Appetite and Nutritional Assessment [1 ed.] 9781617281389, 9781607410850

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Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved. Ellsworth, Shane J., and Reece C. Schuster. Appetite and Nutritional Assessment, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved. Ellsworth, Shane J., and Reece C. Schuster. Appetite and Nutritional Assessment, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook

Nutrition and Diet Research Progress Series

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

APPETITE AND NUTRITIONAL ASSESSMENT

No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information Ellsworth, Shane J., and Reece C.herein. Schuster. Appetite anddocument Nutritional Assessment, Nova Publishers, Incorporated, ProQuest Ebook contained This digital is sold with theScience clear understanding that the2009. publisher is not engaged in

NUTRITION AND DIET RESEARCH PROGRESS SERIES Diet Quality of Americans Nancy Cole and Mary Kay Fox 2009. ISBN: 978-1-60692-777-9 School Nutrition and Children Thomas J. Baxter 2009. ISBN: 978-1-60692-891-2

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Appetite and Nutritional Assessment Shane J. Ellsworth and Reece C. Schuster 2009. ISBN: 978-1-60741-085-0

Ellsworth, Shane J., and Reece C. Schuster. Appetite and Nutritional Assessment, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook

Nutrition and Diet Research Progress Series

APPETITE AND NUTRITIONAL ASSESSMENT

SHANE J. ELLSWORTH AND

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

REECE C. SCHUSTER EDITORS

Nova Science Publishers, Inc. New York

Ellsworth, Shane J., and Reece C. Schuster. Appetite and Nutritional Assessment, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook

Copyright © 2009 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers‘ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works.

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Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Appetite and nutritional assessment / [edited by] Shane J. Ellsworth and Reece C. Schuster. p. ; cm. -- (Nutrition and diet research progress) Includes bibliographical references and index. ISBN H%RRN 1. Appetite. 2. Nutrition--Evaluation. I. Ellsworth, Shane J. II. Schuster, Reece C. III. Series: Nutrition and diet research progress. [DNLM: 1. Nutrition Assessment. 2. Appetite--physiology. 3. Eating Disorders. 4. Nutrition Disorders. QU 146.1 A646 2009] QP136.A675 2009 612.3--dc22 2009008014

Published by Nova Science Publishers, Inc.  New York

Ellsworth, Shane J., and Reece C. Schuster. Appetite and Nutritional Assessment, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook

CONTENTS Preface Chapter 1

Ghrelin: A Peptide Involved in the Control of Appetite Carine De Vriese, Jason Perret and Christine Delporte

Chapter 2

Appetite Control- The role of central and gut neuropeptides Sarika Arora

Chapter 3

Central Inhibitory Mechanisms Controlling Water and Sodium Intake José Vanderlei Menani, Laurival Antonio De Luca Jr, Patrícia Maria de Paula, Carina Aparecida Fabrício de Andrade, Lisandra Brandino de Oliveir and Daniela Catelan Ferreira daSilva

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Chapter 5

Chapter 6

1 49

107

Cachexia: Disruption in Appetite Regulation in Need of a Successful Intervention Mark D. DeBoer

137

Clinical Holistic Medicine: A Sexological Approach to Eating Disorders Søren Ventegodt, Katja Braga, Isack Kandel and Joav Merrick

155

Making Sense of what Is Healthy for You: Children‘s and Adults‘ Evaluative Categories of Food Simone P. Nguyen and Mary Beth McCullough

175

Chapter 7

The Validity of Nutritional Assessment: Current Status Christopher N. Ochner, Eva M. Conceição and Olga Gorlova

Chapter 8

Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls Suzanne Domel Baxter, Caroline H. Guinn, James W. Hardin, Julie A. Royer and Dawn K. Wilson

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197

vi Chapter 9

Chapter 10

Contents Contemporary Assessment of Child Dietary Intake in the Context of the Obesity Epidemic Anthea M. Magarey, Annabelle M. Wilson and Emma Goodwin

259

The Use of Composite Scores to Assess Adherence to Dietary Patterns: The Mediterranean Diet Case Angeliki Papadaki and Manolis Linardakis

285

Expert Commentary Estimation of Dietary Intakes by Digital Images: Potential and Limitation Da-Hong Wang, Michiko Kogashiwa and Keiki Ogino

355

Short Commentary A Nutrition and Diabetes Mellitus Type 1: A Brief Overview Abdullah Al-Abdulhadi and Rossana Salerno-Kennedy

361

Short Commentary B Diabetes Mellitus Type 1 and Eating Disorders: A Brief Overview Steven Laragh and Rossana Salerno-Kennedy

371

Short Commentary C Use of Mid-Upper Arm Circumference as a Measure of Nutritional Status and its Relationship with Self Reported Morbidity among Adult Bengalee Male Slum Dwellers of Kolkata, India Raja Chakraborty, Kaushik Bose and Samiran Bisai

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Index

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377 387

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PREFACE Appetite is the desire to eat food and it exists in all higher lifeforms, and serves to regulate adequate energy intake to maintain metabolic needs. A person's nutritional assessment is an in-depth evaluation of both objective and subjective data related to the individual's food and nutrient intake, lifestyle, and medical history. The association of appetite, diet and nutrition with chronic disease such as diabetes has been well documented. This book presents a variety of topics on appetite and health. It highlights the complexity of accurately assessing dietary patterns and dietary needs. Also included is new research on the role of peptides in appetite control as well as a new approach in the thinking on why eating disorders occur. Chapter 1 - Ghrelin is the endogenous ligand for the growth hormone secretagogue receptor. Ghrelin is a peptide of 28 amino acids possessing an uncommon octanoyl moiety on the serine in position 3, which is crucial for its biological activity. Ghrelin is predominantly produced and secreted into the blood stream by the endocrine X/A like cells of the stomach mucosa. Besides, it is also expressed in other tissues like duodenum, jejunum, ileum, colon, lung, heart, pancreas, kidney, testis, pituitary and hypothalamus. Some of the major biological actions of ghrelin are the secretion of growth hormone, the stimulation of appetite and food intake, the regulation of gastric motility and acid secretion and the modulation of the endocrine and exocrine pancreatic functions. Ghrelin is an orexigenic peptide involved in the short-term regulation of appetite and food intake. The plasma ghrelin levels increase before meal and decrease strongly during the postprandial phase. Long-term body weight is also regulated by ghrelin, since it induces adiposity. The purpose of this chapter is to provide updated information on ghrelin, the role of ghrelin in the control of appetite, as well as the potential clinical applications of ghrelin agonists and antagonists in certain physiopathological conditions. Chapter 2 - Obesity, one of the most prevalent nutritional problems worldwide, results when energy intake exceeds the energy expenditure. In a normal state, powerful and complex physiological systems exist to balance these two sides of the equation. These systems consist of multiple pathways between Gastrointestinal Tract (GIT) and Central Nervous System (CNS), which maintain eating patterns. This gut-brain axis has both neural and humoral components that relay information to important CNS centres, including hypothalamus and brainstem. Specific populations of peptidergic neurons in the medial hypothalamus act as metabolic integrators sensing both short- and long-term availability of fuels and then orchestrate the adaptive responses through changes in food intake as well as endocrine and

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Shane J. Ellsworth and Reece C. Schuster

autonomic responses. The structure and function of many hypothalamic peptides [ Neuropeptide Y (NPY), melanocortins, agouti-related peptide (AGRP), cocaine and amphetamine regulated transcript (CART), melanin concentrating hormone (MCH), orexins have been characterized in rodent models. The gastrointestinal neuropeptides such as cholecystokinin (CCK), ghrelin, peptide YY (PYY-36), amylin regulate important gastrointestinal function such as motility, secretion, absorption and provide feedback to the central nervous system on the availability of nutrients. The mechanisms by which hormones interact with CNS appetite centers are the subject of some contention. The proximity of both the hypothalamus and brainstem to structures with a relative deficiency of blood-brain barrier (the median eminence in the case of the hypothalamus and the area postrema in respect of the brainstem) may allow direct access of circulating factors to CNS neurons. There is a growing body of evidence, however, that points to the vagus nerve as a primary site of action of some appetite-modulating hormones An understanding of these mechanisms is important to determine the pathophysiology of obesity and to allow identification of targets for the treatment of obesity. The pursuit of the body's own satiety signals as therapeutic targets promises effective reductions in body weight with minimum disruption to other systems, avoiding the side effects that occur as an unwanted consequence of therapies targeting ubiquitous neurotransmitter and receptor complexes. Chapter 3 - Ingestion of sodium and/or water is controlled by excitatory mechanisms that involve stimuli like angiotensin II (ANG II), mineralocorticoids or hiperosmolarity acting on specific areas of the brain and by inhibitory mechanisms present in different central areas and involving different hormones and neurotransmitters that act to limit these behaviors. Recent studies have shown two important inhibitory mechanisms for the control of sodium and water intake: the inhibitory mechanism of the lateral parabrachial nucleus (LPBN) and the α2 adrenergic mechanism located in forebrain areas. In the LPBN different neurotransmitters like serotonin, cholecystokinin, glutamate, corticotropin-releasing factor, GABA and opioid may modulate the inhibitory mechanism. Interactions between neurotransmitters in the LPBN, like the interdependence and cooperactivity between serotonin and cholecystokinin have also been demonstrated. In the forebrain, mixed alpha2-adrenergic and imidazoline receptor agonists, like clonidine and moxonidine, are the most effective to inhibit water and sodium intake induced by different stimuli. Inhibition of water or NaCl intake dependent on alpha2adrenergic receptor activation has been demonstrated with injection of these drugs into the lateral ventricle (LV), septal area, lateral preoptic area, and lateral hypothalamus. Previous and unpublished results presented in this chapter have shown that: A) in normovolemic rats, moxonidine injected into the LV induced c-fos expression in the organum vasculosum lamina terminalis (OVLT), ventral median preoptic nucleus (vMPN), paraventricular and supraoptic nucleus of the hypothalamus, while in sodium depleted rats, moxonidine reduced c-fos expression in the OVLT and increases it in the dorsal MPN; B) moxonidine bilaterally injected into basal amygdala (BA) reduced sodium depletion-induced sodium intake, while no effects were observed injecting moxonidine into the central amygdala; C) moxonidine into the LV reduced water and sodium intake and hypertension induced by daily subcutaneous (sc) injection of deoxycorticosterone; D) moxonidine injected into the LV also reduced food intake-induced water intake, but did not change food deprivation-induced food intake, suggesting that inhibitory effects of moxonidine in the forebrain are not due to non specific inhibition of behaviors; E) contrary to the inhibitory effects produced by injections into the

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amygdala, LV or other forebrain areas, bilateral injections of moxonidine into the LPBN increases sodium intake. Chapter 4 - Cachexia is a devastating syndrome of body wasting that worsens quality of life and survival for patients suffering from already dire and restrictive diseases such as cancer, chronic kidney disease and chronic heart failure. The common features of cachexia in these disease states and the common feature of systemic inflammation suggest shared pathophysiologic roots of cachexia in these conditions. However, previous attempts to treat cachexia via anti-inflammatory interventions and multiple other means have not proven effective, and no unifying treatment has emerged that is effective in treating cachexia in multiple disease states. Basic science investigations have revealed that inflammation-induced activation of the central melanocortin system is one likely means of producing anorexia and lean body wasting in this syndrome. Similarly, basic science approaches to blocking melanocortin activity appeared promising by demonstrating improvement of food intake and weight retention in cachexia, though unfortunately data regarding human treatment is still lacking. Finally, a new treatment approach via administration of ghrelin or ghrelin agonists appears to be a promising means of treatment, as suggested by both basic science and early human experiments, though much more investigation is needed. The hope of all investigators and clinicians in the field is that successful treatment of the symptoms of cachexia will lead to an improvement in quality of life and survival among all patients suffering from this disease. Chapter 5 - Virtually all teenage girls and young women have to some extent an eating disorder, which research has shown to covariate with the intensity of psychosexual developmental disturbances and sexual problems. We suggest simple psychosexual (psychodynamic) explanations for the most common eating disorders like anorexia nervosa, bulimia nervosa, and binge eating disorder and propose the hypothesis that eating disorders can be easily understood as symptoms of the underlying psychosexual developmental disturbances. We relate the symptoms of the eating disorders to three major strategies for repressing sexuality: 1) The dispersion of the flow of sexual energy - from the a) orgasmic potent, genitally mature (―vaginal‖) state via the b) more immature, masturbatory (―clitoral‖) state, and further into the c) state of infantile autoerotism (―asexual state‖). 2) The dislocation from the genitals to the bodies other organs, especially the digestive and urinary tract organs (the kidney-bladder-urethra) giving the situation where sexual energy is accumulated and subsequently released though the substituting organs. 3) The repression of a) free, natural and joyful sexuality into first b) sadism, and then further into c) masochism. We conclude that the eating disorders easily can be understood as sexual energies living their own life in the nongenital body organs, and we present results from the Research Clinic for Holistic Medicine, Copenhagen, where eating disorders have been treated with accelerated psychosexual development. We included the patients with eating disorders into the protocol for sexual disturbances and found half these patients to be cured in one year and with 20 sessions of clinical holistic therapy. Chapter 6 - The domain of food is highly relevant to our everyday lives and thinking, particularly its evaluative components. Evaluative categorization within the domain of food involves the grouping together of foods that share the same value laden. This chapter focuses on the evaluative categories of healthy and unhealthy foods. Healthy foods are defined as foods that give your body what it needs to help you grow, give you long lasting energy, and keep you from getting sick whereas unhealthy foods are defined as foods that do not give your body what it needs to help you grow, give you long lasting energy, and keep you from

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getting sick. In this chapter, we will review research in our cognitive development laboratory that examines evaluative categorization of foods in children and adults. In this chapter, we will also discuss new advances in our lab that begin to reveal on what basis children and adults form their evaluative categories of food. We will discuss studies in which participants were asked to evaluatively categorize unidentified foods as healthy or unhealthy through the use of their senses. The results suggest the information that children and adults gather from their own experiences/observation with the physical properties of foods helps them to determine the evaluative status of foods. Examining how children develop their evaluative categories of food is a critical issue given the astounding increase in overweight and obese children in the United States. Chapter 7 - The field of nutritional assessment is host to considerable disagreement about which methods of dietary intake assessment may be more or less valid and which techniques are most appropriate for research trials versus clinical practice. This commentary provides a brief overview of the evolution of dietary intake assessment as well as discussing if, and how, newer techniques (i.e., 24-hour food intake recalls) have improved on the validity of dietary assessment. A synopsis of the psychometric data supporting, and not supporting, the most commonly used assessment techniques is provided. Techniques are also discussed in terms of their applicability and utility in both clinical and research settings. Finally, potential offerings for future directions in the area of nutritional assessment are briefly discussed. In both research and clinical practice in dietary nutrition, the importance of accurately assessing nutritional patterns and dietary intake has led investigators to develop a range of methods for the assessment of dietary intake in outpatient settings. Below we list the most commonly used methods and describe the strength of each one, as well as their applicability in each clinical or research settings. The chapter will conclude with an overview of the major limitations, and will assess the issue of validity inherent to the use of self-report methods. Chapter 8 - Although studies involving elementary school children sometimes collect dietary reports from parents either solely or in collaboration with children, many study designs necessitate that children‘s self-reports be collected because parents are not present for the eating occasions of interest (e.g., school meals). In a dietary-reporting validation study, reported information (food items and their respective amounts) from a method such as dietary recalls is compared to reference information (food items and their respective amounts) from a gold standard method such as observation which is assumed to be the truth, collected independent of the subject‘s memory, and concerns the same meal(s) as reported information. Comparing reported information to reference information allows identification of reporting errors including omissions (referenced [eaten] items that are unreported and intrusions (reported items that are unreferenced [uneaten]). This chapter summarizes key findings from 26 methodological studies concerning children‘s dietary recall accuracy that were conducted by Baxter and colleagues and published between 1994 and 2009; the 26 studies consist of nine dietary-reporting validation studies, one non-validation study, and 16 secondary analyses studies that utilized data from one or more of the nine validation studies. The validation method was observation of school lunch, or observation of school breakfast and school lunch. The subjects were usually fourth-grade children (ages nine to ten years). Each validation study was designed to evaluate the effect on children‘s dietary recall accuracy of aspects including prompting methods, consistency of accuracy over multiple recalls, reporting-order prompts, interview modality, interview format, retention interval, and children‘s body mass index (BMI). The non-validation study investigated whether being observed eating school

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meals influenced children‘s dietary recalls. The secondary analyses studies utilized data from one of more of the validation studies to examine aspects including retrieval response categories (of children‘s verbalizations of how they remembered items eaten), accuracy over multiple 24-hour recalls by BMI category, accuracy for recalling school lunch as a singlemeal recall versus during a 24-hour recall, accuracy for reporting school breakfast versus school lunch during 24-hour recalls, the analytic approach for comparing reported and reference information to assess recall accuracy for energy and macronutrients, sources (or origins) of intrusions and types of intrusion, and intrusions in misreported and correctly reported breakfast options in the school breakfast parts of 24-hour recalls. The chapter concludes with recommendations for (a) dietary-reporting validation studies to fill research gaps, (b) maximizing children‘s dietary recall accuracy, and (c) publications of studies that utilize dietary recalls. Chapter 9 - Dietary intake has received considerable interest as part of understanding and addressing the global obesity epidemic. Food intake has an important role in the aetiology of overweight and obesity and interventions targeting communities and individuals for either prevention or management invariably include a nutrition component. An important element in evaluating the effectiveness of such interventions is assessment of dietary intake. Traditionally dietary assessment has focussed on energy, micro and macro nutrient intakes and consequent deficiency. In the 1970s this view expanded to consider the role of nutrition in chronic disease and included both deficient and excessive intakes but remained focussed on energy, macro and micro nutrients. As nutrition research turned more to prevention and management of chronic disease, the concept of a healthy diet (usually based on official dietary guidelines and recommendations) increasingly became useful and assessment tools were developed and continue to be, to classify individuals accordingly. In the last two decades and particularly the last decade, interest has progressively turned to food patterns. In the context of the rising prevalence of obesity, the characterisation of food patterns that increase the risk of positive energy balance and thus accumulation of excess weight and those associated with a protective effect against obesity will inform development and evaluation of prevention and management strategies. In addition there is increasing interest in identifying and describing those factors which influence food behaviour such as knowledge, attitudes and environments. As researchers explore the most effective way to prevent and manage the obesity epidemic there is simultaneous interest in dietary assessment as a component of impact evaluation of such interventions. Traditional methods of dietary assessment are associated with high subject burden and/or high administrative and/or analysis costs which are often not appreciated by funding bodies and thus beyond the scope of many studies. Alternative less costly methods of dietary assessment, more relevant to contemporary dietary issues and that also consider factors influencing dietary intake behaviour, are of increasing value. This review assesses the relevance to obesity of traditional and contemporary child dietary outcomes and their methods of assessment. Recent developments in dietary assessment tools, including those that assess factors influencing behaviour (i.e. intake) namely knowledge, attitudes and environments are reviewed. The important issue of tool validation will be addressed and how this might be achieved for contemporary tools. Chapter 10 - The association of diet with chronic disease has been well documented, and in recent years, research interest has focused on the investigation of whole dietary patterns, instead of single nutrients, for the prevention, and/or treatment of several diseases. The Mediterranean diet is recommended to the Western world as a dietary pattern that is both

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Shane J. Ellsworth and Reece C. Schuster

palatable and healthy, and that can be easily incorporated within a modern lifestyle. Although it is difficult to establish a definition of the ‗typical‘ traditional Mediterranean diet, Mediterranean dietary patterns share eight characteristics that differentiate them from American and northern European food cultures. In particular: a high ratio of monounsaturated to saturated fat (MUFA:SFA); high intake of vegetables; fruits, nuts and seeds; legumes/ pulses; (mainly unrefined) cereals; a low-to-moderate intake of dairy products; low intake of meat, meat products and poultry; and moderate alcohol consumption. In 1995, the use of an 8unit „a priori‟ dietary score to assess adherence to the Mediterranean diet was proposed, based on the above characteristics of this dietary pattern. This score was later revised to account for fish consumption, the intake of which in the Mediterranean diet was moderate-tohigh. Since then, several studies have used adaptations of the original Mediterranean Diet Score, and found significant inverse associations between adherence and overall mortality, disease risk, and biomarkers of health, as well as positive associations with survival. Further, the score has been utilised to detect dietary improvements in nutrition intervention studies. The purpose of this chapter is to describe and investigate the use of the original score and its adaptations in research studies, present the findings of studies utilising such indexes, and discuss validity and reliability issues for dietary assessment purposes. Suggestions for researchers wishing to employ Mediterranean diet indexes to investigate associations with chronic disease and assess adherence to the Mediterranean diet in the future will also be provided. Expert Commentary - Accurate measurement of dietary exposure is a prerequisite for understanding the relation between daily dietary intake and health effects. Dieticians and the researchers have long been striving for accuracy and simplicity in dietary measurement methods. Along with recent advance in technologies, there is an increasing popularity of using digital camera to obtain dietary intake data from target individuals. Particularly, handheld personal digital assistants with attachments of a digital camera and mobile phone card are drawing attention. This article covers strengths and problems related to the estimation of dietary consumption using digital images. In addition, the authors also proposed the potential possibility of developing camera phone as an alternative tool of dietary assessment in future clinical and research practice since camera phone will certainly become a very popular appliance in our daily life. However, whether these techniques can accurately estimate dietary intake requires a series of investigations beginning with the validation, reliability, and practicality in comparison with the conventional dietary assessment methods. Further, the effect of age on the ability to operate the electronic instruments should be considered and needs to be examined in variant age cohorts. Short Commentary A - It is well established that the pathogenesis of Type 1 diabetes (T1D) is mainly caused by genetic susceptibility. It is also believed that in these genetically susceptible individuals, environmental factors trigger autoimmunity and destruction of the insulin secreting beta cells in the pancreas. Although susceptibility may be inherited, there is a growing body of evidence showing that environmental factors might not only trigger but also maintain the chronic autoimmune process. The mostly studied environmental agents contributing to the disease are viruses and nutrition. Major dietary factors involved in the development of the disease are: a short period of breastfeeding, an early introduction to cow‘s milk, nitrates and nitrites, gluten in wheat, tea and coffee consumption in childhood. Vitamin C, D, E and zinc have all been reported to be protective agents against the development of T1D. This review will focus on the nutritional aspects that may influence T1D.

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Short Commentary B - This review will focus on the relationship between Diabetes Mellitus Type 1 (T1D) and the development of eating disorders (ED); in particular it will try to determine whether altering or skipping insulin doses as a means of weight control (diabulimia), is recognised as a common practice among diabetics. Results from the studies on the prevalence of eating disorders among those suffering from T1D, in comparison to the normative population were varied. Findings indicate that some patients do engage in insulin deprivation as a means of controlling their weight, with serious health implications. Insulin deprivation as a means of purging calories is therefore an issue not be ignored and to be considered in diabetics presenting with signs of an eating disorder. Short Commentary C - A cross-sectional study of 474 adult (> 18 years) Bengalee male slum dwellers of Kolkata, (India), was undertaken investigate the use of mid-upper arm circumference (MUAC) as a measure of nutritional status and its relationship with current reported morbidity. Height, weight and MUAC were measured using standard techniques. The body mass index (BMI) was computed following the standard formula. Classification of chronic energy deficiency (CED) was done following the WHO guideline of BMI < 18.5 kg/m2. Results revealed that MUAC of 24 cm was the best cut-off point to distinguish between CED and non-CED individuals with sensitivity (SN), specificity (SP), positive (PPV) and negative (NPV) predictive values of 86.3, 85.1, 73.3 and 92.9, respectively. Moreover, there was a significant (chi-square = 11.834, p < 0.005) difference in the presence of self reported morbidity between the two MUAC groups (MUACGI: MUAC < 24 cm and MUACGII: MUAC ≥ 24 cm) with subjects in MUACGI 2.09 times more likely to be currently morbid compared with those in MUACGII. Furthermore, morbid subjects had significantly lower mean values of weight (p < 0.005), BMI (p < 0.005) and MUAC (p < 0.001) compared to non-morbid individuals. It can be concluded that a MUAC value of 24 cm can be used as a simple and efficient cut-off point for the determination of CED and morbidity status in this population.

Ellsworth, Shane J., and Reece C. Schuster. Appetite and Nutritional Assessment, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved. Ellsworth, Shane J., and Reece C. Schuster. Appetite and Nutritional Assessment, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook

In: Appetite and Nutritional Assessment Editors: S. J. Ellsworth, R. C. Schuster

ISBN: 978-1-60741-085-0 © 2009 Nova Science Publishers, Inc.

Chapter 1

GHRELIN: A PEPTIDE INVOLVED IN THE CONTROL OF APPETITE Carine De Vriese, Jason Perret and Christine Delporte* Laboratory of Biological Chemistry and Nutrition, Université Libre de Bruxelles, Brussels, Belgium

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ABSTRACT Ghrelin is the endogenous ligand for the growth hormone secretagogue receptor. Ghrelin is a peptide of 28 amino acids possessing an uncommon octanoyl moiety on the serine in position 3, which is crucial for its biological activity. Ghrelin is predominantly produced and secreted into the blood stream by the endocrine X/A like cells of the stomach mucosa. Besides, it is also expressed in other tissues like duodenum, jejunum, ileum, colon, lung, heart, pancreas, kidney, testis, pituitary and hypothalamus. Some of the major biological actions of ghrelin are the secretion of growth hormone, the stimulation of appetite and food intake, the regulation of gastric motility and acid secretion and the modulation of the endocrine and exocrine pancreatic functions. Ghrelin is an orexigenic peptide involved in the short-term regulation of appetite and food intake. The plasma ghrelin levels increase before meal and decrease strongly during the postprandial phase. Long-term body weight is also regulated by ghrelin, since it induces adiposity. The purpose of this chapter is to provide updated information on ghrelin, the role of ghrelin in the control of appetite, as well as the potential clinical applications of ghrelin agonists and antagonists in certain physiopathological conditions.

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2

Carine De Vriese, Jason Perret and Christine Delporte

1. DISCOVERY OF GHRELIN

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Growth hormone releasing hormone (GHRH) is known to activate the pituitary secretion of growth hormone, while somatostatin inhibits it. Endorphin-derived peptides were shown to stimulate GH secretion and this led to the development of peptidic and non-peptidic synthetic molecules named growth hormone secretagogues (GHS). Both GHRH and GHS stimulate GH secretion via the cAMP and the inositol triphosphates/calcium pathways, respectively, suggesting they are acting on distinct receptors. In 1996, GHS receptor (GHS-R 1a) was cloned from human pituitary and remained an orphan G-protein coupled receptor (GPCR) until the discovery, in 1999, of its natural ligand, ghrelin [Kojima et al., 1999; Kojima & Kangawa, 2008]. Ghrelin was purified from rat stomach and its structure is unprecedented as this 28 amino acid peptidic hormone contains a unique modification: a n-octanoylation of serine in position 3 [Kojima et al., 1999; Kojima et al., 2001] (figure 1). This modification turned out to be essential for its known biological activity encountered by its binding to the GHS-R 1a receptor.

Figure 1. Human ghrelin gene structure contains 4 exons (boxes) and 3 introns (lines). After transcription, the mRNA is translated into prepro-ghrelin of 117 amino acids. Prepro-ghrelin is finally processed into ghrelin and/or obestatin.

*

Corresponding author: Laboratory of Biological Chemistry and Nutrition, Faculty of Medicine, Université Libre de Bruxelles, Bat G/E, CP 611, 808 route de Lennik, B-1070 Brussels, Belgium. Tel: 32 2 555 62 10; Fax: 32 2 555 62 30; Email: [email protected]

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2. HUMAN GHRELIN GENE STRUCTURE The human ghrelin gene is located on chromosome 3 (3p25-26). Originally, human ghrelin gene was shown to contain a 20 bp non-coding exon, 4 coding exons and 3 introns and encoding a 511 bp mRNA [Kanamoto et al., 2004; Nakai et al., 2004]. Very recently, the human ghrelin gene was shown to contain an additional novel exon (termed exon -1) and a 5‘ extension to exons 0 and 1 [Seim et al., 2007]. Therefore, a revised exon-intron structure proposes that the human ghrelin gene spans 7.2 kb and consists of six rather than five exons [Seim et al., 2007] (figure 1). Mature ghrelin is encoded by exons 1 and 2. Prepro-ghrelin contains 117 amino acids (AA), the first 23 AA represent the signal peptide, followed by 94 AA coding pro-ghrelin [Korbonits et al., 2004]. In 2005, another peptide, called obestatin, was shown to be derived from prepro-ghrelin [Zhang et al., 2005]. The sequence of obestatin starts at the 25th AA downstream of ghrelin and consists of 23 AA (figure 1). Another ghrelin gene-derived mRNA transcript, not coding for ghrelin but that may encode for the C-terminal region of the full-length prepro-ghrelin, was also identified [Seim et al., 2007]. Moreover, several spliced variants of human ghrelin gene were identified. A first group of transcripts include exons 1 to 4, coding for prepro-ghrelin, and varying only in the length of the sequence upstream of exon 1 (the prepro-ghrelin 5‘ untranslated region). Splice variant resulting from an alternative exon 2 splice site include des-Gln14-ghrelin [Hosoda et al., 2000b]. A second group of transcripts contain splice variants that include exon -1 in various combinations with exons downstream of exon 1 (exons 2 to 4) [Seim et al., 2007]. Putative peptides encoded by these transcripts would include the sequence for C-ghrelin (exons -1, 2, 3, 4, including the coding sequence for obestatin as well) [Pemberton et al., 2003; Seim et al., 2007], the obestatin sequence (exons -1, 3, 4) [Seim et al., 2007; Zhang et al., 2005], and a novel Cterminal pro-ghrelin peptide lacking exon 3 (exons -1, 4) [Jeffery et al., 2005; Seim et al., 2007]. Interestingly, this latter transcript has been shown to be upregulated in two cancers, i.e. breast cancer [Jeffery et al., 2005] and prostate cancer [Yeh et al., 2005]. These various variants have been identified in different human tissues and cell lines, strongly suggesting a higher order of complexity of ghrelin gene expression. Indeed, an additional level of complexity may play an increasingly important role delivered by a third group of natural antisense transcripts (transcribed from the anti-sense strand), that were also recently identified [Seim et al., 2007], and subject as well to multiple transcription start sites and splice variants. However, these transcripts, to date do not seem to code for proteins, and may represent a source of non-coding RNAs implicated in gene regulation at the post-transcriptional and/or post-translational level. Taken together, the data published to date on the human ghrelin gene structure strongly suggests that the ghrelin locus is far more complex than previously recognized. Further investigation will be necessary to understand the fine-tuning regulatory mechanisms that may be tissue specific, as well as dependent on physiological requirements. Likewise, it would be important to re-examine the ghrelin locus in order to identify and characterize novel peptides that may derive from it, and maybe other novel transcripts. This will raise challenging questions pertaining to their physiological functions in the light of ghrelin's pleiotropic actions. This in turn will open the way to their implication in various physiopathological conditions.

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3. PREPRO-GHRELIN PROCESSING

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Processing of the 117 AA prepro-ghrelin containing, containing pro-ghrelin (1-94), can lead to the formation of ghrelin 1-28 (in position 24-51 of prepro-ghrelin [Kojima et al., 1999], obestatin 1-23 (in position 76-98 of prepro-ghrelin) [Zhang et al., 2005], a C-terminal peptide of 66 AA (in position 52-117 of prepro-ghrelin) [Bang et al., 2007], and peptides derived from the 66 carboxy-terminal AA of pro-ghrelin (termed C-ghrelin) [Pemberton et al., 2003] (figure 2). Several enzymes responsible for processing the ghrelin precursor have been identified. Knockout mice for prohormone convertase 1/3 (PC 1/3), 2 (PC 2) and 5/6A (PC 5/6A) revealed that PC 1/3, but not PC 2 or PC 5/6A, is involved in the conversion of proghrelin to ghrelin by cleaving at a single Arg residue in the stomach [Zhu et al., 2006] (figure 2). It is worth noting that the ghrelin sequence ends at Pro27 and Arg28, two amino acids corresponding to a processing signal. A cleavage most frequently occurs following Pro27Arg28, and rarely after Pro27, generating respectively ghrelin 1-28 (Kojima et al., 1999) and ghrelin 1-27 [Hosoda et al., 2003]. Cleavage following Pro27 is mostly the result of a carboxypeptidase-B like enzyme [Hosoda et al., 2003]. Either ghrelin 1-28 or ghrelin 1-27 are then subjected to a particular post-translational modification: the acylation of the hydroxyl group of Ser3. The acylation most frequently occurs with an octanoyl group (C8:0), and more rarely with a decanoyl (C10:0) or a decenoyl (C10:1) group [Hosoda et al., 2003]. Acylation of ghrelin can be increased by ingestion of either medium-chain fatty acids or medium chain triacylglycerols [Nishi et al., 2005].

Figure 2. Processing of the prepro-ghrelin precursor. Prepro-ghrelin, composed of 117 amino acids, is processed into pro-ghrelin by the cleavage of the signal peptide by a signal peptidase (SP). In the endoplasmic reticulum, pro-ghrelin is octanoylated by the ghrelin O-acyl transferase (GOAT). Octanoylated pro-ghrelin is then processed into ghrelin and obestatin by prohormone convertase 1/3 (PC 1/3), followed by another prohormone convertase, and an amidase.

Very recently, the enzyme responsible for ghrelin octanoylation was simultaneously identified by two separate research groups as being an orphan membrane-bound O-acyl transferase (MBOAT) and renamed ghrelin O-acyl transferase (GOAT) [Gutierrez et al., 2008; Yang et al., 2008] (figure 2). Both teams based their reasoning on the same observations. Firstly, porcupine, an enzyme sharing structural similarities with MBOAT, is required for the acylation of serine in position 209 with palmitoleic acid and for transport of Wnt3a (member 3 of the wingless-type mouse mammary tumor virus integration site family)

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from the endoplasmic reticulum for secretion [Takada et al., 2006]. Secondly, porcupine was localized in the same cellular compartment through which ghrelin is expected to pass during its processing. These observations led to the hypothesis that an acyl transferase of the MBOAT family could be involved in the acyl modification of ghrelin [Gutierrez et al., 2008; Yang et al., 2008]. Like porcupine, all other MBOATs are believed to transfer only longchain fatty acids of 16-18 carbons. Both teams discovered GOAT using slightly distinct approaches. Gutierrez et al. [Gutierrez et al., 2008] beneficited from the capacity of the human medullary thyroid carcinoma cells to produce ghrelin, allowing them to identify the ghrelin acyl transferase. Indeed, that cell line was used to perform gene-silencing of twelve candidate sequences. The selection was based on their similarity to known acyl transferases sequences, the presence of a human homologue, and the unknown function of the gene. Gene-silencing experiments revealed the knock-down of only one candidate gene encoding an uncharacterized protein containing structural motifs reminiscent of the MBOAT acyl transferase family. The authenticity of the human gene identified was verified using RT-PCR and 5‘ RACE reactions. The predicted protein encoded by the gene was named GOAT. Transient transfections of the GOAT cDNA were performed to assess the octanoylation of ghrelin. Mutation of the MBOAT-conserved histidine residue in position 338 of GOAT abolished the octanoylation of ghrelin. GOAT was also shown to acylate ghrelin with fatty acid ranging from C7 to C12. Yang et al. [Yang et al., 2008] also sought for a cell line capable of octanoylating ghrelin in order to transfect cells with ghrelin cDNA and look at subsequent acylated ghrelin production by Western blot analysis. To confirm the presence of ghrelin in rat insulinoma Ins1 cells, further transfections were performed using mutant forms of ghrelin cDNA encoding mutant forms of prepro-ghrelin with amino acid substitution at or near the arginine in position 28. To determine if any of the sixteen MBOATs, identified as containing 11 catalytic domains bearing conserved sequences, was capable of producing acylated ghrelin, Ins-1 cells were transfected with the corresponding sixteen MBOATs cDNA. Only one MBOAT cDNA led to ghrelin production. Furthermore, mutation of either serine in position 3 of ghrelin or of the MBOAT-conserved histidine residue in position 338 of GOAT abolished ghrelin acylation by GOAT. GOAT appears to be specific for medium chain fatty acids like octanoate. Moreover, [3H]octanoate labeling experiments indicated that ghrelin is octanoylated before it translocates to the Golgi where it is cleaved by prohormone convertase 1/3 to form mature ghrelin. This suggested that GOAT is located in the endoplasmic reticulum. GOAT, sharing structural similarities with members of the MBOAT family of acyl transferases [Chamoun et al., 2001; Hoffmann et al., 2000; Liang et al., 2004], is a highly hydrophobic protein with eight postulated membrane-spanning helices. Sequence conservation of GOAT across vertebrates and its tissue coexpression with ghrelin are consistent with the identification of ghrelin octanoylated forms in vertebrates. The presumed donor for octanoylation is octanoyl-CoA. However, how octanoyl Co-A gets into the endoplasmic reticulum lumen remains unclear. GOAT could possibly bind octanoyl CoA, and due to its hydrophobic nature, and allow transmembrane octanoylation of ghrelin An in vitro biochemical assay for GOAT activity was recently developed using membranes from insect cells expressing mouse GOAT and purified recombinant pro-ghrelin as the acyl acceptor [Yang et al., 2008]. Using that assay, it was shown that GOAT recognizes several amino acids in pro-ghrelin surrounding the octanoylation site on serine-3. Glycine-1,

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serine-3 and phenylalanine-4 represent the crucial residues for the GOAT activity, in consistency with their strict conservation among all vertebrate ghrelins [Kojima & Kangawa, 2008]. A pentapeptide, corresponding to the first five N-terminal amino acids of ghrelin with its C-terminal end amidated, competitively inhibited GOAT activity and was used as a substrate by GOAT. A more efficient inhibition was obtained when the pentapeptide contained an octanoyl group linked to serine-3 by an amide linkage, instead of an ester linkage. A similar pentapeptide, but containing an alanine-3, instead of serine-3, also inhibited GOAT, was not used as a substrate by the enzyme. These data suggest that GOAT is subjected to end-product inhibition [Yang et al., 2008]. Very recently, it was shown that gastric GOAT mRNA levels were similar in fed and 48h-fasted rats, and that exogenous leptin administration to fasted rats markedly increased GOAT mRNA levels [Gonzalez et al., 2008]. These data indicated that during fasting, low leptin levels prevent an increase in GOAT mRNA levels, and that GOAT is a leptin-regulated gene. Long-term chronic malnutrition (21 days) led to an increase in GOAT mRNA levels [Gonzalez et al., 2008] and this could represent the underlying mechanism responsible for increased acylated ghrelin levels in chronic undernutrition, such as anorexia nervosa [Soriano-Guillen et al., 2004]. GOAT knockout mice are therefore a valuable tool to determine the physiological consequences of a specific deficiency in acylated ghrelin. Moreover, GOAT represents a useful target for the development of anti-obesity and/or anti-diabetes drugs [Gualillo et al., 2008]. Much work remains to be done to fully understand how GOAT fits into the control of energy homeostasis.

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4. GHRELIN-RELATED PEPTIDES Ghrelin peptides can be classified into two group based on the length, ghrelin 1-28 and ghrelin 1-27, or into four groups based on the nature of the acyl group on Ser3 (non-acylated, octanoylated, decanoylated, decenoylated). Although the major active form is octanoylated ghrelin 1-28, decanoyl ghrelin 1-28, decenoyl ghrelin 1-28, octanoyl ghrelin 1-27 and decanoyl ghrelin 1-27 were also found in the stomach and in plasma [Hosoda et al., 2003] (figure 3). In the stomach, decanoyl ghrelin 1-28, decanoyl ghrelin 1-27, octanoyl ghrelin 127 and decenoyl ghrelin 1-28 represent respectively only 17%, 8%, 17% and 8% of the biologically active ghrelin. In contrast to rat stomach, human stomach is devoid of des-Gln14 ghrelin [Hosoda et al., 2000b]. It must be noted that the major circulating form of ghrelin is the des-acyl ghrelin, the so called biologically inactive form of ghrelin, at least on GHS-R 1a [Hosoda et al., 2000a]. Besides, in human plasma, C-ghrelin also circulates at higher concentrations than octanoyl ghrelin [Pemberton et al., 2003]. A novel peptide derived from the carboxy-terminal of pro-ghrelin was identified in rat stomach and named obestatin, due to its appetite-suppressing potential [Zhang et al., 2005]. Obestatin is a 23 AA peptide that is amidated, notably due to the presence of C-terminal GlyLys motif following the C-terminal AA of obestatin [Zhang et al., 2005]. During the purification of obestatin from rat stomach, an obestatin truncated peptide was identified as containing the last 13 C-terminal AA of obestatin and named obestatin 11-23 [Zhang et al., 2005].

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Ghrelin was identified in various mammalian species such as human [Kojima et al., 1999], rat [Kojima et al., 1999], mouse [Tanaka et al., 2001] (figure 4). In mammals, the first 10 N-terminal AA are identical and the acylation of Ser3 result principally in an octanoylation. Human ghrelin is identical to rat ghrelin, except for two AA in position 11 and 12. In ovines and bovines, ghrelin is composed of 27 AA, rather than 28, and is devoid of Gln14 similarly to rat des-Gln14-ghrelin.

Figure 3. Ghrelin forms identified from human stomach.

Very recently, ghrelin and des-acyl ghrelin were shown to be phosphorylated by protein kinase C on the Ser in position 18. While ghrelin and des-acyl ghrelin bind to phosphatidylcholine:phosphoserine sucrose-loaded vesicles in a phosphatidylserinedependent manner, this binding capacity was greatly lowered when the peptides were phosphorylated. A possible explanation is the disruption of the amphipathic helix formed by about two third of the C-terminal part of the peptide [Dehlin et al., 2008]. Further

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investigations will be required to determine if phosphorylation can occur in cells under specific conditions, and if so what would be the impact of such phosphorylation on the subcellular localization and function of the peptide.

Figure 4. Amino acid sequence homologies among mammalian ghrelin sequences. Multiple sequence alignment of 40 mammalian ghrelin peptide sequences, available to date in the two public sequence databases sets (Ensembl release 50 and NCBI Nucleotide). Dark gray shading are residues sharing 100% conserved identity (40/40 sequences), light gray shaded residues share at least 80% identity (i.e. identity in at least 32/40 sequences). Note that the amino terminal hepta-peptides is conserved with 100% identity. Every 10 amino acids are indicated by *. Peptide lengths are indicated in the rightmost column.

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5. HUMAN GHRELIN RECEPTOR GENE STRUCTURE The ghrelin receptor, termed GHS-R, belongs to the family of G-protein coupled receptor, characterized by seven transmembrane helix domains [Howard et al., 1996]. GHS-R gene is located on chromosome 3 (3q26.2) and is composed of two exons separated by one intron. Exon 1 codes for the extracellular amino-terminal domain through to the fifth transmembrane helix of the GHSR. Exon 2 codes then for the sixth transmembrane helix through to the carboxy-terminal segment [McKee et al., 1997]. GHS-R has two variants resulting from alternative splicing of its mRNA: GHS-R 1a and GHS-R 1b. GHS-R 1a mRNA, encoded by the two exons and from which the intron is excised by splicing, codes for a protein of 366 AA comprising the seven transmembrane helix domains. GHS-R 1b mRNA is coded only by exon 1 and and followed by the non-excised intron. Thereby, GHS-R 1b codes for a protein of 289 AA comprising only five transmembrane helix domains. The nucleotide sequences are identical for AA 1 to 265 , thereafter GHS-R 1b mRNA nucleotide sequence is distinct from that of GHS-R 1a mRNA as of codon Leu265 and codes only for 24 additional AA using an alternative stop codon [McKee et al., 1997]. Since the coupling of Gprotein coupled receptor with the G-protein involves the third intracellular loop, GHS-R 1b is unable to couple to G-proteins. Though there is no obvious role for such a truncated receptor, it has recently been proposed to act as a dominant negative mutant of GHS-R 1a by heterodimerization [Leung et al., 2007], attenuating the latter's constitutive activity. GHS-R 1b was also detected in PBMCs, in the absence of the functional GHS-R 1a [Mager et al., 2008]. GHS-R 1a is not obviously related to known families of G-protein coupled receptors, although it is often included in a small family of the class A receptors for small polypeptides comprising the motilin receptor (52% homology), neurotensin receptor-1 and neurotensin receptor-2 (33-35% homology), neuromedin receptor-1 and neuromedin receptor-2 (± 30% homology), and the orphan GPR39 (27-32% homology) [McKee et al., 1997; Tan et al., 1998]. Concerning GPR39, it must be cautioned that it was at first described as the receptor for obestatin [Zhang et al., 2005]. Nevertheless, recent controversy over obestatin binding to GPR39 has lead to the conclusion that GPR39 is ultimately not the obestatin receptor [Lauwers et al., 2006; Tremblay et al., 2007]. Likewise, it must be noted that the scavenger receptor CD36, involved in the endocytosis of the pro-atherogenic oxidized low-density lipoproteins, is a pharmacologically and structurally distinct receptor for peptidyl GHSs, but not for ghrelin [Bodart et al., 1999; Bodart et al., 2002].

6. ACTIVATION MECHANISM OF GHRELIN RECEPTOR Binding of GHSs and ghrelin to GHS-R 1a leads to phospholipase C activation. Phospholipase C activation induces the hydrolysis of phosphatidylinositol 4,5-biphosphate and the subsequent formation of diacylglycerol and inositol 1,4,5-trisphosphate. Diacylglycerol activates protein kinase C and inositol 1,4,5-trisphosphate induces a calcium release from the endoplasmic reticulum [Smith et al., 1996]. Des-acyl ghrelin also seems to bind to GHS-R 1a but at very high concentration (micromolar range) [Gauna et al., 2007].

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Neither ghrelin, nor GHSs, bind to GHS-R 1b, suggesting that GHS-R 1b is pharmacologically inactive (Howard et al., 1996). However, when GHS-R 1b is coexpressed with GHS-R 1a in HEK293 cells, the signal transduction of GHS-R 1a was decreased, suggesting that GHS-R 1b could form an heterodimer with GHS-R 1a [Chan & Cheng, 2004]. GHS-R 1a possesses constitutive activity [Holst et al., 2003] that might be mandatory for proper growth and development of the human body [Holst & Schwartz, 2006]. In HEK293 cells, GHS-R 1a possesses constitutive activity that is about 50% of the maximal agonistinduced activity [Holst et al., 2003; Holst et al., 2006]. The molecular basis for the constitutive activity appears to be related to three aromatic residues located in the sixth and seventh transmembrane helix domains that would promote the formation of a hydrophobic core between helices 6 and 7. This would ensure proper docking of the extracellular end of the seventh transmembrane helix domain into the sixth transmembrane domain, mimicking agonist activation and stabilizing the receptor in its active conformation [Holst et al., 2004]. However, a naturally occurring non-conservative mutation, A204E, occurring surprisingly in the second extracellular loope, that eliminates the constitutive activity without impairing stimulation by ghrelin [Holliday et al., 2007; Pantel et al., 2006].

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7. GENETIC POLYMORPHISM OF GHRELIN AND GHRELIN RECEPTOR Interestingly, both ghrelin and its receptor (GHSR) genes are located on chromosome 3, and the regions have been linked to obesity [Kissebah et al., 2000; Yeh et al., 2005]. A large number of polymorphisms have been identified in the ghrelin gene, not counting the transcript and splice variants described above. Several are found in the coding region of ghrelin, however a large number are in non-coding regions or in prepro-ghrelin but outside the ghrelin coding region. Polymorphisms of both ghrelin and its receptor GHSR 1a have been studied in a wide series of disorders and pathologies, such as in obesity [Bing et al., 2005; Dardennes et al., 2007; Hinney et al., 2002; Korbonits et al., 2002; Larsen et al., 2005; Martin et al., 2008; Miraglia et al., 2004; Ukkola et al., 2001; Vivenza et al., 2004; Wang et al., 2004], in particular the Leu72Met polymorphism in prepro-ghrelin was associated with early onset of obesity [Korbonits et al., 2002; Miraglia et al., 2004; Ukkola et al., 2001; Ukkola et al., 2002]. Another polymorphism, 3056T>C single nucleotide polymorphism (SNP), has been reported to be correlated, in Japanese women, to higher body mass index, fat mass and eating disorders [Ando et al., 2007]. However, other studies yielded conflicting results [Bing et al., 2005; Hinney et al., 2002; Jo et al., 2005; Larsen et al., 2005]. Another example of conflicting results, with respect to weight, is the Arg51Gln allele, for which a positive association was found [Ukkola et al., 2001], but no correlation was found in another study [Hinney et al., 2002]. These authors also found that a frameshift mutation leading to ghrelin haploinsufficiency was compatible with normal body weight. GH secretion was also studied in relation to short stature (height), as measured by IGF-1 and IGFBP-3 hepatic secretion in response to GH. A recent study showed lowered circulating levels of IGF-1 in ghrelin rs3755777 allele bearing subjects [Dossus et al., 2008], whereas decreased circulating levels of IGFBP-3 were correlated (though borderline) with the ghrelin rs2075356 SNP. Other studies, however, found no correlation [Ukkola et al., 2002; Vartiainen et al., 2004; Vivenza

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et al., 2004]. On the other hand, 5 of the 15 alleles studied [Dossus et al., 2008] showed a correlation with height, whereas in a smaller study no significant association with genotype or haplotype were found with height, weight or body mass index (BMI) [Garcia et al., 2008]. Likewise, a study of the Leu72Met, Gln90Leu and Arg51Gln proposed that ghrelin levels rather than ghrelin/obestatin polymorphism would play a role in GH deficiency and thus height [Zou et al., 2008]. In contrast, the GHS-R 1a naturally occurring A204 mutation, leads to a loss of constitutive, activity, that decreases cell surface expression without impairing stimulation by ghrelin, and segregated with short stature in two unrelated families [Pantel et al., 2006]. A correlation between Leu72Met and bing eating disorder was found [Monteleone et al., 2007], whereas no association of Leu72Met and Arg-51-Gln could be found with anorexia nervosa or bulimia nervosa [Monteleone et al., 2006]. In contrast, the Leu72Met/Gln90Leu haplotype had an excess transmission in patients with anorexia nervosa [Dardennes et al., 2007]. These authors invoke in the former study a lack of comparison between the clinical subtypes studied. However, they also argue, that ethnic and international variations in ghrelin gene polymorphism must be taken into account [Cellini et al., 2006; Miyasaka et al., 2006; Ukkola et al., 2002; Zou et al., 2008]. Though, there is controvery as to the effects of ghrelin polymorphic variants on different disorders and pathologies, one must take into account the diversity of the subject panels used in the various studies, and the series of polymorphism investigated. The Leu72Met, as well other SNPs have been studied in relation to other disorders. The Leu72Met showed correlations with metabolic syndrome parameters, such as high-density-lipoproteins (HDL), triglycerides levels, blood pressure and increased risk for type 2 diabetes. However, in one report the levels of HDL/cholesterol were increased when compared to the Leu72Leu allele [Hubacek et al., 2007], whereas in another report it decreased in a study of older Amish [Steinle et al., 2005]. Likewise, the risk factor was positively associated to ghrelin gene polymorphism in a Finnish study [Mager et al., 2006], and was not in a Korean study [Choi et al., 2006]. Another study of 5 SNPs in exon 1, in introns and in the 3‘ untranslated region did not correlate with body fat percentage or serum lipid profiles [Martin et al., 2008]. A GHS-R 1a polymorphism, rs2232165, has also been shown to be associated with alcohol-abuse [Landgren et al., 2008]. Finally, ghrelin SNPs have been associated with various cancers, such as breast cancer [Dossus et al., 2008; Jeffery et al., 2005] and prostate cancer [Yeh et al., 2005]. In the light of an increasing body of data, displaying conflicting results, in the various areas investigated, a word of caution must be made regarding the polymorphisms in the prepro-ghrelin mRNA, outside of the ghrelin coding-region, e.g. Leu72Met. Indeed, these ―mutated‖ sites may either affect proper processing of prepro-ghrelin, thereby potentially disrupting trafficking, posttranslational modification and secretion. However, most investigators did not see variations in circulating plasma levels. Though this may not be the best parameter, the acyl form is rapidly degraded in plasma and therefore plasma levels do not reflect local concentrations of the octanoylated form [De Vriese et al., 2004]. Moreover, the recent discovery of novel peptides stemming from the prepro-ghrelin RNA (as discussed above), containing polymorphic differences studied previously, might have an impact on the cellular processing and physiological effects of these peptides, independently of ghrelin itself. Consequently, the study of prepro-ghrelin will link observed effects/correlations to ghrelin in a misleading manner; as the studies are conducted at the mRNA level and not at the protein(s) level. Clearly, in view of ghrelin‘s pleiotropic effects and the high level of complexity, in the ghrelin gene in terms of transcript variants, alternative splice variants, polymorphism, and

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multiple peptide products besides ghrelin, will require much more investigation and revisiting of previous studied areas. Furthermore, the polymorphic sites, thus far, described may affect the reverse strand transcript processing as well. Should the hypothesis that the anti-sense transcript harbor non-coding regulatory RNAs [Seim et al., 2007], such as microRNA, then such polymorphisms might alter considerably these regulatory molecules as well as potential target sequences on the sense strand. We speculate that these new findings will certainly open up future fascinating avenues of investigation in ghrelin gene expression and regulation.

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8. TISSUE DISTRIBUTION OF GHRELIN In the digestive system, ghrelin is predominantly synthesized in the stomach [Ariyasu et al., 2001; Kojima et al., 1999]. Five endocrine cell types have been identified in the gastric mucosa: enterochromaffin cells (EC), enterochromaffin-like cells (ECL), D cells, G cells and X/A like cells which respectively secrete serotonin, histamine, somatostatin, gastrin, GABA and ghrelin. Rat oxyntic cells display 60-70% of ECL cells, 20% of X/A-like cells, 2.5% of D-cells and 0-2% of EC and G cells. Human oxyntic endocrine cells display 30% of ECL cells, 20% of X/A-like cells, 22% of D-cells and 7% of EC and G cells [Simonsson et al., 1988; Solcia et al., 2000]. X/A like cells are gastric endocrine cells located in the fundus [Date et al., 2000b; Rindi et al., 2002]. They are round to ovoid cells, containing compact and dense secretory granules, located next to the capillary lumen, indicating ghrelin is secreted in an endocrine fashion into the plasma [Date et al., 2000b]. Immunoreactive ghrelin cells have also been located in the duodenum, jejunum, ileum and colon [Date et al., 2000b; Hosoda et al., 2000a; Sakata et al., 2002]. In the intestine, ghrelin concentration progressively decreases from the duodenum to the colon [Hosoda et al., 2000a]. Circulating ghrelin arises in majority from the gastric mucosa and the intestine [Ariyasu et al., 2001; Krsek et al., 2002]. In the endocrine pancreas, ghrelin-secreting cells have been colocalized with either glucagon in cells [Date et al., 2002b; Kageyama et al., 2005], or insulin in ß-cells [Volante et al., 2002], or in a new cell type called [Prado et al., 2004; Wierup et al., 2002; Wierup & Sundler, 2005]. In the exocrine pancreas, ghrelin has been located to acinar cells [Lai et al., 2007]. In the central nervous system, ghrelin is found in low amounts [Hosoda et al., 2000a]. However, neurons producing ghrelin have been identified in the arcuate nucleus of the hypothalamus, a region involved in the regulation of food intake [Kojima et al., 1999; Lu et al., 2002]. Moreover, ghrelin has also been identified in a particular area in the hypothalamus. By sending their efferent fibers, ghrelin-containing neurons could stimulate the release of peptides from neurons containing neuropeptide Y (NPY) and the agouti-related protein (AGRP), orexins, pro-opiomelanocortin (POMC), and cocaïn- and amphetamine-regulated transcript (CART) [Cowley et al., 2003]. Pituitary also contains ghrelin [Korbonits et al., 2001b; Korbonits et al., 2001a]. In vivo studies indicated that ghrelin stimulates GH secretion, suggesting that somatotropic cells are target cells for ghrelin [Date et al., 2000a; Takaya et al., 2000]. Furthermore, in the rat, ghrelin was found in cells secreting prolactin, GH, and thyroid stimulating hormone [Caminos et al., 2003]. Ghrelin is also expressed in other tissues such as in kidneys, adrenal glands, thyroid, breast, ovary, placenta, testis, prostate, liver, gallbladder, lung, skeletal muscle, myocardium, skin [Ghelardoni et al., 2006; Gnanapavan et al., 2002].

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Studies related to tissue expression of obestatin remain limited. Obestatin expression was reported in the stomach, duodenum, jejunum, colon, myenteric plexus, pancreas, spleen, testis, cerebral cortex [Chanoine et al., 2006; Dun et al., 2006; Zhang et al., 2005; Zhao et al., 2008]. In the stomach, most of obestatin-producing cells are distributed in the basal part of the oxyntic mucosa, and are with prepro-ghrelin-producing cells more numerous than ghrelinproducing cells [Zhao et al., 2008]. In the pancreas, obestatin is present in the periphery of the islets, with a distribution distinct from that of -cells, ß-cells, and -cells [Zhao et al., 2008].

