistance programs); and enhance available resources (e.g., SNAP, cash payments to retirees). However, policies and programs also can exacerbate cumulative inequality by reinforcing and reifying the structural conditions that lead to group differences. For example, policies associated with the ongoing “War on Drugs” have resulted in unprecedented mass incarceration in the United States. Mass incarceration has compounded the long-standing, multifaceted structural racism that Black Americans experience given that those policies have disproportionately affected Black men, with dire consequences for their lives, the lives of their family members, and the communities in which they live. Despite the intended design of policies, it is essential to recognize their unintended consequences (see Dannefer and Han in this volume). These unintended consequences, which can be either positive or negative, can affect program participants, as well as those whose lives are linked to program participants through family or community ties. For example, Social Security, which is designed to provide income support to older adults, has positive unintended consequences for adult children because it helps to alleviate the need to provide financial support to aging parents. Conversely, that same program has negative unintended consequences for many women because the benefits calculation does not recognize their unpaid labor as caregivers. These unintended consequences also can ameliorate or exacerbate cumulative inequality.

Life-Course Perspectives on Specific Policies When assessing the efficacy of specific policies, and their associated programs, from a life-course perspective, it is helpful to consider Settersten’s (2003) framework for analyzing the intersection between human development and social policy. As shown in Table 1.2, this framework poses key questions that encourage a broad consideration of the ways in which policies reflect, address, and shape human lives. Similarly, reflecting the life-course principle of linked lives, the Family Impact Institute (2020) has developed a series of questions that facilitate family-friendly policies. Life-course scholars, policy makers, and program administrators should routinely ask themselves these questions as they consider the various short- and long-term consequences of policies and programs. The chapters in this volume draw on various life-course principles, cumulative (dis)advantage theory, and cumulative inequality theory to inform our understanding of the role of specific U.S. policies and programs in the lives of individuals and their consequences for inequality across groups. In considering policies and programs overall and in particular domains, they take into account many of the questions raised by Settersten (2003). “Process, Policy, and Unintended Consequences: The Life-Course Patterning of Cumulative (Dis)advantage” by Dale Dannefer and Chengming Han sets the stage

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TABLE 1.2 Settersten’s (2003) framework for analyzing the intersection between human

development and social policy  At what life domain(s) is a policy aimed?  What dimension(s) of human development does a policy address?  Does a policy intend to ameliorate, or even eliminate, something negative? Does it intend to actively promote something positive? Or does it intend to do both?  Is the temporal view of a policy more prospective or retrospective?  What model of the life course underlies a policy?  Does a policy relate to a certain segment of life or to the life course as a whole?  Is its vision of the life course rigid or flexible?  To what degree does a policy promote or prevent innovation in the life course?  Does a policy intend to reinforce, change, or reflect life patterns?  To what extent does a policy lag “behind the times”?  Whom does a policy target, whom does it exclude, and why?  What are its underlying assumptions about who is “at risk,” for what, and why?  What are its underlying assumptions about who should be helped (or who is worthy or help)?  What are its underlying assumptions/theory of change?  How do the effects of a policy come about?  Are its effects temporary or permanent?  What should occur in the short- and long-term?  What unintended effects might occur? And for whom? Note: Abridged from Table 1, p. 194 in Settersten (2003).

for later chapters by discussing the processes underlying cumulative (dis)advantage and considering the extent to which public policies can intervene in and offset those processes. Dannefer and Han draw a distinction between generic social processes, which are a part of everyday social life, and intentionally constructed processes, which are deliberate courses of action designed to accomplish a particular goal or outcome. By doing so, they are able to highlight how some aspects of life, and some mechanisms of cumulative (dis)advantage, are more likely to be changed by public policies and social programs than others, and that policies can generate both intended and unintended consequences. In “Structural Sexism and Life-Course Health: Implications for Public Policy,” Patricia Homan explains structural sexism at the micro-, meso-, and macro-levels and how it impacts health across the life course. Given mounting evidence that structural sexism is universally harmful and everyone would be healthier in a more gender-equal context, she effectively argues that policies created to promote gender equity also have enormous potential to improve population health. By explicitly drawing on the life-course principles of life-long development, timing, and linked lives, Homan identifies potentially fruitful avenues for future research. “Wealth Policy as Health Policy: A Population Aging and Racial Equity Perspective” by Courtney Boen draws on the literature on the social determinants of racial health disparities and cumulative (dis)advantage to demonstrate how rising

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wealth inequality has shaped individual- and population-level racial disparities in health. She proposes baby bonds and reparations as policy responses that have the potential to reduce large and persistent Black–White wealth gaps, which in turn might reduce Black–White health gaps. These broad-based policies, which are akin to social insurance, have the potential to disrupt persistent cumulative inequality that is deeply embedded in U.S. social structures. Baby bonds can circumvent early-life disadvantage by providing economic resources early in the life course, while reparations can rectify wealth gaps that plague Black adults of all ages. In “Understanding the Role of Housing Policy in Life-Course Health: HUD Rental Assistant and Health Outcomes for Children and Adults,” Andrew Fenelon examines how health outcomes for children and adults are influenced by housing policies. Fenelon argues that federal rental assistance programs, such as public housing, housing choice vouchers, and multifamily housing, can offset early-life disadvantage by providing low-income families with an income boost and promoting socioeconomic mobility as children transition to adulthood. However, as Fenelon demonstrates, the unequal structure of housing policy limits its effectiveness in reducing health inequalities across socioeconomic groups. Next, Colleen Heflin draws attention to “U.S. Food and Nutrition Policy Across the Life Course.” Like housing assistance, food and nutrition programs, such as SNAP, WIC, and school nutrition programs, are intended to provide support to low-income individuals and households. By providing access to food that encourages sufficient nutritional intake, these programs promote child development and health throughout adulthood. Yet, Heflin argues, these policies do not handle life-course transitions well, which leaves children transitioning to full-time school, young adults leaving their family of origin, and mature adults moving into retirement vulnerable. Jason Robey and Michael Massoglia draw on the life-course principle of timing in “Crime and Delinquency Over the Life Course: Adolescence, Peers, and Policy.” The expansion in the U.S. penal system over the past 40 years has led to increasingly harsh punishment and substantial incarceration rates, particularly for Black Americans. Robey and Massoglia argue that crime prevention strategies should focus on adolescent peer influences and call for more rigorous assessment of the ways in which peers influence the development of criminal behaviors during the critical life-course stage of adolescence. Appropriately designed and timed interventions have the potential to increase desistance and thereby disrupt criminal offending in adult life-course stages. Zoya Gubernskaya examines “Immigration Policies and the Health of Older Foreign-Born in the United States.” She makes the case that immigrant admission policies, immigrant naturalization policies, and immigration enforcement policies have a cumulative effect across the life course that shapes health disparities among older adults. Gubernskaya demonstrates how the life-course

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principles of linked lives and time and place can be used to understand the long-term impact of policies for specific groups. Jacqueline Angel and Sunshine Rote also consider the implications of policy for older adults in “The Future of Long-Term Care in the Latino Population: Where Will the Burden Fall?” After reviewing current long-term care policies, Angel and Rote focus on the challenges encountered by Latinos who are caregivers to older adults with dementia. Through the life-course principle of linked lives, Angel and Rote demonstrate how policies shape intergenerational care provision. They also explore different policy responses designed to address the confluence of defamilization and increasing long-term care needs within the Latino population. Madonna Harrington Meyer and Amra Kandic examine “How Social Policies Affect Grandparent Work.” They document the extensive involvement of American grandparents in providing care to grandchildren and how it varies by gender, race, and class. Then, they make the case that the policy context shapes the demand for grandparental involvement. Specifically, they argue that the limited support working families receive in the United States creates the need for grandparents to care and sometimes to sacrifice their own well-being for that of their children and grandchildren. Given programs that rely heavily on meanstesting, and no guarantees of paid vacation, paid sick leave, paid parental leave, or affordable and high-quality child care, working parents have to rely on grandparents for assistance. Harrington Meyer and Kandic provide insight into how this impacts the lives of older adults, for better and for worse. Finally, Debra Street and Áine Ní Léime focus on “Social Policies for Older Workers.” They note that U.S. policy makers have paid more attention to public policies that delay access to Social Security retirement benefits than to policies aimed at supporting adequate employment opportunities for different types of older workers. They argue that policies that can benefit older workers must confront the challenges of cumulative (dis)advantage, employment capacity, and the adequacy of employment opportunities for older workers. Policy makers must understand that some older workers are able to work longer and choose to do so because their jobs fulfill them, while other older workers can no longer work or must work, regardless of the constraints of their health and social circumstances. Street and Ní Léime discuss how policies related to delaying retirement, pension reform, work-family balance, and anti-discrimination might support older adult workers. The authors also provide sobering thoughts about how the COVID-19 pandemic presents new challenges. Collectively, these chapters paint a broad picture of the influence of public policies and their associated programs on life in the United States. The authors contribute to a broader understanding of how past legislation shapes current public policy debates and identify opportunities to strengthen the social safety net. Recent events worldwide and in the United States, including the COVID-19 pandemic and the strengthening of the Black Lives Matter social movement, have prompted public debate about the causes and consequences of long-standing

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inequalities. The life-course perspective offers a critical lens through which social inequalities can be understood. It shines a light on how inequalities develop and compound over time as people move from childhood through adulthood and then into later life through variable institutional, social, and economic contexts that are fundamentally structured by public policies and their associated social programs. It is our hope the chapters in this edited volume will inform current discourse on the pressing social challenges of our time, spur public policies that dismantle social structurest, which intentionally and unintentionally contribute to inequalities, and lead to the development of social programs that improve population health and well-being.

References Avendano, Mauricio and Ichiro Kawachi. 2014. “Why Do Americans Have Shorter Life Expectancy and Worse Health Than People in Other High-Income Countries?” Annual Review of Public Health 35:307–325. Bor, Jacob, Gregory H. Cohen, and Sandro Galea. 2017. “Population Health in an Era of Rising Income Inequality: USA, 1980–2015.” The Lancet 389:1475–1490. Chetty, Raj, David Grusky, Maximilian Hell, Nathaniel Hendre, Robert Maduca, and Jimmy Narang. 2017. “The Fading American Dream: Trends in Absolute Income Mobility Since 1940.” Science 356 (6336):398–406. Early Childhood Learning & Knowledge Center. 2020. “Head Start Program Facts: Fiscal Year 2019.” https://eclkc.ohs.acf.hhs.gov/about-us/article/head-start-program-fa cts-fiscal-year-2019. Eastman, Scott and Anna Tyger. 2019. “Home Mortgage Interest Deduction.” Tax Foundation. https://taxfoundation.org/home-mortgage-interest-deduction/. Escarne, Johannie G., Hani K. Atrash, David S. de la Cruz, Benita Baker, and Madelyn Rayes. 2017. “Introduction to the Special Issue on Healthy Start.” Maternal and Child Health Journal 21:1–3. Family Impact Institute. 2020. “The Impact Guide for Policy Makers: Viewing Policies Through the Family Impact Lens.” https://www.purdue.edu/hhs/hdfs/fii/wp-con tent/uploads/2015/06/fi_pmguide_0712.pdf. Ferraro, Kenneth F., Tetyana P. Shippee, and Markus H. Schafer. 2009. Cumulative Inequality Theory for Research on Aging and the Life Course. P. 413–433 in V.L. Bengtson, D. Gans, N.M. Putney, and M. Silverstein (eds) Handbook of Theories of Aging. New York: Springer Publishing Co. Greenstone, Michael and Adam Looney. 2012. “Just How Progressive Is the U.S. Tax Code?” Brookings Up Front Blog. https://www.brookings.edu/blog/up-front/2012/04/ 13/just-how-progressive-is-the-u-s-tax-code/. Heflin, Colleen M., Andrew S. London, and Peter R. Mueser. 2013. “Clients’ Perspectives on a Technology-Based Food Assistance Application System.” American Review of Public Administration 43 (6):658–674. Leisering, Lutz. 2002. Government and the Life Course. P. 205–228 in Jeylan T. Mortimer and Michael J. Shanahan (eds) Handbook of the Life Course. New York: Springer. Montez, Jennifer Karas, Mark D. Hayward, and Douglas A. Wolf. 2017. “Do U.S. States’ Socioeconomic and Policy Contexts Shape Adult Disability?” Social Science & Medicine 178:115–126.

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Montez, Jennifer Karas, Anna Zajacova, and Mark Hayward. 2016. “Explaining Inequalities in Women’s Mortality Between U.S. States.” SSM—Population Health 2:561–571. O’Rand, Angela M. 2003. Risk, Rationality and Modernity: Social Policy and the Aging Self. P. 225–249in K. Warner Schaie and Jon Hendricks (eds) Societal Impact on the Aging Self. New York: Springer. Pomerleau, Kyle and R. Borean. 2014. “Percentage of Filers Claiming the Earned Income Tax Credit in the States.” Tax Foundation. https://taxfoundation.org/percentage-filer s-claiming-earned-income-tax-credit-states/. Quadagno, Jill and Debra Street. 2006. “Recent Trends of U.S. Social Welfare Policy: Minor Retrenchment or Major Transformation.” Research on Aging 28 (3):3030–3316. Reynolds, Arthur J., Judy A. Temple, Dylan L. Robertson, and Emily A. Mann. 2001. “Long-Term Effects of an Early Childhood Intervention on Educational Attainment and Juvenile Arrest: A 15-Year Follow-Up of Low-Income Children in Public Schools.” Journal of the American Medical Association 258 (18):2339–2346. Ridzi, Frank and Andrew S. London. 2006. “‘It’s Great When People Don’t Even Have Their Welfare Cases Opened’: TANF Diversion as Process and Lesson.” Review of Policy Research 23 (3):725–743. Schwartz, Andrew and Alex Rowell. 2017. “Nearly 9 Million Americans Claim the Medical Expense Deduction.” Center for American Progress. https://www.americanp rogress.org/issues/economy/news/2017/11/09/442632/nearly-9-million-americans-cla im-medical-expense-deduction/. Scott, Ellen K., Andrew S. London, and Glenda A. Gross. 2007. “‘I Try Not to Depend on Anyone But Me’: Welfare-Reliant Women’s Perspectives on Self-Sufficiency, Work, and Marriage.” Sociological Inquiry 77 (4):601–625. Settersten, Richard A., Jr. 1999. Lives in Time and Place: The Problems and Promises of Developmental Science. Amityville, NY: Baywood Publishing. Settersten, Richard A., Jr. 2003. Rethinking social policy: Lessons of a life-course perspective. P. 191–224 in R. A. Settersten Jr., (ed.), Invitation to the Life Course: Toward New Understandings of Later Life. Amityville, NY: Baywood Publishing. Settersten, Richard A., Jr., and Barbara Ray. 2010. “What’s Going on With Young People Today? The Long and Twisting Path to Adulthood.” The Future of Children 20 (1):19–41. Settersten, Richard A., Jr., et al. 2020. “Understanding the Effects of COVID-19 Through a Life Course Lens.” Advances in Life Course Research 45:100360. https://doi. org/10.1016/j.alcr.2020.100360. Stewart, Karyn A. and Andrew S. London. 2015. “Falling Through the Cracks: Lack of Health Insurance Among Elderly Foreign- and Native-Born Blacks.” Journal of Immigrant and Minority Health 17 (5):1391–1400. Tax Policy Center. 2020a. “Briefing Book: What Is the Child Tax Credit?” https:// www.taxpolicycenter.org/briefing-book/what-child-tax-credit. Tax Policy Center. 2020b. “Briefing Book: How Does the Tax System Subsidize Child Care Expenses?” https://www.taxpolicycenter.org/briefing-book/how-does-tax-syste m-subsidize-child-care-expenses. Tax Policy Center. 2020c. “Briefing Book: What Is the Earned Income Tax Credit?” https:// www.taxpolicycenter.org/briefing-book/what-earned-income-tax-credit. U.S. Bureau of Labor Statistics. 2019. “Employee Benefits in the United States—March 2019.” https://www.bls.gov/news.release/pdf/ebs2.pdf.

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U.S. Bureau of Labor Statistics. 2020. “Labor Force Statistics from the Current Population Survey.” https://data.bls.gov/timeseries/LNS14000000. U.S. Census Bureau. 2015a. “Dynamics of Economic Well-Being: Participation in Government Programs, 2009–2012: Who Gets Assistance?” https://www.census.gov/con tent/dam/Census/library/publications/2015/demo/p70-141.pdf. U.S.. Census Bureau. 2015b. “Time Spent in Government Programs.” https://www. census.gov/content/dam/Census/newsroom/releases/2015/cb15-97_graphic.jpg. U.S. Department of Education. 2020. “Federal Pell Grant Annual Data Reports.” https:// www2.ed.gov/finaid/prof/resources/data/pell-data.html. U.S. Department of Labor. 2019. “Application and Recipiency CY 1988–2019.” https:// oui.doleta.gov/unemploy/images/carousel/application_and_recipiency.png. U.S. Social Security Administration. 2020. “Fact Sheet: Social Security.” https://www.ssa. gov/news/press/factsheets/basicfact-alt.pdf. Wilmoth, Janet M. and Andrew S. London. 2013. Life Course Perspectives on Military Service. New York: Routledge. Wilmoth, Janet M., Andrew S. London, and Colleen M. Heflin. 2015. “The Use of VA Disability Compensation and Social Security Disability Insurance Among WorkingAged Veterans.” Disability and Health Journal 8 (3):388–396. Wilmoth, Janet M., Andrew S. London, and Scott D. Landes. 2020. “A Population-Based Perspective on Health Care for U.S. Veterans.” Public Policy & Aging Report, 30 (1):6–11. Wilmoth, Janet M. and Andrew S. London. 2021. The Role of the Military in Women’s Lives. P. 181–200 in Kenneth F. Ferraro and Deborah Carr, eds., Handbook of Aging and the Social Sciences (9th ed). Boston: Elsevier.

2 PROCESS, POLICY, AND UNINTENDED CONSEQUENCES The Life-Course Patterning of Cumulative (Dis)advantage Dale Dannefer and Chengming Han

Over the past three decades, one of the more significant developments in lifecourse research has been attention to the intersection of age and inequality, and especially to the social processes that produce cumulative (dis)advantage (CDA) (Dannefer 2003, 2018/2020; Crystal and Shea 2002; Kelley 2020). CDA can be defined as “the systemic tendency for inter-individual divergence in a given characteristic…with the passage of time” (Dannefer 2003:S327), entailing processes by which “a favorable relative position (in society) becomes a resource that produces relative further gains” (DiPrete and Eirich 2006:271). The corollary is that an unfavorable initial relative position in society contributes to further relative disadvantage by reducing access to critical social, cultural, economic, political, and geographic resources. This concept has a long history both in social theory and in folk wisdom. It is reflected in many cultures in folk sayings like “the rich get richer, the poor get poorer” and “nothing succeeds like success.” A tendency for inequality within cohorts to increase as the cohort moves through the life course has been documented in multiple societies, and nowhere more compellingly than in the United States (Crystal, Shea, and Reyes 2016; O’Rand and Henretta 1999; Osberg 2002). Theoretical treatments of CDA have suggested that this apparently robust tendency can be accounted for, at least in substantial part, by a broad array of interacting social processes at the micro-, meso-, and macro-levels of society (Dannefer 2003, 2018/2020; Pallas and Jennings 2009). In his pioneering treatment of the concept of CDA (termed “cumulative causation”), Gunnar Myrdal attributed race relations in the United States in part to such general, systemic processes: there is no … tendency toward automatic self-stabilization in the social system…a change does not call forth countervailing changes but, instead,

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supporting changes, which move the system in the same direction as the first change but much further. Because of such circular causation, a social process tends to become cumulative and often to gather speed at an accelerating rate. (Myrdal 1957:13) Such tendencies appear at all levels of society (Bourdieu 1984; Dannefer 1987, 2003). At the macro-level, a currently vivid example is the tendency for the accumulation and concentration of capital and wealth in the United States (e.g., O’Connor 1986). At the organizational level, it has been documented in the dynamics involved in tournament mobility, based in organizational rules and practices that regulate mobility in schools and work organizations (Lucas 1999; Rosenbaum 1978). Organizations also are a key setting within which CDA plays out at the micro-level, as labeling and related ubiquitous tendencies of micro-interaction create, reinforce, and reproduce invidious differences (Holstein and Gubrium 2000; Kanter 2008). In each case, these CDA processes are general social system processes that can be observed without reference to the life course. However, their temporal durability and sustained intersection with historical and cohort-based processes, and with individual lives, gives them a sustained life-course relevance. In this chapter, we take up the general question of how social policy can address the processes underlying observed patterns of CDA. Can policy alter observed patterns of CDA? What kinds of policy initiatives are likely to counter systemic tendencies for inequality in power and resources to increase over the life course? How are we to understand the relation of such processes, policy, and life-course outcomes? Our goal is to provide some orienting thoughts for approaching such questions. In approaching a discussion of the nexus of social processes, policy, and life-course patterning, it is helpful to begin by considering what we mean by “process.” Specifically, we want to suggest a distinction between: (1) generic social processes, which are integral to everyday life and social order; and (2) intentionally constructed processes, which are deliberate plans of action that are devised and implemented with the goal and hope of influencing outcomes of interest, as is typically done in the domain of policy (e.g., reductions in crime, disease, or poverty, or the protection of existing social arrangements). As a second-order consideration, there also is a distinction in the domain of policy between intended and unintended consequences that is germane to discussions of phenomena such as CDA.

Generic Social Processes It is important to begin by recognizing that policy is not likely to change the most basic processes that generate inequality and produce CDA over the life course. These processes are inherent and pervasive in social life across contexts. This is nowhere truer than in micro-interaction, although such dynamics are generally opaque to the participants of a given social world. The production of

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inequality is built into basic reality-constructing processes, such as typification, labeling, and other modes of meaning-making in everyday activity and interaction (Berger and Luckmann 1967; Collins 2004; Bourdieu 1984). Making and sustaining meaning and order inevitably entails appraising differences between people and comparing and contrasting individuals, including age peers. Perhaps the first and still one of the best attempts to explicate how these processes relate to age and the life course was made in the earliest work of Vern Bengtson (1973), when he described the cycle of induced incompetence, which shows how social interaction works as a self-fulfilling prophecy. The cycle depicts an older person operating in an ageist social context, in which any breach of “normal competence” (say, a memory lapse) becomes confirmation bias for others. As the person’s competence is questioned, she herself might internalize a selfdefinition as incompetent. As this iterative process continues, it amplifies such effects, potentially leading to a full embrace of dependency or the sick role. Such cycles, which can be positive as well as negative (see Dannefer and Siders 2013), depict a set of dynamics that are generic to social life in most social settings and that have effects that tend to cumulate as an inherent feature of everyday life. It is important to recognize that this cycle is not something that occurs once in a while as an exceptional event; it is integral to human interaction generally. Although the cumulative implications of such processes, and their linkage to macro-level processes, was not explicated in Bengtson’s formulation, they have been in other research (see, e.g., MacLeod 1987). Many examples in the extant research literature make the cumulative effects of these dynamics across the life course clear, while also demonstrating that those effects are sometimes malleable and subject to modification by social intervention, including policy intervention. Such largely generic processes that might be the target of direct and intentional policy intervention also can be seen at the meso- and macro-levels—for example, in organizational and broader social dynamics. Examples of these include homosocial reproduction in work organizations (Kanter 2008; Rivera 2013) and, at the macro-level, a panoply of institutionalized social processes and practices operating continuously to reproduce obdurate patterns of social stratification. In the United States, such patterns are powerfully structured by multiple axes of discrimination that are embedded in the stock of knowledge of everyday life, including race, class, gender, sexual orientation, age, and ability. Such processes also are the appropriate targets of policy intervention.

Policy and Planning: The Intentional Construction of Social Processes In contrast to generic social processes, innumerable examples of deliberate, policy-driven plans to counter adverse circumstances have been devised for every level of social-system operation. Many such initiatives are directly targeted to exposing, disrupting, and ameliorating the effects of cycles like those Bengtson

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depicts, as well as other generic social processes that are seen as contributing to negative outcomes. At the micro-level, for example, various forms of awareness or sensitivity training for teachers represent efforts to counter stereotypes and labeling dynamics in K-12 education, and family therapy sessions typically entail efforts to break destructive cycles of interaction within families. As they are the products of deliberate design efforts, complex organizations lend themselves to policy interventions to counteract persistent biases. That is, indeed, the ostensible purpose of basic, Weberian bureaucratic rules that prohibit the use of particularistic criteria or personal preference or bias in allocating rewards. Beyond such basic rules, examples of such policies applied to meso-level entities include affirmative action policies and other such initiatives designed to address the unfair allocation of resources, rewards, or sanctions. Readily observable macro-level examples include national policies designed to redress inequalities in health care access or to guarantee voting rights in those contexts in which long-established social practices and cultural impulses operate to undermine them. At various times and with various degrees of effectiveness, policies and practices have been proposed and/or implemented to address such systemic sources of inequality (see Boen in this volume for a discussion of reparations to address the racial wealth gap). As is well known, many social policies represent macro-level initiatives designed to regulate the distribution of resources (see Fenelon in this volume for a discussion of housing assistance policies; see Heflin in this volume for a discussion of food assistance policies). This includes, of course, progressive policies designed to counteract the skewed distribution of resources deriving from both generic and intentional social processes. These policy interventions generally aim to ameliorate circumstances of adversity. This is especially clear in the case of initiatives designed to address hardship and adversity, where many well-known and successful social programs seek to address the circumstances of socially and economically disadvantaged persons. Such persons might be disadvantaged because they are caught in the maelstrom of adverse social dynamics or because they have suffered tragic events. It should be noted that the use of policy to affect the distribution of resources has not always been progressive; such policy initiatives also have included many regressive efforts designed to protect the assets of those already well off (e.g., relying on sales taxes to avoid taxing earnings) or preserve status quo arrangements. This was done, for example, through the design of Social Security rules in the 1930s that limited access of many Black citizens to the program by excluding domestic and agricultural work—common occupations for Black citizens at the time (Dannefer, Gilbert, and Han 2020). This was deemed necessary to secure the votes of Southern senators, which were essential to passing the Social Security Act of 1935 (Katznelson 2005; Poole 2006). Of course, progressive macro-level efforts include diverse forms of safety nets and ameliorative initiatives, often targeted to specific age groups. These include:

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preschool programs for kids; programs designed to support challenged families, such as the Farmers Market Nutrition Program (FMNP) of the Women, Infants, and Children Program (WIC); and job retraining for midlife adults or transfer payments for retirees. When implemented, such policies institutionalize structured dynamics that operate as new or reformed social processes. Examples of how such processes might affect inequality among age peers and trajectories of inequality over the life course exist in abundance (see Harrington Meyer and Kandic in this volume). In the context of life-course studies, a familiar and important instance concerns the establishment of pension programs. In the United States, Social Security (sometimes supplemented by private pensions) is credited with dramatic reductions in old-age poverty over the past century (Romig 2008). Additionally, elders and other vulnerable persons and families have come to rely on Medicare and/or Medicaid to provide what would for many be otherwise unaffordable health care. This remains true even though the support provided by these programs is remarkably modest compared with the benefits provided by state-sponsored retirement programs in many other societies (Hungerford 2017). In numerous advanced industrial societies, citizens need not wait for retirement to gain the benefits of public policy. In those societies, significant support is provided during childhood, adolescence, and midlife for meeting basic needs and educational advancement, in addition to support for citizens facing unemployment, health challenges, or other forms of hardship across the life course. This can take many forms. In Germany, federal work policies include Bildungsurlaub (literally “education vacation”), which allows workers to take time off annually to pursue learning. As noted by Harrington Meyer and Kandic (in this volume), the absence of many family policies provided in other countries shapes the demand and experience of grandparent care in the United States. While the United States generally does not provide the same level of social welfare supports that many advanced industrial societies do, it has at times provided a comprehensive suite of benefits to some. For example, the Servicemen’s Readjustment Act of 1944 (the “GI Bill”) provided financial support to returning servicemen in domains including home ownership, small business start-up, and education (Wilmoth and London 2013). It is associated with post-World War II mobility and the establishment of the middle class in the United States. Other policies implicitly and somewhat invisibly support the advantage of some segments of the population more so than others (see Fenelon in this volume). Whatever its strengths or limitations, no single policy-based process is likely to negate the generic tendencies toward inequality generation in social life. Nevertheless, many such policy-based efforts have had welcome and salutary effects, and it is readily possible to relate such policy-driven efforts to the underlying generic processes that create a need for intervention. As one example, consider the inequality-generating effects of social stratification in the socialization experiences of early childhood. Tracing the trajectory of learning over time

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highlights the cumulative effects of educational differences at the beginning of the life course. Opportunities for language learning in early childhood are clearly stratified by the education level of parents. For example, Hart and Risley (2003) found that more than 10 million (M) words are addressed to children 12 months of age in families headed by professional workers compared to approximately 9M and 4M words, respectively, for children from working-class and welfare-reliant families. Moreover, this inequality diverged further by age 4, when the numbers were 40M, 30M, and 11M, respectively. This set of outcomes is, of course, largely the product of the daily routines of face-to-face interaction in the home, in the neighborhood, and other domains of everyday interaction, which are accomplished through the operation of generic social processes (Lareau 2011). The need to address the costs of such circumstances to disadvantaged children has served as the catalyst for innumerable efforts at intervention over the past half century. Head Start is perhaps the best-known and most widely scrutinized of such efforts. Cunha and Heckman (2007) provide evidence that early childhood intervention and adolescent skill development programs like Head Start are effective in addressing such disadvantages. For example, they find young adults who had received intervention in childhood or adolescence were only about half as likely to depend on welfare, compared with those who had received no remedial intervention. Moreover, continuous intervention (both childhood and adolescence) had more than an additive effect: less than 15% of such young adults were on welfare, compared to the baseline population, and less than one-third of them were on welfare compared to those who received only childhood or adolescent intervention, but not both (Cunha and Heckman 2007; Dannefer, Kelley-Moore, and Huang 2016). This analysis clearly suggests that the developmental disadvantages across a range of domains—language development, access to health care, nutrition—might be constructively addressed by policies that dedicate resources to young people. Cunha and Heckman’s (2007) analysis also is instructive with respect to the policy implications of intervention at different ages, specifically with respect to the relative merits of programs targeting early childhood compared to interventions coming later. Their analysis clearly indicates that policy interventions targeting adolescents are just as effective, at least with respect to welfare dependency, as those focused on early childhood (Dannefer, Kelley-Moore, and Huang 2016; see also Robey and Massoglia in this volume for a discussion of crime-related interventions in adolescence). Of course, the degree to which such a similar pattern might be found for other characteristics remains to be seen. Other analyses have provided evidence for the impact of interventions during adulthood. Such evidence dates back to the earliest known analysis of withincohort trajectories of inequality (Dannefer and Sell 1988). This study documented a robust trend of increasing inequality over the life course across seven birth cohorts, but also a notable exception to the general trend—declining inequality for the “Good Times” cohort during their 40s (in the late 1960s and

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early 1970s). This trend reversal likely reflects the impact of the positive policy initiatives of the post-war period, including the GI Bill, education expansion, and the progressive changes advanced in the 1960s, which reduced inequality before the economic and political strains of the 1970s and the neoliberal policy reversals that began in the Carter and Reagan years. Such an interpretation suggests that the economic and political circumstances that cohorts experience across the years of adulthood have an immediate effect on the economic fortunes of their members, an effect that is largely independent of childhood effects. This popular narrative of the positive effects of benefits available during adulthood stands in contrast to the strong and growing emphasis on the importance of the circumstances of early childhood in life-course and epidemiological research on health over the life course. Numerous researchers have presented evidence of strong associations between childhood socioeconomic circumstances and an array of indicators of adult health and well-being (Hayward and Gorman 2004; Poulton et al. 2002; Haas 2008). However, a major unresolved question concerns whether these associations represent direct, immutable effects of childhood or whether they reflect a more indirect path, resulting from stratified opportunities that are either facilitated or foreclosed in early adulthood in ways that could be ameliorated. This issue has been the focus of vigorous debate between advocates of “latency” and “pathways” approaches (Dannefer 2018/2020; Keating and Hertzman 1999; Kuh and Ben-Shlomo 2004). Associations between early-childhood conditions and later-life outcomes often are remarkably strong. This empirical evidence, combined with the attractiveness of a model that can avoid the complexities of intervening adult circumstances, has given early-childhood arguments an immediate appeal for many researchers. As has been noted earlier, this is a debate rich in policy implications. One clear implication is the importance of investment in health and development in early childhood, something that no one disputes. If the events and circumstances of childhood are decisive, it follows that the scarce resources available for developing effective ameliorative strategies should be directed to the beginning decades of life. This could encourage the neglect of those who have endured childhood hardship in their adult years. By contrast, if evidence suggests that interventions beyond childhood can yield positive results, then there is clear warrant for allocating programmatic resources to the adult years and beyond (Dannefer, Kelley-Moore, and Huang 2016; Laub and Sampson 2003, 2019) and for not allowing investments in childhood to serve as a justification for triage of adults who have experienced adversity. Evidence of benefits of both childhood and adult investment would, of course, support cradle-to-grave investments in health and welfare similar to those made in some other countries. Evidence from those countries across multiple domains tends to support a “both-and” approach rather than an “either-or” approach. In some areas of health, it seems quite clear that policy initiatives targeted to individuals at key points in the life course could prove cost-effective. For example, nutritional education policies designed to enhance access to nutritional foods

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for young and midlife adults who have lacked the opportunity to develop healthful dietary practices could reduce obesity and the risk of diabetes or other health problems. New York City’s Food Retail Expansion to Support Health (FRESH) program is one such program designed to enhance the nutritional value of foods available to adults, as well as children. Similarly, the Universal Free Meals (UFM) program in middle schools in New York City has improved participation and academic performance for both poor and non-poor students (Schwartz and Rothbart 2020). The same might apply to adults in later life, whose health can be measurably improved by similar dietary changes and other health inputs, such as smoking cessation programs (Taylor et al. 2002; Anthonisen et al. 2005). Policies that support such programs, as well as policies that restrict access or provide disincentives to unhealthy food and sugary drinks, obviously are very important to pregnant and nursing mothers, as well as young children (Malik et al. 2006; Jacka et al. 2013). They also have been shown to have beneficial effects for adults of every age (Goetzel et al. 2007).

Intended and Unintended Consequences of Policy Initiatives Beyond the “generic/constructed” distinction, a second type of policy distinction to consider takes us back to the idea of latent functions or unintended consequences. There might be as many policies that affect CDA without having any intention to do so as there are policies designed to have such an effect. As an example, consider the transformative impact of military service, and especially wartime service, on individual lives and cohorts. The likelihood of serving in the military often derives from political and policy decisions that are made with virtually no forethought regarding their specific life-course consequences (Wilmoth and London 2013). More generally, consider the recent analysis of Crystal, Shea, and Reyes (2016), which reveals a dramatic increase in midlife inequality from the early 1980s to 2010. This puts older adults at risk for manifesting even greater levels of inequality than preceding cohorts as their members continue to age. When one considers conditions and events occurring in society in the first decade of this century, it appears unlikely that this increase is related to policies having anything to do with the life-course outcomes of these cohorts per se. Rather, the broad economic, military, and public relations policies of the U.S. government during the George W. Bush administration set the context that is generally credited with causing the economic crisis of 2008. During the Great Recession of 2008, less advantaged families experienced greater declines than wealthier households, which means wealth inequality also increased between rich and poor (Pfeffer et al. 2013). More generally, recession has been identified as a robust predictor of worsening mental health, apparently owing to unemployment and related financial strains (Modrek et al. 2013). In this way, recession further aggravates the relentless effects of the socioeconomic gradient and CDA processes.