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9. GHRELIN IN CIRCULATION Following surgical gastric mucosa removal, circulating ghrelin concentration is drastically reduced by about 80% in rat [Dornonville de la Cour et al., 2001] and human [Ariyasu et al., 2001; Jeon et al., 2004]. Human plasma ghrelin-immunoreactivity consists of more than 90% of des-acyl ghrelin [Patterson et al., 2005]. C-ghrelin also circulates at higher concentrations than octanoyl ghrelin in human plasma [Pemberton et al., 2003]. It is presently not yet well understood if both ghrelin and des-acyl ghrelin, which are present in the stomach, are both secreted into the bloodstream via the same or differently regulated pathway(s). In rat stomach, ghrelin is degraded by deacylation, as well as by N-terminal proteolysis [De Vriese et al., 2004; Shanado et al., 2004], and lysophospholipase I was identified as a ghrelin deacylation enzyme [Shanado et al., 2004]. Several mechanisms could account for the large presence of des-acyl ghrelin in the circulation: shorter half-life of ghrelin compared to desacyl ghrelin [Akamizu et al., 2005] and plasma ghrelin deacylation [De Vriese et al., 2004; Hosoda et al., 2004]. In serum, ghrelin desoctanoylation is achieved in human by butyrylcholinesterase and other esterase(s), such as platelet-activating factor acetylhydrolase, and in rat by carboxylesterase [De Vriese et al., 2004; De Vriese et al., 2007]. Although paraoxonase was suggested to also participate to ghrelin deacylation [Beaumont et al., 2003], this hypothesis was not confirmed by us due to the lack of effect of EDTA on ghrelin deacylation in human serum and the negative correlation between des-acyl ghrelin and paraoxonase activity [De Vriese et al., 2004]. Due to ghrelin degradation by serum, it is difficult to accurately determine the ghrelin level and consequently its physiological and pathophysiological roles. Therefore, we suggested that addition of inhibitors of esterases and proteases to blood collected samples would be critical to ensure ghrelin stability. It is interesting to note that butyrylcholinesterase knockout mice fed with a normal standard 5% fat diet had normal body weight, while mice fed with high-fat diet (11% fat) became obese. Since the obesity could not be explained by increased ghrelin, caloric intake, or decreased exercise, it is hypothesized that butyrylcholinesterase plays a role in fat utilization [Li et al., 2008]. While des-acyl ghrelin mostly circulates as a free peptide, the majority of circulating acyl ghrelin is bound to larger molecules. In particular, ghrelin was found to bind to lipoproteins [Beaumont et al., 2003; De Vriese et al., 2007]. The presence of the acyl group is necessary for ghrelin interaction with triglyceride-rich lipoproteins and low-density lipoprotein but not high-density lipoproteins and very high-density lipoproteins. Ghrelin interacts via its N- and C-terminal parts with high-density lipoproteins and very high-density lipoproteins. These data suggest that, whereas triglyceride-rich lipoproteins mostly transport acylated ghrelin, high-

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density lipoproteins and very high-density lipoproteins transport both ghrelin and des-acyl ghrelin [De Vriese et al., 2007].

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10. GHRELIN- AND GHRELIN RECEPTOR-NULL MICE PHENOTYPES The phenotype of ghrelin knockout mice is indistinguishable from that of wild-type mice. Indeed, no differences were noticed concerning the size, growth rate, body composition, food intake, reproduction, bone density, activity, development, organs weight, tissular pathology [De Smet et al., 2006; Sun et al., 2003; Wortley et al., 2004]. Food intake of ghrelin knockout mice was similar to wild-type mice in response to starvation and to ghrelin injection. Though, in old ghrelin knockout mice interruption of the normal light/dark cycle triggers additional food intake [De Smet et al., 2006]. Pre- and post- prandial concentrations of glucose, insulin, leptin and GH were similar. Ghrelin knockout mice fed for six weeks with a high fat diet displayed a decrease in the respiratory quotient and in the fat mass, independently of any body weight change [Wortley et al., 2004]. However, male ghrelin knockout mice submitted to a continuous high-fat diet three weeks after weaning (at approximately six weeks of age) are protected from the rapid weight gain occurring in wild-type mice [Wortley et al., 2005]. Very recently, it was shown that congenic adult ghrelin knockout mice submitted to either a positive (high-fat diet) or negative (caloric restriction) energy balance displayed similar body weight as wild-type littermates [Sun et al., 2008]. These contradictory data could be explained by differences in the mouse genetic backgrounds and/or the moment at which the high-fat diet was given to the animals. Further studies will be necessary to define the role of ghrelin in preventing or not preventing diet-induced obesity or weight gain after weight loss. Ghrelin could modulate the type of metabolic substrate that is used preferentially to maintain energy balance, particularly under a high fat diet. These data are in agreement with the observed decreased use of fat in response to ghrelin administration in adult rats [Tschop et al., 2000]. Furthermore, the lack of modification body weight in ghrelin-null mice as in NPYor AGRP-null mice, and in NPY- and AGRP-null mice, strongly suggest the existence of compensatory mechanisms [Erickson et al., 1996; Herzog, 2003]. GHS-R knockout mice displayed a slightly smaller size, without any modification in appetite, food intake and body composition. Their ghrelin, insulin and leptin levels in response to starvation were similar to wild-type mice. In response to ghrelin injection, GHSR-null mice do not release GH and do not increase their food intake, indicating that these effects are mediated by the GHS-R [Sun et al., 2004]. A similar phenotype has been observed in transgenic rats expressing an antisense GHS-R mRNA, thereby attenuating GHS-R protein expression in the arcuate nucleus, also indicating that the GHS-R was involved in the regulation of GH secretion and food intake [Shuto et al., 2002]. More recently, it was shown that GHS-R-null mice eat less food, metabolize more fat, become less adipose, and are more insulin-sensitive [Zigman et al., 2005]. These latter data are consistent with the fact that ghrelin-null mice resist weight gain induced by early exposure to high fat diets [Wortley et al., 2005], but not with the fact that congenic adult knockout mice for GHS-R are not resisting diet-induced obesity or weight gain after weight loss [Sun et al., 2008]. Interestingly, when fed with a standard chow diet, GHS-R and ghrelin double knockout mice display decreased

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body weight, increased energy expenditure, and increased motor activity [Pfluger et al., 2008]. Both ghrelin and GHS-R knockout mice submitted to caloric restriction displayed lower blood glucose levels, suggesting that the primary function of ghrelin in adult mice is to modulate glucose sensing and insulin sensitivity [Sun et al., 2008]. This hypothesis was supported by the fact that GHS-R knockout mice fed with high-fat diet had several fold greater insulin sensitivity, no hepatic steatosis, and lower total cholesterol [Longo et al., 2008].

11. PHYSIOLOGICAL FUNCTIONS OF GHRELIN IN FEEDING

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Appetite and Food Intake The control of food intake is under the control of complex physiological mechanisms. Food intake is regulated by the hypothalamus but also directly influenced by gastrointestinal peptides, which respond to nutritional status and body composition. To defend against starvation, the organism replies in an integrative fashion using central brain centers, gastrointestinal peptides and adipose-derived signals [Baynes et al., 2006]. In response to food intake, the concentrations of plasma glucose, free fatty acids and other nutrients increase, leading to hormones release. These hormones act on the tractus solitary nucleus, and on the arcuate nucleus of the hypothalamus to regulate the appetite and the energy metabolism at short and long terms. The arcuate nucleus of the hypothalamus contains two neuronal populations involved in the control of appetite: neurons synthesizing the neuropeptide Y (NPY) and agouti-related protein (AGRP) (their activation stimulates appetite) and neurons containing pro-opiomelanocortin (POMC), melanocortin ( -MSH) and cocaine- and amphetamine-regulated transcript (CART) (their activation inhibits appetite) [Ramos et al., 2005]. Intracerebroventricular, intravenous, or subcutaneous administration of ghrelin to rats leads to stimulation of food intake and decrease of energy expenditure, accounting for body weight increase [Kamegai et al., 2001; Nakazato et al., 2001; Shintani et al., 2001; Tschop et al., 2000; Wren et al., 2001]. Intravenous ghrelin administration of ghrelin in humans also increases appetite and stimulates food intake [Wren et al., 2001]. During fasting, before the onset of the meal, plasma ghrelin levels increase. After feeding, plasma ghrelin levels decrease strongly after 30 minutes [Cummings et al., 2001; Tschop et al., 2001]. In fasting subjects, ghrelin levels display a circadian pattern similar to that described in people eating three meals per day [Natalucci et al., 2005]. The preprandial increase and the postprandial decrease of plasma ghrelin levels strongly suggest that ghrelin might serve as a signal for meal initiation. Recently it has been demonstrated that the timing of ghrelin peaks is related to habitual meal patterns and may rise in anticipation of eating rather than eliciting feeding [Frecka & Mattes, 2008]. In contrast to ghrelin, most of the orexigenic peptides as NPY, AGRP, orexins, melaninconcentrating hormone (MCH) and galanin stimulate food intake when centrally administrated but not when peripherally administrated. Ghrelin is the only circulating hormone that stimulates appetite after systemic administration (table 1).

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Among the anorexigenic peptides, several are synthesized in the hypothalamus, such as α-MSH, cocaine-and amphetamine-regulated transcript (CART), or corticotrophin-releasing hormone (CRH). Others are synthesized in endocrine cells of the gastrointestinal tractus, such as cholecystokinin (CCK), gastrin-related peptide (GRP), glucagon-like peptides (GLP-1 and GLP-2), pancreatic polypeptide (PP) and peptide YY (PYY). Leptin is synthesized in adipose tissue (table 1). Table 1. Orexigenic and anorexigenic peptides Orexigenic peptides

Anorexigenic peptides

Ghrelin Neuropeptide Y (NPY)

Melanocortin ( -MSH) Cocaïne- and amphetamine-regulated transcript (CART) Corticotropin-releasing hormone (CRH) Cholecystokin (CCK)

Agouti-related protein (AGRP) Melanin-concentrating hormone (MCH) Orexin A Orexin B Galanin

Gastrin-related peptide (GRP) Glucagon-like peptide 1 (GLP-1) Glucagon-like peptide 1 (GLP-2) Pancreatic polypeptide (PP) Peptide YY (PYY) Leptin

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Mechanisms of Appetite Stimulation and Food Intake Control Neurons expressing ghrelin have been identified in the arcuate nucleus of the hypothalamus, and in a previously uncharacterized group of neurons adjacent to the third ventricle between the dorsal, ventral, paraventricular, and arcuate hypothalamic nuclei. These neurons send efferents onto neurons producing NPY, AGRP, POMC, and CRH [Cowley et al., 2003]. Ghrelin stimulates appetite and food intake through two different pathways:

1. Central Pathway Ghrelin stimulates the activity of NPY/AGRP neurons [Cowley et al., 2003]. In rats, intracerebroventricular injection of ghrelin induces overexpression of NPY and AGRP mRNAs [Kamegai et al., 2001]. Inhibition of endogenous NPY and AGRP by anti-NPY and anti-AGRP antibodies, and by antagonists for Y1 and Y5 receptors abolished ghrelin-induced feeding [Nakazato et al., 2001]. Similarly, in NPY or AGRP null-mice, ghrelin-induced feeding is weakly attenuated, but completely abolished in mice lacking both NPY and AGRP [Chen et al., 2004]. Ablation of the NPY/AGRP neurons in mice completely suppress the feeding response to ghrelin [Luquet et al., 2007]. In rats, peripheral injection of ghrelin also activates the dorsomedial hypothalamic nucleus, which is innervated by projections from other brain areas like NPY/AGRP fibers arising from the arcuate nucleus [Kobelt et al., 2008]. In NPY neurons, ghrelin interacts with the GHS-R and increases intracellular calcium via mechanisms depending on phospholipase C and adenylate cyclase-protein kinase A pathways [Kohno et al., 2007; Kohno et al., 2008]. In humans, ghrelin increases circulating NPY levels [Coiro et al., 2006]. All these data indicate that ghrelin activates hypothalamic

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NPY/AGRP neurons, stimulating the production of NPY and AGRP and therefore increasing food intake. Intracerebroventricular administration of ghrelin activates not only the ARC but also the paraventricular nucleus and the lateral hypothalamus, including in orexin neurons [Scott et al., 2007]. Ghrelin activates in vitro neurons expressing orexins (hypothalamic orexigenic neuropeptides) [Yamanaka et al., 2003]. Appetite stimulation induced by ghrelin is inhibited in orexin-null mice and attenuated in mice pretreated with an anti-orexin antibody [Toshinai et al., 2003]. Peripheral ghrelin increases noradrenaline in the ARC and loss of neurons expressing dopamine β-hydroxylase abolishes ghrelin-induced feeding, suggesting that ghrelin stimulates food intake at least in part through the noradrenergic pathway [Date et al., 2006]. Ghrelin also inhibits POMC neurons, preventing the release of the anorexigenic peptide α-MSH [Riediger et al., 2003]. CART inhibits food intake and is expressed by both vagal afferent and hypothalamic neurons. Ghrelin administration decreases CART expression in rat vagal afferents neurons [de Lartigue et al., 2007] while peripheral ghrelin blockade using a specific anti-ghrelin antibody increases the expression of CART in the hypothalamic paraventricular nucleus [Solomon et al., 2005]. Although GHS-R mRNA is expressed in the tuberomammilary nucleus, ghrelin does not affect histamine release, and increases food intake in histamine H(1)-receptor knock-out mice. Thus, ghrelin expresses its action in a histamine-independent manner [Ishizuka et al., 2006].

2. Vagal Pathway Ghrelin may also stimulate appetite via the vagus nerve. Detection of the ghrelin receptor in afferent neurons of the rat and human nodose ganglion suggests that the vagus nerve may transmit ghrelin signal from the stomach to the brain [Burdyga et al., 2006; Sakata et al., 2003]. In rats, blockade of the vagal afferent pathway, by vagotomy or perivagal application of an afferent neurotoxin, suppress ghrelin-induced feeding [Date et al., 2002a]. In the same way, patients with vagotomy and oesophageal or gastric surgery are insensitive to the appetite stimulatory effect of ghrelin [le Roux et al., 2005; Takeno et al., 2004]. Thus, through the activation of GHS-R on vagal afferent to the stomach, the signal induced by ghrelin may reach the nucleus of tractus solitarius, which communicates with the hypothalamus to increase food intake. However, intraperitoneal injection of ghrelin stimulates eating in rats with subdiaphragmatic vagal deafferentation, suggesting that the ghrelin signal does not involve vagal afferents [Arnold et al., 2006].

Regulation of Energy Homeostasis In addition to its role in short-term regulation of food intake, ghrelin may also play a role in long-term body-weight regulation. Plasma ghrelin levels are negatively correlated with BMI. Indeed, plasma ghrelin level is increased in anorexia nervosa and cachexia, and decreased in obesity. Moreover, ghrelin levels fluctuate in a compensatory manner to body weight variations [Soriano-Guillen et al., 2004]. Ghrelin levels decrease with weight gain resulting from overfeeding [Williams et al., 2006], pregnancy [Palik et al., 2007], olanzapine treatment [Hosojima et al., 2006], or high fat

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diet [Otukonyong et al., 2005]. Conversely, weight loss induces an increase of ghrelin levels. This effect is observed with weight loss resulting from food restriction [Purnell et al., 2007], long-term chronic exercise but not acute exercise [Kraemer & Castracane, 2007], cachectic states induced by anorexia nervosa [Soriano-Guillen et al., 2004], severe congestive heart failure [Nagaya et al., 2001], lung cancer [Shimizu et al., 2003], breast and colon cancers [Wolf et al., 2006]. However, data on ghrelin levels after weight loss induced by gastric bypass surgery are controversial. Some studies found a decrease [Chan et al., 2006; Cummings et al., 2002b; Fruhbeck et al., 2004; Korner et al., 2006], no change [Couce et al., 2006; Mancini et al., 2006; Stenstrom et al., 2006] or an increase of ghrelin secretion [Haider et al., 2007; Mingrone et al., 2006; Stratis et al., 2006]. In vivo, chronic ghrelin administration induces adiposity [Tschop et al., 2000; Tsubone et al., 2005]. Ghrelin increases body weight not only by stimulating food intake, but also by reducing energy expenditure, decreasing utilization of fat and increasing utilization of carbohydrates [Wortley et al., 2004]. Ghrelin may thus influence adipocyte metabolism. In vitro, ghrelin stimulates differentiation of preadipocytes [Thompson et al., 2004], inhibits adipocyte apoptosis [Kim et al., 2004] and antagonizes lipolysis [Muccioli et al., 2004]. Fat may be directed to either oxidation in skeletal muscle or brown adipose tissue, or to triglyceride storage in white adipose tissue. Chronic central infusion of ghrelin inhibits lipid oxidation and increases lipogenesis and triglyceride uptake in white adipocytes. An increase of the respiratory quotient indicates the decreased use of lipids for the generation of energy [Theander-Carrillo et al., 2006]. Ghrelin has also been shown to shift food preference towards diets high in fat [Shimbara et al., 2004]. Finally, ghrelin improves also lean body mass retention [Deboer et al., 2007]. In elderly subjects and after diet-induced weight loss, ghrelin levels increase with reduction of fat-free mass, specially skeletal muscle mass, but not with changes in fat mass [Purnell et al., 2007]. Recent data strongly support that ghrelin and desacyl ghrelin modulate directly and positively adipogenesis and adipocyte function in rats, suggesting an important role for maintaining homeostasis [Giovambattista et al., 2008]. Ghrelin-null mice suggest a physiological role for ghrelin in energy homeostasis. The phenotype of ghrelin-null mice is similar to wild-type mice in terms of size, growth rate, food intake, body composition, reproduction, gross behavior, and tissue pathology [Sun et al., 2003]. However, young ghrelin-null mice are protected from the weight gain induced by chronic exposure to a high-fat diet. These mice have lower adiposity, higher energy expenditure and locomotor activity. This suggests that ghrelin plays a role in excess dietary fat storage [Wortley et al., 2005; Wortley et al., 2004]. In patients with Prader-Willi syndrome (PWS), a genetic disorder characterized by mental retardation and hyperphagia leading to severe obesity, plasma ghrelin levels are higher than in healthy subjects and do not decrease after a meal [Cummings et al., 2002a; DelParigi et al., 2002]. Other studies showed that ghrelin levels decreased postprandially in adult patients with PWS, but to a lesser extent than in obese and lean subjects [Gimenez-Palop et al., 2007; Paik et al., 2007]. This lesser postprandial ghrelin suppression may be due to a blunted postprandial response of PYY, an anorexigenic peptide that decreases postprandial ghrelin levels. The low PYY levels could partially explain the high ghrelin levels observed in PWS [Gimenez-Palop et al., 2007]. Interestingly, children (5 years of age and younger) with PWS have normal ghrelin levels. Since these children have not yet developed hyperphagia or excessive obesity, it suggests that ghrelin levels increase with the onset of hyperphagia [Erdie-Lalena et al., 2006; Haqq et al., 2008]. In opposition with these data, Fiegerlova et al.,

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showed that plasma ghrelin levels in children with PWS were elevated at any age, including the first years of life, thus preceding the development of obesity [Feigerlova et al., 2008]. Thus, ghrelin may be responsible, at least partially, for the insatiable appetite and the obesity of these patients.

Relationships between Ghrelin and Obestatin

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As opposed to ghrelin, which increases food intake and body weight gain, Zhan et al. reported that intraperitoneal or intracerebroventricular injection of obestatin to mice decreased food intake and body weight gain [Zhang et al., 2005]. The initial observation that obestatin suppresses food intake in a time-dependent and dose-dependent manner ([Zhang et al., 2005] was reproduced in few studies ([Bresciani et al., 2006; Carlini et al., 2007; Green et al., 2007; Sibilia et al., 2006], but not by the majority of the studies carried out on rodents [Gourcerol et al., 2006; Gourcerol et al., 2007; Holst et al., 2007; Moechars et al., 2006; Nogueiras et al., 2007; Samson et al., 2007; Tremblay et al., 2007; Yamamoto et al., 2007; Zizzari et al., 2007]. This issue in reproducing the effects of obestatin has been partially clarified by the existence of a U-shaped dose-response relationship between intraperitoneal administration of obestatin and suppression of food intake and body weight gain in rodent [Lagaud et al., 2007]. The possible effect of obestatin on food intake might be secondary to an initial action in inhibiting thirst [Samson et al., 2007]. However, if obestatin only minimally affects food intake, obestatin does not seem to modify energy metabolism in longterm administration to rats [Sibilia et al., 2006]. In human, underweight anorectic and normal weight patients are characterized by higher plasma obestatin levels as well as an increased ghrelin to obestatin ratio, compared to obese patients. This suggests that obestatin might play a role in body weight regulation in these pathologies [Monteleone et al., 2008; Nakahara et al., 2008; Zamrazilova et al., 2008].

Relationships between Ghrelin and Leptin Oppositely to ghrelin, leptin, a protein mainly produced by the adipose tissue, decreases food intake and increases energy expenditure to maintain the body fat stores. Fasting increases plasma ghrelin levels and decreases plasma leptin levels. Ghrelin expression in stomach cells, and plasma ghrelin levels are higher in leptin-null mice, the so called Ob/Ob mice which are hyperphagic and obese, than in healthy mice. However, ablation of ghrelin in Ob/Ob mice does not improve the obese phenotype, suggesting that the Ob/Ob phenotype is not a consequence of high ghrelin plasma levels [Sun et al., 2006]. After leptin administration, ghrelin concentration and food intake decrease, and energy expenditure increases [Nogueiras et al., 2008; Shintani et al., 2001]. Ghrelin and leptin have thus opposite effects on food intake. Leptin activates POMC neurons, stimulating release of anorexigenic peptides α-MSH and CART, and inhibits NPY/AGRP neurons, preventing release of orexigenic peptides NPY and AGRP [Cowley et al., 2001]. Moreover, inhibition of NPY/AGRP neurons induced by leptin prevents γ-aminobutyric acid (GABA) release, leading to activation of POMC neurons. Oppositely, ghrelin activates NPY neurons and increases GABA release, leading to POMC neurons inhibition [Cowley et al., 2003; Nogueiras et al.,

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2008]. By activating NPY neurons, ghrelin increases intracellular calcium via mechanisms dependent on both the adenylate cyclase and phospholipase C (PLC) pathways. Leptin inhibits intracellular calcium increase induced by ghrelin via phosphatidylinositol 3-kinase(PI3K) and phosphodiesterase 3- (PDE3) mediated pathways [Kohno et al., 2007]. Therefore, leptin acts on hypothalamic neurons by inhibiting the effects of ghrelin. Finally, inverse variations of ghrelin and leptin levels are clearly critical for energy homeostasis regulation.

12. OTHER PHYSIOLOGICAL FUNCTIONS OF GHRELIN

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The pleiotropic physiological functions of ghrelin are summarized in figure 5.

Figure 5. Pleiotropic biological functions of ghrelin. Major biological actions are summarized. GH: growth hormone; ACTH: adrenocorticotrophic hormone; PRL: prolactin.

Growth-Hormone Releasing Activity Ghrelin strongly and dose-dependently stimulates growth hormone (GH) secretion, both in vivo and in vitro, in humans and animals by acting on GHS-R 1a present on pituitary somatotropic cells [Date et al., 2000a; Hataya et al., 2001; Malagon et al., 2003; Takaya et al., 2000]. To induce GH secretion from somatotropic cells, ghrelin activates the cGMP signal tranduction pathway but also requires activation of the nitric oxide synthase pathway [Rodriguez-Pacheco et al., 2008]. Combined administration of ghrelin and GH-releasing hormone (GHRH) displays synergistic effects, rather than additive effects, on GH release.

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Ghrelin action on GH release also seems to be mediated by the hypothalamus as patients presenting organic lesions in the hypothalamus region are still able to release GH in response to ghrelin [Popovic et al., 2003]. Apart from GH release, ghrelin stimulates adrenocorticotrophic hormone (ACTH), cortisol and prolactin (PRL) release [[Lengyel], 2006]. Des-acyl ghrelin is unable to stimulate GH secretion under physiological conditions, as it cannot bind to GHR-R. However, over-expression of des-acyl ghrelin in transgenic animals results in a small phenotype, maybe by modulation the GH-insulin growth factor 1 axis [Ariyasu et al., 2005]. Most studies have so far been unable to demonstrate that obestatin affects GH secretion in rats [Bresciani et al., 2006; Nogueiras et al., 2007; Samson et al., 2007; Yamamoto et al., 2007; Zhang et al., 2005]. However, obestatin might inhibit ghrelin action on GH secretion under certain conditions, but this remains to be confirmed [Zizzari et al., 2007].

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Gastrointestinal Functions Ghrelin modulates gastric acid secretion. In anesthetized rats, intravenous administration of ghrelin dose-dependently increases gastric acid secretion [Asakawa et al., 2001; Masuda et al., 2000]. This effect is abolished by vagotomy and by preliminary administration of atropine, suggesting that ghrelin might act through the vagus nerve [Masuda et al., 2000]. The intracerebroventricular administration of ghrelin in anesthesized rats also stimulates gastric acid secretion [Date et al., 2001]. However, other studies have shown that intracerebroventricular administration of ghrelin inhibited gastric acid secretion in conscious rats [Levin et al., 2005; Sibilia et al., 2002]. Recently, it has been shown that simultaneous administration of ghrelin and gastrin induced a synergistic increase of gastric acid secretion [Fukumoto et al., 2008]. Stimulatory or inhibitory effects of ghrelin on gastric acid secretion may depend on experimental conditions and models. Ghrelin stimulates gastric motility by inducing the migrating motor complex and accelerating gastric emptying [Dass et al., 2003; Depoortere et al., 2005; Fujino et al., 2003; Peeters, 2003; Peeters, 2005]. By its prokinetic effect, ghrelin is able to reverse gastric postoperative ileus in rat [Trudel et al., 2002]. Moreover, ghrelin exerts a gastroprotective effect against stress-, ethanol- and cysteamine-induced ulcers [Konturek et al., 2004; Sibilia et al., 2003]. This effect depends on sensory nerve fiber integrity and is mediated by the nitric oxide system [Peeters, 2005].

Pancreatic Functions Ghrelin seems to influence glucose metabolism. Acute ghrelin administration increases plasma glucose levels and amplifies the hyperglycemic effect of arginine. This effect could be due to glycogenolysis activation, indirectly by stimulation of catecholamine release, or directly by acting on hepatocytes where ghrelin might modulate neoglucogenesis. [Broglio et al., 2005; Gauna et al., 2005; Murata et al., 2002]. Ghrelin has been reported to influence the endocrine pancreatic function. Depending on the experimental conditions, ghrelin either stimulates [Adeghate & Ponery, 2002; Date et al.,

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2002b; Lee et al., 2002] or inhibits insulin secretion [Broglio et al., 2001; Colombo et al., 2003; Cui et al., 2008; Reimer et al., 2003]. Salehi et al. suggest that the effect of ghrelin on insulin secretion depends on concentration: ghrelin might have an inhibitory effect at low concentration and a stimulating effect at high concentration [Salehi et al., 2004]. Besides the direct effect of ghrelin on insulin secretion, a negative association between ghrelin secretion and insulin secretion has been observed [Ariyasu et al., 2001; Cummings et al., 2001; Saad et al., 2002; Toshinai et al., 2001]. This could be explained by the increase of plasma ghrelin levels and the decrease of plasma insulin levels during fasting, but this does not involve a direct inhibitory effect on insulin secretion. The effects of ghrelin on exocrine pancreatic function are also controversial. In rat pancreas, ghrelin was shown to inhibit pancreatic protein secretion or to increase protein output. These effects are indirect and may involve cholecystokinin and reflex vagal pathways [Jaworek, 2006].

Cardiovascular Functions

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Ghrelin has diverse cardiovascular effects. In vitro, ghrelin inhibits apoptosis of cardiomyocytes and endothelial cells. Moreover, by inhibiting NF-κB activation in human endothelial cells and mononuclear cell adhesion, ghrelin might oppose inflammation of the cardiovascular system. Ghrelin exerts vasodilatory effects by an endothelium-independent mechanism. Administration of ghrelin decreases mean arterial pressure without changing the heart rate. Ghrelin improves cardiac contractility and left ventricular function in chronic heart failure and reduces infarct size [Isgaard & Johansson, 2005]. In rats with myocardial infarction, ghrelin suppresses cardiac sympathetic activity and prevents early left ventricular remodeling, suggesting the potential usefulness of ghrelin as a new cardioprotective hormone early after myocardial infarction [Soeki et al., 2008].

Anti-Inflammatory Functions Ghrelin has anti-inflammatory effects. Indeed, ghrelin inhibits production of proinflammatory cytokines in human endothelial cells, T cells, monocytes, and in a rat model of endotoxic shock [Chang et al., 2003; Dembinski et al., 2003; Dixit et al., 2004; Li et al., 2004; Nagaya et al., 2001; Xia et al., 2004]. Also, ghrelin attenuates the development of acute pancreatitis in rats [Dembinski et al., 2003]. Ghrelin dose-dependently inhibits proliferation of anti-CD3 activated splenic T lymphocytes in mice [Dixit & Taub, 2005]. Ghrelin possesses a neutrophil-dependent anti-inflammatory effect that prevents burn-induced multiple organ injury and protects against oxidative organ damage [Sehirli et al., 2008]. Ghrelin attenuates lipopolysaccharide-induced acute lung inflammation and suppresses lipopolysaccharide-induced proinflammatory cytokine production in lung macrophages, which is partially mediated by increased NO production [Chen et al., 2008].

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Other Functions Ghrelin participates in the regulation of the reproductive function. In the testis, ghrelin inhibits testosterone secretion. Besides having direct gonadal effects, ghrelin may participate in the regulation of gonadotropin secretion and may influence the timing of puberty. In the pituitary, ghrelin inhibits luteinizing hormone secretion [Garcia et al., 2007]. Ghrelin stimulates bone formation by stimulating in vitro osteoblastic cell proliferation and differentiation, inhibiting apoptosis, and increasing in vivo bone mineral density in both normal and GH-deficient rats [Fukushima et al., 2005]. In addition to these functions, ghrelin also modulates cell proliferation in various cell types [De Vriese et al., 2005; De Vriese & Delporte, 2007; Korbonits et al., 2004].

13. POTENTIAL CLINICAL APPLICATIONS OF GHRELIN In search of GHS-R 1a agonists and antagonists, numerous structure-function studies have been performed using peptidic and non-peptidic ghrelin analogues. Given that ghrelin stimulates food intake, ghrelin agonists or antagonists are mainly developed for cachexia treatment and for obesity treatment, respectively. Although patients with cachexia have increased plasma ghrelin levels, reflecting a compensatory response to weight loss, ghrelin administration still improves food intake and weight gain in a rat model of cancer cachexia [Deboer et al., 2007], and in patients with congestive heart failure or chronic obstructive pulmonary disease [Nagaya et al., 2006]. In patients with cachexia associated with anorexia nervosa, the effect of ghrelin administration is controversial [Miljic et al., 2006].

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GHS-R 1a Agonists As an alternative to growth hormone replacement therapy, an effort has been made to identify peptidomimetic and nonpeptidic small molecular growth hormone secretagogues (GHSs). Synthetic ghrelin agonists existed long before ghrelin was discovered. Indeed, in search for hypothalamic factor controlling the release of growth hormone, enkephalin analogues were synthesized as they induced weak GH release. This led to the discovery of GHSs, peptidic or non peptidic molecules inducing potent growth hormone release, such as growth hormone-releasing peptide-2 (GHRP-2), growth hormone-releasing peptide-6 (GHRP6), hexarelin, MK-0677, CP-424,391 and NNC-26-073 [Smith et al., 1997; Smith et al., 2007; Wu et al., 1996]. Several GHSs have advanced to clinical studies including MK-677 (Merck), CP-424391 (Pfizer), LY-444711 (Lilly). In the full ghrelin sequence, the presence of the voluminous hydrophobic groups on Ser3 is critical for the biological activity of the peptide [Bednarek et al., 2000; Matsumoto et al., 2001]. Maximal activity is reached with the acylation of Ser3 by an octanoyl group (C8:0). A substantial activity is maintained by the acylation of Ser3 by a decanoyl (C10:0), lauryl (C12:0) or palmitoyl (C16:0) group. However, the activity is largely decreased by the acylation of Ser3 by a butyryl (C4:0) or an acetyl (C2:0) group. Ser3 modification by a polyunsaturated fatty acid, such as 3-octenoyl (C8:1), or by a fatty acid containing a lateral

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Carine De Vriese, Jason Perret and Christine Delporte

chain, such as a 4-methylpentanoyl, maintain the activity [Matsumoto et al., 2001]. Whereas the replacement of Ser3 by a Trp maintains the activity of ghrelin, its replacement by aliphatic AA such as Val, Leu or Ile totally inhibits the activity of ghrelin [Bednarek et al., 2000]. Short peptides encompassing the first four or five residues of ghrelin remained functionally active, nearly as efficiently as the full-length ghrelin, on the on GHS-R 1a [Bednarek et al., 2000]. Ala-scan of ghrelin 1-14 revealed the importance of the amino-terminal positive charge and Phe in position 4 for the receptor interaction. Furthermore, analogs of ghrelin 1-14 modified in position 8 (Glu) by Ala or Tyr were more potent that ghrelin 1-14 [Van Craenenbroeck et al., 2004]. BIM-28125, a peptidic analogue of ghrelin, was reported as a potent stimulator of growth hormone secretion [Rubinfeld et al., 2004]. BIM-28131, a compound related to BIM-28125, induced body weight gain in rats [Strassburg et al., 2008]. Certain oxindole derivatives such as SM-130686((+)-6-carbamoyl-3-(2-chlorophenyl)-2-diethylaminoethyl)-4-tri fluoro methyloxindo-le) had potent growth hormone releasing activity, and induced body weight as well as fat-free mass gain [Nagamine et al., 2001; Tokunaga et al., 2001]. Structure-activity relationship of the C3-aromatic part of SM-130686 was examined and a series of 3dichlorophenyl analogues were identified as potent ghrelin agonists [Tokunaga et al., 2005]. Among a series of GHS analogues synthesized based on the 1,2,4-triazole structure, some behaved as GHS-R 1a agonists such as JMV2873 [Demange et al., 2007]. Some 3,4,5trisubstituted 1,2,4-triazoles were synthesized and two possessed potent GHS-R 1a agonist activity [Moulin et al., 2008]. From a series of pseudopeptidic analogues derived from EP-51389, based on a gemdiamino structure, JMV1843 was identified as a potent GHS-R 1a agonist [Guerlavais et al., 2003]. This molecule is currently under a phase III clinical trial in the US for the diagnosis of growth hormone deficiency in adults. Diltiazem and some of its metabolites were reported to behave as GHS-R 1a agonists [Ma et al., 2007]. A series of small molecules GHS-R 1a agonists, SB-791016, were identified but suffered from poor oral absorption which may be attributed to the relatively high lipophilicity and poor solubility [Heightman et al., 2007]. Subsequent structure-activity relationship optimization of these compounds and in vivo properties were recently reported, and a potent GHS-R 1a agonist was identified: GSK899490A [Witherington et al., 2008]. The potential use of GHS-R 1a agonists as therapeutic agents for the treatment of gastrointestinal motility disorders has also been investigated [Peeters, 2006]. GHRP-6 is a GHS-R 1a agonist able to increase gastric emptying in normal rats [Depoortere et al., 2005], as well as in animal models of postoperative ileus [Trudel et al., 2002], septic ileus [De Winter et al., 2004], burn-induced slow gastrointestinal transit [Sallam et al., 2007], diabetes mellitus [Qiu et al., 2008a; Qiu et al., 2008b; Zheng et al., 2008]. RC-1139, a GHS-R 1a agonist, was reported to behave as a potent gastrokinetic in rats, and it also reversed postoperative ileus, even in the presence of opiates [Poitras et al., 2005]. TZP-101, a small GHS-R 1a agonist displaying superior bioavailability than the ghrelin peptide, increases gastric emptying and intestinal transit in normal rats [Fraser et al., 2008], in a rat model of postoperative ileus [Venkova et al., 2007], and in patients with diabetic gastroparesis [Madsen et al., 2007]. In a clinical phase I study, the safety, pharmacokinetics and pharmacodynamic of TZP-101 were recently evaluated in healthy volunteers and

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suggested that this compound could be used for gastrointestinal motility disorders [Lasseter et al., 2008]. GSK894281 (N-[5-(cis-3,5-dimethyl-1-piperazinyl)-2-(methyloxy)phenyl]-3-fluoro-4-(5methyl-2-furanyl)benzenesulphonamide) is a GHS-R 1a agonist triggering defecation in rats [Shafton et al., 2008].

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GHS-R 1a Antagonists A GHS-R 1a antagonist, D-Lys3-GHRP-6 delayed gastric emptying induced by GHS-R 1a agonist [Depoortere et al., 2006; Qiu et al., 2008a], but this could be due at least in part by interacting with the serotonergic 5-HT2B receptors [Depoortere et al., 2006]. The potential benefits of using GHS-R 1a antagonists for the treatment of type 2 diabetes and obesity, particularly in Prader-Willi syndrome, have been investigated. Ghrelin-receptor antagonists, as [D-Lys-3]GHRP-6, decrease food intake in lean mice and obese mice, and reduce weight gain [Asakawa et al., 2003; Beck et al., 2004]. Piperidine-substituted quinazolinone derivatives were identified as a novel class of smallmolecules GHS-R 1a antagonists [Rudolph et al., 2007]. Phenyl or phenoxy groups were identified as optimal substituents at position 6 of the quinazolinone core, and the replacement of phenyl groups in position 2 by small alkyl substituents were proven to be beneficial [Rudolph et al., 2007]. YIL-781, a piperidine-substituted quinazolinone derivative acting as potent GHS-R 1a antagonist, was shown to improve glucose tolerance due to increased insulin secretion, to reduce food intake and to promote weight loss in diet-induced obese mice [Esler et al., 2007]. Among a series of GHS analogues synthesized based on the 1,2,4-triazole structure, some behaved as GHS-R 1a antagonists such as JMV2866 and JMV2844 [Demange et al., 2007]. Some 3,4,5-trisubstituted 1,2,4-triazoles were synthesized and most of them possessed potent GHS-R 1a antagonist activity [Moulin et al., 2008].

Inverse Agonists Consistent with the high constitutive activity of the ghrelin receptor, inverse agonists of the receptor, decreasing its constitutive activity, may be useful for the treatment of obesity [Holst et al., 2003]. During long fasting, GHS-R 1a expression increases in the hypothalamus, leading to an increase of GHS-R 1a signaling, a higher appetite, and a decrease of energy expenditure. The decrease of the GHS-R 1a constitutive activity by an inverse agonist could increase the sensitivity to anorexigenic hormones like leptin or PYY, and prevent food intake between meals [Holst & Schwartz, 2004]. [D-Arg1, D-Phe5, D-Trp7,9, Leu11]substance P was identified as an inverse agonist on GHS-R 1a [Holst et al., 2006]. The use of inverse agonists of the GHS-R 1a in obesity treatment needs to be further investigated.

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Others Spiegelmers, antisense polyethylene glycol-modified L-oligonucleotides capable to specifically bind a target molecule, have been synthesized to neutralize ghrelin and inhibit its binding to the GHS-R 1a. The spiegelmer NOX-B11-2 decreased food intake and body weight in diet-induced obese mice [Asakawa et al., 2003; Kobelt et al., 2006; Shearman et al., 2006]. Another Spiegelmer, NOX-B11-3 was also shown to inhibit ghrelin-induced GH release in rats [Helmling et al., 2004]. NOX-B11-3 exerted long-lasting action after a single peripheral injection: it blocked ghrelin, but not fasting-induced neuronal activation in the hypothalamic arcuate nucleus [Becskei et al., 2008]. The neutralization of circulating ghrelin by these Spiegelmers may be useful to treat diseases associated with high ghrelin levels such as the PWS. Ghrelin hapten immunoconjugates lead to the production of antibodies specifically directed against acylated ghrelin. In rats with strong anti-ghrelin immune responses, body weight gain is reduced with preferential reduction of fat mass compared to lean mass, by decreasing feed efficiency (weight gain per kilocalorie of food) [Zorrilla et al., 2006].

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14. CONCLUSION The importance of ghrelin in appetite stimulation and body weight regulation is intensively investigated. The effect of ghrelin on appetite is mediated in hypothalamus through stimulation of NPY, AGRP and orexin release, and inhibition α-MSH and CART release, and through activation of GHS-R on vagal afferents in the stomach. The effect of ghrelin on body weight is mediated by stimulating food intake, but also by reducing energy expenditure and promoting adiposity. Ghrelin agonists seem useful for treatment of gastrointestinal motility disorders, cancer-induced cachexia, congestive heart failure or chronic obstructive pulmonary disease. Ghrelin-receptor antagonists, Spiegelmers and antighrelin vaccine reduce body weight gain and might be useful for type 2 diabetes and obesity treatment, particularly in PWS. Recently, the enzyme responsible for the octanoylation of ghrelin, GOAT, was identified and could represent an additional interesting therapeutic target for the treatment of type 2 diabetes and obesity. All these clinical applications of ghrelin will require further intensive investigations.

ACKNOWLEDGEMENTS This work was supported by grants 3.4510.03 and 3.4561.07 from the Fund for Medical Scientific Research (Belgium).

15. REFERENCES Adeghate, E. & Ponery, A. S. (2002). Ghrelin stimulates insulin secretion from the pancreas of normal and diabetic rats. J. Neuroendocrinol. 14, 555-560.

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Akamizu, T., Shinomiya, T., Irako, T., Fukunaga, M., Nakai, Y., Nakai, Y., & Kangawa, K. (2005). Separate Measurement of Plasma Levels of Acylated and Desacyl Ghrelin in Healthy Subjects Using a New Direct ELISA Assay. J. Clin. Endocrinol. Metab. 90, 6-9. Ando, T., Ichimaru, Y., Konjiki, F., Shoji, M., & Komaki, G. (2007). Variations in the preproghrelin gene correlate with higher body mass index, fat mass, and body dissatisfaction in young Japanese women. Am. J. Clin. Nutr. 86, 25-32. Ariyasu, H., Takaya, K., Tagami, T., Ogawa, Y., Hosoda, K., Akamizu, T., Suda, M., Koh, T., Natsui, K., Toyooka, S., Shirakami, G., Usui, T., Shimatsu, A., Doi, K., Hosoda, H., Kojima, M., Kangawa, K., & Nakao, K. (2001). Stomach Is a Major Source of Circulating Ghrelin, and Feeding State Determines Plasma Ghrelin-Like Immunoreactivity Levels in Humans. J. Clin. Endocrinol. Metab. 86, 4753-4758. Ariyasu, H., Takaya, K., Iwakura, H., Hosoda, H., Akamizu, T., Arai, Y., Kangawa, K., & Nakao, K. (2005). Transgenic mice overexpressing des-acyl ghrelin show small phenotype. Endocrinology. 146, 355-364. Arnold, M., Mura, A., Langhans, W., & Geary, N. (2006). Gut vagal afferents are not necessary for the eating-stimulatory effect of intraperitoneally injected ghrelin in the rat. J. Neurosci. 26, 11052-11060. Asakawa, A., Inui, A., Kaga, T., Yuzuriha, H., Nagata, T., Ueno, N., Makino, S., Fujimiya, M., Niijima, A., Fujino, M. A., & Kasuga, M. (2001). Ghrelin is an appetite-stimulatory signal from stomach with structural resemblance to motilin. Gastroenterology. 120, 337345. Asakawa, A., Inui, A., Kaga, T., Katsuura, G., Fujimiya, M., Fujino, M. A., & Kasuga, M. (2003). Antagonism of ghrelin receptor reduces food intake and body weight gain in mice. Gut. 52, 947-952. Bang, A. S., Soule, S. G., Yandle, T. G., Richards, A. M., & Pemberton, C. J. (2007). Characterisation of proghrelin peptides in mammalian tissue and plasma. J. Endocrinol. 192, 313-323. Baynes, K. C., Dhillo, W. S., & Bloom, S. R. (2006). Regulation of food intake by gastrointestinal hormones. Curr. Opin. Gastroenterol. 22, 626-631. Beaumont, N. J., Skinner, V. O., Tan, T. M., Ramesh, B. S., Byrne, D. J., MacColl, G. S., Keen, J. N., Bouloux, P. M., Mikhailidis, D. P., Bruckdorfer, K. R., Vanderpump, M. P., & Srai, K. S. (2003). Ghrelin can bind to a species of high density lipoprotein associated with paraoxonase. J. Biol. Chem. 278, 8877-8880. Beck, B., Richy, S., & Stricker-Krongrad, A. (2004). Feeding response to ghrelin agonist and antagonist in lean and obese Zucker rats. Life Sci. 76, 473-478. Becskei, C., Bilik, K. U., Klussmann, S., Jarosch, F., Lutz, T. A., & Riediger, T. (2008). The anti-ghrelin Spiegelmer NOX-B11-3 blocks ghrelin- but not fasting-induced neuronal activation in the hypothalamic arcuate nucleus. J. Neuroendocrinol. 20, 85-92. Bednarek, M. A., Feighner, S. D., Pong, S. S., McKee, K. K., Hreniuk, D. L., Silva, M. V., Warren, V. A., Howard, A. D., Van Der Ploeg, L. H., & Heck, J. V. (2000). Structurefunction studies on the new growth hormone-releasing peptide, ghrelin: minimal sequence of ghrelin necessary for activation of growth hormone secretagogue receptor 1a. J. Med. Chem. 43, 4370-4376. Bing, C., Ambye, L., Fenger, M., Jorgensen, T., Borch-Johnsen, K., Madsbad, S., & Urhammer, S. A. (2005). Large-scale studies of the Leu72Met polymorphism of the

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ghrelin gene in relation to the metabolic syndrome and associated quantitative traits. Diabet Med. 22, 1157-1160. Bodart, V., Bouchard, J. F., McNicoll, N., Escher, E., Carriere, P., Ghigo, E., Sejlitz, T., Sirois, M. G., Lamontagne, D., & Ong, H. (1999). Identification and Characterization of a New Growth Hormone-Releasing Peptide Receptor in the Heart. Circ. Res. 85, 796802. Bodart, V., Febbraio, M., Demers, A., McNicoll, N., Pohankova, P., Perreault, A., Sejlitz, T., Escher, E., Silverstein, R. L., Lamontagne, D., & Ong, H. (2002). CD36 Mediates the Cardiovascular Action of Growth Hormone-Releasing Peptides in the Heart. Circ. Res. 90, 844-849. Bresciani, E., Rapetti, D., Dona, F., Bulgarelli, I., Tamiazzo, L., Locatelli, V., & Torsello, A. (2006). Obestatin inhibits feeding but does not modulate GH and corticosterone secretion in the rat. J. Endocrinol. Invest. 29, RC16-RC18. Broglio, F., Arvat, E., Benso, A., Gottero, C., Muccioli, G., Papotti, M., van der Lely, A. J., Deghenghi, R., & Ghigo, E. (2001). Ghrelin, a natural GH secretagogue produced by the stomach, induces hyperglycemia and reduces insulin secretion in humans. J. Clin. Endocrinol. Metab. 86, 5083-5086. Broglio, F., Prodam, F., Me, E., Riganti, F., Lucatello, B., Granata, R., Benso, A., Muccioli, G., & Ghigo, E. (2005). Ghrelin: endocrine, metabolic and cardiovascular actions. J. Endocrinol. Invest. 28, 23-25. Burdyga, G., Varro, A., Dimaline, R., Thompson, D. G., & Dockray, G. J. (2006). Ghrelin receptors in rat and human nodose ganglia: putative role in regulating CB-1 and MCH receptor abundance. Am. J. Physiol. Gastrointest. Liver Physiol. 290, G1289-G1297. Caminos, J. E., Tena-Sempere, M., Gaytan, F., Sanchez-Criado, J. E., Barreiro, M. L., Nogueiras, R., Casanueva, F. F., Aguilar, E., & Dieguez, C. (2003). Expression of ghrelin in the cyclic and pregnant rat ovary. Endocrinology. 144, 1594-1602. Carlini, V. P., Schioth, H. B., & Debarioglio, S. R. (2007). Obestatin improves memory performance and causes anxiolytic effects in rats. Biochem. Biophys. Res. Commun. 352, 907-912. Cellini, E., Nacmias, B., Brecelj-Anderluh, M., Badia-Casanovas, A., Bellodi, L., Boni, C., Di Bella, D., Estivill, X., Fernandez-Aranda, F., Foulon, C., Friedel, S., Gabrovsek, M., Gorwood, P., Gratacos, M., Guelfi, J., Hebebrand, J., Hinney, A., Holliday, J., Hu, X., Karwautz, A., Kipman, A., Komel, R., Rotella, C. M., Ribases, M., Ricca, V., Romo, L., Tomori, M., Treasure, J., Wagner, G., Collier, D. A., & Sorbi, S. (2006). Case-control and combined family trios analysis of three polymorphisms in the ghrelin gene in European patients with anorexia and bulimia nervosa. Psychiatr. Genet. 16, 51-52. Chamoun, Z., Mann, R. K., Nellen, D., von Kessler, D. P., Bellotto, M., Beachy, P. A., & Basler, K. (2001). Skinny Hedgehog, an Acyltransferase Required for Palmitoylation and Activity of the Hedgehog Signal. Science. 293, 2080-2084. Chan, C. B. & Cheng, C. H. K. (2004). Identification and functional characterization of two alternatively spliced growth hormone secretagogue receptor transcripts from the pituitary of black seabream Acanthopagrus schlegeli. Mol. Cell Endocrinol. 214, 81-95. Chan, J. L., Mun, E. C., Stoyneva, V., Mantzoros, C. S., & Goldfine, A. B. (2006). Peptide YY levels are elevated after gastric bypass surgery. Obesity (Silver Spring), 14, 194-198. Chang, L., Zhao, J., Yang, J., Zhang, Z., Du, J., & Tang, C. (2003). Therapeutic effects of ghrelin on endotoxic shock in rats. Eur. J. Pharmacol. 473, 171-176.

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Wolf, I., Sadetzki, S., Kanety, H., Kundel, Y., Pariente, C., Epstein, N., Oberman, B., Catane, R., Kaufman, B., & Shimon, I. (2006). Adiponectin, ghrelin, and leptin in cancer cachexia in breast and colon cancer patients. Cancer. 106, 966-973. Wortley, K. E., Anderson, K. D., Garcia, K., Murray, J. D., Malinova, L., Liu, R., Moncrieffe, M., Thabet, K., Cox, H. J., Yancopoulos, G. D., Wiegand, S. J., & Sleeman, M. W. (2004). Genetic deletion of ghrelin does not decrease food intake but influences metabolic fuel preference. Proc. Natl. Acad. Sci. U. S. A. 101, 8227-8232. Wortley, K. E., del Rincon, J. P., Murray, J. D., Garcia, K., Iida, K., Thorner, M. O., & Sleeman, M. W. (2005). Absence of ghrelin protects against early-onset obesity. J. Clin. Invest. 115, 3573-3578. Wren, A. M., Seal, L. J., Cohen, M. A., Brynes, A. E., Frost, G. S., Murphy, K. G., Dhillo, W. S., Ghatei, M. A., & Bloom, S. R. (2001). Ghrelin Enhances Appetite and Increases Food Intake in Humans. J. Clin. Endocrinol. Metab. 86, 5992. Wu, D., Chen, C., Zhang, J., Bowers, C. Y., & Clarke, I. J. (1996). The effects of GHreleasing peptide-6 (GHRP-6) and GHRP-2 on intracellular adenosine 3',5'monophosphate (cAMP) levels and GH secretion in ovine and rat somatotrophs. J. Endocrinol. 148, 197-205. Xia, Q., Pang, W., Pan, H., Zheng, Y., Kang, J. S., & Zhu, S. G. (2004). Effects of ghrelin on the proliferation and secretion of splenic T lymphocytes in mice. Regul. Pept. 122, 173178. Yamamoto, D., Ikeshita, N., Daito, R., Herningtyas, E. H., Toda, K., Takahashi, K., Iida, K., Takahashi, Y., Kaji, H., Chihara, K., & Okimura, Y. (2007). Neither intravenous nor intracerebroventricular administration of obestatin affects the secretion of GH, PRL, TSH and ACTH in rats. Regul. Pept. 138, 141-144. Yamanaka, A., Beuckmann, C. T., Willie, J. T., Hara, J., Tsujino, N., Mieda, M., Tominaga, M., Yagami, K., Sugiyama, F., Goto, K., Yanagisawa, M., & Sakurai, T. (2003). Hypothalamic orexin neurons regulate arousal according to energy balance in mice. Neuron. 38, 701-713. Yang, J., Brown, M. S., Liang, G., Grishin, N. V., & Goldstein, J. L. (2008). Identification of the Acyltransferase that Octanoylates Ghrelin, an Appetite-Stimulating Peptide Hormone. Cell. 132, 387-396. Yeh, A. H., Jeffery, P. L., Duncan, R. P., Herington, A. C., & Chopin, L. K. (2005). Ghrelin and a novel preproghrelin isoform are highly expressed in prostate cancer and ghrelin activates mitogen-activated protein kinase in prostate cancer. Clin. Cancer Res. 11, 82958303. Zamrazilova, H., Hainer, V., Sedlackova, D., Papezova, H., Kunesova, M., Bellisle, F., Hill, M., & Nedvidkova, J. (2008). Plasma obestatin levels in normal weight, obese and anorectic women. Physiol. Res. 57 Suppl 1, S49-S55. Zhang, J. V., Ren, P. G., Avsian-Kretchmer, O., Luo, C. W., Rauch, R., Klein, C., & Hsueh, A. J. W. (2005). Obestatin, a Peptide Encoded by the Ghrelin Gene, Opposes Ghrelin's Effects on Food Intake. Science. 310, 996-999. Zhao, C. M., Furnes, M. W., Stenstrom, B., Kulseng, B., & Chen, D. (2008). Characterization of obestatin- and ghrelin-producing cells in the gastrointestinal tract and pancreas of rats: an immunohistochemical and electron-microscopic study. Cell Tissue Res. 331, 575-587.

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Zheng, Q., Qiu, W. C., Yan, J., Wang, W. G., Yu, S., Wang, Z. G., & Ai, K. X. (2008). Prokinetic effects of a ghrelin receptor agonist GHRP-6 in diabetic mice. World J. Gastroenterol. 14, 4795-4799. Zhu, X., Cao, Y., Voodg, K., & Steiner, D. F. (2006). On the Processing of Proghrelin to Ghrelin. J. Biol. Chem. 281, 38867-38870. Zigman, J. M., Nakano, Y., Coppari, R., Balthasar, N., Marcus, J. N., Lee, C. E., Jones, J. E., Deysher, A. E., Waxman, A. R., White, R. D., Williams, T. D., Lachey, J. L., Seeley, R. J., Lowell, B. B., & Elmquist, J. K. (2005). Mice lacking ghrelin receptors resist the development of diet-induced obesity. J. Clin. Invest. 115, 3564-3572. Zizzari, P., Longchamps, R., Epelbaum, J., & Bluet-Pajot, M. T. (2007). Obestatin Partially Affects Ghrelin Stimulation of Food Intake and GH Secretion in Rodents. Endocrinology. 148, 1648-1653. Zorrilla, E. P., Iwasaki, S., Moss, J. A., Chang, J., Otsuji, J., Inoue, K., Meijler, M. M., & Janda, K. D. (2006). Vaccination against weight gain. Proc. Natl. Acad. Sci. U. S. A. 103, 13226-13231. Zou, C. C., Huang, K., Liang, L., & Zhao, Z. Y. (2008). Polymorphisms of the ghrelin/obestatin gene and ghrelin levels in Chinese children with short stature. Clinical Endocrinology. 69, 99-104.

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In: Appetite and Nutritional Assessment Editors: S. J. Ellsworth, R. C. Schuster

ISBN: 978-1-60741-085-0 © 2009 Nova Science Publishers, Inc.

Chapter 2

APPETITE CONTROL- THE ROLE OF CENTRAL AND GUT NEUROPEPTIDES Sarika Arora Department of Biochemistry, G.B. Pant Hospital, New Delhi, India

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ABSTRACT Obesity, one of the most prevalent nutritional problems worldwide, results when energy intake exceeds the energy expenditure. In a normal state, powerful and complex physiological systems exist to balance these two sides of the equation. These systems consist of multiple pathways between Gastrointestinal Tract (GIT) and Central Nervous System (CNS), which maintain eating patterns. This gut-brain axis has both neural and humoral components that relay information to important CNS centres, including hypothalamus and brainstem. Specific populations of peptidergic neurons in the medial hypothalamus act as metabolic integrators sensing both short- and long-term availability of fuels and then orchestrate the adaptive responses through changes in food intake as well as endocrine and autonomic responses. The structure and function of many hypothalamic peptides [ Neuropeptide Y (NPY), melanocortins, agouti-related peptide (AGRP), cocaine and amphetamine regulated transcript (CART), melanin concentrating hormone (MCH), orexins have been characterized in rodent models. The gastrointestinal neuropeptides such as cholecystokinin (CCK), ghrelin, peptide YY (PYY-36), amylin regulate important gastrointestinal function such as motility, secretion, absorption and provide feedback to the central nervous system on the availability of nutrients. The mechanisms by which hormones interact with CNS appetite centers are the subject of some contention. The proximity of both the hypothalamus and brainstem to structures with a relative deficiency of blood-brain barrier (the median eminence in the case of the hypothalamus and the area postrema in respect of the brainstem) may allow direct access of circulating factors to CNS neurons. There is a growing body of evidence, however, that points to the vagus nerve as a primary site of action of some appetite-modulating hormones An understanding of these mechanisms is important to determine the pathophysiology of obesity and to allow identification of targets for the treatment of obesity. The pursuit of the body's own satiety signals as therapeutic targets promises effective reductions in body weight with minimum disruption to other systems, avoiding the side effects that occur as an unwanted consequence of therapies targeting ubiquitous neurotransmitter and receptor complexes.

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INTRODUCTION Obesity is one of the most prevalent nutritional problems worldwide which in the long run predisposes to development of diabetes mellitus, hypertension, endometrial carcinoma, osteoarthritis, gall stones and cardiovascular diseases [1]. The upward trend of this health crisis continues despite lifestyle interventions. This growing incidence would result in a pandemic that needs urgent attention if the potential morbidity, mortality and economic tolls that will be left in its wake are to be avoided. An understanding of the mechanisms regulating food intake, energy expenditure and energy balance is important for combating this epidemic.