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When events or circumstances transcend national boundaries, as did the Great Recession, the role of policy in creating a differential impact might also be seen by making comparisons across nations. For example, health disparities during the Great Recession increased in Southeast Asian countries, whereas there is no evidence of worse health inequality during recession in European counties. This is apparently due to the buffering effects of social policies, such as public health care programs in European countries (Mackenbach et al. 2018). In the United States, the American Recovery and Reinvestment Act of 2009, as well as the expansion of Medicaid, are claimed to “have had substantial buffering effects on health, especially among poor women and their children” (Modrek et al. 2013:1). It would be interesting to know if these effects have reduced health disparities in the United States. What is known about the United States during this period is that the wealth gap between rich and poor, as well as among different racial/ethnic groups, has continued to increase despite the Act’s implementation in 2009 (Saez 2018) and other intentional policy efforts aimed at addressing the effects of the Great Recession. Whether those policies will have unintended consequences for CDA processes remains to be seen. The life-course importance of linked lives too often has been neglected by policy makers. For instance, generous and job-protected paid leave not only provides support to employees, but also protects mothers’ mental health and predicts lower infant mortality rates (Chen et al. 2016; Patton et al. 2017; Montez 2020; Bullinger 2019). While correlation does not prove causality in such matters, it is telling to note that U.S. policies provide the most limited paid maternal leave among Organization of Economic Cooperation and Development (OECD) countries and are accompanied by higher infant mortality rates than European countries (Chen et al. 2016). The importance of linked lives has increased in the context of COVID-19. The combination of a high level of transmissibility with a high level of risk for adverse effects has created a general awareness of the need to regulate physical distance from others. This has a special impact within families, where the realities of physically living together and the need to interact in workplaces, markets, and other extra-familial locations differentially influence risks within the household. Another example is the unintended benefits of minimum wage for health outcomes. States in which the minimum wage is above the federal wage reported lower infant mortality, teenage parenthood, and death rates from heart disease among working-age adults (Van Dyke et al. 2018; Montez 2020).

Unintended Consequences of Generic Processes? COVID-19 and Intentional Social Processes The experience of the United States with the COVID-19 pandemic offers an immensely tragic, yet clearly telling, example of what happens when generic social processes take their course, unchecked by an effective effort to design and

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implement policy initiatives that might counteract them. Comparative analysis makes clear the disastrous effects of the U.S. response to COVID-19 relative to that of other advanced postindustrial societies, which (as of this writing) appear to have succeeded in avoiding uncontrolled spread. The United States has 20% of the world’s COVID-19 cases and deaths, respectively, even though it has about 4% of the world’s population. Beyond the societal-level data, the operation of generic social processes is especially clear in the distribution of COVID-19 morbidity and mortality within the United States, where the risk differentials of COVID-19-related morbidity follow the lines of race and class inequality, accentuated by age-related vulnerabilities. For example, people aged 85 and older experienced the highest mortality (10–27%), followed by people older than 65 and younger than 84 (3–11%) (Centers for Disease Control and Prevention 2020a). In addition, age-adjusted hospitalization rates are much higher among Hispanics and Blacks, nearly four times higher than Whites (Centers for Disease Control and Prevention 2020b). In Chicago, Hispanics reported the highest mortality (187/100,000), followed by African Americans (184/100,000). Meanwhile, the mortality rate for Whites was 93/100,000 as of May 2020 (Hooper, Nápoles, and Pérez-Stable 2020).

Conclusion In this chapter, we have sought to set forth some foundational distinctions for considering the interaction of processes of CDA and social policy. We began by suggesting the importance of distinguishing between CDA processes that are generic to social life everywhere from deliberate processes set in motion by specific efforts at influencing such generic social tendencies. We also argued for the importance of recognizing that policies deliberately designed to influence CDA processes have sometimes been regressive as well as progressive in intent, reflecting the political nature of policymaking. Although generic processes operate at multiple levels of social-system operation (i.e., micro, meso, and macro), interventions typically are targeted to a specific level. They often also are targeted to specific ages, which is a matter that can be informed by sociological, epidemiological, and other research on the life course. The policy implications of research are well illustrated by the ongoing “latency/pathways” debate in the study of health trajectories and the linkage between circumstances in childhood and adulthood. Finally, we note that, as often as not, the effects of policy over the life course might be altogether unintended or indirect. We illustrated this by considering the policy decisions associated with the Great Recession of 2008, which in their intent had nothing to do with age or the shaping of life-course trajectories. Arguably, the policy framework that produced the Great Recession had an impact on individual and family well-being that was greater in magnitude than policies designed to have a direct effect on CDA processes and life-course

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outcomes. Such considerations are relevant to the discussions that follow in this volume, as well as the framing of future research on CDA.

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3 STRUCTURAL SEXISM AND LIFE-COURSE HEALTH Implications for Public Policy Patricia Homan

Life-course scholars long have been interested in the health consequences of social inequality. Decades of research in this area indicate that exposure to socioeconomic disadvantage and interpersonal discrimination has harmful longterm effects on the health and well-being of individuals (Hayward and Gorman 2004; Williams, Lawrence, and Davis 2019). This vast literature has focused primarily on individual-level behaviors, exposures, and resources. However, several emergent lines of health disparities research are beginning to explore more macro-level structural factors in order to further our understanding of the ways in which discriminatory social systems affect health. This new area of inquiry, which includes research on structural sexism, structural racism, and other types of structural stigma or discrimination, is still in its infancy and has not yet fully engaged with life-course perspectives or developed and tested policy interventions aimed at reducing structural inequalities and improving population health. In this chapter, I review the emerging literature on structural sexism and health and then provide a framework for considering how gender equity policy can improve population health. Additionally, I discuss how all other types of public policies (i.e., those not explicitly related to gender equity) also can shape and be shaped by structural sexism in ways that influence health. I close by outlining how life-course scholars can push this important line of research and policy analysis forward.

Structural Sexism and Health Despite the tremendous gains made by women during the past 50 years in terms of educational attainment, paid employment, and formal legal protections from discrimination, gender inequality remains a persistent problem in the United

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States (Cotter, Hermsen, and Vanneman 2011; England 2010; Scarborough and Risman 2018). Although women’s college graduation rates now exceed men’s (Goldin, Katz, and Kuziemko 2006), women continue to be underpaid in the labor market, unequally burdened by unpaid domestic labor, and underrepresented in positions of economic and political power. For example, among full-time, year-round workers in 2018, women’s earnings were 81% of men’s (U.S. Bureau of Labor Statistics 2018). Regardless of their increasing involvement in the paid labor market, women still spend about twice as much time on child care and about three times as much time on housework than men (Bianchi et al. 2012). Gender inequity at the highest levels of business leadership is even more pronounced; only 5.2% of S&P 500 company CEOs were women as of December 2019 (Catalyst 2019). In the political realm, on average, the percentage of state legislature seats held by women in 2019 was 28.9%, and women achieved equal representation in only one state—Nevada—where they occupied 52.4% of the seats (CAWP 2019). This type of persistent gender inequality in a society can profoundly shape the life chances, health, and well-being of its members, even if it is not directly perceived or conceptualized as discriminatory. Thus, a new structural sexism and health literature has emerged that aims to understand the broader population health consequences of living in a social environment where power, resources, roles, and opportunities are unequally distributed along gender lines. Structural sexism refers to systematic gender inequality in power and resources manifest in a given gender system (Homan 2019). Because gender systems are multilevel social structures (Risman 2004), structural sexism exists at multiple levels: at the macro-level, in large-scale social institutions; at the meso-level, in interactional settings, such as neighborhoods, workplaces, marriages, and families; and at the micro-level, where sexism is internalized and embodied by individuals (Homan 2019). This chapter focuses on macro-level structural sexism because it has received the least attention in the gender and health literature, and because it is particularly amenable to state and federal policy interventions. Table 3.1 provides a conceptual overview of the ways that macro-level structural sexism can manifest across four key domains: political, economic, cultural, and physical/reproductive. Systematic gender inequality can be observed in each of these areas and many more. For example, structural sexism in the political domain manifests in the degree to which men and women are unequal in both their numerical representation in state legislatures and their positions within certain committee or executive roles that would afford them power over resource allocation and major decisions. In the economic domain, one can see structural sexism in the well-known patterns of gender-related job segregation, gender wage gaps, and the underrepresentation of women in powerful business and professional positions. Structural sexism in the cultural domain consists of the marginalization of women in religious organizations and the media, as well as wide-spread popular beliefs and stereotypes regarding women’s value,

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competence, natural abilities/tendencies, and appropriate roles in social life. Finally, structural sexism in the physical/reproductive domain appears in the differential affordance of bodily autonomy and appropriate medical care to women and men. It also is evident in the curtailment of sexual and reproductive freedoms, as well as in legal and cultural perspectives related to sexual violence. Many of these issues have been studied individually, and a nascent body of research is beginning to connect systemic sexism across multiple domains to indicators of population health and well-being in the United States. For example, Homan (2019) used a six-item structural sexism index, with items representing each of the four domains measured at the U.S. state level, and found that living in a state with higher levels of structural sexism was associated with more chronic conditions, worse self-rated health, and worse physical functioning among women and men in midlife. Other work using various composite measures of women’s status or gender equity in U.S. states also has found that systemic gender inequality is related to higher depressive symptoms among women (Chen et al. 2005), higher mortality rates/risk among both women and men (Kavanagh, Shelley, and Stevenson 2017; Kawachi et al. 1999), and higher state infant mortality rates (Kawachi et al. 1999; Koenen, Lincoln, and Appleton 2006). Understanding why structural sexism would be harmful for women’s health is relatively straightforward given that they are the oppressed group. Living in a more sexist environment is likely to reduce women’s access to health-promoting factors (such as material resources, quality health care, self-esteem, autonomy, and social support) and to increase women’s exposure to health-harming factors (such as violence, discrimination and harassment, stress, low subjective social status, and poor employment conditions) (Homan 2019). TABLE 3.1 Conceptual overview of domains in which macro-structural sexism occurs

Political domain Numerical legislative representation Administrative (decision-making) power Lobbying/special interest $$ and representation Economic domain Gender wage gap Gender segregation of jobs Business leadership representation Labor force participation Feminization of poverty

Cultural domain Marginalization of women by religious institutions Media (coverage, representation, and images) Wide-spread gender beliefs and norms Physical/reproductive domain Bodily autonomy Medical care Abortion and contraception (legality and access) Sexual assault/consent (prevalence/laws/ education)

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Evidence shows, however, that structural sexism harms men’s and children’s health as well as women’s health. The fact that structural sexism exhibits a pattern of universal harm is consistent with theory and evidence in three related areas of research. First, research on types of structural inequality other than sexism and health indicates that inequality can harm everyone in a society because it damages social relationships, increases competition for dominance, and undermines the safety, productivity, and well-being of the entire society (Wilkinson and Pickett 2011). Second, studies of masculinities and men’s health suggest patriarchal social systems can foster constructions of masculinity that are “toxic” for men’s health because of increased pressure to engage in risk-taking and unhealthy behaviors (Connell 2012; Courtenay 2000) as well as stress associated with being a family’s sole provider (King et al. 2020). Third, cross-national, comparative research in the developing world shows that gender equity is integral to economic development and improvements in population health (World Bank 2011). The evidence is particularly strong for child health, which repeatedly has been shown to improve with women’s empowerment (Pratley 2016). Thus, theory and research suggest that structural sexism is a broad public health problem.

Improving Health Through Gender Equity Policy A key implication of this research is that gender equity policy also is smart health policy. Given mounting evidence that structural sexism is universally harmful and everyone would be healthier in a more gender-equal context, policies created to promote gender equity also have enormous potential to improve population health. Policies aiming to increase women’s political representation, strengthen equal pay and anti-discrimination laws, reduce workplace harassment, prevent sexual assault and domestic violence, secure access to and funding for reproductive health services (including contraception and abortion), or otherwise advance gender equity are crucial from social justice and human rights perspectives. These policies (and many others) are essential for women’s equal citizenship and full participation in social, political, and economic life. Additionally, by reducing structural sexism, these policies also can translate into population health gains for all members of society, not only for women.

Improving Health Through Gender Equity in All Policies In addition to policies with the explicit goal of increasing gender equity, other types of policies that are not obviously gendered can shape and be shaped by structural sexism in ways that are relevant for population health. Figure 3.1 provides a conceptual framework for understanding the relationships among structural sexism, public policy, and health. Both structural sexism and public policy can directly influence health because both affect individuals’ health risk factors and resources, such as: living and working conditions, stress exposure, material

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resources, psychosocial resources, and health care. The black arrows depict the pathway through which a wide variety of public policies can influence health indirectly by increasing or decreasing structural sexism via their impact on the gendered distribution of resources. Even seemingly gender-neutral policies, such as those focused on issues like housing, nutrition, crime, immigration, work and retirement, health care, welfare, transportation, wealth, and taxes, often create or exacerbate unequal distributions of power and resources along gendered lines. The resulting structural sexism has important consequences for population health. Moving in the opposite direction, the white arrows illustrate how the amount of structural sexism that already exists across various domains in a society will influence which policies are enacted and how they are implemented. Studies show that when women have political power, they often influence social policy in ways that promote education, health care, social programs, and other expenditures that improve health for the entire population (Bolzendahl and Brooks 2007). Furthermore, when more women are empowered to be leaders in other sectors, such as business, health care, engineering, and urban planning, there will be more products, treatments, programs, and designs that meet women’s needs as well as men’s (Caroline 2019). Finally, structural pluralist perspectives indicate that bringing a diverse group of voices to the table improves the health of the entire society through the shaping of public policies that promote universal wellbeing (Young 2001). In sum, the reciprocal relationships between structural sexism and public policies suggest that a combination of gender equity policies and a push for gender equity in all policies is a promising approach for population health improvement.

FIGURE 3.1

A conceptual framework for understanding the relationships among structural sexism, public policies, and health.

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Moving Forward: Research and Policy with a Life-Course Approach Research on structural sexism and health is still at an early, formative stage of development. There is a great deal more work to be done in order to first identify and measure structural sexism in various settings and then to develop policy interventions to address it. As I elaborate below, it is my contention that the integration of structural sexism and life-course perspectives is imperative to advance both of these areas. First, regarding academic research, the largest gaps in current knowledge of how structural sexism works to shape health are all related to core life-course concerns, including life-long development, timing of events, and linked lives (Elder, Johnson, and Crosnoe 2003). A rich tradition of research and theory has built a gendered life-course approach to understanding how biographical, historical, and structural forces differentially shape men’s and women’s lives as they age (Moen 2001). However, the emerging structural sexism research has not yet interfaced with this scholarship; therefore, very little is known about how sexism and its health effects fluctuate and compound over the life course. For example, are different types of sexism measures necessary for different stages in the life course because some aspects of the gender structure are more salient at certain stages? Are there critical or sensitive periods for exposure to structural sexism that have more serious or longer-term effects on health? Does structural sexism exposure through the families, neighborhoods, and institutions that shape one’s early life continue to affect health in later life? Additionally, the principle of linked lives helps make sense of the finding that sexism is universally harmful by pointing to the way that institutional contexts serve as a general link across all individuals living in a specific time and place. This principle also raises questions about the transmission of sexism exposures and effects between people who are even more closely linked. For instance, are married men more harmed by macro-level structural sexism than unmarried men because they are more closely linked to women, who are the most affected group? How does structural sexism exposure experienced by parents affect their children? These and many more key questions remain for life-course scholars to address. Second, in terms of policy applications, a consideration of life-course principles can enable us to design effective policies by helping us identify sensitive periods during which specific types of interventions can produce lasting gains, not only for individuals, but for generations of families whose lives are inter-connected. For example, focusing on the midlife period could be a powerful intervention strategy because a substantial gender wage gap and an unequal burden of caregiving responsibilities (for both young children and aging parents) occur at this life stage (Bird and Fremont 1991; Grigoryeva 2017; U.S. Department of Labor 2017). These manifestations of structural sexism undermine women’s economic success and harm their health (Homan 2019). The economic and health

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disadvantages generated by these midlife sexism exposures then accumulate with age to create massive gender inequalities by retirement (Harrington Meyer 1990). For example, at age 65 and over, women are 80% more likely than men to be impoverished (Brown et al. 2016). Attention to cumulative (dis)advantage processes (see Dannefer and Han in this volume) leads to a recognition that women retiring today have a resource profile that was shaped by a lifetime of exposure to structural sexism. Therefore, policy interventions are needed both to rectify gender inequity among current retirees and to change the structural conditions earlier in the life course that set these trajectories of gender inequality in motion. If we intervene now at midlife with policies that strengthen equal pay laws, reduce the gender wage gap, and provide caregiver leave and benefits, then we can dramatically reduce the later-life inequalities that would otherwise have occurred as this generation ages. This could improve population health over the longer-term. The need for such midlife interventions has become especially acute in the context of the COVID-19 pandemic, which has exacerbated gender inequalities in child care and paid employment, disproportionately harming women’s careers. In the first three months of the pandemic, mothers reduced their work hours five times more than fathers and the gender gap grew by 20–50% (Collins et al. 2020). Thus, establishing guaranteed paid family and medical leave, increasing child care subsidies, and expanding publicly funded early childhood care are now urgent policy priorities in the short-term that also can reduce future gender inequalities and continue to pay health dividends for women in the future. Attention to the linked lives principle points toward another reason why midlife interventions might be particularly effective for improvements in population health. In addition to providing long-term benefits to middle-aged women, these policies also would provide more immediate benefits to the network of family members for whom they provide support and care. For instance, research shows that in addition to improving women’s health and economic outcomes in midlife, paid parental leave also improves health and survival among infants and children (Nandi et al. 2018). Moreover, caregiver leave policies also could improve the health of older, retirement-aged adults in at least two ways: (1) by allowing their adult children the flexibility to care for them as they age; and (2) by relieving pressure put on them to engage in intensive caregiving for their grandchildren (Harrington Meyer and Kandic 2017; see also Harrington Meyer and Kandic in this volume). This example illustrates the promise of life-course perspectives for generating valuable insights to inform public policy. In sum, many critical tasks remain for researchers and policy makers seeking to understand and address structural sexism and its population health consequences. With a rich theoretical tradition and an ever-expanding methodological toolkit, life-course scholars are uniquely positioned to make these kinds of important contributions to science and policy that will help create a more equal and healthier future for everyone.

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References Bianchi, Suzanne M., Liana C. Sayer, Melissa A. Milkie, and John P. Robinson. 2012. “Housework: Who Did, Does or Will Do It, and How Much Does It Matter?” Social Forces 91 (1):55–63. Bird, Chloe E. and Allen M. Fremont. 1991. “Gender, Time Use, and Health.” Journal of Health and Social Behavior, 32 (2):114. https://doi.org/10.2307/2137147. Bolzendahl, Catherine and Clem Brooks. 2007. “Women’s Political Representation and Welfare State Spending in 12 Capitalist Democracies.” Social Forces 85 (4):1509–1534. https://doi.org/10.1353/sof.2007.0061. Brown, Jennifer, Nari Rhee, Joelle Saad-Lessler, and Diane Oakley. 2016. “Shortchanged in Retirement: Continuing Challenges to Women’s Financial Future.” National Institute on Retirement Security. Available at https://www.nirsonline.org/reports/shortcha nged-in-retirement-continuing-challenges-to-womens-financial-future/. Catalyst. 2019. “Women CEOs of the S&P 500.” https://www.catalyst.org/research/ women-ceos-of-the-sp-500/. CAWP. 2019. “Women in State Legislatures 2019.” Center For American Women in Politics. https://www.cawp.rutgers.edu/women-state-legislature-2019. Chen, Ying-Yeh, S. V. Subramanian, Doloros Acevedo-Garcia, and Ichiro Kawachi. 2005. “Women’s Status and Depressive Symptoms: A Multilevel Analysis.” Social Science & Medicine 60 (1):49–60. https://doi.org/10.1016/j.socscimed.2004.04.030. Collins C., L.C. Landivar, L. Ruppanner, and W.J. Scarborough. 2020. “COVID-19 and the Gender Gap in Work Hours.” Gender Work and Organization 2020:1–12. https:// doi.org/10.1111/gwao.12506. Connell, Raewyn. 2012. “Gender, Health and Theory: Conceptualizing the Issue, in Local and World Perspective.” Social Science & Medicine 74 (11):1675–1683. https://doi. org/10.1016/j.socscimed.2011.06.006. Cotter, David, Joan M. Hermsen, and Reeve Vanneman. 2011. “The End of the Gender Revolution? Gender Role Attitudes from 1977 to 2008.” American Journal of Sociology 117 (1):259–289. Courtenay, Will. 2000. “Constructions of Masculinity and Their Influence on Men’s Well-being: A Theory of Gender and Health.” Social Science & Medicine 50 (10):1385– 1401. https://doi.org/10.1016/S0277-9536(99)390–391. Elder, Glen H., Jr., Monica Kirkpatrick Johnson, and Robert Crosnoe. 2003. The Emergence and Development of Life Course Theory. P. 3–19 in Jeylan T. Mortimer and Michael J. Shanahan, eds., Handbook of the Life Course. https://doi.org/10.1007/ 978-0-306-48247-2_1. England, Paula. 2010. “The Gender Revolution Uneven and Stalled.” Gender & Society 24 (2):149–166. Goldin, Claudia, Lawrence F. Katz, and Ilyana Kuziemko. 2006. “The Homecoming of American College Women: The Reversal of the College Gender Gap.” Journal of Economic Perspectives 20 (4):133–156. Grigoryeva, Angelina. 2017. “Own Gender, Sibling’s Gender, Parent’s Gender: The Division of Elderly Parent Care among Adult Children.” American Sociological Review 82 (1):116–146. Harrington Meyer, Madonna. 1990. “Family Status and Poverty Among Older Women: The Gendered Distribution of Retirement Income in the United States.” Social Problems 37 (4):14.

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Harrington Meyer, Madonna and Amra Kandic. 2017. “Grandparenting in the United States.” Innovation in Aging 1 (2):1–10. https://doi.org/10.1093/geroni/igx023. Hayward, Mark D. and Bridget K. Gorman. 2004. “The Long Arm of Childhood: The Influence of Early-Life Social Conditions on Men’s Mortality.” Demography 41 (1):87– 107. https://doi.org/10.1353/dem.2004.0005. Homan, Patricia. 2019. “Structural Sexism and Health in the United States: A New Perspective on Health Inequality and the Gender System.” American Sociological Review 84 (3):486–516. https://doi.org/10.1177/0003122419848723. Kavanagh, Shane A., Julia M. Shelley, and Christopher Stevenson. 2017. “Does Gender Inequity Increase Men’s Mortality Risk in the United States? A Multilevel Analysis of Data from the National Longitudinal Mortality Study.” SSM—Population Health 3:358– 365. https://doi.org/10.1016/j.ssmph.2017.03.003. Kawachi, Ichiro, Bruce P. Kennedy, Vanita Gupta, and Deborah Prothrow-Stith. 1999. “Women’s Status and the Health of Women and Men: A View from the States.” Social Science & Medicine 48 (1):21–32. https://doi.org/10.1016/S0277-9536(98)00286-X. King, T. L., M. Shields, S. Byars, A.M. Kavanagh, L. Craig, and A. Milner. 2020. “Breadwinners and Losers: Does the Mental Health of Mothers, Fathers and Children Vary by Household Employment Arrangements? Evidence From Seven Waves of Data From the Longitudinal Study of Australian Children.” American Journal of Epidemiology. https://doi.org/10.1093/aje/kwaa138. Koenen, Karestan C., Alisa Lincoln, and Allison Appleton. 2006. “Women’s Status and Child Well-Being: A State-Level Analysis.” Social Science & Medicine 63 (12):2999– 3012. https://doi.org/10.1016/j.socscimed.2006.07.013. Moen, Phillis. 2001. The Gendered Life Course. P. 179–196 in Robert H. Binstock and Linda K. George, eds., Handbook of Aging and the Social Sciences. San Diego, CA: Academic Press. Nandi, Arijit, Deepa Jahagirdar, Michelle C. Dimitris, Jeremy A. Labrecque, Erin C. Strumpf, Jay S. Kaufman, Ilona Vincent, Efe Atabay, Sam Harper, Alison Earle, and S. Jody Heymann. 2018. “The Impact of Parental and Medical Leave Policies on Socioeconomic and Health Outcomes in OECD Countries: A Systematic Review of the Empirical Literature: Parental and Medical Leave Policies in OECD Countries.” The Milbank Quarterly 96 (3):434–471. https://doi.org/10.1111/1468-0009.12340. Pratley, Pierre. 2016. “Associations Between Quantitative Measures of Women’s Empowerment and Access to Care and Health Status for Mothers and Their Children: A Systematic Review of Evidence from the Developing World.” Social Science & Medicine. https://doi.org/10.1016/j.socscimed.2016.08.001. Risman, Barbara J. 2004. “Gender as a Social Structure: Theory Wrestling with Activism.” Gender and Society 18 (4):429–450. Scarborough, William J. and Barbara J. Risman. 2018. Gender Inequality. P. 339–362 in A.J. Treviño (ed) The Cambridge Handbook of Social Problems. Cambridge University Press. U.S. Bureau of Labor Statistics. 2018. “Highlights of Women’s Earnings in 2018: BLS Reports.” https://www.bls.gov/opub/reports/womens-earnings/2018/home.htm. U.S. Department of Labor. 2017. “Women’s Earnings and the Wage Gap [Issue Brief].” https://www.dol.gov/wb/resources/Womens_Earnings_and_the_Wage_Gap_17.pdf. Wilkinson, Richard and Kate Pickett. 2011. The Spirit Level: Why Greater Equality Makes Societies Stronger (Reprint edition). New York: Bloomsbury Press. Williams, David R., Jourdyn A. Lawrence, and Brigette A. Davis. 2019. “Racism and Health: Evidence and Needed Research.” Annual Review of Public Health 40 (1):105– 125. https://doi.org/10.1146/annurev-publhealth-040218-043750.

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World Bank. 2011. World Development Report 2012: Gender Equality and Development. http://elibrary.worldbank.org/doi/book/10.1596/978-0-8213-8810-5. Young, Frank W. 2001. “Structural Pluralism and Life Expectancy in Less-Developed Countries: The Role of Women’s Status.” Social Indicators Research 55 (2):223–240. http s://doi.org/10.1023/A:1010982822560.

4 WEALTH POLICY AS HEALTH POLICY A Population Aging and Racial Equity Perspective Courtney Boen

Few topics have garnered as much discussion and debate as reparations. Offered as a means to acknowledge the long-term harms caused by slavery, Jim Crow laws, and other forms of institutionalized racism and to provide restitution and reconciliation to the descendants of enslaved individuals, reparations have received support—and push-back—from candidates and advocates across the political spectrum. Proponents argue that reparations would help to close the persistent racial wealth gap in the United States, the early roots of which scholars trace to slavery and the failure of the U.S. government to provide “40 acres and a mule” to formerly enslaved individuals during Reconstruction (Darity and Mullen 2020). The Black–White wealth gap in the United States has widened over the last century—exacerbated by Jim Crow, redlining, and more contemporary forms of racial discrimination, violence, and injustice—with recent estimates indicating that Black Americans own between 5 and 9 cents for every dollar owned by White Americans (Kochhar, Taylor, and Fry 2011). Although reparations programs are touted by proponents as economic—and, in part, moral—projects, I argue that policy efforts to close the large and growing racial wealth gap are essential health policies of critical relevance to aging and life-course scholars. A large body of literature across disciplines examines the social determinants of racial health disparities. Because socioeconomic factors are both fundamental determinants of health and strongly patterned by race, the racial stratification of socioeconomic resources and opportunities is a primary mechanism through which racism contributes to population health inequality (Phelan and Link 2015). In particular, recent research indicates the essential role of wealth in shaping lifecourse patterns of health, net of other indicators of socioeconomic factors, such as income and education (Boen and Yang 2016; Cessarini et al. 2016). Given

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documented links between wealth and health, a growing body of research shows the particularly prominent contribution of wealth inequality to life-course patterns of Black–White health gaps (Boen 2016; Boen, Keister, and Aronson 2020), which highlights the relevance of wealth-building policies and interventions—such as reparations—for life-course health and aging outcomes and scholarship. Still, despite increased attention to the contribution of the racial wealth gap to inequalities in health and aging, critical gaps in our understanding of these links remain. First, little is known about how the association between wealth and health varies across the life course, as most of the literature on this topic is based on data from older adult samples. In the same way that health and aging are lifelong, cumulative processes, wealth accumulation also is a life-course process that reflects both past and contemporary experiences and exposures. Wealth accumulation also is intergenerational. As such, understanding the early-life origins and intergenerational, mutually reinforcing processes of racial wealth and health inequality requires an integration of life-course theories and methodological approaches into studies of wealth–health linkages. Second, research in this area has been restricted to an almost exclusive reliance on binary health measures as opposed to continuous outcomes, which raises concerns about misclassification error, limits understanding of the biological and physiological mechanisms underlying the links between wealth and health, and risks underestimating racial and socioeconomic health gaps (Aneshensel, Rutter, and Lachenbruch 1991). For example, studies in this area use outcomes that indicate whether individuals have ever been diagnosed with conditions like heart disease or diabetes rather than integrating continuous measures of cardio-metabolic or inflammatory functioning. This can mask heterogeneity in well-being within diagnosis categories and leave questions about how social exposures “get under the skin” unanswered (Green and Darity 2010). Further, given documented disparities in health care access and treatment, an over-reliance on diagnostic outcomes might also substantially underestimate racial–ethnic and socioeconomic health gaps, as well as the contribution of social exposures to those gaps (Boen 2020). Finally, concerns about confounding and reverse causality plague studies of wealth and health, casting uncertainty about whether the links between wealth and health are, in fact, causal. Taken together, these gaps suggest that aging and life-course scholars can play a critical role in improving scientific understanding of the links between wealth inequality and population health and informing policy solutions for addressing the socioeconomic roots of health disparities across the life course (see Dannefer and Han in this volume). This chapter proceeds as follows. I begin by reviewing evidence of the association between wealth and individual and population health. Next, I discuss rising levels of wealth inequality in the United States, generally, and Black– White wealth inequality, specifically. Given documented associations between wealth and health and staggering levels of wealth inequality, I argue that the racial wealth gap is a critical driver of population-level racial health inequities. I

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continue with a discussion of how policies and interventions to reduce wealth inequality and shrink the racial wealth gap might, in fact, be essential health policies. I close the chapter with a discussion of future directions for research on wealth and health, paying particular attention to the role of aging and life-course scholars in shaping policy debates. Throughout the chapter, I review published research and also present original empirical estimates from both the Panel Study of Income Dynamics (PSID) and the Health and Retirement Study (HRS).

Wealth and Health Across the Life Course A growing body of literature provides evidence of a link between household wealth and individual and population health. While income and education are perhaps the most widely used indicators of socioeconomic status (SES) in research on aging and health, studies increasingly highlight the essential role of wealth in shaping well-being, net of other indicators of social status (Boen and Yang 2016; Pollack et al. 2007). Wealth—typically operationalized as net worth, or a sum of total assets minus debts—can serve as a safety net for families in times of economic hardship, providing financial stability and allowing households to continue paying for housing, transportation, health care, and other needs in times of unemployment or illness. Evidence suggests that wealth might be particularly important for older adults, as individuals exit the paid labor market and turn to their accumulated assets to support their health and well-being (Boen and Yang 2016). Research using quasi-natural experimental designs linking wealth shocks from the Great Recession (Boen and Yang 2016) and lottery winnings (Cesarini et al. 2016) to both adult and child health outcomes suggests that the association between wealth and health might be causal. Although rarely tested empirically, three mechanisms are thought to underlie the association between wealth and health (Boen and Yang 2016). First, wealth supports household consumption in ways that relate to health. Individuals and households with more wealth can afford higher-quality housing, food, and medical care than those with less wealth. Conversely, household spending on medical and dental care and other health-related expenditures decreases as wealth levels decline. Second, wealth affects health by shaping time-use patterns. Individuals and households with greater wealth stocks have more time and energy to engage in health-promoting activities—including more time for exercise, socializing, and leisure—than individuals and households with fewer assets and higher debt, who spend more time and energy dealing with the challenges and responsibilities associated with financial insecurity. Finally, stress mediates the relationship between wealth and health. Low wealth, asset loss, and high debt can increase anxiety, frustration, and hopelessness in ways that shape both physical and mental health. The stress associated with low wealth can induce a host of psychological and physiological changes, including upregulating functioning across immune, neuroendocrine, metabolic, and cardiovascular systems. Chronic

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and repeated activation of these systems in response to long-term low wealth can promote psychological and physiological dysregulation and allostatic load, thereby increasing health risk from a host of causes. In line with this notion, recent studies link financial strain—such as that associated with chronically low wealth—to increased metabolic and inflammatory risk in later life (Boen 2020). In these ways, cumulative exposure to the many stressors and strains associated with low wealth over the life course can contribute to the emergence and divergence of intra-individual health trajectories with age (Ferraro and Shippee 2009). A growing body of research utilizes markers of biological aging to examine the role of social exposures in accelerating physiological deterioration and shaping mortality risk (Levine and Crimmins 2014; Wolf and Morrison 2017). Measures of biological aging aim to quantify multi-system, age-related changes in physiology and can be useful proxies for the pace of aging in individuals when using cross-sectional biomarker data (Belsky et al. 2015). Use of these measures, which can include composite biomarker measures of biological age acceleration or single indicators of cellular aging such as telomere length, helps to capture the reality that individuals do not all age at the same pace from a biophysiological perspective, due in large part to disparities in social exposures. Although researchers tend to use chronological age as a proxy for the biological aging process, individuals might be biologically “older” or “younger” than suggested by their chronological age. As such, markers of biological age can be useful indicators of age-related changes in physiological well-being, providing new insights into how social exposures “get under the skin” to shape mortality risk. Figure 4.1 uses data from HRS to show the relationship between long-term household wealth, which considers household wealth over a 20-year period, and a composite measure of biological age acceleration (Klemera and Doubal 2006). As seen in Figure 4.1, there is a strong wealth gradient in biological age, whereby individuals with higher levels of long-term wealth are substantially “younger” biologically than individuals with lower levels of wealth. In fact, individuals with household wealth levels two standard deviations above the mean are nearly 13 years “younger” biologically than individuals with wealth levels two standard deviations below the mean.

Wealth Inequality and the Racial Wealth Gap Wealth inequality in the United States is striking. In 2010, the top one percent of wealth holders owned approximately 34 percent of all net worth, and the next nine percent of wealth owners held an additional 40 percent of net worth, leaving the remaining 90 percent of American households with just 25 percent of all wealth (Keister 2014). Even in this context of high overall wealth inequality, the racial wealth gap is particularly striking. The median net worth of White households is roughly 20 times that of Black households. More than one-third of all

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FIGURE 4.1 Long-term wealth and biological age. Notes: Association of long-term wealth and biological age in the Health and Retirement Study. Figure derived from model regressing biological age acceleration on age, gender, cohort, race, early-life SES, education, and long-term wealth. Longterm wealth is inflation-adjusted, inverse hyperbolic sine-transformed, averaged across all waves, and included as a z-score. Biological age was measured in 2016 using the Klemera–Doubal method and is included here as a measure of biological age acceleration (biological age – chronological age). Biological age measures courtesy of Daniel Belsky.