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APPETITE REGULATION AND ADAPTATION – A BIO-BEHAVIORAL SYSTEM Appetite regulation is the target of scientific research for a number of different researchers including physiologists, nutritionists, psychologists, biochemists, endocrinologists and many others. Under normal conditions, in most adults, adiposity and body weight are remarkably constant despite huge variations in daily food intake and energy expenditure. This homeostasis is maintained by powerful and complex physiological systems composed of both afferent signals and efferent effectors. These systems consist of multiple pathways which incorporate significant redundancy in order to maintain the appetite or the drive to eat [2]. Appetite regulation includes various aspects of the eating patterns. The first aspect is qualitative which includes food choice (choices of high fat or low fat foods, variety of foods accepted, palatability of diet), preferences and the sensory aspects of food together with subjective phenomena such as hunger, fullness and hedonic sensations which accompany eating and which are sometimes regarded as causal agents. The second aspect is primarily concerned with quantitative aspects of consumption such as frequency, size of eating episodes (gorging versus nibbling), variability in day-to-day intake and the energetic value of food [1]. At the present time particular importance is attached to the macronutrient composition of food and its impact on energy balance. Nutritional intake plays an obvious role in homeostatic processes, which serve the purpose of biological regulation, but as a behavior, nutrient intake is also adapted to particular environmental demands. Feeding behavior is the result of complex integration of central and peripheral neural, hormonal and neuro-chemical signals relating to brain and metabolic states. Meals are initiated, maintained and terminated by a series of short-term hormonal (cholecystokinin and ghrelin), psychological and neural signals derived from the gastro-intestinal tract several times a day separated by inter meal intervals without food intake. Other hormones such as leptin and insulin, together with circulating nutrients indicate long-term energy stores [1]. All these signals are integrated by peripheral nerves and brain centers, such as the hypothalamus and brain stem. The integrated signals regulate central neuropeptides, which modulate feeding and energy expenditure. This energy homeostasis, in most cases, regulates body weight tightly. While hypothalamus and caudal brainstem play crucial roles in this homeostatic function, areas in the cortex and limbic system are important for processing information regarding prior experience with food, reward, and emotion, as well as social and environmental context [3]. The appetite control system of the brain normally establishes a

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weight ‗set-point‘ and tries to maintain it even when food supplies vary a great deal. This interplay between biological demands and environmental requirements has implications for the regulation of body weight and also draws attention to key principles which govern the operation of this bio-behavioral system. As energy deficit is most likely to compromise survival, it is not surprising that most powerful of these pathways are those that increase food intake and decrease energy expenditure when body stores are depleted. A consideration of anthropological, epidemiological and experimental evidence suggests that it is easier for human beings to gain weight than to reduce weight. This implies that the control of appetite (by the psychobiological system) is asymmetrical rather than symmetrical. Most vertebrates can store a considerable amount of energy as fat for later use, and this ability has now become one of the major health risks for many human populations. However, since the food is more readily available, it has been argued that evolutionary pressure has resulted in a drive to eat without limit. The disparity between the environment in which these systems evolved and the current availability of food may contribute to over-eating and the increasing prevalence of obesity.

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ROLE OF CENTRAL NERVOUS SYSTEM- HYPOTHALAMUS, BRAIN STEM AND REWARD CENTERS The role of hypothalamus in feeding control has been revealed by classical (but crude) experiments nearly half a century ago. Lesioning and stimulation of the hypothalamic nuclei initially suggested roles for the ventromedial nucleus as ‗satiety centre‘ and the lateral hypothalamic nucleus (LHA) as ‗feeding centre‘ [4]. With the exception of lesions in the LHA, these experimental manipulations within the brain disrupted the daily food intake pattern to produce permanently enhanced appetite or hyperphagia. The inference from these investigations generated voluminous information on the patterns of ingestive behavior and the attendant shifts in endocrine and autonomic systems in rats undergoing these experimental manipulations [5-7]. The main regions of hypothalamus involved in feeding and satiety are: (a) Arcuate Nucleus (ARC)- It acts as a feeding control centre which integrates hormonal signals for energy homeostasis [8]. The Arcuate Nucleus encloses the third ventricle and lies immediately above the median eminence. It extends rostrocaudally from the posterior borders of the optic chiasm to the mamillary bodies. The ARC is capable of sampling the circulating signals of energy balance, via the underlying median eminence, as this region of the brain is not protected by the blood–brain barrier [9]. The blood brain barrier plays a dynamic role in passage of circulating energy signals. Some peripheral gut hormones, such as peptide YY and glucagon-like peptide 1 (GLP-1) are able to cross the blood–brain barrier via non-saturable mechanisms [10, 11] whereas, other signals, such as leptin and insulin (both considered to be the signals of fat mass) [12] are transported from blood to brain by a saturable mechanism [13, 14]. There are two primary populations of neurons within the ARC which integrate signals of nutritional status, and influence energy homeostasis [15]. One neuronal circuit inhibits food intake, via the expression of the neuropeptides pro-opio melanocortin (POMC) and cocaineand amphetamine-regulated transcript (CART [16, 17]. The other neuronal circuit stimulates

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food intake, via the expression of neuropeptide Y (NPY) and agouti-related peptide (AgRP) [18, 19]. (b) Ventromedial Nucleus (VMH) is mainly acting as satiety centre. Bilateral VMH lesions produce hyperphagia and obesity [20]. The VMH receives projections from arcuate NPY-, AgRP- and POMC -immunoreactive neurons and in turn VMH neurons project to other hypothalamic nuclei (e.g. Dorsomedial hypothalamus (DMH)) and to brain stem regions such as the Nucleus Tractus Solitarius (NTS). It has been identified as a key target for leptin, which acts on hypothalamus to inhibit feeding, stimulate energy expenditure and cause weight loss. NPY expression is altered in the VMH of obese mice [21] and melanocortin receptor (MC4R) expression is upregulated in the VMH of diet-induced obese rats [22]. (c) Paraventricular Nucleus (PVN) is adjacent to the superior part of the third ventricle in the anterior hypothalamus. The PVN is the main site of corticotrophin releasing hormone [CRH] and thyrotropin releasing hormone [TRH] secretion. Numerous neuronal pathways implicated in energy balance converge in PVN, including major projections from NPY neurons of the ARC, Orexins, POMC derivative α- melanocyte stimulating hormone (αMSH) and the appetite stimulating peptide galanin. Thus PVN plays a role in the integration of nutritional signals with the thyroid and hypothalamic-pituitary axis [23]. The PVN is highly sensitive to administration of many appetite regulatory- peptides, e.g. cholecystokinin (CCK) [24], NPY [25], ghrelin [26], orexin-A [27, 28], leptin [29, 30] and GLP-1 [29]. Electro-physiological studies in the PVN have shown that neurons expressing NPY/AgRP attenuate inhibitory GABA-ergic signalling, whereas POMC neurons potentiate GABA-ergic signalling [31]. GABA-ergic signalling also occurs in a subpopulation of ARC NPY neurons which release GABA locally and inhibit POMC neurons. Lesions of either the VMH or the PVN produce impressive syndromes of hyperphagia and obesity, but it is not entirely clear whether these syndromes are due to damage to neurons themselves or to fibres passing through these regions [23]. (d) The Dorsomedial Hypothalamus (DMH) has extensive connections with other hypothalamic nuclei, including the ARC, from which it receives AgRP/NPY projections [32]. Integration of signals may also take place in the DMH, as α-MSH-positive fibres are in close proximity to NPY-expressing cells in the DMH, and melanocortin agonists attenuate DMH NPY expression and suckling-induced hyperphagia in rats [33]. Electrolytic lesions in the DMH disrupt feeding to a far less extent than lesions in the VMH [34]. A crucial role of neurons in the DMH has been indicated by the observation that inhibition of NPY-induced feeding by leptin enhances neuronal c-fos, the protein product of the immediate early gene and a marker of neuronal activation [30, 35]. (e) The Lateral Hypothalamic Area (LHA) is the classical ‗feeding centre‘. It has a lower density of cell bodies than the obvious nuclei but includes neurons expressing MCH and the orexins. It also contains numerous fibre systems projecting to and from the medial hypothalamus, brainstem structures concerned with various visceral functions and with relaying taste and gastric distension and locus coeruleus concerned with arousal and the sleep-wake cycle [36]. It also contains glucose-sensitive neurons that are stimulated by hypoglycemia (by ascending pathways from brainstem) and it is crucial in mediating the marked hyperphagia which is normally induced by hypoglycemia [36]. The relative positions of the important Central Nervous System nuclei with their important neuropeptides are shown in figure 1.

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Appetite Control- The Role of Central and Gut Neuropeptides

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Figure 1. Schematic diagram showing the relative position and communication between different central Nervous System Nuclei (Hypothalamic Brain Stem and Reward Centres).

Figure 2. Diagrammatic model of appetite regulation by Central and peripheral neuropeptides.

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The Brainstem The hypothalamus and brainstem are linked via projections from the NTS neurons to the PVN and lateral hypothalamus, such as GLP-1 neurons and the projections of serotoninergic neurons of the Raphe nuclei to the ARC [37-39]. In addition to interacting with hypothalamic circuits, the brainstem also plays a principal role in the regulation of energy homeostasis. Like the ARC, the NTS is in close anatomical proximity to a circumventricular organ with an incomplete blood–brain barrier – the area postrema [40] and is therefore in an ideal position to respond to peripheral circulating signals, in addition to receiving vagal afferents from the gastrointestinal tract [41-43]. The NTS has a high density of NPY-binding sites [44], including Y1 receptors [45] and Y5 receptors [46]. Extracellular NPY levels within the NTS fluctuate with feeding [47], and NPY neurons from this region project forward to the PVN [48]. There is also evidence for a melanocortin system in the NTS, separate from that of the ARC as evidenced by the presence of MC4R receptor in NTS [49, 50]. POMC-derived peptides are synthesized in the NTS of the rat [49, 51, 52], and caudal medulla in humans [53], and these POMC neurons are activated by feeding and by peripheral CCK administration [54]. The role of brainstem in appetite and feeding regulation has been examined using experimental decerebrate rats in which connections between the brainstem and forebrain are severed surgically [55]. The decerebrate rats were able to compensate for changes in the composition of individual meals offered to them. However, when challenged with a reduction in meal number from three to two per day, intact rats compensated by increasing their food intake at each meal, but the decerebrate rats failed to adjust their meal size. Thus while the brainstem plays a role in individual meal size, the hypothalamus is required for long-term energy balance and appetite regulation.

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The Reward Pathways The rewarding nature of food may act as a stimulus to feeding, even in the absence of an energy deficit. The sensation of reward is, however, influenced by energy status, as the subjective palatability of food is altered in the fed, compared with the fasting, states [56]. Thus, signals of energy status, such as leptin, are able to influence the reward pathways [57]. The reward circuit is complex and involves interactions between several signalling systems. The dopaminergic system is integral to this circuit. The influence of central dopamine signalling on feeding is thought to be mediated by the D1 and D2 receptors [58]. Mice which lack dopamine, due to the absence of the tyrosine hydroxylase gene, have fatal hypophagia. Dopamine replacement, by gene therapy, into the caudate putamen restores feeding, whereas replacement into the caudate putamen or nucleus accumbens restores preference for a palatable diet [59]. Opioids also play an important role,since lack of either enkephalin or ß-endorphin in mice abolishes the reinforcing property of food, regardless of the palatability of the food tested. This reinforcing effect is lost in the fasted state, indicating that homeostatic mechanisms can override the hedonistic mechanisms [60]. In man, opiate antagonists are found to reduce food palatability without reducing subjective hunger [61]. The nucleus accumbens is an important component of reward circuitry. Injections of opioid agonists and dopamine agonists into this region preferentially stimulate the ingestion of highly palatable foods such as sucrose and fat [62, 63]. Conversely, opioid receptor

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antagonists injected into the nucleus accumbens reduce the ingestion of sucrose rather than less palatable substances [62]. The reciprocal GABA-ergic connections between the nucleus accumbens and LHA may mediate hedonistic feeding by disinhibition of LHA neurons [64]. The MCH neurons in the LHA may reciprocally influence the reward circuitry, as the nucleus accumbens is a site which expresses MCH receptors [65].

ROLE OF CENTRAL NEUROPEPTIDES IN APPETITE REGULATION As discussed above, the hypothalamus being the central feeding organ mediates regulation of short-term and long-term dietary intake. However, rather than specific hypothalamic nuclei controlling energy homeostasis, it is now thought to be regulated by neuronal circuits, which signal using specific orexigenic and anorectic neuropeptides. These compounds bind and activate their Central Nervous System (CNS) receptors, triggering downstream pathways/ regulators that result in appropriate changes in ingestive behavior. Complex interactions exist between pathways, such that absence of one regulatory factor may be compensated by alterations in other factors to maintain appetite regulation [66].

Central Orexigenic Neuropeptides

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A few of the appetite stimulating neuropeptides of recent interest include NPY, the orexins, melanin concentrating hormones (MCH), galanin, endorphins, Agouti-related peptide (AgRP), Growth Hormone Releasing Hormone (GHRH) and γ- amino butyric acid (GABA).

1. Neuropeptide Y Neuropeptide Y (NPY) contains 36 amino acid residues, including a tyrosine at each end (hence ‘Y‘, the code for Tyrosine) [67 ]. NPY is one of the most abundant peptides of the hypothalamus [68] and one of the most potent orexigenic factors [27]. Although NPY can produce diverse effects on behavior, cardiovascular regulation and control of neuro-endocrine axes, affective disorders, seizures and memory retention [69], its most noticeable effect is the stimulation of feeding after central administration [70]. Hypothalamic levels of NPY reflect the body‘s nutritional status. The levels of hypothalamic NPY mRNA and NPY release increase with fasting or increased metabolic demand such as starvation, insulin-dependent diabetes mellitus, lactation and physical exercise [70] and decrease after refeeding [71,72]. The ARC is the major hypothalamic site of NPY expression [73]. ARC NPY neurons project to the ipsilateral paraventricular nucleus (PVN) [74]. Repeated intracerebroventricular (ICV) injection of NPY into the PVN causes hyperphagia, and obesity [75, 76]. Central administration of NPY also reduces energy expenditure, resulting in reduced brown fat thermogenesis [77], suppression of sympathetic nerve activity [78] and inhibition of the thyroid axis [79]. It also results in an increase in basal plasma insulin level [75, 80] and morning cortisol level [75], independent of increased food intake. Five G- protein coupled NPY receptors have been identified Y1, Y2, Y4, Y5 and Y6 that mediate their actions in the hypothalamus either by decreasing adenylate cyclase and consequently decreasing cAMP levels and increasing intracellular calcium [81,82]. These

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NPY receptors are found with individual distribution patterns in many hypothalamic neurons including neuroendocrine motor neurons, magnocellular neurosecretory neurons and numerous other neurons connecting the hypothalamus with the limbic and the autonomic nervous system [83]. Y5 receptors in particular have been implicated as important receptors that mediate the feeding effects of NPY [84, 85]. The Y5 receptor is expressed at relatively high levels in the LHA, close to the site where NPY acts most potently to stimulate feeding [67]. NPY receptor density in this area is decreased during starvation, which may be explained by down regulation of these receptors following increased local availability of NPY [72]. Administration of antisense oligonucleotides to the Y5 receptor inhibits food intake [86], and Y5 receptor-deficient mice have an attenuated response to NPY and hence develop late – onset obesity [84]. However, antagonists to the Y 5 receptor have no major feeding effects in rats [87]. NPY-induced and fast-induced feeding is prevented by antagonists to the Y1 receptor [88, 89], and is reduced in Y1 receptor- knockout mice [90]. ARC Y1 receptor numbers, distribution and mRNA, are reduced during fasting, but this effect is attenuated by administration of glucose [91]. Furthermore, NPY fragments with weak affinity to the Y1 receptor elicit a dose-dependent increase in food intake to NPY [92]. Y1 receptor-deficient mice are obese, but are not hyperphagic, suggesting that the Y1 receptor may affect energy expenditure rather than feeding [93]. The presynaptic Y2 and Y4 receptors have an auto-inhibitory effect on NPY neurons [94, 95]. Y2 receptor-knockout mice have increased food intake, weight and adiposity [96]. However, Y2 receptor conditional-knockout mice (perhaps with more normal development of the neuronal circuits) have a temporarily reduced body weight and food intake, which returns to normal after a few weeks [97]. There is also evidence for a role of Y4 receptors in the orexigenic NPY response. NPY and other orexigenic peptides like AgRP, GABA and adrenergic transmitters, initiate appetitive drive directly through Y1, Y5, GABAA and α-1 receptors, co-expressed in the magnocellular neurosecretory neurons and ARC neurons and by simultaneous repression of anorexigenic melanocortin signaling in the ARC [98]. NPY synthesis in the ARC and its release into the PVN, are regulated by afferent signals such as leptin, insulin (both inhibitory), and glucocorticoids (stimulatory). The NPY neurons express long form of leptin receptor and are potential hypothalamic targets for leptin [99]. Insulin receptors are expressed in the mediobasal hypothalamus, and median eminence, and insulin has been shown to inhibit NPY synthesis and secretion in the PVN: however, it is not clear whether insulin receptors are actually carried by the NPY neurons or by the neurons that impinge on them [72, 100, 101]. Circadian and ultradian pattern of NPY secretion and corresponding reciprocal circadian and ultradian rhythmicities of peripheral neuropeptides like anorectic leptin from adipocytes and orexigenic ghrelin from stomach determine the daily meal pattern [98]. A primary physiological role of the ARC NPY neurons may thus be to restore normal energy balance and body fat stores under conditions of energy deficit, the signals of which are falling leptin and/or insulin occurring in these conditions. Although NPY seems to be an important orexigenic signal, NPY-null mice have normal body weight and adiposity [102], although they demonstrate a reduction in fast-induced feeding [103]. This absence of an obese phenotype may be due to the presence of compensatory mechanisms or alternative orexigenic pathways, such as those which signal via AgRP [104].

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By contrast, dietary obesity induced by voluntary over-eating of highly- palatable diet is not accompanied by obvious increases in the activity of ARC NPY neurons; Indeed there is some evidence that their activity may be inhibited thus attempting to restrain overeating palatable food [105]. It is possible that there is evolutionary redundancy in orexigenic signalling in order to avert starvation. This redundancy may also contribute to the difficulty in elucidating the receptor subtype that mediates NPY-induced feeding [106].

2. Melanin- Concentrating Hormone Melanin-concentrating hormone (MCH) is an orexigenic cyclic 19 amino acid neuropeptide. MCH was initially discovered in salmon pituitaries as a regulator of skin color change [107]. The cell bodies of MCH-containing neurons are mainly present in the lateral hypothalamus and zona incerta that are recognized as the feeding center of mammalian brain and project into several hypothalamic and limbic areas [70, 108-111]. MCH receptors, MCH-1R and MCH-2R are also widely distributed in the brain areas, especially in the hippocampus, amygdala and cerebral cortex. MCH augmented ongoing feeding, fasting stimulated MCH gene expression in the hypothalamus, and MCH mRNA was elevated in genetically obese ob/ob mice [112]. MCH administration at the onset of the dark phase also potentiated ongoing nocturnal feeding for 4–6 h[112]. MCH also stimulated the hypothalamo-pituitary-adrenal axis [113]. Microinjection of MCH into the zona incerta-LH region reduced feeding [114]. In contrast, Rossi et al.[115] confirmed the orexigenic effects of MCH in rats, but relative to NPY, MCH-induced feeding was small and of short duration. Further, despite the acute stimulatory effects of MCH, cumulative 24-h intake was unaffected, and repeated daily injections stimulated food intake for a few days without changing the body weight. Diet-induced and genetically obese animals have increase in MCH tone in the brain which is suppressed by leptin treatment. MCH-transgenic mice exhibit obese syndromes when fed on high-fat diet. On the other hand, the MCH- or MCH-1R-deficient mice showed the resistance to high-fat diet induced obesity. Furthermore, MCH produces anxiety and increases the hippocampal synaptic efficacy, resulting in the enhancement of learning and memory processes. Non-peptide antagonists for MCH-1R prevented the high-fat diet-induced obesity, and possess anti-anxiety and antidepressant effect. These finding indicate the involvement of MCH in the development of obesity, memory and emotion. MCH receptor antagonist might be useful for the treatment of obese syndrome including psychological disorder related obesity [116]. 3. Glutamate and Γ-Aminobutyric Acid Glutamate and the inhibitory amino acid γ-aminobutyric acid (GABA), the most abundant neurotransmitters in the hypothalamus [117-120], have been shown to stimulate feeding in the rats. Horvath et al. have [121] shown that GABAergic fibers form synaptic contacts with βEndorphin containing neurons in the ARC that project into the diverse sites, raising the likelihood that GABAergic synapses regulate the output of POMC-derived peptides- α-MSH and β-END . More recent observations indicate coexpression of GABA in NPY- and GALproducing subpopulations of neurons in the ARC [122] with projections of NPY and GABA expressing neurons into the PVN [123]. N-methyl-D-aspartic acid (NMDA) (a glutamate receptor agonist), stimulates immediate and transient feeding lasting for about 10 min when injected into LHA [124,125]. Thus, excitation of neural pathways originating and/or traversing the LH by NMDA may stimulate

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the release of orexigenic signals such as NPY, GAL, opioids, and orexins; however, since NMDA-induced feeding was short lived as compared with that induced by peptides, the possibility that neuropeptides mediate the NMDA-induced feeding is highly unlikely. In contrast, microinjection of muscimol, the GABAA receptor agonist, into several hypothalamic sites, e.g., VMN, DMH and PVN, readily stimulated feeding lasting for 30 min [126-129]. The β-subunit of GABAA receptors has been found to be localized within the POMC-immunopositive neurons [130], where POMC gene expression and α-MSH release have been found to be inhibited by muscimol and GABA [131], suggesting of an interplay of GABA with other orexigenic and anorexigenic signals. Because injections of NPY and muscimol either intraventricularly or directly into the PVN elicited a synergistic feeding response [123], it is likely that corelease of NPY and GABA in the PVN and neighboring sites may amplify feeding. On the other hand, GABA mediates inhibitory synaptic transmission in the brain [117]. Therefore, the alternate possibility that GABA may inhibit a tonic restraint to evoke feeding either on its own or in conjunction with NPY and other orexigenic signals cannot be excluded [122- 123]. Biphasic responses to GABA, an initial inhibition followed by excitation, are observed either when large amounts of GABA are employed or when inhibitory synapses are activated at high frequency, causing depolarization of postsynaptic contacts to trigger an action potential [132,133]. Further studies devoted to understanding the precise mechanism of GABA involvement are needed to clarify its role in the daily patterning of feeding behavior and in the peptidergic orexigenic network.

4. Orexins The orexins are a class of neuropeptides that were earlier described as hypocretins [134,135]. Orexin A and orexin B are 33- and 28- amino acid peptides, respectively, sharing 46% identity. Both peptides are coded by the same gene, and are localized in neurons in the dorsal and lateral hypothalamic areas and perifornical hypothalamus. [136, 137]. The orexins activate two closely related and highly conserved G- Protein coupled receptors termed orexin1 and orexin-2 receptor (OX1R and OX2R respectively). While orexin A has equal affinity for both the recptors , Orexin B has 10 times higher affinity for OX2R [134,138]. OX2R is found mainly in PVN, but is expressed widely in the hypothalamus including ARC, VMH and Suprachiasmatic Nucleus (SCN). Activation of these receptors in hypothalamic cells leads to a marked increase in intracellular Ca2+ levels, a post-synaptic effect mediated via stimulation of a Gq G- protein and protein kinase C [139]. In the peripheral tissues, OX1R is expressed mainly in the brown adipose tissue and OX2R is expressed in the adrenal medulla [140]. Orexin neurons project throughout the central nervous system (CNS) to nuclei known to be important in the control of feeding, sleep-wakefulness, neuroendocrine homeostasis, and autonomic regulation [141]. Central administration of orexins is also associated with increased EEG arousal and wakefulness, locomotor activity, grooming, sympathetic activity, metabolic rate and stimulated feeding in a dose-related fashion and pain-thresholds. [134, 140]. The orexin system is selectively activated by signals that indicate severe nutritional deficit; hence it would be highly adaptive for a hungry animal not only to seek sustenance but also to remain fully alert to dangers in the environment [140]. Orexin mRNA expression is upregulated by fasting and insulin-induced hypoglycemia. C-fos expression in orexin

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neurons, an indicator of neuronal activation, is positively correlated with wakefulness and negatively correlated with rapid eye movement (REM) and non-REM sleep states [141]. These data suggest that orexin-1 receptors mediate the episodic signaling of satiety and appear to bridge the transition from eating to resting in the feeding-sleep cycle [140]. Furthermore, it is likely that orexin-mediated food intake results partly from stimulation of feeding pathways in the hypothalamus such as those involving the NPY pathway. Recent electrophysiological studies have shown that orexin neurons are regulated by metabolic cues, including leptin, glucose, and ghrelin. Crucial evidence indicates that orexin-A increases food intake by delaying the onset of a behaviorally normal satiety sequence. Selective orexin-1 receptor antagonists suppress food intake and advance the onset of a normal satiety sequence [140]. The close relationship between orexin –A fibers and the surface of the cerebral ventricular system suggests that orexin –A may be released directly into the cerebrospinal fluid, where it could interact with other appetite –regulating factors (e.g. leptin and insulin) or perhaps have a neurohormonal role via volume transmission. [142]. Thus, orexin neurons have the requisite anatomical connections and interactions with hypothalamic feeding pathways, and regulation by circadian and nutritional factors to suggest that they may be an important cellular and molecular link in the integration of sleep and energy homeostasis [136]. Orexin may also play a role as a peripheral hormone involved in energy homeostasis. Orexin neurons, expressing both orexin and leptin receptors, have been identified in the gastrointestinal tract, and appear to be activated during starvation [143]. Orexin is also expressed in the endocrine cells in the gastric mucosa, intestine and pancreas [143] and peripheral administration increases blood insulin levels [144].

5. Agouti-Related Peptide AgRP is 132-amino acid peptide that has generated intense interest because of evidence of its role in the regulation of feeding and body weight [145]. AgRP has sequence similarity to the product of the Agouti coat color gene in mice, a paracrine-signaling molecule produced normally in the skin that inhibits the effect of -Melanocyte Stimulating Hormone (αMSH), on MC-1 receptor [146]. Instead of being expressed only at a certain time during hair growth, Agouti is constitutively expressed throughout the body of yellow Agouti (Ay) mice, and this ectopic Agouti expression gives rise to pleiotropic effects including yellow coat color, obesity, insulin resistance, hyperglycemia, and increased body length. AgRP is a potent and selective antagonist of MC-3 and MC-4 receptors [147], the melanocortin receptors implicated in control of energy balance. AgRP enhances appetite by antagonism of α-MSH binding to the MC4R [148, 149]. The inhibition of melanocortin receptors may thus lead to the obese phenotype that is associated with hyperphagia, decreased thermogenesis, and increased caloric efficiency [54, 150]. AgRP expression increases markedly in ob/ob and db/db mice [151,152] and transgenic mice with ubiquitous AgRP expression develop an obesity syndrome analogous to those of the Ay and MC-R ‗knockout‘ mice [152]. Mice homozygous for null mutations of Agouti do not display abnormalities of weight regulation [145]. Humans also have an agouti gene that is normally expressed in adipose tissue [153]. Studies have also shown that central administration of AgRP exerts changes in hypothalamic neuropeptides gene expression and metabolic effects that are independent of the effects on food intake and body weight. AgRP is expressed only in the ARC of the hypothalamus in the brain, and all of the AgRP-producing neurons are NPY-positive and

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project to various hypothalamic (such as PVN and DMH) and extra hypothalamic sites and are inhibited by leptin [18, 154 -156]. Like NPY, expression of AgRP is up-regulated in leptin deficiency due to fasting or mutation [18, 145]. In contrast to potent but short-lived effects of NPY, central administration of AgRP in rodents leads to increase in food uptake for upto 1 week [157]. Recent studies suggest that at least part of the long-term actions of AgRP may be independent of competitive antagonism of MC3/4R and may involve additional mechanisms such as prolonged downstream signaling changes initiated by MC3/4R antagonism, inverse agonism of MC3/4R, or interaction with an unknown receptor [158]. Intracerebroventricular injection of AgRP or the C-terminal peptide AgRP (62, 121) stimulated food intake [159]. Chronic administration of AgRP in rodents has been shown to cause sustained hyperphagia and leads to obesity [160]. Studies by Huang et al. [22] have reported that 22 weeks of high-fat diet significantly reduced hypothalamic arcuate nucleus AgRP mRNA expression and increased MC4R expression. Similarly, Tritos et al [161] reported a suppressed AgRP mRNA expression in obese mice with brown adipose tissue deficiency.

6. Galanin and Galanin Like Peptides Galanin is a neuropeptide which is not a member of any known family of neuropeptides, despite repeated efforts to discover related peptides. It is a 29 amino acid C-terminally amidated (30 amino acid, non-amidated in humans), highly conserved but unique neuroendocrine peptide originally isolated from intestine. The first 14 amino acids are fully conserved in almost all species. The first 16 N-terminal amino acids appear to contain galanin agonist activity on increasing food consumption [162]. Galanin is found in the brain (ARC, DMH, and PVN of the hypothalamus) and the gut. It modulates a variety of physiological processes including cognition/memory, sensory/pain processing, neurotransmitter/ hormone secretion, and feeding behavior [163, 164]. Its central actions are mediated via Gi-proteincoupled receptors and ion channels and peripheral actions through inhibition of gastric neuropeptides via potassium channels [165]. Galanin coexists with GABA, noradrenaline, 5hydroxytryptamine (5-HT), and NPY in several regions of the brain [164]. In many respects, the inhibitory actions of galanin are similar to γ-aminobutyric acid (GABA) and neuropeptide Y (NPY). Like MCH and orexin, galanin-induced feeding is less remarkable than that of NPY, and continuous galanin infusion was ineffective in inducing sustained hyperphagia and obesity [166]. Evidence suggests that hypothalamic galanin (GAL) has a variety of functions related to energy and nutrient balance, body weight regulation, reproduction, water balance, and neuroendocrine regulation [164]. Many galanin-positive fibers as well as galanin-positive neurons have been demonstrated in the dorsal vagal complex, suggesting that galanin produces its effects by involving vagal neurons [165].Acute central administration of galanin has been reported to increase fat consumption. Studies of the newly discovered galanin family peptide, ‗galanin-like peptide‘ (GALP), highlight the likely role of galanin peptides and receptors in the physiological coupling of body weight, adiposity and reproductive function [167]. GALP shows sequence homology to galanin and binds to galanin receptors in vitro [168]. GALP neurons express leptin receptors and respond to leptin treatment by increasing their expression of GALP mRNA. GALP is produced by a discrete population of neurons within the basomedial ARC (and median eminence) that send projections to the anterior PVN and makes close contact with leutinizing hormone-releasing hormone (LHRH) neurons in basal forebrain. Centrally administered

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GALP activates LHRH-immunoreactive neurons and increases plasma LH levels. These findings suggest a direct stimulatory action of endogenous GALP on gonadotropin secretion via actions within the hypothalamus/basal forebrain, with leptin actions linking this system to body adipose levels [167].

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7. Endogenous Opioids The opioid system is composed of three families of biologically active peptides, bendorphin, dynorphin, and enkephalins and their receptors, l-opioid receptor, j-opioid receptor, and d-opioid receptor, respectively [32, 157, 169,170]. Opioid peptides mediate the hunger component in the control of food intake [171]. Opioid peptides may potentiate fat as well as protein ingestion [172]. b- Endorphin, derived from precursor POMC, and dynorphin from prodynorphin, stimulate feeding after central administration [6, 32,171]. POMC neurons are localized in the ARC and innervate the PVN, VMH, and other areas of the hypothalamus, where microinjection of b-endorphin and opiate agonists that bind to the l-opioid receptors stimulate feeding [32, 171]. Dynorphin producing neurons are also found in various regions of the hypothalamus, including the ARC and PVN. The opioid receptor antagonists, especially the l- and j- antagonists decreased feeding in animals and humans [6]. Antagonists such as naloxone and naltrexone decreased body weight during chronic administration, and were more potent in decreasing food intake and weight gain in obese than in lean rodents [171]. b-Endorphin reduces sympathetic nerve activity thus having a potential role in thermogenesis [173]. Although the opioid-evoked feeding is modest, b-endorphin in particular may represent an important interconnected orexigenic signal [32]. b-endorphin may be situated downstream from NPY, galanin, and GABA because all three molecules stimulate b-endorphin release in the hypothalamus, and opioid antagonists such as naloxone inhibit feeding stimulated by any one of the three [6, 32]. Opioid peptides may provide the palatability and rewarding aspects of feeding rather than those for energy needs [169]. 8. Endocannabinoids Over past centuries, Cannabis sativa (D9-tetrahydrocannabinol) has been used extensively for both medicinal and recreational uses [174]. Cannabis also has many pleasurable effects in elevating mood and diminishing stress. There is historical support for the role of marijuana (i.e. exogenous cannabinoids) in regulation of appetite. The search for the endogenous receptor for the psychoactive component of Cannabis sativa has led to the discovery of physiological endocannabinoids (anandamide, NADA, 2- arachidonylglycerol (2-AG), noladin ether and virodhamine) and physiological ‗‗cannabinoid‘‘ signaling system that acts on at least 2 receptors: CB1 and CB2 [174-176].These receptors are located not only in pleasure centers of the central nervous system, but also in many organs associated with feeding and energy regulation, such as the hypothalamus and the gastrointestinal tract [176]. In a number of species, including human beings, the administration of exogenous and endogenous cannabinoids leads to robust increases in food intake and can promote body weight gain. These effects are believed to be mediated through activation of the CB1 receptor [174]. The endocannabinoids appear to regulate energy balance and food intake at four functional levels within the brain and periphery: (i) limbic system (for hedonic evaluation of foods), (ii) hypothalamus and hindbrain (integrative functions), (iii) intestinal system, and (iv) adipose tissue. At each of these levels, the endocannabinoid system interacts with a number of

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other neuropeptides involved in appetite and weight regulation, including leptin, ghrelin, and the melanocortins [175]. Functional relationships between cannabinoids and leptin have been demonstrated [177], and endocannabinoid synthesis may be regulated by leptin. Thus, leptin administration, which exerts an anorectic action, suppresses hypothalamic endocannabinoid levels in normal rats, while genetically obese, chronically hyperphagic rats and mice express elevated, leptinreversible, hypothalamic anandamide or 2-AG levels [177]. These findings provide evidence for the role of the hypothalamic endocannabinoid system in food intake and appetite regulation [176]. Experiments with selective CB1 receptor antagonists (e.g. Rimonabant, SR141716) have demonstrated reductions in food intake and body weight with repeated compound administration. These reductions in body weight appear to be greater in obese animals and may be the result of a dual effect on both food intake and metabolic processes [174].

9. Fatty Acid Synthase Fatty acid synthase (FAS) catalyzes the condensation of acetyl-CoA and malonyl-CoA to generate long-chain fatty acids in the cytoplasm. FAS inhibition has been shown to facilitate weight loss through increased peripheral utilization of fat as well as reduction of food intake [178]. FAS is expressed in various regions of the brain, including ARC and PVN. FAS is colocalized with NPY in neurons in the ARC. Fasting down-regulates liver FAS, but levels remain high in hypothalamus even in the fasting state suggesting different regulatory mechanisms. C75, a specific inhibitor of FAS, may alter food intake via interactions within the ARC-PVN pathway mediated by NPY [179]. In obese mice, C75 rapidly suppressed food intake, reduced body weight, and normalized obesity-associated hyperglycaemia and hyperinsulinaemia. The suppressive effect of C75 on food intake in lean mice seems to be mediated both by NPY/AgRP and POMC/CART neurons, whereas in obese mice the effect seems to be mediated primarily by NPY/AgRP neurons [180]. C75 blocks the normal, fasting- associated, hypothalamic increases in NPY/ AgRP expression and the decrease in POMC/ CART expression. In both lean and obese mice, C75 markedly increases expression of MCH and its receptor in the hypothalamus. While acute C75 treatment in lean mice produce changes in NPY, the reduced food consumption in chronic C75-treated DIO (dietinduced obesity) mice was accompanied by an increase in CART expression and not by changes in NPY [181]. A low dose of C75 administered for 30 days in ob/ob mice reduced food intake by 62% and body weight by 43%, whereas body weight of ad lib-fed controls increased by 11%. Decreased food intake correlated with decreased expression of hypothalamic neuropeptide mRNAs for NPY, AGRP, and MCH and an increased expression of neuropeptide mRNAs for α-MSH (POMC) and CART [182]. Intraperitoneal injection of C75 causes a decrease in food intake by approximately 95% which may persist for at least 24 hours. Intraperitoneal C75 administration seems to work in two phases, a rapid initial phase via the NTS area postrema of the brainstem and a delayed phase via the ARC, LHA, and PVN of the hypothalamus. The latter phase correlates well with its ability to interfere with the fasting-induced effects on the expression of orexigenic (NPY and AgRP) and anorexigenic (POMC, α- MSH) and CART) messages in the hypothalamus [183]. The extensive anatomical and experimental evidence detailed above clearly implies that orexigenic signals do not act one at a time, but rather an interconnected orexigenic network

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integrates the hypothalamic regulation of daily food intake. The connectivities of NPY neurons with other orexigenic signals, coupled with the coexpression and corelease of these signals, exemplify the operational complexities of the orexigenic network in the hypothalamus.

Central Anorectic Peptides

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Negative regulators of appetite / anorexigenic signal-producing pathways orchestrate neural events for dissipation of appetite and to terminate feeding, possibly by interrupting NPY efflux and action at a postsynaptic level within the hypothalamus. It is possible that some of these may represent the physiologically relevant "off" switches under the influence of GABA alone, or AgRP alone, or in combination with NPY released from the NPY-, GABA-, and AgRP-coproducing neurons. The various central anorectic peptides include:

1. Corticotropin Releasing Factor (CRF) and Related Peptides Corticotropin releasing factor (CRF) is a 41-amino acid mammalian neurohormone that is best known as the major physiological regulator of pituitary ACTH secretion. In addition, it stimulates complimentary stress-related endocrine,autonomic, and behavioral responses [184186]. There is considerable evidence indicating that CRF is an endogenous anorectic and thermogenic agent [187]. CRF secretion modulates food intake in the absence of stress by exerting an inhibitory tone on appetite [188]. CRF mediates its actions through interaction with two distinct receptor subtypes, CRF-1 and CRF- 2, which have been cloned and characterized [186, 189]. CRF-2 receptor is primarily involved in the feeding-suppressive and thermogenic response to CRF and CRF-related peptides [190, 191]. Abundant CRF-2 expression is demonstrated in the VMN (ventromedial nucleus). CRF-2 expression is downregulated by increased food intake and up-regulated by reduction in food intake. Both CRF and NPY may exert local site-specific effects on feeding behavior within the PVN relative to the extra hypothalamic site that constitutes a sensitive substrate for nonappetite behavioral actions of these peptides [192]. In addition to coordination of anorectic and thermogenic effects, CRF is also sensitive to the action of peripheral peptides signaling the brain about the fluctuations in energy reserves especially leptin. Leptin has been reported to reduce CRF expression in the PVN of leptin-deficient obese rodents thus, inhibiting the hyperactivity of the hypothalamic pituitary adrenal axis and the resultant energy deposition. Leptin has also been reported to increase the expression of the CRH type 2[a] in the VMH, a key structure in the control of insulin secretion and in the regulation of energy balance [187]. CRF injection into the PVN inhibits NPY-induced feeding, while injection elsewhere did not, suggesting that the PVN could be the target for the actions of CRH on appetite suppression [170, 192- 194]. Chronic administration of CRF causes sustained anorexia and progressive body weight loss [194]. CRF decreases feeding stimulated by GABA agonists, norepinephrine, dynorphin, and NPY [195]. Conversely, pharmacological blockade of CRF receptors in hypothalamus using antagonists or antisense oligonucleotides, immunoneutralization, or immunotoxin enhances basal and NPY-stimulating feeding, suggesting that CRF may tonically restrain the actions of orexigenic signals [196, 197]. Finally, the CRF system appears to demonstrate plasticity in obesity and in response to food deprivation that is consistent with its action on food intake and thermogenesis. The

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observations have been made that food deprivation and obesity can blunt the expression of the CRF type 2[a] receptor in the VMN and can induce the expression of the CRF-binding protein (a CRF-inactivating protein) in brain areas involved in the anorectic and thermogenic actions of CRF [187]. Stress with its increased cortisol levels might decrease CRH and increase appetite leading to obesity with chronic stress due to comfort eating in a subset of individuals [198]. Two identified endogenous ligands for CRF-2 receptors indicated in mediation of anorexic and vascular responses in the stress are human Stresscopin (SCP) and Stresscopinrelated peptide (SRP). These are able to suppress food intake, delay gastric emptying and decrease heat-induced edema. The gene of SCP and SRP are expressed in central and diverse peripheral tissues. Because CRF-2 is believed to be important in the regulation of the recovery phase of the stress response, SCP and SRP might be important in protecting the organism from damage incurred by prolonged or excessive exposure to stress. Urocortin is a 40-amino acid peptide and a potent activator of CRF-2 rather than CRF-1 receptors [111, 199]. Urocortin reduces food intake and promotes weight loss at doses that do not activate the stress response [199, 200]. Unlike CRF and Urocortin, SCP and SRP have minimal effects on ACTH release and the resultant elevations in glucocorticoids [201]. Almost all obesities depend on the presence of adrenal glucocorticoids and an over activity of type II corticosteroid receptors [202]. Glucocorticoids also stimulate food intake by inhibiting CRF while facilitating NPY actions [188]. All types of hyperphagia and obesity syndromes are reversed or prevented by adrenalectomy and can be readily restored by steroid replacement [203] providing further evidence in support of the role of CRH system in control of feeding.

2. Cocaine and Amphetamine Regulated Transcript CART is a relatively new neuropeptide which appears to be a powerful physiological anorexic signal. The high conservation of CART across species suggests that it has an important role in mammalian physiology [204]. The gene for CART peptides has now been characterized in both humans and mice [205,206] along with several CART peptides produced through posttranslational modifications [207]. Human and rat CART mRNA share 92% sequence identity. In the rat, a long and a short splice variant of the CART peptide are produced, whereas humans only produce the short form: CART (1–89) [208]. CART mRNA were identified on the basis of their increase following cocaine or amphetamine treatment in rats [209]. The CART peptides are localized in specific areas of the hypothalamus including the periventricular nucleus, PVN, DMN, perifornical regions, lateral nucleus, and ARC. In the PVN, CART mRNA is colocalized with vasopressin and CRF- containing neurons [210]. CART neurons are also associated with reinforcement and reward, sensory processing [211], stress and endocrine regulation [212], and feeding [213]. There is evidence that CART and leptin pathways are linked [214]. Intra Crebroventricular (ICV) administration of CART (42– 89), (particularly in 4th ventricle) results in neuronal activation in the PVN, rich in CRH and TRH and thus, reduces normal and fast-induced feeding in rats [208, 215-217]. The CART peptides are colocalized with leptin receptors in hypothalamic neurons, both fa/fa rats and ob/ob mice have reduced levels of CART mRNA in the ARC, and administration of leptin to ob/ob mice increased CART mRNA [208, 212, 218]. Fasting or diabetes attenuates CART mRNA expression in the hypothalamus, demonstrating that CART mRNA regulation is related to the fuel availability and peripheral hormonal status [210]. Administration of CART antiserum increases nighttime feeding [217]. There is a decrease in arcuate nucleus CART

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mRNA following food deprivation. Interestingly, CART administration blocks the NPYinduced feeding in fasted and normal rats [208]. Mice with a targeted deletion of the CART gene become obese when fed a high fat diet, than wild type littermates [219]. A delay of up to 14 weeks has been noted for this effect on weight gain to be produced highlighting the crucial contribution of environmental factors to obesity production in this mouse model. Chronic over-expression of CART in the ARC increases the thermogenic responses in the rat. Chronic cold increases Arcuate CART levels [220]. CART injection centrally reduces gastric emptying and motility [221] contributing to its actions on food intake. This effect seems to be CRF dependent [222]. CART also co-localises with CB1 cannabinoid receptor [223]. CB1 knock out mice have lower levels of CART mRNA in the DMN and lateral hypothalamus. Glucocorticoids regulate CART expression in the hypothalamus [224], pituitary [225] and blood [226]. CART is detectable in circulation, and is thought to be from a pituitary source [226] with a possible contribution from the gut. CART levels in blood show a circadian rhythm. Fasting increases blood levels of CART. Adrenalectomy reduces CART levels. Replacement of corticosteroids reverses the effect of adrenalectomy. CART rhythm shows similarity to corticosteroid rhythm with a morning peak in primates [226]. CART receptors need to be identified to further our understanding of its physiological role. CART levels and distribution in lean and obese humans also needs to be defined.

3. Glucagon-Like Peptides Preproglucagon gene expression is limited to a-cells in the pancreas, L cells in the gut, and neurons in the brain stem NTS. Whereas post-translational processing of proglucagon in the pancreas leads to the formation of glucagon and the major proglucagon fragment, proteolytic cleavage in the L cells of the gut and in the NTS yields the peptides glicentin, oxyntomodulin, glucagon-like peptide (GLP)-1,and GLP-2 [227]. GLP-1 (7–36 amide) and GLP-2 are both involved in a wide variety of peripheral functions, such as glucose homeostasis, gastric emptying, intestinal growth, insulin secretion as well as the regulation of food intake [228,229]. After a meal, GLP-1 and GLP-2 are secreted in parallel in the circulation. Intravenous (IV) GLP-1 has an inhibitory effect on gastric emptying, hunger and food intake in man [230]. GLP-1 containing nerve fibres and the GLP-1 receptor are found predominantly in hypothalamic midline nuclei. GLP-1 given centrally to naive rats results in a marked induction of c-fos protein in the supraoptic nucleus, PVN and central nucleus of the amygdala, but only a moderate increase in the ARC. The pattern of c-fos activation is compatible with the appetite suppressing effects of GLP-1. This anorectic effect of GLP-1 appears to be mediated by the PVN, as direct injections of GLP-1 into this nucleus cause anorexia without concomitant taste aversion, suggesting a specific action upon neuronal circuits involved in the regulation of feeding. Recent experiments have also shown that GLP1 is implicated in mediating signals from the gastrointestinal tract pertaining to discomfort and malaise. The distribution of the co-localized peptide, GLP-2, displays a perfect overlap with GLP-1 in the CNS with the highest concentration in the diffuse ventral part of the DMH [229, 231]. In rodents, central administration of GLP-2 increases satiety similar to GLP-1 [230]. In contrast to the widely distributed GLP-1 receptor mRNA, GLP-2 receptor mRNA is exclusively expressed in the compact part of the DMH. Interestingly, the compact part of

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DMH is also the only nucleus responding to central administration of GLP-2 with a significant increase in the number of c-fos positive cells. When injected into the lateral ventricle, GLP-2 has a marked inhibitory effect on feeding. The effect of GLP-2 on feeding is both behaviorally and pharmacologically specific [229]. Oxyntomodulin is mainly considered as a circulating gut hormone and is hence considered under anorectic peripheral neuropeptides. Repeated administration of GLP-1 reduced food intake and body weight without an apparent tachyphylaxis in response [232]. The GLP-1- receptor antagonist, exendin 9-39, stimulated feeding in satiated animals, and daily administration of exendin 9-39 augmented food intake and body weight gain. The anorectic effects of GLP-1 may be mediated through NPY signaling because GLP-1 inhibited and exendin 9-39 augmented NPY-induced feeding, respectively [32, 233]. The GLP-1 receptor antagonist also blocked the leptin-induced inhibition of food intake and body weight, indicating that the GLP-1 pathway may be one of the targets for the anorectic effects of leptin [155].

4. Melanocortins The melanocortins are bioactive peptides derived from the precursor molecule proopiomelanocortin (POMC) via tissue-specific post-translational cleavage. The POMC gene is expressed at physiologically significant levels in a number of mammalian tissues including anterior and intermediate pituitary, skin, the immune system and hypothalamic neurons [234236]. The repertoire of products derived from POMC by any tissue is determined by the specificities of the endoproteases (convertases) expressed in the tissue [237, 238]. Thus, anterior pituitary expresses prohormone convertase1 (PC1) and cleaves POMC to ACTH. The intermediate lobe in lower animals expresses PC2 and cleaves ACTH to yield α-MSH which is involved in the control of coat/skin color. The physiological roles of the various melanocortin peptides have been defined with varying degrees of certainty. Five different types of Melanocortin receptors have been described. MC1 receptor is involved in pigmentation of the skin, MC2 in mediating the actions of ACTH and thus regulation of steroid synthesis and secretion, and MC5 in inflammatory responses. MC3 and MC4 are the predominant receptors involved in mediating energy balance. MC4 receptors are mainly expressed in the PVN of the hypothalamus, although they are also detectable in the nucleus accumbens and dorsal motor nucleus of the vagus [239]. α- MSH produced from POMC, acts on the hypothalamus via the MC4 receptor. Central administration of α MSH or its synthetic analogue (Melanotan II) produces significant reduction in food intake with loss of body weight [240]. Melanotan II also prevents NPY induced feeding in rats [54]. The MC3 and MC4 receptors are biologically unique in that there is an endogenous antagonist (AgRP) in addition to endogenous agonist (the melanocortins) [23]. Central ICV administration of αMSH inhibits feeding and reduces body weight. The stimulatory effect of AgRP is inhibited by α -MSH [158]. Thus α -MSH and Ag RP neurons act as a dynamic system in vivo, both mediated via the MC4 receptors in the PVN. Mice over expressing AgRP as well as MC4- R knockout mice are hyperphagic and obese and are insensitive to α -MSH [241, 242]. POMC is also synthesized in the caudal brainstem although its role here remains to be clarified. AgRP immunoreactivity is low or absent in the brainstem, and it seems unlikely that hypothalamic AgRP regulates the melanocortin tone in the brainstem unlike in the hypothalamic milieu. Deletion of the MC4 R in mice causes hyperphagia and obesity, while ICV administration of MC4 R agonist to fasted mice causes inhibition of food intake [243].

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POMC is co-expressed with another anorexigenic peptide- CART in the ARC and these neurons are directly stimulated by leptin [244]. This combination is opposed by AgRP and NPY both of which are also co-secreted in a different set of neurones in the ARC itself [245]. Other neuropeptides like MCH and Orexins A and B expressed in the LHA may mediate their actions through the POMC and AgRP neurons [245]. Serotonin receptors are present on POMC neurones and implicate the melanocortin pathway in the therapeutic potential of serotonergic agonists (dexfenfluramine) in obesity, which have been shown to increase POMC activity [246]. MC3R are also expressed in the POMC/CART and AgRP/NPY neurons in the ARC. Targeted deletion of MC3R gene in transgenic mice results in higher susceptibility to diet induced obesity resulting in a late-onset-obesity phenotype with intact regulation of appetite and metabolism [247]. But interestingly, deletion of MC3R in rats results in no change in body weight, although adiposity increases with concomitant decrease in lean body mass [248]. It has been proposed that the MC system mediates some of the central actions of leptin in the brain. Leptin receptor mRNA is concentrated in the ARC and approximately 30% of POMC-expressing neurons also express the long form of leptin receptor (OBRb) [249]. Pharmacological blockade of MC-4R impairs the ability of leptin to reduce food intake and body weight [250]. Conditions associated with reduced leptin levels (e.g. fasting) or the absence of functional leptin (the ob/ob mouse) show reduced mRNA [251]. Leptin administered to ob/ob mice in turn increases hypothalamic POMC mRNA [252] and the release of α -MSH into the circulation, suggesting a possible feedback loop between the sites of α -MSH release and the release of leptin from the adipose tissue. However, physiological significance of this putative feedback probably depends upon the underlying state of energy balance, since in the fasting state there is a parallel decrease in plasma leptin and plasma α-MSH [253]. Gut hormones as Ghrelin (orexigenic) and Peptide YY (anorexigenic) decrease [254] and increase [255], the hypothalamic POMC neuronal activity respectively, suggesting the role of the melanocortin pathway in transmitting gut signals regarding satiety to the brain. Ghrelin increases c- fos activity in the NPY/AgRP neurons but not in the POMC neurons [256], suggesting that the hyperpolarisation of POMC neurons induced by Ghrelin might be mediated through GABA release by NPY/AgRP neuron depolarization [257]. While leptin might transmit signals regarding energy balance over a long term, the gut hormones might mediate short term signalling due to rapid fluctuation with meals. The presence of MC 4R in rat adipocytes supports the involvement of this receptor subtype in this interaction. Up to 26 mutations of the human MC4R have been identified. 3-4% of childhood- onset obesity is associated with functional mutations in the MC4 R [258], and thus MC4R mutations are the most common monogenic determinants of obesity in humans. The minority with homozygous mutations tend to be more severely obese [258]. Loss of function mutations in the POMC gene have been described characterized by early onset obesity, red hair and adrenal insufficiency [259, 260]. Mutations in the genes for pro-convertase I and carboxypeptidase E [245, 261] can disrupt melanocortin signalling resulting in disturbed αMSH mediated actions and obesity in humans but not in rats [262]. The contribution of polymorphisms in the MC4 receptor towards development of obesity remains to be elucidated.

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5. Serotonin Serotonin (5-HT) originates from the midbrain dorsal raphe nucleus and projects to the hypothalamus, including the PVN and the VMH. It is an important modulator of many developmental, behavioral, and physiological processes, including sleep, appetite, temperature regulation, pain perception, and motor activity . The pivotal role of 5-HT in the control of appetite was formally proposed nearly 30 years ago. In particular endogenous hypothalamic 5-HT has been implicated in the processes of within meal satiation and the end state of post meal satiety. Several receptor subtypes have been described for the 5-HT receptor family [263]. Activation of the 5-HT1A receptor in the dorsal raphe nucleus stimulates food intake acutely [264], while stimulation of the 5-HT1B receptor reduces food intake [265]. In fact, 5-HT1B receptor knock out prevents the fenfluramine induced reduction in food intake [266]. The 5HT1B induced satiety induction might be mediated through NPY reduction in the PVN [267]. A third serotonin receptor 5-HT2C may also have a role in food intake regulation, as shown by weight gain in mice lacking this receptor [268]. Studies seem to suggest that 5HT1B and 5-HT2A/2C receptors seem to be mainly involved with food intake regulation [269]. Functional interrelationships between serotonin and CRF, CCK or NPY were also suggested, which were thought to be through 5-HT2A, 5-HT2C, or 5-HT2A(2C) receptors [270,271]. Serotonin receptors in the GIT may play a role in modulation of gastric motility/emptying and in turn regulation of food intake. Enterostatin, a gut hormone secreted following fat ingestion, seems to have effects on the serotoninergic system with increased serotonin turnover [272]. Serotonin and its agonists inhibit food intake when administered either peripherally or centrally in freely feeding or food deprived animals [192, 273]. Stimulants of this monoamine reduce weight gain and increase energy expenditure in both animals and humans by action on medial hypothalamus, specifically PVN, VMH and suprachiasmatic nuclei [273]. 5-HT drugs such as d-fenfluramine, selective serotoninergic reuptake inhibitor (SSRIs) and 5-HT2C receptor agonists have all been shown to significantly attenuate rodent body weight gain, an effect strongly associated with marked hypophagia. DFenfluramine, sibutramine, fluoxetine and the 5-HT2C receptor agonist [1-(3-chlorophenyl) piperazine] (mCPP) have also all been shown to reduce caloric intake by modifying appetite in both lean and obese humans. Specifically, 5-HT drugs reduce appetite prior to and after the consumption of fixed caloric loads, and reduce premeal appetite and caloric intake at ad libitum meals. 6. Neurotensin Neurotensin (NT) is a 13-amino acid peptide, first isolated in 1973 from bovine hypothalamus by Carraway and Leeman [274]. In 1988, the rat NT gene was isolated and sequenced [275]. The gene encodes a 170-amino acid precursor protein containing both the tridecapeptide NT and a closely related hexapeptide, neuromedin N (NN). The four amino acids at the carboxy terminal of NT and NN are identical, and amino acids 8–13 of NT are essential for biologic activity [276]. There are currently three characterized receptors for NT in the CNS: a receptor with low affinity for NT (NTRL orNT2) that also binds the histamineH1 receptor antagonist levocabastine [277-279], a high affinity receptor (NTRH or NT1) [280], and a third NT receptor (NTR; NT3) that is located intracellularly [281]. NT1 mediates most of the central and peripheral actions of Neurotensin [282]. There is strong

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homology and identity between NT1 and NT2 across species [283]. Both NT1 and NT2 are G-protein coupled receptors with the typical 7-transmembrane configuration. Second messenger systems associated with the NTRs in vivo are unclear. However in vitro, the NT system has alternately been shown to regulate cyclic AMP [284, 285], cyclic GMP [286], phosphatidyl inositol (PI) turnover [287,288], intracellular Ca2+ influx [285, 289], phospholipase C [290,291], and Na+, K+-ATPase activity [292]. Neurotensin is produced in the ARC, PVN, and DMH of the hypothalamus and its microinjection into the PVN decreases food intake [32, 293]. Evidence from in vivo studies in rats indicates that NT may modulate the central effects of leptin on feeding behavior [294]. NT neurons appear to play an anorectic role downstream of leptin. Evidence of this is seen in leptin deficient ob/ob mice [295] or leptin-insensitive fa/fa rats [296], in which hypothalamic NT expression is decreased and food intake is reduced. In contrast, ICV injection of leptin into the PVN significantly stimulates NT synthesis in association with reduced food intake [296, 297]. Furthermore, immuno- neutralization with an NT antibody or an NTR antagonist (SR 48692) completely reverses the effects of a leptin-induced decrease in food intake [298]. These results suggest that leptin action may be mediated, at least in part, by NT. Neurotensin has also been shown to inhibit the orexigenic effect of MCH, but not that of NPY. [299]. Intraperitoneal injection of NTR antagonists were shown to affect the satiating effects of leptin on food deprivation induced feeding [298].