Black households have zero or negative net worth—meaning their debts exceed the total worth of their assets—compared to 15 percent of White households (Kochhar et al. 2011). Contemporary Black–White wealth disparities are the product of a host of historical and contemporary factors. Scholars trace the origins of the racial wealth gap in the United States to chattel slavery and the failure of the Freedmen’s Bureau and the Homestead Act of 1862 to provide land—“40 acres and a mule”—to formerly enslaved people during the Reconstruction era (Darity and Mullen 2020). The seizure of Black assets by Whites through terrorism and violence, the implicit and explicit exclusion of Black Americans from receiving benefits offered through the New Deal, the unequal distribution of G.I. Bill benefits after World War II, and the proliferation of Jim Crow laws throughout the nineteenth and twentieth centuries further contributed to the racial patterning of wealth in the United States (Oliver and Shapiro 2013; Turner and Bound

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2003). Present-day racial discrimination in the housing, lending, and labor markets continues to exacerbate racial wealth inequality by denying Black Americans access to the same wealth-building resources and opportunities afforded to Whites (Hamilton and Darity 2010). Wealth accumulation is both a life-course and an intergenerational process; individuals accumulate wealth as they age and often pass along their assets—and, sometimes, debts—to descendants, highlighting the critical role of the life-course concept of “linked lives” in the production of wealth inequality. These features of wealth accumulation mean that age, cohort, and period trends in racial wealth inequality typically follow a process of cumulative (dis)advantage (Dannefer 2003). As a result, Black–White wealth inequality widens across the life course, across successive cohorts, and across historical time. Figure 4.2 uses data from the Child Development Supplement of the PSID and the HRS to show age and period trends in Black-White wealth inequality. Figure 4.2A reveals that Black children are born into families with considerably less wealth than White children, and Figure 4.2B shows that Black older adults spend their years in late life with considerably fewer financial assets than White older adults. These patterns of racial wealth inequality have become starker over time, with Black–White wealth inequality among households with children and among older adults increasing since the 1990s.

FIGURE 4.2 Racial wealth inequality among children and older adults. Notes: Figures display household wealth by race among households with children (from Child Development Supplement of Panel Study of Income Dynamics, 1999– 2007) and older adults (from Health and Retirement Study, 1992–2010). Wealth is inflation-adjusted and measured in hundreds of thousands of dollars.

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The Racial Wealth Gap and the Life-Course Patterning of Health Inequality Given the documented links between wealth and health, and striking levels of racial wealth inequality, it follows that wealth inequality plays a role in the patterning of Black–White health inequality. In fact, studies show that life-course wealth patterns shape the age patterning of Black–White health gaps, net of other socioeconomic factors such as income and education (Boen 2016; Boen, Keister, and Aronson 2020). As seen in Figure 4.3, analyses examining the sources of Black–White disparities in biological age provide similar findings. Figure 4.3 displays estimates of the magnitude of the Black–White gap in biological aging derived from stepwise models examining the socioeconomic determinants of racial disparities in biological aging. Figure 4.3 indicates how much of the Black– White gap in biological age is “explained” by different dimensions of SES. Model 1 of Figure 4.3 is a basic adjusted model that accounts for race, age, gender, and birth cohort; Model 2 builds on Model 1 by also including measures of education and early-life SES; and Model 3 is the fully adjusted model that also includes long-term wealth. As seen in Figure 4.3, the magnitude of the Black– White disparity in biological age is largest in Model 1, where there are no controls for SES. The racial disparity is attenuated with the inclusion of education and early-life SES in Model 2, but the Black–White disparity is smallest in Model 3, which also adjusts for long-term wealth. These results reveal that wealth is not only a driver of individual health, but also a key driver of Black–White disparities in biological age in mid- to late-life, net of other socioeconomic factors. Taken together, these results show that the highly unequal racial patterning of socioeconomic resources—including wealth—plays an essential role in the production of racial disparities in health and aging.

Policies for Wealth and Health Equity So, what will it take to close the large and persistent Black–White wealth gap in the United States? It is clear that policies, programs, and interventions aimed at changing individual and household behavior—such as those promoting saving behavior or financial literacy—will be woefully inadequate. Because the root causes of Black–White wealth inequality are structural—located in historical and contemporary racial domination—closing the racial wealth gap requires widespread systemic and policy change aimed at building and/or redistributing wealth (Darity and Mullen 2020; Darity et al. 2018). While a number of proposals exist, two policy options have garnered particularly high levels of attention from policy makers, scholars, and advocates. First, baby bonds are a race-neutral intervention for reducing overall levels of wealth inequality by providing the equivalent of a trust fund for wealth-poor American babies, a disproportionate number of whom are Black (Hamilton and Darity 2010). The idea is

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The socioeconomic determinants of black–white disparities in biological age. Notes: Figure shows the magnitude of Black–White disparities in biological age in the Health and Retirement Study (2016) after adjusting for: age, gender, and birth cohort (Model 1); age, gender, birth cohort, education, and early-life SES (Model 2); and age, gender, birth cohort, education, early-life SES, and long-term wealth (Model 3). Biological age measures courtesy of Daniel Belsky.

FIGURE 4.3

to provide all American children with a lump sum or smaller regular deposits in funds administered by a centralized governmental agency to ensure that children have access to the capital needed to build wealth as they age. Importantly, proponents argue that the funds should be structured progressively so that children from lower-wealth families receive more funds than children from wealthier families (Hamilton et al. 2020). Because wealth accumulation is a life-long process, intervening on intra-cohort levels of wealth inequality early in the life course through the provision of baby bonds is an innovative strategy. Second, as briefly described in the introduction to this chapter, reparations are intended to acknowledge and redress historical and contemporary racial injustice by providing direct compensation to the descendants of enslaved individuals. Proponents of reparations argue that an effective reparations program would provide direct, substantial payments to every documented U.S. descendant of slavery as a means, in part, of building wealth among Black Americans (Darity and Mullen 2020). Given that previous race-neutral efforts have failed to successfully eliminate persistent Black–White wealth gaps, proponents argue that policies explicitly targeting racial inequality are needed (Darity and Mullen 2020). While evaluating the promises and limitations of these two proposals is beyond the scope of this chapter, the evidence on the links between the racial wealth gap and life-course patterns of health inequality offered here makes it clear that wealth-building policies are not solely economic in nature; wealth policies are, implicitly, health policies that fundamentally shape aging and well-being across the life course.

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Future Directions on the Wealth–Health Nexus for Aging and Life-Course Scholars In order to best inform policy and intervention efforts, four outstanding questions about the links between wealth inequality and population health require the future attention of aging and life-course scholars. First, most research on the links between wealth and health uses data on older adults, so less is known about how wealth impacts the health of children and adolescents. Levels of wealth inequality are especially high among households with children, and these households experience comparatively weak social safety net protections (Gibson-Davis and Percheski 2018). Childhood and adolescence also are sensitive periods for health, which suggests that wealth exposures during these life-course stages have important implications for later-life health and well-being (Kuh et al. 2003). Given that both wealth accumulation and health are life-course, intergenerational processes, future research on the early-life origins of wealth and health inequalities could provide new insights into how policies and programmatic efforts can intervene before such disparities emerge and diverge. Further, it is possible that the mechanisms linking wealth to health vary across the life course, which further highlights the need for more research on life-course variations in the associations between wealth and health. Second, studies typically examine how wealth relates to single indicators of disease or self-reported health status, which restricts understanding of the biophysiological processes underlying wealth-health links. Studies using diagnosis outcomes risk misclassification error (Aneshensel, Rutter, and Lachenbruch 1991), where individuals with high levels of psychological and/or physiological dysregulation are classified as “well.” Given documented social class and racial disparities in health care access and diagnosis, the use of disease outcomes in studies of socioeconomic and racial health inequality might be particularly worrisome, as it risks underestimation of both the magnitude of health disparities and the role of social exposures in population health gaps (Boen 2020). As such, more research using biomarkers of psychophysiological functioning and biological aging is needed both to provide more accurate estimates of population health disparities and to elucidate the biophysiological and psychological mechanisms linking wealth and health. Third, concerns about causal inference—including issues related to reverse causality and time-varying confounding—continue to plague the literature in this area. While cross-sectional data has provided preliminary evidence of a possible association between wealth and health, future research utilizing longitudinal data and exploiting quasi-experimental exogenous wealth shocks will provide stronger and clearer evidence of the links between wealth and health. Finally, aging and life-course scholars have an essential role to play in conducting policy-relevant research on how wealth policy proposals can improve population health and reduce health disparities. They also must identify effective

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ways to translate and communicate their findings to non-academic audiences in order to realize their contributions more fully. As debates about whether or how to intervene on rising levels of wealth inequality continue, aging and life-course scholars are poised to provide new insights into the role of wealth policy in contributing to patterns of health and well-being across the life course.

References Aneshensel, Carol S., Carolyn M. Rutter, and Peter A. Lachenbruch. 1991. “Social Structure, Stress, and Mental Health: Competing Conceptual and Analytic Models.” American Sociological Review 56 (2):166–178. Belsky, Daniel W., Avshalom Caspi, Renate Houts, Harvey J. Cohen, David L. Corcoran, Andrea Danese, HonaLee Harrington, Salomon Israel, Morgan E. Levine, Jonathan D. Schaefer, Karen Sugden, Ben Williams, Anatoli I. Yashin, Richie Poulton, and Terrie E. Moffitt. 2015. “Quantification of Biological Aging in Young Adults.” Proceedings of the National Academy of Sciences 112 (30):E4104–E4110. Boen, Courtney. 2016. “The Role of Socioeconomic Factors in Black-White Health Inequities Across the Life Course: Point-in-time Measures, Long-Term Exposures, and Differential Health Returns.” Social Science & Medicine 170:63–76. Boen, Courtney. 2020. “Death by a Thousand Cuts: Stress Exposure and Black–White Disparities in Physiological Functioning in Late Life.” The Journals of Gerontology: Series B 75 (9):1937–1950. Boen, Courtney, Lisa Keister, and Brian Aronson. 2020. “Beyond Net Worth: Racial Differences in Wealth Portfolios and Black–White Health Inequality across the Life Course.” Journal of Health and Social Behavior 61 (2):153–169. Boen, Courtney and Y. Claire Yang. 2016. “The Physiological Impacts of Wealth Shocks in Late Life: Evidence from the Great Recession.” Social Science & Medicine 150:221– 230. Cesarini, David, Erik Lindqvist, Robert Östling, and Björn Wallace. 2016. “Wealth, Health, and Child Development: Evidence from Administrative Data on Swedish Lottery Players.” The Quarterly Journal of Economics 131 (2):687–738. Dannefer, Dale. 2003. “Cumulative Advantage/Disadvantage and the Life Course: CrossFertilizing Age and Social Science Theory.” The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 58 (6):S327–S337. Darity, William A., Jr., Darrick Hamilton, Mark Paul, Alan Aja, Anne Price, Antonio Moore, and Caterina Chiopris. 2018. “What We Get Wrong About Closing the Racial Wealth Gap.” Samuel DuBois Cook Center on Social Equity and Insight Center for Community Economic Development. https://socialequity.duke.edu/portfolio-item/ what-we-get-wrong-about-closing-the-racial-wealth-gap/. Darity, William A., Jr., and A. Kirsten Mullen. 2020. From Here to Equality: Reparations for Black Americans in the Twenty-First Century. Chapel Hill, NC: The University of North Carolina Press. Ferraro, Kenneth F. and Tetyana Pylypiv Shippee. 2009. “Aging and Cumulative Inequality: How Does Inequality Get Under the Skin?” The Gerontologist 49 (3):333– 343. Gibson-Davis, Christina M. and Christine Percheski. 2018. “Children and the Elderly: Wealth Inequality Among America’s Dependents.” Demography 55 (3):1009–1032.

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Green, Tiffany L. and William A. Darity, Jr. 2010. “Under the Skin: Using Theories From Biology and the Social Sciences to Explore the Mechanisms Behind the Black– White Health Gap.” American Journal of Public Health 100(S1):S36–S40. Hamilton, Darrick and William A. Darity, Jr. 2010. “Can ‘Baby Bonds’ Eliminate the Racial Wealth Gap in Putative Post-Racial America?” The Review of Black Political Economy 37 (3–4):207–216. Hamilton, Darrick, Emanuel Nieves, Shira Markoff, and David Newville. 2020. A Birthright to Capital: Equitably Designing Baby Bonds to Promote Economic and Racial Justice. Washington, DC: Prosperity Now and the Kirwan Institute for the Study of Race and Ethnicity. https://prosperitynow.org/sites/default/files/PDFs/Federal%20Policy/Kirwa n_Institute_Prosperity_Now-Baby_Bonds_FULL_REPORT_FINAL_FEB_2020.pdf. Keister, Lisa A. 2014. “The One Percent.” Annual Review of Sociology 40:347–367. Klemera, Petr and Stanislav Doubal. 2006. “A New Approach to the Concept and Computation of Biological Age.” Mechanisms of Ageing and Development 127 (3):240–248. Kochhar, Rakesh, Paul Taylor, and Richard Fry. 2011. Wealth Gaps Rise to Record Highs Between Whites, Blacks and Hispanics. Vol. 26. Washington, DC: Pew Research Center. Kuh, Diana, Yoav Ben-Shlomo, John Lynch, Johan Hallqvist, and Chris Power. 2003. “Life Course Epidemiology.” Journal of Epidemiology and Community Health 57 (103):778–783. Levine, Morgan E. and Eileen M. Crimmins. 2014. “Evidence of Accelerated Aging Among African-Americans and Its Implications for Mortality.” Social Science & Medicine 118:27–32. Oliver, Melvin and Thomas Shapiro. 2013. Black Wealth/White Wealth: A New Perspective on Racial Inequality. 2nd ed. New York: Routledge. Phelan, Jo C. and Bruce G. Link. 2015. “Is Racism a Fundamental Cause of Inequalities in Health?” Annual Review of Sociology 41:311–330. Pollack, Craig Evan, Sekai Chideya, Catherine Cubbin, Brie Williams, Mercedes Dekker, and Paula Braveman. 2007. “Should Health Studies Measure Wealth?: A Systematic Review.” American Journal of Preventive Medicine 33 (3):250–264. Turner, Sarah and John Bound. 2003. “Closing the Gap or Widening the Divide: The Effects of the G.I. Bill and World War II on the Educational Outcomes of Black Americans.” The Journal of Economic History 63 (1):145–177. Wolf, Erika J. and Filomene G. Morrison. 2017. “Traumatic Stress and Accelerated Cellular Aging: From Epigenetics to Cardiometabolic Disease.” Current Psychiatry Reports 19 (10):75.

5 UNDERSTANDING THE ROLE OF HOUSING POLICY IN LIFE-COURSE HEALTH HUD Rental Assistance and Health Outcomes for Children and Adults Andrew Fenelon

Low-income Americans are currently experiencing a crisis in access to stable and affordable rental housing. While half of rental households experience rental cost burden (i.e., spending more than 30% of income on rent), the problem is particularly acute for renters in the bottom income quintile. Among the poorest 20% of American households, more than 80% experience a rental cost burden and more than 70% spend at least half of their income on rent (Joint Center for Housing Studies 2018). Federal rental assistance programs—including public housing, housing choice vouchers, and multifamily housing—represent the bulk of the public housing assistance resources available to low-income families. However, these programs are significantly underfunded and only serve 20–25% of eligible families (HUD 2019b). In the wake of the 2020 COVID-19 pandemic, rapidly rising housing instability, eviction risk, and homelessness are likely to greatly raise the need for well-funded federal rental assistance programs (Grinstein-Weiss et al. 2020). In addition to providing a source of safe, stable, and affordable shelter, rental assistance programs might have positive effects on health and well-being at all stages of the life course, but especially in childhood. Such early-life benefits have implications for socioeconomic attainment and health at older ages. Since recipients of rental assistance experience high levels of socioeconomic disadvantage and are disproportionately members of racial and ethnic minority groups, rental assistance might also promote socioeconomic mobility from childhood to adulthood and reduce socioeconomic and racial disparities in adult health (see also Boen in this volume). As of 2018, the U.S. Department of Housing and Urban Development (HUD) provided rental assistance to approximately five million families that included nearly four million children (HUD 2019a). HUD housing is designed to be

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affordable—assisted households are expected to pay 30% of their incomes to rent with the difference subsidized by HUD. HUD housing subsidies are intended to provide access to more stable and higher-quality housing than families would be able to afford in the private market. The disposable income boost that comes from paying less for housing might also have additional benefits for the health and well-being of disadvantaged children and adults. However, I argue that the potential utility of housing policy as a lever to reduce socioeconomic inequalities in health and improve health at all ages is limited by the structure of federal housing policy priorities. At present, we know less than we should about the long-term influence of rental assistance on recipients’ lives because empirical research on the effects of rental assistance programs on life-course outcomes is limited (Slopen et al. 2018). In this chapter, I consider the role of federal rental assistance programs in improving life-course health and reducing inequalities within the context of America’s growing low-income housing crisis. First, I outline key historical developments in American housing policy that structure the priorities of current federal rental assistance programs. Next, I discuss how rental assistance programs might have an impact on health across the life course and review existing evidence for a causal effect of rental assistance on health in both childhood and adulthood. Finally, I provide an assessment of the current state of research on rental assistance policy and life-course health and consider some of the limitations of existing studies. I conclude that increased investment in rental assistance programs now would represent a needed intervention in U.S. housing policy that has the potential to reduce health disparities in the future.

The Unequal Structure of American Housing Policy Federal housing affordability policy is implemented as a two-tiered system that simultaneously focuses on supporting home purchasing and ownership and on subsidies for affordable rental housing (Radford 1996). Homeownership support programs have origins in the housing legislation of the “New Deal” that led to the establishment of the Federal Housing Administration (FHA); the Federal National Mortgage Association (Fannie Mae) and the Federal Home Loan Mortgage Corporation (Freddie Mac), which were designed to encourage mortgage lending; and in the Servicemen’s Readjustment Act of 1944 (also known as the “G.I. Bill”), which fueled the expansion of homeownership in the midtwentieth century and still subsidizes home buying for veterans through lowinterest home loans. Rental assistance programs also originated during the New Deal but were greatly expanded during the “War on Poverty” and the civil rights movement (Quadagno 1996), which makes them more like welfare programs than FHA homeownership supports. Although HUD spent $40 billion on rental assistance programs in 2015, federal support for homeownership through tax relief and reduced mortgage costs was 70% greater (Woo and Salvati 2017).

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Overall, the current structure of housing assistance policy in the United States disproportionately benefits middle-class and upper-class families. The two-tiered system and the spending imbalance contribute to two outcomes that serve to maintain housing inequality and social stratification. First, although middle-class and high-income homeowners receive federal support for housing, this support is hidden within the mortgage financing system and the tax code. Indeed, the mortgage interest deduction arose gradually within the tax code under the auspices of a 1913 tax deduction that had no explicit support for home financing (Radford 1996). Thus, rather than claiming a federal, meanstested welfare benefit, middle-class and wealthy homeowners can “pay” less and thereby claim that they do not “receive” assistance. To be clear, however, the mortgage interest deduction has significant costs in foregone tax revenue that the federal government could use to fund various programs and services. In contrast, HUD rental assistance programs have origins in the War on Poverty. As such, these programs function like other safety-net welfare programs and are subject to the stigma associated with receiving public assistance (Quadagno 1996). Second, the two-tiered system reduces the size of the potential constituency for federal rental assistance programs, which limits the political power that housing advocates can mobilize to seek increases in support. Unlike other assistance programs, such as the Supplemental Nutrition Assistance Program (SNAP) or Medicaid, not all households that meet eligibility criteria are able to receive assistance (Center on Budget and Policy Priorities 2017). This means that, in practice, the recipients of rental assistance tend to be considerably more disadvantaged than participants in other programs (Irving and Loveless 2015). Furthermore, because of the program’s limited carrying capacity, families might be forced to wait several years before obtaining access to assistance (HUD 2019a). Modern rental assistance programs grew out of post-World War II policy and involved significant federal investment during the 1950s and 1960s in the construction of public housing developments for families unable to afford housing in the private market. Rental assistance is provided primarily through three major programs that are federally funded but administered locally by public housing agencies (PHAs): public housing, housing choice vouchers, and multifamily housing. The public housing program refers to entire developments of subsidized housing owned, operated, and maintained by PHAs. The concentration of assisted families in public housing can in some circumstances permit the relatively efficient delivery of services, such as health care or food assistance (Digenis-Bury et al. 2008). However, the high density of public housing also has been a source of criticism in academic and policy circles, given the expectation that a concentration of poverty was responsible for reducing life chances for disadvantaged children (DeLuca, Garboden, and Rosenblatt 2013). In response, HUD reoriented its approach to housing policy by focusing on providing low-income families greater choice and flexibility. The housing choice vouchers program originated in Section 8 of the Housing and Community

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Development Act of 1974. The program was intended to address the criticisms raised in relation to public housing (Center on Budget and Policy Priorities 2017). Vouchers allow recipients to rent private housing using a subsidy that is paid on the renter’s behalf directly to the landlord (Center on Budget and Policy Priorities 2017). In theory, vouchers are highly flexible, and renters may use them at any qualified property in the United States. In practice, the extent of neighborhood mobility provided by housing choice vouchers has been somewhat limited (Buron, Levy, and Gallagher 2007). Although voucher recipients tend to reside in less disadvantaged neighborhoods than public housing residents, their neighborhoods are significantly more disadvantaged than the U.S. average (Fenelon et al. 2017). Finally, multifamily housing programs involve privately owned housing developments that contain HUD-subsidized units. Unlike vouchers, recipients of multifamily housing are not permitted to transfer their subsidy to new properties. Few existing studies have examined the health effects of these programs or how effects might vary across contexts (e.g., urban, suburban, rural locations) or characteristics of recipients.

Rental Assistance and Life-Course Health Rental assistance might have positive effects on children’s health and well-being outcomes by improving housing quality, stability, and affordability (Swope and Hernández 2019). Improvement in housing quality is likely to reduce exposure to unhealthy substances, such as lead in paint, and improve air quality, which can reduce children’s frequency of illness (Thomson, Petticrew, and Morrison 2001). Likewise, more stable and affordable housing can reduce children’s own stress, as well as exposure to parental stress, and thereby improve children’s mental health. More affordable housing also frees up resources to spend on things that can benefit children’s health, including health care, transportation, education, and leisure activities (Newman and Holupka 2014). Additionally, housing mobility programs, such as housing choice vouchers, might provide access to safer or higher-opportunity neighborhoods than recipients would otherwise be able to afford. A small number of studies have examined the impact of rental assistance programs on children’s health outcomes, with mostly mixed results (Slopen et al. 2018). However, from a life-course perspective, the benefits of investment in rental assistance in childhood might emerge later or accumulate (see also Dannefer and Han in this volume). This could particularly be the case if rental assistance has implications for socioeconomic attainment. One mechanism by which such effects might emerge is through the reduction of household crowding during childhood (Lopoo and London 2016). Emerging evidence from experimental and quasi-experimental studies indicates that children whose families receive rental assistance enjoy socioeconomic gains in adulthood. A longitudinal study using data from the Panel Study of Income

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Dynamics found that living in public housing during childhood led to increased employment and reduced welfare use in adulthood, compared to similar children who did not receive rental assistance (Newman and Harkness 2002). One study comparing siblings by the amount of childhood spent in assisted housing found that additional years of rental assistance led to increases in adult income and reductions in incarceration (Andersson et al. 2016). Findings from the long-term follow up of the “Moving to Opportunity” study indicate that children who moved to low-poverty neighborhoods using vouchers early in life had higher earnings in adulthood than those who moved later (Chetty, Hendren, and Katz 2016). Finally, a study of children displaced due to public housing demolitions in Chicago found greater employment and higher earning in adulthood among those who were relocated into vouchers than among their counterparts who remained in public housing (Chyn 2018). The findings of these studies are particularly striking given that there is little evidence of short-term socioeconomic benefits of housing vouchers (Jacob 2004). Although these studies do not directly specify the mechanisms that drive the observed socioeconomic mobility benefits of rental assistance, improved health in childhood is a promising possibility.

Recent Evidence on Federal Rental Assistance and Health Historically, the lack of access to high-quality, nationally representative datasets that contain information on participation in rental assistance programs and health outcomes has limited research on the life-course consequences of rental assistance receipt. In 2016, the National Center for Health Statistics (NCHS) and HUD developed a data linkage program to match individuals in two national health surveys to administrative records of rental assistance participants. Respondents from the National Health Interview Survey (NHIS) and the National Health and Nutrition Examination Survey (NHANES) were linked with a high degree of accuracy to their HUD administrative record using Social Security numbers, birth dates, and sex. The linkage provides a longitudinal record of participation in HUD programs, which can be used to generate full housing histories for each national survey participant over the period 1999–2012 (Lloyd and Helms 2016). Following the release of the NCHS-HUD linked data files, a series of empirical studies has examined the impact of rental assistance on the health outcomes of children and adults (Ahrens et al. 2016; Boudreaux et al. 2020; Fenelon et al. 2017, 2018; Simon et al. 2017; Wong et al. 2018, 2019). One challenge to studying the causal effect of rental assistance on resident outcomes is selection into assistance. Families receiving rental assistance experience high levels of socioeconomic disadvantage—the average family income of participants is 75% below the median family income in the area where they live, and more than two-thirds of families have income-to-needs below the federal poverty line (Helms, Sperling, and Steffen 2017). To address the potential for adverse selection to bias findings, researchers have used quasi-experimental

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research designs because fully experimental designs employing random assignment to treatment and control groups often is not feasible. Ahrens et al. (2016) used the NHANES-HUD linked dataset to study measured, as opposed to selfreported, blood lead. They found that children ages 2–5 receiving rental assistance had lower blood lead levels than a propensity score-matched comparison group. This is significant given the long-term, negative consequences of even low levels of childhood lead exposure (Needleman et al. 1990). To date, this is the only empirical study to draw from the NHANES-HUD linkage. A series of other studies has used a pseudo-waitlist comparison group—comparing outcomes among individuals receiving rental assistance and those who will enter assisted housing within a typical waitlist period of two years (HUD 2019a). This approach implicitly adjusts for unobserved factors that select families into receiving rental assistance. Fenelon et al. (2018) used this approach to examine the effect of rental assistance on mental health and well-being for children and adolescents ages 2–17. Figure 5.1 presents predicted values on the abridged Strengths and Difficulties Questionnaire (SDQ) for children living in public housing and children in the pseudo-waitlist group. The SDQ score is an index ranging from 1–10, with higher values indicating poorer mental health. Children living in public housing were found to have significantly better well-being than their waitlist counterparts. For reasons that are not yet determined, the study did not find similar effects for housing choice vouchers or multifamily housing. Consistent with these findings among youth ages 2–17, Fenelon et al. (2017) showed that adults receiving rental assistance were less likely to report fair or poor health status and experience serious psychological distress than pseudowaitlist adults. Also consistent with results for children and adolescents, these benefits were limited to adults living in public housing (Figure 5.2). The positive impact of rental assistance on adult health is not unexpected, but the mechanisms driving this relationship are not clear. Simon et al. (2017) used the NHIS-HUD linked dataset to show that adults ages 18–64 receiving rental assistance were more likely to have health insurance and less likely to delay needed care due to cost than their pseudo-waitlist counterparts. In contrast to findings related to selfreported health and psychological distress, health care access effects did not differ among public housing, housing choice vouchers, and multifamily housing. In addition to direct effects on health outcomes and access to health care, rental assistance might also provide the opportunity for recipients to engage in healthier behaviors. For example, Wong et al. (2018) analyzed the NHIS-HUD linked dataset and found that non-elderly adults receiving rental assistance were more likely to report vigorous exercise than those in the pseudo-waitlist group. However, the evidence regarding the influence of rental assistance on health behaviors is inconsistent. A different study using the NHIS-HUD linked dataset found no evidence for a beneficial effect of rental assistance receipt on screenings for colorectal, breast, or cervical cancer (Wong et al. 2019).

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Predicted Strengths and Difficulties Questionnaire (SDQ) score for children (ages 2–17) by rental assistance status. Notes: Predicted SDQ score for children currently living in public housing and children who will enter public housing within two years (pseudo-waitlist). The SDQ is a series of five questions about the well-being and behavior of a child, with responses ranging from 0 (no difficulty) to 2 (difficulty all or almost all of the time). The total index is a summation of these responses with values ranging from 0–10. Higher values indicate poorer well-being. Analyses draw from the 1999–2012 NHISHUD linked data file. Source: Fenelon et al. (2018).

FIGURE 5.1

An Assessment of Rental Assistance and Life-Course Health Until recently, obtaining estimates of the impact of programs that provide affordable rental housing on health and well-being outcomes has been challenging due to data limitations. The release of the NHANES-HUD and NHISHUD linked datasets in 2016 has provided the research community a promising new resource for addressing these and other policy-relevant questions. The findings from studies utilizing these data sources provide a growing base of evidence for rental assistance as a platform for improved mental and physical health. The evidence indicates that rental assistance can improve outcomes for disadvantaged children and adolescents; similar benefits also are found for disadvantaged adults, owing to the stability provided by affordable rental housing (Fenelon et al. 2017; Keene et al. 2020; Keene et al. 2018; Keene, Guo, and Murillo 2018).

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Percent reporting fair/poor health and serious psychological distress among adults (ages 18+) by rental assistance status. Notes: Percent reporting fair/poor health and serious psychological distress for adults living in public housing and adults who will enter public housing within two years (pseudo-waitlist). Fair/poor health is based on a question asking about general health status in which respondents assess their health as excellent, very good, good, fair, or poor. Serious psychological distress is based on the Kessler-6 scale. Analyses draw from the 1999–2012 NHIS-HUD linked data file. Source: Fenelon et al. (2017).

FIGURE 5.2

An important lesson for social scientists and policy analysts is the difference between public housing and housing vouchers in their impacts on various health and well-being outcomes. Evidence for the mental health benefits of living in public housing contrasts with conventional wisdom about the effects of growing up in “the projects.” It is plausible that the density of subsidized households in public housing developments might actually promote some benefits for residents, such as access to social support. Qualitative research on the experience of public housing residents suggests that social ties among economically isolated families in public housing provide a source of stability for children (Keene and Ruel 2013). This might be one reason why public housing has more pronounced beneficial effect than other forms of rental housing assistance on children’s mental health, which might respond more strongly to social network dynamics. Although evidence on the health benefits of vouchers is less consistent, their impacts might manifest in the long-term, particularly if they afford access to higher-opportunity neighborhoods. Indeed, an important policy goal of the

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housing choice vouchers program is to improve socioeconomic mobility, and there is evidence that it has done so (Chyn 2018). As a result, vouchers might be particularly valuable for improving life-course health outcomes by providing support for socioeconomic gains earlier in life. However, voucher recipients also could face short-term negative consequences in the form of discrimination or exclusion in high-opportunity locations. For racial–ethnic minority families, moving to a new neighborhood, particularly a predominantly White neighborhood, might increase exposure to social stressors related to racial-ethnic bias and changes in neighborhood norms (DeLuca et al. 2013). As a housing mobility program, vouchers might also limit the residential stability of recipient families. Among families relocated with vouchers after public housing demolition in the early 2000s, 40% had moved again within two years, compared to only 9% of the families who moved to another public housing development (Buron et al. 2007).

Limitations of Existing Research The availability of NCHS-HUD linked datasets offers an outstanding new opportunity to examine the life-course consequences of rental assistance. However, recent research leaves some questions of broader importance unanswered. First, although recent studies using these datasets provide results that are generalizable to the nation, they often are unable to specify the primary mechanisms through which rental assistance leads to improved child and adult health. The answer to this question is important for developing political support for rental assistance. Second, future research should attempt to quantify the longer-term health and economic benefits from increased federal investment in rental assistance. In addition to raising employment and earnings in adulthood, increased investment would likely reduce economic and racial disparities in health across the life course. Finally, the high level of unmet need for federal rental assistance programs represents a major challenge for population health. While just five million households receive HUD assistance, HUD identifies more than nine million unassisted households who experience high rent burdens and severe housing quality issues (HUD 2019b).

Conclusion Although the number of subsidized rental housing units supported by HUD has grown since the 1990s, the stock of affordable units relative to demand remains significantly below what it was in the middle of the twentieth century. There is a nationwide shortage of affordable rental housing in the United States, which has severe implications for the household budgets of low-income families (Joint Center for Housing Studies 2018). While the current rental housing affordability crisis has spread to the middle class, the response from the federal government has been limited. The number of rental households with incomes below 80% of their

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area median increased from 22 million in 1999 to 28 million in 2015, yet the number of federally subsidized rental units remained stagnant during this period at around five million and HUD spending on housing programs has not increased (Kingsley 2017; Rice 2016). Furthermore, the rise in job losses and income reductions resulting from the COVID-19 pandemic bring the lack of federal action on affordable housing into sharp focus. Researchers and housing advocates are increasingly concerned that a lack of investment in affordable rental housing is likely to have implications for the economic circumstances and the health of lower- and middle-income individuals for many years to come.

References Ahrens, Katherine A., Barbara A. Haley, Lauren M. Rossen, Patricia C. Lloyd, and Yutaka Aoki. 2016. “Housing Assistance and Blood Lead Levels: Children in the United States, 2005–2012.” American Journal of Public Health 106 (11):2049–2056. Andersson, Fredrik, John C. Haltiwanger, Mark J. Kutzbach, Giordano E. Palloni, Henry O. Pollakowski, and Daniel H. Weinberg. 2016. “Childhood Housing and Adult Earnings: A Between-Siblings Analysis of Housing Vouchers and Public Housing.” National Bureau of Economic Research. Working Paper No. 22721. Boudreaux, Michel H., Andrew Fenelon, Natalie Slopen, and Sandra J. Newman. 2020. “Association of Childhood Asthma with Federal Rental Assistance.” JAMA Pediatrics 174 (6):592–598. Buron, Larry F., Diane K. Levy, and Maggie Gallagher. 2007. Housing Choice Vouchers: How HOPE VI Families Fared in the Private Market. Washington, DC: Urban Institute, Issue Brief No. 3. Center on Budget and Policy Priorities. 2017. Fact Sheet: Federal Rental Assistance. Washington, DC. http://www.cbpp.org/sites/default/files/atoms/files/4-13-11hous-US.pdf. Chetty, Raj, Nathaniel Hendren, and Lawrence F. Katz. 2016. “The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment.” The American Economic Review 106 (4):855–902. Chyn, Eric. 2018. “Moved to Opportunity: The Long-Run Effects of Public Housing Demolition on Children.” American Economic Review 108 (10):3028–3056. DeLuca, Stefanie, Philip M. E. Garboden, and Peter Rosenblatt. 2013. “Segregating Shelter: How Housing Policies Shape the Residential Locations of Low-Income Minority Families.” The Annals of the American Academy of Political and Social Science 647 (1):268–299. Digenis-Bury, Eleni C., Daniel R. Brooks, Leslie Chen, Mary Ostrem, and C. Robert Horsburgh. 2008. “Use of a Population-Based Survey to Describe the Health of Boston Public Housing Residents.” American Journal of Public Health 98 (1):85–91. Fenelon, Andrew, Patrick Mayne, Alan E. Simon, Lauren M. Rossen, Veronica Helms, Patricia Lloyd, Jon Sperling, and Barry L. Steffen. 2017. “Housing Assistance Programs and Adult Health in the United States.” American Journal of Public Health 107 (4):571– 578. Fenelon, Andrew, Natalie Slopen, Michel H. Boudreaux, and Sandra J. Newman. 2018. “The Impact of Housing Assistance on the Mental Health of Children in the United States.” Journal of Health and Social Behavior 59 (3):447–463.

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Grinstein-Weiss, Michal, Brinda Gupta, Yung Chun, Hedwig Lee, and Mathieu Despard. 2020. Housing Hardships Reach Unprecedented Heights during the COVID-19 Pandemic. Washington, DC. Helms, V. E., Jon Sperling, and Barry L. Steffen. 2017. A Health Picture of HUD-Assisted Adults, 2006–2012. Washington, DC: U.S. Department of Housing and Urban Development. HUD. 2019a. “Picture of Subsidized Households.” Washington, DC: U.S. Department of Housing and Urban Development. https://www.huduser.gov/portal/datasets/assthsg.html. HUD. 2019b. Worst Case Housing Needs: 2019 Report to Congress. Irving, Shelley K. and Tracy A. Loveless. 2015. “Dynamics of Economic Well-Being: Participation in Government Programs 2009–2012: Who Gets Assistance?” U.S. Census Bureau; Department of Commerce: Economics and Statistics Administration. Jacob, Brian A. 2004. “Public Housing, Housing Vouchers, and Student Achievement: Evidence from Public Housing Demolitions in Chicago.” The American Economic Review 94 (1):233–258. Joint Center for Housing Studies. 2018. America’s Rental Housing 2018. Joint Center for Housing Studies, Harvard University. https://www.jchs.harvard.edu/sites/default/files/ Harvard_JCHS_State_of_the_Nations_Housing_2018.pdf. Keene, Danya E., Monica Guo, and Sascha Murillo. 2018. “‘That Wasn’t Really a Place to Worry about Diabetes’: Housing Access and Diabetes Self-Management Among Low-Income Adults.” Social Science & Medicine 197:71–77. Keene, Danya E., Mariana Henry, Carina Gormley, and Chima Ndumele. 2018. “‘Then I Found Housing and Everything Changed’: Transitions to Rent-Assisted Housing and Diabetes Self-Management.” Cityscape (Washington, D.C.) 20 (2):107–118. Keene, Danya E., Linda Niccolai, Alana Rosenberg, Penelope Schlesinger, and Kim M. Blankenship. 2020. “Rental Assistance and Adult Self-Rated Health.” Journal of Health Care for the Poor and Underserved 31 (1):325–339. Keene, Danya E. and Erin Ruel. 2013. “‘Everyone Called Me Grandma’: Public Housing Demolition and Relocation among Older Adults in Atlanta.” Cities 35:359–364. Kingsley, G. Thomas. 2017. Trends in Housing Problems and Federal Housing Assistance Main Findings and Conclusions. Washington, DC: Urban Institute. Lloyd, P. C. and V. E. Helms. 2016. NCHS-HUD Linked Data: Analytic Considerations and Guidelines. Hyattsville, MD: Office of Analysis and Epidemiology, National Center for Health Statistics. Lopoo, Leonard M. and Andrew S. London. 2016. “Household Crowding During Childhood and Long-Term Education Outcomes.” Demography 53 (3):699–721. Needleman, Herbert L., Alan Schell, David Bellinger, Alan Leviton, and Elizabeth N. Allred. 1990. “The Long-Term Effects of Exposure to Low Doses of Lead in Childhood: An 11-Year Follow-up Report.” New England Journal of Medicine 322 (2):83–88. Newman, Sandra J. and Joseph M. Harkness. 2002. “The Long-Term Effects of Public Housing on Self-Sufficiency.” Journal of Policy Analysis and Management 21 (1):21–43. Newman, Sandra J. and C. Scott Holupka. 2014. “Housing Affordability and Investments in Children.” Journal of Housing Economics 24:89–100. Quadagno, Jill. 1996. The Color of Welfare. Oxford: Oxford University Press. Radford, Gail. 1996. Modern Housing for America: Policy Struggles in the New Deal Era. Chicago, IL: University of Chicago Press. Rice, Douglas. 2016. Chart Book: Cuts in Federal Assistance Have Exacerbated Families’ Struggles to Afford Housing. Washington, DC: Center on Budget and Policy Priorities.

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Simon, Alan E., Andrew Fenelon, Veronica Helms, Patricia C. Lloyd, and Lauren M. Rossen. 2017. “HUD Housing Assistance Associated With Lower Uninsurance Rates And Unmet Medical Need.” Health Affairs 36 (6):1016–1023. Slopen, Natalie, Andrew Fenelon, Sandra J. Newman, and Michel H. Boudreaux. 2018. “Housing Assistance and Child Health in the United States: A Systematic Review.” Pediatrics 141 (6). Swope, Carolyn B. and Diana Hernández. 2019. “Housing as a Determinant of Health Equity: A Conceptual Model.” Social Science and Medicine 243. Thomson, Hilary, Mark Petticrew, and David Morrison. 2001. “Health Effects of Housing Improvement: Systematic Review of Intervention Studies.” BMJ 323(7306):187–190. Wong, Michelle S., Carolyn M. Arnold, Eric T. Roberts, and Craig E. Pollack. 2019. “The Relationship Between Federal Housing Assistance and Uptake of Cancer Screening Among Low-Income Adults.” Journal of General Internal Medicine 34:2714–2716. Wong, Michelle. S., Eric. T. Roberts, Carolyn. M. Arnold, and Craig. E. Pollack. 2018. “HUD Housing Assistance and Levels of Physical Activity Among Low-Income Adults.” Preventing Chronic Disease 15:E94. Woo, Andrew and Chris Salvati. 2017. “Imbalance in Housing Aid: Mortgage Interest Deduction vs. Section 8.” https://www.apartmentlist.com/rentonomics/imbalancehousing-aid-mortgage-interest-deduction-vs-section-8/.

6 U.S. FOOD AND NUTRITION POLICY ACROSS THE LIFE COURSE Colleen M. Heflin

Since the Great Depression and the creation of the Food Stamp Program in 1939, the federal government has played a direct role in supporting the food consumption of poor households. Current federal food programs were either created or expanded as part of President Lyndon Johnson’s “War on Poverty.” While U.S. food policy targets low-income households, federal food and nutrition programs are administered from the U.S. Department of Agriculture (USDA), in recognition that U.S. farmers benefit when citizens have money to buy their goods. As a consequence, for several decades, legislation for food assistance programs was bundled with agricultural crop supports in what were known as “Farm Bills.” This tactic was successful in attracting political support from both urban and rural politicians across both political parties. Unfortunately, this strategy broke down in 2012 and has since been unsuccessful in the context of the overall breakdown in Congressional bipartisanship cooperation. As a result, support for food assistance programs, as well as other policies that support lowincome populations, has declined (Lusk 2013). Pre-COVID-19 food policy debates focused on the generosity of benefit programs and limiting access to food programs through the imposition of time limits and the expansion of work requirements. In the early 1990s, as part of the trend in public administration to measure the effectiveness of government programs, the USDA created a measure of food (in) security. Food security “means access by all people at all times to enough food for an active, healthy life” (Coleman-Jensen et al. 2018:2). Since its adoption in 1996 as an official measure of household well-being, it has become clear that food insecurity in the United States is an enduring social problem that spans the life course and has life-course patterning and connections to other life events. In 2018, 11.1% of households were considered food insecure according the USDA’s

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measure (Coleman-Jensen et al. 2019). During the COVID-19 pandemic, food insufficiency, a measure that indicates households sometimes or often do not have enough food, increased threefold from 3.4 percent in 2019 to 10.8 percent in July 2020 (Ziliak 2020). Key factors that shape the risk of food insecurity include marital status, household composition, race and ethnicity, education, income, homeownership, type of health insurance, and enrollment in federal food assistance programs (Ziliak and Gundersen 2018; Gundersen and Ziliak 2015; Goldberg and Mawn 2015). For example, those who are below the federal poverty line (FPL) are more than eight times as likely to be food insecure as those above 200% of the FPL; those who are divorced or separated are three times as likely to be food insecure as those who are married; and those who are unemployed are four times as likely to be food insecure as those who are employed (Ziliak and Gundersen 2019; Coleman-Jensen et al. 2017). Residents of certain states and geographic areas also are more likely to be food insecure. For example, 4.1% of those aged 60 and older in Colorado are food insecure compared to 18.6% of those aged 60 and older in Kentucky (Ziliak and Gundersen 2019; Keith-Jennings and Palacios 2017). Finally, race plays an especially salient role in the distribution of food insufficiency, with Black adults reporting rates of food insufficiency that are 2–3 times higher than White adults in typical years. During the summer of 2020, food insufficiency among Black adults rose to 20%. In what follows, I first provide an overview of the prevalence of food insecurity by age. Then, I provide a brief summary of the food programs that are currently available in the United States and discuss how the life-course perspective can inform future policy and research. I conclude with suggestions for future policy-relevant research in this area.

Food Insecurity Across the Life Course As with many measures of economic well-being, there is an age gradient to the risk of food insecurity. Using nationally representative, cross-sectional data from the 2015 and 2016 Current Population Survey, Figure 6.1 presents the prevalence of household food insecurity at each age. At birth, the risk of food insecurity is over 15% and it fluctuates between 15% and 20% during the first 18 years of life. Around age 18, the risk drops to about 15% and stays around there until young adults enter their mid-20s. The risk remains fairly constant around 13% between the mid-20s and mid-40s, before dropping consistently to approximately 11% in the 50s, 9% in the 60s, 8% in the 70s, and 5% in the 80s. The simple analysis shown in Figure 6.1 has a couple of limitations that are worth noting. First, the cross-sectional age pattern illustrated in Figure 6.1 might reflect cohort differences in the likelihood of reporting food insecurity. For example, those who lived during the Great Depression, when food was rationed, might be less likely to report food insecurity than other cohorts with less

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FIGURE 6.1 Household food insecurity by age. Note: Author’s calculations based on the 2015 and 2016 Current Population Survey.

common experiences of extreme scarcity because they have different expectations. Second, those who experience food insecurity might be more likely to die prematurely (Heflin et al. 2019), which could result in the positive selection of food-secure adults into the older ages. Nonetheless, the age-specific risk of food insecurity shown in Figure 6.1 illustrates many ideas central to the life-course perspective. First, the risk of food insecurity is highest during childhood, particularly from birth to school entry. Given that children are dependent on their primary care-takers for the provision of basic needs, this is an example of the linked lives principle of the life-course perspective, which focuses on the extent to which individuals in important relationships, such as the parent–child relationship, share outcomes and trajectories (Elder, Johnson, and Crosnoe 2003). There are many negative consequences associated with experiencing food insecurity over the life course (Gunderson and Ziliak 2015; Heflin et al. 2019), and there is a growing interest in identifying how these consequences vary based on the timing and sequencing of exposure. Generally, food insecurity is associated with poor physical health, mental health, and reduced health care utilization (sometimes termed the “treat or eat” trade-off) (Herman et al. 2015; Berkowitz et al. 2014; Gundersen and Ziliak 2015). Oftentimes, individuals who experience food insecurity simultaneously experience other forms of material hardship, such as housing hardships, utility hardships, or transportation hardships,

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and face the problem of having “more month than money” (Edin et al. 2013; Heflin 2017). Low-income individuals adopt a variety of strategies to try to mitigate food insecurity in the context of other material hardships (Heflin et al. 2011). Food insecurity is associated with reduced work productivity, school achievement, and cognitive functioning when mental bandwidth becomes preoccupied with identifying a food procurement strategy (Mani et al. 2013). As this occurs, executive functioning declines. Food insecurity-related declines in executive functioning during adolescence might lead to an increase in risky or negative behaviors, which translate into increased teen births, school suspension, and high school drop-out (Heflin et al. 2019). Finally, food insecurity also impacts personal relationships and family formation. Food insecurity is associated with a reduction in the probability that unmarried parents will marry after the birth of a child and an increase in family dissolution among married or cohabiting partners with a young child (Lerman 2002).

Food and Nutrition Programs in the United States In response to the prevalence of food insecurity at particular ages and its negative consequences for a range of life-course outcomes, the USDA has created a patchwork of food and nutrition programs that together reach one in four Americans annually. Eligibility criteria for these programs depend on the age, income, and (in some cases) the location of household members. Early childhood is targeted by the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), which currently covers half of all infants at birth in the United States. WIC program benefits are allocated for specific, nutrition-dense food items that can be purchased at food retailers or farmers’ markets. In addition, the Child and Adult Care Food Program is available to subsidize food for both child care centers and family care providers. Once children enter school, they are eligible to participate in the School Breakfast Program and National School Lunch Program. In addition, after-school snacks (and sometimes dinner) are available through the Child and Adult Care Food Program. During the transition to adulthood, especially after individuals transition out of secondary education, this patchwork of support becomes thin. For some adults, transitions to publicly funded total institutions—the military and prisons—become their source of food. For community-based, able-bodied adults without dependent children, in many states, the Supplemental Nutrition Assistance Program (SNAP) is limited to three months of receipt in a 36-month period, unless the individual meets state work requirements. For other adults, SNAP is the mainstay food and nutrition program to which they have access because it is available to all adults who meet the income requirements and is not time-limited for those who are disabled or have dependent children in the home (Wilde 2018). In terms of participation in food and nutrition programs among older adults: one in four SNAP households contains an older adult; many older-adult SNAP

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recipients live in multigenerational households; there has been a 10 percentagepoint increase in older adult SNAP recipients since 1992; and 13% of current SNAP participants are 60 or older (Cronquist and Lauffer 2019). Yet, SNAP participation among eligible adults aged 60 and over was roughly half that of the general population in 2015: 42% compared to 83% overall (Gray et al. 2017). This means that roughly 60% of those age 60 and older who are eligible are not enrolled in SNAP (Gundersen and Ziliak 2015). Moreover, significant state differences exist in the share of SNAP participants who are seniors (5% in Minnesota versus 15% in New York), which suggests that local conditions affect older adults’ access to this federal program (Popham 2019). Non-participation in SNAP among older adults often is attributed to the administrative burden of applying, lack of information about the program, and the low value of the benefits (Finkelstein and Notowidigdo 2018; Harrington Meyer and Adbul-Malak 2020; Gundersen and Ziliak 2015). Online application systems do not seem to reduce barriers to SNAP for older adults (Heflin et al. 2013), although they might for some other groups. Despite low participation rates, the absolute number of older adults participating in SNAP has continued to increase as the Baby Boom generation reaches retirement and older age (Cronquist and Lauffer 2019). For older adults, other food programs are available through the Older Americans Act. Sometimes known as Title III(C) programs, these include home delivered meals (commonly referred to as “Meals on Wheels”) and senior feeding sites (both congregate meal sites and senior centers). These programs, which are designed primarily to serve older adults, are not available in many locations because they are dependent on local non-profit organizations rather than state agencies to host the programs at the community level. Thus, access is limited by both geography and means-testing. Use of emergency food assistance, such as food pantries, which often operate under the Commodity Supplemental Food Program, is another way that foodinsecure households cope with their situation. Heflin and Price (2019) used nationally representative Current Population Survey data from 2002–2014 to examine changes over time in reported use of food pantries and to document how the age composition of food pantry users has shifted over time. In 2002, the largest share of food pantry users was between the ages of 25 and 49 (62.6%), followed by those age 50–64 (18.0%), those age 65 and older (11.4%), and young adults age 18–24 (7.9%). Beginning in 2004, users in the 50–64 age group started to grow. By 2014, household heads age 50–64 constituted 34.3% of the food pantry population, with those over age 65 constituting nearly 18%. By the end of the Great Recession in 2010, the food pantry population was much older than it had been at the beginning of the decade. The effectiveness of existing food and nutrition programs in reducing food insecurity is a subject of serious debate given that individuals who participate are likely to be more needy than similar eligible households who do not participate

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in the programs (Nord and Golla 2009). However, recent research suggests that SNAP alleviates hardship across a variety of domains (Gundersen and Ziliak 2014, 2015). Depending on the sample and the method of identification used, participation in SNAP has been found to lower the risk of household food insecurity by 5% to 20% (Kreider et al. 2012; Mabli et al. 2013). Additionally, from 2000 to 2011, SNAP benefits reduced the average level of household poverty by 4.9% and deep poverty by 14%, with even larger effects observed on child poverty (Tiehen et al. 2015).

Directions for Future Research There are two primary weaknesses of existing food and nutrition policies. First, there are three life-course transitions that are not well supported by existing policy. The first is when children transition to full-time school around the age of five. Currently, WIC eligibility ends in the month when a child turns five. Many school districts have moved the age at which children are eligible to attend kindergarten closer to age six, which creates a gap between when WIC ends and school meal programs begin. Recent research indicates that the gap between WIC and school entry is associated with negative effects on reading scores at kindergarten entry (Arteaga et al. 2018). This is an easy problem to fix: extend age eligibility for WIC to the age of school entry. An amendment to the last farm bill that would have extended WIC eligibility to age six was not adopted. The second life-course transition that existing food and nutrition policies do not adequately address is when young adults leave the family of origin and invest in further schooling or set up their first household. Research indicates that approximately 17% of young adults enrolled in two-year colleges and 11% of young adults enrolled in four-year colleges are food insecure (Blagg et al. 2017). The transition to adulthood is a precarious time, even for those privileged enough to attend college. Our public policies ought to invest in successful young adult transitions by ensuring food security. College campuses are no place for food pantries, which ultimately can only address students’ needs in a limited and piecemeal fashion. One potential policy solution would be to offer subsidized meal programs on college campuses as we do at earlier points in the life course. Such investments might focus on those who qualify for Pell Grants. Finally, the move into retirement often involves a change in an individual’s standard of living. Income inadequacy in retirement can progress into food insecurity and contribute to health decline. Our current measure of food insecurity might not accurately capture food insecurity among older Americans since it is rooted exclusively in capturing affordability (Jones et al. 2013). For older Americans, especially those with functional limitations and disabilities, getting to the store, transporting and storing the food, standing and cooking the food, and feeding oneself might be more significant barriers to food consumption than affordability (Heflin et al. 2019). Access to both SNAP and the Commodity

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Supplemental Food Program requires participants to be mobile. Meals on Wheels is the only program tailor-made for seniors, but it is available only in communities where there is a non-profit organization and a sufficient volunteer base to run the program. We need to do more to support food security among older Americans. The second major weakness of existing food and nutrition policies is that they often ignore the complexity of American households. SNAP, by far the largest of the federal programs, defines a SNAP household as those who live together and share food expenses. However, food might be cooked for those who live outside the household (as in the case where food is shared with a relative who cannot cook for herself or himself). Alternatively, food might be cooked separately among those who live together (often at great expense) because of health restrictions. With increasing complexity in family structure, children might move between and draw on the food resources of multiple households. These extra food costs are not accounted for in the structure of most food assistance programs. American food policy needs to account for complexities in how contemporary households prepare, share, and consume food.

Conclusion In summary, while food and nutrition policy currently spans the life course in the sense that federal food assistance is available from cradle to grave, it is not necessarily informed by a coherent life-course perspective. A coherent, lifecourse-informed set of food policies would pay more attention to the three transition points discussed above, as well as the complexity of modern families and the realities of inter- and intra-household food practices. However, this policy failure also stems from limitations in the extant research. Current research is hampered by the limitations of the data available to track and study food insecurity. Most U.S. panel datasets are currently fielded every two years, but food insecurity is defined as a 12-month measure. The food insufficiency measure used during the COVID-19 era captures conditions in the previous seven days. Thus, in longitudinal data sets, there is at least a one-year measurement hole. Additionally, there is a small sample size problem when one tries to focus on food insecurity among a particular age group (such as adolescents) or during a particular life-course transition (marriage, retirement, death of a spouse). These data limitations make it difficult to conduct systematic research on how the timing or sequencing of food insecurity influences future events. The current measure of food insecurity is perhaps even more problematic in that it focuses narrowly on identifying when food consumption is constrained by financial hardship. There are many other constraints on food consumption that are not rooted in financial resources. For example, functional limitations and disabilities might limit the ability to transport or prepare food, while cognitive problems might limit a person’s ability to organize or prepare healthy meals

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(Heflin et al. 2019). As another example, recent immigrants might be unfamiliar with local food options, unaware of emergency food assistance in their community, or unable to access culturally appropriate foods. It would be helpful for the research community to create a systematic food access measure that incorporates these other domains. In conclusion, the United States is distinct among industrialized countries for the variation in the forms of food and nutrition assistance available across the life course. There is substantial variation and complexity in approaches and outcomes across other countries. The existing food and nutrition policy structure in the United States is an important asset that allows the country to respond quickly in times of economic distress, such as the COVID-19 pandemic. For example, within months of the onset of COVID-19, households received the maximum SNAP benefit amount allowable for their family size, benefits in many states were revised to allow for home delivery, and states provided families with an electronic benefit card with benefits equal to the value of the school meals lost due to the cessation of in-person instruction. Given the importance of food security for health and development across the life course, and the rising concerns during the COVID-19 era over food prices, food access, and food insufficiency, state and federal policy makers should increase the accessibility of existing food and nutrition assistance programs by increasing the size of program benefits and by reducing administrative hurdles to application and recertification.

References Arteaga, Irma, Colleen Heflin, and Sarah Parsons. 2018. “Design Flaws: Consequences of the Coverage Gap in Food Programs on Children at Kindergarten Entry.” Applied Economics. Perspectives and Policy 41(2):265–283. https://doi.org/10.1093/aepp/ppy009. Berkowitz, Seth A., Hilary K. Seligman, and Niteesh K. Choudhry. 2014. “Treat or Eat: Food Insecurity, Cost-Related Medication Underuse, and Unmet Needs.” The American. Journal of Medicine 127(4):303–310. Blagg, Kristen, Craig Gundersen, Diane Whitmore Schanzenbach, James P. Ziliak. 2017. “Assessing Food Insecurity on Campus.” Urban Institute. https://www.urban.org/ sites/default/files/publication/92331/assessing_food_insecurity_on_campus_3.pdf. Coleman-Jensen, Alisha, Matthew P. Rabbitt, Christian A. Gregory, and Anita Singh. 2017. Household Food Security in the United States in 2016 (ERR-237). U.S. Department of Agriculture, Economic Research Service. Coleman-Jensen, Alisha, Matthew P. Rabbitt, Christian A. Gregory, and Anita Singh. 2018. Household Food Security in the United States in 2017 (ERR-256). U.S. Department of Agriculture, Economic Research Service. Coleman-Jensen, Alisha, Matthew P. Rabbitt, Christian A. Gregory, and Anita Singh. 2019. Household Food Security in the United States in 2018 (ERR-270). U.S. Department of Agriculture, Economic Research Service. Cronquist, Kathryn and Sarah Lauffer. 2019. Characteristics of Supplemental Nutrition. Assistance Program Households: Fiscal Year 2017. No. 9, ceac00f7e0f49ef85d3cc7ebfd2496b. Mathematica Policy Research.

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Edin, Kathryn, Melody Boyd, James Mabli, Jim Ohls, Julie Worthington, Sara Greene, Nicholas Redel, and Swetha Sridharan. 2013. SNAP Food Security In-depth Interview Study. Mathematica Policy Research. Elder, Glen H., Jr., Monica Kirkpatrick Johnson, and Robert Crosnoe. 2003. The Emergence and Development of Life Course Theory. P. 3–19 in Jeylan T. Mortimer and Michael J. Shanahan, eds,, Handbook of the Life Course. Boston, MA: Springer Publishing. Finkelstein, Amy and Matthew J. Notowidigdo. 2018. “The Effects of Information and Application Assistance: Experimental Evidence from SNAP.” Institute for Policy. Research Working Paper 18–03. Goldberg, Shari L. and Barbara E. Mawn. 2015. “Predictors of Food Insecurity Among Older Adults in the United States.” Public Health Nursing 32 (5):397–407. Gray, Kelsey Farson and Karen Cunnyngham. 2017. Trends in Supplemental Nutrition. Assistance Program Participation Rates: Fiscal Year 2010 to Fiscal Year 2015. https://www. mathematica.org/our-publications-and-findings/publications/trends-in-snap-participati on-rates-fiscal-year-2010-to-fiscal-year-2015. Gundersen, Craig and James P. Ziliak. 2014. Childhood Food Insecurity in the U.S.: Trends, Values, and Policy Options. The Future of Children, Vol. 24. Princeton University. Gundersen, Craig and James P. Ziliak. 2015. “Food Insecurity and Health Outcomes.” Health Affairs 34 (11):1830–1839. Harrington Meyer, Madonna and Ynesse AbdulMalak. 2020. Grandparenting Children with Disabilities. Boston, MA: Springer Publishing. Heflin, Colleen. 2017. “The Role of Social Positioning in Observed Patterns of Material Hardship: New Evidence from the 2008 Survey of Income and Program Participation.” Social Problems 64(4):513–531. https://doi.org/10.1093/socpro/spw041. Heflin, Colleen, Claire Altman, and Laura Rodriguez. 2019. “Food Insecurity and Disability in the United States.” Disability and Health Journal 12 (2):220–226. https://doi. org/10.1016/j.dhjo.2018.09.006. Heflin, Colleen, Sharon Kukla-Acevedo, and Rajeev Darolia. 2019. “Adolescent Food Insecurity and Risky Behaviors and Mental Health During the Transition to Adulthood.” Children. and Youth Services Review 105:104416. https://doi.org/10.1016/j. childyouth.2019.104416. Heflin, Colleen M., Andrew S. London, and Ellen K. Scott. 2011. “Mitigating Material Hardship: The Strategies Low-Income Families Employ to Reduce the Consequences of poverty.” Sociological Inquiry 81 (2):223–246. Heflin, Colleen M., Andrew S. London, and Peter R. Mueser. 2013. “Clients’ Perspectives on a Technology-Based Food Assistance Application System.” American Review of Public Administration 43 (6):658–674. Heflin, Colleen and Ashley Price. 2019. “Emergency Food Assistance and the Great Recession.” Journal of Hunger and Environmental Nutrition 14(1–2):225–239. https://doi. org/10.1080/19320248.2018.1434099. Herman D., P. Afulani, Alisha Coleman-Jensen, and Gail G. Harrison. 2015. “Food Insecurity and Cost-Related Medication Underuse Among Nonelderly Adults in a Nationally Representative Sample.” American Journal of Public Health 105 (10):48–59. Jones, Andrew D., Francis M. Ngure, Gretel Pelto, and Sera L. Young. 2013. “What Are We Assessing When We Measure Food Security? A Compendium and Review of Current Metrics.” Advances in Nutrition 4(5):481–505. https://doi.org/10.3945/an.113.004119. Keith-Jennings, Brynne and Vincent Palacios. 2017. “SNAP Helps Millions of Low-Wage Workers.” Center on Budget and Policy Priorities. May 10. https://www.cbpp.org/ research/food-assistance/snap-helps-millions-of-low-wage-workers.

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Kreider, Brent, John V. Pepper, Craig Gundersen, and Dean Jolliffe. 2012. “Identifying the Effects of SNAP (Food Stamps) on Child Health Outcomes When Participation Is Endogenous and Misreported.” Journal of the American Statistical Association 107 (499): 958–975. Lerman, Robert I. 2002. Impacts of Marital Status and Parental Presence on the Material Hardship of Families with Children. Report. Washington, DC: Urban Institute and American University. Lusk, Jayson. 2013. “Public Opinion about the Food Stamp Program.” Farmdoc Daily (3):199. Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, October 18. Mabli, James, Jim Ohls, Lisa Dragoset, Laura Castner, and Betsy Santos. 2013. Measuring the Effect of Supplemental Nutrition Assistance Program (SNAP) Participation on Food Security No. 69d901432c7a46779666a240a0974a5d. Mathematica Policy Research. Mani, Anandi, Sendhil Mullainathan, Eldar Shafir, and Jiaying Zhao. 2013. “Poverty Impedes Cognitive Function.” Science 341(6149): 976–980. http://doi.org/10.1126/sci ence.1238041. Nord, Mark and Marie Golla. 2009. “Does SNAP Decrease Food Insecurity? Untangling the Self-Selection Effect” (ERR-85). U.S. Department of Agriculture, Economic Research Service. Popham, Lauren. 2019. “Supplemental Nutrition Assistance Program (SNAP) Participation Rates Among Eligible Adults Age 60+.” National Council on Aging. https:// www.ncoa.org/economic-security/benefits/visualizations/senior-snap-participation/. Tiehen, Laura, Dean Jolliffe, and Timothy Smeeding. 2015. The Effect of SNAP on Poverty. P. 49–73 in Judith Bartfeld, Craig Gundersen, Timothy Smeeding, and James P. Ziliak, eds., SNAP Matters: How Food Stamps Affect Health and Well-Being. Stanford University Press. Wilde, Park. 2018. Food Policy in the United States: An Introduction. 2nd ed. New York: Routledge. Ziliak, James P. 2020. “Food Hardship During the COVID-19 Pandemic and Great Recession.” Applied Economic Perspectives and Policy. Forthcoming. Ziliak, James P. and Craig Gundersen. 2018. “The State of Senior Hunger in America 2016.” https://www.feedingamerica.org/sites/default/files/research/senior-hunger-re search/state-of-senior-hunger-2016.pdf. Ziliak, James P. and Craig Gundersen. 2019. “The State of Senior Hunger in America 2017.” https://www.feedingamerica.org/sites/default/files/research/senior-hunger-re search/state-of-senior-hunger-2017.pdf.

7 CRIME AND DELINQUENCY OVER THE LIFE COURSE Adolescence, Peers, and Policy Jason P. Robey and Michael Massoglia

Policies focused on criminal behaviors tend either to react to criminal behavior with punishment or to attempt to prevent criminal behavior through intervention. The criminal justice system tends to take the former approach by responding to criminal behavior with various punishments, generally enforced after the peak ages of participation in criminal behavior (Cohen 1985; Chalfin and McCrary 2017). As the penal system expanded in recent decades, the main focus of criminal justice policy was expanding the number of people controlled by the system, as well as increasing the severity with which they were punished (Garland 2001a, 2001b; Western 2006). Often overlooked during the recent period of rising incarceration rates are policies that seek to prevent the initial development of criminal behaviors. With respect to crime prevention policy, two of the most robust findings in the study of criminal behavior are relevant: (1) the age–crime curve (Gottfredson and Hirschi 1990; Steffensmeier et al. 1989; Moffitt 1993; Sampson and Laub 1995); and (2) the strong association between individuals and their peers on delinquent outcomes (Matsueda 1982; Haynie 2001; McGloin and Thomas 2019). On the basis of these findings, an extensive theoretical and empirical literature has developed that focuses on peer influences on delinquency among adolescents. This literature recognizes that adolescence is the stage in life when individuals begin to experiment with delinquent behaviors. This experimentation often occurs in the presence of peers. In this chapter, we draw upon the life-course perspective to advance the idea that the strategy of crime prevention should be preferred over the strategy of punishment both when enacting new policy and when evaluating existing policy. Specifically, we argue that prevention strategies should focus on peer influences during adolescence given the extant empirical literature on the development of crime during adolescence and the strong association between peers and

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individuals on delinquent outcomes. However, we maintain that the development of more robust crime prevention strategies must begin with a reassessment of the empirical evidence regarding the influence of adolescent peers on the development of criminal behaviors. Although the literature has established evidence of a strong association between peers with respect to delinquent outcomes, it remains empirically unclear whether this association is due to peer influence or peer selection. If peers truly influence each other to commit delinquent acts, then interventions focused on peer networks will be effective in reducing delinquency. However, if peer selection drives the correlation of behavior among peers, then intervening on peer networks will have only limited success because the true cause of the delinquency lies outside the peer group. We begin our life-course-informed reassessment of theory and evidence relevant to crime prevention with a brief overview of the literature on the development of criminal behaviors over the life course. We then examine the most well-developed theories in life-course criminology. Next, we consider how and why the extant criminological literature on peer effects has produced compelling observational evidence but maintain that causal evidence in this field remains somewhat limited. In a brief methodological aside, we discuss the importance of causal estimates for the development of policies related to adolescent peer influences and prevention. To illustrate these concepts, we provide a brief review of a few of the most well-known intervention strategies proposed for and evaluated among adolescents. Finally, we conclude with a proposal for a renewed policy emphasis on prevention strategies that focus on peer relations in adolescence. Our proposal includes a call for a reinvigorated effort to demonstrate empirically the causal effects of peers on delinquent outcomes among adolescents.

The Age–Crime Curve and Life-Course Criminology One of criminology’s most consistently demonstrated findings is the rapid development and concentration of criminal behavior in young adulthood, or the age–crime curve. The relationship between age and crime varies somewhat across time, space, demographic groups, and different crime types. However, it tends to follow a unimodal distribution with a rapid increase in criminal involvement beginning in early adolescence that peaks in the late teens to early twenties (Gottfredson and Hirschi 1990; Steffensmeier et al. 1989; Moffitt 1993). Although this pattern is generally observed, the degree of desistance with age varies, and there is some evidence that criminal behavior has relatively recently become even more concentrated in adolescence and young adulthood (Steffensmeier et al. 1989). Building from the empirical foundation of the age–crime curve, criminology has developed a strong life-course perspective. In life-course criminology, two major theories predominate: (1) Sampson and Laub’s age-graded theory of informal social control (Sampson and Laub 1995; Laub and Sampson 2003); and

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(2) Moffitt’s taxonomy of life-course-persistent and adolescent-limited trajectories of offending (Moffitt 1993). Sampson and Laub’s age-graded social control model builds on Hirschi’s theory of social control (Hirschi 1969). In perhaps the most well-known adaptation of Hirschi’s original articulation of control theory, Sampson and Laub incorporate a life-course perspective and provide further evidence of the salience of social bonds. Their theory attempts to explain both continuity and change in delinquent involvement over the life course by positing that the social bonds that constrain deviant behavior change and are more impactful at different points in the life course. In other words, social bonds prevent individuals from committing criminal or delinquent behaviors, and the salience of these social bonds change over the life course, from the family in childhood, to peers and schools in adolescence, and returning to the family and employment during adulthood. In adulthood, the central social bonds described by Sampson and Laub are job stability, commitment to occupation, and attachment to spouse, as these normative role-related connections to work and family are the most strongly associated with desistance from criminal activity (Sampson and Laub 1995; Laub and Sampson 2003). Overall, the theory implies that individuals with meaningful ties to work and family have more to lose if they are caught, which restrains their impulses to engage in deviant or criminal behavior. As criminology-oriented sociologists developed and empirically tested a lifecourse perspective related to social bonds, psychologists posited a developmental theory of crime over the life course. Moffitt (1993) theorizes a dual taxonomy to characterize developmental types and claims that underlying population heterogeneity explains the age–crime curve. Moffitt’s theory posits two typologies of criminal careers over the life course: life-course-persistent and adolescent-limited. The life-course-persistent offenders display early signs of antisocial behavior in childhood and continue their anti-social behavior throughout adolescence and adulthood, with different manifestations of the behavior over the life course. For these individuals, the roots of their behavior lie in neuropsychological development, as early as the fetal development of their brains, and childhood development. Moreover, these early childhood behavioral difficulties lead to challenges with socialization and strained personal relationships with peers, family members, and other potentially pro-social network members. To the extent that peers matter for life-course-persistent offenders, they reinforce tendencies that already exist or provide opportunities for individuals to act in ways in which they already are primed to act. For adolescent-limited offenders, on the other hand, the development of antisocial behavior is explained by more proximal factors, including association with lifecourse-persistent peers in contexts where they can exercise some agency in making choices about whether, how, and for how long to associate with such individuals. With respect to explaining the behavior of life-course-persistent offenders, one must explain the continuity of their behavior. For those who follow the

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adolescent-limited trajectory, one must explain the discontinuity of their behavior. The available evidence indicates that the adolescent-limited trajectory is far more common than the life-course-persistent trajectory (Moffitt 1993). This suggests that, from a policy perspective, efforts to prevent initiation for both groups and to understand the factors that lead to desistance will likely yield the highest return on investment. Regardless of the particular theoretical tradition to which one ascribes or the number of career types one identifies, life-course criminology has demonstrated a robust relationship between age and crime (Piquero 2008). Given that all crime trajectories start in adolescence, it is clear that the development, persistence, and desistance of criminal behavior depend on changing social contexts over the life course. As a result, policy efforts aimed at either preventing or responding to criminal behaviors must pay particular attention to an individual’s position in the life course and the social contexts associated with that stage of life.