7. Neuromedins Neuromedin S (NMS) is a newly identified 36-amino acid peptide in the rat brain, named S after its specific expression in the Suprachiasmatic nucleus [300]. NMS shares a C-terminal core structure with Neuromedin U (NMU). NMS mRNA is highly expressed in the central nervous system, spleen and testis [300]. Previously Neuromedin U (NMU) had been shown to be an anorexigenic hormone with suppressive effects on fasting-induced feeding in rats when administered intracerebroventricularly [301]. NMS seems to be the endogenous ligand for NMU type1 and type 2 receptors. This affinity of NMS for NMU receptors indicates that NMS may also have anorexigenic actions, infact it has been shown to have higher potency than NMU [302]. Neuromedin U gene disruption (as in Neuromedin KO mice) results in obesity [303]. ICV injection of NMS in rats produces a reduction in food intake over a 12 hour period. NPY, ghrelin, and AgRP-induced food intake was counteracted by coadministration of NMS, suggesting that the NPY, ghrelin, and AgRP are independently antagonistic with NMS for feeding regulation [302]. This antagonism seems to be mediated by increasing the POMC and CRH mRNA levels in the PVN, as shown by a blockade of this effect by pre-treatment with antagonist to α- MSH or CRH. This is in contrast to NMU which seems to produce its actions mainly through an increase in CRH rather than MSH, as shown by a lack of effect of NMU in CRH knock out mice [304]. This difference in downstream mechanisms of feeding regulation by NMS and NMU is intriguing despite common receptors. A difference in intrinsic rhythmic expression in the suprachiasmatic nucleus has been proposed to explain this variation [305].The possibility of NMS being a downstream signal for leptin rather than an independently acting signal [303] is being investigated now that specific antisera are becoming available to distinguish Neuromedin U and S.

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ROLE OF PERIPHERAL NEUROPEPTIDES Numerous peripheral signals arise due to release of gastrointestinal peptides in response to passage of food from the gut. These signals are mainly involved in short-term regulation of feeding (termination of a meal) and energy homeostasis. Afferent signals from stretch receptors and chemo-receptors travel via vagus nerve fibers to the higher control centers. These receptors signal the presence and the energy-density of food in the gastrointestinal tract and contribute to satiety in the immediate post-prandial period [306]. Also changes in circulating glucose concentrations appear to elicit meal initiation and termination by regulating activity of specific hypothalamic neurons that respond to glucose. However, the energy density of food and short-term hormonal signals by themselves are insufficient to produce sustained changes in energy balance and body adiposity. Rather, these signals interact with long-term regulators (i.e. insulin, leptin and possibly orexigenic gastric peptide and ghrelin) to maintain energy homeostasis [307].

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Orexigenic Peripheral Peptides 1. Ghrelin Ghrelin is a 28-amino acid peptide that was isolated from rat stomach [308]. It is mainly produced in endocrine cells of the human gastric mucosa, but it was also found in several other tissues, e.g., in the pituitary, the hypothalamus and the pancreas, lung, immune cells, placenta, ovary, testis, kidney and in different tumors including pituitary adenoma, neuroendocrine tumors, thyroid carcinomas, endocrine tumors of the pancreas and lung [309,310]. It is a ‗‗saginary‘‘ hormone, from the Latin, saginare, which means, ‗‗to fatten‘‘. It is only known circulating appetite stimulant [311]. The functional receptor belongs to the family of the 7-transmembrane G-protein receptors, which are predominantly detected in the pituitary and at lower levels in hypothalamic nuclei, the stomach, heart, lungs, kidneys, gut, the adipose and many other tissues. According to the widespread distribution of the peptide and its receptor, ghrelin has multiple biological effects: it stimulates the release of growth hormone in the pituitary (due to its action on Growth hormone secretagogue receptor and induces a rise in the serum concentration of ACTH, cortisol, aldosterone, catecholamines and prolactin [308, 309, 312]. The high levels of ghrelin expressed in stomach [308] led to the recognition of its central role in the regulation of appetite, body adiposity and energy balance [313]. Ghrelin causes an increase of food intake and body weight by stimulating the production of NPY and AgRP in the arcuate nucleus and antagonizes the leptin-induced inhibition of food intake [314]. It further leads to elevated concentrations of plasma glucose [309]. ICV and peripheral administration of ghrelin to rodents caused a dose-dependent increase in food intake and body weight coupled to a reduction in fat utilization [313]. Ghrelin levels in GH-deficient adults are similar to those in healthy subjects and do not change with GH replacement [315]. Ghrelin administration to GH-deficient dwarf rats, however, resulted in effective food intake and increased body weight [313]. On the other hand, ghrelin treatment failed to induce adiposity in hypophysectomised rats [316]. In humans, ghrelin levels increase during fasting and decrease following feeding [317]. This preprandial rise in ghrelin levels may serve as a signal for meal initiation [318]. Ghrelin levels

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are decreased in obese subjects and are markedly raised in patients with anorexia nervosa [317]. However, other factors besides body composition may impact ghrelin levels since significant decrease in plasma ghrelin levels are observed in anorexic patients even before the changes in the body mass index appear. Also, healthy lean subjects have higher ghrelin levels [319] and patients with bulimia nervosa have higher ghrelin levels than weight-matched controls [320]. It is apparent that ghrelin plays an important role in both acute and long-term control of energy balance and is also influenced by behavioral parameters [321]. Thus, ghrelin may be regarded as a thrifty gene product that evolved to help animals consume and store fat well, thereby increasing their chances of survival during times of famine [311].

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Anorectic Peripheral Peptides 1. Peptide YY Peptide YY (PYY) is a 36 amino acid peptide belonging to PP-fold peptide family [NPY, PYY and Pancreatic Polypeptide]. All these peptides share sequence homology and are rich in tyrosine residues [322]. Produced by the intestinal L-cells, the highest tissue concentrations of PYY are found in distal segments of the GIT, although it is present throughout the gut [323]. Circulating PYY exists in two major forms: PYY1–36 and PYY 3–36. PYY3–36, the peripherally active anorectic signal, is created by cleavage of the N-terminal Tyr-Pro residues by dipeptidyl peptidase IV (DPP-IV) [324].It is a major form of PYY in both the gut mucosal endocrine cells and the circulation. Like NPY, PYY also acts on Y receptors. PYY3–36 shows high affinity for Y2 and some affinity for Y1 and Y5 receptors [325]. The binding of PYY3–36 to the Y2 receptor leads to an inhibition of the NPY neurons and a possible reciprocal stimulation of the POMC neurons. Thus, PYY3–36 appears to control food intake by providing a powerful feedback on the hypothalamic circuits. The effect on food intake has been demonstrated at physiological concentrations and, therefore, PYY 3–36 may be important in the everyday regulation of food intake [326]. Following food intake, PYY is released into the circulation and peak plasma levels appear 1-2 hours postprandial [327]. PYY concentrations are proportional to meal energy content, so that higher levels are seen after fat-intake as compared to carbohydrates and proteins [328]. Administration of PYY causes a delay in gastric emptying, a delay in secretions from the pancreas and stomach, and increases the absorption of fluids and electrolytes from the ileum after a meal [329,330]. Peripheral administration of PYY3–36 to rodents has been shown to inhibit food intake, reduce weight gain [255, 331] and improve glycemic control in rodent models of diabetes [332]. The effect on appetite may be dependent on a minimization of environmental stress, which in itself can result in a decrease in food intake [333]. Acute stress has been shown to activate the NPY system [334, 335], which may render the system insensitive to the inhibitory effect of PYY3–36, resulting in masking of the anorectic effect of the peptide. Single 90-min intravenous infusion of PYY3–36 to normal-weight human subjects also has potent effects on appetite, resulting in a 30% reduction in food intake [255, 299, 336]. The reduction in calories is accompanied by a reduction in subjective hunger without an alteration in gastric emptying. This effect persists for up to 12 h after the infusion

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is terminated, despite circulating PYY3–36 returning to basal levels [255]. Thus, PYY3–36 may be physiologically important as a postprandial satiety signal. Obese human subjects have a relatively low circulating PYY and a relative deficiency of post-prandial secretion [299, 336], although these subjects retain sensitivity to exogenous administration. Obese patients treated by jejuno-ileal bypass surgery [337] or vertical-banded gastroplasty [338] have elevated PYY levels, which may contribute to their appetite loss. Thus long-term administration of PYY3–36 could be an effective obesity therapy. After chronic peripheral administration of PYY3–36, rodents demonstrated reduced weight gain [255]. Potential therapeutic manipulations based on the PYY system include development of Y2 agonists, exogenously administration of PYY or increased endogenous release from the gastrointestinal tract [299].

2. Cholecystokinin Cholecystokinin (CCK) is an important endogenous peptide found in the GIT and the brain. It is present in multiple bioactive forms, including CCK- 58, CCK-33 and CCK-8, all derived from the same gene product [339]. CCK is rapidly released locally and into the circulation in response to nutrients, and remains elevated for up to 5 h [340]. Mapping of CCK-sensitive brain sites in the rat revealed that active sites lie not only in the LH, but also in the medial pons and lateral medulla in the vicinity of the NTS, where vagal afferent fibers terminate, being involved in diverse processes such as reward behavior, memory and anxiety, as well as satiety [341, 342]. CCK plays an important role in several physiological functions like stimulation of pancreatic secretion, gall bladder contraction, intestinal motility, memory enhancement and inhibition of gastric motility [193, 343-345]. It is also demonstrated that endogenous CCK has an important role in the control of meal size and several studies have uncovered the pathways by which CCK mediate these effects [346]. Administration of CCK, to both humans and animals, has long been known to inhibit food intake by reducing meal size and duration [347,348], an effect which is enhanced by gastric distension [349]. Although CCK exerts its effect on food intake rapidly, its duration of action is brief. It has a half-life of only 1–2 min, and it is not effective at reducing meal size if the peptide is administered more than 15 min before a meal [347]. Cholecystokinin mediates these physiological effects by its endocrine actions in the intestines and by its paracrine and neurocrine actions in other parts of the body especially the brain. Cholecystokinin acts by binding to the CCK receptors (CCKr). There are two types of CCKr (CCKA and CCKB) that are characterized molecularly and pharmacologically [344]. CCKA receptors bind to CCK-8 and CCK-33 with a sulphated tyrosine moiety. CCK-B receptors in contrast have a high affinity to desulphated CCK [344]. The CCK receptors are G-protein coupled receptors consisting of seven- transmembrane domains. It has been demonstrated that the satiety actions of CCK are mediated by CCK-A receptors and not CCKB [344, 350]. CCK-A receptors are found in the afferent vagal neurons and on the circular muscle cells of the pyloric sphincter. It is suggested that CCK has a direct effect on the food intake through the activation of CCK-A receptors located on the vagal afferent neurons [344]. CCK-A receptors are reported to exist in two functional states, a low affinity state and a high affinity state. CCK contracts the pyloric sphincter and activates the gastric and duodenal vagal neurons. Activity of CCK at both these sites is reported to be mediated by the low affinity sites of the receptor [343,344] suggesting that the actions of CCK in mediating the

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satiety signal is not an endocrine action but a neurocrine or paracrine because plasma concentrations of CCK can activate only the high affinity receptors [344]. Recently, it was demonstrated that exogenous CCK-8 rapidly mobilizes gastric leptin with a concomitant increase in plasma leptin concentrations [351]. Evidence was provided for a synergistic interaction between leptin and CCK leading to short term reduction in food intake [352]. It was further suggested that CCK can contribute to the long-term control of feeding and body weight when central leptin levels are elevated [353]. Intraperitoneal administration of CCK-8 failed to decrease food intake in mice lacking CCK-A receptors, whereas CCK-8 decreased food intake by up to 90% in both wild-type and CCK-B receptordeficient mice. However, CCK-A receptor-deficient mice showed normal day- and night-food intake and body weight that is comparable to the corresponding age- and sex matched wildtype controls [350].

3. Leptin Leptin (also termed OB protein), a product of leptin gene (Lep(ob) was discovered in 1994 by Friedman and colleagues [354]. It is a protein of molecular weight 18,000, containing a signal sequence which is cleaved to produce the mature hormone of molecular weight 16,000 [354]. Initial studies suggested that leptin was only synthesized by the white adipose tissue, but it is now recognized that the hormone is produced in several other sites like brown adipose tissue, stomach, placenta, mammary gland, ovarian follicles and certain fetal organs such as heart and bone or cartilage and perhaps even the brain [355-357]. The ob gene is expressed in all adipose tissue depots but the subcutaneous adipose tissue expresses higher levels of ob mRNA than omental fat [358, 359]. A mutation in the ob gene, resulting in the absence of circulating leptin, leads to the hyperphagic obese phenotype of the ob/ob mouse, which can be normalized by the administration of leptin [360-362]. Similarly, mutations resulting in the absence of leptin in humans cause severe obesity and hypogonadism [363, 364] which can be ameliorated with recombinant leptin therapy in both children and adults [365,366]. One or more isoforms of leptin receptors (Ob-R) are found in most tissues [367], including white adipose tissue, suggesting that the hormone may have an autocrine or paracrine function in adipose tissue. Leptin receptors, of which several spice variants (Ob-Ra through Ob-Re) are known, belong to the superfamily of cytokine receptors, which use the JAK-STAT pathway of signal transduction. The different splice forms of the receptor can be divided into three classes: long, short and secreted [368,369]. The long-form Ob-Rb receptor differs from the other forms of the receptor by having a long intracellular domain, which is necessary for the action of leptin on appetite [370]. Ob-Rb is found mainly in the ARC, PVN, DMH and LHA of the hypothalamus [371-373]. After binding to its receptors in hypothalamus, leptin stimulates a specific signaling cascade that results in the inhibition of several orexigenic peptides, while stimulating several anorectic peptides. The orexigenic neuropeptides downregulated by leptin are NPY, MCH, orexins and AgRP. The anorectic neuropeptides that are up-regulated by leptin are a-MSH which acts on MC4 receptor, CART and CRH [374]. Obese db/db mice, which have a mutation in the intracellular portion of ObRb are unable to perform JAK-STAT signal transduction [370, 375]. Circulating leptin is transported across the blood– brain barrier via a saturable process [14]. Regulation of transport may be an important modulator of the effects of leptin on food intake. Starvation reduces transport, whereas refeeding increases the transport of leptin across

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the blood–brain barrier [376]. The short forms of the receptor have been proposed to have a role in the transport of leptin across the blood–brain barrier [377], whereas the secreted form is thought to bind to circulating leptin thus modulating its biological activity [369]. Production of leptin correlates positively with adipose tissue mass [378]. Independent of the adiposity leptin level is higher in women than in men [379]. Leptin has a dual regulation in human physiology. During the periods of weight maintenance, when energy intake and output are equal, leptin levels reflect total body fat mass. However, in conditions of negative (weight loss programs) and positive (weight-gain programs) energy balances the dynamic changes in plasma leptin concentration function as a sensor of energy imbalance and influence the efferent energy regulation pathways [379]. Rising levels of leptin signal the brain that excess energy is being stored, and this signal brings about adaptations of decreased appetite and increased energy expenditure that resist obesity. Transgenic over expression of leptin in the liver by using the human serum amyloid P component promoter has resulted in markedly decreased food intake and body weight gain with the complete disappearance of white adipose tissue and brown adipose tissue [380]. Restriction of food intake, over a period of days, results in a suppression of leptin levels, which can be reversed by refeeding [378, 381] or administration of insulin [382]. Exogenous leptin replacement decreases fast-induced hyperphagia [383], and chronic peripheral administration of leptin to wild-type rodents result in reduced food intake, loss of body weight and fat mass [361]. In human beings, there is a highly organized pattern of leptin secretion over a 24-h period. In general, the circadian pattern is characterized by basal levels between 0800 and 1200 h, rising progressively to peak between 2400 and 0400 h, and receding steadily to a nadir by 1200 h [384]. The nocturnal rise in leptin secretion is entrained to mealtime probably due to cumulative hyperinsulinemia of the entire day [379]. Unlike in rodents, increases in leptin secretion do not appear to be driven by meal patterns. Leptin is secreted in a regular pulsatile fashion with an inter peak interval of about 44 min, and the circadian rhythm is attributable solely to increased pulse height [384]. This circadian pattern of leptin secretion is preserved in obese patients and hyperleptinemia in these patients could be due to increased pulse height. This circadian and pulsatile pattern of fluctuation in blood leptin levels implies that neural and neuro-hormonal components in brain may regulate leptin secretion from adipocytes [384]. About 5% of obese populations can be regarded as ‗‗relatively‘‘ leptin deficient which could benefit from leptin therapy [379].

4. Amylin Amylin consisting of 37 amino acids, also known as islet amyloid polypeptide was identified in 1987 [385]. Amylin is a member of a family of structurally related peptides, which includes calcitonin gene-related peptide (CGRP) and calcitonin (CT). In mammals, amylin is co-released with insulin from pancreatic b-cells in response to carbohydrate (glucose) and protein ingestion and has an anorectic effect [386]. Plasma levels of amylin, like insulin, show a pulsatile diurnal pattern with low basal levels in the fasting state with rapid rise in response to meals [387]. Healthy humans have a fasting plasma amylin concentration of 4-8 pmol/L, and 15-25 pmol/L in the post prandial state with higher levels in insulin resistant states [388]. Amylin seems to decrease food intake through both central and peripheral mechanisms and indirectly by slowing gastric emptying. The mean basal amylin concentration is higher in obese than in lean human subjects. Amylin has been reported to

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reduce food intake in rodents when given centrally as well as peripherally [386]. One mechanism by which amylin appears to reduce food intake is by augmenting the actions of other peptides such as CCK, glucagon, and bombesin, all of which also increase amylin secretion. However, the CCK antagonists failed attenuate amylin‘s reduction of food intake, suggesting that amylin does not produce its effect through the release of CCK [389]. Instead it appears to be the converse that the anorectic effects of CCK and bombesin depend partly on the presence of amylin or the calcitonin gene related peptide (CGRP) [390]. When amylin action is blocked with a CGRP receptor antagonist, the anorectic effects of CCK and bombesin are also attenuated in rats [390]. Amylin is nearly 50% homologous to the 37-amino-acid neuropeptide a- and b-CGRP [391] and all of these act on a family of related G protein-coupled receptors by modulating nitric oxide synthesis [392]. Both CGRP and amylin peptides have nearly identical N- and Cterminal regions and the disulfide bridge between amino acids 2 and 7 [393]. In contrast to amylin, which is only expressed by the b cell of the pancreas, CGRP is expressed in many tissues, such as the brain, spinal cord, thyroidal C cells and pancreatic islets, and is a potent vasodilator, involved in regulating blood flow [393]. Concerning amylin as a satiating hormone, it is well established that amylin is released during meals, and that exogenous amylin leads to a dose-related reduction in meal size. Amylin has a rapid onset and brief duration of action. The area postrema (AP) plays a predominant role in peripheral amylin‘s satiating effect, involving a direct activation of AP neurons by blood-borne amylin. The NTS relays this effect to higher brain structures, the lateral parabrachial nucleus, and possibly the central nucleus of the amygdale and the bed nucleus of the stria terminalis [394]. Amylin‘s anorectic effect may in part be due to reduced expression of orexigenic neuropeptides in the LHA [394]. There is evidence that amylin may also exert its effects through serotonergic, histaminergic, and dopaminergic systems. Amylin may induce anorexia through its effect on brain serotonin by increasing the transport of the precursor tryptophan into the brain [395]. Amylin stimulates histamine H1 receptors but does not enhance endogenous histamine release, as indicated by the anorectic effect being absent in mice lacking functional H1 receptors [396]. Additionally, the anorectic effect of amylin was attenuated in rats treated with dopamine D2 receptor antagonists [397, 398]. In animal and human studies, it has been found that amylin delays gastric emptying and decreases food intake. Obese subjects exhibit hyperamylinemia, and their elevated amylin levels may cause down-regulation of amylin receptors and lessen the impact of postprandial amylin secretion on satiety and gastric emptying. Obese subjects often experience hyperglycemia and increased corticosteroid secretion [399], both of which enhance amylin secretion in response to a meal, which could lead to amylin resistance. Amylin administration to obese individuals may have the potential to promote weight loss by delaying gastric emptying and inhibiting food intake, and overcoming resistance at the target tissues. Preclinical data with amylin and clinical data with pramlintide (a human amylin analogue) support a role for amylin in satiety. Pramlintide administration led to sustained weight loss when given for up to one year to type 1 and type 2 diabetic patients at doses resulting in plasma concentrations close to those in non-diabetic humans [400- 402].

5. Insulin Insulin is a major metabolic hormone produced by the pancreas and the first adiposity signal to be described [101]. Levels of plasma insulin vary directly with changes in adiposity Ellsworth, Shane J., and Reece C. Schuster. Appetite and Nutritional Assessment, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook

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[403] so that plasma insulin increases at times of positive energy balance and decreases at times of negative energy balance [404]. Visceral fat is a key determinant of insulin sensitivity and hence plasma insulin levels [405]. However, unlike leptin, insulin secretion increases rapidly after a meal, whereas leptin levels are relatively insensitive to meal ingestion [406]. Insulin penetrates the blood–brain barrier via a saturable, receptor- mediated process, at levels proportional to the circulating insulin [407]. Recent findings suggest that little or no insulin is produced in the brain itself [13, 408]. Once insulin enters the brain, it acts as an anorectic signal [409]. The insulin receptor is composed of an extra cellular b-subunit which binds insulin, and an intracellular b subunit which transduces the signal and has intrinsic tyrosine kinase activity. There are several insulin receptor substrates (IRSs) including IRS-1 and IRS-2, both identified in neurons [410,411]. The phenotype of IRS-1-knockout mice does not show differences in food intake or body weight [412], but that of IRS-2-knockout mice is associated with an increase in food intake, increased fat stores and infertility [411]. IRS-2 mRNA is highly expressed in the ARC, suggesting that neuronal insulin may be coupled to IRS-2 [411]. There is also evidence to suggest that insulin and leptin, along with other cytokines, share common intracellular signalling pathways via IRS and the enzyme phoshoinositide 3-kinase, resulting in downstream signal transduction [405, 413]. Insulin receptors are widely distributed in the brain, with highest concentrations found in the olfactory bulbs and ARC. Other regions of hypothalamus expressing Insulin receptors are DMH, PVN, and suprachiasmatic and periventricular regions [409,414]. Both the NPY and melanocortin systems are important downstream targets for the effects of insulin on food intake and body weight [100,415]. ICV administration of insulin during food deprivation in rats prevents the fasting -induced increase in hypothalamic levels of both NPY in the PVN and NPY mRNA in the ARC [101, 416]. Insulin receptors have also been found on POMC neurons in the ARC [415]. Administration of insulin into the third ventricle of fasting rats increases POMC mRNA expression [416]. The reduction of food intake caused by ICV injection of insulin is also blocked by a POMC antagonist [415]. Furthermore, POMC mRNA is reduced by 80% in rats with untreated diabetes, and this can be attenuated by peripheral insulin treatment which partially reduces the hyperglycemia [417]. Male mice with neuron-specific deletion of the insulin receptor in the CNS are obese and dyslipidemic with increased peripheral levels of insulin [418]. Reduction of insulin receptor proteins in the medial ARC, by administration of an antisense RNA directed against the insulin receptor precursor protein, results in hyperphagia and increased fat mass [419]. Treatment of mice with orally available insulin mimetics decreases the weight gain produced by a high-fat diet as well as adiposity and insulin resistance [416].

6. Bombesin Bombesin is a 14-aminoacid peptide originally purified from the skin of the European amphibian Bombina bombina [420,421]. Although Bombesin itself does not exist in mammalian tissue, peptides with structural homology to bombesin (Bombesin like Peptides) were identified in mammals. The known bombesin-like peptides are neuromedin B (NMB) and gastrin-releasing peptide (GRP). Bombesin and related peptides bind to G-protein coupled receptors and mediate their actions through phospholipase C. These receptors are designated as BB1 (specific for NMB, NMB-R), BB2 (specific for GRP, GRP-R) [422]. More recently, a third Bombesin receptor subtype 3 (BRS3) has been cloned whose endogenous

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ligands have not yet been successfully established [423]. The GRP-receptors and neuromedin B-receptors are widely expressed in the CNS and GIT [424, 425]. The GRP-R is also expressed in the hypothalamus such as in the PVN, and GRP is more potent than neuromedin B in inhibiting feeding. Although NMB-R is not highly expressed in these regions, it may participate in the control of food intake in the caudal hindbrain [426]. Bombesin, induced by gastric distension, might act as a messenger informing the nervous centres that the subject is satiated [427]. Meal-related fluctuations in the release of bombesin (GRP)-like peptides were reported in the PVN of rats [428]. In the CNS, these neuropeptides are thought to play a role in the regulation of feeding behavior, metabolism, and thermoregulation. Central administration of bombesin and bombesin-related peptides elicit suppression of food intake [429]. Central administration of bombesin-receptor antagonists blocked the satiety effect of bombesin and also enhanced food intake in satiated rats [429, 430]. Certain hypothalamic and hindbrain structures, such as the PVN and the NTS are particularly sensitive to the feeding suppressant effects of bombesin [431]. Bombesin might mediate its feeding-suppressant effects through an interaction with CRF because CRF antagonists attenuated the satiety effects of bombesin administered centrally or peripherally [432]. Animal studies also suggested that at least some of the effects of bombesin like peptides on food intake are mediated through endogenous CCK release, although in humans, GRP can act independently to reduce food intake [433]. Because the effects of systemically administered bombesin are abolished by total neural disconnection of the gut from the brain and are attenuated by central pretreatment of bombesin antiserum or antagonists, the satiety effects of bombesin may be neurally communicated to the brain where bombesin receptors participate [434]. Studies on the gene knock-out mice showed that GRP-R deficient mice showed some increase in weight gain [434-437]. However, similar changes were not seen with NMB-R deficient mice indicating that for regulation of food intake GRP/ GRP-R is more important as compared to NMB/ NMB-R [437]. BRS-3 deficient mice also demonstrated mild obesity due to reduced metabolic rate, increased feeding efficiency, hyperphagia [438]. BRS-3 deficient mice also demonstrated elevated circulating leptin levels and resistance to exogenously administered leptin. However, when leptin was applied ICV, food-intake was inhibited in wild-type mice but this effect was attenuated in BRS-3 deficient mice [437]. Orexigenic response to MCH, MCH levels and MCH mRNA expression was seen to be enhanced in BRS-3 deficient mice [437].

7. Oxyntomodulin Oxyntomodulin (OXM) is a circulating gut hormone derived from pro-glucagon. It is released post prandial from cells of the gastrointestinal mucosa in response to ingestion of carbohydrates and lipids [439]. Circulating OXM may have a role in the regulation of food intake and body weight [440].Oxyntomodulin probably interacts with GLP-1 and glucagon receptors, although with lower affinity than GLP-1 itself, to effect a reduction in food intake. Circulating OXM levels are raised in conditions associated with anorexia. When given ICV to rats, it inhibits food intake and promotes weight loss. Peripheral administration of OXM dose-dependently inhibits food intake without delaying gastric emptying. Peripheral OXM administration also inhibits fasting plasma ghrelin [441]. OXM injected directly into the ARC produces a potent and sustained reduction in re-feeding after a fast. Seven-day peripheral administration of OXM causes a reduction in the rate of body weight

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gain and adiposity [440]. A 4-week subcutaneous administration of OXM three times a day in obese and overweight subjects in a randomized controlled double blind study was shown to reduce food intake with a decrease in body weight by 0.45-kg per week [442]. A concomitant reduction in Leptin and increase in adiponectin was noted. C-fos immunoreactivity, a marker of neuronal activation, is increased in ARC when OXM was administered. Prior intra-arcuate administration of the glucagon-like peptide-1 (GLP-1) receptor antagonist, exendin (9-39) blocked the anorectic actions of peripherally administered OXM. This suggests that the arcuate nucleus, which lacks a complete bloodbrain barrier, could be a potential site of action for circulating OXM [443]. The actions of peripheral GLP-1, however, were not blocked by prior intra-arcuate administration of exendin (9-39), indicating the potential existence of different OXM and GLP-1 pathways.

Synopsis Food intake and energy expenditure are controlled by complex, redundant, and distributed neural systems that reflect the fundamental biological importance of adequate nutrient supply and energy balance. Much progress has been made in identifying the various hormonal and neural mechanisms by which the brain informs itself about availability of ingested and stored nutrients and, in turn, generates behavioral, autonomic, and endocrine output. While hypothalamus and caudal brainstem play crucial roles in this homeostatic function, areas in the cortex and limbic system are important for processing information regarding prior experience with food, reward, and emotion, as well as social and environmental context. However, in some individuals, genetic and environmental factors interact to result in obesity. Understanding of the complex system which regulates energy homeostasis is progressing rapidly, enabling new obesity therapies to emerge. As mechanisms of disordered energy homeostasis are clarified, treatments based on peripheral hormones or central neuropeptide signals could be tailored to the individual; just as leptin deficiency is treated successfully with leptin replacement. Therapeutic strategies may thus significantly impact on the enormous morbidity and mortality associated with obesity, as even modest weight loss can reduce the risk of diabetes, cancer and cardiovascular disease. Table 1. Major Neuropeptides involved in Appetite Regulation

Orexigenic

Anorexigenic

Central 1.Neuropeptide Y 2. Melanin Concentrating Hormone 3. Glutamate and γ-amino butyric acid (GABA) 4. Orexins 5. Agouti Related Peptide (AgRP) 6. Galanin 7. Endogenous opioids 8. Endocannabinoids 9. Fatty Acid Synthase 1.Corticitropin Releasing factor (CRF) 2. Cocaine and Amphetamine Related Transcript (CART) 3. Glucagon like peptides 4. Melanocortins (POMC) 5. Serotonin 6. Neurotensin 7. Neuromedins (NMS and NMU)

Peripheral 1. Ghrelin

1. Peptide YY 2. Cholecystokinin (CCK) 3. Leptin 4. Amylin 5. Insulin 6. Bombesin 7. Oxyntomodulin (OXM)

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[419] Obici S, Feng Z, Karkanias G, Baskin DG, Rossetti L. Decreasing hypothalamic insulin receptors causes hyperphagia and insulin resistance in rats. Nat. Neurosci. 2002; 5 (6): 566–572. [420] Spindel E. Mammalian bombesin-like peptides. Trends Neurosci. 1986; 9:130–133. [421] Tache´ Y, Brown M. On the role of bombesin in homeostasis. Trends Neurosci. 1982; 5: 431–433. [422] Battey JF, Way JM, Corjay MH, Shapira H, Kusano K, Harkins R, Wu JM, Slattery T, Mann E, Feldman RI. Molecular cloning of the bombesin/gastrin-releasing peptide receptor from Swiss 3T3 cells. Proc. Natl. Acad. Sci. U.S.A. 1991; 88: 395– 399. [423] Ohki-Hamazaki H, Iwabuchi M, Maekawa F. Development and function of bombesinlike peptides and their receptors. Int. J. Dev. Biol. 2005; 49: 293–300. [424] Wada E, Way J, Shapira H, Kusano K, Lebacq-Verheyden AM, Coy D, Jensen R, Battey J. cDNA cloning, characterization, and brain region-specific expression of a neuromedin-B-preferring bombesin receptor. Neuron. 1991; 6: 421– 430. [425] Wada E, Wray S, Key S, Battey J. Comparison of gene expression for two distinct bombesin receptor subtypes in postnatal rat central nervous system. Mol. Cell. Neurosci. 1992; 3: 446–460. [426] Ladenheim EE, Taylor JE, Coy DH, Carrigan TS, Wohn A, Moran TH. Caudal hindbrain neuromedin B-preferring receptors participate in the control of food intake. Am. J. Physiol. 1997; 272: R433–R437. [427] Rampal P. Mechanisms of the control of appetite. Presse Med.1986; 15 (1): 23–25. [428] Plamondon H, Merali Z. Push-pull perfusion reveals meal dependent changes in the release of bombesin-like peptides in the rat paraventricular nucleus. Brain Res. 1994; 668: 54–61. [429] Merali Z, Moody TW, Coy D. Blockade of brain bombesin/ GRP receptors increases food intake in satiated rats. Am. J. Physiol. 1993; 264: R1031–R1034. [430] Flynn FW. Fourth ventricular injection of selective bombesin receptor antagonists facilitate feeding in rats. Am. J. Physiol. 1993; 264: R218–R221. [431] Flynn FW. Caudal brain stem systems mediate effects of bombesin-like peptides on intake in rats. Am. J. Physiol. 1992; 262: R39– R45. [432] Plamondon H, Merali Z. Anorectic action of bombesin requires receptor for corticotropin-releasing factor but not for oxytocin. Eur. J. Pharmacol. 1997; 340: 99– 109. [433] Gutzwller J-P, Drew J, Hildebrand P, Rossi L, Lauer JZ, Bellinger C. Effect of intravenous human gastrin-releasing peptide on food intake in humans. Gastroenterology. 1994; 106: 1168–1173. [434] Hampton LL, Ladenheim EE, Akeson M, Way JM, Weber HC, Sutliff VE, Jensen RT, Wine LJ, Arnheiter H, Battey JF. Loss of bombesin-induced feeding suppression in gastrin-releasing peptide receptor deficient mice. Proc. Natl. Acad. Sci. U.S.A. 1998; 95: 3188–3192. [435] Ladenheim EE, Hampton LL, Whitney AC, White WO, Battey JF, Moran TH. Disruptions in feeding and body-weight control in gastrin-releasing peptide receptor deficient mice. J. Endocrinol. 2002; 174: 273–281. [436] Wada E, Watase K, Yamada K, Ogura H, Yamano M, Inomata Y, Eguchi J, Yamamoto K, Sunday ME, Maeno H, et al. Generation and characterization of mice lacking gastrin-releasing peptide receptor. Biochem. Biophys. Res. Commun. 1997; 239: 28–33.

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[437] Maekawa F, Quah H-M, Tanaka K, Ohki-Hamazaki H. Leptin resistance and enhancement of feeding facilitation by melanin-concentrating hormone in mice lacking Bombesin receptor subtype- 3 (BRS-3). Diabetes. 2004; 53: 570–576. [438] Ohki-Hamazaki H, Watase K, Yamamoto K, Ogura H, Yamano M, Yamada K, Maeno H, Imaki J, Kikuyama S, Wada E, et al. Mice lacking bombesin receptor subtype-3 develop metabolic defects and obesity. Nature. 1997; 390: 165–169. [439] Holst JJ. Enteroglucagon. Annu. Rev. Physiol. 1997; 59:257-71. [440] Dakin CL, Small CJ , Batterham RL , Neary NM, Cohen MA, Patterson M, Ghatei MA, Bloom SR. Peripheral Oxyntomodulin Reduces Food Intake and Body Weight Gain in Rats. Endocrinology. 2004; 145(6): 2687-2695. [441] Cohen MA, Ellis SM, Le Roux CW, Batterham RL, Park A, Patterson M, Frost GS, Ghatei MA, Bloom SR. Oxyntomodulin suppresses appetite and reduces food intake in humans. J. Clin. Endocrinol. Metab. 2003; 88(10): 4696-4701. [442] Wynne K, Park AJ, Small CJ, Patterson M, Ellis SM, Murphy KG, Wren AM, Frost GS, Meeran K, Ghatei MA, Bloom SR.Subcutaneous oxyntomodulin reduces body weight in overweight and obese subjects: a double-blind, randomized, controlled trial. Diabetes. 2005; 54: 2390-2395. [443] Dakin CL, Gunn I, Small CJ, Edwards CMB, Hay DL, Smith DM , Ghatei MA, Bloom SR. Oxyntomodulin Inhibits Food Intake in the Rat. Endocrinology. 2001; 142 (10): 4244-4250

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Chapter 3

CENTRAL INHIBITORY MECHANISMS CONTROLLING WATER AND SODIUM INTAKE José Vanderlei Menani*1, Laurival Antonio De Luca Jr1, Patrícia Maria de Paula1, Carina Aparecida Fabrício de Andrade1,3, Lisandra Brandino de Oliveira1,2 and Daniela Catelan Ferreira da Silva1 1

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Department of Physiology and Pathology, School of Dentistry, São Paulo State University, UNESP, Araraquara, SP, Brazil. 2 Department of Biological Sciences, DECBI-NUPEB, Federal University of Ouro Preto, Ouro Preto, MG, Brazil 3 Department of Biomedical Sciences, Federal University of Alfenas, Unifal-MG, Alfenas, MG, Brazil

ABSTRACT Ingestion of sodium and/or water is controlled by excitatory mechanisms that involve stimuli like angiotensin II (ANG II), mineralocorticoids or hiperosmolarity acting on specific areas of the brain and by inhibitory mechanisms present in different central areas and involving different hormones and neurotransmitters that act to limit these behaviors. Recent studies have shown two important inhibitory mechanisms for the control of sodium and water intake: the inhibitory mechanism of the lateral parabrachial nucleus (LPBN) and the α2 adrenergic mechanism located in forebrain areas. In the LPBN different neurotransmitters like serotonin, cholecystokinin, glutamate, corticotropinreleasing factor, GABA and opioid may modulate the inhibitory mechanism. Interactions between neurotransmitters in the LPBN, like the interdependence and cooperactivity between serotonin and cholecystokinin have also been demonstrated. In the forebrain, mixed alpha2-adrenergic and imidazoline receptor agonists, like clonidine and moxonidine, are the most effective to inhibit water and sodium intake induced by different stimuli. Inhibition of water or NaCl intake dependent on alpha2-adrenergic *

Correspondence: José Vanderlei Menani, Ph.D. Dept. of Physiology and Pathology, School of Dentistry, UNESP, Rua Humaitá 1680, 14801-903, Araraquara, SP, Brazil. Phone: +55 (16) 3301-6486; FAX: +55 (16) 33016488; E-mail: [email protected]

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José Vanderlei Menani, Laurival Antonio De Luca Jr et al. receptor activation has been demonstrated with injection of these drugs into the lateral ventricle (LV), septal area, lateral preoptic area, and lateral hypothalamus. Previous and unpublished results presented in this chapter have shown that: A) in normovolemic rats, moxonidine injected into the LV induced c-fos expression in the organum vasculosum lamina terminalis (OVLT), ventral median preoptic nucleus (vMPN), paraventricular and supraoptic nucleus of the hypothalamus, while in sodium depleted rats, moxonidine reduced c-fos expression in the OVLT and increases it in the dorsal MPN; B) moxonidine bilaterally injected into basal amygdala (BA) reduced sodium depletion-induced sodium intake, while no effects were observed injecting moxonidine into the central amygdala; C) moxonidine into the LV reduced water and sodium intake and hypertension induced by daily subcutaneous (sc) injection of deoxycorticosterone; D) moxonidine injected into the LV also reduced food intake-induced water intake, but did not change food deprivation-induced food intake, suggesting that inhibitory effects of moxonidine in the forebrain are not due to non specific inhibition of behaviors; E) contrary to the inhibitory effects produced by injections into the amygdala, LV or other forebrain areas, bilateral injections of moxonidine into the LPBN increases sodium intake.

Keywords: thirst, sodium appetite, lateral parabrachial nucleus, α2-adrenoceptors, serotonin, moxonidine.

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INTRODUCTION Water and sodium intake are behavioral responses controlled by facilitatory and inhibitory mechanisms found in different areas of the brain [Sakai et al., 1986; Edwards & Johnson, 1991; Galaverna et al., 1991; Menani & Johnson, 1995; Johnson & Thunhortst, 1997; Fitzsimons, 1998; Menani et al., 2000; Antunes-Rodrigues et al.; 2004; Menani et al., 2006]. The most well known facilitatory mechanisms are located in the forebrain, while the inhibitory mechanisms have been found in the forebrain or in the hindbrain and are still not completely understood. Some facilitatory mechanisms are common for water and sodium intake and others are specific for only one of these behaviors. Angiotensin II (ANG II) is a mechanism that facilitates both water and sodium intake, while mineralocorticod hormones facilitate only sodium intake [Braun-Menendez & Brandt, 1952; Avrith & Fitzsimons, 1980; Coghlan et al., 1981; Galaverna et al., 1991; Ma et al., 1993; Fitzsimons, 1998]. Osmoreceptor activation facilitates water intake at the same time it inhibits sodium intake [Fitzsimons & Wirth, 1976; Fitzsimons, 1985; Blackburn et al., 1995; Sakai et al., 1996; Johnson & Thunhortst, 1997]. Central ANG II receptors and osmoreceptors are located mainly in the subfornical organ (SFO) and in the organum vasculosum lamina terminalis (OVLT), while mineralocorticoids seem to act in the amygdala and nucleus of the solitary tract [Nitabash et al., 1989; Schulkin et al., 1989; Galaverna et al., 1991; Zhang et al., 1993; Zardetto-Smith et al., 1994; Sakai et al., 1996; Johnson & Thunhortst, 1997; Fitzsimons, 1998; McKinley & Johnson, 2004; Geerling et al., 2006; Geerling & Loewy, 2008]. The inhibition of sodium intake may involve hormones like atrial natriuretic peptide (ANP) or oxytocin and neurotransmitters like serotonin, colecystokinin (CCK), tachykinin, noradrenaline that may act in the forebrain and/or in the hindbrain [Antunes-Rodrigues et al., 1986; Blackburn et al., 1992; De Luca Jr et al., 1994; Ciccocioppo et al.,1994; Verbalis et al., 1995; Blackburn et al., 1995; Menani & Johnson, 1995; De Paula et al., 1996; Menani et al., 1996; Stricker & Verbalis, 1996; McCann et al., 1996; Yada et al., 1997a; Yada et al., 1997b;

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Sato et al., 1997; De Luca Jr & Menani, 1997; Menani & Johnson, 1998; Menani et al., 1998a,b; Sugawara et al., 1999; Menani et al., 1999; De Gobbi et al., 2000; Menani et al., 2000; Amico et al., 2001; De Gobbi et al., 2001; Fitts et al., 2003; McCann et al., 2003; De Oliveira et al., 2003, Franchini et al., 2003]. Some of these hormones/neurotransmitters, like ANP, serotonin, noradrenaline, also inhibit water intake. Mixed alpha2 adrenergic and imidazoline receptor agonists like moxonidine and clonidine usually used as anti-hypertensive drugs [Ernsberger et al., 1993; Buccafusco et al., 1995] produce strong antidipsogenic and antinatriorexigenic effects when injected into forebrain areas [Fregly et al., 1981; Ferrari et al., 1990; De Paula et al., 1996; Sato et al., 1996; Yada et al., 1997a; Yada et al., 1997b; Menani et al., 1999; Sugawara et al., 1999; Sugawara et al., 2001; Andrade et al., 2003; De Oliveira et al.; 2003; Menani et al., 2006]. Previous central injection of alpha2-adrenergic receptor antagonists (yohimbine, SKF 86466 or RX 821002) abolished or reduced the inhibition of sodium depletion-induced sodium intake produced by moxonidine injected into the lateral ventricle (LV) [De Oliveira et al., 2003]. The pretreatment with SKF 86466 centrally, but not yohimbine, also reduced the antinatriorexigenic effect of clonidine [Yada et al., 1997b; Sugawara et al., 1999]. Therefore, the inhibitory effects of moxonidine and clonidine on sodium and water intake depend on the activation of central alpha2 adrenergic receptor. Functional studies have recently shown the existence of important inhibitory mechanisms in the LPBN for the control of water and NaCl intake [Ohman & Johnson, 1986; Menani et al., 1995,1996,1998a,b]. Bilateral injections of methysergide (serotonin antagonist), DNQX (glutamate antagonist) or alpha-helical corticotropin-releasing factor (CRF)9–41 (CRF antagonist) into the LPBN increase hypertonic NaCl intake and eventually water intake induced by the treatment with the diuretic furosemide (FURO) combined with low dose of the angiotensin converting enzyme inhibitor captopril (CAP) subcutaneously (sc), while injections of the respective agonists (DOI, AMPA and CRF) produce opposite effects [Menani et al., 1996; Xu et al., 1997; De Castro & Silva et al., 2006]. Blockade of CCK receptors into the LPBN also increases FURO + CAP-induced sodium intake [Menani & Johnson, 1998]. Contrasting with the inhibitory effects in forebrain areas, the activation of alpha2-adrenergic receptors into the LPBN increases FURO + CAP-induced sodium intake [Andrade et al., 2004]. Recent results have also shown that the activation of GABAA receptors with bilateral injections of muscimol or the opioid receptors with beta-endorphin into the LPBN induces strong ingestion of hypertonic NaCl in satiated normovolemic rats that did not receive any other treatment [Callera et al., 2005, De Oliveira et al., 2008].

CHANGES IN FOREBRAIN C-FOS EXPRESSION INDUCED BY ICV MOXONIDINE Recently, the neuronal marker c-fos protein expression has been used as an important tool to understand the neuronal mechanisms of thirst and sodium appetite control. C-fos gene belongs to immediate early gene (IEG) family. They can be activated in different neuronal systems by distinct physiological or pharmacological stimuli [Morgan & Curran, 1989; Sheng & Greenberg, 1990]. The proteins encoded by IEGs can act as transcriptional factors to interact with specific sequences of the target genes, modulating the expression of these genes

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and, therefore, the phenotypic expression of the cell. [Tsai et al., 1988; Beato, 1989; Sheng & Greenberg, 1990]. Therefore, activation of IEGs could be considered the link between external stimuli and phenotypic changes in neuronal cells [Herrera & Robertson, 1996]. Imunohistochemistry analysis of c-fos protein expression has been used to map brain areas that are metabolically activated during treatments that induce water and sodium intake. Previously it was showed that hypertonic saline infusion activated forebrain areas as paraventricular (PVN) and supra optic (SON) hypothalamic nuclei, median preoptic area (MnPO) and organum vasculosum of lamina terminalis (OVLT) and hindbrain areas like the parabrachial nucleus (PBN), nucleus of solitary tract (NTS) and rostroventrolateral medulla (RVLM) [Hochstenbach & Ciriello, 1996]. A protocol (injection of furosemide combined to a low dose of angiotensin converting enzyme inhibitor – captopril sc) that produces in a short time (1 h after the treatment) water and sodium intake induced c-fos expression in the subfornical organ (SFO), OVLT, MnPO, SON, PVN, area postrema (AP), PBN, rostral and caudal NTS [Thunhorst et al., 1998]. Intraperitoneal dialysis or 24 h sodium depletion (sc injection of furosemide followed by sodium deficient food for 24 h) induced c-fos expression in the SFO and OVLT [Vivas et al., 1995; Rowland et al., 1996]. Peripheral administration of clonidine induced c-fos immunoreactivity in oxytocinergic neurons in the PVN and SON [Tsujino et al., 1992; Herrera & Robertson, 1996). Peripheral administration of yohimbine (alpha2-adrenergic receptor antagonist) increased the amount of mRNA to c-fos protein in the brain [Gubits et al., 1989] and the immunoreactivity to c-fos in the locus coerulus (LC), central nucleus of amygdala (CeA), bed nucleus of stria terminalis, NTS, rostral ventrolateral medulla (RVLM), PVN, SON, neocortex and piriform cortex [Tsujino et al., 1992; Bing et al., 1992]. C-fos expression induced by yohimbine is partially blocked by beta (propanolol) and alpha1 (prazosin) adrenergic receptor antagonists and by the alpha2 adrenergic/imidazoline receptor agonist (clonidine) [Gubits et al., 1989; Bing et al., 1992; Hughes & Dragunow, 1995; Herrera & Robertson, 1996]. Moxonidine, like clonidine, is an alpha2 adrenergic/imidazoline receptor agonist that inhibits water and/or sodium intake induced by different treatments when administered intracerebroventricularly (icv). A question is if central moxonidine would affect c-fos protein expression in different areas of the brain involved in the control of water and sodium intake in normovolemic and in sodium depleted rats. To investigate this question, male rats with a stainless steel cannula implanted in the lateral ventricle (LV) were submitted to sodium depletion by the treatment with the diuretic furosemide (20 mg/kg of body weight) injected sc followed by 24 h of sodium deficient food (powdered corn meal, 0.001% sodium, 0.33% potassium) and water available. After 24 h, rats received moxonidine hydrochloride (20 nmol) or vehicle into the LV. Control normovolemic rats not treated with furosemide also received the same treatments into the LV. One hour after central injections, both normovolemic and sodium depleted rats had the brains removed and processed by imunohistochemistry for c-fos expression [Andrade et al., 2004]. C-fos protein expression was studied in the OVLT, ipsilateral (ipsLSA) and contralateral (contLSA) lateral septal área (using as reference the side of the injection into the LV), dorsal (dMnPO) and ventral MnPO (vMnPO), SFO, PVN, SON and amygdala. In normovolemic rats, LV injection of moxonidine (20 nmol) increased c-fos positive cells in the following areas: OVLT [F(1,6) = 6.9; p < 0.05], ipsLSA [F(1,12) = 16.3; p < 0.05]; vMnPO [F(1,6) = 22.9; p < 0.05]; PVN [F(1,6) = 12.1; p < 0.05] and SON [F(1,6) =

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6.8; p < 0.05] (Figures 1 and 2). No significant changes were observed in the other areas analyzed (Figure 1). In comparison to sodium depleted animals that received vehicle into the LV, moxonidine into the LV induced an increase in c-fos protein expression in dMnPO [F(1,10) = 7.7; p < 0.05]; ipsLSA [F(1,10) = 8.3; p < 0.05] and a reduction in OVLT [F(1,10) = 16.6; p < 0.05] in sodium depleted animals (Figures 3 and 4). No significant changes were observed in the other areas analyzed (Figure 3).

Figure 1. C-fos protein positive cells/mm2 1 h after vehicle or moxonidine (20 nmol) injection into the LV in normovolemic and satiated rats. A) OVLT (organum vasculosum of lamina terminalis), ipsilateral (ipsLSA) and contralateral (contLSA) lateral septal area; B) dorsal (dMnPO) and ventral (vMnPO) median preoptic nucleus, subfornical organ (SFO); C) paraventricular nucleus (PVN), supraoptic nucleus (SON) and amygdala (Amg). Results are expressed as means ± SEM; n, number of rats.

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Figure 2. Photomicrographs of slices of the rat‘s brain showing c-fos protein labeling 1 h after vehicle or moxonidine (20 nmol) injection into the LV in normovolemic and satiated rats. A) OVLT (organum vasculosum of lamina terminalis); B) contralateral (contLSA) and ipsilateral (ipsLSA) lateral septal area; C) ventral median preoptic nucleus (vMnPO); D) paraventricular nucleus (PVN); E) supraoptic nucleus (SON).

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Figure 3. C-fos protein positive cells/mm2 1 h after vehicle or moxonidine (20 nmol) injection into the LV in 24 h sodium depleted rats. A) OVLT (organum vasculosum of lamina terminalis), ipsilateral (ipsLSA) and contralateral (contLSA) lateral septal area; B) dorsal (dMnPO) and ventral (vMnPO) median preoptic nucleus, subfornical organ (SFO); C) paraventricular nucleus (PVN), supraoptic nucleus (SON) and amygdala (Amg). Results are expressed as means ± SEM; n, number of rats.

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Figure 4. Photomicrographs of slices of the rat‘s brain showing c-fos protein labeling 1 h after vehicle or moxonidine (20 nmol/1 l) injection into the LV in 24 h sodium depleted rats. A) ipsilateral (ipsLSA) lateral septal area; B) OVLT (organum vasculosum of lamina terminalis); C) dorsal median preoptic nucleus (dMnPO).

The results show that in normovolemic rats, icv injection of moxonidine induced c-fos protein expression in forebrain areas like OVLT, ipsLSA, vMnPO, PVN and SON that are areas involved in the control of fluid electrolyte balance and cardiovascular regulation [Covian et al., 1975; Brody et al., 1978; Brody & Johnson, 1980; Johnson, 1985; Colombari et al., 1992; Fitzsimons, 1998]. Previous data had showed that activation or deactivation of alpha2 adrenergic and/or imidazoline receptors affect c-fos protein expression [Bing et al., 1992; Tsujino et al., 1992; Shen et al., 1995]. While peripheral injection of yohimbine increased immunoreactivity to c-fos in many areas (LC, CeA, bed nucleus of stria terminalis, NTS, RVLM, PVN, neo and piriform cortex, and SON) [Bing et al., 1992; Tsujino et al., 1992], icv yohimbine did not affect c-fos expression [Blume et al., 2002]. Intraperitoneal injection of alpha2 adrenergic/imidazoline receptor agonist (clonidine) induced c-fos expression in the PVN and SON [Tsujino et al., 1992], while administration of alpha2 adrenergic receptor antagonist (RX 821002) increased mRNA expression to c-fos protein in the cortex, but with no remarkable effects on other areas [Shen et al., 1995]. Previous data showed that 24 h of sodium depletion induced c-fos protein expression in the SFO (100% of the animals analyzed) and OVLT (40% of the animals analyzed) [Rowland et al., 1996], a result consistent with the proposed role of these areas for the control of sodium intake induced by sodium depletion. In the present study, sodium depleted rats treated with

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moxonidine increased c-fos protein expression in the ipsLSA and dMnPO, while reduced cfos expression in the OVLT. In summary, central injection of moxonidine in normovolemic rats promoted activation of some forebrain areas (OVLT, ipsSLA, vMnPO, PVN and SON). Moxonidine also increased the activity of ipsSLA, dMnPO and reduced the activity of OVLT in sodium depleted rats, suggesting that these areas are possible central sites involved in the inhibitory effects of moxonidine on sodium and water intake.

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INHIBITION OF SODIUM AND WATER INTAKE BY MOXONIDINE INTO THE AMYGDALA Amygdala, a limbic structure, plays a fundamental role in the control of sodium and water intake [Covian et al., 1975]. The amygdaloid complex includes different sub nuclei that may subserve different effects (inhibitory or excitatory) on sodium appetite [Gentil et al., 1968; Covian et al., 1975]. Ablation of the whole amygdaloid complex results in a severe impairment of food and water intake immediately after the lesion with a recovering to nearly normal levels into 2 to 3 weeks later. Amygdaloid lesions also drastically reduce 0.5 M NaCl intake induced by mineralocorticoid and natriuretic agent treatment [Cox et al., 1978]. Aldosterone receptors and angiotensinergic terminals are present in the central nucleus of amygdala (CeA) [Stumpf & Sar, 1979; Sakai et al., 1990; Lind et al., 1985]. Lesions of CeA reduce daily sodium intake and sodium intake induced by mineralocorticoid, icv injection of renin, sc yohimbine or sodium depletion [Galaverna et al., 1991; Zardetto-Smith et al, 1994). Although bilateral lesions of CeA impair daily food and water intake, they do not affect water intake induced by ANG II or sc hypertonic saline [Galaverna et al, 1991; Zardetto-Smith et al., 1994; Ganaraj & Jeganathan, 1998). The medial region of amygdala is also important for salt intake induced by aldosterone, but not by sodium depletion or adrenalectomy [Schulkin et al., 1989]. On the other hand, electrolytic or chemical ablation of the corticomedial nucleus of the amygdala increases daily 1.5% NaCl intake and bilateral lesions of the basolateral nucleus of amygdala increase water and food intake [Ganaraj & Jeganathan, 1998]. Therefore, important facilitatory mechanisms for sodium intake seem to be present in the CeA and medial amygdala, while inhibitory mechanisms for ingestive behavior are present in the corticomedial and basolateral nuclei of amygdala. Previous studies have shown the presence of alpha2-adrenergic and imidazoline receptors in the amygdaloid complex [Mallard et al., 1992; French, 1995; King et al., 1995; Ruggiero et al., 1998; Newman-Tancredi et al., 2000]. Because central alpha2 adrenergic receptors and the amygdaloid complex are involved in the control of sodium intake, we investigated the effects of moxonidine injected into the whole amygdala or in specific nuclei of the amygdala (central and basal nuclei of amygdala) on sodium depletion-induced sodium intake. Male rats with stainless steel cannulas implanted bilaterally into the basal (BA, 2.2 mm caudal to bregma, 4.7 mm lateral to midline and 6.4 mm below the dura-mater) or central (CeA, 2.2 mm caudal to bregma, 4.5 mm lateral to midline and 5.4 mm below dura-mater) nucleus of amygdala received moxonidine hydrochloride (5, 10 and 20 nmol) or vehicle injections into the BA and CeA. Sodium appetite was induced by 24 h of sodium depletion. After 24 h, food and water were removed from the cage, the drugs were bilaterally injected

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into amygdala, BA or CeA and 20 minutes later, water and 0.3 M NaCl were returned to the animals. Cumulative intakes of water and 0.3 M NaCl were measured at 15, 30, 60 and 120 min. The brains were removed at the end of the experiments, fixed in 10% formalin, cut in 50 m sections, stained with Giemsa and analyzed by light microscopy to confirm the injections into the BA, CeA or amygdala. Bilateral injections of large volume of moxonidine (5, 10 and 20 nmol/1 microliter) into any part of amygdala (Amg) reduced sodium depletion-induced 0.3 M NaCl intake [F(3, 60) = 15.3; p < 0.05] (Figure 5A) during the whole treatment. When injected into the BA, moxonidine only at the dose of 20 nmol (0.4 microliter) was able to reduce hypertonic NaCl intake in sodium depleted rats [F(3, 12) = 6.3; p < 0.05] (Figure 5B). However, when injected into CeA, moxonidine did not change sodium depletion-induced 0.3 M NaCl intake [F(1,6) = 4.8; p > 0.05] (Figure 5C). Water intake by sodium-depleted rats was not affected by moxonidine bilaterally injected into the amygdala or BA (Figures 5D, 5E). On the other hand, moxonidine injected into CeA decreased water intake that follows sodium depletion-induced sodium intake [F(3, 18) = 8.3; p < 0.05] (Figure 5F). Figure 6 shows the typical bilateral injections into the basal or central amygdala.

Figure 5. (A), (B), (C) Cumulative 0.3 M NaCl intake; (D), (E), (F) cumulative water intake by 24 h sodium depleted rats that received bilateral injections of vehicle or moxonidine (5, 10 and 20 nmol) into amygdala (AMG, 1 l); basal (BA, 0.2 or 0.4 l) or central nucleus of amygdala (CeA, 0.2 or 0.4 l). Results are expressed as means ± SEM; n, number of rats.

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Figure 6. Photomicrographs showing the sites of injections into the (A) BA and (B) CeA (arrows).