Peer Influences In the period of adolescence when criminal behaviors develop and are concentrated, peer influence is one of the most relevant social contexts. In addition to the age– crime curve, one of the most robust empirical findings in criminology is the strong association between an individual’s delinquency and the delinquency of the individual’s friends (Warr 2002). Theoretically, the extant criminological research on peer effects focuses on testing two dominant theories of peer influence—differential association and social learning—against competing hypotheses, such as social control theory (Sutherland and Cressey 1978; Burgess and Akers 1966; Matsueda 1982; Haynie 2001; McGloin and Thomas 2019). The longest-standing and most-developed theoretical tradition in the study of peer influence is Sutherland’s differential association theory (Sutherland and Cressey 1978). At its core, differential association theory posits that social interactions with close peers are the mechanism through which individuals learn most behaviors, including criminal behaviors. More specifically, criminal behaviors are learned through interactions with intimate personal groups, including family and friends. In these interactions, individuals learn the techniques for committing criminal behavior and the motivations and justifications for and against committing criminal behavior. Sutherland referred to the individual’s knowledge of the benefits and consequences of criminal behavior as the “definitions favorable to violation of law” and “definitions unfavorable to violation of law,” respectively (Sutherland and Cressey 1978:81). The central idea underlying differential association theory is that only those who have an excess of definitions in favor of law violation relative to definitions against violating the law will commit crimes. Thus, peer influence indirectly affects criminal behavior by influencing whether individuals view criminal behavior favorably or unfavorably. Burgess and Akers’ (1966) social learning theory generalizes differential association theory and

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eliminates the need for individuals to adopt definitions in favor of the law. They draw on the psychological theories of Skinner (1953) to posit that criminal behaviors are learned from peers through mimicry, imitation, and positive reinforcement. Neither of these theories explicitly states the ages at which the learning of criminal behavior occurs. However, in combination with the prevailing knowledge of the age–crime curve and a life-course perspective, these theories clearly point to adolescence as the key period for learning criminal behaviors (see also Moffitt 1993). In addition to these theories focused on peer influence, some scholars have posited peer influence as a more proximate causal mechanism in other theories of criminal behavior, such as age-graded social control theory (Warr 2002). Warr (1998) argues that the crime-constraining effect of marriage operates through peers because spouses constrain individuals’ contacts with delinquent peers. Overall, for the purposes of crime prevention, there is ample theoretical justification for focusing on the influence of peers on delinquent outcomes, particularly in the adolescent period of the life course. Based on this theoretical foundation, there have been numerous empirical tests of the influence of peers, particularly adolescent peers, on delinquent outcomes (McGloin and Thomas 2019). In general, the empirical literature has found a strong association between the delinquency of individuals and their peers, using a variety of datasets, methods, and measures of delinquency. Although this empirical foundation is strong, it is important to recognize that convincing evidence of causal effects has been somewhat limited, even though the field has made significant improvements toward causal identification in recent decades. In our view, six major innovations in methodology, data, and measurement are of particular importance. Together, these six improvements have contributed to stronger claims related to the causal identification of peer influences on criminal behavior by limiting the potential influence of confounding factors, such as environmental conditions, selection, and endogenous measurement. The first, and perhaps the most important, change was the shift in the measurement of peer delinquency from perceived peer delinquency (Matsueda 1982) to actual peer delinquency (Haynie 2001; Clark and Loheac 2007). In surveys like the National Youth Survey (NYS), perceived peer delinquency was measured by asking individuals how much delinquency their friends committed. These perceived measures of peer delinquency were critiqued for being endogenous to self-reported measures of delinquency because the same person was reporting both their own self-reported delinquency and their friends’ delinquency. In contrast, more innovative datasets like the National Longitudinal Study of Adolescent to Adult Health (Add Health) measure friends’ delinquency directly by connecting the self-reported delinquency of respondents through information on their friendship networks. This measurement development in Add Health was an enormous development in the study of peer effects (Haynie 2001).

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Second, the shift from cross-sectional to longitudinal research designs enhanced the ability of researchers to determine temporal order, which is necessary for valid causal inference (Clark and Loheac 2007). This was one of the most important methodological developments for the field because it helped resolve the reflection problem (Manski 1993). The reflection problem means that if you observe two individuals at a single point in time, it is nearly impossible to distinguish the direction of the association (i.e., is it the effect I have on my friend or the effect my friend has on me?). This reflection problem makes cross-sectional studies of peer effects inherently flawed. Third, in relation to these two developments, new datasets became available and researchers shifted from the Richmond Youth Project (Matsueda 1982) to the NYS to the now-predominant Add Health (Haynie 2001; Clark and Loheac 2007). Each of these newer datasets had advantages relative to the older datasets they replaced. A fourth major methodological shift was a reexamination of the mechanism by which individuals are influenced by their friends’ delinquency. Early studies of peer delinquency focused on the definitions of the law as a mediator, meaning that individuals learned definitions favorable to law violation that led them to commit delinquency (Matsueda 1982). However, more recent work has focused on the direct effect of peer delinquency on individual delinquency (Haynie 2001). Fifth, there has been a limited methodological transition toward including contextual fixed effects in models (Clark and Loheac 2007; Kim and Fletcher 2018), which is essential for reducing the bias of environmental confounders in peer-effects studies. The final shift, and the least commonly adopted in the field, has been the modification of the definition of the peer group. This entails moving beyond “friends” to include other potential peers, such as the school grade and roommates (Clark and Loheac 2007; Duncan et al. 2005). Authors generally use these different definitions of peer groups to exploit exogenous variation for causal identification. Overall, these six shifts in methodology, data, and measurement have served to reduce, but not fully eliminate, the effects of selection and environmental confounding on estimates of peer influence. Although the field has made significant strides toward stronger causal identification in peer effect estimates, we argue that the current empirical literature does not provide a consensus on causation with respect to peer delinquency. As a result, we call for more research attention to be focused on adopting recent methodological advances in the causal identification of peer effects. Identifying the causal effect of peer delinquency will have significant implications for both policy and theoretical understandings of peer influences. We advocate a counterfactual framework to thinking about causal peer effects, which emphasizes the distinct roles of different sources of peer associations and

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the implications each has for theory and policy. The counterfactual framework of causal inference (Morgan and Winship 2015) seeks to answer causal questions by theorizing about a world in which everything is the same except that a specific variable of interest has changed value, as in a randomized control trial. In this case, we recommend thinking about a world in which everything in the adolescent’s life is the same, except that the amount or kind of delinquency among their friends has changed. The counterfactual framework for understanding causal peer effects has several useful, policy-relevant, theoretical, and empirical implications for the criminological literature on peer delinquency. A central aspect of the counterfactual framework as applied to this topic is a recognition that there are three different sources of peer association in any given outcome measure. Peer associations on outcomes can arise from: direct peer influence, peer selection, or shared environmental characteristics (Blume et al. 2011; Manski 1993; VanderWeele and An 2013). Direct peer influence is the mechanism that criminologists have theorized affects individual outcomes, whereas peer selection and shared environmental characteristics are two potential sources of confounding. To the extent that previous tests of peer influence are confounded by unmeasured peer selection and shared environmental factors, studies have likely incorrectly estimated why individuals and peers have similar levels of delinquency. In the presence of strong peer selection on delinquent outcomes, it could simply be that delinquent individuals are more likely to be friends with each other. Whether the peer association is a result of direct peer influence or peer selection has significant policy implications because these different sources of peer association suggest different policy interventions. We examine these policy implications further in the next section. The different sources of peer association remain relatively unexamined in the criminological literature, despite the importance of addressing this issue for theory and policy (notable exceptions include Duncan et al. 2005; Clark and Loheac 2007; Kim and Fletcher 2018). Empirically, the existing literature has relied largely on limited observational datasets from the United States and smallscale experimental designs. One common experimental design exploits randomization in college roommate assignment to identify the causal effect of roommates on delinquency outcomes. Although studies with this design provide compelling causal evidence, their focus on college students misses the critical period of adolescence in the development of criminal behaviors and the population most likely to engage in criminal behavior (Duncan et al. 2005). Several observational studies since 2000 use the Add Health dataset and only address peer selection effects to a limited degree (Haynie 2001; Clark and Loheac 2007; Kim and Fletcher 2018). From our perspective, it is critically important for researchers to use other data sources that offer different, and perhaps more suitable, options for causal identification. For instance, registry data from Scandinavian countries offers one potential avenue for understanding peer influences with comprehensive administrative data from birth through death on every citizen. More generally, an

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incorporation of the counterfactual framework of causal peer effects will greatly improve the fields’ ability to empirically disentangle the peer effect of interest (influence) from other confounding forms of peer association.

Relevant Policy Programs and Experiments In the late 1970s, the U.S. penal system began to expand to unprecedented levels, historically and cross-nationally. By 2008, the incarceration rate had risen more than five-fold (Western 2006). During this expansion of the penal system, the majority of reforms focused on increasing the harshness of punishments and expanding the population being punished. Although increased penalties were theorized to deter as well as to punish crime, relatively less policy attention was devoted to specific prevention or intervention programs for youth. Although not the primary emphasis in criminal justice practice, the field of policy criminology has built a significant body of knowledge on what works (and what does not work) to reduce crime (Sherman et al. 1998; Abt and Winship 2016). One of the most well-known intervention programs focused on adolescent peers is the Drug Abuse Resistance Education (D.A.R.E.) program. The D.A.R.E program involves a series of short educational lessons led by uniformed police officers in schools across the United States and around the world. The central message of D.A.R.E. is that teaching students about the dangers of drugs, gangs, and violence will better enable students to resist the impulse to engage in these behaviors. In particular, D.A.R.E. emphasizes peer pressure from delinquent peers as one of the central causes of delinquent behaviors. Thus, the prevention strategy that D.A.R.E. emphasizes is mostly oriented toward resisting peer pressure. The program also encourages participants to inform the authorities of any criminal behavior at home or among their peers. Despite the program’s strong focus on peer relations, it has been repeatedly shown to be ineffective in reducing criminal behaviors (for a review of the literature, see Sherman et al. 1998). The failure of the D.A.R.E. program demonstrates that simply focusing on peer relations in adolescence does not guarantee successful reductions in criminal behavior. Thus, a more nuanced understanding of peer effects on delinquent outcomes is necessary for successful intervention. Another common approach used to intervene on delinquent behavior among youth is separating delinquent youth into their own classrooms in schools or groups in community-service programs. The assumption is that removing delinquent youth from general classrooms and groups will limit their influence on their peers’ behavior. However, concentrating youth with behavioral problems in classrooms might encourage greater delinquency among already delinquent youth. A comprehensive review of the literature concludes that programs that separate delinquent youth are largely inconsistent with the findings of the existing literature on peer influences on delinquency. Specifically, this is inconsistent because the prior literature suggests that segregating delinquent youth will

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exacerbate their delinquent behavior, yet many schools rely primarily on segregation as a means of disciplining delinquent youth (Gifford-Smith et al. 2005). Moreover, an experimental study of randomly assigned college roommates provides some support for the idea that aggregating deviant individuals can exacerbate their deviant behaviors, even when those individuals are randomly assigned and thus have no prior relationship. It should be noted that this effect was only present among males for drinking behavior and no effect was found for females or males on sexual behaviors or marijuana use (Duncan et al. 2005). Given our limited knowledge of the mechanisms through which peers influence delinquent behaviors, it might be premature to conclude that separating delinquent youths is an ineffective or harmful policy strategy. Moreover, there are remaining policy-relevant questions regarding optimal allocation and overall effects. For example, if separating delinquent youth has a strong protective effect against delinquency in general classrooms and only a modest multiplier effect on delinquency in the delinquent classrooms, then the policy might be beneficial overall in reducing crime. The aggregation of delinquent students in a single classroom also could facilitate targeted intervention strategies. In sum, existing policy interventions have had limited success, but there still is hope; as discussed above, research designed with better measurement and identification strategies can inform more robust and successful policies.

Policy Implications—Why Focus on Peer Effects? As it relates to policy implications, studying adolescent peer effects from a counterfactual framework will contribute three distinct but intersecting advantages. First, adolescence is a key period in the development of criminal behaviors, as demonstrated by the robustness of the age–crime curve. Adolescence is the stage of the life course with the highest rates of initiation and prevalence of delinquency behaviors. Thus, it is a key life-course period for interventions to reduce criminal behaviors. Second, adolescence is a period of life that is ripe with opportunity for interventions. Interventions can be implemented and targeted through schools, parents, friends, neighborhoods, extracurricular activities, or the juvenile justice system. Lastly, the strength of the counterfactual framework for research is that it allows researchers to distinguish between different sources of peer association, each of which suggests a different point of intervention. If the primary source of peer association is direct peer influence, this suggests that interventions in peer networks could effectively reduce criminal behaviors. If, however, the main source is peer selection, then interventions on peer networks will not address the true source of delinquent behaviors and might even provide opportunities for delinquency. Instead, peer selection effects suggest intervention through traditional social controls, such as schools, parents, employment, or early-life factors. Lastly, if the source is actually the shared environment, then interventions should focus on the environmental or

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community-level characteristics that influence criminal behaviors. In any given context or study, any of these sources of peer association might influence outcomes. Thus, if we aim to make specific policy recommendations, it is essential to specify which source we are testing empirically and to develop an analytic strategy that isolates the desired source of influence. Intervening to disrupt adolescent peer networks is difficult and efforts evaluated to date have been found to be minimally effective (Sherman et al. 1998; Abt and Winship 2016; Gifford-Smith et al. 2005). In the end, we have much to learn about adolescent development as it relates to peer influence, which suggests the need for the more nuanced, counterfactual approach that we recommend for estimating the influence of delinquent peers. It is not enough to simply demonstrate that individuals and their peers have similar levels of delinquency; we need to know whether delinquent peers influence greater delinquency in others and the mechanisms through which this influence operates. Moreover, given this information, we need to strongly consider whether interventions should be focused on creating certain individual-level or group-level outcomes. For example, if the intervention is schoolbased, is the ultimate goal reducing the proportion of individual students involved in delinquency, reducing the number of delinquent acts committed by delinquent students, reducing the overall number of delinquent acts committed in a given school, reducing the severity of delinquent acts, or limiting the progression of delinquent youth to criminal adults? Only when we have defined the desired outcomes of interventions can we begin to devise effective policy innovations for reducing criminal behaviors among youth. Given that most life-course-persistent criminal careers start in adolescence, successful interventions in adolescence are also likely to reduce the incidence of criminality in adulthood.

Life-Course Implications of Crime and Criminal Justice Involvement Although preventing criminal behaviors in adolescence is important in its own right (Odgers et al. 2008), it is particularly consequential in an era of criminal justice expansion. The criminal justice policies common in the era of mass incarceration both increased the number of individuals, including many youth, caught in the system and punished them more severely. As a result, involvement in the criminal justice system today creates social consequences that endure across the life course (London and Myers 2006). These social consequences include but are not limited to: lower and stagnated wages (Western 2002; Western 2006); difficulties gaining employment (Pager 2003); worse health outcomes (Massoglia 2008; Massoglia and Pridemore 2015); poor neighborhood attainment (Massoglia et al. 2013); disenfranchisement for individuals with potential ramifications for state and national election outcomes (Uggen and Manza 2002; Manza and Uggen 2008); increased likelihood of divorce or separation (Lopoo and Western 2005: Massoglia, Remster, and King 2011); and worse outcomes for the expanding

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population of children with incarcerated parents (Wildeman 2009; Wakefield and Wildeman 2013). These social consequences of the criminal justice system are not experienced evenly across the United States, with poor communities and communities of color consistently suffering the worst consequences (Western 2006). In addition to these social consequences, incarceration also has become a significant life-course event, particularly in these same poor communities and communities of color. Pettit and Western (2004) estimate that the cumulative risk of incarceration was 60% for Black male high school dropouts coming of age at the height of penal expansion. Among Black males born during this era, incarceration was a more common experience than college. Finally, involvement in criminal behaviors, and particularly in the criminal justice system, disrupts other life-course events, such as marriage and education, and inhibits the selfappraised attainment of adult status (Massoglia and Uggen 2010). In response to disparities in the criminal justice system and police violence, in particular, a political consensus is building that our criminal justice system needs to be reformed (Beckett 2018; Levin 2018; Obama 2016; Western 2019). Calls for reform focus on grassroots organization, as well as specific legislative initiatives aimed at local, state, and federal policy reforms. We agree that there is a pressing need to directly address the intended and unintended social consequences of current policies and practices (see Dannefer and Han in this volume) and disparities in the criminal justice system with policy reforms. However, in the interest of reducing the initial exposure to our criminal justice system, it is also imperative that we focus on policy reforms that will prevent the development of delinquent and criminal behaviors in adolescence. As we have argued in this chapter, a renewed focus on peer effects among adolescents, with better data that allow for the estimation of causal effects, is a promising direction for future policy-relevant investigations.

References Abt, Thomas and Christopher Winship. 2016. “What Works in Reducing Community Violence: A Meta-Review and Field Study for the Northern Triangle.” Center for Victim Research. Democracy International, Inc., Bethesda, MD. Beckett, Katherine. 2018. “The Politics, Promise, and Peril of Criminal Justice Reform in the Context of Mass Incarceration.” Annual Review of Criminology 1:235–259. Blume, Lawrence E., William A. Brock, Steven N. Durlauf, and Yannis M. Ioannides. 2011. Identification of Social Interactions. P. 853–964 in Handbook of Social Economics. Elsevier. Burgess, Robert L. and Ronald L. Akers. 1966. “A Differential Association-Reinforcement Theory of Criminal Behavior.” Social Problems 14 (2):128–147. Chalfin, Aaron and Justin McCrary. 2017. “Criminal Deterrence: A Review of the Literature.” Journal of Economic Literature 55 (1):5–48. Clark, Andrew E. and Youenn Loheac. 2007. “‘It Wasn’t Me, It Was Them!’ Social Influence in Risky Behavior by Adolescents.” Journal of Health Economics 26 (4):763– 784.

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Cohen, Stanley. 1985. Visions of Social Control: Crime, Punishment and Classification. Cambridge, UK: Polity Press. Duncan, Greg J., Johanne Boisjoly, Michael Kremer, Dan M. Levy, and Jacque Eccles. 2005. “Peer Effects in Drug Use and Sex Among College Students.” Journal of Abnormal Child Psychology 33 (3):375–385. Garland, David. 2001a. Mass Imprisonment: Social Causes and Consequences. Thousand Oaks, CA: Sage. Garland, David. 2001b. The Culture of Control: Crime and Social Order in Contemporary Society. Chicago, IL: University of Chicago Press. Gifford-Smith, Mary, Kenneth A. Dodge, Thomas J. Dishion, and Joan McCord. 2005. “Peer Influence in Children and Adolescents: Crossing the Bridge from Developmental to Intervention Science.” Journal of Abnormal Child Psychology 33 (3):255–265. Gottfredson, Michael R. and Travis Hirschi. 1990. A General Theory of Crime. Palo Alto, CA: Stanford University Press. Haynie, Dana L. 2001. “Delinquent Peers Revisited: Does Network Structure Matter?” American Journal of Sociology 106 (4):1013–1057. Hirschi, Travis. 1969. Causes of Delinquency. Berkeley, CA: University of California Press. Kim, Jinho and Jason M. Fletcher. 2018. “The Influence of Classmates on Adolescent Criminal Activities in the United States.” Deviant Behavior 39 (3):275–292. Laub, John H. and Robert J. Sampson. 2003. Shared Beginnings, Divergent Lives. Cambridge, MA: Harvard University Press. Levin, Benjamin. 2018. “The Consensus Myth in Criminal Justice Reform.” Michigan Law Review 117 (2):259–318. London, Andrew S. and Nancy A. Myers. 2006. “Race, Incarceration, and Health: A Life-Course Approach.” Research on Aging 28 (3):409–422. Lopoo, Leonard M. and Bruce Western. 2005. “Incarceration and the Formation and Stability of Marital Unions.” Journal of Marriage and Family 67 (3):721–734. Manski, Charles F. 1993. “Identification of Endogenous Social Effects: The Reflection Problem.” The Review of Economic Studies 60 (3):531–542. Manza, Jeff and Christopher Uggen. 2008. Locked Out: Felon Disenfranchisement and American Democracy. Oxford, UK: Oxford University Press. Massoglia, Michael. 2008. “Incarceration, Health, and Racial Disparities in Health.” Law & Society Review 42 (2):275–306. Massoglia, Michael, Glenn Firebaugh, and Cody Warner. 2013. “Racial Variation in the Effect of Incarceration on Neighborhood Attainment.” American Sociological Review 78 (1):142–165. Massoglia, Michael and William A. Pridemore. 2015. Incarceration and Health. Annual Review of Sociology 4: 291–310. Massoglia, Michael, Brianna Remster, and Ryan D. King. 2011. “Stigma or Separation? Understanding the Incarceration-Divorce Relationship.” Social Forces 90 (1):133–155. Massoglia, Michael and Christopher Uggen. 2010. “Settling Down and Aging Out: Toward an Interactionist Theory of Desistance and the Transition to Adulthood.” American Journal of Sociology 116 (2):543–582. Matsueda, Ross L. 1982. “Testing Control Theory and Differential Association: A Causal Modeling Approach.” American Sociological Review 47 (4):89–504. McGloin, Jean Marie and Kyle J. Thomas. 2019. “Peer Influence and Delinquency.” Annual Review of Criminology 2:241–264. Moffitt, Terrie E. 1993. “Adolescent-Limited and Life-Course-Persistent Antisocial Behavior: A Developmental Taxonomy.” Psychological Review 100 (4):674–701.

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Morgan, Stephen L. and Christopher Winship. 2015. Counterfactuals and Causal Inference. New York, NY: Cambridge University Press. Obama, Barack. 2016. “The President’s Role in Advancing Criminal Justice Reform.” Harvard Law Review 130(3):811–866. Odgers, Candice L., Avshalom Caspi, Daniel S. Nagin, Alex R. Piquero, Wendy S. Slutske, Barry J. Milne, Nigel Dickson, Richie Poulton, and Terrie E. Moffitt. 2008. “Is It Important to Prevent Early Exposure to Drugs and Alcohol Among Adolescents?” Psychological Science 19 (10):1037–1044. Pager, Devah. 2003. “The Mark of a Criminal Record.” American Journal of Sociology 108 (5):937–975. Pettit, Becky and Bruce Western. 2004. “Mass Imprisonment and the Life Course: Race and Class Inequality in U.S. Incarceration.” American Sociological Review 69 (2):151–169. Piquero, Alex R. 2008. Taking Stock of Developmental Trajectories of Criminal Activity Over the Life Course. P. 23–78 in Akiva Liberman (ed) The Long View of Crime: A Synthesis of Longitudinal Research. New York: Springer. Sampson, Robert J. and John H. Laub. 1995. Crime in the Making: Pathways and Turning Points Through Life. Cambridge, MA: Harvard University Press. Sherman, Lawrence W., Denise C. Gottfredson, Doris L. MacKenzie, John Eck, Peter Reuter, and Shawn D.Bushway. 1998. “What Works?” U.S. Department of Justice, Office of Justice Programs, National Institute of Justice. Research in Brief. Skinner, B.F. 1953. Science and Human Behavior. New York: McMillan. Steffensmeier, Darrell J., Emilie Andersen Allan, Miles D. Harer, and Cathy Streifel. 1989. “Age and the Distribution of Crime.” American Journal of Sociology 94 (4):803–831. Sutherland, Edwin H. and Donald R.Cressey. 1978. Criminology. 10th ed. Philadelphia: Lippincott. Uggen, Christopher and Jeff Manza. 2002. “Democratic Contraction? Political Consequences of Felon Disenfranchisement in the United States.” American Sociological Review 67(6):777–803. Vander Weele, Tyler J. and Weihua An. 2013. Social Networks and Causal Inference. P. 353–374 in Stephen L. Morgan (ed) Handbook of Causal Analysis for Social Research. New York: Springer. Wakefield, Sara and Christopher Wildeman. 2013. Children of the Prison Boom: Mass Incarceration and the Future of American Inequality. Oxford, UK: Oxford University Press. Warr, Mark. 1998. “Life-Course Transitions and Desistance from Crime.” Criminology 36 (2):183–216. Warr, Mark. 2002. Companions in Crime: The Social Aspects of Criminal Conduct. Cambridge, UK: Cambridge University Press. Western, Bruce. 2002. “The Impact of Incarceration on Wage Mobility and Inequality.” American Sociological Review 67 (4):526–546. Western, Bruce. 2006. Punishment and Inequality in America. New York: Russell Sage Foundation. https://squareonejustice.org/expert/bruce-western-3/. Western, Bruce. 2019. “The Challenge of Criminal Justice Reform.” The Square One Project. Wildeman, Christopher. 2009. “Parental Imprisonment, the Prison Boom, and the Concentration of Childhood Disadvantage.” Demography 46 (2):265–280.

8 IMMIGRATION POLICIES AND THE HEALTH OF THE OLDER FOREIGN-BORN IN THE UNITED STATES Zoya Gubernskaya

Immigration policies are critical for understanding the health and health disparities among the foreign-born, especially those at older ages. From the lifecourse perspective, immigration can be thought of as a transformative life-course transition or a turning point that shapes virtually every life-course process and outcome (Treas 2014; Treas and Gubernskaya 2016). By definition, immigration involves drastic changes in physical and social environments. In sociological, demographic, and public health literatures, immigration is increasingly considered one of the key social determinants of health (Castañeda et al. 2015). Immigration policies, which vary across time, critically influence immigrants’ lives and health trajectories. It is important to recognize that there is a bundle of immigration policies that shape the experiences of the foreign-born, rather than a singular, monolithic immigration policy. First, immigration admission policies determine who can migrate and under what circumstances. At least some of the health disparities among the older immigrants today can be traced to the specific circumstances of their migration to the United States. Second, immigrant naturalization policies set the rules and procedures for formal recognition as a full member of the U.S. society. Although the causal direction of the relationship is not always clear, there are persistent differences between citizens and non-citizens on various outcomes, including health (Gubernskaya, Bean, and Van Hook 2013; Torres and Young 2016; Van Hook, Brown, and Bean 2006). Because of how they entered the country, some foreign-born persons have no legal pathway to citizenship, even though they have lived in the United States as law-abiding and tax-paying members of communities for a long time. Other policies that either exclude immigrants from certain public assistance programs or promote immigrants’ inclusion set the context of reception for the foreign-born once they are in the

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United States (Perreira and Pedroza 2019). Finally, immigration enforcement policies shape the context of reception and the experiences of the foreign-born in the United States (Amuedo-Dorantes and Arenas-Arroyo 2018; Perreira and Pedroza 2019). Since 2000, the amount of effort and funding state and local agencies have committed to locate, arrest, detain, and deport non-U.S. citizens who violate U.S. immigration laws has increased dramatically (Meissner et al. 2013). Even though Immigration and Customs Enforcement (ICE) activities rarely target older immigrants, such activities can affect the health and well-being of older foreign-born persons through their impact on older immigrants’ families and communities. In this chapter, I provide examples of how policies related to immigrant admission, naturalization, context of reception, and enforcement impact the health status of the older foreign-born in the United States. I argue that considering the impact of these policies from the life-course perspective is crucial for understanding existing health disparities among older immigrants. I conclude with a discussion of future directions for research and a recommendation that policy makers pay special attention to the potential impact of immigration policies on population health.

Immigrant Admission Policies Immigrant admission policies have not significantly changed since the middle of the twentieth century. By determining who can come to and who remain in the United States, these policies dramatically transformed the demographic makeup of the U.S. population. The Immigration and Naturalization Act of 1965 (the Hart-Celler Act) replaced discriminatory national origin quotas with yearly numeric quotas and established a preference-based admission system. Preferences were given to close relatives of U.S. citizens, immediate relatives of lawful permanent residents (LPRs), and those with desirable labor-market skills and qualifications. Immediate relatives of U.S. citizens—spouses, minor children, and parents—are admitted outside of the numeric quotas, but their numbers count toward total yearly limits. As a result, the majority of immigrants to the United States have come through the family reunification path (Gubernskaya and Dreby 2017). Smaller numbers have been admitted through the employment path and as refugees or asylum seekers. The same legislation also limited immigration from the Western hemisphere, thereby blocking previously available migration opportunities for people born in Latin America and the Caribbean. Currently, there are about 7.2 million foreign-born persons age 65 and older in the United States, and the population of older immigrants is extremely diverse (U.S. Census Bureau 2018). The demographic composition of the older immigrant population in the United States reflects past and current immigrant admission policies. Indeed, the top countries of origin (Figure 8.1) tell a story about: the long history of migration from Mexico and Canada; early- and mid-twentieth

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Top countries of origin of foreign-born age 65 and over in the United States: 2016 IPUMS American Community Survey.

century waves of immigration from Europe (Germany, England, Italy, and Poland); refugee admissions from Vietnam and Cuba; and a mix of earlier and more recent immigration waves from the Philippines, China, India, South Korea, the Dominican Republic, Jamaica, Haiti, Colombia, and El Salvador. Remarkably, about one-third of older immigrants were born in countries that each contribute less than 1% to the total. As Figure 8.2 shows, the vast majority of older immigrants are long-term residents, with close to one-third residing in the United States for more than 50 years (author’s tabulations using the 2016 IPUMS American Community Survey data). However, a significant percentage have been in the United States for shorter durations. About 8% have lived in the United States for less than 10 years, and another 9% have lived in the United States for 10 to 20 years. Although more than half of older immigrants arrived when they were children or young adults and aged into mid- and later life in the United States, about 24% migrated after age 50. These figures reflect a sizable stream of older immigrant

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FIGURE 8.2

Foreign-born age 65 and over by duration of stay in the United States and by year of migration: 2016 IPUMS American Community Survey.

newcomers—parents of naturalized U.S. citizens, who can be admitted outside of established numeric quotas. About three-quarters of the foreign-born who are age 65 and over are naturalized United States citizens. While 23% speak English only, about 16% do not speak English at all, and another 20% speak some English, but not very well. About 45% of older immigrants are non-White, with close to one-third reporting Hispanic ethnicity. These demographic differences by race, ethnicity, citizenship, linguistic ability, duration of residence, and age at migration reflect the diversity of older immigrants’ experiences and are crucial for understanding existing health disparities among the older foreign-born. As a group, immigrants often have better health and lower mortality than U.S.born older adults (Cunningham, Ruben, and Narayan 2008). However, the average conceals substantial health disparities within the population. Many of these disparities can be traced to various circumstances related to migration, such as country of origin, legal status, and age at migration. It is important to note, however, that researchers are not always able to measure the factors that likely matter for understanding the context of migration. For example, legal status at the time of migration is rarely available in large-scale surveys. Specific countries of origin, especially combined with the period of migration, often serve as imperfect proxies for legal status upon arrival. However, in many publicly available data sets, including the National Health Interview Survey (NHIS), data on specific countries of origin, years of migration, and even the exact age in older age groups are suppressed to preserve respondents’ privacy. Even when this information is available, the sample sizes by country of origin often are too small to produce reliable estimates and the findings can be difficult to interpret. Despite these methodological difficulties, research that uses proxy variables, imputation techniques, or qualitative methods provides evidence of the impact of legal status and migration category on immigrants’ health (Torres and Young 2016). For example, traumatic past experiences of refugees have long-lasting consequences for physical and mental health (Marshall et al. 2005). Family-based migration has the benefits of family support and the security of LPR status, but it

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might also slow social and economic incorporation in the society at large through easy access to ethnic community services and employment in enclave economies (Gubernskaya and Dreby 2017). Undocumented migrants and those with “temporary protected status” are the most disadvantaged as they: lack access to vital services (e.g., public assistance programs, a driver’s license, and financial services); experience barriers to employment, housing, and education; face criminalization and discrimination; and live in fear of deportation. Both positive and negative experiences of migration can potentially accumulate over the life course and produce divergent health trajectories that result in substantial health disparities among the older foreign-born (Treas 2014; Treas and Gubernskaya 2015). Such health outcomes can place enormous demands on family caregivers who struggle to meet the long-term care needs of their older-adult family members (see Angel and Rote in this volume). Age at migration (i.e., the timing of migration in the life course) is an important factor for understanding older immigrants’ health. Older immigrants who arrived in the United States as children or young adults have had more time and opportunities to learn English and dominant cultural norms. They also acquire social and economic capital through participation in mainstream institutions, such as schools and workplaces. Conversely, those who migrated in midlife or old age have had less time and fewer opportunities to incorporate into U.S. society. Older immigrant newcomers face multiple barriers to employment due to the combination of several factors, such as advanced age, unfamiliarity with American society, foreign credentials, poor English language proficiency, and, sometimes, declining health. The usual correlates of socioeconomic well-being, such as level of education, might be poor indicators of financial stability for recently arrived older immigrants, who often lack savings and do not have sufficient work history in the United States to qualify for Social Security. Thus, older age at immigration and limited English are significant barriers to incorporation, even for well-educated older recent immigrants. Not surprisingly, older age at migration is consistently associated with: low income (O’Neil and Tienda 2014); higher rates of public assistance program participation; intermittent health insurance coverage (Reyes and Hardy 2014; Stewart and London 2015); and worse health in later life (Angel et al. 2010; Choi 2012). Those who arrived after age 50 report higher rates of functional difficulties (Garcia and Reyes 2017) and faster decline in self-reported health in later life (Gubernskaya 2014).

Naturalization Policy The relationship between naturalization and health is complex and challenging to study (Torres and Young 2016). Similar to legal status at arrival, researchers tend to rely on proxies and imputation methods to identify self-reported non-citizens who are and are not likely to be eligible to naturalize (Bachmeier, Van Hook, and Bean 2014). To be eligible to naturalize, most foreign-born persons need to

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reside in the United States as LPRs (also known as “green card” holders) for at least five years, although the wait time is shorter for spouses of U.S. citizens, veterans, and a few other categories of the foreign-born. Because many foreignborn individuals adjust their legal status to LPR while already in the United States, and the process can take years, length of residence is a poor indicator of eligibility to naturalize. Undocumented immigrants are not eligible to naturalize or even adjust their status to LPR. As of today, there are relatively few undocumented immigrants age 65 and over, as many of those immigrants who were undocumented during the 1980s were able to legalize after the passage of the Immigrant Reform and Control Act (IRCA) in 1986 (Donato and Armenta 2011). However, in the absence of a new legalization program similar to IRCA or DACA (Deferred Action for Childhood Arrivals, the number of undocumented adults age 65 and over is projected to increase (Passel and Cohn 2009; Treas and Gubernskaya 2015). Most, if not all, of this increase will be due to the aging of undocumented middle-aged adults who currently lack a path to legalization and citizenship. Despite the standard formal requirements, the perceived costs and benefits of naturalization might vary depending on age, family circumstances, and economic circumstances (Gubernskaya et al. 2013). Immigrants cite a variety of reasons for naturalizing, including: to obtain the ability to vote; to sponsor the immigration of their relatives; to hold certain governmental jobs; and to travel more easily with a U.S. passport. At the same time, there are numerous barriers to naturalization that are especially salient for older immigrants, including the civic and English exams, the non-refundable application fees ($640 plus an $85 biometric fee), and the paperwork. For many older newcomers, the paperwork is challenging because they do not speak English well and must rely on their adult children for assistance (Treas and Gubernskaya 2015). In sum, the naturalization process can be easy, difficult, or simply not available for different subgroups of the foreign-born population. Theoretically, naturalization is understood to be an indicator of immigrant incorporation into U.S. society (Van Hook et al. 2006). However, the relationship is likely to go both ways, as naturalization can promote further political, social, and economic incorporation and improve psychological well-being (Patler and Pirtle 2018). Whether the effect of naturalization on health is direct or primarily mediated through other pathways, such as socio-economic status, access to services, and psycho-social mechanisms, is an open question. Extant research points to persistent differences between citizens and non-citizens with respect to access to health care and health status (Gubernskaya et al. 2013; Torres and Young 2016). Previous research (Gubernskaya et al. 2013) and related analyses of more recent data that are presented in Figure 8.3 illustrate how the relationship between naturalization and health in later life is contingent on the age at migration. Among older immigrants who came to the United States as children or young adults, naturalization is associated with better health (i.e., a lower

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probability of functional limitations) after age 65. Although this association could partly be due to the self-selection of healthier individuals into citizenship, becoming a citizen is linked with improved socio-economic mobility, as well as intangible benefits that might translate into better health (Patler and Pirtle 2018). Among later-life migrants, naturalization is associated with having more functional limitations. This change in the direction of the association is indicative of negative health selection into citizenship among older immigrants who migrated in advanced age. Older newcomers often are reluctant to naturalize because the naturalization process—navigating the application paperwork, paying the application fee, and passing the civic and English language tests—is more difficult for them than for younger immigrants due to poor English language proficiency, limited income, and barriers to acculturation at advanced ages. They also are reluctant to apply for Medicaid as non-citizens out of fear of becoming labeled a “public charge” even if they are eligible based on their age, LPR status, and duration of residence. Dated back to the Immigration Act of 1882, the “public charge rule” might prevent foreign-born persons from becoming LPRs if they are likely to become dependent on the government for subsistence, as demonstrated by either the receipt of public assistance or institutionalization for longterm care at government expense. Although receiving non-cash benefits and services, like participation in Medicaid (until recently), did not count under the public charge rule in naturalization proceedings, many older immigrants worry that the law might change, bringing negative consequences if they participate in any kind of public assistance program. However, declining health and mounting medical bills push older immigrant newcomers to naturalize despite their worries and the difficulties of the process, conditional on their eligibility for Medicaid and Supplemental Security Income (SSI) based on their duration of residence, age, and income (Nam and Kim 2012). Figure 8.3 provides additional support for this interpretation of the association between naturalization and functional health by showing that the timing of naturalization in the life course is important. Those who migrated as children or young adults and naturalized within 10 years of arrival have a significantly lower probability of having functional limitations after age 65 relative to child and young-adult migrants who did not naturalize or naturalized after spending more than 10 years in the United States. A longer share of life as a U.S. citizen confers health benefits that are not entirely explained by socio-economic status. However, those who migrated at older ages and naturalized within 10 years have a significantly higher probability of having functional limitations after age 65 compared to later-life migrants who did not naturalize. Even though the naturalization process is daunting for many later-life immigrants, very few can afford expensive private health insurance plans or pay out of pocket for health care (Stewart and London 2015). Becoming a citizen and receiving Medicaid and SSI is a way to reduce the health care cost burden on individuals and families when older immigrants develop health problems and functional limitations/disabilities.

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Predicted probability of functional difficulties by age at migration, citizenship, and timing of naturalization: Foreign-born age 65+, 2016 IPUMS American Community Survey. Note: Author calculations based on a logistic regression model predicting probability of having any functional limitation (cognitive, ambulatory, independent living or selfcare) adjusted for age, age squared, sex, Hispanic ethnicity, race, marital status, education, ability to speak English, and health insurance coverage. FIGURE 8.3

Context of Reception The available research on legal status and health shows the importance of policies that either promote immigrant incorporation or place restrictions on access to public services for the foreign-born (e.g., Torres and Young 2016). Although these policies are not strictly speaking immigration policies, they create specific historical contexts of reception for immigrants and have long-lasting implications for their health and well-being (Perreira and Pedroza 2019). The life-course principle of lives in time and place is especially useful for understanding the impact of the context of reception. For example, LPRs who immigrated before the implementation of the 1996 Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) were eligible for Medicaid, SSI, and food stamps (now the Supplemental Nutrition Assistance Program [SNAP]) on arrival, while those who migrated after the implementation of welfare reform were not eligible for any federal public assistance programs during the first five years of their residence in the United States. These restrictions affected many older foreign-born persons, who were previously eligible for these programs based on their age and income. Research shows that the policy produced a so-called

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“chilling effect” as even those who were eligible for public assistance programs were reluctant to apply for them (Nam 2008; Van Hook 2003). The recent push to implement the “public charge rule,” as well as to expand the list of benefits from cash assistance to include participation in SSI, Medicaid, and housing assistance, is likely to have a similar chilling effect and might have negative consequences on older immigrants’ health (Batalova, Fix, and Greenberg 2019; see also Fenelon in this volume for a discussion of how housing policy influences health outcomes).

Immigration Enforcement Policies Emerging research demonstrates multiple negative health impacts of immigration enforcement policies and practices (Perreira and Pedroza 2019; Rhodes et al. 2015; Torres et al. 2019; Wang and Kaushal 2018). Immigration workplace raids, E-verify mandates, local immigration enforcement policies, detentions, and expedited deportations have increased dramatically during the 2000s and 2010s (Amuedo-Dorantes and Arenas-Arroyo 2018; Meissner et al. 2013). From the life-course perspective, past experiences of apprehension, detention, or deportation—or even a fear of such experiences (Rodriguez, Paredes, and Hagan 2017; Torres et al. 2019)—might have long-lasting impacts on mental and physical health and might contribute to health-relevant processes of accumulating inequality (see Dannefer and Han in this volume). Even though older immigrants are rarely targeted for deportation (although some do get deported and many fear deportation), and most research focuses on the immediate impact of immigration enforcement on undocumented adults and their children, the life-course principle of linked lives suggests that these policies can affect older immigrants’ health through their impact on families and communities. Fear of being subjected to enforcement policies (or having family, friends, and community members subjected to them) might be a source of chronic stress, which can lead to immune system dysregulation and manifest in depression, cognitive decline, cardiovascular disease, obesity, and gastrointestinal problems (Martínez, Ruelas, and Granger 2018). Beyond their immediate negative impact, continuing harsh immigration enforcement efforts might bear the additional hidden cost of worsening the health of older foreign-born Americans in the future.

Conclusion The life-course perspective provides useful lenses for understanding how past and present immigration policies are related to the health of older immigrants in the United States. The demographic composition of the older immigrant population and its diversity in terms of countries of origin, duration of residence, age at migration, and legal status can be traced to variation in immigrant admission policies over the course of many decades. Both admission and naturalization

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policies create unequal access to socio-economic resources and health care for the foreign-born in the United States. As both positive and negative consequences of such unequal access tend to accumulate over the life course, accounting for the current socio-economic circumstances of older immigrants is insufficient to fully explain the existence of substantial health disparities among older immigrants. The context of reception might promote or undermine immigrants’ health in the long run by allowing or denying access to public assistance programs at different points in the life course. The current nexus of naturalization and public assistance eligibility policies creates a “chilling effect” (underutilization of services by eligible younger and older immigrants who are non-citizens) and negative health selection into naturalization (higher rates of naturalization among immigrants who are in poor or declining health and likely eligible for Medicaid and SSI). Finally, harsh immigration enforcement policies negatively affect older immigrants’ health by inducing chronic stress and fear of deportation of family members or friends. Future academic and policy-evaluation research will benefit from more careful consideration of the possible health effects of current immigration policies that are not typically viewed as affecting health. For example, long waiting lines for family-sponsored immigrants from certain countries due to currently enforced, restrictive quotas will lead to a larger number of foreign-born migrating at older ages. As older age at migration is associated with barriers to socio-economic incorporation, higher rates of reliance on public assistance, and worse health in later life, this policy-driven shift in the age structure of new immigrants alone can lead to an increased number of socio-economically disadvantaged older foreign-born persons in the future. Potential fiscal benefits of the current five-year ban on participation in public assistance programs (especially Medicaid) for recent immigrants should be weighed against negative effects of delaying necessary medical care and forgoing preventative health care services. Forgoing medical care often leads to late diagnosis and more expensive treatment options once immigrants gain access to Medicare and Medicaid. Ultimately, the five-year waiting period on eligibility for public assistance programs for recent immigrants combined with the chilling effect of the public charge rule might not be the most cost-effective policy because of its negative effects on population health. Many undocumented middle-aged adults in the United States lack a pathway to legalization, which means that in 10–20 years there will be a large number of undocumented older adults not eligible for any public assistance program for the elderly, including SSI, Medicaid, Social Security, and Medicare. This means that an increasing number of older immigrants will have to rely on their own (often limited) resources, their families, and emergency rooms to access medical care. As a result, many olderadult immigrants might fall through the cracks of health care coverage (Stewart and London 2015). Shifting the responsibility for health care of older immigrants on their families will likely to lead to redistribution of the family resources to the detriment of young children and adults.

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Finally, there is mounting evidence that current immigration enforcement activities are detrimental to the physical and mental health of the foreign-born (Wang and Kaushal 2018). They need to be scaled back or reversed. In sum, careful examination of the health consequences of past and present immigration policies will ensure that future immigration policies promote older immigrants’ health.

Acknowledgement The author gratefully acknowledges the services and support of the Center for Demographic and Social Analysis at the University at Albany and the Center for Aging and Policy Studies, funded by the National Institutes of Health NIA Center Grant P30AG066583.

References Amuedo-Dorantes, Catalina and Esther Arenas-Arroyo. 2018. Understanding the Consequences of Heightened Interior Immigration Enforcement. P. 107–139 in The Human and Economic Implications of Twenty-First Century Immigration Policy. Angel, Ronald J., Jacqueline L. Angel, Carlos Díaz Venegas, and Claude Bonazzo. 2010. “Shorter Stay, Longer Life: Age at Migration and Mortality among the Older MexicanOrigin Population.” Journal of Aging and Health 22 (7):914–931. Bachmeier, James D., Jennifer Van Hook, and Frank D. Bean. 2014. “Can We Measure Immigrants’ Legal Status? Lessons from Two U.S. Surveys.” International Migration Review 48 (2):538–566. Batalova, Jeanne, Michael Fix, and Mark Greenberg. 2019. “Millions Will Feel Chilling Effects of U.S. Public-Charge Rule That Is Also Likely to Reshape Legal Immigration.” Migraton Policy Institute. https://www.migrationpolicy.org/news/chilling-ef fects-us-public-charge-rule-commentary. Castañeda, Heide, Seth M. Holmes, Daniel S. Madrigal, Maria-Elena DeTrinidad Young, Naomi Beyeler, and James Quesada. 2015. “Immigration as a Social Determinant of Health.” Annual Review of Public Health 36:375–392. Choi, Sunha H. 2012. “Testing Healthy Immigrant Effects Among Late Life Immigrants in the United States: Using Multiple Indicators.” Journal of Aging and Health 24 (3):475–506. Cunningham, Solveig Argeseanu, Julia D. Ruben, and K. M. Venkat Narayan. 2008. “Health of Foreign-Born People in the United States: A Review.” Health & Place 14 (4):623–635. Donato, Katharine M. and Amada Armenta. 2011. “What We Know About Unauthorized Migration.” Annual Review of Sociology 37:529–543. Garcia, Marc A. and Adriana M. Reyes. 2017. “Physical Functioning and Disability Trajectories by Age of Migration Among Mexican Elders in the United States.” The Journals of Gerontology: Series B 73 (7):1292–1302. Gubernskaya, Zoya. 2014. “Age at Migration and Self-Rated Health Trajectories After Age 50: Understanding the Older Immigrant Health Paradox.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 70 (2):279–290.

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Gubernskaya, Zoya, Frank D. Bean, and Jennifer Van Hook. 2013. (Un)Healthy Immigrant Citizens: Naturalization and Activity Limitations in Older Age. Journal of Health and Social Behavior 54 (4):427–443. Gubernskaya, Zoya and Joanna Dreby. 2017. “U.S. Immigration Policy and the Case for Family Unity.” Journal on Migration and Human Security 5 (2):417–430. Marshall, Grant N., Terry L. Schell, Marc N. Elliott, S. Megan Berthold, and Chi-Ah Chun. 2005. “Mental Health of Cambodian Refugees 2 Decades After Resettlement in the United States.” Journal of the American Medical Association 294 (5):571–579. Martínez, Airín. D., Lillian Ruelas, and Douglas A. Granger. 2018. “Household Fear of Deportation in Relation to Chronic Stressors and Salivary Proinflammatory Cytokines in Mexican-Origin Families Post-SB 1070.” SSM—Population Health 5:188–200. Meissner, D. M., D. M. Kerwin, M. Chishti, and C. Bergeron. 2013. Immigration Enforcement in the United States: The Rise of a Formidable Machinery. Washington, DC: Migration Policy Institute. Nam, Yunju. 2008. “Welfare Reform and Older Immigrants’ Health Insurance Coverage.” American Journal of Public Health 98 (11):2029–2034. Nam, Yunju and Wooksoo Kim. 2012. “Welfare Reform and Elderly Immigrants’ Naturalization: Access to Public Benefits as an Incentive for Naturalization in the United States.” International Migration Review 46 (3):656–679. O’Neil, Kevin and Marta Tienda. 2014. “Age at Immigration and the Incomes of Older Immigrants, 1994–2010.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 70 (2):291–302. Passel, Jeffrey S. and D’Vera Cohn. 2009. “A Portrait of Unauthorized Immigrants in the United States.” Washington, DC: Pew Hispanic Center, April. Patler, Caitlin and Whitney Laster Pirtle. 2018. “From Undocumented to Lawfully Present: Do Changes to Legal Status Impact Psychological Wellbeing Among Latino Immigrant Young Adults?” Social Science & Medicine 199:39–48. Perreira, Krista M. and Juan M. Pedroza. 2019. “Policies of Exclusion: Implications for the Health of Immigrants and Their Children.” Annual Review of Public Health 40 (1):147–166. Reyes, Adriana M. and Melissa Hardy. 2014. “Another Health Insurance Gap: Gaining and Losing Coverage Among Natives and Immigrants at Older Ages.” Social Science Research 43:145–156. Rhodes, Scott D., Lilli Mann, Florence M. Simán, Eunyoung Song, Jorge Alonzo, Mario Downs, Emma Lawlor, Omar Martinez, Christina J. Sun, Mary Claire O’Brien, Beth A. Reboussin, and Mark A. Hall. 2015. “The Impact of Local Immigration Enforcement Policies on the Health of Immigrant Hispanics/Latinos in the United States.” American Journal of Public Health 105 (2):329–337. Rodriguez, Nestor, Cristian L. Paredes, and Jacqueline Hagan. 2017. “Fear of Immigration Enforcement Among Older Latino Immigrants in the United States.” Journal of Aging and Health 29 (6): 986–1014. Stewart, Karyn A. and Andrew S. London. 2015. “Falling Through the Cracks: Lack of Health Insurance Among Elderly Foreign- and Native-born Blacks.” Journal of Immigrant and Minority Health 17 (5):1391–1400. Torres, Jacqueline M., Julianna Deardorff, Nina Holland, Kim G. Harley, Katherine Kogut, Kyna Long, and Brenda Eskenazi. 2019. “Deportation Worry, Cardiovascular Disease Risk Factor Trajectories, and Incident Hypertension: A Community-Based Cohort Study.” Journal of the American Heart Association 8 (23).

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Torres, Jacqueline M. and Maria-Elena D. Young. 2016. “A Life-Course Perspective on Legal Status Stratification and Health.” SSM—Population Health 2:141–148. Treas, Judith. 2014. “Incorporating Immigrants: Integrating Theoretical Frameworks of Adaptation.” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 70 (2):269–278. Treas, Judith and Zoya Gubernskaya. 2015. “Policy Contradictions and Immigrant Families.” Public Policy & Aging Report 25 (3):107–112. Treas, Judith and Zoya Gubernskaya. 2016. Immigration, Aging, and the Life Course. P. 143–161 in L. K. George and Kenneth F. Ferraro, eds., Handbook of Aging and the Social Sciences (8th ed). San Diego, CA: Academic Press. U.S. Census Bureau. 2018. American Community Survey 1-Year Estimates, Table S0501. http://data.census.gov. Van Hook, Jennifer. 2003. “Welfare Reform’s Chilling Effects on Noncitizens: Changes in Noncitizen Welfare Recipiency or Shifts in Citizenship Status?” Social Science Quarterly 84 (3):613–631. Van Hook, Jennifer, Susan K. Brown, and Frank D. Bean. 2006. “For Love or Money? Welfare Reform and Immigrant Naturalization.” Social Forces 85 (2):643–666. Wang, Julia Shu-Huah and Neeraj Kaushal. 2018. “Health and Mental Health Effects of Local Immigration Enforcement.” International Migration Review 53 (4):970–1001.

9 THE FUTURE OF LONG-TERM CARE IN THE LATINO POPULATION Where Will the Burden Fall? Jacqueline L. Angel and Sunshine M. Rote

Introduction One of the most notable recent demographic transformations in the United States is the profound change in the age structure of the population. By 2035, it is projected that there will be more older adults than children in the United States (Vespa 2018). As a larger portion of the population lives to advanced ages, the number of people living with Alzheimer’s disease and related dementias will steadily increase from five million currently to nearly 15 million in 2060 (Matthews et al. 2019). This growth in the number of people living with Alzheimer’s disease and related dementias will be accompanied by changes in other domains that impact the availability of care providers for older adults, including: below-replacement fertility; geographic mobility and residence far from families of origin; residential arrangements that result from neoliberal market reforms; international migration; divorce/family disruption, remarriage/re-partnering, and remarital/multi-partner fertility; dual-partner labor force participation; and uncertainties associated with the transmission, prevention, and treatment of COVID-19. Informal support systems are smaller, more dispersed, and generally unable to offer the time and resources necessary to provide all the care aging family members need, which results in high levels of unmet need (Herrera et al. 2013; Miranda-Castillo et al. 2010; Silverstein and Wang 2015; Zwingmann et al. 2019). The care gap is real and likely has been exacerbated during the COVID-19 pandemic. Over the coming decades, the growing number of older people with and without Alzheimer’s disease in conjunction with the declining number of family care providers, many of whom have numerous constraints on their capacity to provide care, and the emerging challenges associated

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with providing care to older adults who are at higher risk of COVID-19 complications will present the nation with a daunting social problem. At the same time that dependency ratios are accentuated, the aging population is becoming more ethnically diverse than ever before. Latinos, specifically, represent a growing share of the older adult population; they are expected to increase from around 8% to 28.6% of older adults by 2060 (Colby and Ortman 2015). Despite having fewer resources, on average, such as lower educational attainment and income, than White Americans, Latinos tend to outlive nonLatinos by several years. This is known as the “Latino Paradox” (Markides and Eschbach 2011). Although Latinos live longer, many of their additional years of life are characterized by poor health and functional limitations, as well as increasing levels of dependency on family members for care and support (Rote, Angel, and Markides 2015). Among people age 85 and older, Blacks are at the highest risk of Alzheimer’s disease and related dementias (43%), but the risk among Hispanics (40%) is greater than for non-Hispanic Whites (34%), Asian and Pacific Islanders (32%), and American Indian and Alaska Natives (35%) (Matthews et al. 2019). Taken together, these patterns suggest that Latino family caregivers will have longer and more time-intensive caregiving careers as they care for their older adult family members. To the extent that the demands of care for Alzheimer’s disease and related dementias generate stress proliferation processes (Aneshensel et al. 1995), Latinos will disproportionately face care-related challenges to their own health and well-being. With these foregoing patterns as context, we outline in this chapter the basic long-term care policy challenges facing the United States, with a specific focus on the Latino population. After briefly reviewing current policies that shape the long-term care landscape in the United States, we discuss the unique challenges facing Latino dementia caregivers. Our review highlights defamilization among Latinos in addition to several current and proposed policy responses. Throughout the chapter, we draw on two of the major tenets of the life-course perspective: cumulative (dis)advantage and linked lives (Settersten 2015). As the older adult population has grown increasingly diverse, social and economic inequality also has increased. Earlier disadvantage (e.g., low socioeconomic resources) leads to later disadvantage, which places ethnic minority older adults and their families at greater risk for poor health in mid- and late life (Angel and Angel 2018a). As older adults age and experience health limitations, they begin to rely on significant others for more care and support. The concept of linked lives focuses on the embeddedness of individuals within and across generations, which can have reciprocal effects on trajectories and life-course outcomes. Community-based care for someone with advanced dementia, for example, can be especially challenging and stressful (Aneshensel et al. 1995) and impact long-term well-being and financial security, especially for Latino caregivers (Rote, Angel, and Markides 2017). This strain might be offset by using formal, privately or publicly paid

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resources (e.g., home or respite care workers) or support from other family members, including “fictive kin” and neighbors (Dahlrup et al. 2015).

Long-Term Care Policies In the United States, as in most other nations, long-term care is provided by families or purchased privately on the market (Angel and Angel 1997). Neither the federal government nor states provide or pay for such care for individuals with personal resources. For individuals who have few resources or who deplete the resources they might have had paying for long-term care, Medicaid serves as the payor of last resort. For the most part, then, long-term care is a privately purchased commodity. Options in long-term care span home, community, and institutional settings and depend on whether the need is more intensive (skilled nursing) or less intensive (custodial), intermittent or continuous, or for posthospitalization needs. Given the lack of universal coverage, long-term care financing depends on a means test. Access to services varies from state to state. Although Medicare is the largest health insurance plan, long-term care services and supports are primarily paid for by Medicaid, which covers most expenses for the poor and for those who have exhausted their resources with coverage (Quesnel-Vallée, Farrah, and Jenkins 2011). In many respects, Medicaid is a stop-gap measure that does not provide a sufficient safety net to older adults and their families. Family members continue to shoulder the majority of the cost of long-term care in the United States, which poses financial challenges for caregivers. By 2040, the economic cost of dementia will more than double; most of these costs will be associated with long-term care (Shih et al. 2014). Increasing social and economic inequality, as well as increasing rates of dementia, create a great deal of uncertainty about the capacity of the oldage welfare state to meet the growing financial and health care needs of the very old (Angel 2018). These trends raise a fundamental question about who should carry the potential dependency burden: individuals, families, or the state? Medicaid is funded by federal and state governments, which means that a growing population of Medicaid recipients places heavy demands on state revenues. As a consequence, states are forced to attempt to control costs (Angel, Angel, and Cantu 2019). As the proportion of older individuals in the population grows, and as individuals live longer and deplete their resources, states are particularly concerned about the costs associated with dual-eligible individuals— Medicare beneficiaries who meet the criteria for Medicaid eligibility—who are the frailest and costliest Medicaid recipients (Medicaid and CHIP Payment and Access Commission 2018). With respect to cognitive impairment, Alzheimer’s disease or related dementia is much more common among older dual-eligible beneficiaries than those who are eligible for only Medicare or only Medicaid (Garfield et al. 2015). In response to increased need, Medicaid community-based waiver programs have grown at a remarkable rate in the last decade (Musumeci,

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Chidambaram, and Watts 2019). Although these programs help low-income families keep both young disabled and elderly family members at home, delaying premature institutionalization, access to waivers is limited. As a result, waiting (or interest) lists exist in most states. In recent years, an important policy goal has been the integration of health services and supports across the continuum of care. The response of many states has been to develop different innovative coverage models that promote coordinated, high-value care for dual-eligible and chronically ill Medicare beneficiaries. These efforts include dementia care. States are using a mix of approaches to support community-based care, including: the consolidation of Medicaid waivers to integrate Medicaid long-term care with acute care services within a managed care system (Angel et al. 2018); the Program of All-Inclusive Care of the Elderly (Gonzalez 2017), a Medicaid state option; and an 1115 demonstration project, a waiver program that allows state flexibility under existing federal Medicaid law to develop processes to integrate acute and chronic care financing for dual-eligible older adults (Angel, Angel, and Cantu 2019). The Affordable Care Act of 2010 created an optional state plan benefit for states to establish health homes to coordinate care for people with Medicaid who have chronic physical and mental conditions like dementia. At the local level, municipalities are struggling fiscally to support aging in place, given all of the services and supports that are needed for their older residents, while also trying to attract the younger generation necessary to ensure continued economic prosperity and social vitality (Angel 2018).

Latino Dementia Caregiving and Defamilization One factor that leads to extensive caregiving demands and strain is dementia. Dementia, along with diabetes and depression, is more prevalent in the Latino (all races) population than in the non-Latino White population (Mehta and Yeo 2017). Among Latinos alone, the projected economic impact of dementia is staggering: the cost of care for Latinos living with Alzheimer’s disease could reach a cumulative $2.35 trillion (in 2012 dollars) by 2060 (Wu, Vega, and Jin 2018). As we will show, a growing number of Latino communities, families, and systems of care will be confronted with both the impending crisis of a rapidly aging population with high risk for Alzheimer’s disease and the relative lack of access to the resources to help manage the illness. As important as the Latino family has been—and continues to be—in providing care to older family members, those tasks are increasingly being “defamilized.” Defamilization refers to a shift in responsibility from the family to the state (Esping-Andersen 2009). With industrialization and the emergence of the modern welfare state, the financial support of the elderly has been socialized through social security systems in middle- and high-income countries. Consequently, the family has been increasingly replaced by the state as the major source

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of financial support and medical care for elderly citizens. Yet, as previously mentioned, the state faces serious limitations in its ability to provide all the care that older Americans need. Dramatic declines in fertility and the retirement of approximately 10,000 Baby Boomers each day present the country with massive problems at all levels of government (Vespa 2018). By 2028, the federal government will spend half its budget (not counting interest on the national debt) on supporting older adults, mostly on Medicare and Social Security. Compare this figure to that from 2005, when the federal government spent only one-third of its budget on the same programs (Congressional Budget Office 2019). For Latino caregivers, early studies tended to focus on familism as both a cultural reference and an approach to caregiving. Familismo is the similar Spanish term that refers to familial ideals, which inform the structures, processes, and interactions that constitute Latino culture (Flores et al. 2019). Recent research on Latino dementia caregiving shows that the caregiving task is fraught with challenges, and familism is not now, if it ever was, reflective of all the support systems available to aging Latinos. Compared to non-Latino Whites, the Latino caregiver experience is multidimensional and varies by gender, immigration experience, and economic incorporation, as well as across generations (Angel and Angel 2018b). Data from the Survey of Caregiving reveals that while Latino caregivers have larger families, especially among the foreign-born population, they provide more support for care recipients with higher-care needs (e.g., dementia and disability assistance) and receive less help from others with caregiving tasks within and outside of the family compared to non-Latino White and Black caregivers (Rote et al. 2019). The majority of Latino care also tends to fall on female adult children, of which a large portion are Medicaid beneficiaries (Angel and Angel 2018b). In addition, for certain segments of the Latino population, elder care plays out within a global context as family members move across international borders over time. For example, forced deportations among undocumented workers or circular migration between the United States and Mexico of either the working-age adult caregivers or the aging family member could make it more difficult to meet older adults’ long-term care needs (see Gubernskaya in this volume for more information about immigration policies and the older foreign-born population). Caregiving under low levels of family support, low income, and low utilization of formal care is extremely demanding and could potentially undermine family members’ health. In the context of demographic and social safety net changes over the past several decades, the caregiver role might have become more complex and demanding than it has been in the past. However, even in the face of increasing complexity, Latino family caregivers continue to view the care of aging relatives as an honorable duty. Families with fewer adult children face higher time burdens per child in caring for elderly parents, particularly for elderly mothers. Demographic trends suggest that the decreasing number of adult children available to share the caregiving load could increase long-term care use

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in the years ahead. If, as is often the case, the Latino family lacks the financial resources to pay for in-home care services, few alternatives exist. As shown in Table 9.1, empirical evidence underscores these observations. Our analyses of data from the 2015 National Survey of Caregiving (NSOC) and 2016 Hispanic Established Populations for the Epidemiologic Study of the Elderly (HEPESE) provide a social and demographic profile of family caregivers by race and Mexican-origin ethnicity. First, a higher percentage of MexicanAmerican caregivers than non-Latino caregivers are female, have low education, and are Medicaid participants. Similar to Black caregivers, they are younger than non-Latino Whites. Second, there are statistically significant differences between Mexican-American caregivers and non-Latino caregivers in terms of intensity of care, including assistance with basic activities of daily living in the past month and (especially) dementia care. Third, almost two-thirds of Mexican-American and non-Latino White caregivers live in the same household as the care recipient. TABLE 9.1 Caregiving experiences by race/ethnicity (%)

Non-Latino Whitea N Caregiving intensity Dementia** Lives together* Daily personal care*** Caregiver support Informal support*** Formal support *** Training* Caregiver–care recipient relationship*** Adult child Spouse Other family Non-family Caregiver background Age (means, standard deviation)*** Female*** Education:*** Less than high school High school More than high school Insurance Any Medicaid*** a

MexicanAmericanb

Blacka

449 25 64 16

287 35 60 38

218 23 53 21

57 18 5

45 14 8

70 17 13

44 44 7 6

62 8 16 14

54 18 21 8

66.33(13.07) 59 9 29 62

58.76(12.53) 82 40 32 28

58.03(14.07) 67 19 22 59

11

22

17

National Study of Caregiving (NSOC), 2015. Hispanic established populations for the Epidemiological Study of the Elderly (HEPESE) Caregiver Supplement, 2016. ***p < .001, **p < .01, * p< .05. b

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Lastly, a lower share of Mexican-American caregivers than non-Latino caregivers reports the use of informal support (calling on family or friends to help with caregiving) and formal support (paid in-home health care services). Compared to non-Latino Whites (57%) and Mexican-Americans (45%), Black caregivers tend to rely heavily on a convoy of family and friends for support (70%). Given that Latino families face daunting challenges to provide care, other institutional arrangements must be considered. This includes semi-formal organizations comprising community-based resources that Latino and other family caregivers can call upon to assist in dealing with relatives who are seriously cognitively impaired. These resources range from informal, unpaid care from family members and others to formal governmental agencies that provide eldercare services. In between are non-governmental organizations, such as faith-based organizations, synagogues, and congregations. These are becoming an increasingly important source of assistance to families caring for elders with dementia and to older individuals who have no family support.

Solutions: Public, Private, or Both? Defamilization will inevitably have the most serious impact on the most vulnerable Latino families and caregivers of individuals with dementia, given gaps and even reductions in funding in Medicaid and Medicare. Our country’s current response to the public health threat of Alzheimer’s disease is positive. The Centers for Disease Control and Alzheimer’s Association have developed a series of policy maps that chart the public health response to dementia. The innovative Healthy Brain Initiative (HBI) addresses gaps in dementia knowledge and practice by establishing state and local public health partnerships. Significant advances have been made in the science of reducing inequalities in risk and early detection of memory loss and Alzheimer’s disease. The result of this public health discovery led to the use of a life-course conceptual model to identify the timing of exposure to early-life risk factors for understanding mechanisms influencing late-life inequalities in cognitive functioning and cognitive reserve (those who stave off symptoms of neurological degenerative disease). Recent findings from the Wisconsin Longitudinal Study add to the growing body of evidence that demonstrates the consequences of socioeconomic differences in childhood memory loss for cognitive functioning in later life (Greenfield and Moorman 2019). However, existing public policy interventions and related prevention programs designed to promote optimal brain health and keep individuals healthy often do not reach those who need preventive services the most. In addressing this caregiver dilemma, a combination of both public and private solutions must be considered for a dementia-prepared future (Olivari, French, and McGuire 2020). In various ways, Congress has acknowledged the critical role that families play in the nation’s system of long-term care services and supports. It has done so by authorizing the National Family Caregiver Support Program (NFCSP) as part of

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the Older Americans Act (OAA) in 1965 and the Alzheimer’s Disease Supportive Services Program (ADSSP) in 1992 (Administration on Aging 2012). A recent evaluation of the NFCSP underscored both the value of respite services in reducing caregiver burden and the importance of education and training services in fostering caregiver confidence over time (Administration for Community Living 2018). The integration of age into program development for dementia caregivers was recognized by Congress in the proposed Younger-Onset Alzheimer’s Disease Act as part of the reauthorization of the Older Americans Act. This new piece of legislation (“Supporting Older Americans Act”), signed into law by President Donald Trump on March 25, 2020, addresses the unique challenges— family, work, and finances—of individuals living with younger-onset Alzheimer’s disease (U.S. Congress 2020). Federal recognition of the effectiveness of both programs led to bipartisan support of funding for caregiver support, research, and the enhancement of outreach efforts, as well as distributing culturally sensitive materials to individuals and families facing Alzheimer’s disease. For example, the Alzheimer’s Disease Research Semipostal Stamp Act of 2019 reauthorizes the U.S. Postal Service (USPS) to advance causes it considers in the public interest. The USPS will sell an Alzheimer’s research stamp for an additional six years (U.S. Congress 2019a, U.S. Congress 2019b). The sale of the stamp benefits Alzheimer’s research at the National Institutes of Health and helps to raise public awareness about the disease. The proposed Alzheimer’s Caregiver Support Act is another example of targeted legislation (U.S. Congress 2019c). It would make grants available to public and nonprofit-private health care providers to expand training and support services for families and caregivers of patients with Alzheimer’s disease or a related dementia. This bill would promote dementia-capable states and local municipalities (i.e., making it possible to support individuals with dementia and those who care for them, especially in medically underserved communities) (Tilly, Wiener, and Gould 2014). The proposed legislation requires coordination with the Office on Women’s Health and the Director of the Office of Minority Health to provide services in the most appropriate language and ensure that minority families and caregivers of patients with Alzheimer’s disease benefit from these services. A further strength of this proposal is that these important provisions are consistent with the national plan to address Alzheimer’s disease through the 2018 Recognize, Assist, Include, Support, and Engage (RAISE) Act. The RAISE Family Caregivers Act was signed into law in January 2018 (U.S. Congress 2018). The new law authorizes the U.S. Department of Health and Human Services to develop and maintain a strategy to recognize and support the more than 43 million unpaid caregivers in the United States (Administration for Community Living 2019). According to the Administration on Community Living (2019), non-governmental community-based organizations (NGOs) can potentially play an assistive

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role by providing training, information, and support to family and older relative caregivers. Additionally, access to state-sponsored services, like state Area Agencies on Aging (AAA) and Disability Resource Centers, is critical for older adults and their families. These local agencies offer an important support system for adults aged 60 and over by providing information and assistance, help with managing services, and access to publicly funded programs such as Medicaid. State AAAs might also receive grant funding, based on their share of the population age 70 and over, to administer the NFCSP program, which links services to caregivers aged 18 years and older, regardless of the age of the care recipient. Several provisions in the 2010 Affordable Care Act (ACA) create programs to improve resources for providers. The law requires expanded education and training programs for health professionals to reduce health care workforce shortages in underserved areas, such as those serving frail and dependent Latino elderly. Currently, a large fraction of older Latinos reside in designated shortage areas, which are underserved by physicians and hospitals (Bastida, Brown, and Pagan 2008). Clearly, rural residents and residents in seriously underserved areas, such as the United States–Mexico border region, have very different levels of access to support than exist in other locales with multiple agencies and organizations. In rural and peri-urban areas, such as the Colonias of South Texas, the availability of services is limited. The availability of bilingual/bicultural health professionals is critical to the provision of culturally competent, high-quality health and long-term care. To close this service gap, the ACA supports the Patient-Centered Medical Home Program, which includes community health teams to improve access to primary care provided by community-based social services agencies (elder NGOs) serving older individuals (Abrams et al. 2011). NGOs, however, clearly cannot replace the state in providing financial and medical support to large numbers of infirm elderly individuals (Angel et al. 2016). They might, however, supplement the efforts of formal agencies and assist caregivers in dealing with the highly demanding task of caring for seriously ill and incapacitated elders in the community, which often involves managing complex health care and assistive technology activities at home. The potential role of care coordinators in organizing and integrating the combinations of all the formal and informal assistance available is a critical link in increasing collaboration and enhancing overall quality across both domains (Maestre and Fernandez 2019). Care coordinators and geriatric social workers have been shown to play an important role in managing older adults and patients in other contexts, such as HIV/AIDS (London, Leblanc, and Aneshensel 1998). Of course, if health care financing reform simply funds medical care without providing an infrastructure in which to deliver it in rural and hard-to-reach areas, true reform will not occur. As previously mentioned, Latino elderly often cite waiting lists and costs as barriers to using such caregiver services. Finally, to deal with financial hardships, the Credit for Caring Act of 2019 gives eligible caregivers a tax credit for qualified long-term care expenses (e.g.,

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adult day care), not to exceed $3,000. Similarly, at the state level, the Commonwealth of Massachusetts has currently referred a bill—the Family Caregiver Tax Credit Act—to the Joint Committee on Revenue by both the Senate and House, which would provide a tax credit for certain expenses incurred by a family caregiver for the care and support of a qualifying family member. The Family Caregiver Tax Credit Act of 2019 allows for a maximum tax credit of $1,500 for certain caregiving-related, out-of-pocket expenses, such as home repairs that enable the care recipient to remain mobile, safe, and independent (Commonwealth of Massachusetts 2019). These proposals, by and large, are likely to address many caregiver financial hardships. However, a new study found that Latino caregivers spend an average of $9,022 per year (44% of their income) caring for a cognitively or physically disabled loved one, compared to the $6,954 on average among the general caregiver population (Rainville, Skufca, and Mehegan 2016). The relatively high expenditures for Hispanics/Latinos reflect a longer length of time (five years or more) caring for a recipient. Compared to other racial/ethnic groups, the majority of Latinos (61%) are the most financially strained caregivers because they are almost twice as likely to care for recipients with dementia and also tend to carry out their responsibilities alone, often resulting in their spending more than their total retirement savings. Clearly, the family provides vital support, but longer life spans and protracted periods of disability will inevitably give rise to the need for both formal (use of paid health and social care services) and informal caregiving assistance (reliance on family and neighbors for emotional and instrumental caregiver support). For Latino elderly individuals with serious physical or cognitive impairments (which often co-occur), the only alternative in the future could be institutionalization. As the Latino population ages, a better understanding of the community support system that they need and can draw upon merits attention. It is becoming increasingly clear that the unmet needs of older Latinos—especially those with serious dementia and their caregivers—are best addressed with a combination of all the formal and informal assistance available. While volunteers and informal organizations cannot serve as a substitute for the state in providing financial and instrumental care to frail, older individuals, they can play a very important ancillary role as advocates and providers of routine services, including companionship and help with activities of daily living, to allow family members the respite that they require. It is essential to investigate how families can mobilize support and reduce the barriers they face in acquiring support for the care of an aging parent, especially a parent with dementia and related conditions. The information that is necessary for the development of optimal policy concerning the community support of elderly Latinos includes an asset survey of the services available in Latino communities. In addition to a household asset survey, there is a need for qualitative research that examines recipients’ experiences of aging services, as well as services

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and supports that would be useful but are not available or are difficult to access. Specialized focus group data from outreach efforts by formal and informal organizations would help researchers better understand the pathways into caregiving services used by disadvantaged older adults in general, and Latino older adults in particular. Robust research into the quality and effectiveness of these services in relieving the burden that the caregivers of the seriously impaired elderly experience is especially necessary.