Therefore, all doses of moxonidine injected into amygdala were able to reduced sodium depletion-induced sodium intake. When small volumes (maximum of 0.4 microliter) were used in a restrict area, only the highest dose of moxonidine (20 nmol) injected into the BA reduced 0.3 M NaCl intake. However, the same doses of moxonidine into the CeA did no affect sodium intake. Sodium depleted rats usually ingest a small amount of water with the ingestion of hypertonic NaCl. The ingestion of water in control conditions ranged from 0.5 to 3 ml in the 2-h test. Only moxonidine injected into the CeA produced a slight reduction of water intake. The present results showing that alpha2 adrenergic/imidazoline mechanisms acting in amygdala, specifically in the basal amygdala, inhibit sodium intake, extend previous studies in which moxonidine and/or clonidine injected icv, into the lateral hypothalamus or medial septal area, reduced sodium and water intake induced by different treatments [Fregly et al., 1981; Ferrari et al., 1990; De Paula et al., 1996; Sato et al., 1996; Yada et al., 1997a; Yada et al., 1997b; Menani et al., 1999; Sugawara et al., 1999; Sugawara et al., 2001; Andrade et al., 2003; De Oliveira et al., 2003; Menani et al., 2006]. A good correlation exists between binding of alpha2 adrenergic receptor agonists to the basal nuclei of the amygdala and an alpha2-adrenergic receptor-dependent inhibition of sodium intake by moxonidine. This agonist into the LV acts on central alpha2 adrenergic receptors to inhibits sodium depletion-induced sodium intake (Oliveira et al, 2003) and, whereas both alpha2-adrenergic and imidazoline receptors are present in the amygdaloid complex (French, 1995; King et al, 1995), only the alpha2-adrenergic receptors are at high levels in the basomedial and basolateral nuclei of amygdala. Thus, it seems that moxonidine injected into the amygdala acts preferentially on alpha2 adrenergic receptors, instead of imidazoline receptors, to inhibit sodium or water intake. Previous studies have shown that bilateral electrolytic lesions in the amygdaloid complex may increase or decrease hypertonic NaCl intake depending on the size and place of the lesion and that complete amygdalectomy produces severe impairment of sodium appetite

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induced by mineralocorticoid and other natriuretic agents [Gentil et al., 1968; Cox et al., 1978]. Lesions of the medial portion of the amygdala abolish sodium intake induced by mineralocorticoid [Nitabash et al., 1989; Zhang et al., 1993] and lesions of CeA reduce sodium intake induced by different treatments [Galaverna et al., 1991; Galaverna et al., 1993; Seeley et al., 1993; Zardetto-Smith et al., 1994], suggesting that medial and central nuclei of amygdala might facilitate sodium intake. On the other hand, chemical or electrolytic lesions of corticomedial nucleus of the amygdala increase daily 1.5% NaCl intake and ablation of the basolateral nucleus of amygdala increases water and food intake [Saad et al., 1994; Ganaraj & Jeganathan, 1998], suggesting that corticomedial and basolateral nuclei of amygdala inhibit ingestive behavior. The present results show that activation of alpha2-adrenergic/imidazoline receptors in the BA reduces sodium depletion-induced 0.3 M NaCl intake, which also suggests an inhibitory action of basal amygdala in the control of sodium intake. In spite of the importance of CeA for sodium intake [Galaverna et al., 1991; Galaverna et al., 1993; Seeley et al., 1993; Zardetto-Smith et al., 1994; Ganaraj & Jeganathan, 1998], bilateral injections of moxonidine in this area produced no effect on NaCl intake. Considering the suggested interaction between basolateral amygdala and CeA, it is possible that the activation of alpha2 adrenergic/imidazoline receptors in the basal amygdala could inhibit the activity of CeA reducing NaCl intake.

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MOXONIDINE ICV REDUCED DEOXYCORTICOSTERONE-INDUCED WATER AND SODIUM INTAKE AND HYPERTENSION Chronic treatment with the mineralocorticoid deoxycorticosterone (DOCA) induces strong ingestion of hypertonic NaCl and hypertension [Fluharty & Epstein, 1983; Denton, 1984; Sakai et al., 1986; Galaverna et al., 1991; Balasubramaniam et al., 1995; Kanagy & Webb, 1996; Sakai et al., 1996; De Gobbi et al., 2000]. Moxonidine is a potent central antihypertensive drug suggested to reduce sympathetic activity by activation of imidazoline receptors located in the rostroventrolateral medulla [Ernsberger et al., 1993; Haxhiu et al., 1994; Ernsberger et al., 1997]. Moxonidine also induces diuresis and natriuresis [Menani et al., 1999; Menani et al., 2006; Penner & Smyth, 1994a; Penner & Smyth, 1994b; Penner & Smyth, 1995], which combined to the inhibition of water and sodium intake may have a role in its anti-hypertensive effect. Thus, we tested if moxonidine injected into the lateral ventricle might reduce water and sodium intake as well as the hypertension induced by chronic treatment with sc DOCA. A group of male Holtzman rats with stainless steel cannula into the LV were treated with sc DOCA (25 mg/kg of body weight, twice a week). Rats received water and food pellets ad libitum and had access to 1.8% NaCl during 2 h a day. After 15 days of DOCA treatment, rats received injections of vehicle (control) or moxonidine (5, 10 or 20 nmol) into the LV, 15 minutes before the access to 0.3 M NaCl. Water and 0.3 M NaCl intake was measured at every 30 min for 2 hours starting immediately after the access to 0.3 M NaCl. All doses of moxonidine (5, 10 and 20 nmol) into the LV reduced sodium intake, [F(3,30) = 8.7; P < 0.05], while water intake was not affected [F(3,30) = 1.6; P > 0.05] (Figure 7).

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Figure 7. A) Cumulative 0.3 M NaCl intake and B) cumulative water intake in rats treated with DOCA (25 mg/kg b.w., twice a week) sc that received icv moxonidine (moxo; 5, 10 or 20 nmol/1 l) or vehicle (veh; 1 l). Values expressed as mean S.E.M. n = number of animals.

Another group of male rats with stainless steel cannula into the lateral ventricle treated with sc DOCA (25 mg/kg of body weight, twice a week) had water and 0.3 M NaCl intake recorded daily and arterial pressure recorded before and 5, 20, 22 and 25 days after starting DOCA treatment. From the 20th to the 25th day of DOCA treatment rats received icv injections of vehicle or moxonidine (50 nmol/1 l) twice a day (at 8:00 AM and 6:00 PM). Chronic DOCA treatment increased arterial pressure [F(1,55) = 5.89; P < 0.05], daily water intake [F(47, 264) = 4.12; P < 0.0001] and 0.3 M NaCl intake [F(47, 264) = 4.98; P < 0.0001] (Figure 8, 9 and 10). Moxonidine treatment into the LV (50 nmol twice a day, for 5 days) reduced daily 0.3 M NaCl intake in the last 4 days, (Figure 8), and water intake in the last 2 days of moxonidine treatment when compared to control treatment (vehicle injection) (Figure 9). DOCA-induced increase in arterial pressure was reduced by moxonidine treatment only after the 4th day of moxonidine treatment (Figure 10).

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Figure 8. Daily 0.3 M NaCl intake (ml/24 h) in rats treated with DOCA (25 mg/kg b.w., twice a week) sc that received icv moxonidine (50 nmol/1 l twice a day) or vehicle (1 l twice a day). Values expressed as mean S.E.M. n = number of animals.

Figure 9. Daily water intake (ml/24 h) in rats treated with DOCA (25 mg/kg b.w., twice a week) sc that received icv moxonidine (50 nmol/ l twice a day) or vehicle (1 l twice a day). Values expressed as mean S.E.M. n = number of animals.

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Figure 10. Mean arterial pressure in rats treated with DOCA (25 mg/kg b.w., twice a week) sc that received icv moxonidine (50 nmol/1 l twice a day) or vehicle (1 l twice a day). Values expressed as mean S.E.M. n = number of animals.

To investigate if alpha2-adrenergic/imidazoline receptor agonists into the LV could also modify other ingestive behaviors, we tested the effects of moxonidine into the LV on 24 h food deprivation-induced food intake and meal-associated water intake in the same rats. Male rats (n = 11) with cannula implanted in the LV were used. The rats were submitted to 24 h food deprivation with water available. Fifteen minutes prior to the beginning of food and water intake tests, rats received moxonidine (5, 10 or 20 nmol) or vehicle injection into the LV. Moxonidine injection (10 and 20 nmol) into the LV reduced meal-associated water intake (3.1 ± 1.3 ml/90 min and 4.1 ± 1.9 ml/90 min, respectively) compared to control group (6.6 ± 1.4 ml/90 min), [F(3,30) = 5.4; p < 0.05], (Figure 11). Moxonidine (5, 10 and 20 nmol) into the LV had no effect on food intake (7.3 ± 0.1; 6.3 ± 0.2; 6.0 ± 1.1 g/90 min, respectively) compared to control group (6.6 ± 1.6 g/90 min), [F(3,30) = 0.3; p > 0.05], (Figure 12).

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Figure 11. Cumulative meal-induced water intake in rats submitted to 24 h food deprivation treated with icv injection of moxonidine (5, 10 or 20 nmol/1 l) or vehicle. Values expressed as mean S.E.M. n = number of animals.

Figure 12. Cumulative food deprivation-induced food intake in rats submitted to 24 h food deprivation treated with icv injection of moxonidine (5, 10 or 20 nmol/1 l) or vehicle. Values expressed as mean S.E.M. n = number of animals.

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Previous studies have already shown acute (in the first 2 h after the injections) inhibitory effects of alpha2-adrenergic/imidazoline receptor agonists like clonidine and moxonidine injected icv or in different forebrain areas on water intake and sodium intake [Le Douarec et al., 1971; Fregly et al., 1981; Fregly et al., 1984a; Fregly et al., 1984b; Sugawara et al., 1999; Callera et al., 1993; De Luca Jr & Menani, 1997; De Paula et al., 1996; Ferrari et al., 1990; Menani et al., 1999]. The pre-treatment with specific alpha1 or alpha2-adrenergic antagonists or alpha2/imidazoline antagonists showed that the inhibitory effects of clonidine or moxonidine on sodium and water intake depend on the activation of alpha2 adrenergic receptors located probably in the forebrain [Ferrari et al., 1990; Callera et al., 1993; De Luca Jr & Menani, 1997; Menani et al., 1999; Sugawara et al., 1999; Andrade et al., 2003; de Oliveira et al., 2003]. The present results show that also daily water and sodium intake is reduced by moxonidine injected icv twice a day and these effects are also probably dependent on the activation of forebrain alpha2-adrenergic receptors. Because moxonidine injected into the lateral ventricle did not change food intake, the effects of moxonidine on water and sodium intake cannot be attributed to a non-specific inhibition of ingestive behaviors. The results also show that there is a good correlation between the reduction of DOCAinduced water and NaCl intake and the reduction of hypertension produced by the activation of central alpha2-adrenergic/imidazoline receptors. Increases in sodium and water intake and changes in renal excretion are probably involved in DOCA-induced hypertension [Fluharty & Epstein, 1983; Denton, 1984; Sakai et al, 1986; Galaverna et al., 1991; Balasubramaniam et al., 1995; Kanagy & Webb, 1996; De Gobbi et al, 2000; O‘Donaughy et al., 2006; O‘Donaughy & Brooks, 2006; Sakai et al., 1996]. Besides the inhibition of water and sodium intake, moxonidine into the lateral ventricle also induces diuresis and natriuresis [Penner & Smyth, 1994a; Penner & Smyth, 1994b; Penner & Smyth, 1995; Menani et al., 1999; Menani et al., 2006]. Chronic ingestive and renal effects may play important role in the reduction of arterial pressure by chronic treatment with moxonidine into the lateral ventricle in DOCAtreated rats, because differently from the inhibition that it produces on water and sodium intake, moxonidine produces no change in arterial pressure or heart rate when injected into the lateral ventricle. However, moxonidine acutely reduces arterial pressure, heart rate and mesenteric and hindlimb vascular resistances when injected into the 4th ventricle, an effect dependent on the inhibition of sympathetic system [Nurminen et al., 1998; Moreira et al., 2004]. The reduction of arterial pressure became evident in the 5th day of treatment with moxonidine, but is not significant in the first 2 days of treatment, which suggests a more chronic mechanism to reduce arterial pressure, instead of the inhibition of sympathetic system that may occur minutes after moxonidine administration.

THE INHIBITORY MECHANISMS OF THE LATERAL PARABRACHIAL NUCLEUS ON WATER AND SODIUM INTAKE - EFFECTS OF MOXONIDINE The lateral parabrachial nucleus (LPBN) is a pontine structure located dorsolaterally to the superior cerebellar peduncle (SCP). The LPBN is reciprocally connected to forebrain areas, such as the paraventricular nucleus of the hypothalamus, central nucleus of amygdala and median preoptic nucleus, and to medullary regions, like the area postrema (AP) and

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medial portion of the nucleus of the solitary tract (mNTS), [Norgren, 1981; Ciriello et al., 1984; Fulwiler & Saper, 1984; Lança & van der Kooy, 1985; Herbert et al., 1990; Jhamandas et al., 1992; Krukoff et al., 1993; Jhamandas et al., 1996]. Therefore, the LPBN may convey signals that ascend from AP/mNTS to the forebrain areas involved with the control of fluid and electrolyte balance. Recent results have shown the existence of important inhibitory mechanisms for sodium and water intake in the LPBN. Bilateral injections of methysergide, a serotonergic receptor antagonist, into the LPBN, markedly increase NaCl intake induced by ANG II administered either icv or into SFO and by 24 h of water deprivation, 24 h of sodium depletion or DOCA [Colombari et al., 1996; Menani et al., 1996; Menani et al., 1998a; De Gobbi et al., 2000]. Methysergide injected bilaterally into the LPBN also increases, while injections of the serotonergic 5-HT2A/2C receptor agonist 2,5-dimetoxy-4-iodoamphetamine hydrobromide (DOI) reduces NaCl intake induced by combined treatment with furosemide (FURO) and the angiotensin converting enzyme inhibitor captopril (CAP) injected subcutaneously [Menani et al., 1996]. Besides metysergide, also DNQX (glutamate antagonist) or α-helical corticotropinreleasing factor (CRF)9–41 (CRF antagonist) into the LPBN increase hypertonic NaCl intake and eventually water intake induced by the treatment with FURO + CAP, while injections of the respective agonists (AMPA and CRF) produce opposite effects [Xu et al., 1997; De Castro e Silva et al., 2006]. Blockade of cholecystokinin (CCK) receptors with proglumide bilaterally into the LPBN also increases FURO + CAP-induced sodium intake [Menani & Johnson, 1998]. CCK and serotonin may act in an interdependent and cooperative manner in the LPBN to inhibit sodium intake [De Gobbi et al., 2001]. The interdependent and cooperative action of serotonin and CCK in the LPBN means that the release of serotonin induces also the release of CCK in the LPBN and vice-versa, and that the action of both in their respective receptors in the LPBN is necessary for the full inhibition of sodium intake [De Gobbi et al., 2001]. Differently from the inhibition produced in forebrain areas, the activation of alpha2 adrenergic receptors with moxonidine bilaterally into the LPBN increases FURO + CAP-induced sodium intake [Andrade et al., 2004]. The blockade of serotonin and CCK or the activation of alpha2-adrenergic receptors in the LPBN only increases sodium intake in animals previously submitted to treatments that stimulate sodium and/or water intake, but not in satiated and normovolemic animals, which suggests that the blockade of LPBN inhibitory mechanisms only increases sodium intake if facilitatory mechanisms were also simultaneously active [Colombari et al., 1996; Menani et al., 1996; Menani et al., 1998a; Menani et al., 1998b; Menani et al., 2000]. However, more recent results have also shown that the activation of GABAA receptors with bilateral injections of muscimol or the opioid receptors with beta-endorphin into the LPBN induces strong ingestion of hypertonic NaCl in satiated and normovolemic rat not submitted to any other treatment, which suggests that only the blockade of LPBN inhibitory mechanisms is enough to release sodium intake in satiated animals [Callera et al., 2005, De Oliveira et al., 2008]. It is particularly interesting the strong increase in 0.3 M NaCl intake by rats submitted to intragastric load of 2 ml of 2 M NaCl that received bilateral injections of methysergide or moxonidine into the LPBN [De Luca Jr et al., 2003; Andrade et al., 2006]. The intragastric 2 M NaCl load induces a 4% increase in plasma sodium and osmolality and reduces plasma renin activity by half without changing blood volume [Pereira et al., 2002]. Therefore, in rats

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submitted to intragastric 2 M NaCl combined with methysergide or moxonidine into the LPBN sodium appetite arises in a condition of hyperosmolarity. Because methysergide or moxonidine into the LPBN in satiated rats produces no effect on sodium intake, the ingestion of hypertonic NaCl by hyperosmotic rats suggests that the increase in osmolarity may also be an excitatory stimulus for sodium intake, which suggests that brain circuits that control sodium appetite, like those subserving thirst, are activated not only by extracellular dehydration, but also by intracellular dehydration. However, the activation of the behavior depends on the modulation exerted by mechanisms involving the LPBN that strongly inhibit sodium appetite. The blockade of serotonin or the activation of alpha2-adrenergic receptors in the LPBN deactivates the inhibitory mechanisms and releases hypertonic NaCl intake if osmolarity is high [De Luca Jr et al., 2003; Andrade et al., 2006]. Because the activation of alpha2-adrenergic receptors by bilateral injections of moxonidine into the LPBN increases 0.3 M NaCl and water intake induced by extracellular or intracellular dehydration [Andrade et al., 2004; Andrade et al., 2006], we tested also the effects of moxonidine into the LPBN on water and 0.3 M NaCl intake by rats submitted to 24 h of water deprivation. Water deprivation produces an absolute dehydration, i.e., produces simultaneous extracellular and intracellular dehydration. In male rats submitted to 24 h water deprivation, water and 0.3 M NaCl intake was tested 15 min after bilateral injections of moxonidine (0.5 nmol/0.2 microliter) or vehicle into the LPBN. Moxonidine injections increased 0.3 M NaCl intake (23.4 8.0 ml/2 h, vs. vehicle: 2.0 0.7 ml/2 h), [F(1, 4) = 8.3; p < 0.05], but did not change water intake, [F(1, 4) = 0.6; p > 0.05], (Figure 13). Similar to rats treated with ANG II or hypertonic NaCl, as shown in Figure 13, water deprived rats strongly prefer to ingest water immediately after the access to it, while ingestion of 0.3 M NaCl is almost absent. However, water deprived rats start ingesting marked amount of 0.3 M NaCl if they received moxonidine into the LPBN. Note that the amount of 0.3 M NaCl ingested after moxonidine injections into the LPBN by water deprived rats is similar to those ingested during intracellular [Andrade et al., 2006] or extracellular dehydration [Andrade et al., 2004] separately. Because moxonidine injected into the LPBN did not change sodium intake in satiated animals that do not receive an additional dipsogenic/natriorexigenic treatment, it is possible to suggest that moxonidine in the LPBN releases facilitatory signals for sodium intake that are otherwise under inhibitory control of LPBN. Ingestion of sodium intake increases the activity of LPBN neurons, which results in increases in the activity of LPBN inhibitory mechanisms. Without the action of these inhibitory mechanisms the ingestion of sodium induced by different mechanisms increases. Recent results also show that moxonidine injections into the LPBN induce hypertonic NaCl intake without changing food or water intake during a meal [Andrade et al., 2007]. When food was not available during the test, moxonidine into the LPBN produced no change in 0.3 M NaCl intake or in water intake in food-deprived rats, suggesting that signals generated during meal, not hunger, combined with moxonidine acting in the LPBN induce NaCl intake [Andrade et al., 2007]. Based on these results, one may consider that dipsogenic signals activated during a meal may also facilitate hypertonic NaCl intake besides water intake. However all or at least some of these signals, like cell-dehydration or hyperosmolarity, activate LPBN inhibitory mechanisms to restrain sodium intake. Moxonidine blocks the LPBN inhibitory mechanisms and releases the influence of facilitatory signals activated by meal to induce hypertonic NaCl intake [Andrade et al., 2007].

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Figure 13. A) Cumulative 0.3 M NaCl intake and B) cumulative water intake in rats submitted to 24 h water deprivation treated with bilateral injections of moxonidine (0.5 nmol/0.2 l) or vehicle into the LPBN. Values expressed as mean S.E.M. n = number of animals.

CONCLUSIONS Recent studies clearly show the strong influence of the inhibitory mechanisms on sodium appetite. Although the activation of excitatory mechanisms may drive animals to ingest sodium, this behavior is strongly facilitate by the deactivation of inhibitory mechanisms, which means that inhibitory mechanisms act limiting sodium intake. The importance of inhibitory mechanisms for the control of sodium appetite or for the satiety is also clearly demonstrated by the ingestion of hypertonic NaCl after only the deactivation of LPBN inhibitory mechanisms, like that produced by gabaergic or opioid activation in the LPBN in satiated and normovolemic rats that received no other treatment. In this case sodium ingestion is induced only by the blockade of LPBN inhibitory mechanisms, independently on the

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activation of excitatory mechanisms. Another interesting mechanism that modulates sodium (and water intake) is the alpha2-adrenergic receptors that have opposite effects on sodium and water intake depending on the central area they are located. In the forebrain, the activation of alpha2-adrenergic receptors stimulates inhibitory mechanisms and in the LPBN the activation of alpha2-adrenergic receptors deactivates the inhibitory mechanisms, facilitating water and sodium intake. The antidipsogenic and antinatriorexigenic effects like those produced in DOCA-treated rats, together with the diuretic and natriuretic effects of the alpha2adrenergic/imidazoline agonist moxonidine acting in the forebrain areas may reinforce the anti-hypertensive response that is suggested to depend on sympathetic inhibition produced by the action in the hindbrain.

ACKNOWLEDGEMENTS The authors thank Silas P. Barbosa, Reginaldo C. Queiroz and Silvia Fóglia for expert technical assistance, Silvana A. D. Malavolta for secretarial assistance and Ana V. de Oliveira for animal care. They also thank Solvay Pharma and Dr. P. Ernsberger for the donation of moxonidine. This research was supported by public funding from Fundação de Amparo a Pesquisa do Estado de São Paulo (FAPESP) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).

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Sato, M.A.; Sugawara, A.M.; Menani, J.V. & De Luca Jr, L.A. (1997). Idazoxan and the effect of intracerebroventricular oxytocin or vasopressin on sodium intake of sodiumdepleted rats. Regul. Pept. 30;69(3),137-42. Schulkin, J., Marini, J. & Epstein, A.N. (1989). A role for the medial region of the amygdala in mineralocorticoid-induced salt hunger. Behav. Neurosc. 103,178-185. Seeley, R.J., Galaverna, O., Schulkin, J., Epstein, A.N. & Grill, H.J., (1993). Lesions of the central nucleus of amygdala. II. Effects on intraoral NaCl intake. Behav Brain Res., 59(12):19-25. Sheng, M. & Greenberg, M.E. (1990). The regulation and function of c-fos and other immediate early genes in the nervous system. Neuron, 4,477-485. Stricker, E.M. & Verbalis, J.G. (1996). Central inhibition of salt appetite by oxytocin in rats. Regul. Pept. 66(1-2),83-5. Stumpf, W.E. & Sar, M. (1979). Glucocorticoid and mineralocorticoid hormone target sites in the brain: autoradiographic studies with corticosterone, aldosterone and dexamethasone. In: Interaction within the brain pituitary-adrenocortical system. Jones, M. T., Dallman, M. F., Chattopadhyay, S. eds.. New York: Academic Press, 137-147. Sugawara, A.M., Miguel, T.T., De Oliveira, L.B., Menani, J.V. & De Luca Jr, L.A. (1999). Noradrenaline and mixed alpha2 adrenoreceptor/imidazoline-receptor ligands: effects on sodium intake. Brain Res. 839, 227-234. Sugawara, A.M., Miguel, T.T., Pereira, D.T.B., Menani, J.V. & De Luca Jr, L.A. (2001). Effects of central imidazolinergic and alpha2-adrenergic activation on water intake. Braz. J. of Med. and Biol. Res., 34,1185-1190. Thunhorst, R.L., Xu, Z., Cicha, M.Z., Zardetto-Smith, A.M. & Johnson, A.K. (1998). Fos expression in rat brain during depletion-induced thirst and salt appetite. Am. J. Physiol., 274,R1807-R1814. Tsay, S.Y., Caristedt-Duke, D., Weigel, N.L., Dahlman, K., Gustaffsson, J.A., Tsay, M.J. & O‘Malley, B.W. (1988). Molecular interactions of steroid hormone receptor with its enhancer element: evidence for receptor dimer formation. Cell, 55,361-369. Tsujino, T, Sano, H., Kubota, Y., Hsieh, S.T., Miyajima, T., Saito, K., Nakajima, M., Saito, N. & Yokoyama, M. (1992). Expression of Fos-like immunoreactivity by yohimbine and clonidine in the rat brain. Eur. J. Pharmacol. 226,69-78. Verbalis, J.G.; Blackburn, R.E.; Hoffman, G.E. & Stricker, E.M. (1995). Establishing behavioral and physiological functions of central oxytocin: insights from studies of oxytocin and ingestive behaviors. Adv. Exp. Med. Biol. 395,209-25. Vivas, L., Pastuskovas, C.V. & Tonelli, L. (1995). Sodium depletion induces Fos immunoreactivity in circumventricular organs of the lamina terminalis. Brain Res., 679,34-41. Xu, J., Woodworth, C.H. & Johnson, A.K. (1997). Glutamate and the role of the lateral parabrachial nucleus in the control of water and salt intake in rats. Soc Neurosc Abstr, 23, p.1348. (Abstract) Yada, M.M., De Paula, P.M., Menani, J.V., Renzi, A., Camargo, L.A.A., Saad, W.A. & De Luca Jr, L.A. (1997a). Receptor-mediated effects of clonidine on need-induced 3% NaCl and water intake. Brain Res. Bull. 42, 205-209. Yada, M.M., De Paula, P.M., Menani, J.V. & De Luca Jr, L.A. (1997b). Central alphaadrenergic agonists and need-induced 3% NaCl and water intake. Pharmacol. Biochem. Behav. 57, 137-143.

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Zardetto-Smith, A.M., Beltz, T.G. & Johnson, A.K. (1994). Role of central nucleus of the amygdala and bed nucleus of the stria terminalis in experimentally-induced salt appetite. Brain Res., 645(1-2),123-34. Zhang, D., Epstein, A.N. & Schulkin, J. (1993). Medial region of the amygdala: involvement in adrenal-steroid-induced salt appetite. Brain Res., 600,20-26.

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Chapter 4

CACHEXIA: DISRUPTION IN APPETITE REGULATION IN NEED OF A SUCCESSFUL INTERVENTION Mark D. DeBoer University of Virginia School of Medicine Charlottesville, VA 22901

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ABSTRACT Cachexia is a devastating syndrome of body wasting that worsens quality of life and survival for patients suffering from already dire and restrictive diseases such as cancer, chronic kidney disease and chronic heart failure. The common features of cachexia in these disease states and the common feature of systemic inflammation suggest shared pathophysiologic roots of cachexia in these conditions. However, previous attempts to treat cachexia via anti-inflammatory interventions and multiple other means have not proven effective, and no unifying treatment has emerged that is effective in treating cachexia in multiple disease states. Basic science investigations have revealed that inflammation-induced activation of the central melanocortin system is one likely means of producing anorexia and lean body wasting in this syndrome. Similarly, basic science approaches to blocking melanocortin activity appeared promising by demonstrating improvement of food intake and weight retention in cachexia, though unfortunately data regarding human treatment is still lacking. Finally, a new treatment approach via administration of ghrelin or ghrelin agonists appears to be a promising means of treatment, as suggested by both basic science and early human experiments, though much more investigation is needed. The hope of all investigators and clinicians in the field is that successful treatment of the symptoms of cachexia will lead to an improvement in quality of life and survival among all patients suffering from this disease.

INTRODUCTION Cachexia is a wasting syndrome that afflicts patients with multiple different underlying diseases and that has been recognized since antiquity for its dire effects on prognosis. The term itself is derived from the Greek ―kakos‖ (bad) and ―hexis‖ (condition), and indeed the

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syndrome of lost body mass was described by Hippocrates, who observed, ―…the shoulders, clavicles, chest and thighs melt away. This illness is fatal…‖ Despite this long-standing nature of our recognition of this disorder, successful treatment has remained elusive. However, as the entity of cachexia has gained recognition over the past decade new treatment modalities have continued to be introduced in an attempt to improve the destructive symptoms seen in this disease. Cachexia produces anorexia, loss of lean and fat mass, and increased energy expenditure, symptoms that occur with remarkable similarity among patients with a variety of underlying disease processes including cancer,[1] renal failure,[2] and heart failure.[3] Given the catabolic nature of the syndrome, perhaps the most perplexing symptom is the loss of appetite, which occurs at a time when the body would logically require increased energy supply as it utilizes muscle and fat stores. Additionally, given the pleasure that most individuals derive from food consumption, the anorexia of cachexia also contributes to decreases in quality of life. Not surprisingly, then, many of the newer proposed treatments for cachexia focus on increasing appetite and food intake. As we shall see, in addition to sharing common symptoms of cachexia, the underlying diseases that involve cachexia also bear other similarities with respect to each other, including the production of systemic inflammation. This is seen by increases in acute phase reactants and pro-inflammatory cytokines in the setting of cancer, renal failure and heart failure. This systemic inflammation is felt to be part of the underlying pathophysiology resulting in cachexia. Recent work has demonstrated that inflammation acts on the brain to stimulate important appetite-regulating centers including the central melanocortin system in the hypothalamus. Thus, many additional interventions have focused on decreasing inflammation as a means of improving the cachexia. We will review here the data on clinical symptoms of cachexia caused by three common underlying conditions: cancer, chronic kidney disease, and chronic heart failure. We will also review data regarding the inflammatory processes increased by these diseases and evidence from trials for potential therapeutic agents to treat cachexia in these settings, revealing an overall impression that current treatment modalities have been for the most part ineffective. We will end by reviewing promising data on the use of two potential treatments for cachexia: antagonism of the melanocortin system and appetite stimulation via use of ghrelin-receptor agonists.

I. UNDERLYING DISEASE STATES AND EARLY TREATMENT APPROACHES Cancer Clinical Features Cachexia is a common feature of multiple malignancies, affecting up to 85% of patients with certain types of cancer and contributing to over 20% of all cancer deaths.[1,4,5] The weight loss experienced by patients can be severe, including loss of up to 75% of muscle mass.[6] However, even subtle amounts of weight loss and anorexia are associated with a poorer prognosis, a worsened response to chemotherapy and increased morbidity.[4,6,7]

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Cachexia: Disruption in Appetite Regulation in Need of a Successful Intervention 139 Additionally, the loss of appetite as a feature is an ominous sign among malignancies: one survey of patients with terminal cancer found the presence of nausea or emesis was associated with a 68% decrease in survival.[8] Despite this weight loss, patients with cancer cachexia frequently exhibit a paradoxic increase in resting energy expenditure.[9,10] The sum of these issues is that cancer patients with cachexia have a substantial decrease in quality of life.[11,12] Not surprisingly, cancer cachexia is pleomorphic in etiology with multiple contributing causes including tumor production of cachexia-related factors and host responses to the tumor burden.[1] One mechanism for wasting in cancer cachexia appears to be via tumor release of specific cachectogenic agents including lipid mobilizing factor (LMF), which was originally isolated from the urine of patients with cachexia‘[13,14]. LMF stimulates lipolysis and increases uncoupling proteins that contribute to increased metabolic rate. Despite a strong implication in the loss of lean body mass, LMF has not been linked to the loss of appetite related to cancer cachexia.[1] One common factor that has been implicated in the loss of appetite in cancer is the presence of pro-inflammatory cytokines including IL-1 , IL-6 and TNFThese have been demonstrated to be produced by tumor cells in tissue culture as well as in vivo, suggesting a possible survival advantage to the tumor from increased local mobilization of nutrients.[15,16] Additionally, the host response to tumor presence involves production of acute phase proteins (APP) including C-reactive protein (CRP) that are associated with increased levels of pro-inflammatory cytokines. Up to 50% of cancer patients have elevated APP at diagnosis and the associated increase in cytokines is strongly implicated in producing anorexia.[1,17] The importance of APP in tumor prognosis was demonstrated in a study of patients with pancreatic cancer in which elevated CRP at diagnosis predicted a 78% reduction in survival time.[17] Among patients with other gastrointestinal malignancies, CRP was better than tumor staging at predicting survival one year after surgery.[16] This production of inflammation is important because one means by which inflammation suppresses appetite in cancer cachexia and other cachexia syndromes has been shown to be via direct stimulation of appetite-regulating centers in the hypothalamus and brainstem, including the central melanocortin system, as will be discussed later.

Anti-Inflammatory Treatment Because of the prominent feature of inflammation in cancer cachexia, many attempts to treat the associated wasting have focused on decreasing the inflammatory state. Non-steroidal anti-inflammatory agents and monoclonal antibodies against specific pro-inflammatory cytokines have produced minor improvements in decreasing serum markers of APP response but have not produced significant improvements in weight. For example, one randomized trial tested the effect of providing indomethacin, prednisone or placebo to 135 patients with terminal solid tumor malignancies. In this trial, indomethacin treatment failed to increase weight, and though prednisone did result in a significant weight gain, other studies have shown a high rate of corticosteroid toxicity that ultimately had a negative impact on quality of life.[18,19] Thus far, no NSAID or corticosteroid treatment has produced significant improvements in retaining or increasing lean body mass in cachectic patients. Another treatment chosen for its anti-inflammatory characteristics is eicosapentanoic acid (EPA), which is an essential polyunsaturated fatty acid found in fish oil. EPA has been shown to decrease levels of IL-6.[20,21] Initially it appeared that EPA might increase weight gain in

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cancer, such as in a trial in an unrandomized trial among patients with pancreatic cancer.[22] More recently, however, other randomized trials of EPA vs. placebo failed to produce clinically significant differences in weight or lean body mass over an 8 week time frames.[23,24]

Megestrol Acetate Megestrol acetate, a synthetic prostaglandin analogue, also initially offered much promise as a treatment modality for cancer cachexia. Administration of megestrol acetate has been shown in multiple studies and a recent Cochran review to increase food intake in patients with cachexia through an unknown mechanism.[25] Unfortunately, the weight gain observed following megestrol acetate treatment has been demonstrated to be due primarily to increased water and fat content without significant changes in lean body mass.[26-28] Also, patients taking megestrol acetate did not have an increase in quality of life or an improvement in cancer outcomes, deflating many of the initial hopes. Other failed treatments included cyproheptidine and dronabinol, both of which failed to prevent weight loss or perform better than megestrol acetate.[29,30] Need for Effective Therapies in Cancer Cachexia Thus, as will become a theme among the common cachexia syndromes, none of the treatments studied have had an impressive enough effect on weight, quality of life or survival to transfer to widespread use. In such a common and emotional disease pattern, the introduction of an effective treatment would be likely to be employed in widespread use and have major effects on patients suffering from cancer cachexia.

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Chronic Kidney Disease Clinical Features Significant weight loss—predominantly in the form of protein energy imbalance—is also a major feature of chronic kidney disease (CKD), affecting up to 64% of patients on hemodialysis.[31] In the setting of CKD this syndrome is sometimes incorrectly referred to as ―malnutrition,‖ which is misleading because it implies that the syndrome can be resolved simply by improving the diet.[32,33] As in cancer cachexia, the anorexia and decreased protein intake of chronic renal failure are associated with increased metabolic demand.[34] Increased resting energy expenditure (REE) is common in patients on dialysis and in one prospective study, higher REE was associated with greater mortality in patients on peritoneal dialysis.[35] The appetite and metabolic changes associated with CKD have been attributed to a wide variety of causes including uremia, acidosis and high levels of leptin (due to impaired renal clearance).[33,34,36] As is the case with cancer cachexia, the cachexia of CRF is strongly linked to increased inflammatory markers, though the cause of the increased inflammation in CKD is not entirely clear.[32] Inflammatory markers such as c-reactive protein (CRP) are highly associated with clinical features of protein energy imbalance, increased metabolic rate and poor prognosis.[37] A study of 128 patients on hemodialysis who were followed prospectively for 36 months found that compared to survivors patients who died over the 3 years were approximately twice as likely (85% vs. 44%) to have had malnutrition and were

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more than three times as likely (44% vs. 13%) to have a highly elevated c-reactive protein (CRP).[38] Both elevated CRP and malnutrition were likely to coincide with heart disease, and each is an independent risk factor for mortality.

Treatment Approaches Approaches to treating cachexia of CKD have differed somewhat from cancer cachexia, likely owing to the differences in the underlying diseases. Unlike the cancer field, antiinflammatory treatment for CKD has not yet been studied extensively, though pilot studies for such an intervention are now underway. One unblinded trial of omega 3 fatty acids failed to reduce markers of inflammation.[39] Pharmacologic treatment of wasting in CKD has thus far focused on increasing lean body mass via anabolic compounds. Two trials used recombinant human growth hormone for adults who had lost weight on dialysis, since there is some evidence that adults and children with renal failure exhibit growth hormone resistance. These trials were performed as doubleblinded, placebo-controlled studies over a 6 month time course. Growth hormone treatment resulted in 3-6 kg gains in lean body mass accompanied by a 3-6 kg decreases in fat mass.[40,41] Neither of these trials evaluated changes in appetite or sense of well-being. Another randomized trial used the anabolic steroid nandrolone or placebo for 6 months among 29 subjects on hemo- or peritoneal-dialysis.[42] Nandrolone produced a 4.5 kg gain in lean body mass (versus 2 kg gain for placebo) with a 2.5 kg loss in fat mass (vs. 0.5 kg loss for placebo). Quality of life was improved as indicated by decreased fatigue in the nandrolone group vs. placebo but again no comment was made regarding the effects of treatment on appetite. These results clearly are promising, though one limitation of nandrolone treatment is that it can only be used in male patients, since women would experience excessive virilization during treatment. As with cancer cachexia, treatment with megestrol acetate has been attempted in a double-blined, crossover study of patients with CKD on hemodialysis. This study revealed a significant amount of side effects during treatment with megestrol acetate vs. placebo. As was the case in cancer cachexia, megestrol acetate failed to improve retention of lean body mass.[43] Thus, cachexia caused by chronic kidney disease has had some improvement in identifying potential treatments—including growth hormone injections and an anabolic steroid—but neither with any reported improvement in appetite.

Heart Failure Clinical Features Chronic heart failure (CHF) caused by prior myocardial infarctions or dilated cardiomyopathy is seen in 1-2% of the population of developed countries.[44,45] As is the case with cancer and chronic kidney disease patients, many of these patients begin to exhibit significant weight loss and anorexia, frequently referred to as cardiac cachexia, affecting approximately 15% of this population.[46] The weight loss observed in this group involves significant losses of lean and adipose tissue (18% and 37% respectively, compared to noncachectic patients with CHF) and this loss of body mass is an independent risk factor for mortality with a hazard ratio of 3.73 over an 18 month period.[46,47] Interestingly, whereas

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non-cachectic patients with CHF exhibit increase in resting metabolic rate vs. controls, CHF patients with cachexia exhibit a decreased resting metabolic rate, marking a difference between cachexia in CHF and cancer or chronic kidney disease.[48,49] The exact etiology behind the cachexia seen in CHF is again uncertain, and the importance of adequate perfusion to many normal body processes further complicates the process. Anorexia in CHF can be related to dyspnea and fatigue, as well as to intestinal edema and resultant nausea.[50] Fat malabsorption further contributes to decreased calorie influx.[51] Also, anorexia in CHF can be associated with some of the treatments for CHF such as due to side effects of medications such as digoxin and ACE inhibitors or due to lower palatability of a sodium-restricted diet.[50] Finally, as was the case for cachexia caused by cancer and chronic kidney disease, a constant feature in CHF cachexia is the presence of inflammatory markers. Patients with CHF cachexia exhibit a 2-2.5 fold increase in TNF- and IL-6 compared to patients with noncardiac CHF. This increase in inflammation is the strongest predictor for prior weight loss.[52-54] Serum levels of TNF- and IL-6 are also independent risk factors for survival in CHF patients.[55,56] The increase in cytokines is postulated to be due to several sources including release of TNF- by the failing myocardium, release of endotoxin through an edematous bowel wall or production of inflammatory factors from hypoxic tissue.[50] As is observed for patients with anorexia secondary to CRF, patients with CHF-induced cachexia exhibit a growth hormone resistance, which is associated with increased levels of TNF- .[57]

Treatment Approaches Many of the treatments that have been shown to help in cachexia associated with CHF are aimed at treating the underlying disease. Short term trials of the positive inotrope levosimendan resulted in decreased levels of IL-6, though it is not known if this resulted in a change in lean body mass.[58] Use of angiotensin-converting enzyme (ACE) inhibitors in a large (817 subject) trial showed a decreased risk of weight loss vs placebo (hazard ratio 0.8) over a 4 year study period.[59] The effect of ACE inhibitors was likely partially due to improved disease but may also have produced effects through decreasing the effects of angiotensin II on IGF-1.[60] Lastly, anti-inflammatory treatment has thus far proven ineffective in the setting of CHF. For example, a TNF- receptor fusion protein (eternacept) was designed to decrease bioavailable TNF- but it produced no difference in outcome from placebo in a large trial. In another trial, adminstration of a TNF- antibody resulted in increased mortality in the treatment group.[50] Furthermore, long-term use of non-steroidal anti-inflammatory COX-2 inhibitors caused an increase in cardiac events. One anti-inflammatory trial that did prove successful from a cardiac standpoint involved the use of a procedure known as CelacadeTM, in which autologous blood is exposed to oxidative stress at an increased temperature and then re-administered intramuscularly. This is known to decrease pro-inflammatory cytokine levels possibly via increases in anti-inflammatory mediators. A randomized, double blinded trial of this failed to change serum levels of cytokines but did result in an improvement in mortality.[61] No comment was made on changes in appetite, weight or lean body mass during this trial.

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Cachexia: Disruption in Appetite Regulation in Need of a Successful Intervention 143

SUMMARY OF CACHEXIA ASSOCIATED WITH CANCER, CRF AND CHF There are many similarities in the syndrome of cachexia caused by these diverse disease processes. In each of these conditions cachexia consists of wasting of lean body mass with a paradoxical decrease in appetite and an association with worsened prognosis. In each of these disorders there appears to be a link to elevated inflammatory markers or cytokines are in turn thought to play a role in the pathophysiology and illness symptoms. Nutritional support alone does not appear to improve the symptoms of cachexia caused by any of these diseases and pharmacologic interventions have failed to produce demonstrable gains in appetite, lean body mass and quality of life.

II. TARGETED APPETITE INTERVENTIONS IN THE TREATMENT OF CACHEXIA

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Central Melanocortin System In addition to the targeting of inflammatory pathways for the treatment of cachexia, much of the recent focus has been on affecting appetite regulating centers in the brainstem and hypothalamus. The best-described of these centers is the central melanocortin system, the main nucleus of which is in the arcuate nucleus of the hypothalamus.[62] The importance of the central melanocortin system first came to widespread recognition with the description of the agouti mouse, which exhibited hyperphagia and morbid obesity due to over-expression of agouti, an endogenous inhibitor of the melanocortin system.[63] Since that time, the melanocortin system has been well-described as consisting of two classes of neurons: anorexigenic and orexigenic. The anorexigenic neurons produce pro-opiomelanocortin (POMC), which is a long precursor peptide that is cleaved to produce -MSH. -MSH then binds to and activates specific melanocortin receptors on a variety of second-order neurons in the hypothalamus and brainstem (see Figure 1).[64] The action of -MSH on these receptors—including the melanocortin 3 receptor (MC3-R) and melanocortin-4 receptor (MC4-R)—produces a tonic restraint on feeding activity. That is to say that activation of the central melanocortin system causes a decrease in appetite. By contrast the orexigenic neurons in the arcuate nucleus produce both neuropeptide-Y (NPY) and agouti-related peptide (AgRP), both of which act on second-order neurons to result in an increase in feeding behavior. What is unique about the melanocortin system is that AgRP acts on the same MC3-R and MC4-R receptors as does -MSH but AgRP acts as an antagonist and thus produces an increase in feeding behavior. Thus, inhibition of the melanocortin system causes an increase in appetite. These pathways of the central melanocortin system lead to another interesting feature of the system in that mutations in the MC4-R receptor in humans result in early onset obesity and increased lean mass. In fact these MC-4R mutations are the most common monogenic cause of severe obesity, though they also lead to an increase in lean body mass as well.[65]

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Figure 1. Model of the effects of inflammation produced during cachexia on activity to the central melanocortin system. Inflammatory cytokines such as that are produced by the underlying disease activate cytokine receptors on neurons in the arcuate nucleus of the hypothalamus (such as IL-1 binding to the IL-1 receptor in the figure). When this occurs on neurons expressing proopiomelanocortin (POMC), this leads to an increase in anorexigenic signaling via stimulation of MC4 receptors on second-order neurons. Conversely, when IL-1 binds to neurons that produce Agoutirelated peptide (AgRP) and neuropeptide Y (NPY) this leads to a decrease in orexigenic signaling by NPY via the NPY Y1 receptor and by AgRP acting as an antagonist of MC4 receptors on second-order neurons. The response of second order neurons produces signals that lead to cachexia. Blockade of MC4 receptors on second-order neurons attenuates the increased anorexigenic signals and improves the symptoms of cachexia. From reference 64, used by permission.

The demonstration that melanocortin inhibition causes an increase in appetite immediately made the melanocortin system a logical target for pharmacologic interventions to treat cachexia.[66,67] These efforts became an even more logical step when it was demonstrated that the anorexigenic output by the melanocortin system was mediated by direct stimulation by central inflammation—particularly mediated by IL-1 —on neurons that express POMC in the arcuate nucleus.[68] This sets up the link between underlying cachexiaassociated conditions and activation of the central melanocortin system. As discussed previously, each of the conditions that result in cachexia also involves the up-regulation of inflammatory mediators. Also, for the case of cancer cachexia and chronic renal failure, it has been demonstrated that increases in inflammation cause decreased expression of AgRP and/or increased expression of POMC in the hypothalamus.[69,70] Thus, it appears that a common path for varying conditions resulting in cachexia is activation of the melanocortin system via increased inflammation. This increase in melanocortin activity by inflammation is at least in part at the level of the neurons expressing POMC and thus upstream of second-order neurons expressing MC4-R. Importantly, the sequence of these events leaves open the possibility of inhibiting the MC4-R—via use of genetic knock out animals or through administration of AgRP or small molecule antagonists—as a means of ameliorating the effects of increased inflammation on melanocortin tone.

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Cachexia: Disruption in Appetite Regulation in Need of a Successful Intervention 145 It is not surprising, then, that animal models of cachexia have consistently shown improvements in appetite and weight-gain following inhibition of the melanocortin system. The approaches that have been tested have employed models of cachexia produced via multiple underlying stimuli in rodents, including multiple types of implanted tumors and models of chronic kidney disease.[67,71-80] When left untreated, these models of cachexia result in decreased appetite and weight loss, ranging from a decrease in food intake of 50%80% vs. controls and loss of lean mass of 5%-10% vs. controls. Melanocortin inhibition was initially studied by using knock-out mice that are unable to express MC4-R and thus lack the constant anorexigenic tone placed on second-order neurons. Once this approach toward melanocortin antagonism was shown to ameliorate the decrease in appetite and weight loss among laboratory animals, administration of AgRH and multiple different small molecule antagonists of the MC-4R have been employed with success.[67,71-80] The success of melanocortin antagonists in laboratory models of cachexia lead to optimism that these would produce impressive clinical results as well. Unfortunately, as of the date of this publication, no clinical trial information has been released—positive or negative—regarding the use of melanocortin antagonists in the treatment of cachexia in humans.[81] This raises strong suspicions that treatment with these molecules is either inefficacious in humans or involves excessive risk or side effects. It is unclear when we will have answers to these questions.

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Ghrelin Treatment Another new avenue of treatment for cachexia involves the endogenous hormone ghrelin. Ghrelin was originally discovered because of its ability to stimulate growth hormone release via activity on the growth-hormone-secretagogue-1a (GHS-1a) receptor on growth hormone secreting cells in the pituitary.[82] However, after its discovery it became clear that a much more striking property of ghrelin was to stimulate food intake. Ghrelin is the only known circulating orexigenic hormone and is released principally by the stomach in response to time after a meal. Following meal ingestion, ghrelin levels in the serum then drop back to basal amounts and begin to rise again until the next meal.[83] Ghrelin is thus felt to be a mealinitiating signal. Another interesting feature of ghrelin is that serum levels increase in individuals following weight loss, paralleling an increased perception of hunger.[83] As with the central melanocortin system, the properties of increasing appetite made ghrelin a logical tool to test in cachexia intervention.[84] Interestingly, treatment with ghrelin may end up being the means by which melanocortin inhibition is achieved in clinical settings. This is because one of ghrelin‘s mechanisms of action is via stimulation of GHS-1a receptor in the hypothalamus.[85] In normal physiology, ghrelin acts on these receptors in the arcuate nucleus to increase expression and release of AgRP and NPY.[86] The same is also true when ghrelin is used as a treatment during an animal model of cancer cachexia, in which animals revieving ghrelin exhibit an increase in AgRP and NPY expression as well as increased food intake and lean body mass retention vs. controls.[69] Thus, one means by which ghrelin improves food intake in cachexia is via inhibition of the central melanocortin system. Another intriguing property of ghrelin is that the GHS-1a receptors are expressed on leukocytes, and ghrelin treatment has been shown to decrease release of immune mediators.

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This was shown in a mouse model of arthritis in which ghrelin treatment caused a decrease in paw swelling.[87] Additionally, pre-treatment with ghrelin caused a decrease in lipopolysaccaride-induced cytokine release from isolated macrophages. In a rat model of chronic kidney disease, ghrelin treatment caused an overall decrease in systemic inflammatory cytokines,[88] and a growing body of reports confirm other anti-inflammatory effects.[89-91] These anti-inflammatory effects of ghrelin may be another means by which ghrelin decreases melanocortin activity and improves appetite in the setting of cachexia. As was demonstrated with melanocortin antagonists, ghrelin has been shown to be efficacious in improving food intake and improving retention of lean body mass in a great variety of models of cachexia, including that caused by cancer, chronic renal failure and chronic heart failure.[69, 88, 92-95] These experiments have consistently demonstrated improvements in food intake (increases of 20%-56% vs. placebo), weight gain (300%-2200% over placebo) and lean body mass retention (changes of -1%-+26% following ghrelin treatment vs. changes of -12.6% - +2.8% with placebo). More significantly, ghrelin treatment has also been shown to be efficacious in short-term trials on humans with cachexia as well. Double-blinded cross-over studies of single doses of ghrelin given intravenously to patients with cancer cachexia resulted in 31-56% increases in food intake following administration.[96,97] Among patients with renal failure, a cross-over trial demonstrated that a single dose of ghrelin given subcutaneously increased food intake by 57% over placebo. And on a more long-term basis, ghrelin infusions were administered to in separate studies to patients with cachexia related to either chronic heart failure or chronic obstructive pulmonary disease.[98,99] In both of these studies, patients received twice-daily infusions of ghrelin over a 3 week course, resulting in 8-9% increases in food intake, 1.6-2% increases in weight and 1.8-2% increases in lean body mass. One draw back of all of the above studies is that they utilized ghrelin itself, as opposed to a small-molecule agonist. The acylated (active) ghrelin molecule has a half life of approximately 30 minutes in the serum and requires IV or subcutaneous administration.[100] The potential to design GHS-1a agonists with longer serum half-lives and oral bioavailability has stimulated the development of multiple synthetic ghrelin analogues. The only one of these to be reported in clinical use was RC-1291, an orally-bioavailable GHS-1a agonist that was administered to patients with cancer cachexia during a 12-week trial, resulting in a 0.6% increase in weight vs. a 1.45% weight loss among patients treated with placebo.[101] Several other such compounds have had efficacy demonstrated in animal models of cachexia but have yet to be reported in human application. Thus, treatment with ghrelin and other GHS-1a agonists represents an emerging avenue in the field of cachexia, with hope that its use will prove effective in the treatment of cachexia caused by a host of underlying etiologies. An important issue for consideration as ghrelin agonists are tested is whether the stimulation of growth hormone by ghrelin will prove problematic to patients with tumors. Also, there has been some suggestion of uncomfortable gastrointestinal side effects with ghrelin administration to humans which will have to looked at carefully as these studies proceed.[84,97] Finally, long-term studies will be necessary to see whether the short-term effects of ghrelin on appetite and weight gain will be sustained with long-term use. A major hope in the field of cachexia is that medications that prove effective in treating the symptoms of cachexia—particularly improving appetite, retention of lean and fat mass, and improved quality of life—will also improve the treatment and survival

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Cachexia: Disruption in Appetite Regulation in Need of a Successful Intervention 147 of the underlying disease. This consideration will be important in the analysis of any new compounds proposed as new treatments for cachexia.

CONCLUSION In conclusion, cachexia is a devastating syndrome of body wasting that worsens quality of life and survival for patients suffering from already dire and restrictive diseases such as cancer, chronic kidney disease and chronic heart failure. The common features of cachexia in these disease states and the common feature of systemic inflammation suggest shared pathophysiologic roots. However, previous attempts to treat cachexia via anti-inflammatory interventions have not proven effective, and no unifying treatment has emerged that is effective in treating cachexia in multiple disease states. Basic science investigations have revealed that inflammation-induced activation of the central melanocortin system is one likely means of producing anorexia and lean body wasting in this syndrome. Similarly, basic science approaches to blocking melanocortin activity appeared promising by demonstrating improvement of food intake and weight retention in cachexia, though unfortunately data regarding human treatment is still lacking. Finally, a new treatment approach via administration of ghrelin or ghrelin agonists appears to be a promising means of treatment, as suggested by both basic science and early human experiments, though much more investigation is needed. The hope of all investigators and clinicians in the field is that successful treatment of the symptoms of cachexia will lead to an improvement in quality of life and survival among all patients suffering from this disease.

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Mark D. DeBoer Bosaeus I, Daneryd P, Lundholm K. Dietary intake, resting energy expenditure, weight loss and survival in cancer patients. J Nutr. Nov 2002;132(11 Suppl):3465S-3466S. Falconer JS, Fearon KC, Plester CE, Ross JA, Carter DC. Cytokines, the acute-phase response, and resting energy expenditure in cachectic patients with pancreatic cancer. Ann Surg. Apr 1994;219(4):325-331. Richey LM, George JR, Couch ME, et al. Defining cancer cachexia in head and neck squamous cell carcinoma. Clin Cancer Res. Nov 15 2007;13(22 Pt 1):6561-6567. Fearon KC. Cancer cachexia: developing multimodal therapy for a multidimensional problem. Eur J Cancer. May 2008;44(8):1124-1132. Todorov P, Cariuk P, McDevitt T, Coles B, Fearon K, Tisdale M. Characterization of a cancer cachectic factor. Nature. Feb 22 1996;379(6567):739-742. Hirai K, Hussey HJ, Barber MD, Price SA, Tisdale MJ. Biological evaluation of a lipidmobilizing factor isolated from the urine of cancer patients. Cancer Res. Jun 1 1998;58(11):2359-2365. Wigmore SJ RJ, Fearon KCH et al. IL-8 and IL-6 are produced constitutively by human pancreatic cancer cell lines. Gut. 1994;35(Suppl 5):539. Deans C, Wigmore SJ. Systemic inflammation, cachexia and prognosis in patients with cancer. Curr Opin Clin Nutr Metab Care. May 2005;8(3):265-269. Falconer JS, Fearon KC, Ross JA, et al. Acute-phase protein response and survival duration of patients with pancreatic cancer. Cancer. Apr 15 1995;75(8):2077-2082. Lundholm K, Gelin J, Hyltander A, et al. Anti-inflammatory treatment may prolong survival in undernourished patients with metastatic solid tumors. Cancer Res. Nov 1 1994;54(21):5602-5606. Loprinzi CL, Kugler JW, Sloan JA, et al. Randomized comparison of megestrol acetate versus dexamethasone versus fluoxymesterone for the treatment of cancer anorexia/cachexia. J Clin Oncol. Oct 1999;17(10):3299-3306. Wigmore SJ, Fearon KC, Maingay JP, Ross JA. Down-regulation of the acute-phase response in patients with pancreatic cancer cachexia receiving oral eicosapentaenoic acid is mediated via suppression of interleukin-6. Clin Sci (Lond). Feb 1997;92(2):215221. Smith HJ, Lorite MJ, Tisdale MJ. Effect of a cancer cachectic factor on protein synthesis/degradation in murine C2C12 myoblasts: modulation by eicosapentaenoic acid. Cancer Res. Nov 1 1999;59(21):5507-5513. Barber MD, Ross JA, Voss AC, Tisdale MJ, Fearon KC. The effect of an oral nutritional supplement enriched with fish oil on weight-loss in patients with pancreatic cancer. Br J Cancer. Sep 1999;81(1):80-86. Fearon KC, Barber MD, Moses AG, et al. Double-blind, placebo-controlled, randomized study of eicosapentaenoic acid diester in patients with cancer cachexia. J Clin Oncol. Jul 20 2006;24(21):3401-3407. Fearon KC, Von Meyenfeldt MF, Moses AG, et al. Effect of a protein and energy dense N-3 fatty acid enriched oral supplement on loss of weight and lean tissue in cancer cachexia: a randomised double blind trial. Gut. Oct 2003;52(10):1479-1486. Berenstein EG, Ortiz Z. Megestrol acetate for the treatment of anorexia-cachexia syndrome. Cochrane Database Syst Rev. 2005(2):CD004310.