Conclusion As with other ethnic groups, the family remains the principal source of instrumental and emotional support for older Latinos. We argue that policy makers should avoid formulating policies that weaken the resolve of each generation to care for its elders. Our analysis also casts doubt upon the ability of Latino families to care for aging relatives in the absence of sufficient structural supports. Furthermore, the assumption that “la familia” will provide care for aging relatives might be overstated. Bringing the long-held Latino traditions of elder care into the middle of the twenty-first century will require the help and participation of families, as well as public and private organizations. While it is still too soon to predict the fate of Medicaid, it is clear that benefit cuts and increases in out-ofpocket spending by nursing home residents and their families are likely to affect access to and the quality of care for all low-income seniors, not just those on Medicaid. There are no clear solutions that both enhance the quality of life for low-income, frail elders and reduce state Medicaid expenditures, particularly in light of recent challenges associated with providing long-term care to older adults during the COVID-19 pandemic. What is evident and essential, though, is that discussions of policy and program reforms must consider equity and the pact between generations.

Acknowledgement Support for this research comes from the National Institute on Aging (NIA), A Binational Study of the Dementia Trajectory and Living Arrangements in the U.S. and Mexico (#R03AG063183).

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Rote, Sunshine, Jacqueline L Angel, and Kyriakos Markides. 2017. “Neighborhood Context, Dementia Severity, and Mexican American Caregiver Wellbeing.” Journal of Aging and Health (29):1030–1055. Rote, Sunshine M., Jacqueline L. Angel, Heehyul Moon, and Kyriakos Markides. 2019. “Caregiving Across Diverse Populations: New Evidence from the National Study of Caregiving and Hispanic EPESE.” Innovation in Aging 3 (2):igz033. Settersten, Richard A., Jr. 2015. “Relationships in Time and the Life Course: The Significance of Linked Lives.” Research in Human Development 12(3–4):217–223. Shih, Regina A., Thomas W. Concannon, Jodi L. Liu, and Esther M. Friedman. 2014. What to Do About Dementia? Policy Options for Crucial Long-Term Care. Santa Monica, CA: RAND Corporation. https://www.rand.org/pubs/research_briefs/RB9780.html. Silverstein, Merril and Rebecca Wang. 2015. “Does Familism Inhibit Demand for LongTerm Care? Public Policy Implications of Growing Ethnic Diversity in the United States.” Public Policy & Aging Report 25 (3):83–87. Tilly, Jane, Joshua M. Wiener, and Elizabeth Gould. 2014. Dementia-Capable States and Communities: The Basics. https://Acl.Gov/Sites/Default/Files/Triage/Bh-Brief-Dem entia-Capable-Basics.Pdf. U.S. Congress. 2018. “Public Law 115–119—Jan. 22, 2018.” https://Acl.Gov/Sites/Defa ult/Files/About-Acl/2018-10/Plaw-115publ119%20-%20raise.Pdf. U.S. Congress. 2019a. “Alzheimer’s Semipostal Stamp.” https://Www.Congress.Gov/ Bill/116th-Congress/House-Bill/3113/Text. U.S. Congress. 2019b. “Alzheimer’s Semipostal Stamp Act.” https://Www.Congress. Gov/Bill/116th-Congress/Senate-Bill/1728/Text?R=57&S=1. U.S. Congress. 2019c. “S.740 - Alzheimer’s Caregiver Support Act.” https://Www.Con gress.Gov/Bill/116th-Congress/Senate-Bill/740/Text. U.S. Congress. 2020. “S.901–116th Congress: Younger Onset Alzheimer’s Disease Act.” https://Www.Govtrack.Us/Congress/Bills/116/S901. Vespa, Johnathan. 2018. “The U.S. Joins Other Countries with Large Aging Populations.” https://Www.Census.Gov/Library/Stories/2018/03/Graying-America.Html. Wu, Shinyi, William A. Vega, and Haomiao Jin. 2018. “Latinos & Alzheimer’s Disease: Projection of the Costs for U.S. Latinos Living with Alzheimer’s Disease through 2060.” https://Www.Usagainstalzheimers.Org/Sites/Default/Files/2018-02/Latinos-a nd-Ad_Usc_Usa2-Impact-Report.Pdf. Zwingmann, Ina, Bernhard Michalowsky, Alexander Esser, Anika Kaczynski, Jessica Monsees, Armin Keller, Johannes Hertel, Diana Wucherer, Jochen René Thyrian, Tilly Eichler, Ingo Kilimann, Stefan Teipel, Adina Dreier Wolfgramm, and Wolfgang Hoffmann. 2019. “Identifying Unmet Needs of Family Dementia Caregivers: Results of the Baseline Assessment of a Cluster-Randomized Controlled Intervention Trial.” Journal of Alzheimer’s Disease 67 (2):527–539.

10 HOW SOCIAL POLICIES AFFECT GRANDPARENT CARE WORK Madonna Harrington Meyer and Amra Kandic

Several years ago, when Harrington Meyer presented her work on the intensification of grandparenting in the United States at an International Sociological Association meeting, a Swedish scholar asked: “What is wrong with American grandmothers? Why don’t they just say ‘no’?” Harrington Meyer’s response was (and our response still is): There is nothing wrong with American grandparents, but there is a lot wrong with the U.S. welfare state. U.S. grandparents provide a great deal of care, money, and other resources to their grandchildren. The question is: Why? Here, we review the extent of grandparent care in the United States and note how such care varies by gender, race, and class. Then, we discuss two sets of reasons that inform our understanding of why U.S. grandparents provide so much care. First, the U.S. does not provide federal policies for paid vacation, paid sick leave, paid parental leave, or affordable, high-quality child care. Second, with the notable exceptions of Social Security and Medicare, the United States relies almost entirely on poverty-based social welfare programs, including Supplemental Security Income (SSI) and Medicaid. These programs tend to emphasize meager benefits and gatekeeping. To illuminate how these weak social supports shape grandparent care work, we weave in excerpts from in-depth interviews discussed in greater detail in Harrington Meyer (2014) and Harrington Meyer and Abdul-Malak (2020). U.S. grandparents provide a great deal of care for their grandchildren. About 51% of adults ages 50–64, and 80% of those 65 and older, have grandchildren (Livingston and Parker 2010). Approximately 50% of grandparents in the United States provide some type of financial support to their grandchildren, and 31% provide help with housework, errands, and home repairs (Livingston and Parker

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2010). Using data from the 1998–2008 Health and Retirement Study, Lou, LaPierre, Hughes, and Waite (2012) found that over 60% of grandparents provided some child care over a 10-year period, with 70% providing child care for two years or more. Some grandparents provide occasional babysitting, while others provide regular daycare, care within multigenerational households, and custodial care as guardians (Hayslip, Fruhauf, and Dolbin-MacNab 2019; Lou et al. 2012; Livingston and Parker 2010). Adult children often regard grandparents as trustworthy, reliable, and inexpensive sources of child care (Silverstein and Lee 2016). Grandparents often are more flexible than organized daycare in that they are able and willing to rearrange their schedules to care for grandchildren before school, after school, evenings, weekends, on national holidays, on snow days, and when children are sick (Harrington Meyer 2014). Grandparenting varies by gender, race, and socioeconomic standing. Grandmothers are more likely to provide care than grandfathers (Silverstein and Lee 2016; Lou et al. 2012; Livingston and Parker 2010; Baker, Silverstein, and Putney 2008). Of grandparents who are primarily responsible for grandchild care, 62% are women (Livingston and Parker 2010). Black and Hispanic grandparents are more likely than White grandparents to be primary caregivers (Livingston and Parker 2010). Hispanic grandparents are more likely to live in multigenerational households and to stay in those households longer than Whites and Blacks (Lou et al. 2012) (see Angel and Rote in this volume for a discussion of family care for Latino older adults with Alzheimer’s disease and related dementias). In part due to higher rates of poverty, joblessness, drug use, and incarceration, Blacks are more likely to have custodial care of their grandchildren (Hayslip et al. 2019; Silverstein and Lee 2016; Lou et al. 2012). Custodial grandparents are more likely to have lower incomes and to live in poorer housing in poorer neighborhoods (Livingston and Parker 2010; Baker et al. 2008). Regardless of the type and intensity of care provided by grandparents, many grandparents express joy in visiting and caring for their grandchildren (Harrington Meyer 2014; Livingston and Parker 2010). That said, caring for their grandchildren is not for everyone (Harrington Meyer 2014; Livingston and Parker 2010). In any given year, about half of grandparents in their 60s and early 70s provide some type of needed grandchild care, while the remainder do not (Livingston and Parker 2010). Demand for grandparent assistance has been fueled in part by an increase in single parenting, an increase in women’s labor force participation, and the Great Recession. Single-parent households have increased dramatically; currently, 40% of all babies are born to an unmarried mother (Martin et al. 2019; Livingston 2018; Baker et al. 2008). American women’s participation in the labor force has grown, with an increase from 38% in 1963 to 57% in 2015 (Toossi and Morisi 2017; Heymann 2013). In 2017, 67% of mothers in married-couple families and 73% of unmarried mothers worked outside the home (Glynn 2019). During and after the Great Recession, many young families who were plagued by job and housing insecurities turned to grandparents for financial assistance and grandchild care

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(Silverstein and Lee 2016; Harrington Meyer 2014; Livingston and Parker 2010; Baker et al. 2008). While it is clear that these socio-demographic and economic trends shape the demand for grandparent care work in profound and dynamic ways, it also is clear that they would have lesser effects on grandparent care work if the United States provided federal policies and universal social welfare programs that are more akin to those found in the European Union.

Lack of Federal Policies for Working Families Grandparents in the United States provide more care than grandparents in many other countries, more care than U.S. grandparents used to provide in previous decades, and, in many cases, more care than they expect to provide (Harrington Meyer 2014; Igel and Szydlik 2011). This intensification of grandparent care is linked to key features of the U.S. welfare state. The United States does not provide federal policies that help families juggle work and child care (Igel and Szydlik 2011; Baker et al. 2008). Igel and Szydlik (2011) found that in countries where there are many policies that help young families, grandparents provide less intensive child care, whereas grandparents provide more child care in countries with few or no such policies. The intensification of grandparenting in the United States is linked to the lack of U.S. government policies like paid vacation, paid sick time, paid parental leave, health insurance, and affordable, high-quality daycare (Harrington Meyer 2014; Igel and Szydlik 2011). Some U.S. employees have access to these benefits through their jobs, but the U.S. government does not guarantee such access. Employers are more likely to offer these benefits to higher-paid, full-time employees (Glynn 2012). Worldwide, 127 countries guarantee paid vacation to workers, but the United States is not one of them (Maye 2019; Glynn 2012). Instead, 77% of U.S. workers receive paid vacation benefits through their employers, and access varies markedly (Maye 2019). Currently, 90% of full-time workers, compared to 40% of part-time workers, have paid vacation days (Maye 2019). Roughly 52% of workers in the bottom wage quartile, compared to 91% in the top wage quartile, have paid vacation (Maye 2019). Race and gender differences are noteworthy. Blacks, Hispanics, and women, who are more likely to be in part-time or lower-wage work, tend to be less likely to have paid vacation time (Glynn 2012). The absence of paid vacation is especially difficult for lower-paid workers who cannot afford to go without paychecks. Parents who have paid vacation may use their time off to care for their children when other options are not available, such as during national holidays, snow days, and when children become sick (Glynn 2012; Harrington Meyer 2014). Parents without paid vacation might have little choice but to call on grandparents for assistance. For example, 57-year-old Deanne has held her job as an elected official for many years and has accumulated a substantial amount of vacation time, but her recently divorced daughter holds a

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new job and has not yet earned any vacation time. Moreover, because layoffs are expected, her daughter is unable to miss work for fear of losing her job. Hence, Deanne changes her work schedule almost daily to care for her grandchildren. She comes in late, leaves early, takes days off, minds the grandchildren while at her office, and takes work home. Deanne explains: “She started a new job last spring and doesn’t have much time built up for family time, so Grandma is here” (Harrington Meyer 2014:5). The United States is the only developed country that does not guarantee workers paid sick leave (Glynn 2012). Although most public-sector employees receive paid sick leave, in 2018, 29% of private sector workers did not (Boesch 2018). Only 26% of workers in the bottom income quintile have paid sick leave, compared to 75% of workers in the top income quintile (Glynn 2012). Part-time workers are 50% less likely than full-time workers to have access to paid sick leave (Boesch 2018). Hispanic workers are 27% less likely than non-Hispanic White workers to have paid sick leave, and only 49% of Hispanic women have access to paid sick leave (Boesch 2018). Thus, the lack of federal guarantees for paid sick leave disproportionately affects lower-wage, part-time, Hispanic, and women workers and makes it more likely that families will turn to grandparents for care. When formal child care is not available due to inclement weather, national holidays, or child illness, parents who have sick leave may use it to care for their children, while parents without it frequently turn to grandparents for help (Glynn 2012; Harrington Meyer 2014). For example, at 50, Natalie has better benefits and more scheduling flexibility than her adult children. She works full-time but has arranged her schedule so that she has one full day off a week. She spends that day, all of her evenings, most of her weekends, and most of her paid vacation and sick leave time caring for the grandchildren. Natalie explains how she helps her daughter with child care: “I rearrange my day, come in late, or leave early. I will use my day off every other week on the days she needs me in a pinch” (Harrington Meyer 2014:104). The lack of paid parental leave negatively affects most families in the United States. While 180 countries worldwide offer paid maternity leave, and 81 offer paid paternity leave, the United States offers neither (Heymann 2013). According to the Bureau of Labor Statistics (2018), only 17% of workers have access to paid family leave, which includes maternity and paternity leave. Workers are more likely to be offered paid family leave if they are full-time, higher-paid, and in larger firms (Glynn 2012). The United States guarantees unpaid leave through the Family and Medical Leave Act, and the Bureau of Labor Statistics (2018) reports that 89% of workers have access to unpaid family leave. However, to be able to take unpaid leave, employees must have worked with the company for 12 months, must have worked at least 1,250 hours during the preceding 12 months, and must work for an employer with at least 50 employees within a 75-mile radius (Bureau of Labor Statistics 2018; Heymann 2013). Access to unpaid family

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leave increases with wages; 74% of workers earning over $100,000 qualify, compared to 39% of those earning $20,000 (Heymann 2013). Even when workers qualify for the program, many cannot afford to take advantage of it because their families cannot afford to go without their pay (Glynn 2012). Those who have no paid parental leave might turn more readily to grandparents to help them balance work and family. For example, Marsha’s daughter and son-in-law were permitted very little time off with the birth of their twin sons. When her grandsons were diagnosed with Down’s syndrome and autism, Marsha, age 64, and her husband moved to a new city and changed careers to help take care of them. Like many grandparents, Marsha gave up a stable job with steady pay, paid vacation and sick leave, a private pension, and health insurance for a job in real estate that allowed her more flexibility to care for her grandsons. Marsha and her husband rearrange their work schedules constantly. Because they used most of their retirement savings to launch their new, more flexible careers, Marsha and her husband are delaying retirement. Marsha explained: “I plan to work for a long time…we both went back to school and started second careers. We lived off our savings for years, and so we do not have much put aside for retirement” (Harrington Meyer 2014:138). The lack of affordable, high-quality daycare options puts tremendous stress on young families. Among parents with a child under the age of 5, 83% reported that finding quality, affordable child care was a serious problem in their area (Malik et al. 2018). Over 50% of Americans live in child care deserts (Malik et al. 2018). Hispanic and Native American families are especially in need of affordable child care options, with 57% and 60%, respectively, living in child care deserts (Malik et al. 2018). Daycare options vary markedly between rural and urban areas. Fully 59% of rural areas are daycare deserts, compared to 56% of urban areas and 44% of suburban areas (Malik et al. 2018). The United States does offer child care support to middle- and lower-class families through tax subsidies, tax credits, and subsidized child care (Malik et al. 2018). Of the low-income families eligible for subsidized child care, only 15% actually receive it due to long waiting lists and insufficient funding (Malik et al. 2018). Affordable daycare options are essential. Child care is too expensive for many families, with costs sometimes exceeding rent or in-state college tuition (Malik et al. 2018). Given the dearth of affordable, high-quality child care, working parents have few options, and often rely on unstable patchworks of child care anchored in care work by family members (Scott, London, and Hurst 2005). To remain employed while raising children, they might be more likely to rely on grandparents for child care. For example, Patty, age 63, retired from her earlier occupation and now works as a house cleaner part-time so that she can watch her grandchildren. She only takes clients who will let her cancel or switch days if she needs to rearrange her schedule. She cares for her four grandchildren every day of the week except Tuesdays:

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I get there at seven. I help get them ready for school and work, make sure they have eaten, put the baby down for a nap. I get my granddaughter ready for school, walk or drive her to school, put laundry away, collect laundry, cook, put toys away, pick her up from pre-K, then feed everyone lunch. (Harrington Meyer 2014:70). Patty is so integrated into the family child care schedule that she continues to care for the children even when she is not feeling well. She explained: “Last week, I was sick and went anyway, and I slept while they did” (Harrington Meyer 2014:71). In the evenings, she cares for her husband, who is 80 and has Alzheimer’s disease and cancer, and for her mother, whose health is failing quickly.

Poverty-Based Social Welfare Programs Grandparents in the United States also tend to be called upon for help more often than in other countries because U.S. social welfare programs are primarily poverty-based rather than universal (Igel and Szydlik 2011). As such, benefits tend to be small, and the emphasis tends to be on gatekeeping. U.S. povertybased social welfare programs include SSI and Medicaid (see Fenelon in this volume for a discussion of housing policies for low-income families). Taken together, these programs tend to provide meager, temporary benefits with a great deal of administrative burden (Herd and Moynihan 2019). When applying for SSI, applicants must overcome administrative burdens, including attending interviews, proving immigration status, or providing financial records, such as pay stubs, lease agreements, or diagnostic records (Herd and Moynihan 2019; Center for Budget and Policy Priorities 2018). The combination of strict asset limits, meager benefits, and administrative burdens means SSI brings few people above the poverty line and leaves family members turning to each other for income stability as they raise the next generation. When families struggle, they might turn to grandparents to provide financial assistance, live together in multigenerational households to combine resources, or take custody of the grandchildren (Silverstein and Lee 2016; Harrington Meyer 2014; Luo et al. 2012; Baker et al. 2008). Grappling with poverty-based programs such as Medicaid can usurp a great deal of time and energy for families. For example, despite repeated attempts, Minnie’s parents could not qualify for Medicaid because they made $30 a month over the limit. Minnie was born with complex medical problems that required several surgeries. Thus, the family now owes $580,000 in medical bills. Minnie’s grandmother, Jill, age 48, moved closer, and now works from home most days to provide care for Minnie while the parents work. Jill’s employer has allowed her maximum flexibility. Jill said: “My job has been really, really supportive, and I’m

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now working pretty much whatever schedule I can work. Somedays, I go in at four in the evening and work until midnight. Some nights I work the overnight” (Harrington Meyer and Abdul-Malak 2020:251). Jill helps pay Minnie’s medical bills, giving Minnie’s parents $300 a month, and still raising her two younger sons who live with her. She loves being with Minnie but grows quite weary. Medicaid coverage of medical bills would diminish the families’ financial anxieties. Medicaid coverage of at-home skilled nursing care would provide Jill with much-needed respite. It is worth noting that the United States has two universal old age entitlement programs, Social Security and Medicare, which provide steady income and coverage of health care costs. As such, they enable many grandparents to leave paid work and focus on care work for grandchildren. However, given that the average age at which Americans become grandparents is about 50, these programs often provide support after grandchildren are grown (American Association of Retired Persons 2019). Eligibility for Medicare begins at age 65, and early receipt of Social Security benefits begins at age 62. However, those who take Social Security benefits early face up to a 30% reduction in benefits for the remainder of their lives (Munnell 2013). Therefore, while Social Security and Medicare generally provide robust support for older persons, they provide an alternative to employment only for those grandparents who become grandparents at later ages. Those who become grandparents earlier in life are not able to rely on old age programs. The timing and sequencing of grandchildren can significantly impact grandparent well-being but is not something grandparents control (Harrington Meyer 2014).

Discussion In contrast to most other nations, the United States provides little support for working families. The United States does not provide federally guaranteed paid vacation, paid sick leave, paid parental leave, flexible work schedules, health care, or affordable, high-quality child care. When providing assistance for working families, the United States relies mainly on poverty-based social welfare programs, including SSI and Medicaid. Due to the dearth of federal supports for families, unmet need is substantial, and families turn to grandparents for muchneeded assistance. Although grandparents often are happy to help, doing so can adversely impact financial, social, emotional, and physical well-being (Harrington Meyer 2014; Harrington Meyer and Abdul-Malak 2020). Grandparents with substantial resources and relatively few competing demands often are able to provide grandchild care seamlessly. Conversely, grandparents with fewer resources and relatively more competing demands disproportionately experience the consequences of inadequate federal guarantees and the U.S. government’s reliance on poverty-based programs. In March 2020, another layer of complexity surrounding grandparent care work arose due to the emergence of the COVID-19 pandemic. Older

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individuals are at increased risk of developing a severe and sometimes lethal case of COVID-19, prompting many grandparents to socially distance without their children and grandchildren (Aleccia 2020; Frost 2020; Harrington Meyer 2020). Across America, millions of grandparents and grandchildren experienced the heartbreak of not being able to hug each other (Frost 2020; Harrington Meyer 2020). Conversely, some grandparents socially distanced with their grandchildren because they were needed to provide more child care than ever. In these families, parents struggled to juggle work and child care as daycares closed, schools switched to online instruction, and some lost their jobs and health insurance (Aleccia 2020; Frost 2020; Gidick 2020; Harrington Meyer 2020). Indeed, during the pandemic, many grandparents increased grandchild care, even though it meant increasing their risk of contracting COVID-19 (Aleccia 2020; Gidick 2020). Some grandparents have moved in with their children; others continue visiting daily or weekly, while some socially distancing grandparents have turned to technology to help provide some type of grandchild care (Aleccia 2020; Frost 2020; Harrington Meyer 2020). In addition to these dynamics, the pandemic has caused some grandparents to lose their jobs, which has disrupted their capacity to provide the monetary support they had been providing to their children and grandchildren before the pandemic (Harrington Meyer 2020). Other grandparents have kept their jobs and reduced their expenditures, enabling them to increase financial supports to younger generations (Harrington Meyer 2020). Hence, the pandemic has prompted some grandparents to increase grandchild care while preventing others from providing care (Aleccia 2020; Frost 2020; Gidick 2020; Harrington Meyer 2020). Future research on the impact of policies on grandparent care work will need to pay careful attention to variation linked to socioeconomic standing. The benefits of spending time together for both grandchildren and grandparents have been well documented (Gidick 2020; American Association of Retired Persons 2019; Harrington Meyer 2014). Grandparents often reap tremendous social, emotional, and physical rewards when caring for their grandchildren. However, the benefits can be overshadowed when the need for care outpaces grandparent resources. Grandparents with the fewest economic, educational, and physical resources often are asked to do the most. Hence, more research is needed on the impact of U.S. policies on grandparent financial, social, emotional, and physical well-being (Harrington Meyer 2014). Research to date suggests that more comprehensive policies would allow grandparents with sparse resources to provide more comprehensive care with minimal adverse consequences.

References Aleccia, JoNel. 2020. “‘We Miss Them All So Much’: Grandparents Ache as the COVID Exile Grinds On.” Kaiser Health News. https://khn.org/news/we-miss-them-all-so-m uch-grandparents-ache-as-the-covid-exile-grinds-on/.

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American Association of Retired Persons. 2019. 2018 Grandparents Today National Survey. https://www.aarp.org/content/dam/aarp/research/surveys_statistics/life-leisure/2019/ aarp-grandparenting-study.doi.10.26419-2Fres.00289.001.pdf. Baker, Lindsey A., Merril Silverstein, and Norella M. Putney. 2008. “Grandparents Raising Grandchildren in the United States: Changing Family Forms, Stagnant Social Policies.” Journal of Societal & Social Policy 7:53–69. Boesch, Diana. (2018). The Uneven Expansion of Access to Paid Sick Days, Center For American Progress. Washington, DC: Center for American Progress. https://www.americanp rogress.org/issues/women/news/2018/08/30/457309/uneven-expansion-access-paid-s ick-days/. Bureau of Labor Statistics. 2018. “Access to Paid and Unpaid Family Leave in 2018.” http s://www.bls.gov/opub/ted/2019/access-to-paid-and-unpaid-family-leave-in-2018.htm. Center on Budget and Policy Priorities. 2018. “Policy Basics: Supplemental Security Income (SSI) Program.” https://www.cbpp.org/research/social-security/policy-basicssupplemental-security-income. Frost, Alexandra. 2020. “Heartache for Those Unable to See Their Newborn Grandchildren.” AARP. https://www.aarp.org/home-family/friends-family/info-2020/gra ndparents-newborn-coronavirus.html. Gidick, Kinsey. 2020. “Grandparents Play Starring Role in Multigenerational Home Life.” AARP. https://www.aarp.org/home-family/friends-family/info-2020/grandpa rents-support-during-coronavirus.html. Glynn, Sarah J. 2012. Working Parents’ Lack Of Access To Paid Leave And Workplace Flexibility. Washington, DC: Center for American Progress. https://cdn.americanprogress. org/wp-content/uploads/2012/11/GlynnWorkingParents-1.pdf. Glynn, Sarah J. 2019. Breadwinning Mothers Continue to Be the U.S. Norm. Washington, DC: Center for American Progress. https://www.americanprogress.org/issues/women/ reports/2019/05/10/469739/breadwinning-mothers-continue-u-s-norm/. Harrington Meyer, Madonna. 2014. Grandmothers at Work: Juggling Families and Jobs. New York: NYU Press. Harrington Meyer, Madonna. 2020. Grandmothers at Work During Coronavirus. Lerner Center of Public Health Promotion. https://lernercenter.syr.edu/2020/05/01/grandm others-at-work-during-coronavirus/. Harrington Meyer, Madonna and Ynesse Abdul-Malak. (2020). Grandparenting Children with Disabilities. New York: Springer Publications. Hayslip, Bert, Christine A. Fruhauf, and Megan L. Dolbin-MacNab. 2019. “Grandparents Raising Grandchildren: What Have We Learned Over the Past Decade?” The Gerontologist, 59(3):e152–e163. https://doi.org/10.1093/geront/gnx106. Herd, Pamela and Donald P. Moynihan. 2019. Administrative Burden: Policymaking by Other Means. New York: Russell Sage Foundation. Heymann, Jody. 2013. Children’s Chances: How Countries Can Move from Surviving to Thriving. Cambridge, MA: Harvard University Press. Igel, Corinne and Marc Szydlik. 2011. “Grandchild Care and Welfare State Arrangements in Europe.” Journal of European Social Policy 21 (3):210–224. https://doi.org/10.1177/ 0958928711401766. Livingston, Gretchen. 2018. “About One-Third of U.S. Children are Living with an Unmarried Parent.” Washington, DC: Pew Research Center. https://www.pewresea rch.org/fact-tank/2018/04/27/about-one-third-of-u-s-children-are-living-with-an-un married-parent/.

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Livingston, Gretchen and Kim Parker. 2010. “Since the Start of the Great Recession, More Children Raised by Grandparents.” Washington, DC: Pew Charitable Trusts. https://www.pewsocialtrends.org/2010/09/09/since-the-start-of-the-great-recessionmore-children-raised-by-grandparents/. Luo, Ye, Tracey A. LaPierre, Mary Elizabeth Hughes, and Linda J. Waite. 2012. “Grandparents Providing Care to Grandchildren: A Population-Based Study of Continuity and Change.” Journal of Family Issues 33 (9):1143–1167. https://doi.org/10. 1177/0192513X12438685. Malik, Rasheed, Katie Hamm, Leila Schochet, Cristina Novoa, Simon Workman, and Steven Jensen-Howard. 2018. America’s Child Care Deserts in 2018. Washington, DC: Center for American Progress. https://www.americanprogress.org/issues/early-child hood/reports/2018/12/06/461643/americas-child-care- deserts-2018/. Martin, Joyce A., Brady E. Hamilton, Michelle J.K. Osterman, and Anne K. Driscoll. 2019. Births: Final Data for 2018. U.S. Department of Health and Human Services, National Vital Statistics Reports. https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_ 13-508.pdf. Maye, Adewale. 2019. No Vacation Nation, Revised. Washington, DC: Center for Economic and Policy Research. https://cepr.net/images/stories/reports/no-vacation-na tion-2019-05.pdf. Munnell, Alicia H. 2013. Social Security’s Real Retirement Age is 70 (IB#13–15). Chestnut Hill: Center for Retirement Research at Boston College. https://crr.bc.edu/wp-con tent/uploads/2013/10/IB_13-15-508x.pdf. Scott, Ellen K., Andrew S. London, and Allison Hurst. (2005). “Instability in Patchworks of Child Care When Moving from Welfare to Work.” Journal of Marriage and Family, 67 (2); 370–386. Silverstein, Merril and Yooumi Lee. (2016). Race and Ethnic Differences in Grandchild Care and Financial Transfers with Grandfamilies: An Intersectional Resource Approach. P. 19–39 in M. Harrington Meyer and Y. Abdul-Malak, eds., Grandparenting in the United States. Amityville, NY: Baywood Publishing. Toossi, Mitra and Teresa L. Morisi. 2017. Women in the Workforce Before, During, and After the Great Recession. Washington, DC: U.S. Bureau of Labor Statistics. https://www.bls. gov/spotlight/2017/women-in-the-workforce-before-during-and-after-the-great-reces sion/pdf/women-in-the-workforce-before-during-and-after-the-great-recession.pdf.

11 SOCIAL POLICIES FOR OLDER WORKERS Debra Street and Áine Ní Léime

Since at least the 1970s, policy debates about the future of Social Security retirement have crowded out comprehensive consideration of policies that could support older workers remaining in employment longer. Similar to the rhetoric of international policy influencers (Organization of Economic Cooperation and Development [OECD] 2006), U.S. policy makers have centered debate more on the prospects of delaying retirement to bolster the fiscal health of the U.S. retirement system than on considering how, where, and what kinds of policies would support adequate employment opportunities for different types of older workers. This is problematic, we argue, because delaying retirement and extending work are not merely two sides of the same coin. Compelling people to delay retirement is actually quite straightforward. Recent increases in the normal retirement age (NRA) for full eligibility for Social Security Old Age Security (OAS) retirement benefits makes employment to older ages an unavoidable necessity for many workers. The nudge toward delayed retirement via public pension policies is not about dignifying employment or ensuring adequate jobs, it is about balancing Social Security’s books into the future. Whether working longer is the most appropriate mechanism to accomplish that is open to debate. What is not debatable is that devising policies that would actually support extending work is much more difficult to achieve than increasing the retirement age. Work-centric policies would need to take into account not only cutting pension costs but also the availability of suitable employment, willing employers, and a constellation of broader life-course factors that reflect the contours of contemporary older Americans’ life experiences, as well as those of people to whom their lives are linked (see Harrington Meyer and Kandic in this volume).

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Life-course scholars underscore the accumulation of advantages and disadvantages over the entire life course (Dannefer 2003; Ferraro et al. 2009; see Dannefer and Han in this volume) that create the outcomes older workers experience. Devising effective social policies for older workers necessarily involves comprehending how family status, age, gender, race, ability, and other social statuses intersect with employment structures, and then accommodating the unequal life chances that structure individual life-course trajectories and outcomes. In the increasingly bifurcated world of employment, job-rich older workers might extend work in the later phase of professional, satisfying, highlycompensated careers and feel empowered while being enriched by working to later ages (Fideler 2012). However, for job-poor workers, with a lifetime of low wages and unfulfilling and often precarious or insecure employment, the demand to extend work ignores their persistent disadvantages and barriers to working longer. Policy innovations could adjust Social Security-credited earnings by adequately accounting for time out of employment for motherhood and caring, requiring employers to sustain age-friendly workplaces and employment practices, and factoring in the kinds of work that actually compel workers in some occupations to retire earlier. Proponents of extending working lives must confront the challenges of cumulative (dis)advantage, employment capacity, and the adequacy of employment opportunities for older workers. They must recognize the distinction between “elders who must work, and those who can afford not to” (Ghilarducci 2015). Gender, race, family status, compromised health, disability, and other characteristics differentiate, and to some extent stratify, older workers: some must work, others can afford to stop; some struggle to remain in the labor force, others are able to work but choose not to do so; some need the money, others love the job.

Delaying Retirement/Working Longer Discussion about continued employment too often centers around an imagined potential for most older Americans’ employment rather than acknowledging the employment circumstances they actually encounter. Labor market complications create wicked problems—situations lacking consensus on either problem definition or potential solutions (Roberts 2000)—for older workers. Complexities include: the mismatch between available jobs and older workers’ skills; frequent disconnects between expanding local labor markets and where older people live; physical challenges of work in the face of functional disabilities that increase with age; employment and retirement preferences; and competing family responsibilities, whether grandparenting (see Harrington Meyer and Kandic in this volume) or caring for disabled or frail adult family members. It is all the more difficult to develop progressive policies for older workers against a backdrop of an ageist and age-denying culture (Street and Tompkins 2017).