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Cachexia: Disruption in Appetite Regulation in Need of a Successful Intervention 149 [26] Loprinzi CL, Schaid DJ, Dose AM, Burnham NL, Jensen MD. Body-composition changes in patients who gain weight while receiving megestrol acetate. J Clin Oncol. Jan 1993;11(1):152-154. [27] Simons JP, Schols AM, Hoefnagels JM, Westerterp KR, ten Velde GP, Wouters EF. Effects of medroxyprogesterone acetate on food intake, body composition, and resting energy expenditure in patients with advanced, nonhormone-sensitive cancer: a randomized, placebo-controlled trial. Cancer. Feb 1 1998;82(3):553-560. [28] Strang P. The effect of megestrol acetate on anorexia, weight loss and cachexia in cancer and AIDS patients (review). Anticancer Res. Jan-Feb 1997;17(1B):657-662. [29] Kardinal CG, Loprinzi CL, Schaid DJ, et al. A controlled trial of cyproheptadine in cancer patients with anorexia and/or cachexia. Cancer. Jun 15 1990;65(12):2657-2662. [30] Jatoi A, Windschitl HE, Loprinzi CL, et al. Dronabinol versus megestrol acetate versus combination therapy for cancer-associated anorexia: a North Central Cancer Treatment Group study. J Clin Oncol. Jan 15 2002;20(2):567-573. [31] Qureshi AR, Alvestrand A, Danielsson A, et al. Factors predicting malnutrition in hemodialysis patients: a cross-sectional study. Kidney Int. Mar 1998;53(3):773-782. [32] Mak RH, Cheung W, Cone RD, Marks DL. Orexigenic and anorexigenic mechanisms in the control of nutrition in chronic kidney disease. Pediatr Nephrol. Mar 2005;20(3):427-431. [33] Mitch WE. Robert H Herman Memorial Award in Clinical Nutrition Lecture, 1997. Mechanisms causing loss of lean body mass in kidney disease. Am J Clin Nutr. Mar 1998;67(3):359-366. [34] Bergstrom J. Why are dialysis patients malnourished? Am J Kidney Dis. Jul 1995;26(1):229-241. [35] Wang AY, Sea MM, Tang N, et al. Resting energy expenditure and subsequent mortality risk in peritoneal dialysis patients. J Am Soc Nephrol. Dec 2004;15(12):31343143. [36] Heimburger O, Lonnqvist F, Danielsson A, Nordenstrom J, Stenvinkel P. Serum immunoreactive leptin concentration and its relation to the body fat content in chronic renal failure. J Am Soc Nephrol. Sep 1997;8(9):1423-1430. [37] Kaysen GA, Rathore V, Shearer GC, Depner TA. Mechanisms of hypoalbuminemia in hemodialysis patients. Kidney Int. Aug 1995;48(2):510-516. [38] Qureshi AR, Alvestrand A, Divino-Filho JC, et al. Inflammation, malnutrition, and cardiac disease as predictors of mortality in hemodialysis patients. J Am Soc Nephrol. Jan 2002;13 Suppl 1:S28-36. [39] Fiedler R, Mall M, Wand C, Osten B. Short-term administration of omega-3 fatty acids in hemodialysis patients with balanced lipid metabolism. J Ren Nutr. Apr 2005;15(2):253-256. [40] Johannsson G, Bengtsson BA, Ahlmen J. Double-blind, placebo-controlled study of growth hormone treatment in elderly patients undergoing chronic hemodialysis: anabolic effect and functional improvement. Am J Kidney Dis. Apr 1999;33(4):709717. [41] Hansen TB, Gram J, Jensen PB, et al. Influence of growth hormone on whole body and regional soft tissue composition in adult patients on hemodialysis. A double-blind, randomized, placebo-controlled study. Clin Nephrol. Feb 2000;53(2):99-107.

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Cachexia: Disruption in Appetite Regulation in Need of a Successful Intervention 151 [59] Anker SD, Negassa A, Coats AJ, et al. Prognostic importance of weight loss in chronic heart failure and the effect of treatment with angiotensin-converting-enzyme inhibitors: an observational study. Lancet. Mar 29 2003;361(9363):1077-1083. [60] Brink M, Wellen J, Delafontaine P. Angiotensin II causes weight loss and decreases circulating insulin-like growth factor I in rats through a pressor-independent mechanism. J Clin Invest. Jun 1 1996;97(11):2509-2516. [61] Torre-Amione G, Sestier F, Radovancevic B, Young J. Broad modulation of tissue responses (immune activation) by celacade may favorably influence pathologic processes associated with heart failure progression. Am J Cardiol. Jun 6 2005;95(11A):30C-37C; discussion 38C-40C. [62] Cone RD. Anatomy and regulation of the central melanocortin system. Nat Neurosci. May 2005;8(5):571-578. [63] Ollmann MM, Wilson BD, Yang YK, et al. Antagonism of central melanocortin receptors in vitro and in vivo by agouti-related protein. Science. 1997;278(5335):135138. [64] DeBoer MD, Marks DL. Cachexia: lessons from melanocortin antagonism. Trends Endocrinol Metab. Jul 2006;17(5):199-204. [65] Farooqi IS, Keogh JM, Yeo GS, Lank EJ, Cheetham T, O'Rahilly S. Clinical spectrum of obesity and mutations in the melanocortin 4 receptor gene. N Engl J Med. Mar 20 2003;348(12):1085-1095. [66] DeBoer MD, Marks DL. Therapy insight: Use of melanocortin antagonists in the treatment of cachexia in chronic disease. Nat Clin Pract Endocrinol Metab. Aug 2006;2(8):459-466. [67] Marks DL, Ling N, Cone RD. Role of the Central Melanocortin System in Cachexia. Cancer Res. 2001;61(4):1432-1438. [68] Scarlett JM, Jobst EE, Enriori PJ, et al. Regulation of Central Melanocortin Signaling by Interleukin-1{beta}. Endocrinology. Sep 2007;148(9):4217-4225. [69] DeBoer MD, Zhu XX, Levasseur P, et al. Ghrelin treatment causes increased food intake and retention of lean body mass in a rat model of cancer cachexia. Endocrinology. Jun 2007;148(6):3004-3012. [70] Marks DL, Cone RD. Central melanocortins and the regulation of weight during acute and chronic disease. Recent Prog Horm Res. 2001;56:359-375. [71] Chen C, Tucci FC, Jiang W, et al. Pharmacological and pharmacokinetic characterization of 2-piperazine-alpha-isopropyl benzylamine derivatives as melanocortin-4 receptor antagonists. Bioorg Med Chem. May 15 2008;16(10):56065618. [72] Cheung W, Yu PX, Little BM, Cone RD, Marks DL, Mak RH. Role of leptin and melanocortin signaling in uremia-associated cachexia. J Clin Invest. Jun 2005;115(6):1659-1665. [73] Cheung WW, Kuo HJ, Markison S, et al. Peripheral administration of the melanocortin4 receptor antagonist NBI-12i ameliorates uremia-associated cachexia in mice. J Am Soc Nephrol. Sep 2007;18(9):2517-2524. [74] Cheung WW, Rosengren S, Boyle DL, Mak RH. Modulation of melanocortin signaling ameliorates uremic cachexia. Kidney Int. Jul 2008;74(2):180-186.

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[75] Joppa MA, Gogas KR, Foster AC, Markison S. Central infusion of the melanocortin receptor antagonist agouti-related peptide (AgRP(83-132)) prevents cachexia-related symptoms induced by radiation and colon-26 tumors in mice. Peptides. Jan 2 2007. [76] Markison S, Foster AC, Chen C, et al. The regulation of feeding and metabolic rate and the prevention of murine cancer cachexia with a small-molecule melanocortin-4 receptor antagonist. Endocrinology. Jun 2005;146(6):2766-2773. [77] Marks DL, Butler AA, Turner R, Brookhart GB, Cone RD. Differential role of melanocortin receptor subtypes in cachexia. Endocrinology. 2003;144(4):1513-1523. [78] Nicholson JR, Kohler G, Schaerer F, Senn C, Weyermann P, Hofbauer KG. Peripheral administration of a melanocortin 4-receptor inverse agonist prevents loss of lean body mass in tumor-bearing mice. J Pharmacol Exp Ther. May 2006;317(2):771-777. [79] Vos TJ, Caracoti A, Che JL, et al. Identification of 2-[2-[2-(5-bromo-2methoxyphenyl)-ethyl]-3-fluorophenyl]-4,5-dihydro-1H-imidazole (ML00253764), a small molecule melanocortin 4 receptor antagonist that effectively reduces tumorinduced weight loss in a mouse model. J Med Chem. Mar 25 2004;47(7):1602-1604. [80] Wisse BE, Frayo RS, Schwartz MW, Cummings DE. Reversal of cancer anorexia by blockade of central melanocortin receptors in rats. Endocrinology. 2001;142(8):32923301. [81] DeBoer MD. Melanocortin interventions in cachexia: how soon from bench to bedside? Curr Opin Clin Nutr Metab Care. Jul 2007;10(4):457-462. [82] Kojima M, Hosoda H, Date Y, Nakazato M, Matsuo H, Kangawa K. Ghrelin is a growth-hormone-releasing acylated peptide from stomach. Nature. Dec 9 1999;402(6762):656-660. [83] Cummings DE, Weigle DS, Frayo RS, et al. Plasma ghrelin levels after diet-induced weight loss or gastric bypass surgery. N Engl J Med. May 23 2002;346(21):1623-1630. [84] DeBoer MD. Emergence of ghrelin as a treatment for cachexia syndromes. Nutrition. Sep 2008;24(9):806-814. [85] Willesen MG, Kristensen P, Romer J. Co-localization of growth hormone secretagogue receptor and NPY mRNA in the arcuate nucleus of the rat. Neuroendocrinology. Nov 1999;70(5):306-316. [86] Chen HY, Trumbauer ME, Chen AS, et al. Orexigenic action of peripheral ghrelin is mediated by neuropeptide Y and agouti-related protein. Endocrinology. Jun 2004;145(6):2607-2612. [87] Granado M, Priego T, Martin AI, Villanua MA, Lopez-Calderon A. Anti-inflammatory effect of the ghrelin agonist growth hormone-releasing peptide-2 (GHRP-2) in arthritic rats. Am J Physiol Endocrinol Metab. Mar 2005;288(3):E486-492. [88] DeBoer MD, Zhu X, Levasseur PR, et al. Ghrelin treatment of chronic kidney disease: improvements in lean body mass and cytokine profile. Endocrinology. Feb 2008;149(2):827-835. [89] Gonzalez-Rey E, Delgado M. Anti-inflammatory neuropeptide receptors: new therapeutic targets for immune disorders? Trends Pharmacol Sci. Sep 2007;28(9):482491. [90] Chorny A, Anderson P, Gonzalez-Rey E, Delgado M. Ghrelin protects against experimental sepsis by inhibiting high-mobility group box 1 release and by killing bacteria. J Immunol. Jun 15 2008;180(12):8369-8377.

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Cachexia: Disruption in Appetite Regulation in Need of a Successful Intervention 153 [91] Kodama T, Ashitani J, Matsumoto N, Kangawa K, Nakazato M. Ghrelin treatment suppresses neutrophil-dominant inflammation in airways of patients with chronic respiratory infection. Pulm Pharmacol Ther. 2008;21(5):774-779. [92] Hanada T, Toshinai K, Kajimura N, et al. Anti-cachectic effect of ghrelin in nude mice bearing human melanoma cells. Biochem Biophys Res Commun. Feb 7 2003;301(2):275-279. [93] Nagaya N, Uematsu M, Kojima M, et al. Chronic administration of ghrelin improves left ventricular dysfunction and attenuates development of cardiac cachexia in rats with heart failure. Circulation. Sep 18 2001;104(12):1430-1435. [94] Wang W, Andersson M, Iresjo BM, Lonnroth C, Lundholm K. Effects of ghrelin on anorexia in tumor-bearing mice with eicosanoid-related cachexia. Int J Oncol. Jun 2006;28(6):1393-1400. [95] Xu XB, Pang JJ, Cao JM, et al. GH-releasing peptides improve cardiac dysfunction and cachexia and suppress stress-related hormones and cardiomyocyte apoptosis in rats with heart failure. Am J Physiol Heart Circ Physiol. Oct 2005;289(4):H1643-1651. [96] Neary NM, Small CJ, Wren AM, et al. Ghrelin increases energy intake in cancer patients with impaired appetite: acute, randomized, placebo-controlled trial. J Clin Endocrinol Metab. Jun 2004;89(6):2832-2836. [97] Strasser F, Lutz TA, Maeder MT, et al. Safety, tolerability and pharmacokinetics of intravenous ghrelin for cancer-related anorexia/cachexia: a randomised, placebocontrolled, double-blind, double-crossover study. Br J Cancer. Jan 29 2008;98(2):300308. [98] Nagaya N, Itoh T, Murakami S, et al. Treatment of cachexia with ghrelin in patients with COPD. Chest. Sep 2005;128(3):1187-1193. [99] Nagaya N, Moriya J, Yasumura Y, et al. Effects of ghrelin administration on left ventricular function, exercise capacity, and muscle wasting in patients with chronic heart failure. Circulation. Dec 14 2004;110(24):3674-3679. [100] Akamizu T, Takaya K, Irako T, et al. Pharmacokinetics, safety, and endocrine and appetite effects of ghrelin administration in young healthy subjects. Eur J Endocrinol. Apr 2004;150(4):447-455. [101] Garcia JM BR, Graham, C, Kumor K, Polvino W. A Phase II, randomized, placebocontrolled, double blind study of the efficacy and safety of RC-1291 for the treatment of cancer-cachexia. Abstract 2007 American Society of Clinical Oncology (ASCO) Meeting, Chicago, IL. Journal of Clinical Oncology. 2007;Supp. Vol 25 (No18S).

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In: Appetite and Nutritional Assessment Editors: S. J. Ellsworth, R. C. Schuster

ISBN: 978-1-60741-085-0 © 2009 Nova Science Publishers, Inc.

Chapter 5

CLINICAL HOLISTIC MEDICINE: A SEXOLOGICAL APPROACH TO EATING DISORDERS Søren Ventegodt*1,2,3,4,5, Katja Braga2,3, Isack Kandel6,7 and Joav Merrick*5,7,8,9 1

The Quality of Life Research Center, Copenhagen, Denmark Research Clinic for Holistic Medicine, Copenhagen, Denmark 3 Nordic School of Holistic Medicine, Copenhagen, Denmark 4 Scandinavian Foundation for Holistic Medicine, Sandvika, Norway 5 Interuniversity College, Graz, Austria 6 Faculty of Social Sciences, Department of Behavioral Sciences, Ariel University Center of Samaria, Ariel, Israel 7 National Institute of Child Health and Human Development, Jerusalem, Israel 8 Office of the Medical Director, Division for Mental Retardation, Ministry of Social Affairs, Jerusalem, Israel 9 Kentucky Children‘s Hospital, University of Kentucky, Lexington, United States

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2

ABSTRACT Virtually all teenage girls and young women have to some extent an eating disorder, which research has shown to covariate with the intensity of psychosexual developmental disturbances and sexual problems. We suggest simple psychosexual (psychodynamic) explanations for the most common eating disorders like anorexia nervosa, bulimia nervosa, and binge eating disorder and propose the hypothesis that eating disorders can be easily understood as symptoms of the underlying psychosexual developmental disturbances. We relate the symptoms of the eating disorders to three major strategies for *

Søren Ventegodt, MD, MMedSci, MSc, Director, Quality of Life Research Center, Classensgade 11C, 1 sal, DK2100 Copenhagen O, Denmark. Tel: +45-33-141113; Fax: +45-33-141123; E-mail: [email protected]; Website: http://www.livskvalitet.org * Professor Joav Merrick, MD, MMedSci, DMSc, Medical Director, Division for Mental Retardation, Ministry of Social Affairs, POBox 1260, IL-91012 Jerusalem, ISRAEL. Tel: 972-2-6708122; Fax: 972-2-6703657; Mobile: 972-50-6223832; E-mail: [email protected]; Website: www.nichd-israel.com; homepage: http://jmerrick50.googlepages.com/home

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Søren Ventegodt, Katja Braga, Isack Kandel et al. repressing sexuality: 1) The dispersion of the flow of sexual energy - from the a) orgasmic potent, genitally mature (―vaginal‖) state via the b) more immature, masturbatory (―clitoral‖) state, and further into the c) state of infantile autoerotism (―asexual state‖). 2) The dislocation from the genitals to the bodies other organs, especially the digestive and urinary tract organs (the kidney-bladder-urethra) giving the situation where sexual energy is accumulated and subsequently released though the substituting organs. 3) The repression of a) free, natural and joyful sexuality into first b) sadism, and then further into c) masochism. We conclude that the eating disorders easily can be understood as sexual energies living their own life in the non-genital body organs, and we present results from the Research Clinic for Holistic Medicine, Copenhagen, where eating disorders have been treated with accelerated psychosexual development. We included the patients with eating disorders into the protocol for sexual disturbances and found half these patients to be cured in one year and with 20 sessions of clinical holistic therapy.

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INTRODUCTION Virtually every teenage girl on the western hemisphere – and most women between 12 and 35 years– has an eating disorder to some extends. Working as physicians in general practice we have observed not only a high prevalence of severe eating disorders like anorexia (the general loss of appetite or disinterest in food), anorexia nervosa (the intended weight loss by starvation, over-exercise, purging etc.) and bulimia nervosa (the cyclical, recurring pattern of binge eating often followed by guilt, self-recrimination and compensatory behavior such as dieting, over-exercising and purging) (see list of the eating disorders listed in ICD-10 in table 1 [1]), but also a number of milder disorders that less often are put into diagnoses followed by medical treatment, like binge eating disorder (uncontrolled bursts of overeating followed by compulsive vomiting), extreme and obsessive weight control (often by patients with a normal weight) where the bathroom weight are used several times a day, and obsessive, neurotic attitudes to food i.e. a too large importance attributed to avoiding calories, or carbohydrates, or fat, or even the compulsive abandonment of a single foot items like white sugar, white bread etc. Other expressions of this are extreme exercise-programs sometimes even encouraged by the physician, and vanity that converts into a compulsive drive for being as slim as the commercial fashion-models. The girls often present severely disturbed body images in combination with either an antisocial behavioral pattern with withdrawal and social isolation (antisocial or severely disturbed personality), or a strong dependency on the confirmation of their value as a person from peers and parents (dependent personality type), or a need for constant appraisal of the bodies‘ sexual value from boys (hypersexual behavior). So the closer we look at the appetite dysregulations, the more they seem deeply connected to psychosexual factors. Therapists who work with young female patients with eating disorders often notice that there seem to be both a mental (psychoform) and a bodily (somatoform) aspect of the problem. The patient‘s mind often carries a lot of thoughts and ideas about the vital importance of not getting too fat and ugly, combined with feelings of shame and guilt from not being able to control the eating habits, etc. The patient‘s body often seems to live its own

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life. Some times it is compensatory attracted to food, at other times strongly repelled by food, and at other times again not interested in food at all. Often the phases vary in a cyclic, rather predictable way. In anorexia, food is simply not of any interest; in anorexia nervosa there is a battle in the patient not to eat in spite of an urge for eating; in bulimia we have the compensatory overeating, and in bulimia nervosa we have the inner conflict between one part of the patient that want to eat and an other that do not. In binging the striving is for simply filling the stomach and thereafter emptying it totally again, releasing all tension. The emotional character of the eating disorder has made them difficult to treat with behavioral therapy; it has not been able to treat them successfully with drugs either. So most patients suffer from their eating disorder the first 20 years after early puberty; after that is normally tend to burn out – as to the sexual urge. There are many scientific speculations about biological reasons for the eating disorders the same way psychiatrists for a hundred years now have speculated in possible biological reasons for mental illnesses; but neither has till this day showed genetic or any other clear scientific evidence for being ―hardwired‖ in the human nature. It is often said that the eating disorders disturb other aspects of the patient‘s life, including her sexual life, but this is most likely to be the other way round: the eating disorder is a symptom of a deeper psychosexual disturbance. It is worth to speculate that the problems started with puberty and gradually goes down (―burns out‖) during the next 20 years until the 35-year old woman, who statistically have come to know her body and sexuality by getting rid of her eating disorder, or at least of its symptoms. The close association in time and intensity is a strong clue that eating disorders might be causally linked to sexuality. Psychosomatic and psychosexual research has in accordance with this shown sexuality to be closely linked to the eating disorders. Morgan et al [2] found that anorectics were less likely than bulimics to have engaged in masturbation and also scored lower on a measure of sexual esteem, and both groups exhibited less sexual interest and more negative affect during sex than did a normative sample [2]. Abraham et al [3] found that bulimic patients were more likely to experience orgasm with masturbation, were more likely to have experimented with anal intercourse, and were more likely to describe their libido as ―above average‖, while their controls were more likely to experience orgasm during sexual intercourse [3]. Raboch and Faltus [4] found that ―primary or secondary insufficiencies of sexual life were found for 80% of the anorectic patients‖[4], while Raboch [5] found that sexual development of patients with anorexia nervosa was accelerated in the initial stages. Sarol-Kulka et al [6] found in a pilot study that the anorectic patients showed interest in the opposite sex at an earlier age than patients with bulimia; however, the anorectic females, more frequently than bulimic, reported that these interests were never realized. 36% of patients with anorexia and 29% of patients with bulimia had no sexual initiation. When evaluating the negative aspects of their own sexuality, 28% of patients with bulimia and 9% of patients with anorexia reported difficulties in achieving orgasm; 13% of bulimic and 9% of anorectic females reported difficulties in getting aroused, 22% of bulimic and 17% of anorectic females reported fearing the sexual initiation [6]. Handa et al [7] found that 16.3% of patient with eating disorders had been physically abused and Sanci [8] found that childhood sexual abuse happed 2.5 times as often as normal with patients that later developed bulimia; the patients who developed anorexia did not show this association. Although the picture is not at all clear, and even somewhat contradictory,

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research has shown a strong association between sexuality and eating disorders. In science we must agree that our present understanding of sexuality is messy and unclear in itself that this most likely is the reason for the messy conditions of the research; we actually believe that it is the incomplete understanding of sexuality itself in the mind of the researchers that is the major hindrance for shedding light into this. As we aim to improve our present state of understanding we have incorporated into this chapter a number of classical and modern theories of sexuality and psychosexual development. We believe that this synthesis is of clinical value and have, after working 10 years with holistic sexology in the clinic setting [9-25] developed a holistic sexological cure for the eating disorders that we have tested with success on several patients. We therefore want to present our theoretical understanding to make a basis for further research in clinical holistic medicine both in Denmark and in other countries (this chapter is a part of the Open Source Research Protocol for Clinical Holistic Medicine, that includes all the published strategies for helping the patients with clinical holistic medicine (CHM) and the obtained results from the clinical practice, to be found at www.pubmed.gov, search for papers with ―clinical holistic medicine‖ in the title).

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Table 1. The 2007 ICD-10 list of eating disorders and sexual disorders. Notice the similarities (F50.) Eating disorders (F50.0) Anorexia nervosa (F50.1) Atypical anorexia nervosa (F50.2) Bulimia nervosa (F50.3) Atypical bulimia nervosa (F50.4) Overeating associated with other psychological disturbances (F50.5) Vomiting associated with other psychological disturbances (F50.8) Other eating disorders (F50.9) Eating disorder, unspecified (F52.) Sexual dysfunction, not caused by organic disorder or disease (F52.0) Lack or loss of sexual desire (F52.1) Sexual aversion and lack of sexual enjoyment (F52.2) Failure of genital response (F52.3) Orgasmic dysfunction (F52.4) Premature ejaculation (F52.5) Nonorganic vaginismus (F52.6) Nonorganic dyspareunia (F52.7) Excessive sexual drive (F52.8) Other sexual dysfunction, not caused by organic disorder or disease (F52.9) Unspecified sexual dysfunction, not caused by organic disorder or disease

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ORAL SEXUALITY, SEXUAL REPRESSION, AND THE EATING DISORDERS The Freudian concept of oral sexuality is little understood by contemporary physicians and psychiatrists [26], but Freud‘s concept was acknowledged by the whole tradition of psychoanalysts and psychodynamic researchers and therapists from the last century including Jung [27] and Reich [28,29].

Case Story

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Female Patient 36 Years Old The patient tells her story about an eating disorder (bulimia nervosa) starting when she was 16 years, a little before she became sexually active. She had this condition until recently – first when she was 30 years old did she have spontaneous remission from it - in spite of many years of cognitive psychotherapy. She was first treated on an individual basis at the University Hospital Psychiatric Clinic; then she came in a bulimia psychotherapy group for 18 month, when she was 20-21 years old, followed by 6 years in individual psychotherapy with a female experienced psychologist. The focus of the therapy was getting control over the eating habits. She reported that she always had big problems with desire, getting sexually aroused, and getting satisfactory orgasm, and she complains about a life-long history of unsatisfactory sexual relationships. She explained that her binging was motivated primarily of the extremely relaxed and happy feelings she got after filling her stomach completely until it almost bursted, and then immediately after emptying again completely by vomiting. The process itself was not really emotionally rewarding, neither the eating part of it nor the vomiting part, but the total bodily relaxation was what she was really after. Only after she learned how to relax and go with ―the flow in life‖, letting go of controlling everything, did the eating disorder leave her. It seemed that the therapy was unproductive, because it aimed at helping the patient getting control, not at helping the patient to learn to let go of the control.

Freud believed that sexuality during the child‘s psychosexual development traveled from the mouth to the anus (and bladder), until it reached its final destination in the genitals. Reich had a somewhat different understanding, as he believed that the sexually healthy little girl had genital sexuality, and only when she was denied her ―genital rights‖ i.e. by being punished for masturbation, would she repress her sexuality away from the genitals and into the other organs. Freud also had the idea of sexual development from infantile autoerotism into the more mature masturbatory, clitoral sexual competency, before the girl finally reach genital maturity and able to have sexual intercourse. Reich believed that whenever sexuality became repressed is was kept by the body-amour and the muscles of the body. So when sexuality was repressed, it moved into the tensions of the body, and thus out of reach and use for the patient [28]. Today we know in theory three ways for sexuality to become repressed – three neurotic strategies for getting rid of a sexuality that cannot be contained in the patient‘s childhood environment: •

Repression of sexual energy by destroying the sexual ray of energy: from the genital state (orgasmic potency) to ―infantile autoerotism‖ (lack of orgasmic potency).

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•

•

The first is the repression of the sexual energy, from flowing freely through the genitals allowing the person so engage in sexual intercourse, to the more restricted masturbatory state, where the sexual energy still can be used for pleasure raising a sexual circle, but only within the person herself, into the still more futile and useless state of infantile autoerotism, where sexual energy cannot any longer form a beam of energy and flow, but only hang as a cloud of sexual energy (a sexual quality or ―odor‖), just barely allowing the observer to identify the gender of the person. The infantile autoerotism is the typical sexual state of the schizophrenic patient; in psychodynamic theory the lack of sexual interest in the world from this state is one of the suggested reason for autism. Repression of sexual energy by displacement from the genital to other organs – sexualisation of the digestive system. When sexuality cannot be accepted by the girl‘s parents it can still survive by being transformed into emotional charge associated with eating, defecation and urination. The mouth, intestines, anus and bladder can, as observed already by Freud carry enormities of charge of sexual energy. The reader that doubts this might recall Gräfenberg study from 1950 where he quite surprisingly documented the very important role of the urethra in many women‘s sexuality [30]. This means that the sexual energies in many ways can be preserved, but disguised, as sexual emotions connected to non-sexual organs; the joy associated with the later is obviously often much easier to accept for the parents: The little girls is cute when the eats; she is even cute when she goes to the bathroom, but she is definitely naughty and not-socute when she plays with her own genitals. So the displacement of sexual energies turns her, if she is raised in a sex-negative environment, into a socially acceptable person. If we compare the eating disorders with the sexual disorders, it is quite interesting to see how parallel these two lists are (see table 1). Of course this psychodynamic understanding of body and sexuality might seem rather incomprehensible, if you are unwilling to acknowledge sexual energies as the fundamental vital energies in the human being, as did Freud, Jung, Reich, and so many of the other great psychologists and physicians of the last century. But if you can follow this scheme of thinking, then you can also examine your female patient presenting an eating disorder for a deeper layer of psychosexual developmental disturbances, that could be corrected, and by doing so you can help the young woman not only to get rid of her eating disorder, but also of other more existentially important problems related to a poorly developed sexuality. Repression of sexual energy by degeneration into sadism and masochism A third way sexuality could be repressed is as sadism and masochism. The idea that sexual repression leads to masochism, which is perhaps most strongly and clearly expressed by Reich in his book ―Character Analysis‖ [29], is that sexuality basically calls for meeting with the opposite sex, in an active, aggressive way. Sexual aggression is thus the most natural thing with both sexes, although the expression of male and female sexual aggression is very different, the male aggression often looking like sexual violation and harassment, while the female aggression often is looking more like seduction and ―hooking‖. When sexual aggression becomes blocked, i.e. when the girl is told not to be so sexually challenging to the boys in the way she dresses and acts, or when she is sexually neglected of the father and other

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boys and men who she is depending on interacting with for her psychosexual development, her sexuality first turns into evil sexual intent (i.e. sexually torturing the boys by rejecting them or slating or intimidating them); the logic in this is that sexuality still exists, because is breaks through the barrier using force (which is sadism). If sadism is also repressed, the flow of sexual energy is turned inwards, instead of outwards (which is masochism). So masochism is basically sadism turned inwards towards self. If the reader wonders how sadism is created from sexual energy turned evil, we refer to our explanation of evilness in general in the Life Mission Theory [31-39]. This theory explains how and why all intents seem to turn evil, when they cannot be realized by the little child [36].

SEXUAL THEORIES FOR ANOREXIA NERVOSA, BULIMIA NERVOSA AND BINGE EATING DISORDER

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Anorexia Nervosa The basic pattern of anorexia nervosa seems to be the lack of desire and the lack of selfacceptance and acceptance of body and sexuality. The girl often presents severe problems related to her personality; her mind is often not fully developed compared to other girls her age, her sexuality is often less active, unless she uses this as a kind of activity that uses calories i.e. instrumentally and not for the sexual pleasure; spiritually she is often not able to give and receive love, and she often also has a poorly developed self (see [40] for a systematic way to analyze the personality disturbances). So it might be a little simplistic to point to the patients psychosexual development as the fundamental cause of the eating disorders, but according to psychosomatic theory the problems related to the lack of development of her personality is actually also likely to be caused by her more fundamental problems related to her psychosexual development. So we do not find it hard to see how anorexia nervosa relates to repressed sexuality; the patient‘s sexuality is often repressed in several ways: obviously there is often the regression toward the infantile autoerotism; then there is the translocation of sexuality from her genitals to her digestive system (and often also bladder-urethra); and finally there is often a strong component of masochism leading to self-destruction. If the reason for starvation really is masochism, and it often looks so, there is a hidden sexual pleasure in the self-destruction that is stronger than any pain you can inflict on the patient during the most rigorous scheme of behavioral therapy. Actually any scheme that represses the masochistic sexual energy is likely to deprive the female masochistic patient even the last remaining joy and meaning of life. This is likely to be the reason why behaviors coercive therapy, which is still in use in psychiatry, most often is strongly contra-productive.

Bulimia Nervosa Bulimia is in many practical ways the opposite of anorexia, but it still contains from a psychodynamic view many of the same basic elements of repressed sexuality. The shift from

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the genitals to the digestive organs (and often also bladder-urethra) is the same; the repression of vital sexuality and orgasmic potency into the masturbatory, clitoral state is the same, although the bulimic patient often is less repressed than the anorectic; and the masochistic quality of the bulimic behavior is often rather obvious. But in bulimia the fundamental drive is preserved. The patients wants to eat; when the patient tells about the strength of the urge it carries the same feel as the other basic biological urges, making it highly likely to be an expression of a hidden sexual urge. If this is the case, it is clear that it is uncontrollable by the girl or young woman. The power of sexuality is stronger than the power of the mind; it cannot be controlled by direct repression; it can only be handled by intelligent negotiation. So if this is the case, the bulimic patient must learn to acknowledge her compensatory drive for eating as an expression of her sexuality; and her neurotic sexuality must be developed to enable it to shift back and inhabit once again her pelvis, genitals - and become a natural sexuality.

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Binge Eating Disorder This disorder is a less serious disorder that seldom leads to medical attention, as we find it in girls and young women with almost normal psychopathology. In many ways this disorder is the clearest expression of sexuality taken to the digestive system. Instead of filling her vagina she is filling her stomach; and instead of releasing the tension in an orgasm, she releases is through vomiting. Many of these patients seem to have their sexuality repressed to the clitoral level being able to masturbate, but not to have full orgasm during coitus (loss of orgasmic potency). The masochistic component is often lacking, but it can be there also. The simplest way to understand this is the patient masturbating though her digestive system, the same way other women masturbate by filling the vagina and emptying it again; we have noticed the habit of some of these patients to fill their anus and rectum with objects or large amount of water, and releasing this again for sexual pleasure or for reasons of ―purification‖. This is obviously the same sexual dynamics taking directly to the intestines. The same way the urine can be held back and finally released as a masturbatory practice of some of these often sexually innovative patients. The bulimic and the binging patients are often sexually active also; not all their sexual energy is channeled to the digestive organs, making the situation a little more complex. It is like a diverted river, where more of less water is running in a parallel river. The cure is to help the patient lead all the water, all the flow of sexuality, back into the main river. First when the patient own all her sexual energy and is able to use it maturely genitally for satisfying sex with a partner, will her eating disorder – the symptoms of her disturbed sexuality – finally be cured.

SEXOLOGICAL TREATMENT OF EATING THE DISORDERS In treating the eating disorders as sexological disturbances it is important to go directly to the patient‘s sexuality; this means that the therapist and the patient should agree completely that her sexuality and personality as a whole is much more important than her eating disorder. Of course, if the patient is dying from starvation or excessive overweight there might be

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practical problems in using such a strategy; it is important to remember that all problems start as small problems and only if they remain unsolved for a very long time turn into huge, even mortal situations. So this approach is wisely used as soon as the symptoms of the eating disorder appears, not when the girl or young woman has lost so much weight that she is unable to concentrate on anything and close to dying. The aim of the holistic sexological therapy is the development of the patient‘s whole personality through rehabilitation of her sexuality – her genital character – with an often-used expression by Reich [28,29]. Holistic Medicine is nothing but the classical, European medicine going back to Hippocrates; this is the beginning of modern medicine, which we know rather well from uniquely well-preserved sources called the Corpus Hippocraticum [41]. We have in recent years tried to develop holistic medicine into a modern, scientifically based system of clinical medicine, where patients are cured mostly without drugs and surgery. The theory and practice of clinical holistic medicine has been described in a number of books [42-45] and experimental cures for many illnesses and disorders including cancer and schizophrenia have already been presented in a serious of papers [46-75]. The sense of coherence seems to be a core concept in the understanding of holistic healing [76-81]. We are not in this chapter going to repeat all the practical tools and details, but the interested physician is encouraged to start just by talking with the patient about her personal history and present problems and after obtaining the trust of the patient continuing this therapeutic work by using therapeutic touch, i.e. massage of the whole body. The combination of the conversational therapy and the bodywork has been used for millennia to rid the patients of repressed emotions hidden in the body or related to the body and sexuality in the patient‘s mind. The basic idea in the therapy is to work against the patient‘s emotional resistance, to bring all difficult emotions up to the surface of consciousness, but first a variety of emotions will show in the therapy, often sorrow, anxiety, anger, helplessness, hopelessness or despair. After the emotional layer an even more intense layer of emotions connected to the sexual aspects of the body and its energies, including the genitals and pelvic area will appear. The holistic sexological bodywork is normally not including the patient‘s genitals, as many patients can be helped without this degree of intimacy. If the patient is not sufficiently helped there are a number of small and large sexological tools to be used, like acceptance through touch [11] and vaginal physiotherapy [14,15], which are relative small tools and much smaller procedures than the standard pelvic examination, and larger tools like the expanded holistic pelvic examination [13], going all the way up to direct sexual stimulation of the patient in a radical and provocative technique developed 50 years ago by sexologist like Hoch and Reich called the sexological examination [82-92]. The fundamental strategy of therapy is to take the patient back in time, to allow her to confront the emotional and sexual problems of her early life, childhood, and even fetal life if necessary, that she cold not solve at that time. The patient will get well again the reverse order of her getting ill – this is the law of Hering [93]. The patients will heal her whole existence, not only a part – that is the salutogenic principle [94-95]. The patient will come back into the old traumas, when she is exposed, in a symbolic form, for the traumatic events and energies that once created her wounds – that is the famous principle of similarity going all the way back to the ideas op Hippocrates; and finally she will heal when she got the resources needed at the time of the trauma, and is so confident with the therapist that she is able to receive them.

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The eating disorders can easily be understood as sexual energies living their own life in the parallel body organs related to digestions, and we present our experience from the Research Clinic for Holistic Medicine that the eating disorders easily can be treated, if therapist and patient can agree that sexuality, not the eating disorder, is the focus of the therapy. In our project we have observed that virtually all young female patients to some degree have an eating disorder; we understand these as symptoms of psychosexual developmental disturbances and we therefore successfully included the patietns with eating disorders into the protocol for sexual disturbances [9]. We found that about half the patients was cured, not only for their sexual problems, but also systematically from their eating disorders, in one year and with 20 sessions of clinical holistic therapy. In general we found that independently of the type of problem about half the patients were cured, and the more direct the patient‘s sexuality was approached in the therapy, the more efficient it was [9,15,96].

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ETHICAL CONSIDERATIONS Holistic therapy and holistic sexology should be made according to the ethical standard of the International Society for Holistic Health [97] and the laws of the country you reside in. It will be difficult for physicians not familiar with contemporary holistic medicine or the works of Freud, Jung, Reich, Lowen, Rosen and others [26-29,98.99], to understand the full clinical rationality in interpreting the eating disorders as psychosexual disturbances. It will also be difficult for psychiatrists that normally do not touch their patients at all, to understand the therapeutic value of therapeutic touch. And when it comes to using the manual sexological tools, many physicians who are not sexologists, might find these tools too intimate and too directly sexual. In our clinic we have until now used the small manual sexological tools, and only rarely the holistic pelvic exam. Direct sexual stimulation of the female patients seems to be necessary in primary anorgasmia and similar sexual disorders, but we have not, in spite of the indication, found it correct to use these tools in our clinic, but have referred the patients in need of such therapy to the sexologists using these methods. When it comes to teenagers below 18 years old, we have chosen to wait with the manual sexological treatment until they could sign up for these treatments themselves as adults legally responsible for their own treatment. For patients below 18 years we have often used the normal pelvic examination as basis for a conversation about sexuality and related issues, and we have found the pelvic examination to be as therapeutic as it is unpleasant and even experienced as ―very painful‖ by 15% of the teenagers [100]. We know from several studies that patients with a history of sexual abuse very often react very negative emotionally to the pelvic examination [101]; the penetration of the vagina with the speculum and other instruments, or just even the fingers, often gives strong associations to - and memories of the sexual abuse, and according to the principle of similarity this can – and should – be used therapeutically to help the female patient to heal her old wound on body an soul from the sexual abuse [18-20].

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DISCUSSION The observation of the psychoform and somatoform dissociation of the patient will naturally lead to an intent to heal the patient by reconnecting mentally and bodily to the patient. As we are sexual beings, and as a disturbed sexuality has so many symptoms and is followed by so many complications of all kinds, we cannot afford to be a-sexual and to keep all discussion of the patient problems in the a-sexual realm, if we truly want to help the patient. For almost 100 years psychotherapy and psychiatry have disagreed about the importance of sexuality in mental diseases; this disagreement continues when it comes to the eating disorders. We cannot here settle this old discussion today; just inform the interested reader about the theories and the tools for healing also the patient with an eating disorder. When you have worked for some years in the holistic clinic, as we have now with more than 500 patients, and seen how the dynamics of masochism, sexual repression into autoerotism, and sexual shifts from the genitals to the other organs of the body like the digestive organs (from mouth to anus) and the whole urinary tract (kidney-bladder-urethra) can be easily reversed and often followed by the radical improvement not only of the patient‘s sexuality, but also of quality of life, physical and mental health, and level of social, sexual and working ability, you will also come to believe in the old psychodynamic theories of Freud and his students. We found it often helpful to teach the patients about quality of life theory [102-105] and quality of life philosophy [106-113] The sexological approach in the treatment of physical, mental, and existential problems are not new; the traditional holistic medicine of old Greece did exactly that. We have become quite alienated to simple conversational therapy and bodywork during the last five decades, where biomedicine and drugs have become the answer to every problem of the patient, but with biomedicine we have not be able to help all patients and today every second citizen in modern society is a chronic patient, even in countries like Denmark where biomedicine and health service are absolutely free. So we have to conclude that biomedicine is not going to help all patients and biomedicine is not likely to help teenagers and young women with eating disorders – especially not if the psychodynamic hypothesis presented in this chapter is likely to be true. The most fundamental problem with the sexual approach is that is has proven very difficult to understand the true nature of sexual energy in scientific terms, and that the whole field of human development is theoretically extremely farfetched [114-126]. To simplify everything it is important to recall that the essence of relating is being able to say I-Thou. In therapy the courage to love your patient is what in the end will heal you patient and release the patient from disease/pathology [127].

CONCLUSIONS Virtually all teenage girls and young woman have an eating disorder to some degree. We have suggested simple sexual explanations for the most common eating disorders like anorexia nervosa, bulimia nervosa and binge eating disorder. We have suggested that these disorders could easily be understood as symptoms of psychosexual developmental disturbances. We have analyzed the symptoms in relation to three major ways that patients

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use to repress their sexuality as children: 1) The dispersion of sexual energy from the genitally mature to the immature masturbatory (clitoral) state, and further into the state of infantile autoerotism, 2) the dislocation from the genitals to the other organs especially the digestive organs and the bladder-urethra, giving a situation where sexual energy is accumulated and released though substituting organs and 3) the repression of free, natural and joyful sexuality into first sadism, and then further into masochism. The eating disorders can easily be understood as sexual energies living their own life in the parallel body organs related to digestions and we present our experience from the Research Clinic for Holistic Medicine that the eating disorders can be treated, if therapist and patient can agree that sexuality, not the eating disorder, is the focus of the therapy. In our project we have included patients with eating disorders into the protocol for sexual disturbances, and we have found about half the patients to be cured in one year and with 20 sessions of clinical holistic therapy, independent of the problem the patient initially presented with [9,128-132].

ACKNOWLEDGEMENTS

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The Danish Quality of Life Survey and the Quality of Life Research Center was 19912005 supported by grants from the 1991 Pharmacy Foundation, the Goodwill-fonden, the JLFoundation, E. Danielsen and Wife's Foundation, Emmerick Meyer's Trust, the FrimodtHeineken Foundation, the Hede Nielsen Family Foundation, Petrus Andersens Fond, Wholesaler C.P. Frederiksens Study Trust, Else & Mogens Wedell-Wedellsborg's Foundation and IMK Almene Fond. The research was approved by the Copenhagen Scientific Ethical Committee under number (KF)V.100.2123/91 and further correspondence.

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[125] Ventegodt S, Hermansen TD, Kandel I, Merrick J. Human development XII: a theory for the structure and function of the human brain. Scientific World Journal. 2008;8:62142. [126] Ventegodt S, Hermansen TD, Kandel I, Merrick J. Human development XIII: the connection between the structure of the overtone system and the tone language of music. Some implications for our understanding of the human brain. Scientific World Journal. 2008;8:643-57. [127] Buber M. I and thou. New York: Charles Scribner, 1970. [128] Ventegodt S, Thegler S, Andreasen T, Struve F, Enevoldsen L, Bassaine L, Torp M, Merrick J. Self-reported low self-esteem. Intervention and follow-up in a clinical setting. Scientific World Journal. 2007;7:299-305. [129] Ventegodt S, Thegler S, Andreasen T, Struve F, Enevoldsen L, Bassaine L, Torp M, Merrick J. Clinical holistic medicine (mindful, short-term psychodynamic psychotherapy complemented with bodywork) in the treatment of experienced mental illness. Scientific World Journal. 2007;7:306-9. [130] Ventegodt S, Thegler S, Andreasen T, Struve F, Enevoldsen L, Bassaine L, Torp M, Merrick J. Clinical holistic medicine (mindful, short-term psychodynamic psychotherapy complemented with bodywork) in the treatment of experienced physical illness and chronic pain. Scientific World Journal. 2007;7:310-16. [131] Ventegodt S, Thegler S, Andreasen T, Struve F, Enevoldsen L, Bassaine L, Torp M, Merrick J. Clinical holistic medicine (mindful, short-term psychodynamic psychotherapy complemented with bodywork) improves quality of life, health and ability by induction of Antonovsky-Salutogenesis. Scientific World Journal. 2007;7:317-23. [132] Ventegodt S, Kandel I, Merrick J. A short history of clinical holistic medicine. Scientific World Journal. 2007;7:1622-30.

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In: Appetite and Nutritional Assessment Editors: S. J. Ellsworth, R. C. Schuster

ISBN: 978-1-60741-085-0 © 2009 Nova Science Publishers, Inc.

Chapter 6

MAKING SENSE OF WHAT IS HEALTHY FOR YOU: CHILDREN’S AND ADULTS’ EVALUATIVE CATEGORIES OF FOOD Simone P. Nguyen* and Mary Beth McCullough University of North Carolina Wilmington

ABSTRACT

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The domain of food is highly relevant to our everyday lives and thinking, particularly its evaluative components (Birch, Fisher, & Grimm-Thomas, 1999). Evaluative categorization within the domain of food involves the grouping together of foods that share the same value laden assessment (Nguyen, 2008, 2007; Nguyen & Murphy, 2003; Ross & Murphy, 1999). This chapter focuses on the evaluative categories of healthy and unhealthy foods. Healthy foods are defined as foods that give your body what it needs to help you grow, give you long lasting energy, and keep you from getting sick whereas unhealthy foods are defined as foods that do not give your body what it needs to help you grow, give you long lasting energy, and keep you from getting sick (American Heart Association, 2006; National Institute of Health, 2005; National Institute of Child Health and Development, 2005). In this chapter, we will review research in our cognitive development laboratory (e.g., Nguyen, 2008, 2007; Nguyen & Murphy, 2003) that examines evaluative categorization of foods in children and adults. In this chapter, we will also discuss new advances in our lab that begin to reveal on what basis children and adults form their evaluative categories of food. We will discuss studies in which participants were asked to evaluatively categorize unidentified foods as healthy or unhealthy through the use of their senses. The results suggest the information that children and adults gather from their own experiences/observation with the physical properties of foods helps them to determine the evaluative status of foods. Examining how children develop their evaluative categories of food is a critical issue given the

*

Correspondence regarding this chapter should be addressed to Simone P. Nguyen, Department of Psychology, 601 South College Road, Wilmington, NC 28403-5612; email: [email protected].

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Simone P. Nguyen and Mary Beth McCullough astounding increase in overweight and obese children in the United States (The Center for Disease Control, 2006; The American Heart Association, 2006).

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INTRODUCTION The domain of food is highly relevant to our everyday lives and thinking (Birch, Fisher, & Grimm-Thomas, 1999). For example, the typical child in the United States typically eats 3 meals a day, plus snacks, often hears the ―dos and don‘ts‖ of eating from parents and educators and is exposed to hundreds of television advertisements a week claiming how certain far from healthy foods are good for you, constituting a ―well balanced diet‖ (Birch et al., 1999). How do we cognitively process and make sense of the information that we are constantly experiencing and receiving about food, especially about its evaluative components such as its nutritional value? An important way in which we mentally represent and organize things in the world, including food is through categorization, the grouping together of things that share some kind of similarity. In particular, evaluative categorization, the focus of this chapter, is the grouping together of foods that share the same value laden assessment such as healthy and unhealthy foods (Nguyen, 2008, 2007; Nguyen & Murphy, 2003; Ross & Murphy, 1999) or delicious and disgusting foods (see Rozin, 1990; Rozin, Hammer, Oster, & Horowitz, 1986). Evaluative categorization carries a considerable amount of practical value in that it not only helps us to mentally represent and organize foods, but it can also help guide our decisions about our eating practices and behaviors. Membership in an evaluative category is determined by the value laden assessment that we make about a food. To make an assessment, we might examine the food, make content discriminations, relate the food to prior knowledge and experiences, etc. By engaging in this evaluative process, we are going beyond simply identifying the food as it is. For example, the evaluative category of healthy foods might include skim milk, carrots, and fish. Although these foods are less similar to one another than what would be expected in a taxonomic category that is defined by a set of common properties (e.g., dairy products, vegetables, and meats), these foods all belong to the same evaluative category because they are evaluated as healthy. Skim milk might have the properties of being high in calcium and low in fat, for instance, but evaluative categorization has not occurred until an individual has taken the extra step to make a value laden assessment about these properties. The aim of this chapter is to review research in our cognitive development laboratory that examines evaluative categorization of foods in children and adults. In this chapter, we will also discuss new advances in our lab that begin to reveal on what basis children and adults form their evaluative categories of food. We will discuss studies in which participants were asked to use their senses to evaluatively categorize an unidentified food. Much of our lab‘s work on evaluative categorization has focused on healthy and unhealthy foods. Healthy foods are defined as foods that give your body what it needs to help you grow, give you long lasting energy, and keep you from getting sick whereas unhealthy foods are defined as foods that do not give your body what it needs to help you grow, give you long lasting energy, and keep you from getting sick (American Heart Association, 2006; National Institute of Health, 2005; National Institute of Child Health and Development, 2005). These particular evaluative categories have been the primary focus of our investigation because of their salience and

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pertinence, especially given the serious public health concern regarding the prevalence of overweight and obese children and adults in the United States (American Heart Association, 2006; The Center for Disease Control, 2006). Our lab‘s research on evaluative categories has focused on answering two broad questions: 1) do people form evaluative categories?; 2) how do people use these categories? Our approach to examining evaluative categorization has been to study the development of these categories in children and adults, where adults serve as a developmental endpoint to compare children against. In our studies, we typically use standard categorization tasks to examine the ability to form the evaluative categories of healthy and unhealthy foods (e.g., Nguyen & Murphy, 2003, Experiment 1; Nguyen, 2007; Nguyen, 2008, Experiment 1). Categorization is rarely an end in itself, however. Rather, different categories are often learned in the service of broadening the scope of one‘s knowledge by making inferences or generalizations about unfamiliar items. Thus, in our studies we also typically use standard induction tasks to examine the ability to use the evaluative categories of healthy and unhealthy foods for inductive inferences (e.g., Nguyen & Murphy, 2003, Experiment 4; Nguyen, 2008, Experiment 2). In the following sections, we discuss our lab‘s research on evaluative categorization and induction.

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EVALUATIVE CATEGORIZATION WITHIN THE DOMAIN OF FOOD As a starting point, we (Nguyen & Murphy, 2003) first explored evaluative categorization as a part of a larger project on conceptual development within the domain of food. For the purposes of this chapter, we will only describe aspects of this project that are directly relevant to evaluative categorization. In Nguyen and Murphy (2003, Experiment 1), we examined whether children and adults have the ability to form the evaluative categories of healthy and unhealthy foods. The participants were 16 four-year-olds (M = 4;5), 16 seven-year-olds (M = 7;1), and 16 adults (M = 20;0). In this study, participants were provided with 4 picture triads (see Table 1), each triad included a target (e.g., banana), an evaluative choice (e.g., spinach), and an unrelated choice (e.g., cheetos). Participants were interviewed individually, and for each triad they were asked, ―Which food is the same kind of food as the target?‖ For example, ―This is a banana. Is spinach or cheetos the same kind of food as a banana?‖ The accurate answer in this example is ―spinach,‖ since spinach and banana both belong to the evaluative category of healthy foods. Table 1. Evaluative category triads from Nguyen and Murphy (2003, Experiments 1 and 4) Target

Evaluative Choice

Unrelated Choice

Banana Celery

Spinach Apple

Cheetos Chips

Twinkie Chocolate

Cheetos Chips

Apple Spinach

Healthy

Unhealthy

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The results revealed age-related improvements in the ability to accurately categorize foods as healthy and unhealthy. Four-year-olds, 7-year-olds, and adults were 61%, 77%, and 91% accurate, respectively. All of the age groups had above chance (50%) level of performance. There were no significant differences in performance between the 7-year-olds and adults; however, there was a significant difference between the 4-year-olds and these two age groups. These results suggest that 4-year-olds have a basic understanding of evaluative categories o f food, but that their understanding continues to improve between the ages of 4 and 7 years. By age 7 years, children have an adult-like understanding of evaluative categories of food. To follow up on these findings and to provide a more in-depth examination of the development of evaluative categorization of foods, we conducted an additional study (Nguyen, 2007) that included 3-year-olds as well as a wider range of food stimuli. The materials in Nguyen (2007) were 70 pictures of food (35 healthy and 35 unhealthy), with labels printed under each of the foods. See Table 2. The participants in Nguyen (2007) were 16 three-year-olds (M = 3;5), 16 four-year-olds (M = 4;6), 16 seven-year-olds (M = 7;2), and 16 adults (M = 19;0). In this study, the researcher presented participants with 70 pictures of food, one at a time, and for each food asked, ―Is (insert name of food) a healthy food or junky food?‘‘ Participants were also asked to provide an explanation for 6 of the 70 food classifications (3 that the participants classified as healthy and 3 that the participants classified as junky).

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Table 2. Food stimuli from Nguyen (2007) Healthy foods apple, bagel, banana, bread, broccoli, carrot, cereal, cheese, chicken, cracker, egg, fish, grapes, green beans, ham, juice, milk, noodles, oatmeal, orange, peanuts, peanut butter, potato, pretzel, raisins, rice, salad, sandwich, soup, spaghetti, spinach, strawberry, turkey, yogurt, water Unhealthy foods brownie, buttery popcorn, cake, candy, caramel corn, cheetos, chicken nuggets, chocolate bar, cinnamon roll, cookie, corn chips, corndog, cupcake, donut, French fries, fudge, gum, hamburger, hot chocolate, hot dog, ice cream, marshmallow, nachos, onion rings, pie, pizza, popsicle, pop tart, potato chips, sausage, shake, snack bar, soda pop, sundae, twinkie

The results indicated age-related improvements in the ability to accurately classify healthy and unhealthy foods: 3-year-olds (M = 59%), 4-year-olds (M = 73%), 7-year-olds (M = 78%), and adults (M = 94%). The adults were significantly more accurate than the 3-, 4-, and 7-year-olds. Both 7- and 4-year-olds were significantly more accurate than the 3-yearolds; there was not a significant difference between these two older age groups. All of the age groups had above chance (50%) level performance. Participants‘ performance on each food item was also looked at separately in order to see if the results were due to particular foods. There were many foods that appeared difficult for children of all age groups, including unhealthy vegetable derivatives (potato chips, French fries), meat products (corndogs), grains (donut), and beverages (soda pop). All of the adults and nearly all of the 7-year-olds (94%) provided justifications. Half of the 4-year-olds and none of the 3-year-olds provided justifications. The majority of justifications provided by the adults, 7- and 4-year-olds were related to health/illness (e.g., ―You get sick.‖).

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Overall, the results of Nguyen (2007) provide evidence for the emerging ability for evaluative categorization of foods in 3-year-olds. Even by age 3 years, children are able to evalulatively categorize foods as healthy/unhealthy, and this ability improves markedly between the ages of 4- and 7 years and the adult years. These results and those of Nguyen (2003, Experiment 1) were further replicated and extended by Nguyen (2008, Experiment 1). Although Nguyen (2007) included 70 foods and Nguyen and Murphy (2003, Experiment 1) included 4 picture triads, these stimuli did not provide equal representation of different foods groups. In Nguyen (2008, Experiment 1), the stimuli included an equal number of foods that could be considered as belonging to different food groups to ensure that children were being tested on a variety of foods (as opposed to just certain foods like fruits or snacks). The materials included 24 target foods: 12 (6 healthy/6 unhealthy) taxonomic foods that shared common properties (e.g., fruit, vegetables, meat, dairy, beverages, grains) and 12 (6 healthy/6 unhealthy) script foods that shared the same role in an event or routine (e.g., breakfast, lunch, dinner, snack, dessert, birthday). See Table 3. For example, for the taxonomic category of fruit, the healthy food was a banana and the unhealthy food was apple pie. For the script category of breakfast foods, the healthy food was milk and the unhealthy food was a pop tart.

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Table 3. Stimuli for Nguyen (2008, Experiment 1)

Taxonomic Fruit Vegetables Meat Dairy Beverages Grains Script Breakfast Lunch Dinner Snack Dessert Birthday

Healthy

Unhealthy

banana carrot chicken cheese water bread

apple pie French fries sausage ice cream soda pop donut

milk soup salad raisin strawberry juice

pop tart hot dog hamburger potato chips cookies cake

The participants in Nguyen (2008, Experiment 1) were 16 four-year-olds (M = 4;5), 16 seven-year-olds (M = 7;2), and 16 adults (M = 19;5). In this study, children were presented with the food pictures, one at a time, and were asked, ―Is X a healthy or junky food?‖ The results showed age-related improvements in evaluative categorization. Adults (M = 97%) performed significantly better than both 7-year-olds (M = 79%) and 4-year-olds (M = 72%), who also differed significantly from each other. All of the age groups had above chance (50%) level of performance. The different foods groups were also separated out in order to examine whether the results were due to one or more groups. It appeared that children had the most difficulty classifying meats, lunch foods, and dinner foods. Taken together, the results of Nguyen (2008, Experiment 1) show that by age 4 years, children have the ability to evaluatively categorize foods from different taxonomic and script food groups. This ability also improves markedly from the ages of 4- and 7 years, and up until the adult years.

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Thus far, the results of the studies in our lab reveal that children as young as age 3 years have the emerging ability to form the evaluative categories of healthy and unhealthy foods. Beginning at age 4, there is also evidence that children can evaluatively categorize a range of foods from different food groups. By age 4 years, children are also able to provide explanations for these categories, showing that they are developing an understanding of what it means for foods to be healthy or unhealthy. Additionally, there are important age related improvements in children‘s ability to evaluatively categorize foods between the ages of 3and 7 years as well as the adult years. The results also reveal that there are particular foods that children of all ages find especially challenging, perhaps reflecting important differences in children‘s and adults‘ knowledge and experience within the domain of food, including their eating practices and behaviors.

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EVALUATIVE CATEGORIES OF FOOD AND INDUCTION Our lab has also examined whether people use their evaluative categories of food for induction. As mentioned in the Introduction, the process of induction is important because it allows us to broaden the scope of our knowledge by using our category knowledge to make predictions or generalizations about other, unfamiliar members of a category. Previous work by Ross and Murphy (1999) found that adults use taxonomic categories of food for biochemical inferences about the composition of foods because taxonomically-related foods share the same biochemical makeup or ingredients. In contrast, adults use script categories for situational inferences about when foods should be eaten because script-related foods are served during the same situation or time/event. Using this previous work as a starting point, we (Nguyen & Murphy, 2003, Experiment 4) initially examined whether people use evaluative categories for biochemical inferences and/or situational inferences. The participants in Nguyen and Murphy (2003, Experiment 4) were 28 four-year-olds (M = 4.4), 28 seven-year-olds (M = 7.6), and 28 adults (M = 21). Half of the participants within each age group were assigned to the biochemical condition and the other half to the situational condition. In both conditions, participants saw the same picture triads from Nguyen and Murphy (2003, Experiment 1). See Table 1. However, the directions varied by condition. Participants in the biochemical condition heard the researcher say, ―I‘m going to tell you about a place that some people live…the foods that people eat in this faraway place have different ingredients. This game is about ingredients of foods... Some foods have a certain ingredient, but not all foods do…So can you help me figure out which foods have a certain ingredient in them and which foods do not?‖ Following the directions, the participants in the biochemical condition were told that there is a novel ingredient in a target food, and then they were asked which of two foods has the same ingredient as well (e.g., Dax is an ingredient in a banana. Do you think spinach or cheetos probably also has Dax in it too?‘‘). Participants in the situational condition heard a parallel set of directions about a foreign country where people eat different foods on certain holidays. Following the directions, the participants in the situational condition were told that a food is eaten on novel holiday, and then they were asked which of two foods is eaten on the same holiday as well (e.g., ―A banana is eaten on a special holiday called Dax. Do you think spinach or cheetos is probably eaten on Dax too?‖). Presumably, if evaluative categories are used for either type of

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inference, then participants should tend to select the evaluative category choices in the picture triads. The results revealed that adults use evaluative categories more often to make biochemical inferences than situational inferences whereas 7- and 4-year-olds use evaluative categories for both biochemical and situational inferences. These findings suggest that children use evaluative categories for situational inferences more often than adults perhaps because their food experiences at a young age, more so than adults, typically revolve around certain events like snack time and birthday parties. Overall, the findings from Nguyen and Murphy (2003, Experiment 4) are noteworthy given that the majority of research examining inductive inferences has tended to focus on taxonomic categories, and so the role of other categories, including evaluative, in induction has not been well documented (see Krackow & Gordon, 1998). A question that arose from this study was whether evaluative categories could be used for a unique type of inference that is not associated with taxonomic and script categories. To examine this question, we conducted a study (Nguyen, 2008, Experiment 2) looking at the use of evaluative categories for bodily inferences about the human body. The participants in this study included 96 children: 48 four-year-olds (M = 4;6); 48 seven-year-olds (M = 7;3); and 48 adults (M = 20;6). One third of the participants within each age group were assigned to either the bodily inference condition, arbitrary inference condition, or unrelated inference condition. These last two conditions were control conditions to help rule out the explanation that children would have selected the evaluative choices regardless of whether they were making bodily inferences (e.g., perhaps because the evaluative choices are perceived as being more highly associated with the target than the noncategory choices). Children in the bodily inference condition were asked to make inferences about the consequences that eating has on the human body whereas children in one control condition were asked to make arbitrary inferences with nonprojectible properties about materials/substances and children in the second control condition were asked to make unrelated inferences about potentially projectible properties involving interactions with foods. Thus, if children use evaluative categories of food for bodily inferences, but not other inferences, then this would suggest that children are paying attention to the category as well as the content of the property. The participants were tested individually by a researcher, and heard a different set of directions depending upon the condition. For the bodily inference condition, participants heard, ―I‘m going to show you some foods and tell you what they did to people‘s bodies when they ate a lot of them for a long time. Your job is to pick other foods that do the same thing to their bodies.‖ For the arbitrary inference condition, participants heard, ―I‘m going to show you some foods that have some things stuck on them by accident. Your job is to pick other foods that would have the same things stuck on them.‖ For the unrelated inference condition, participants heard, ―I‘m going to show you some foods and tell you about the different things that people use to eat the foods with. Your job is to pick the foods that people eat using the same thing.‖ All of the participants were presented with 12 food triads (6 healthy and 6 unhealthy), one at a time. Each triad consisted of a target food (either a healthy or unhealthy food), an evaluative category match, and a noncategory match. See Table 4. After each food triad was presented, the researcher asked a test question. For example, in the bodily inference condition, a participant may have heard, ―An orange made Jake‘s body daxy. Would yogurt or ice cream also make Jake‘s body daxy too?‖ In the arbitrary inference condition, a

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participant may have heard, ―The orange has dust on it. Would yogurt or ice cream also have dust on it too?‖ Finally, a participant in the unrelated inference condition may have heard, ―Jake uses a daxy to eat her orange. Would she also use a daxy to eat yogurt or ice cream?‖ The rationale for these three different conditions is that if people selectively use evaluative categories for bodily inferences, then they should only select the evaluative category choice in the bodily inference condition, but not in the other two conditions. Table 4. Picture Triads for Nguyen (2008, Experiment 2)

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Targets Healthy foods 1. orange 2. carrot 3. milk 4. egg 5. chicken 6. broccoli Unhealthy foods 1. cheetos 2. sundae 3. candy 4. gum 5. cookie 6. cupcake

Category Choice

Noncategory Choice

yogurt fish apple pasta grape turkey

ice cream chocolate potato chip snack bar brownie cake

ice cream snack bar brownie cake potato chip chocolate

fish turkey grape apple pasta yogurt

The results showed that people do use evaluative categories of food for bodily inferences about the human body. Across the adult and child age groups, evaluative categories were used significantly more often for bodily inferences (M = 83%) than for arbitrary (M = 50%) and unrelated (M = 54%) ones. There was not a significant difference between arbitrary and unrelated inferences. All three age groups were above chance (50%) in making bodily inferences, but not above chance for arbitrary or unrelated inferences. These results suggest that children as young as 4 years, like adults, are able to selectively use the evaluative categories of healthy/unhealthy to make bodily inferences, and not arbitrary and unrelated inferences. Overall, a major contribution from Nguyen and Murphy (2003, Experiment 4) and Nguyen (2008, Experiment 2) is that they are the first to demonstrate the role of evaluative categories of healthy and unhealthy foods in induction, particularly bodily inferences. These results suggest that these evaluative categories are much more than a random set of items, but rather carry considerable content that can be used in making inductive inferences about the human body.

THE ACQUISITION OF EVALUATIVE CATEGORIES Given the findings that people form and use evaluative categories of food, our lab has recently begun to investigate how children learn their evaluative categories. In particular, we are investigating how children‘s own observations or experiences with the physical properties of foods may inform their evaluative category representations. An important way in which

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children observe or experience the physical properties of foods is through their senses, including the sense of taste, smell, sight, touch, and hearing. While there is a large body of research showing that early on in development, children are sensitive to particular tastes (e.g., Beauchamp, Bertino, & Moran, 1982; Birch, 1999, 1979; Blass & Fitzgerald, 1988; Engen & Gasparian, 1974; Harris & Booth, 1987; Harris, Thomas, & Booth, 1990; Nisbett & Gurwitz, 1970; Steiner, 1977), smells of foods (Balogh & Porter, 1986; Engen & Gasparian, 1974; Lawless, 1985; Reisner, Yonas, & Wilkner, 1976; Schmidt & Beauchamp, 1988; Stein, Ottenberg, & Roulet, 1958; Thomas & Murray, 1980), the appearance of foods (e.g., Walsh, Toma, Tuveson, & Sondhi, 2001), texture of foods and the sounds associated with eating foods with certain textures (Bartoshuk,1991; Lundy, Field, Carraway, Hart, Malphurs, Rosenstein, Pelaez-Nogueras, Coletta, Ott, & Hernandez-Reif, 1998; Matheson, Spranger, & Saxe, 2002; Wagstaff, 1993), to our knowledge, there is no research on how information about the physical properties of foods affects children‘s evaluative category representations. In the following section, we report on two exploratory studies that begin to shed light on how children use information about the physical properties of foods to determine their evaluative category membership. In the first study, Krista Williams, an undergraduate student, and I explored how children and adults use information about the physical properties of foods that they gather from their own senses to help determine the evaluative status of foods. In this study, children (N = 12, M = 4;22, range = 4;13 - 4;84) were asked to experience a series of unidentified foods with one of their senses (e.g., touch, smell, sight, hearing) and to use this sensory input to evaluatively categorize the foods. For example, children were asked to close their eyes and smell a food or to listen to the sound recording of a person eating a food. Then, children were asked to evaluatively categorize the food based on this sensory input. The response options were ―healthy,‖ ―unhealthy,‖ or ―I don‘t know.‖ There were 2 test trials per sense (1 healthy food, 1 unhealthy food) along with some filler trials (i.e., foods that were not clearly healthy or unhealthy). The filler trials were included to simply prevent children from keeping track of the 2 test trials per sense pattern (and thus were excluded from the analyses). All of the trials were presented in one of two random orders. It is important to point out that the foods in the test trials were selected based on an independent set of adult stimuli ratings. Twelve adults were asked to rate the healthfulness of a series of unidentified foods by using either their sense of touch, smell, sight, or hearing. (For the sense of hearing, adults heard sound recordings of a person eating foods.) Only foods rated as unambiguously healthy/unhealthy for each sense were used in this study. These ratings also provided confirmation that these sensory cues could offer distinguishing information about the healthfulness of foods. The data from this study were scored by assigning a ―1‖ when children answered correctly. Otherwise, a ―0‖ was assigned when children answered incorrectly or said, ―I don‘t know.‖ To examine performance, a summary variable was created for each sense by combining their respective healthy and unhealthy food trials. Children were equally accurate at using their sense of smell, touch, sight, and hearing in evaluative categorization, p‘s > .05. Children were also significantly above chance (33%) on all four senses, t‘s (11) > 3.8, p‘s < 0.5. (The same pattern of results was also found when the healthy and unhealthy food trials were separated out per sense). See Figure 1.

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Figure 1. Percentage accuracy by sense.

In a second study, Mary Beth McCullough, a graduate student, and I examined the sense of taste with a new set of children (N = 5; M = 4;67, range = 4;56 - 4;96). None of these children had food allergies or restrictions, as reported by their parents. This examination was a part of a larger study looking at evaluative categorization and eating preferences, but only the most relevant aspects of this study will be reported here. Children in this study were asked to taste various unidentified foods (candy, cheetos, pear, and green beans), one at a time, presented in a random order. For each food children were asked, ―Is this food healthy or unhealthy?‖ As in the previous study, these foods were selected based on independent stimuli ratings gathered from adult participants. Eleven adults were asked to taste a variety of foods, and to indicate whether they thought the foods were healthy or unhealthy based on their taste. Only foods that the majority of adults reported as being healthy or unhealthy were selected for use in this study. The results of this study indicated that 80% of the children used their sense of taste to accurately classify the pear and green beans as healthy. Similarly, 80% of the children used their senses to accurately classified the candy and cheetos as unhealthy. Based on the results of these exploratory studies, it appears that when considering the evaluative category status of foods, children use information about the physical properties of foods that they gather through their senses. Overall, these results are beginning to suggest that an important way in which children acquire their evaluative categories of food is through their direct observations and experiences with food. Future research should continue to examine this issue, as well other ways in which children learn their evaluative categories of food.

CONCLUSIONS The aim of this chapter has been to discuss research in our cognitive development lab that sheds light on how children and adults make sense of the domain of food through evaluative categorization, the grouping together of foods that share the same value laden assessment, such as healthy and unhealthy foods. In particular, the research in our lab has focused on answering the questions, do people form evaluative categories of food and how do people use these categories? The studies described in this chapter are beginning to answer these questions; showing that people do form and use evaluative categories within the domain of food, particularly healthy and unhealthy foods. Children as young as age 3 years have the

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emerging ability to form the evaluative categories of healthy and unhealthy foods. By age 4 years, children have the ability to evaluatively categorize foods from different food groups, and explain their category groupings. Also by age 4 years, children can selectively and appropriately use their evaluative categories of healthy and unhealthy foods to make inductive inferences about the human body. Major improvements in children‘s ability for evaluative categorization and induction occur by age 7 years and the adult years. Recent research is also beginning to reveal that children and adults gather information about the physical properties of foods through their senses, and that this information helps inform their evaluative category decisions. Of course a potential criticism of our work on evaluative categories, however, is that some could argue that this good/bad dichotomy is an oversimplification of how the nutritional value of foods may vary on a continuum and depend upon a number of complex factors (e.g., caloric density, serving size, the historical, cultural, and social context of the situation). Although we admit that this dichotomy is not perfect, given the lack of research on this topic within the conceptual development literature, we argue that this dichotomy is an important starting point since healthy and unhealthy foods are a salient and relevant conceptual distinction for children and adults. Now that we know that children and adults can and do represent these categories accurately, future studies could look at more fine grain distinctions that people may make regarding foods with varying nutritional values to see if there is sensitivity to this continuum. Such findings as well as the current findings from our lab have valuable implications for health education. Given the prevalence and burgeoning rate of child and adult obesity in the United States (American Heart Association, 2006; The Center for Disease Control, 2006), understanding how and when people form evaluative categories of healthy and unhealthy foods is critical in the development of health interventions. For example, based on the findings described in this chapter, health education programs could target children as young as 3-years-old and could focus on foods that children have difficulty classifying as healthy/unhealthy (e.g., unhealthy vegetable derivatives, meat products). Using the research findings on evaluative categorization to inform the development of health education programs can potentially make a positive impact on the effectiveness of these programs as well as on our eating practices and behaviors.

AUTHOR NOTE Simone P. Nguyen and Mary Beth McCullough, University of North Carolina Wilmington. This chapter was supported by NICHD Grant #1R03HD05522201A1 to the first author. We would like to also thank the research assistants, schools, families, and children who participated in the studies described in this chapter.

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REFERENCES American Heart Association. (2006). Overweight in children. Retrieved February 1, 2006 from http://www.americanheart.org. Balogh, R.D. & Porter, R.H. (1986). Olfactory preferences resulting from mere exposure in human neonates. Infant Behavior and Development, 9, 395-401. Bartoshuk, L.M. (1991). Sensory factors in eating behavior. Bulletin of the Psychometric Society, 29(3), 250-255. Beauchamp, G.K., Bertino, M., & Moran, M. (1982). Sodium regulation: Sensory aspects. Journal of the American Dietetic Association, 80, 40. Birch, L.L. (1999). Development of food preferences. Annual Review of Nutrition, 19, 41-62. Birch, L., Fisher, J., & Grimm-Thomas, K. (1999). Children and food. In M. Siegal & C. C. Petereson, (Eds.), Children‟s understanding of biology and health (pp.161-182). Cambridge University Press: Cambridge, England. Birch, L.L. (1979). Dimensions of preschool children's food preferences. Journal of Nutrition Education and Behavior, 11, 77-80. Blass, E.M. & Fitzgerald, E. (1988). Milk induced analgesia and comforting in 10-day-old rats: Opioid mediation. Pharmacology, Biochemistry and Behavior, 29, 9-13. Center for Disease Control and Prevention. (2006). Overweight and obesity: Childhood overweight. Retrieved February 1, 2006, from http://www.cdc.gov Engen, T. & Gasparian, F.E. (1974). A study of taste preferences in young children. Journal of Safety Research, 6, 114. Harris G., & Booth, D.A. (1987). Infants‘ preference for salt in food: Its dependence upon recent dietary experience. Journal of Reproductive and Infant Psychology, 5, 97–104. Harris G., Thomas, A., & Booth, D.A. (1990). Development of salt taste in infancy. Developmental Psychology, 6, 534–538. Krackow, E. & Gordon, P. (1998). Are lions and tigers substitutes or associates? Evidence against slot filler accounts of children‘s early categorization. Child Development, 69, 347-354. Lawless, H. (1985). Sensory development in children: Research in taste and olfaction. Journal of the American Dietetic Association, 85, 577– 582. Lundy, B., Field, T., Carraway, K., Hart, S., Malphurs, J., Rosenstein, M., Pelaez-Nogueras, M. Coletta, F., Ott, D., & Hernandez-Reif, M. (1998). Food texture preferences in infants versus toddlers. Early Child Development and Care, 146, 69-85. Matheson, D., Spranger, K., & Saxe, A. (2002). Preschool children‘s perceptions of food and their food experience. Journal of Nutrition Education and Behavior, 34(2), 85-92. National Institutes of Health. (2005). We Can! Ways to Enhance Children's Activity & Nutrition. Retrieved January 21, 2007 from http://www.nhlbi.nih.gov/health/ public/heart/obesity/ wecan/National Institute of Child Health and Human Development (NICHD). (2005). Media Smart Youth: Eat, think, and be active! Retrieved October 2, 2006, from http://www.nichd.nih.gov/msy/. Nguyen, S. P. (2008). Children‘s evaluative categories and inductive inferences within the domain of food. Infant and Child Development, 17, 285-299. Nguyen, S. P. (2007). An apple a day keeps the doctor away: Children‘s evaluative category representation of food. Appetite, 48, 114-118.

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Nguyen, S. P., & Murphy, G. L. (2003). An apple is more than a fruit: Cross-classification in children‘s concepts. Child Development, 74, 1-24. Nisbett, R.E. & Gurwiz, S.B. (1970). Weight, sex, and the eating behavior of human newborns. J. Comp. Physiol. Psychol., 73, 245-253. Reisner, J., Yonas, A., & Wilkner, K. (1976). Radial localization of odors on newborns. Child Development, 47, 856. Ross, B. H., & Murphy, G. L. (1999). Food for thought: Cross-classification and category organization in a complex real-world domain. Cognitive Psychology, 38, 495-553. Rozin, P. (1990). Development in the food domain. Developmental Psychology, 26, 555-562. Rozin, P., Hammer, L., Oster, H., & Horowitz, T. (1986). The child's conception of food: Differentiation of categories of rejected substances in the 16 months to 5 year age range. Appetite, 7, 141-151. Schmidt, H.J., & Beauchamp, G.K. (1988). Adult-like odor preferences and aversions in three-year-old children. Child Development, 59, 1136-1143. Stein, M.P., Ottenberg, P., & Roulet, M. (1958). A study of the development of olfactorv preferences. AMA Archives of Neurological Psychiatry, 80, 264-266. Steiner J.E. (1977). Facial expressions of the neonate infant indicating the hedonics of foodrelated chemical stimuli. In: Weiffenbach JM, ed. Taste and Development: The Genesis of Sweet Preference. Washington, DC: US Government Printing Office. Thomas, M.A. & Murray, F.S. (1980). Taste perception in young children. Food Technology, 2, 38. Wagstaff, M.A. (1993). Texture as a determinant in the acceptance of snack items by school children. Journal of the American Dietetic Association, 93(11), 1350. Walsh, L.M., Toma, R.B., Tuveson, R.V, & Sondhi, L. (2001). Color preference and food choice among children. The Journal of Psychology, 124(6), 645-653.

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Chapter 7

THE VALIDITY OF NUTRITIONAL ASSESSMENT: CURRENT STATUS Christopher N. Ochner1, Eva M. Conceição2 and Olga Gorlova1 1

New York Obesity Research Center, St. Luke's Roosevelt Hospital Center, Columbia University College of Physicians and Surgeons 2 Universidade do Minho, Department of Psychology

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ABSTRACT The field of nutritional assessment is host to considerable disagreement about which methods of dietary intake assessment may be more or less valid and which techniques are most appropriate for research trials versus clinical practice. This commentary provides a brief overview of the evolution of dietary intake assessment as well as discussing if, and how, newer techniques (i.e., 24-hour food intake recalls) have improved on the validity of dietary assessment. A synopsis of the psychometric data supporting, and not supporting, the most commonly used assessment techniques is provided. Techniques are also discussed in terms of their applicability and utility in both clinical and research settings. Finally, potential offerings for future directions in the area of nutritional assessment are briefly discussed.

In both research and clinical practice in dietary nutrition, the importance of accurately assessing nutritional patterns and dietary intake has led investigators to develop a range of methods for the assessment of dietary intake in outpatient settings. Below we list the most commonly used methods and describe the strength of each one, as well as their applicability in each clinical or research settings. The chapter will conclude with an overview of the major limitations, and will assess the issue of validity inherent to the use of self-report methods.

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METHODS OF NUTRITIONAL ASSESSMENT

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Food Frequency Questionnaires Food frequency questionnaires (FFQs) capture nutritional patterns and frequencies of consumption, measuring long term dietary intake of individuals or groups. As the name implies, FFQs utilize a questionnaire-based format. Responders select from given lists of foods and indicate frequency with which they are consumed (Trabulsi and Schoeller, 2001). Food Frequency Questionnaires are designed assess the type and amount of food carried in the household and consumed over extended periods of time, at least 6 mo to 1 y. Therefore, scientific studies seeking to examine trends in food consumption over long periods of time may choose to include FFQs, while studies with intervention periods less than 6 months typically opt for either traditional food records or 24 hour recalls (described below). Attempts have been made to validate FFQs for short-term use (Eck, Klesges, and Klesges, 1996), however, adequate demonstration of acceptable psychometric properties with short term use remains lacking. When compared to other methods, FFQs are typically not as sensitive regarding specific foods consumed, cooking methods, and portion sizes. In addition, these measures typically require 40 minutes to one hour to complete, making participant burden and compliance potential issues that may hinder its use in certain clinical or research circumstances. However, they are inexpensive and can be self-administered with no oversight or prior training (Thompson and Byers, 1998; Trabulsi and Schoeller, 2001). Out of a wide range of FFQs, the most frequently used are the Block FFQ (Block, Woods, Potosky, and Clifford, 1990), used to estimate the intake of certain food groups and nutrients, and the Willett FFQ (Willett, Sampson, Stampfer, Rosner, Brain, Witschi et al., 1985), which assesses habitual intake. Although the Block and Willett questionnaires differed slightly from each other in estimating absolute nutrients and ranking or classifying individuals (Caan, Slattery, Potter, Quesenberry, Coates, and Schaffer, 1998), they are similar in their ability to predict disease outcome (Caan et al., 1998), and studies and have found similar results when reporting on the criterion validity and the reproducibility of each questionnaire (Subar, Thompson, Kipnis, Midthune, Hurwitz, McNutt et al., 2001).

Dietary History A diet history requires administration by a trained professional and consists of an interview, which assesses the frequency of consumption of various foods, as well as information about the typical content of meals (Thompson and Byers, 1998). The strength of the diet history is its ability to assess typical meal patterns and details of food intake, as opposed to only short term intake (as in food records or 24-hour recalls discussed below) or frequency of food consumption (FFQs; Thompson and Byers, 1998; Trabulsi and Schoeller, 2001). Diet histories also gather details about how foods were prepared (e.g., frying vs. baking), and may better assess nutrient intake as compared to FFQs. However, this method is usually more time-consuming and expensive than other methods, particularly as it requires a trained professional to administer (Thompson and Byers, 1998). Further information on Diet

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History, as well as a Diet History Questionnaire developed by the National Institutes of Health/National Cancer Institute, is available at: http://riskfactor.cancer.gov/DHQ/.

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Food Intake Records (Food Records) The traditional food intake record assessment and is a qualitative diet assessment measures of food intake (Trabulsi and Schoeller, 2001), and remains the most commonly used form of dietary intake. Generally, data is collected in an open-ended format, requiring respondents to record everything they eat and drink, along with specific amounts, immediately after consumption (Buzzard, 1998). Respondents are also instructed to include preparation methods (i.e., fried vs. sautéed), all ingredients, and all additions (e.g., condiments; Thompson and Byers, 1998) each and every time they eat or drink throughout the day. This nutritional information is recorded in blank food diaries (generally appearing like a bank check book) over a period of 3, 5, or 7 days. Food record recordings typically including at least one weekend day, as weekend intake may differ substantially from weekday intake. Food records are the cheapest of the nutritional assessment options and can be selfadministered with relatively little participant/patient training. However, food records do carry several limitations. The opportunity for omission with this method is readily identifiable, both intentionally and unintentionally. Many individuals forget to include, or fail to provide sufficient detail on, preparation methods, ingredients, and additions (Thompson and Byers, 1998). In addition, individuals have a tendency to ―selectively underreport‖ foods higher in caloric density (snack or ―junk‖ foods; Johansson, Wikman, hreÂn, Hallmans,and Johansson, 2001). The degree of underreporting is generally related to body mass index (BMI), reflecting more underreporting the greater the degree of underweight of the individual (BallardBarabash, Graubard, Krebs-Smith, Schatzkin, Thompson, 1996). Selective underreporting is, however, not specific to food records (discussed further below). Degradation of memory over time is of particular concern when using food records, as many individuals report filling out their food diaries at the end of the day, week, or sometimes in the waiting area while waiting to see their weight loss counselor or study personnel. Food records require a very high degree of compliance for individuals to immediately record each item ingested each time they ingest anything.

24-Hour Dietary Recalls This method requires a trained interviewer to work with the individual to recollect, in detail, everything consumed during the previous 24 hours. The trained interviewer reduces the burden placed on the individual and can administer the recall by telephone (Thompson and Byers, 1998). Interviewers are typically trained to use a ―multiple pass‖ (multipass) method of administration. The USDA created a 3-pass method, which was later modified into the standardized 5-pass method now considered the preferred method of administration (Guenther, De Maio, Berlin, 1997). The 5-pass method consists of the following: 1) a ―quick list‖ pass in which the respondent is asked to list everything eaten or drunk the previous day; 2) a ―forgotten foods‖ pass in which a standard list of food/beverages, often forgotten, is read to prompt recall; 3) a ―time and occasion‖ pass in which the time and name of the eating

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occasion are collected; 4) a ―detail‖ pass in which detailed descriptions and portion sizes are collected and the time interval between meals is reviewed to check for additional foods; and 5) the ―final‖ pass, which provides one last opportunity for the respondent to remember foods consumed. For each food reported, interviewers referred to a standardized food pictures and models booklet. Then, the recall data is entered into a nutrient database preprogrammed with the nutrient content of most common foods and ingredients (Shai, 2003). Twenty-four hour dietary recalls are purported to increase the validity of dietary intake assessment over traditional food records (Buzzard, Faucett, Jeffery, McBane, McGovern, Baxter et al., 1996). The presumed improvement in validity is hypothesized to stem from the fact that 24-hour recalls are conducted in interview, as opposed to blank self-report, format. Thus, individuals cannot forget and provide 24-hour recall data retrospectively, decreasing the chance of reporting error due to memory degradation (Thompson and Byers, 1998). Interviews are conducted by trained interviewers, eliminating the potential for omission of preparation methods and reducing the likelihood of omission of food additions. The 24-hour recall is considered by many to be the best method available for nutritional assessment. However, it remains a self-report measure and is, therefore, subject non-random underreporting (Trabulsi and Schoeller, 2001).

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Error and Validity in Nutritional Assessment Major issues regarding the validity of dietary recalls and food records for estimating usual individual intake are generally related to how accurately individuals can record or recall their intakes on a given day (identification foods eaten and estimating of portion sizes), how well food composition database and the coding and nutrition database system reflect the overall composition of the actual food eaten, and how well the selected days of intake represent usual individual intake (Buzzard, 1998). Generally, reporting error may be due to different forms of behavior, each one holding different implications for data analysis: 1. Food beaten but deliberately NOT reported (intentional under-reporting); 2. Reduced food consumption or avoidance of certain foods due to monintoring (unintentional behavioral change or under-eating), and; 3. Food being eaten but genuinely forgotten (unintentional /unknowing under-reporting). A large body of literature has been devoted to examining the extent to, and circumstances under, which individuals tend to under-report their food intake (Macdiarmid, and Blundell, 1998; Miller, Abdel-Maksoud, Crane, Marcus, and Byers, 2008; Johansson et al., 2001). Random underreporting would tend to even out over large samples; however, selective underreporting introduces a systematic bias in all self-report measures of dietary intake (Trabulsi and Schoeller, 2001). In fact, the prevalence of under-reporting in large nutritional surveys seems to range, depending on the studies, from 18 to 54 % of the whole sample, but can be as high as 70 % in particular subgroups (Macdiarmid, and Blundell, 1998). As stated, the degradation of memory over time may lead to reporting error. Memory biases also tend to interact with individual and psychological characteristics, such as BMI and body dissatisfaction (Miller et al., 2008). Overweight individuals tend to underreport intake to a greater degree than lean subjects, due to a heightened fear of social evaluation (negative evaluation by others; Johansson et al., 2001). For instance, Ballard-Barbash et al. (1996) reported the prevalence of under-reporting to be as high as 71 % in overweight women

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(BMI>27.3), which was nearly 1.5 times greater than for normal weight women (BMI = 1927.3) and 2.5 times greater than for underweight women (BMI < 19; Macdiarmid, and Blundell, 1998). Social desirability is associated with reporting accuracy (Taren, Tobar, Hill, Howell, Shisslak, Bell, and Ritenbaugh, 1999), and food items perceived to be socially unacceptable (unhealthy foods) are underreported to a significantly greater extent than are socially acceptable (healthier foods; Johansson et al., 2001). In addition, gender represents another significant influence in underreporting; women are more likely to under-report than men (Macdiarmid, and Blundell, 1998). Social desirable responding may be more prevalent in women due to certain foods, and limited quantities, being associated with ‗femininity‘, reflecting social pressure to conform to a certain ‗diet‘ (Chaiken and Pliner, 1987). The lack of adequate qualitative and quantitative food descriptions may also result in reporting error. This is particularly pertinent during interview-based assessments with responders recalling information by phone, which commonly results in improper portion estimates by the interviewer. (Buzzard, 1998) In addition, lack of motivation can be a potential source of error and result in reporting error on by the subject‘s and/or interviewer. Furthermore, research suggests that a subject‘s motivation to provide complete and accurate information is affected by the perceived importance and applicability of the study results (Bureau of Social Science Research, 1980), which also puts a higher responsibility on the interviewer to stress important points and not the subject: introduce themselves, introduce the study, emphasize its importance, and take time to explain the purpose and steps of the particular program. (Buzzard, 1998)All previously described methods rely on self-reported dietary intake, which is subject to both systematic and random error (Trabulsi and Schoeller, 2001), thus, limiting the validity (accuracy) of these measures (Buzzard, 1998). Some of the systematic biases found in food records and FFQs may be reduced by the use of 24-hour recalls, however, just how ―valid‖ 24-hour dietary recalls are is quite controversial (Johansson et al., 2001). These authors would offer that 24-hour recalls are likely to be less invalid, rather than more valid, than other dietary intake measures. The testing of this assumption is, however, hampered by the availability of only incomplete or indirect measures of nutrient intake for self-report measures to be validated against. Validation of these procedures has been a major concern for researchers, as true validation would require a comparison with another reference instrument, known to be reliably accurate, such as a biological marker. Unfortunately, few such markers have been identified and are generally for individual or small clusters of nutrients, providing a reference measure for only a small percentage of total nutritional intake. Further, some evidence suggests that even biological markers may not necessarily be 100% accurate (REF). Short of continual direct observation, or 100% controlled feeding studies (both typically prohibitively labor/time/staff-intensive and expensive), there remains no way of directly assessing how accurate and valid any currently available measures of dietary intake truly are. The Doubly Labeled water (DLW), developed by Lifson et al. (1949), has been used in attempts to validate nutritional assessment techniques (Trabulsi and Schoeller, 2001). What doubly-labeled water actually measures, however, is energy expenditure. Energy intake is then inferred by the energy balance equation. That being that, when body weight remains constant, energy intake equals energy expenditure (Jebb, 2002). Although this method does allow for more accurate estimates of energy intake and has helped to identify some of the systematic biases (underreporting) endemic to particular populations, it is time and cost

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prohibitive for use in most settings (Thompson and Byers, 1998). Therefore, without direct and continual monitoring, dietary intake assessment will remain largely dependent on selfreport (and the associated biases).

CLINICAL AND RESEARCH APPLICATIONS Despite the noted limitations, estimates of energy intake are useful in both clinical and research settings.

Clinical Applications Food records are frequently used as part of a lifestyle change treatment approach. Details on food intake, along with time of consumption, may provide a weight loss counselor with valuable information in order to address weak points or barriers to success during sessions with the patient. In addition, food recording itself has been shown to reduce caloric intake*

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Research Applications Dietary intake is a frequent outcome measure for dietary interventions, despite our inability to measure it accurately. More accurate measures of intake are desperately needed. Most valid measure is most important (all will provide relatively same data when analyzed with modern nutrition programs, such as NDSR and Nutritionist). However, time may be more of a factor, as certain measures take longer to complete (i.e., FFQ), and some measures require repeated phone contacts (i.e., 24-hour recalls). Finally, cost of collecting such data may be a factor in research studies. Small pilot studies with little funding will likely not be able to afford to have trained nutritionists conduct 24-hour recalls. In such instances, necessity may dictate the choice of measure (e.g., food records chosen due to budgetary restrictions).

Future Directions Being that the next generation of dietary assessment techniques will still, in large part, rely on self-report, the underreporting bias cannot be altogether eliminated. Advances in technology, however, may help to minimize it. The use of personal data assistants, referred to as ecological momentary assessment (EMA) devices, may increase the likelihood that individuals will report intake at the time it occurs and allow researchers or clinicians to note gaps in reporting (e.g., if no data is submitted from lunch to breakfast the following day). Individuals can either be contacted immediately to obtain the missing data, reminded electronically, or the data could be considered missing. What would be prevented is the use of less-valid data as is the case when individuals retrospectively recall data further out from the occurrence (e.g., using food record data that was filled in that morning for the prior week).

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With EMAs, participants could respond to an alarm programmed to go off at several (random) points during any given day, thus providing a sampling of eating frequency or types of foods consumed at these (random) assessment points and over time. Eventually, it may be possible to use EMAs to capture a more accurate sampling of total food intake as well.

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REFERENCES Ballard-Barabash, R., Graubard, I., Krebs-Smith, S. M., Schatzkin, A., Thompson, F. E. (1996). Contribution of dieting to the inverse association between energy intake and body mass index. European Journal of Clinical Nutrition; 50:98-106. Benedict, J. A., and Block, G. (1997). Food Frequency Questionnaires. In St. Jeor ST, ed. Obesity Assessment Tools Methods Interpretations A Reference Case: The RENO DietHeart Study. New York: International Thomson Publishing, 245-250. Block, G., Woods, M., Potosky, A., and Clifford, C. (1990). Validation of a selfadministered diet history questionnaire using multiple diet records. Journal of Clinical Epidemiology, 43, 1327-1335. Buzzard, M. (1998). 24-hour dietary recall and food record methods. In: Willett W., ed. Nutritional Epidemiology. 2. New York : Oxford University Press, 52. Buzzard, I., Faucett, C., Jeffery, R., McBane, L., McGovern, P., Baxter, J., Shapiro, A., Blackburn, G., Chlebowski, R., and Elashoff, R. (1996). Monitoring Dietary Change in a Low-Fat Diet Intervention Study Advantages of Using 24-Hour Dietary Recalls vs Food Records. Journal of the American Dietetic Association, 96(6), 574 – 579. Caan, B. J., Slattery, M. L., Potter, J., Quesenberry, C. P., Jr., Coates, A. O., and Schaffer, D. M. (1998). Comparison of the Block and the Willett Self-administered Semiquantitative Food Frequency Questionnaires with an Interviewer-administered DietaryHistory, American Journal of Epidemiology, 148,1137-47. Eck, L. H., Klesges, L. M., and Klesges, R. C. (1996). Precision and estimated accuracy of two short-term food frequency questionnaires compared with recalls and records. Journal of Clinical Epidemiology, 49(10), 1195-2000. Guenther, P. M., DeMaio, T. J., and Berlin, M. (1997). The multiple-pass approach for the 24-h recall in the Continuing Survey of Food Intakes by Individuals. American Journal of Clinical Nutrition, 65 (4supplement),1316S. Hartman, A. M., Block, G., Chan, W., Williams, J., McAdams, M., Banks, W. L., Jr, and Robbins, A. (1996). Reproducibility of a self-administered diet history questionnaire administered three times over three different situations. Nutrition and Cancer; 25, 305315. Jebb, S. A. (2002). Energy intake and body weight. In: Fairburn CG, Brownell KD, eds. Eating disorders and obesity: a comprehensive handbook. New York: Guilford Press, pp. 37–42. Johansson, G., Wikman, A.E., Ê hreÂn, A. M., Hallmans, G., and Johansson, I. (2001). Underreporting of energy intake in repeated 24-hour recalls related to gender, age, weight status, day of interview, educational level, reported food intake, smoking habits and area of living, Public Health Nutrition, 4(4), 919-927.

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Lifson, N., Gordon, G. B., Visscher, M. B., Nier, A. O. (1949). The fate of utilized molecular oxygen and the source of the oxygen of respiratory carbon dioxide, studied with the aid of heavy oxygen. Journal of Biological Chemistry; 180: 803–811. Macdiarmid, J., and Blundell, J. (1998). Assessing dietary intake: Who, what and why of under-reporting, Nutrition Research Reviews, 11, 231-253 Mares-Perlman, J. A., Klein, B. E., Klein, R., Ritter, L. L., Fisher, M. R., and Freudenheim J. L. (1993). A diet history questionnaire ranks nutrient intakes in middle-aged and older men and women similarly to multiple food records. Journal of Nutrition, 123, 489-510. Miller, T. M., Abdel-Maksoud, M. F., Crane, L. A., Marcus, A. C., and Byers, T. E. (2008). Effects of social approval bias on self-reported fruit and vegetable consumption: a randomized controlled trial, Nutrition Journal, 7:18 Shai, I., Vardi, H., Shahar, R. D., Azrad, A. B., and Fraser, D. (2003) Adaptation of international nutrition databases and data entry system tools to a specific population. Public Health Nutrition, 6, 401–406. Subar, A. F., Thompson, F. E., Kipnis, V., Midthune, D., Hurwitz, P., McNutt, S., McIntosh,A., and Rosenfeld, S. (2001). Comparative Validation of the Block, Willett, and National Cancer Institute Food Frequency Questionnaires, American Journal of Epidemiology, 154, 1089–99. Taren, D. L., Tobar, M., Hill, A., Howell, W., Shisslak, C., Bell, I., and Ritenbaugh, C. (1999). The association of energy intake bias with psychological scores of

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women. European Journal of Clinical Nutrition; 53(7): 570-578. Thompson, F. E., and Byers, T. (1994). Dietary Assessment Resource Manual.Journal of Nutrition. 124, 2245S-2317S. Thompson, F. E., Subar, A. F., Brown, C. C., Smith, A. F., Sharbaugh, C. O., Jobe, J. B., Mittl, B., Gibson, J. T., and Ziegler, R. G. (2002). Cognitive research enhances accuracy of food frequency questionnaire reports: results of an experimental validation study. Journal of the American Dietetic Association, 102(2), 212-25. Trabulsi, J. and Schoeller, D. A. (2001). Evaluation of dietary assessment instruments against doubly labeled water, a biomarker of habitual energy intake, American Journal of Physiology. Endocrinology and Metabolism, 281, E891–E899 Willett, W. C., Sampson, L., Stampfer, M. J., Rosner, B., Brain, C., Witschi, J., Hennekens, C.H., and Speizer F. E. (1985). Reproducibility and validity of a semi-quantitative food frequency questionnaire. American Journal of Epidemiology, 122, S1-65.

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Chapter 8

METHODOLOGICAL RESEARCH CONCERNING THE ACCURACY OF CHILDREN’S DIETARY RECALLS Suzanne Domel Baxter*1, Caroline H. Guinn*2, James W. Hardin*3, Julie A. Royer*4 and Dawn K. Wilson*5 1

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University of South Carolina, Institute for Families in Society, 1600 Hampton Street, Suite 507, Columbia, SC 29208, U.S.A. 2 University of South Carolina, Institute for Families in Society, 1600 Hampton Street, Suite 507, Columbia, SC 29208, U.S.A. 3 University of South Carolina, Department of Epidemiology and Biostatistics, 730 Devine Street, Suite 112-J, Columbia, SC 29208, U.S.A. 4 University of South Carolina, Institute for Families in Society, 1600 Hampton Street, Suite 507, Columbia, SC 29208, U.S.A. 5 University of South Carolina, Department of Psychology, Barnwell College, Columbia, SC 29208, U.S.A.

ABSTRACT Although studies involving elementary school children sometimes collect dietary reports from parents either solely or in collaboration with children, many study designs necessitate that children‘s self-reports be collected because parents are not present for the eating occasions of interest (e.g., school meals). In a dietary-reporting validation study, reported information (food items and their respective amounts) from a method such as dietary recalls is compared to reference information (food items and their respective amounts) from a gold standard method such as observation which is assumed to be the truth, collected independent of the subject‘s memory, and concerns the same meal(s) as reported information. Comparing reported information to reference information allows identification of reporting errors including omissions (referenced [eaten] items that are *

Telephone 8037771824 extension 12; Fax 8037771120; [email protected] Telephone 8037771824 extension 24; Fax 8037771120; [email protected] * Telephone 8037770388; Fax 8037770391; [email protected] * Telephone 8037771824 extension 23; Fax 8037771120; [email protected] * Telephone 8039787500; Fax 8039787521; [email protected] *

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Suzanne Domel Baxter, Caroline H. Guinn, James W. Hardin et al. unreported and intrusions (reported items that are unreferenced [uneaten]). This chapter summarizes key findings from 26 methodological studies concerning children‘s dietary recall accuracy that were conducted by Baxter and colleagues and published between 1994 and 2009; the 26 studies consist of nine dietary-reporting validation studies, one non-validation study, and 16 secondary analyses studies that utilized data from one or more of the nine validation studies. The validation method was observation of school lunch, or observation of school breakfast and school lunch. The subjects were usually fourth-grade children (ages nine to ten years). Each validation study was designed to evaluate the effect on children‘s dietary recall accuracy of aspects including prompting methods, consistency of accuracy over multiple recalls, reporting-order prompts, interview modality, interview format, retention interval, and children‘s body mass index (BMI). The non-validation study investigated whether being observed eating school meals influenced children‘s dietary recalls. The secondary analyses studies utilized data from one of more of the validation studies to examine aspects including retrieval response categories (of children‘s verbalizations of how they remembered items eaten), accuracy over multiple 24-hour recalls by BMI category, accuracy for recalling school lunch as a single-meal recall versus during a 24-hour recall, accuracy for reporting school breakfast versus school lunch during 24-hour recalls, the analytic approach for comparing reported and reference information to assess recall accuracy for energy and macronutrients, sources (or origins) of intrusions and types of intrusion, and intrusions in misreported and correctly reported breakfast options in the school breakfast parts of 24hour recalls. The chapter concludes with recommendations for (a) dietary-reporting validation studies to fill research gaps, (b) maximizing children‘s dietary recall accuracy, and (c) publications of studies that utilize dietary recalls.

INTRODUCTION

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Children’s Dietary Intake and Chronic Diseases Excess dietary intake is a controllable risk factor of chronic diseases such as obesity, diabetes, heart disease, and cancer [77,177,178], and some of the physiological processes that lead to these chronic diseases in adulthood begin in childhood [77,162,177,178,186]. Since the 1960s, the incidence of obesity has increased dramatically among children in the USA [42,72,90,133,134,169], and surveys indicate a growing global obesity epidemic among school-age children [184]. The consequences of obesity are among the most burdensome public health issues faced by the USA [176], and from 1979 to 1999, the percentage of hospital discharges of youths ages six to 17 years increased for all obesity-associated diseases [183]. Research has found that the prevalence of overweight among youth differs by ethnicity [90,101,121,133,134], sex [90,121,133], and socioeconomic status [124], and that overweight youth are at increased risk for type two diabetes, orthopedic problems, and adverse levels of several cardiovascular disease risk factors [71,176]. Furthermore, youth with high body mass index (BMI) percentiles are at high risk of being obese adults [84].

Rationale for Obtaining Children’s Self-Reports of Dietary Intake Assessing dietary intake is challenging, especially among children [7,67,120]. For many purposes, the accuracy of dietary data is inadequate despite decades of developing data

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 199

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collection methods for assessing intake [106]. While it is widely accepted that a major problem in dietary surveys is misreporting [108], most investigations linking diet and disease have used memory-based self-reports of diet, even though memory is imperfect [58,108,154,159]. Parents may be asked to report their elementary school children‘s dietary intake, but validation studies [40,59,61,83,117,137] underscore concerns that it is unrealistic to expect parents to accurately report their children‘s intake, especially for meals eaten in locations at which parents are not present (e.g., at school). Thus, it is necessary to rely on elementary school children to self-report this information. In a dietary-reporting validation study, a set of reported information (which consists of food items and their respective amounts) from a method such as a 24-hour dietary recall (24hDR) is compared to a set of reference information (which also consists of food items and their respective amounts) from a gold standard method such as observation which is assumed to be the truth (i.e., complete and without error), collected independent of the subject‘s memory, and concerns the same meal(s) as reported information. Comparison of the set of reported information to the set of reference information allows identification of dietary reporting errors including omissions (referenced [eaten] items that are unreported and intrusions (reported items that are unreferenced [uneaten]) [154,159]. When reference information is not collected independent of the subject‘s memory but instead both reported information and reference information are reported by subjects, for example, when 24hDRs are compared to food records, the assessment is more appropriately called a relative dietaryreporting validation study. A better understanding of dietary reporting errors could guide the development or refinement of data collection methods to enhance dietary reporting accuracy which could improve ascertainment of diet-disease relationships and provide information to suggest dietary changes in childhood to help decrease chronic disease risk later in life.

Developmental Aspects of Children’s Self-Reports of Dietary Intake The cognitive developmental literature suggests that children in early to mid-elementary years will have less ability to recall dietary intake than children in late elementary years. Children ages six to eight years (early elementary years) understand causal relationships and can manipulate thoughts and intentions; however, their cognitions are tied to personal experiences and external reality [148]. The understanding that reality is constructed in our minds is not evident until the late elementary years (ages nine to 11 years) [66]. Children ages six to eight years have elements of time-based images of reality that can be reversed to consider past sequences; however, the cognitive ability (viewing process) of children this age is still quite linear and tied to reality. This is often referred to as concrete operational thought (i.e., reasoning based on personal experience and concrete reality). Children ages six to eight years are in transition from preoperational to concrete operational thought. Generally, most children ages six to eight years cannot yet consider complex relationships with multiple causality beyond reality. Thus, dietary self-report methods are generally used with children over age nine years, or third grade [67].

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Cognitive Aspects of Self-Reports of Dietary Intake Episodic memory and semantic memory have been differentiated [170]. Episodic memories are context-bound (i.e., memories that particular events occurred in particular contexts). Semantic memory is situation-independent knowledge (e.g., general information). A dietary report is supposed to tap episodic memory, but errors indicate that this tapping is not entirely successful. In publications of dietary-reporting validation studies with children, investigators have speculated that intrusions may be misreports of temporally nearby meals, or products of fantasy [6,47,61]; the former are reports of specific memories of wrong episodes while the latter may be reports of generic information. Similarly, omissions may occur due to specific memories of wrong episodes, or due to reports of generic information.

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Methods for Obtaining Children’s Self-Reports of Dietary Intake Children have completed food frequency questionnaires (FFQs) for numerous studies [5,8,47,51,54,63,64,92,93,130,144,145], but there are concerns that elementary school children lack the cognitive skills (e.g., averaging consumption) necessary to complete FFQs accurately [8,54,64,143]. Food records have been completed by children for many studies [9,47,53,78,125,150]. In theory, food records should be more accurate than retrospective methods, but because a common problem is remembering to complete them [78,180], food records often are completed later from memory instead of at the time of intake. Also, the process of completing food records may change eating behavior [39,143,155]. Children have provided 24hDRs for national surveys [38,79,100,165,172] and epidemiologic studies [113115,129,179,187], for evaluation of nutrition education interventions [45], and for assessment of the relative validity of FFQs [51,64,93,144]. Due to daily intra-individual variation in intake, a single 24hDR is a poor estimate of a person‘s typical intake; a better estimate is obtained from multiple 24hDRs [189]. Information from one 24hDR per subject is often used to estimate a group‘s intake [189]. Daily checklists (a combination of the FFQ, food record, and 24hDR) are completed by subjects who mark yes or no and/or indicate the frequency of consuming specific items on the previous day. Children have completed daily checklists retrospectively for several studies [60,62,104], but validation has indicated limited success [104]. Methodological research by Baxter and colleagues to understand errors in children‘s selfreports of dietary intake has focused on dietary recalls for several reasons. It appears that studies will continue to use children‘s dietary recalls. Furthermore, as reviewed in the previous paragraph, 24hDRs are commonly used with children, food records may lead to changes in eating behavior, and elementary school children lack the cognitive skills necessary to accurately complete FFQs.

Validity of Children’s Dietary Recalls Schools in the USA provide an excellent setting to validate parts of children‘s 24hDRs because millions of children eat school meals each school day [67,151]. For example, on each school day during fiscal year 2007, 10.1 million and 30.6 million children participated in

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 201 school breakfast and school lunch, respectively, representing 24% and 60% of all children attending schools with these meal programs [173]. Observations of children eating meals in private homes is intrusive [41], obvious [151], unacceptable in some communities [187], and may cause substantial reactivity [155]. Reactivity is less likely when observations occur at school [151] where children in groups are accustomed to being watched while eating [32,151] and where groups may be observed without revealing to individual children who, specifically, is being observed [33]. Therefore, results from observing school meals are more generalizable than results from observing children eating meals at home, or from observing meals provided to children in a clinical research center. In most validation studies in which children have provided dietary recalls orally and without parental help, reference information has been obtained by observing one or two school meals [6,18,22,26,29,31-33,47,56,115,116,147,168,185,187]. These validation studies have found that children‘s recall accuracy for school meals is poor due to omissions and intrusions [6,22,26,29,31-33,47,56,61,122,168]. Warren and colleagues [185] found that elementary school children‘s recall accuracy for packed lunches (from home) was better than for school lunches, perhaps due to increased familiarity of foods in packed lunches. Although cycle menus are used in many schools [56], food items in packed lunches from home probably are more common and consistent than food items in school lunches.

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Overview of Chapter This chapter summarizes key findings from 26 methodological studies conducted by Baxter and colleagues and published between 1994 and 2009. The 26 studies consisted of nine dietary-reporting validation studies (Studies 1, 2, 6, 7, 10 through 13, and 15), one nonvalidation study (Study 14) that investigated whether being observed eating school meals influenced children‘s 24hDRs, and 16 secondary analyses studies (Studies 3 through 5, 8, 9, and 16 through 26) that utilized data from one or more of the nine dietary-reporting validation studies. The chapter concludes with recommendations for dietary-reporting validation studies to fill research gaps, recommendations for maximizing the accuracy of children‘s dietary recalls, and recommendations for publications of studies that utilize dietary recalls.

SUMMARY OF SUBJECTS AND METHODS Subjects and Design Prior to data collection for each study, approval was obtained from the appropriate institutional review boards for research involving human subjects; child assent and parental consent to participate were obtained in writing. Details of data collection that were common to many of the 26 studies are summarized in this section; complete details are found in the publications for each specific study. Table 1 provides an illustration along with alphabetized definitions of terms. Table 2 provides an overview of each study including the purpose or focus, sample, grade, school year and number of schools, validation method, target period of recall, interview time, prompts or interview format, design, and key results.

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Table 1. Illustration (using food items, amounts, and energy in kilocalories [kcal] for an interview for a given child) and definitions of terms

Absolute amount difference per match: b This item amount = {sum ([absolute difference between amounts reported and observed for each match] x weight)} / (weighted number of matches). Values are undefined if there are no matches. Values close to zero indicate higher (better) accuracy. In the illustration, the mean absolute amount difference per match for this child for school breakfast and school lunch is ([0.25 × 1.00] + [0 × 1.00] + [0.50 × 1.00] + [0.50 × 1.00] + [0.25 × 1.00] + [0 × 1.00]) / 6.00 = 0.25 serving. Amount per intrusion: b This item amount = {sum ([amount not observed but reported for each intrusion] x weight)} / (weighted number of intrusions). Values are undefined if there are no intrusions. Values close to zero indicate higher (better) accuracy. In the illustration, the mean amount per intrusion for this child for school

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breakfast and school lunch is ([1.00 × 1.00] + [0.75 × 2.00]) / 3.00 = 0.83 serving. Amount per omission: b This item amount = {sum ([amount observed but not reported for each omission] x weight)} / (weighted number of omissions). Values are undefined if there are no omissions. Values close to zero indicate higher (better) accuracy. In the illustration, the mean amount per omission for this child for school breakfast and school lunch is ([1.00 × 1.00] + [1.00 × 2.00] + [1.00 × 0.33]) / 3.33 = 1.00 serving. Arithmetic amount difference per match: b This item amount = {sum ([amount reported – amount observed for each match] x weight)} / (weighted number of matches). Values are undefined if there are no matches. Average under- and over-reporting are indicated by negative and positive values, respectively. Values close to zero are interpreted as indicating higher (better) accuracy; however, under- and over-reported amounts can offset each other, so averages that appear accurate may disguise considerable error balanced over the two directions. In the illustration, the mean arithmetic amount difference per match for this child for school breakfast and school lunch is ([–0.25 × 1.00] + [0 × 1.00] + [0.50 × 1.00] + [0.50 × 1.00] + [–0.25 × 1.00] + [0 × 1.00]) / 6.00 = 0.08 serving. Correspondence rate: For energy or any nutrient, this rate is calculated as (sum of corresponding amounts from matches / total observed amount) × 100%. It is a genuine measure of reporting accuracy that is sensitive to reporting errors. It has a lower bound of 0% (indicating that nothing observed eaten was reported eaten) and an upper bound of 100% (indicating that all observed items and their respective observed amounts were reported correctly). Higher rates reflect better reporting accuracy. In the illustration, the correspondence rate for energy for this child for school breakfast and school lunch is (503 kcal / 900 kcal) × 100% = 56%. Corresponding amount from a match: For energy or any nutrient, this is the smaller of the reported and observed amounts of a match (or the reported amount if it was equal to the observed amount of a match). In the illustration, for energy, the sum of the corresponding amounts from matches for this child for school breakfast and school lunch is 60 kcal (from 0.75 serving of white milk) + 125 kcal (from 1 biscuit) + 40 kcal (from 0.50 serving of applesauce) + 25 kcal (from 0.50 serving of green beans) + 113 kcal (from 0.75 serving of chocolate milk) + 140 kcal (from 1.00 serving of vanilla ice cream) = 503 kcal. Inflation ratio: For energy or any nutrient, this ratio is calculated as ([sum of over-reported amounts from intrusions + sum of over-reported amounts from matches] / total observed amount) × 100%. It is a measure of reporting error. It has a lower bound of 0% (indicating no over-reported amounts of matches and no over-reporting from intrusions), but no upper bound because there is no limit on what an individual can report. Lower inflation ratios reflect better reporting accuracy. In the illustration, for energy, the inflation ratio for this child for school breakfast and school lunch is ([330 kcal + 65 kcal] / 900 kcal) × 100% = 44%. Intruded kilocalories: This is calculated as (sum of kcal from entire reported amounts of intrusions) + (sum of kcal from parts of matches for which reported amounts exceeded observed amounts). For energy, this is the same as (sum of over-reported amounts from intrusions) + (sum of over-reported amounts from matches). Intrusion: This is a food item that was not eaten but was reported eaten for the respective meal. In the illustration, intrusions are Cheerios cereal and spaghetti, and the weighted b number of intrusions for this child for school breakfast and school lunch is 1.00 + 2.00 = 3.00. Intrusion rate: b This food-item rate is calculated as (sum of weighted intrusions / [sum of weighted intrusions + sum of weighted matches]) × 100%. Values are undefined if there are no intrusions and no matches; that is, there are items observed eaten but no items reported eaten. Defined values may range from 0% (indicating no intrusions) to 100% (indicating that no items reported eaten were observed eaten). In the illustration, the intrusion rate for this child for school breakfast and school lunch is (3.00 / [3.00 + 6.00]) × 100% = 33%. Match: This is a food item that was eaten and reported eaten for the respective meal. In the illustration, matches are white milk, biscuit, applesauce, green beans, chocolate milk, and vanilla ice cream, and the weighted b number of matches for this child for school breakfast and school lunch is 1.00 + 1.00 + 1.00 + 1.00 + 1.00 + 1.00 = 6.00. Matched kilocalories: This is the sum of kcal from amounts of matches that overlapped between reported and observed amounts. For energy, this is the same as the (sum of corresponding amounts from matches). Number of items observed eaten: b This is the sum of the weighted number of items observed eaten in any non-zero amount. In the illustration, the weighted number of items observed eaten for this child for school breakfast and school lunch is 1.00 + 1.00 + 1.00 + 1.00 + 2.00 + 0.33 + 1.00 + 1.00 + 1.00 = 9.33.