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Proponents of extending work often overlook the demand for, or quality of, older workers’ potential employment. Yet, many older American workers have health and physical impairments that make continued employment to older ages difficult, impossible, or inequitable. This is particularly the case for those in physically demanding jobs. Older workers might lack the particular skills or pay expectations that employers demand when recruiting or retaining workers. Family members need care, no matter how much caring interferes with employment. Finally, gaps in pay for workers of all ages and savings capacity/ pension eligibility are compounded by an array of intersecting factors: gender, racial/ethnic minority status, immigration status, and levels of education. These inequalities reflect persistent disadvantages structured into labor markets and retirement income systems that structure accumulations of advantage or disadvantage over the life course (see Dannefer and Han in this volume). To use gender as one example of how inequalities accumulate over the life course (see Homan in this volume), older women are more likely to be long-term unemployed given gendered age discrimination and the perception that, young or old, women are never quite the right age for their jobs (Duncan and Loretto 2004). Despite persistent gender gaps in wages represented in women’s lower average incomes, an argument can be made that women actually need higher pay to create potential for enough income in retirement because women typically have longer retirements, provide more uncompensated care, spend more time living alone, and have higher medical costs than men. U.S. employment and retirement policies inadequately accommodate the differing trajectories of women’s and men’s working lives and systematically disadvantage women for fulfilling normative caregiving and motherhood roles (Metlife 2011). Although it is beyond the purview of this short chapter, other social statuses multiply disadvantages related to later-life employment. Life-course inequalities experienced by older workers—and older women workers, in particular—are further magnified when the multiple intersections of age, gender, race/ethnicity, ability, and other marginalized or lesser-valued social statuses are taken into account (Collins 2015).

Delaying Retirement: Pension Reforms In recent decades, an increase in the pension eligibility age for public OAS Social Security benefits has coincided with the expanded individualization of risk under occupational defined-contribution retirement plans. When it is possible, these changes make later retirement a prudent financial choice for most older workers. For beneficiaries who work while receiving OAS retirement benefits before reaching the NRA (currently 66 for workers born up to 1954), wages decrease benefits. For every $2 earned above an annual Social Security retirement benefits limit ($17,640 in 2019), benefits decrease by $1. Once beneficiaries reach the NRA, there are no OAS benefits earnings limits (Social Security Administration 2019). This age-based change in the tax on earnings incentivizes work for those

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66 and older who are able to continue. Finally, postponing receipt of OAS benefits past the NRA yields a monthly actuarially determined increase in benefits. This amounts to 130% of the full NRA retirement benefit if it is not taken up until age 70 (Social Security Administration 2019). The continuing accrual of retirement benefits supports the interpretation of a difference between the de jure and de facto NRA; while the de jure NRA might be 66 or 67 (depending on birth year), age 70 is the de facto age of full benefits (Munnell 2013). Increasing the NRA, eliminating the earnings test once the NRA is reached, and augmenting OAS retirement benefits for three extra years to age 70 represent a set of Social Security reforms that can be construed as policies friendly to older workers, given that the changes were in part enacted to encourage Americans who could, to work longer if they wanted to. The consequences of continued employment and changes in Social Security benefit accrual at different ages indicate that Social Security is, arguably, the single major social policy affecting older workers’ employment in the United States. Saving privately for retirement, whether through a defined-contribution occupational savings plan or an individual retirement account (IRA), depends on secure, steady employment and the availability of a surplus to save. The 2008 economic crisis wreaked havoc on the value of private retirement resources because account balances shrunk as stock market values dropped. Older workers coped in varied ways. Some who intended to retire tried to remain in work to recoup their losses. Some who became unemployed took jobs beneath their skill levels and expertise simply to have a wage (Federal Reserve 2015). Others left the labor force earlier than they preferred and redefined their circumstances as retirement, a response to the stigma of non-voluntary job loss and unemployment (Johnson and Gosselin 2018). To make ends meet, many older workers exhausted their retirement savings at pre-retirement ages, an example of how period effects can have profound consequences at specific points in the life course. While defined-contribution retirement plan policies (such as 40lks and IRAs) permit maximizing older workers’ contributions because of more favorable tax treatment after age 50, having an adequate income is the precursor to savings. During the COVID-19 pandemic (as of early October 2020), the U.S. stock market had rebounded after initial drops, but the labor market had taken an extraordinary beating. It is difficult to predict how older workers can or will respond to current and developing labor market conditions. Some might decide to forgo employment due to discouragement, discrimination, or health conditions that put them at risk for COVID-19 complications. Others might return to or try to stay in the labor force to meet current needs or maximize retirement savings. Even before the pandemic, about half of all American workers worked in jobs with no occupational retirement plans, and about a quarter of working-age adults had no retirement savings or access to pension plans beyond Social Security (Federal Reserve 2019). The pandemic intensifies existing weaknesses in private pension coverage and adequacy, and it might have the unintended social

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policy consequence of making Social Security even more essential for income security in later life than it was pre-pandemic.

Extending Work: Labor Market Realities Whether sufficient jobs—private or public—can be created post-pandemic to meet the desire/need for older workers to be employed, how jobs would be distributed throughout the United States, what skills would be needed, and what pay could be offered are all missing pieces in the “social policy for older workers” puzzle. The boundaries between employment and retirement statuses are fluid, featuring bridge employment, second careers, flexible working, and unretirement (Wang and Schultz 2010). Despite higher rates of older worker employment in recent decades, even before the pandemic, employment prospects for older adults were far from uniformly positive. Most germane during the pandemic are potential lessons that can be derived from the aftermath of the Great Recession of 2008–2009. That period featured high levels of unemployment and early retirement, yet simultaneously accelerated a trend toward work at later ages. Many older workers tried to stem retirement security losses by postponing retirement, staying in jobs longer than they planned. Laid-off and unemployed older workers had the highest risk of remaining long-term unemployed (Bureau of Labor Statistics 2016). When older jobseekers finally found work, it was often with fewer hours, lower pay, or both (General Accounting Office 2012; Lain 2012). Skills–job mismatches made re-employment especially difficult for older workers who were displaced due to factory closings or business downsizing because such workers often lacked the technical skills needed for other available jobs. Workplace stereotypes and ageism in employment decisions also meant that, even when older workers were qualified and capable, they often experienced ageist discrimination by employers. This manifested both in terms of being overlooked for promotion and also through unjustified “downsizing” when older workers were laid off or let go from long-tenure employment as a way for companies to cut costs or to replace them with preferred younger workers (Roscigno et al. 2007). Demand-side issues receive scant attention in many policy debates about older workers. Typically, the expectation is that the older individual is responsible for relocating or upskilling to find or maintain employment. With so much evidence of ageist practices that undermine older workers’ employment, what could make employers eager to retain or recruit older workers? Pre-pandemic, employers seemed to have few jobs for which many older workers’ skills were in high demand. Although 2019 unemployment rates skirted record lows, the 2020 labor market, pummeled as it has been by the pandemic, creates serious doubts about whether there will be either strong demand for older workers’ labor or a desire from employers to hire older workers, no matter what social policies could be imagined.

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Work–Family Imbalance and Anti-Discrimination Policies Paid family leave in the United States is relatively rare and usually at the employer’s discretion. The Family and Medical Leave Act (FMLA) provides for leave due to parenthood or providing care to immediate family members. It covers employees who meet minimum standards of job tenure and hours worked annually and who are employed by the government or large private sector organizations (with 50 or more workers). Job-protected FMLA leave can be taken for up to six months, but there is no requirement that workers on leave must be paid. For most American workers, there is no entitlement to paid or unpaid leave at all (Glynn 2020). All caregivers face a variety of short- and longterm costs associated with caregiving, including out-of-pocket expenses, disrupted employment, the need to shift to part-time work, and lower incomes (and thus less surplus to save for retirement or to contribute to Social Security) (Street and Ní Léime 2020). The use of the 35 highest years of pay in Social Security benefit formula calculations for retirement benefits might provide caregiving individuals who are employed some leeway in maximizing their public pension benefits. However, there is no deliberate policy mechanism within Social Security to compensate employed family caregivers for essential but unpaid work or for care-related work disruptions (Ní Léime and Street 2018). Improving family-friendly policies would be a boon to all (older) workers (see Harrington Meyer and Kandic in this volume). A unique component of the American political economy that keeps older workers employed is the link between health insurance coverage and employment. Employment-based health insurance creates job lock that keeps many U.S. workers in full-time employment until they become eligible for state-provided Medicare insurance at age 65. The Patient Protection and Affordable Care Act of 2010 (ACA or “Obamacare”) had potential to minimize some of the perverse effects embedded in the structure of U.S. health insurance. These include job lock and an array of problems for those trying to purchase individual health insurance policies who confront prohibitive premiums or medical underwriting (which disqualified many with pre-existing health conditions from coverage eligibility). However, the Trump administration made rolling back the gains of ACA a top political priority, including, at the height of the pandemic, an October 2020 Supreme Court challenge to ACA’s constitutionality. One irony associated with U.S. medical care is that current health policies do not support older workers with health problems or the onset of disabilities to remain in employment, although it often compels them to try to remain employed to have any health coverage at all. Workplace policies to improve older workers’ employment prospects are piecemeal at best. In 1986, Congress abolished mandatory retirement (except for certain public safety professions) by amending the Age Discrimination in Employment Act. The Workforce Investment Act of 1998 established local One-Stop centers

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under several federal and state programs to provide access to employment and training services for displaced workers. These One-Stop centers provide services to terminated or laid-off workers (not just older workers) who have exhausted or are ineligible for unemployment benefits and who are unlikely to return to work in their previous industry or occupation (General Accounting Office 2012). The only federal program specifically targeted at older workers is the Senior Community Service Employment Program (SCSEP). SCSEP provides subsidized, community service-based on-the-job training and internships for individuals age 55 and over who have incomes less than 125% of the federal poverty threshold, are unemployed, and have poor prospects for re-employment (General Accounting Office 2012). Nationwide, it serves approximately 70,000 workers each year, with an average age of 64 (Department of Labor 2015). SCSEP jobs and training are part-time jobs with low wages—in many ways, quite the opposite of the good jobs/good pay needed to meet the needs of most older workers. Even the fragmented One-Stop centers and SCSEP programs that do exist are unevenly implemented geographically and variously effective across states (Street 2020). Anti-discrimination policies also have the potential to make a difference. While the United States might have been the world leader in enacting the Age Discrimination in Employment Act (ADEA) in 1967, its de facto impact has been limited to relatively few cases, despite the widespread perception that age discrimination is pervasive in the American workplace (General Accounting Office 2012; American Association of Retired Persons 2014; Ghilarducci 2015). Age discrimination is a barrier to older workers’ employment that pushes willing older workers out of employment they would prefer to keep. Another social policy potentially supportive of older workers is the 1990 Americans with Disabilities Act (ADA). If a worker has an eligible disability, regardless of their age, workplaces of a certain size must offer reasonable accommodation to support employment. On their faces, both age and disability anti-discrimination policies could help older individuals seeking to remain in work. Unfortunately, no legal remedies under the ADEA or the ADA have been particularly effective in helping aging workers remain employed. In a scoping study on the health and safety needs of older workers, researchers concluded that the ADEA did not work well for nonmanagerial older workers who disproportionately confronted health and safety risks at work. To the extent that cases were settled in favor of the plaintiff, verdicts typically favored older White men in managerial posts who suffered from employment-related age discrimination. Further, the ADA defined disability so narrowly that many workers with disabilities (regardless of age) were unable to demonstrate that they had a “qualified” disability to be accommodated. Judges often dismissed ADA claims (Wegman and McGee 2004). Lack of effective legal recourse for discrimination due to age or disability matters for older workers. A pre-pandemic study using the longitudinal Health & Retirement Study found

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that over half of Americans over age 50 reported being involuntarily separated from employment (Johnson and Gosselin 2018).

Social Policies for Older Workers or for Workers Who Will Become Old? Emerging trends in the United States underscore the shifting sands of precarity and security among workers of all ages. The economic havoc wreaked by the global pandemic seems likely to persist and to exacerbate unresolved labormarket problems that shape contemporary workers’ employment experiences. The pandemic will change labor markets, although it is not clear how. Even when jobs were relatively abundant, employers’ behavior indicated that they strongly preferred hiring younger rather than older workers (Neumark 2020). Researchers and policy makers alike will need a fundamental re-think of postpandemic social policies for workers if they are going to try to minimize the challenges inherent in shrinking labor markets. While circumstances for displaced older workers appear to be especially dire and should be the focus of policyrelevant research, life-course scholars also should attend to the ways that disruption associated with the pandemic in early-adulthood employment trajectories is likely to have lingering effects for the older workers of the future. In fact, a life-course framework for social policies suggests that, to be truly effective for older workers in the long-term, policies might best be conceived as policies for workers of all ages, rather than exclusively or especially for older workers. After all, in the work-longer debates referenced above, the most disadvantaged are workers with lower levels of education who have already extended their working lives by starting jobs in their late teens and early twenties while more advantaged individuals were still in education. In the moment, it is entirely predictable that job loss during the pandemic will widen the gap between the securely and wellemployed relative to workers in precarious, low-income, substandard employment. For older workers who experience job loss, there are too few adult working years left to recoup losses, and younger workers might bear a permanent scar from lost post-pandemic employment opportunities unless effective policy interventions are implemented. The United States is hardly renowned for worker- or family-friendly policies to support secure employment over working lifetimes (Street 2020). Most social policies that could improve conditions for older workers would, unless very narrowly targeted, also improve conditions for workers of all ages, since it is the transitions, turning points, and trajectories of lifetime paid and unpaid work that culminate in the seemingly unique challenges older workers face. Routine access to high-quality, affordable child care and elder care institutions is rare. This is a problem for working people of all ages that can be addressed by social policy intervention with sufficient political resolve. More generous and responsive social policies for child care are available in other countries, notably some of the northern

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countries of Europe, along with increasing emphasis on a shift from single breadwinner policies (which characterize most U.S. policies) toward dual earner/dual caregiver policy approaches (Nordstrom 2015; Crowley and Sansonetti 2019). As things stand in the United States, with few affordable services available, employed caregivers (often older women) have to figure out for themselves how to provide or arrange care for children and grandchildren, frail elder parents or partners, or disabled family members (see Harrington Meyer and Kandic in this volume). The peculiar structure of U.S. health insurance leaves many Americans un- or underinsured and places older workers at risk of becoming uninsurable until they reach Medicare eligibility at age 65 if a layoff or job loss disrupts employer-provided health insurance coverage. Americans already favor fixing the broken medical care system by expanding and rationalizing insurance coverage. Such reforms would be an improvement that would benefit workers of all ages. The picture might not be entirely bleak. Many contemporary older Americans have higher levels of education than previous cohorts and might have prospects for continued employment in rewarding jobs. Individuals who are able to delay retirement until age 70 improve their financial security through Social Security in retirement. For some workers who take time out for caregiving, work at older ages could mean that their public pensions will be calculated based on a full 35 years of employment earnings, with fewer missing quarters than in the past (unless benefit formulas change) and better Social Security benefits in their own right. On the downside, the booming economy that once meant there were more jobs to go around is a casualty of the global pandemic. Also lost in the pandemic is the sense of security that is so important to workers of all ages. Policies supporting older workers have tended to be piecemeal, under-funded, and unevenly implemented and experienced across the country. The intensely adversarial U.S. political climate gives little reason to hope for the immediate bipartisan compromises needed to support work-life balance or employment policies that could better support workers, including older workers. Although extra quarters of Social Security credit for lost earnings for caregivers who must quit jobs or work part-time would address some of the gendered disadvantages experienced in the United States, it would not resolve intransigent gender-pay or gender-pension gaps (Tucker 2019). Better support for flexible work arrangements or requiring employers to offer mechanisms for phased retirement could help older workers stay in employment longer. So, too, could putting teeth into age and disability anti-discrimination regulations. None of these policy innovations seems likely to appear soon, although the disruption caused by the pandemic might open a progressive policy window in the future that, even a year ago, seemed firmly closed. Pandemic fallout, the fragmented and strident nature of current U.S. policymaking, and the non-aligned interests of various political actors stymy the formation of social policies responsive to the needs of older workers with different life circumstances. In general, social policies affecting current older workers

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directly have been less about empowering older workers’ ability to pursue satisfying employment and more about pinching pennies in retirement income systems. Individuals in high-quality jobs might perceive employment at older ages as an attractive personal choice available to them (Fideler 2012). However, disadvantaged and vulnerable individuals who need to work to later ages to earn full retirement benefits would see their situation as older workers much differently. Current social policies for older workers are scant and have little effect on helping older workers remain adequately employed. In fact, at least some current social policies might perversely compel many older workers to struggle to find any available paid work, regardless of pay, hours, or working conditions. “Live longer, work longer” cannot be a convincing argument unless, as Burgess (2015) observed, “increases in life expectancy were spread evenly across the workforce. They are not.” What should we expect from future debates about social policies for older workers? Through the end of 2019, shifting governmental priorities, a thriving economy, and neoliberal enthusiasm failed to coalesce around developing social policies to do a better job addressing older workers’ needs. Then the pandemic hit and tanked the job market. Despite the increase in precarity for older workers and retirees, the prior Trump administration pursued policy initiatives that could undermine the future solvency of Social Security. Consequently, developing active labor-market policies for older workers might be more important than ever. The need for policy innovation arises not only from the disruptions that the pandemic has caused. Other labor market trends that need policy attention include the changing nature of work due to autonomous systems and artificial intelligence (Ogg and Rašticová 2020). According to one U.S. study, up to 47% of jobs are at-risk due to computerization (Frey and Osborne 2013). Technology applications in work, whether realized through digitalization (new software apps and use of computers, tablets, or phones) or robotics, might offer both benefits and risks for older workers. Jobs might become more flexible and less physically demanding (TUNED/EUPAE n.d.). At the same time, technology-driven efficiencies might push older workers out of previously secure employment and into more-precarious jobs lacking health insurance or pension benefits (Rutledge, Wettstein, and King 2020). As the pace of these technology innovations accelerates in the aftermath of the pandemic, it would be prudent for older workers to save even more and to work even longer if their health, their caregiving demands, and labor-market demand support it. The period between the aspiration for active employment policies and their future implementation likely will be measured in years, if not decades. Where do we go from here? The seminal work of Glen Elder (1974), Children of the Great Depression, hints at some of the processes that life-course scholars should analyze post-pandemic and draws some lessons policy makers should take to heart. History has shown that relatively good economic times do not

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necessarily inspire meaningful or progressive social policy. In the likely bad times ahead, social policies for older workers could incorporate two key life-course insights: (1) earlier life circumstances strongly shape ensuing ones, and (2) individuals become older workers after experiencing historic events within the linked lives of communities and families. Taking these insights to heart might make it possible for future cohorts of older workers to understand that we are all in this together and for policy makers to support changes in future social policy debates focused on workers in all life-course stages, including older workers.

References American Association of Retired Persons. 2014. Staying Ahead of the Curve 2013: The AARP Work and Career Study, Older Workers in an Uneasy Job Market. Washington, DC: AARP. Bureau of Labor Statistics. 2016. “Local Area Unemployment Statistics.” http://www.bls. gov/lau/stalt.htm. Burgess, Gary. 2015. “Pro-Con: Should the Retirement Age Go Up?”Heritage Foundation, Washington. https://www.heritage.org/social-security/commentary/pro-conshould-the-retirement-age-go. Collins, Patricia Hill. 2015. “Intersectionality’s Definitional Dilemmas.” Annual Review of Sociology 41:1–20. Crowley, Niall and Silvia Sansonetti. 2019. New Visions for Gender Equality 2019. Brussels: European Commission. Dannefer, Dale. 2003. “Cumulative Advantage/Disadvantage and the Life Course: CrossFertilizing Age and Social Science Theory.” The Journals of Gerontology: Series B Psychological Sciences and Social Sciences 58 (6):S327–S337. Department of Labor. 2015. 2015 Congressional Budget Justification. Employment and Training Administration, Community Service Employment for Older Americans. https://www.dol.gov/ sites/dolgov/files/general/budget/2015/CBJ-2015-V1-07.pdf. Duncan, Colin and Wendy Loretto. 2004. “Never the Right Age: Gender and Age-Based Discrimination in Employment.” Gender, Work & Organization 11 (1):95–115. Elder, Glen H., Jr. 1974. Children of the Great Depression: Social Change in Life Experience. Chicago: University of Chicago Press. Federal Reserve Bank of St. Louis. 2015. Age and Gender Differences in Long-Term Unemployment: Before and After the Great Recession. Economic Synopses 26. https://research. stlouisfed.org/publications/economic-synopses/2015-11-10/age-and-genderdifference s-in-long-term-unemployment-before-and-after-thegreat-recession.pdf. Federal Reserve Board of Governors of the Federal Reserve System. 2019. Report on the Economic Well-Being of U.S. Households in 2018. Washington, DC: Federal Reserve. Ferraro, Kenneth F., Tatyana P. Shippee, and Marcus H. Schafer. 2009. Cumulative Inequality Theory for Research on Aging and the Life Course. P. 413–433 in Vern L. Bengston, Daphna Gans, Norella M. Pulney, and Merril Silverstein, eds., Handbook of Theories of Aging. New York: Springer Publishing Company. Fideler, Elizabeth. 2012. Women Still at Work: Professionals over Sixty and on the Job. Lanham, MD: Rowman & Littlefield. Frey, Carl Benedikt and Michael A. Osborne. 2013. The Future of Employment: How Susceptible Are Jobs to Computerisation? Oxford, UK: Oxford Martin School.

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General Accounting Office. 2012 Unemployed Older Workers: Many Experience Challenges Regaining Employment and Face Reduced Retirement Security, GAO 12–445. Washington, DC: General Accounting Office. Ghilarducci, Teresa. 2015. “Senior Class: America’s Unequal Retirement.” American Prospect. https://prospect.org/economy/senior-class-america-s-unequal-retirement/. Glynn, Sara Jane. 2020. “The Rising Cost of Inaction on Work-Family Policies.” Center for American Progress. https://www.americanprogress.org/issues/women/news/2020/ 01/21/479555/rising-cost-inaction-work-family-policies/. Johnson, Richard W. and Peter Gosselin. 2018. How Secure Is Employment at Older Ages? Washington, DC: The Urban Institute. Lain, David. 2012. “Working Past 65 in the UK and the USA: Segregation into ‘LoPAQ’ Occupations?” Work, Employment & Society, 26 (1):78–94. http://doi.org/10.1177/ 0950017011426312. Metlife. 2011. The MetLife Study of Caregiving Costs to Working Caregivers Double Jeopardy for Baby Boomers Caring for Their Parents. Westport, CT: Metlife Mature Market Institute. Munnell, Alicia. 2013. Social Security’s Real Retirement Age Is 70. Issue Brief 13–15. Boston, MA: Center for Retirement Research at Boston College. Neumark, David. 2020. “Age Discrimination in Hiring: Evidence from Age-Blind vs. Non-Age-Blind Hiring Procedures.” National Bureau of Economic Research Working Paper No. 26623. Cambridge, MA: National Bureau of Economic Research. Ní Léime, Áine and Debra Street. 2018. “Working Later in the USA and Ireland: Implications for Precarious and Securely Employed Women.” Ageing & Society 39(10):2194–2218. Nordstrom, Annelie. 2015. A Holistic Approach to the Provision of Care: A Key Ingredient for Economic Independence. Pp. 45–48 in Francesca Bettio and Silvia Sansonetti, eds., Visions for Gender Equality. Luxembourg: European Commission. Ogg, Jim and Martina Rašticová. 2020. Key Issues and Policies for Extending Working Life. Pp. 3–27 in Áine Ní Léime, James Ogg, Martina Rasticova, Debra Street, Clary Krekula, Monika Bédiová, and Ignacio Madero-Cabib, eds., Extended Working Life Policies: International Gender and Health Perspectives. Cham, Switzerland: Springer. http s://doi.org/10.1007/978-3-030-40989-2_5. Organization of Economic Cooperation and Development. 2006. Live Longer, Work Longer. Paris: OECD Publishing. Roscigno, Vincent J., Sherry Mong, Reginald Byron, and Griff Tester. 2007. “Age Discrimination, Social Closure and Employment.” Social Forces 86 (1):313–334. Rutledge, Matthew S., Gal Wettstein, and Sara Ellen King. 2020. “Will Imports and Robots Push Older Workers into Non-Traditional Jobs?” Center for Retirement Research, Issue in Brief Number 20–26. Social Security Administration. 2019. Facts and Figures about Social Security, 2019. Social Security Office of Retirement and Disability Policy. https://www.ssa.gov/policy/docs/ chartbooks/fast_facts/2019/fast_facts19.html. Street, Debra. 2020. United States. P. 481–493 in Áine Ní Léime, James Ogg, Martina Rasticova, Debra Street, Clary Krekula, Monika Bédiová, and Ignacio Madero-Cabib, eds., Extended Working Life Policies: International Gender and Health Perspectives. Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-030-40985-2_39. Street, Debra and Áine Ní Léime. 2020. Problems and Prospects for Current Policies to Extend Working Lives. P. 85–113 in Áine Ní Léime, James Ogg, Martina Rasticova, Debra Street, Clary Krekula, Monika Bédiová, and Ignacio Madero-Cabib (eds)

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Extended Working Life Policies: International Gender and Health Perspectives. Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-030-40989-2_5. Street, Debra and Joanne Tompkins. 2017. Is 70 the New 60? Extending American Women’s and Men’s Working Lives. P. 193–215 in Áine Ní Léime, Debra Street, Sarah Vickerstaff, Clary Krekula, and Wendy Loretto, eds., Gender, Ageing and Extended Working Lives: International Analysis from a Critical Perspective. Bristol: Policy Press. Tucker, Jasmine. 2019. “Women and the Lifetime Wage Gap: How Many Woman Years Does it Take to Equal 40 Man Years?” National Women’s Law Center Fact Sheet, March. TUNED/EUPAE. n.d. Improving work-life balance: opportunities and risks coming from digitalization. SSDC Field Study. https://www.epsu.org/sites/default/files/article/files/ SSDC%20NEA%20Field%20Study%20WLB%20-%20EN.pdf. Wang, Mo and Kenneth Schultz. 2010. “Employee Retirement: A Review and Recommendations for Future Investigation.” Journal of Management 36 (1):172–206. Wegman, David H. and James P. McGee, eds. 2004. Programs and Policies Related to the Older Workforce and Safe Work. Pp. 149–173 in Health and Safety Needs of Older Workers. Washington, DC: National Academies Press. https://www.ncbi.nlm.nih.gov/ books/NBK207714/.

INDEX

Ability see disability Administration on Community Living (ACL) 107–8 Adolescent-limited trajectories of offending 76–7 Affordable Care Act (ACA) 103, 108, 129 Age discrimination 126, 129–30 Age Discrimination in Employment Act, 129–30 Age-crime curve 74–8, 82 Age-graded theory of informal social control 75–6, 78 Alzheimer’s Caregiver Support Act (proposed) 107 Alzheimer’s disease 100–3, 106–7, 115 Alzheimer’s Disease Research Semipostal Stamp Act 107 Alzheimer’s Disease Supportive Services Program 107 American Community Survey 89–90, 94 American Recovery and Reinvestment Act of 2009 25 Americans with Disabilities Act (ADA) 130 Anti-discrimination laws and policies 13, 34, 129–30, 132 Area Agencies on Aging 108 Asian American 101 Baby bonds 12, 47–8 Biological age 44–5, 47–8

Black Americans 10, 12, 20, 65, 84, 106, 115; wealth and health gap compared to White Americans 41–8 Caregiver leave 37 Causal identification 76, 79–81 Child and Dependent Care Credit 4, 6 Child care deserts 118 Child Nutrition program 4 Child Tax Credit 4, 6 Chronical age 44–5 Civil Rights Act of 1964 7 Civil rights movement 2, 53 Context of reception 87–8, 94–5 Counterfactual framework 79–82 COVID-19: child care 37, 100, 120–1; food insecurity and insufficiency 65, 70–1; job market 127; rates of hospitalization, morbidity, and mortality 26 Credit for Caring Act 108–9 Criminal justice system: expansion 12, 81, 83; reactive approach 74; social consequences of 83–4 Cumulative (dis)advantage (CDA) 9–13, 17–8, 24–7, 37, 46, 101, 125 Cumulative inequality 1, 3, 9–10 Current Population Survey 65–6, 68 Cycle of induced incompetence 19

138

Index

Defamilization 101, 103–4, 106 Deferred Action for Childhood Arrivals (DACA) 92 Dental benefits 5, 43 Differential association theory 77–8 Disability Resource Centers 108 Disability 1, 2, 5–6, 8–9, 19, 69, 70, 93, 104, 109, 125–6, 129–30, 132 Disability benefits 4, 5 Disability Resource Centers 108 Discrimination 6–7, 19, 31–4, 41, 46, 60, 91, 126–30, 132 Domestic violence 34 Drug Abuse Resistance Education (D.A.R.E.) program 81 Earned income tax credit 4, 6 Economic Opportunity Act 7 Elementary and Secondary Education Act 7 Employment-based health care 116, 129, 132–3 Equal pay laws 34, 37 Familismo 104 Family and medical leave 5, 6, 37, 117, 129 Family and Medical Leave Act (FMLA) 5, 117–8, 129 Family Caregiver Tax Credit Act (proposed in Massachusetts) 109 Farm bills 64, 69 Farmers Market Nutritional Program (FMNP) 21 Federal Home Loan Mortgage Corporation (Freddie Mac) 53 Federal Housing Administration (FHA) 53 Federal National Mortgage Association (Fannie Mae) 53 Federal rental assistance programs 12, 52–61 Flexible savings accounts 5 Food assistance programs: Child and Adult Care Food Program 67; emergency programs (Commodity Supplemental Food Program and food pantries) 68; National School Lunch Program 67; School Breakfast Program 67; Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) 4, 9, 12, 21, 67, 69; Supplemental Nutritional Assistance Program (SNAP) 3, 9, 67–71, 94

Food insecurity 64–71 Food insufficiency 65, 70–1 Food Retail Expansion to Support Health program (FRESH) 24 Food Stamp Act 7 Gender 6, 8–9, 11, 13, 19, 31–7, 114–6, 126, 132 Gender equity policy 11, 31, 33–5 Gender inequality 31–3, 37 Gender wage gap 11, 32, 36–7 Generic social processes 11, 18–9, 25–6 Grandparent care 21, 114–21 Great Depression 1, 64–5 Great Recession of 2008 24–6, 43, 68, 115, 128 Head Start 3–4, 7, 22 Health and Retirement Study (HRS) 43, 45–6, 48, 115 Health insurance 4, 57, 65, 91, 93–4, 116, 118, 121, 129, 132–3 Health policy 34, 47–8 Healthy Start 3–5 Hispanic American 26, 90, 94, 101, 103–10, 115–18 Hispanic Established Populations for the Epidemiologic Study of the Elderly (HEPESE) 105 Home mortgage interest deduction 4, 7, 9, 54 Homestead Act of 1862 45 Housing and Community Development Act of 1974 55 Housing assistance 3, 4, 52, 54, 59, 95 Housing mobility 55, 60 Immigrant Reform and Control Act 92 Immigrant status 5, 8, 9 Immigrants 5, 71, 87–97 Immigration Act of 1882 93 Immigration admission policies 87 Immigration and Customs Enforcement (ICE) 88 Immigration and Nationality Act 7 Immigration and Naturalization Act (Hart-Celler Act) 88 Immigration enforcement policies 95–6 Immigrant naturalization policies 87 Infant mortality 5, 25, 33 Institutionalized racism 10, 31, 41

Index

Intended and unintended consequences 11, 18, 24–5 Intentionally constructed social processes 11, 18–24 Jim Crow laws 41, 45 Job training 4, 21, 130 Labor market for older adults 127–8, 131, 133 Language barriers 8, 91, 93, 107 Latinx see Hispanic American Latino Paradox 101 Lawful permanent residents (LPRs, “Green Card” holders) 88, 92 Life-course principles: agency 8, 76; ife-long development 9, 11, 36; linked lives 8, 25, 36–7, 46, 66, 95, 101; time and place 7, 94; timing 8, 36, 66, 91, 93–4, 106, 120; see also cumulative dis/advantage and cumulative inequality Life-course-persistent trajectories of offending 76–7, 83 Life insurance 5–6 Lifeline 4 Long-term care policy 101–3, 106–9 Low Income Home Energy Assistance Program 4 Mass incarceration 10, 12, 74, 83–4, 115 Medicaid 3, 8–9, 21, 25, 93–6, 102–3, 119–20 Medical expenses deductions 4 Medicare 5, 21, 96, 102–4, 120 Military service, impact on benefits for veterans and their families 6, 24 Minimum wage 25 Multifamily housing 12, 52, 54–5, 57 National Family Caregiver Support Program 106–7 National Health and Nutrition Examination Survey 56 National Health Interview Survey (NHIS) 56, 90 National Longitudinal Study of Adolescent to Adult Health (Add Health) 78 National Survey of Caregiving 105 National Youth Survey 78 Native American 118 Naturalization 92–6 Neoliberal policies, effect on social safety net 2, 23

139

New Deal 1, 45, 53 Non-governmental organizations 107–8 Normal retirement age (NRA) 106–8 Office of Minority Health 107 Office on Women’s Health 107 Old Age Security (OAS) 124, 126–7 Older Americans Act 68, 107 Paid leave 5, 25 Panel Study of Income Dynamics (PSID) 46, 55–6 Peer associations and crime prevention interventions 75, 79–83 Pell Grants 4, 5, 69 Pension eligibility age 126 Pension programs 2, 4, 6, 13, 21, 124, 126–7, 133 Personal Responsibility and Work Opportunity Reconciliation Act 94 Political representation of women 34 Preschool programs 20–1 Program of All-Inclusive Care of the Elderly 103 Progressive policies 20, 23, 125, 132 Progressive tax code 3, 6 Public assistance programs 91–6 Public charge rule 93, 95–6 Public housing 12, 52–61 Public housing agencies (PHAs) 54 Race/ethnicity 1, 6, 8–9, 21–2, 26, 41, 45–8, 65, 90, 101, 105, 114–6, 125–6 Racism: racial discrimination 6, 41, 46; structural racism 10, 31 Recognize, Assist, Include, Support, and Engage (RAISE) Act 107 Redlining 41 Reparations 12, 41–2, 48 Reproductive health services 34 Retirement age 124 Retirement benefits 4, 6, 13, 124, 126–7, 129, 133 Reverse causality 42, 49 Senior Community Service Employment Program (SCSEP) 130 Sensitive periods 9, 36, 49 Servicemen’s Readjustment Act of 1944 (“G.I. Bill”) 1, 21, 23 Sexism (structural): the linked lives principle and 36; ties to public policy and health 11, 31–7

140

Index

Sexual orientation 1, 6, 9, 19 Slavery 41, 45, 48 Social assistance (“welfare”) programs 3, 114, 116, 119–20 Social control theory 77–8 Social insurance (“entitlement”) programs 3, 5, 120 Social learning theory 77–8 Social safety net: associated stigma 54; barriers to participation 8; U.S. peer comparisons 3, 6, 23, 25, 116–7, 131–2; programs 3–7 Social Security 5, 9–10, 20–1, 114, 120, 124–9, 132 Subsidized child care 118 Supplemental Security Income (SSI) 3, 4, 93–6, 114, 119–20 Tax credits 6, 108–9 Temporary Assistance for Needy Families (TANF)/General Assistance (GA) 3, 4, 9 Undocumented immigrants 91–2, 95–6, 104 U.S. Department of Housing and Urban Development (HUD) 52–61

Vision benefits 4 Voting 7–8, 20 Voting Rights Act 7–8 “War on Drugs” 10 “War on Poverty” 2, 7, 53–4, 64 Wealth: accumulation 42–3, 46, 48–9; inequality by race and gender 12, 24, 42–50; intergenerational process of 46; relationship to health 43–4, 47–8 Welfare state 1–2, 5, 103, 116, White Americans 65, 101, 103–5, 115, 117, 130; wealth and health gap compared to Black Americans 41–8 Wisconsin Longitudinal Study (WLS) 106 Women’s workforce participation 33, 100, 115 Workforce Investment Act 129–30 Working family policies (child care, sick leave, vacation) 13, 114, 116–7, 120 Workplace harassment of women 33–4 Younger-Onset Alzheimer’s Disease Act (proposed) 107