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Number of items reported eaten: b This is the sum of the weighted number of items reported eaten in any non-zero amount. In the illustration, the weighted number of items reported eaten for this child for school breakfast and school lunch is 1.00 + 1.00 + 1.00 + 1.00 + 1.00 + 1.00 + 1.00 + 2.00 = 9.00. Observed kilocalories: This is the sum of kcal from amounts of items observed eaten. For energy, this is the same as the total observed amount. Omission: This is a food item that was eaten but was not reported eaten for the respective meal. In the illustration, omissions are scrambled egg, hot dog on bun, and ketchup, and the weighted b number of omissions for this child for school breakfast and school lunch is 1.00 + 2.00 + 0.33 = 3.33. Omission rate: b This food-item rate is calculated as (sum of weighted omissions / [sum of weighted omissions + sum of weighted matches]) × 100%. Values are undefined if there are no omissions and no matches; that is, if there are no items observed eaten. Defined values may range from 0% (indicating no omissions) to 100% (indicating that no items actually eaten were reported eaten). In the illustration, the omission rate for this child for school breakfast and school lunch is (3.33 / [3.33 + 6.00]) × 100% = 36%. Omitted kilocalories: This is calculated as (sum of kilocalories from entire unreported amounts of omissions) + (sum of kilocalories from parts of matches for which reported amounts were smaller than observed amounts). For energy, this is the same as (sum of unreported amounts from omissions) + (sum of under-reported amounts from matches). Over-reported amount from an intrusion: For energy or any nutrient, this is the entire reported amount of an intrusion. In the illustration, for energy, the sum of the over-reported amounts from intrusions for this child for school breakfast and school lunch is 80 kcal (from 1.00 serving of Cheerios cereal) + 250 kcal (from 0.75 serving of spaghetti) = 330 kcal. Over-reported amount from a match: For energy or any nutrient, this is the part of the reported amount that exceeded the observed amount of a match (or zero if the reported amount was less than the observed amount of a match). In the illustration, for energy, the sum of the over-reported amounts from matches for this child for school breakfast and school lunch is 40 kcal (from 0.50 serving of applesauce) + 25 kcal (from 0.50 serving of green beans) = 65 kcal. Previous-day target period: This is the period of time that occurred from midnight to midnight of the day preceding the interview. For a 24-hour dietary recall conducted on a Tuesday at 1:30 p.m., a child interviewed about the previous-day target period would be asked to report meals and snacks eaten on Monday between midnight and midnight. Prior-24-hour target period: This is the period of time that occurred from 24 hours before the interview until the time the interview started. For a 24-hour dietary recall conducted on a Tuesday at 1:30 p.m., a child interviewed about the prior-24-hour target period would be asked to report meals and snacks eaten between 1:30 p.m. on Monday and 1:30 p.m. on Tuesday. Report rate: For energy or any nutrient, this rate is calculated as (total reported amount / total observed amount) × 100%. It is a conventional measure of reporting accuracy that is indifferent to reporting errors. It has a lower bound of 0% (indicating that nothing was reported), but no upper bound because there is no limit on what an individual can report. Report rates with values close to 100%, greater than 100%, and less than 100% have typically been interpreted as indicating high reporting accuracy, over-reporting, and under-reporting, respectively. The report rate = correspondence rate + inflation ratio. In the illustration, for energy, the report rate for this child for school breakfast and school lunch is (898 kcal / 900 kcal) × 100% = 100%. Reported kilocalories: This is the sum of kilocalories from amounts of items reported eaten. For energy, this is the same as the total reported amount. School breakfast option observed eaten: Observed information for a child on a school morning was used to classify a school breakfast option observed eaten as cold (if ready-to-eat [RTE] cereal and/or graham/animal crackers was/were observed eaten), hot (if a non-RTE-cereal entrée and/or fruit was/were observed eaten), mixed (if RTE cereal and/or graham/animal crackers was/were observed eaten as well as a non-RTE-cereal entrée and/or fruit, with one or more items from the non-selected school breakfast option that was obtained in a trade), beverage only (if only milk and/or juice was/were observed eaten), or nothing (if none of the school breakfast was observed eaten). In the illustration, the school breakfast option observed eaten was hot. School breakfast option reported eaten: Information from a school breakfast report obtained during a child‘s dietary recall was used to classify a school breakfast option

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reported eaten as cold (if RTE cereal and/or graham/animal crackers was/were reported eaten), hot (if a non-RTE-cereal entrée and/or fruit was/were reported eaten), mixed (if RTE cereal and/or graham/animal crackers was/were reported eaten as well as a non-RTE-cereal entrée and/or fruit), beverage only (if only milk, juice, and/or some other beverage was/were reported eaten), or no meal reported met criteria to be considered school breakfast. A school breakfast option reported eaten was further classified as correctly reported if it was the same as an option observed eaten for the respective dietary recall (regardless of whether items reported eaten were intrusions); otherwise, it was classified as misreported. In the illustration, the school breakfast option reported eaten was mixed, so it was misreported. Total inaccuracy: b This is the sum of three components for food items and item amounts: a) the sum, over matches, of the absolute difference between amounts observed and reported for each match times the weight; b) the sum, over intrusions, of each intruded amount times the weight; and c) the sum, over omissions, of each omitted amount times the weight. This measure cumulates errors (in servings) for all items and amounts for matches, omissions, and intrusions. Values close to zero indicate higher (better) accuracy; greater values indicate lower (worse) accuracy. In the illustration, total inaccuracy for this child for school breakfast and school lunch is 0.25 + 1.00 + 0.00 + 1.00 + 0.50 + 2.00 + 0.33 + 0.50 + 0.25 + 0.00 + 1.50 = 7.33 servings. Total observed amount: For energy or any nutrient, this is the sum of amounts observed eaten; this is the same as (sum of corresponding amounts from matches) + (sum of under-reported amounts from matches) + (sum of unreported amounts from omissions). In the illustration, for energy, the total observed amount for this child for school breakfast and school lunch is 80 + 100 + 125 + 40 + 230 + 10 + 25 + 150 + 140 = 900 kcal. Total reported amount: For energy or any nutrient, this is the sum of amounts reported eaten; this is the same as (sum of corresponding amounts from matches) + (sum of over-reported amounts from matches) + (sum of over-reported amounts from intrusions). In the illustration, for energy, the total reported amount for this child for school breakfast and school lunch is 60 + 125 + 80 + 80 + 50 + 113 + 140 + 250 = 898 kcal. Under-reported amount from a match: For energy or any nutrient, this is the part of the observed amount that exceeded the reported amount of a match (or zero if the observed amount was less than the reported amount of a match). In the illustration, for energy, the sum of the under-reported amounts from matches is 20 kcal (from 0.25 servings of white milk) + 37 kcal (from 0.25 serving of chocolate milk) = 57 kcal. Unreported amount from an omission: For energy or any nutrient, this is the entire observed amount of an omission. In the illustration, for energy, the sum of the unreported amounts from omissions for this child for school breakfast and school lunch is 100 kcal (from 1.00 serving of scrambled egg) + 230 kcal (from 1.00 serving of hot dog on bun) + 10 kcal (from 1.00 serving of ketchup) = 340 kcal. Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

a

Amounts observed eaten and/or amounts reported eaten of standardized school-meal portions were recorded using a qualitative scale and then assigned numeric values as none = 0.00, taste = 0.10, little bit = 0.25, half = 0.50, most = 0.75, all = 1.00, or as the actual number of servings if more than one was observed eaten and/or reported eaten. b When calculating food-item and item-amount variables for some studies, a weight was assigned to each match, omission, and intrusion according to meal component (e.g., beverage, bread/grain, breakfast meat, combination entrée, condiment, dessert, entrée, fruit, miscellaneous, vegetable) so that errors for combination entrées (or entrées in Study 2) counted the most and errors for condiments counted the least. The weights assigned varied slightly by study. Specifically, no weights were assigned for Study 1. For Study 2, the assigned weights were entrée (e.g., Salisbury steak) = 1, condiment (e.g., mustard; syrup) = 0.25, and remaining meal components = 0.75. For Studies 6, 7, 9, 10 through 14, and 16, the assigned weights were combination entrée (e.g., hamburger on bun) = 2, condiment = 0.33, and remaining meal components = 1. In the illustration in Table 1, the weights used are based on the assigned weights used for Studies 6, 7, 9, 10 through 14, and 16.

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Table 2. Overview by study for each of 26 studies summarized in this chapter

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a

b

DRV study = dietary-reporting validation study SA study = secondary analyses study NV study = non-validation study AA = African American W = White m = male f = female

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Children were recruited from public elementary schools in one district in a southern state in the USA. Schools were selected based on high participation in school meals. More children than required for a study were recruited so that final random selection of children from the recruited population could be stratified (e.g., by sex and race). As shown in Table 2, for ten of the 26 studies, children provided dietary recalls without assistance from parents — the nine dietary-reporting validation studies (Studies 1, 2, 6, 7, 10 through 13, and 15) and the one non-validation study (Study 14). However, an individual child was not interviewed for more than one of the ten studies with one exception — the 40 children interviewed for Study 15 were a subset of the 120 children who were each interviewed once, approximately three to four months earlier that same school year, for Study 14. For most of the ten studies, the sample of children interviewed was stratified by sex and race (African American, White). As shown in Table 2, children were in the fourth grade (ages nine to ten years) for all studies with the exception of Study 6, for which half of the children were in the fourth grade and half were in the first grade (ages six to seven years).

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School Meal Observations For the nine dietary-reporting validation studies and for half of the 120 children interviewed for the one non-validation study, randomly selected children were observed eating school lunch for three studies (Studies 1, 2, and 6), or school breakfast and school lunch for seven studies (Studies 7 and 10 through 15), as shown in Table 2. Because it can be difficult to unobtrusively identify contents of meals brought from home [152], only children who obtained meals provided by school foodservice were observed. The ―offer-versus-serve‖ provision [174] (which allows children to refuse some food items) was not implemented in the district‘s elementary schools; thus, most food items were served to children. Observations were conducted by trained researchers during usual school meal periods in cafeterias with children seated according to their school‘s typical arrangement. For breakfast, children sat as they arrived in the cafeteria at most schools, or by grade level at a few schools. For lunch, children sat with their classes. Children were observed for their entire meal periods (rather than merely until their trays were returned) to account for trading of food items [27,47,55,142,151]. An observer simultaneously observed one to three children and recorded, for each child, items and amounts eaten in servings of standardized school-meal portions. An observer stood by tables where groups of children sat and appeared to watch the entire group or class; thus, children could see that an observer was present, but children did not know specifically who was being observed or would be interviewed later. Each observer used a checklist form, on which items available at the observed meal were listed, and visually assessed the amount eaten of each serving. School staff and children did not know in advance the days when observations would occur. When observers were present during school meals, usually all children participating in the study at that school wore nametags so observers could identify children [60]. Alternatives to nametags for identifying children during observations (e.g., asking school staff to identify children at each meal [6], using pictures of children [47], or asking children in the study to sit at specific tables) are more reactive and/or less reliable. Prior to data collection each school year, practice observations were conducted to familiarize children with an observer‘s presence [151].

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 223 For Studies 7 and 10 through 15, interobserver reliability was assessed for training prior to data collection as well as regularly (e.g., weekly) throughout data collection to ensure that information collected did not depend on who conducted observations [2]. For each of these studies, overall agreement between observers during data collection was satisfactory (i.e., > 85%) [5,151]. A child observed for a meal for assessment of interobserver reliability was never interviewed about that meal.

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Dietary Recall Interviews For the ten studies in which children provided dietary recalls (without assistance from parents), children were interviewed individually by trained researchers who followed written protocols. Interviews were conducted in private locations, audio-recorded, and later transcribed. For three (Studies 1, 2, and 6) of the ten studies, children were interviewed in the morning (after school breakfast) or in the afternoon (after school lunch) about intake for a single school meal (lunch). Interview protocol details for each of these three studies are summarized in Table 2. For Study 2, after the school lunch recall was obtained, the child was asked to respond to how much he or she liked each item reported and/or observed eaten at school lunch. The response options were ―not at all,‖ ―a little,‖ and ―a lot.‖ For seven (Studies 7 and 10 through 15) of the ten studies, children were interviewed in the morning (after school breakfast), afternoon (after school lunch), or evening (after 6:00 p.m.) about intake for a specified target period that was either the previous day, that same day, or the prior 24 hours. For these seven studies, interviewers followed written, multiplepass protocols patterned after that of the Nutrition Data System for Research (NDSR, Nutrition Coordinating Center, University of Minnesota, Minneapolis, MN, USA) with the following four exceptions or modifications. First, during all interviews, instead of using computerized software, interviewers wrote information reported by children onto paper forms. Second, Study 10 utilized the NDSR interview protocol with forward-order (morningto-evening) prompts about meals/snacks eaten [141] and a protocol that we created based on NDSR but modified to contain reverse-order (evening-to-morning) prompts about meals/snacks eaten [33]. Third, Study 12 utilized a protocol with an open format modeled after the automated multiple-pass method of the United States Department of Agriculture (USDA) [171] and a protocol that we created based on meal name prompts. Fourth, for Studies 13 through 15, children who were interviewed about the prior 24 hours were asked to report intake for the interview day first, and then intake for the previous day, to complete the 24 hours. For seven (Studies 7 and 10 through 15) of the ten studies, quality control for interviews was assessed regularly. At least one interview per interviewer each week, or day, was randomly selected by another interviewer and checked for adherence to protocol [149]. For each of these studies, results for quality control for interviews showed that interviewers adequately followed protocols.

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Weight and Height Measurements At school on days when no observations or interviews were conducted at that particular school, weight and height of children in Studies 7 and 10 through 15 were obtained by trained researchers who used established procedures to measure children (without shoes) on digital scales and portable stadiometers [112,119]. Weight and height measurements were obtained in the afternoon (after school lunch) for Studies 7 and 10 through 12, and in the morning (after school breakfast) for Studies 13 through 15. For each child, weight and height were measured twice (back-to-back) by a researcher; if the two weight or height measurements were not within a tenth of a pound, or a quarter of an inch, respectively, then a third weight or height was measured. If three weight and/or height measurements were obtained, then the average of the closest two was used for the child‘s weight and/or height. Inter-rater reliability was assessed daily across pairs of researchers on a random 10% of children; for each of the four school years, the intraclass correlation reliability was > 0.99 for weight and > 0.99 for height. Each child‘s age, sex, height, and weight were used to determine his or her age/sex BMI percentile [43]. For Studies 7 and 10 through 14, children were interviewed irrespective of age/sex BMI percentile. For Study 15, according to the design, only children with an age/sex BMI percentile that we defined either as low BMI (≥ 5th and < 50th percentiles) or as high BMI (≥ 85th percentile) were interviewed.

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Classification of Observed and/or Reported Items and Amounts For seven (Studies 7 and 10 through 15) of the ten studies in which children provided dietary recalls for more than a single meal, although children were to report all meals and snacks eaten during the specified target period, analyses were restricted to those school meals that had been observed. For these seven studies and for the secondary analyses studies that utilized data from one or more of these seven studies, meals in these children‘s recalls were treated as referring to school meals if children identified school as the location where meals were eaten, referred to breakfast as breakfast or school breakfast, referred to lunch as lunch or school lunch, and reported mealtimes to within an hour of observed mealtimes. For Studies 1, 2, and 6, children were interviewed about school lunch on a specific day at school; thus, questions about location, meal name, and mealtime were not asked. To assess reporting accuracy for the nine dietary-reporting validation studies and for the secondary analyses studies that utilized data from one or more of these nine validation studies, each item observed eaten for a school meal was classified as a match if it was reported eaten (in any non-zero amount) by the child for that school meal; otherwise, it was classified as an omission. Each item reported eaten for a school meal was classified as a match if it had been observed eaten (in any non-zero amount) by the child at that school meal; otherwise, it was classified as an intrusion. Because children can report foods many ways, items reported eaten were classified as matches unless it was clear that children‘s reports did not describe items observed eaten. For example, matches included all kinds of white milk (e.g., skim milk observed, whole milk reported) and all types of pizza (e.g., cheese pizza observed, sausage pizza reported). Intrusions included fruit juices (e.g., orange juice observed, grape juice reported), milk flavors (e.g., white milk observed, strawberry milk

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reported), ready-to-eat [RTE] cereal (e.g., flake-shaped RTE cereal observed, doughnutshaped RTE cereal reported), and vegetables (e.g., corn observed, green beans reported). For the school breakfast illustrated in Table 1, the child was observed to have eaten non-zero amounts of white milk, scrambled egg, biscuit, and applesauce, and the child later reported to have eaten non-zero amounts of white milk, biscuit, Cheerios cereal, and applesauce. Thus, white milk, biscuit, and applesauce were matches, scrambled egg was an omission, and Cheerios cereal was an intrusion. For several studies, a weight was assigned to each match, omission, and intrusion according to meal component (e.g., beverage, bread/grain, breakfast meat, combination entrée, condiment, dessert, entrée, fruit, miscellaneous, vegetable) so that errors for combination entrées (or entrées in Study 2) counted the most and errors for condiments counted the least. The weights assigned varied slightly by study. Specifically, no weights were assigned for Study 1. For Study 2, the assigned weights were entrée (e.g., Salisbury steak) = 1, condiment (e.g., mustard; syrup) = 0.25, and remaining meal components = 0.75. For Studies 6, 7, 9, 10 through 14, and 16, the assigned weights were combination entrée (e.g., hamburger on bun) = 2, condiment = 0.33, and remaining meal components = 1. Amounts observed eaten and/or amounts reported eaten of standardized school-meal portions were recorded using a qualitative scale and then assigned numeric values as none = 0.00, taste = 0.10, little bit = 0.25, half = 0.50, most = 0.75, all = 1.00, or as the actual number of servings if more than one was observed eaten and/or reported eaten. For secondary analyses for six studies (Studies 14 through 19), for each item observed eaten, and/or for each item reported eaten, standardized school-meal portions were used to obtain per-serving information about energy and macronutrients (protein, carbohydrate, fat) from the NDSR database; for items not in the NDSR database, energy and macronutrient information was obtained from the school district‘s nutrition program. Although the portionsize estimates may have been imprecise, the same approach was used to estimate energy and macronutrients for observed items and for reported items.

Retrieval Response Categories For three studies (Studies 1, 3, and 4), children were asked how they remembered the specific items they reported as eaten at school lunch. For Study 1, responses were categorized into retrieval response categories according to written protocols. For Study 3, a Delphi technique study was conducted with ten psychologists to develop and categorize a consensus set of retrieval response categories. For Study 4, the retrieval response categories identified in Study 3 were used. Examples of retrieval response categories included usual practice (e.g., ―We always have milk‖), added to something (―I ate it with my salad‖), taste/smell/texture (e.g., ―It stunk‖), and second helping/mode of eating (e.g., ―I asked for some more‖).

Types of Intrusion For three studies (Studies 23 through 25), each intrusion was categorized by type as either a stretch (on the child‘s tray for that school meal) or a confabulation (not on the child‘s tray for that school meal). For Studies 24 and 25, each confabulation was further categorized

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as either an internal confabulation (in the school foodservice environment but not on the child‘s tray for that school meal) or an external confabulation (not in the school foodservice environment). For the school lunch illustrated in Table 1, suppose that the items on the child‘s tray were hot dog on bun, ketchup, green beans, chocolate milk, and vanilla ice cream. As shown in Table 1, the child was observed to have eaten non-zero amounts of hot dog on bun, ketchup, green beans, chocolate milk, and vanilla ice cream, and the child later reported to have eaten non-zero amounts of spaghetti, green beans, chocolate milk, and vanilla ice cream. Spaghetti is an intrusion. Furthermore, spaghetti would be an internal confabulation if it was in the school foodservice environment for that meal but not on the child‘s tray for that meal; however, spaghetti would be an external confabulation if it was not in the school foodservice environment for that meal. Although not shown in Table 1, suppose that an orange was also on the child‘s tray for school lunch, but was not observed eaten. If the child had reported that a non-zero amount of the orange was eaten, then the orange would be an intrusion; furthermore, the orange would be a stretch because it was on the child‘s tray for that meal.

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Availability of Food Items in School Foodservice Environments For each of five secondary analyses studies (Studies 20 through 22, 24, and 25) concerning origins (or sources) of intrusions and/or types of intrusion, a catalog was created of items available in school foodservice environments for specific meals. The majority of the items in each catalog were identified from production records completed by school foodservice managers (in compliance with federal school meal regulations) to document availability of items at each school meal. Other items in each catalog were added because the items were observed during specific school meals. A few items (usually condiments) were assumed available for specific unobserved meals. (For example, if hamburgers were on a school‘s production record for a specific lunch, but ketchup and mustard were not, then ketchup and mustard were assumed available and added to the catalog for that lunch.) Because RTE cereal, milk, and juice were usually listed in general terms on production records for breakfast, all kinds/flavors of these items were considered available daily for breakfast. Likewise, because milk was usually listed in general terms on production records for lunch, all kinds/flavors of milk were considered available daily for lunch. Although ice cream was never listed on production records, various kinds were considered available daily for lunch because observers noted that various kinds of ice cream were sold à la carte during lunch at most schools on most days. For these five secondary analyses studies, for each intrusion, the availability catalog and/or observation form were checked to determine availability for items denoted by intrusions, or by types of intrusion (stretch, internal confabulation, external confabulation), in the child‘s school foodservice environment for each meal and/or day of interest.

Analytic Variables Table 1 illustrates and defines food-item variables and item-amount variables. Food-item variables (calculated per interview except for Study 16 when calculated for school breakfast

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 227 and school lunch separately) included number of items observed eaten, number of items reported eaten, omission rate, and/or intrusion rate. When results are summarized in Table 2, match rate is sometimes mentioned as the complement of omission rate because omission rate + match rate = 100%. Lower values for omission rate and intrusion rate indicate higher (better) reporting accuracy. Item-amount variables (calculated per interview) included arithmetic amount difference per match, absolute amount difference per match, amount per omission, and amount per intrusion. For arithmetic amount difference per match, values close to zero are interpreted as indicating higher (better) reporting accuracy; however, under- and over-reported amounts can offset each other, so averages that appear accurate may disguise considerable error balanced over the two directions. Absolute amount difference per match indicated the magnitude of error, but not whether under- or over-reporting occurred. For absolute amount difference per match, amount per omission, and amount per intrusion, values close to zero indicate higher (better) reporting accuracy. For most studies, food-item variables and item-amount variables were calculated after assigning a weight to each item according to meal component, as explained previously and in footnote b of Table 1. For eight studies (Studies 6, 7, 9 through 13, and 16), a single variable of total inaccuracy (calculated per interview except for Study 16 when school breakfast and school lunch were calculated separately) combined errors for items and amounts (as illustrated and defined in Table 1). Lower values indicate higher (better) reporting accuracy. This measure provides a composite reporting accuracy score for both food items and amounts, but it does not indicate whether errors are due to omissions, intrusions, or incorrect amounts for matches. For Study 15 only, kilocalorie variables (calculated per interview) included observed kilocalories, reported kilocalories, matched kilocalories, omitted kilocalories, and intruded kilocalories (as illustrated and defined in Table 1). Higher values for matched kilocalories, and lower values for omitted kilocalories and intruded kilocalories, indicate higher (better) reporting accuracy. For Studies 16 through 19, variables for energy and each macronutrient (calculated per interview except for Study 16 when school breakfast and school lunch were calculated separately) included observed amount, reported amount, report rate, correspondence rate, and inflation ratio (as illustrated and defined in Table 1). Higher values for correspondence rate, and lower values for inflation ratio, indicate higher (better) reporting accuracy. Conventional interpretation of report rates is that values close to 100%, greater than 100%, and less than 100% indicate high reporting accuracy, over-reporting, and under-reporting, respectively.

SUMMARY OF RESULTS AND DISCUSSION Cognitive Burden of Recall Study 1 [56] found that most children could articulate how they remembered food items eaten at school lunch; however, after prompted report, accuracy of lunch-only recalls was better for more children with the nonintegrated interview style (for which children verbalized how they remembered after they had reported everything eaten) than with the integrated style (for which children verbalized how they remembered at the same time they reported eating

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each item). This suggests that accuracy was hampered with the integrated interview style. Thus, to avoid imposing too heavy a cognitive burden, the timing of instructions, cues, or prompts is important. For example, the cognitive burden for a child is lighter when asked to recall what was eaten yesterday rather than when asked to recall what fruits were eaten yesterday because in the latter, the child must first categorize what was eaten yesterday to identify fruits so that fruits can be recalled. In Study 8 [24], analyses of omission rates and intrusion rates showed that accuracy was better overall and for every meal component for single-meal recalls (i.e., only school lunch) compared to school lunch abstracted from 24hDRs. Specifically, during lunch-only recalls, children omitted (failed to report) 37% of school lunch items they were observed to have eaten; during 24hDRs, children omitted 55% of school lunch items they were observed to have eaten. Similarly, during lunch-only recalls, of items children reported eating at school lunch, 15% was intruded (not observed eaten); during 24hDRs, of items children reported eating at school lunch, 34% was intruded. Thus, the cognitive burden of recalling food items eaten at school lunch in the context of a 24hDR appears to be greater than that of recalling food items eaten at school lunch in a lunch-only recall. The negative impact on children‘s recall accuracy of a heavier cognitive burden is an important consideration when comparing results across studies.

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Retrieval Response Categories A large variety of retrieval response categories was used by children when accurately recalling school lunch within 90 minutes of eating in Study 3 [28] and the next morning in Study 4 [25]; however, many of the same retrieval response categories were used by children when inaccurately recalling school lunch. An obvious limitation is that there is no way of knowing whether how a child responded to the question, “How do you remember you ate___,” was actually how the child remembered that item. Results from Study 3 [28] and Study 4 [25] suggest that focusing on how children remember what they have eaten will probably not be very helpful in the quest to develop prompts or strategies to enhance the accuracy of children‘s dietary recalls.

Salient Role of Entrée Study 5 [30] found that entrée played a salient role in the accuracy of children‘s lunchonly recalls. Specifically, recalling a school lunch entrée correctly had a keystone effect on the accuracy of children‘s school lunch recalls obtained the next morning by decreasing the occurrence of intrusions. For Studies 20 [13] and 26 [12], if RTE cereal is a breakfast entrée, ―linking‖ (i.e., the occurrence of multiple intrusions) was evident in school breakfast reports obtained during 24hDRs. This linking was especially evident when a cold option with an entrée of RTE cereal was misreported when a hot option with a non-RTE-cereal entrée had been observed eaten.

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 229

Salient Role of Liking for Foods Study 5 [30] also found that liking for foods played a salient role in the accuracy of children‘s lunch-only recalls. Specifically, foods liked ―a lot‖ had higher match rates (and thus lower omission rates) for lunch recalls obtained the next morning, and lower intrusion rates for lunch recalls obtained within 90 minutes of eating and the next morning, compared to foods ―not liked a lot.‖ However, when three types of specific prompting methods – preferences, food category, and visual – were compared in Study 6 [26], there was no difference in total inaccuracy (as a single measure of accuracy). In Study 23 [15], liking ratings were higher for matches than stretches (a type of intrusion), for confabulations (another type of intrusion) than stretches, and for matches than omissions, but did not vary by retention interval — the time that elapses between when the to-be-reported meal(s) happen(s) and the interview occurs — or reporting-order prompts.

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Differences by Grade Level and Specific Prompting Methods Only one study summarized in this chapter included children from more than a single grade level. In Study 6 [26], accuracy of school-lunch recalls by first graders was less than that of fourth graders. Interviews in Study 6 [26] included free recall, non-suggestive prompted recall, and specific prompted recall (as shown in Table 2). Among first graders, specific prompting slightly increased recall accuracy for a few children, but decreased recall accuracy to a greater extent for more children; thus, caution is recommended when prompting first-grade children. Among fourth graders, food category prompting slightly improved recall accuracy, but only among half of the children who received it. Although analyses concerned recall accuracy from before to after specific prompting, it was noted that during the nonsuggestive prompted phase, some children did recant items that had been intruded during free recall. Specifically, these were items for which children failed to report amounts eaten during free recall; during non-suggestive prompted recall, when asked how much of the items they had eaten, children reported that they had the items, but had not eaten them. This suggests that asking children about amounts eaten of each item reported in lunch-only recalls has an important role in decreasing the occurrence of intrusions.

Consistency of Children’s Recall Accuracy Study 7 [31] appears to be the only published validation study concerning the consistency of children‘s dietary recall accuracy over multiple recalls. Study 7 [31] found that according to the measure of total inaccuracy, children‘s accuracy improved between the first and third recall. However, intraclass correlation coefficients were low for omission rate and total inaccuracy, indicating that consistency of accuracy from one recall to the next for an individual child was poor; in other words, individual children were inconsistent in accuracy for food items from one recall to the next.

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Accuracy for Recalling Amounts Eaten Several studies summarized in this chapter found that when children recalled the correct food items (matches), amounts recalled eaten were fairly accurate in terms of servings (i.e., approximately –0.08 and 0.24 serving for arithmetic and absolute amount differences per match, respectively). This was true whether children were recalling an entire day‘s intake (Studies 7, 10, and 11 [31-33]), or only school lunch as a single meal (Study 2 [29]). However, when children omitted (i.e., forgot) food items, the average amount per omission was almost a full serving (Studies 7, 10, and 11 [31-33]); this indicates that omissions were generally not food items for which children had eaten only small amounts. Likewise, when children intruded (i.e., falsely reported) food items, the average amount per intrusion was almost a full serving (Studies 7, 10, and 11 [31-33]); this indicates that intrusions generally were food items for which children falsely claimed to have eaten almost a full serving. Collectively, these results suggest that efforts to improve children‘s recall accuracy should focus first on helping children recall the correct food items (because amounts are fairly accurate for matches, while amounts for omissions and intrusions are almost full servings).

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Interview Modality (In Person Versus by Telephone) Study 11 [32] found that when children were interviewed in the evening about that day‘s intake, accuracy for food items did not differ significantly between in-person versus telephone recalls. This is important because of the potential savings in travel time (for both subjects and investigators) and transportation costs with telephone interviews. Furthermore, this result is beneficial for future studies because it would allow both interview modalities to be used in a single study (e.g., in-person recalls at school in the morning and afternoon; telephone recalls in the evening) without jeopardizing the ability to compare children‘s recall accuracy across retention intervals.

Forward- Versus Reverse-Order Prompts Research on autobiographical memory [94,95,109-111,188] and eyewitness testimony [74-76] has indicated that reporting accuracy may depend on order prompts (i.e., the temporal order in which subjects are instructed and prompted to report the events of a target period), and has provided insight as to why. Reverse- (i.e., most recent to past) order prompts may enhance reporting accuracy because recent events are likely to be easier to remember and may stimulate recall of earlier events; forward- (i.e., past to most recent) order prompts may enhance reporting accuracy because this is the sequence in which the events occurred and recall of earlier events could guide the recall of subsequent events; and open- (i.e., free [no instructions]) order prompts may enhance reporting accuracy because advantages of both reverse- and forward-order prompts are available and no order is imposed initially [95,110,188]. Some research on autobiographical memory [95,111] and eyewitness testimony [74] has indicated that the number of intrusions and intrusion rates may be smaller with reverse- than forward-order prompts.

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 231 There are two prominent protocols used to obtain 24hDRs. One of these is NDSR developed for research studies [52,127,141]; the other is the automated multiple-pass method developed by the USDA for national surveys [34,57,140,171]. Of these two prominently used 24hDR protocols, NDSR [141] utilizes forward-order prompts and USDA‘s automated multiple-pass method [34,140,171] utilizes open-order prompts. Study 10 [33] appears to be the only published validation study concerning forwardversus reverse-order prompts and children‘s dietary recall accuracy. Study 10 [33] found that recalling the previous day‘s intake in morning interviews with reverse-order prompts as opposed to forward-order prompts improved omission rates and intrusion rates for boys more so than for girls; however, overall accuracy for recalling food items was poor. Although the significant order-x-sex interaction in Study 10 [33] was not anticipated, it was similar to results of Jobe and colleagues [95], who found that recall of medical visits was better with reverse- than with forward- or open-order prompts for men, but open-order prompts were better for women than forward- or reverse-order prompts. If order prompts influence 24hDR accuracy differently for girls and boys, then this would have implications for the manner in which girls and boys should be prompted to report their meals and snacks for 24hDRs in future studies. Because all 24hDR protocols prompt subjects to report meals and snacks (usually in forward order or in open order), it could be relatively simple and important to alter 24hDR protocols to use the specific order prompts that produce the most accurate recalls for that sex.

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Meal Name Prompts Because dietary intake may be organized in memory according to meals [68,81,105,117], there has been speculation that meal name prompts may enhance recall accuracy. Study 12 [18] found that although more items were reported eaten with meal interview format (i.e., meal name prompts) than open interview format (i.e., free [no instructions]), accuracy was better with open format interviews than with meal format interviews for two measures – intrusion rates and total inaccuracy. Previously, in a validation study by Mack and colleagues [117], 27 children ages six to 11 years were each observed eating a meal or snack at daycare and then interviewed using one of four prompting formats (open; meal; location; USDA Day One questionnaire in the 1989-91 Continuing Survey of Food Intakes by Individuals). The percentage of items matched (items observed eaten and reported eaten) was lowest for meal (30%) and similar for the other three formats (57% for open, 58% for location, and 50% for USDA Day One). However, intrusions were not investigated in the study by Mack and colleagues. Results from Study 12 [18] highlight two crucial aspects for future dietary-reporting validation studies. First, it is important to measure both aspects of item recall error – omission rates and intrusion rates – because each is an essential yet different component of recall accuracy. Second, it is important to validate recalls because simply relying on differences in the numbers of food items reported eaten without knowing the truth about intake provides no information about the accuracy of those reported items. If Study 12 [18] had not included a validation method, the result that more items were reported with meal format than open format would have been interpreted as meal format yielding ―better‖ recalls due to less underreporting. However, the validation method of observation of school meals in Study 12 [18]

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allowed the classification of each reported item as a match or intrusion; this lead to the result that accuracy was better with open format than meal format interviews because open format interviews had fewer intrusions than meal format interviews. Specifically, with open format interviews, one-third of the children intruded at least one item, but with meal format interviews, over four-fifths of the children intruded at least one item.

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Retention Interval For a 24hDR, two possible target periods are the prior 24 hours (the 24 hours immediately preceding the interview) and the previous day (midnight to midnight of the day before the interview). For each of these target periods, the interview time might be any time of day (e.g., morning, afternoon, or evening). The combination of target period and interview time defines the retention interval. The retention interval, along with intervening meals, can influence recall accuracy. Generally, as the retention interval increases, accuracy decreases, so the sooner something is recalled, the more accurate the report is [49,94]. For a recall targeting the prior 24 hours, the end of the 24 hours coincides with the beginning of the interview, and no meals intervene between the to-be-reported meals and the interview. For a recall targeting the previous day, as the interview is held later in the day, the length of the retention interval increases as does the number of intervening meals. Both prominent protocols used to obtain 24hDRs (NDSR and USDA‘s automated multiple-pass method) concern the previous-day target period [18,141,171]. The importance of retention interval on children‘s dietary recall accuracy is evident across and within several studies summarized in this chapter. In Studies 7 [31] and 10 [33], when interviewed in the morning about the previous-day‘s intake, on average, children failed to recall one-half of the items observed eaten at school meals; furthermore, one-third of the items recalled had not been observed eaten. In contrast, in Study 11 [32], when interviewed in the evening about that day‘s intake, on average, children failed to recall one-third of the items observed eaten at school meals; furthermore, one-fifth of the items recalled had not been observed eaten. In Study 2 [29], analyses of omission rates and intrusion rates showed that children‘s accuracy was better for lunch-only recalls obtained within 90 minutes of eating than the next morning, and the next morning than three mornings later. In Study 13 [22], analyses of omission rates, intrusion rates, and total inaccuracy showed that whether children were interviewed in the morning, afternoon, or evening, accuracy was better for prior-24-hour recalls than previous-day recalls. Also, in Study 13 [22], analyses of omission rates showed that children‘s accuracy was best for prior-24-hour recalls obtained in the afternoon and worst for previous-day recalls obtained in the afternoon. In Study 15 [21], analyses of omitted kilocalories and intruded kilocalories showed that children‘s accuracy was marginally better for prior-24-hour recalls obtained in the evening than previous-day recalls obtained in the morning. Results concerning retention interval from a large dietary-reporting validation study with fourth-grade children (similar in design to Study 13 [22]) will soon be available in an article by Baxter and colleagues.

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 233

Recall Accuracy for School Breakfast Versus School Lunch

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Secondary analyses studies summarized in this chapter provide evidence of differences in children‘s accuracy for recalling school breakfast and school lunch during 24hDRs. Specifically, secondary analyses in Study 16 [17] found that children recalled school breakfast intake (in terms of both food items and kilocalories) less accurately than school lunch intake. Secondary analyses in Studies 20 [13] and 26 [12] found asymmetry in children‘s misreports of school breakfast: Specifically, children observed eating a cold breakfast (i.e., RTE cereal) almost never misreported having eaten a hot breakfast (i.e., nonRTE-cereal entrée), but children observed eating a hot breakfast often misreported having eaten a cold breakfast. Thus, children reported eating RTE cereal at more school breakfasts than were observed. These findings are important for several reasons. Research has shown that breakfast consumption plays an important role in children‘s health and well-being, and is associated with improved nutritional adequacy, more healthful body weight, and benefits to cognitive function (particularly memory), academic performance, school attendance, psychosocial function, and mood [139]. Consumption of RTE cereal, which is common among American children, especially at breakfast [1,128], has been associated with improved nutrient intake (e.g., less fat, more fiber, more minerals) and more healthful body weight [1,11,128,146]. In the USA, millions of children eat breakfast at school; RTE cereal is commonly available at school breakfast [80]. For breakfast each school day, many elementary schools offer a choice between a cold option that includes RTE cereal and a hot option that includes a non-RTE-cereal entrée such as a sausage biscuit [73]. The asymmetry found in misreported breakfast options in secondary analyses in Studies 20 [13] and 26 [12] usually was an incorrect report that a cold option (RTE cereal) was eaten. These misreports undoubtedly have implications for nutrient profiles of children‘s reported intake at school breakfast. In turn, this might lead to different conclusions about the extent of benefits commonly attributed to eating school breakfast, and especially RTE cereal [12].

Children’s BMI and Dietary Recall Accuracy Studies with adults (especially women) have found that energy under-reporting increased as BMI increased [36,37,91,97,98,103,138,181]. Some studies with children ages six to 11 years have found a relationship between dietary reporting accuracy and BMI [21,23,65,118,136] while other studies have not [3,44,99,131]. Two validation studies summarized in this chapter provided evidence that the accuracy of children‘s dietary recalls was related to their age/sex BMI percentile. In Study 9 [23], secondary analyses found that over three recalls, accuracy for items varied according to children‘s age/sex BMI category – accuracy improved for healthy-weight children, improved and then stabilized for children at risk of overweight, but deteriorated and then stabilized for overweight children. These results are especially pertinent considering the current attention given to the increased prevalence of obesity among children and because many studies require individual children to complete multiple 24hDRs (for example, to assess the relative validity of FFQs [51,64,93,144] or to evaluate the effectiveness of nutrition interventions [45]). It should not be assumed that recall accuracy is invariant over trials and independent of BMI category in studies in which multiple 24hDRs are obtained from children.

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In Study 15 [21], high-BMI children omitted more kilocalories than low-BMI children. Furthermore, intruded kilocalories were lower (better) for high-BMI girls than high-BMI boys, but higher (worse) for low-BMI girls than low-BMI boys. No effects were found for reported kilocalories or matched kilocalories. Studies 9 [23] and 15 [21] strictly reflected children‟s recall accuracy (without parental help). When parents help children recall their intake, or when parents provide recalls for children, it is impossible to determine the extent to which dietary recall errors are related to children‟s characteristics such as BMI. The results concerning children‘s recall accuracy and BMI emphasize the need for future validation studies to ensure that parents do not help children during recalls.

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Social Desirability A personality characteristic on which individuals vary systematically is the tendency to respond in a socially desirable way — never reporting behaviors that most people perform at least occasionally (e.g., gossiping), or always reporting behaviors that most people perform usually but omit occasionally (e.g., admitting mistakes). Individuals who respond in a socially desirable way may systematically err in responding to a variety of questions, including questions about dietary intake; thus, social desirability is an example of a response bias [135]. Crandall and colleagues [46] used the Marlowe-Crowne Social Desirability scale for adults [48,50] to develop two versions of the Children‘s Social Desirability (CSD) scale, one version for grades three to five and another version for grades six to 12 [164]. Reliability was evaluated with 956 children in grades three to 12 (with 110 children in each of grades three, four, and five). Spearman-Brown-corrected split-half reliabilities ranged from 0.82 to 0.95 for children at various grade levels, and one-month test-retest reliability was 0.90 for 63 younger children and 0.85 for 98 tenth graders [46]. Social desirability may be related to reports of dietary intake in general and to reporting error in particular. For example, many foods are regarded as good or bad [4,85,102,182,190], so a respondent who answers in a socially desirable way might under-report intake of bad foods and over-report intake of good foods [85,182,190]. Studies of adults‘ dietary reporting accuracy have found a negative association with social desirability, particularly for women [86-89,166]. Researchers who use children‘s dietary reports have indicated concern about social desirability [33,54,65,107], and it has been recommended that social desirability be assessed in studies for which children self-report dietary intake [108]. Study 15 [21] appears to be the only validation study that has examined social desirability and children‟s dietary recall accuracy. After providing the 24hDR, each child completed 20 items [82] from the CSD 46-item scale [46]. Although social desirability was assessed in Study 15 [21], results were not discussed in that publication because social desirability was not a significant covariate for any accuracy variable concerning kilocalories. However, secondary analyses in Study 24 [82] found that social desirability was associated with intrusions for school lunch, and it interacted with BMI-group (low; high) and sex for amounts reported eaten of intrusions for school breakfast. To better understand the role of children‘s social desirability and children‘s dietary recall accuracy, validation studies are needed in which children provide recalls without assistance from parents.

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 235

Conventional Versus Reporting-Error-Sensitive Analytic Methods Studies 17 through 19 [19,20,157] consisted of secondary analyses of validation study data to compare two approaches (and their respective variables) for analyzing energy and macronutrients in dietary-reporting validation studies. The conventional approach disregards accuracy of reported items and reported amounts by transforming reference information, and reported information, to energy (kilocalories) and macronutrients for each subject, and then calculating report rate for energy and each macronutrient. The reporting-error-sensitive approach classifies reported items as matches or intrusions, and reported amounts as corresponding or over-reported, before calculating correspondence rate and inflation ratio for energy and each macronutrient. As shown in Table 1, the conventional report rate is a sum of the correspondence rate (a genuine measure of reporting accuracy) and the inflation ratio (a measure of reporting error). Secondary analyses in Studies 17 through 19 [19,20,157] found that conventional report rates for energy and each macronutrient overestimated reporting accuracy and masked the complexity of reporting errors. Specifically, in Studies 17 through 19 [19,20,157], correspondence rates were lower than report rates, indicating that reporting accuracy was overestimated by conventional report rates. Also, in Study 17 [19], conventional report rates did not detect improvement in accuracy over multiple recalls that were evident with the reporting-error-sensitive variables of correspondence rates and inflation ratios. In Study 18 [20], conventional report rates did not detect sex differences with order prompts that were evident with the reporting-error-sensitive variables of correspondence rates and inflation ratios. In Study 19 [157], inflation ratios differed significantly from zero.

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Using Observation of School Meals to Validate Children’s Dietary Recall Accuracy During data collection for numerous validation studies summarized in this chapter, adequate agreement between observers in the assessment of interobserver reliability was demonstrated. Specifically, throughout data collection for Studies 7 [31] and 10 through 15 [18,21,22,32,33,156], interobserver reliability was assessed regularly and overall agreement between observers was > 85%, which is considered satisfactory [5,151]. Thus, numerous studies have established the use of school-meal observations to validate children‘s dietary recall accuracy. Furthermore, research supports the generalizability of using observation of school meal(s) as the validation method to assess the accuracy of children‘s dietary recalls. In a study by Baranowski and colleagues [6], fourth-grade children were or were not observed eating school lunch, and provided two 24hDRs collected back-to-back (one with child-operated software; one with a dietitian-administered interview). Baranowski and colleagues [6], who defined ―intrusions‖ as items reported in child-operated software interviews but not dietitianadministered interviews, found that observed children had fewer intrusions than unobserved children, and concluded that being observed decreased reports of uneaten foods. However, Smith and colleagues [156] noted that in the study by Baranowski and colleagues [6], children‘s observation status was partially confounded with a bogus pipeline manipulation intended to enhance recall accuracy. The assessment by Smith and colleagues [156] of the

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unconfounded observation-status effect showed a non-significant difference in intrusions between observed and unobserved children. Furthermore, completing back-to-back 24hDRs is similar to completing multiple interview passes in two prominently used 24hDR protocols (NDSR and USDA‘s automated multiple-pass method). Multiple passes provide respondents with numerous opportunities to report additional foods, so obtaining back-to-back 24hDRs from children may have had implications for items defined as ―intrusions‖ in the study by Baranowski and colleagues [6]. Results from Study 14 [156] suggested that school meal observations did not affect fourth-grade children‘s dietary recalls. These results suggest, but do not guarantee (because the small sample prohibited equivalence testing), that conclusions about dietary recalls by children observed eating school meals in validation studies may be generalized to dietary recalls by comparable but unobserved children in non-validation studies (such as national surveys, epidemiologic studies, and nutrition interventions). This is important because the goal of validation studies is to generalize conclusions to subjects in non-validation studies for whom reference information is not collected. Results from equivalence testing in a large trial that investigated whether school-meal observations influenced fourth-grade children‘s 24hDRs (similar in design to Study 14 [156]) will soon be available in an article by Baxter and colleagues.

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Origins (or Sources) of Intrusions and Types of Intrusion Understanding the origins of intrusions may facilitate the development and/or refinement of interview methods to decrease the occurrence of intrusions. According to the source monitoring perspective [96,123], various sources of information must be differentiated to accurately report one‘s intake. Concerning the school meal parts of children‘s 24hDRs, these sources of information include (a) items on a child‘s meal tray at school but not eaten, (b) items available in a child‘s school foodservice environment at that meal but not on the child‘s meal tray, and (c) all other items such as those from other school meals (on previous school days) and from non-school meals. Intrusions occur when a child fails to differentiate between these sources. Dietary-reporting validation studies that utilize school meal observations, along with production records completed by school foodservice managers to document availability of items at each school meal, provide excellent opportunities to systematically investigate the origins of intrusions in school meals in children‘s 24hDRs. Studies 20 through 25 [13-16,82,158] consisted of secondary analyses of data to investigate and thus better understand the origins of intrusions, and/or types of intrusion, in the school meal parts of children‘s 24hDRs. School foodservice production records were used in five of these six secondary analyses studies. Studies 20 [13] and 21 [14] found that intrusions that occurred in school lunch in children‘s 24hDRs were denoted by (or referred to) items that, for each day (that week) closer in time before the interview day, were 1.22 to 1.31 times more likely to have been available in the child‘s foodservice environment at school lunch. In Study 20 [13], exploratory analyses concerning school breakfast found a profound asymmetry in misreports of school breakfast: Children observed eating a cold option (with RTE cereal) almost always reported a cold option, but children observed eating a hot option (with a non-RTE-cereal entrée) reported a cold option in approximately 50% of interviews. Results from Studies 20 [13] and 21 [14] are

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 237 consistent with the idea that confusion of episodic memories (e.g., temporal dating errors) contributed to intrusions in school lunch in children‘s 24hDRs. Results from Study 20 [13] are consistent with the idea that generic dietary information (e.g., cold option items available daily) or confusion of episodic memories may have contributed to intrusions in school breakfast in children‘s 24hDRs. Study 22 [158] found that intrusions that occurred in school meals in children‘s 24hDRs were denoted by items that, for each day (that week) up to and including the interview day, were 1.71 times more likely to have been available in the child‘s foodservice environment at school meals. Also, for the subset of children who reported at least one intrusion, the mean number of intrusions (controlling for the number of items reported eaten) increased with the number of days between the interview day and the last previous non-school day. The results implicate specific memories from periods that are temporally close to (and including) the target period as sources of intrusions in school meals in children‘s dietary recalls, but does not preclude intrusions that originate in general dietary knowledge. Study 23 [15] found that both the occurrence of intrusions and types of intrusion were related to retention interval. As the retention interval increased (from same-day recalls obtained in the evening to previous-day recalls obtained in the morning), the likelihood that a reported item was an intrusion increased 1.92 to 3.33 times, the likelihood that a reported item was a confabulation (not on the child‘s tray for that school meal) increased 2.55 to 4.53 times, and the likelihood that an intrusion was a confabulation increased 2.58 to 3.55 times. The likelihood that a reported item was a stretch (on the child‘s tray for that school meal) did not vary over retention intervals. Results concerning reporting-order prompts were inconclusive. Liking ratings (which were higher for matches than stretches, for confabulations than stretches, and for matches than omissions) did not vary by retention interval or reportingorder prompts. Results from crossmeal examinations suggested that confusing items eaten across school meals, and confusing items available but uneaten across school meals, were not major sources of children‘s intrusions in reports of school meals. In other words, intrusions that occurred during reports of school breakfast were not likely to refer to items observed eaten at school lunch, and vice versa. For Study 24 [82], results revealed several significant effects of the BMI-group-x-sex interaction, interview protocol (which corresponded to retention interval in Study 24), sex, race, social desirability, and the BMI-group-x-sex-x-social desirability interaction on intrusions in the school meal parts of children‘s 24hDRs (see Table 2). As the retention interval increased (from prior-24-hour recalls obtained in the evening to previous-day recalls obtained in the morning), both reported items and intrusions were less likely to be stretches (for school lunch). Additional dietary-reporting validation studies with larger samples of children by BMI-group, sex, and race are needed to replicate these findings and to help develop methods to limit intrusions in children‘s dietary recalls. For Study 25 [16], for school breakfast, compared to previous-day recalls, reported items for prior-24-hour recalls were approximately one-fourth to one-third as likely to be intrusions, internal confabulations (in the school foodservice environment but not on the child‘s tray for that school meal), and external confabulations (not in the school foodservice environment), and intrusions were approximately five times as likely to be stretches. For school lunch, for prior-24-hour recalls obtained in the afternoon versus the other five conditions, reported items were one-twentieth and one-fiftieth as likely to be intrusions and external confabulations, respectively.

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Findings that were not anticipated in Studies 24 [82] and 25 [16] concerned differences in amounts reported eaten by types of intrusion. In both studies, for school breakfast, amounts reported eaten were smaller for stretches than internal confabulations and external confabulations. For school lunch, amounts reported eaten were smaller for stretches than external confabulations in Study 24 [82], and for stretches than internal confabulations in Study 25 [16]. Because stretches accounted for a larger percentage of intrusions in recalls with shorter retention intervals (i.e., for prior-24-hour recalls obtained in the evening than previous-day recalls obtained in the morning for Study 24 [82]; for prior-24-hour recalls than previous-day recalls in Study 25 [16]), these findings concerning amounts reported eaten being smaller for stretches than other types of intrusion have implications for nutrient profiles calculated from 24hDRs provided by children.

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Intrusions in School Breakfast Reports Secondary analyses of data from five studies were conducted in Study 26 [12] to investigate intrusions in school breakfast reports because Study 16 [17] found that children were less accurate in recalling school breakfast than school lunch, and Study 20 [13] found a profound asymmetry in misreports of school breakfast options (i.e., children observed eating a cold option almost always reported a cold option, but children observed eating a hot option misreported eating a cold option in approximately 50% of interviews). A school breakfast option reported eaten was classified as correctly reported if it was the same as an option observed eaten for the respective dietary recall (regardless of whether items reported eaten were intrusions); otherwise, it was classified as misreported. Study 26 [12] found that although intrusions occurred in both correctly reported and misreported school breakfast options, on average, there were more than twice as many intrusions per breakfast report for misreported school breakfast options than correctly reported breakfast options. Furthermore, proportionately more school breakfast reports were intrusion-free when a school breakfast option was correctly reported than misreported. Linking of intrusions (i.e., multiple intrusions from the same option in a school breakfast report) was especially evident with misreported options. Asymmetry was evident in misreported options; specifically, children observed eating a cold option almost never misreported eating a hot option, but children observed eating a hot option often misreported eating a cold option. Beverage intrusions, bread/grain intrusions, misreported breakfast options, and intrusions in misreported breakfast options, all tended to be more likely with longer retention intervals. Concerning interview format, a reported item was less likely to be a beverage intrusion in school breakfast reports for open than meal format interviews. Misreported school breakfast options were usually incorrect reports of a cold option (i.e., RTE cereal) when a hot option was observed eaten. Such school breakfast misreports undoubtedly have implications for nutrient profiles of reported intake at school breakfast; this might lead to different conclusions about benefits commonly attributed to eating school breakfast and especially RTE cereal.

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 239

CONCLUSION

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Recommendations for Dietary-Reporting Validation Studies to Fill Research Gaps The methodological validation studies summarized in this chapter provide valuable insight concerning errors in children‘s dietary recalls. However, additional methodological validation studies are needed to fill several research gaps. First, validation studies are needed to investigate the accuracy of information about children‟s dietary intake when information is obtained from child-only recalls, parent-only recalls, and joint parent-child recalls. For most national surveys (e.g., Continuing Survey of Food Intakes by Individuals 1994-96 and 1998 [35,79,172]; What We Eat in AmericaNational Health and Nutrition Examination Survey [126]), children ages six to 11 years report their intake with assistance from an adult household member. For the School Nutrition Dietary Assessment Study-III, elementary school children were interviewed during the school day, after lunch when possible, and asked to report everything they had consumed that day since awakening; during a second interview which usually occurred the next day, parents attended and helped children recall the rest of the 24-hour period [175]. The joint parent-child recall method used in all of these studies appears to never have been validated. A 1989 study by Eck and colleagues [59] is often incorrectly cited as a rationale to use joint parent-child recalls. That study [59] found that joint recalls by mother, father, and child better reflected observed intake of a cafeteria meal by 34 children ages four to nine and a half years than did recalls by mother or father alone. However, children by themselves did not provide recalls, so no comparison could be made of the accuracy of child-only recalls, parent-only recalls, and joint parent-child recalls of the child‘s intake. Also, joint parent-child recalls were always obtained after mothers and fathers had each provided separate recalls; this could have altered reporting accuracy during the second recall, which was always the joint parent-child recall. Furthermore, the process of completing back-to-back recalls is similar to completing multiple interview passes in two prominently used protocols to obtain 24hDRs (NDSR and USDA‘s automated multiple-pass method). As multiple passes provide many opportunities for subjects to report additional foods, it is possible that the process of completing back-to-back recalls in the study by Eck and colleagues influenced the accuracy of the joint parent-child recalls. Another concern about joint parent-child recalls is that many studies have found relationships between self-reported intake and various characteristics of adults (especially among women) such as BMI [36,37,91,97,98,103,138,181] and social desirability [86-89,166]. Thus, it is plausible that adult characteristics could impact information in joint parent-child recalls about children‘s intake. Based on a study with 34 children ages seven to 11 years, Sobo and colleagues [160,161] provided recommendations to improve the accuracy of data about children‘s intake obtained during parent-assisted 24hDRs. Sobo and colleagues found that parents ―contributed primarily by adding food details and, secondarily, by prompting children;‖ in addition, ―children rejected a notable proportion of items added” by parents, and “children‟s knowledge of food details was considerable.‖ Unfortunately, Sobo and colleagues did not validate the children‘s actual intake, and unassisted children‘s 24hDRs were not obtained.

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Second, validation studies are needed to investigate the combined influence of retention interval and reporting-order prompts (reverse, forward, open) on children‘s dietary recall accuracy. With prior-24-hour recalls, subjects can be prompted to report intake for the interview day first and in forward order (from when they got up that morning to the time of the interview), followed by intake for the previous day (beginning 24 hours before the start time of the interview). Thus, the prior 24 hours is covered in two segments (with the interview day first) and using forward-order prompts for each segment. This process was described by Buzzard [39] and has been used for 24hDRs about the prior 24 hours with children in published validation studies by our group [21,22] and others [68]. The concept of the prior 24 hours is cognitively abstract, especially for children, but it can be simplified by dividing it into two segments (today; yesterday). For prior-24-hour recalls, it is plausible that reverse-order prompts may facilitate reporting accuracy because the subject begins with the eating event closest in time to the interview. A two-segment approach could be used for the prior-24-hour recalls with reverse-order prompts, so that the interview day‘s intake is covered in reverse order (beginning with right before the interview), followed by the previous day‘s intake in reverse order (beginning with last night right before bed), to complete the 24 hours. Reverse-order prompts might also facilitate reporting accuracy for the second segment (i.e., yesterday), especially for children, because, for example, ―before you went to bed last night‖ might be more easily understood than ―after 1:45 yesterday afternoon‖ (for an interview at 1:45 p.m. today), which children may perceive to be a random time yesterday. The combination of retention interval and reporting-order prompts does not appear to have been investigated in any published dietary-reporting validation study with children. Furthermore, to our knowledge, no validation study has compared the forward-order prompts of the NDSR protocol to the open-order prompts of USDA‘s automated multiple-pass protocol to investigate differences in dietary reporting accuracy by children (or adults). Third, for several reasons, there is a crucial need for validation studies to investigate the consistency of children‘s dietary recall accuracy. A single 24hDR is a poor estimate of a person‘s typical intake [189], so multiple 24hDRs are often obtained from children, for example, for assessment of the relative validity of FFQs [51,64,93,144]. Some studies obtain a ―practice‖ 24hDR from children but do not include the practice recall in analyses; if this practice 24hDR does not significantly improve accuracy, the extra burden to subjects and the extra cost to investigators may not be justified. Fourth, validation studies are needed with adequate samples of children by BMI, sex, and race to investigate these potential correlates of dietary recall accuracy. Other potential correlates of children‘s dietary recall accuracy that need to be investigated in validation studies include children‘s age (grade level), children‘s memory/cognitive ability, children‘s social desirability, children‘s self-esteem, children‘s body image, and children‘s socioeconomic status. Fifth, due to the prominent role of intrusions in children‘s dietary recalls, additional validation studies concerning sources of intrusions, types of intrusion, and differences in amounts by types of intrusion could provide valuable insight towards developing or modifying interview techniques to decrease the occurrence of intrusions and their negative impact on reporting accuracy. Towards this end, dietary-reporting validation studies with consecutive days of observation per child are needed to supplement information about availability of food items with information about actual consumption by specific children on multiple and consecutive days.

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 241 Sixth, although multiple passes are included in the two prominent protocols used to obtain 24hDRs from children and from adults (NDSR and USDA‘s automated multiple-pass method), validation studies are needed to investigate whether each consecutive pass enhances recall accuracy as assumed. Results concerning reporting the entrée earlier in lunch-only recalls in Study 5 [30] and the keystone effect of reporting the correct entrée in Study 5 [30], along with results concerning misreported breakfast options and linking of intrusions in Studies 20 [13] and 26 [12], raise questions about whether the multiple passes (which ―build‖ on what was already recalled) in most 24hDR protocols have a positive or negative impact on recall accuracy. If a specific multiple pass of a 24hDR protocol does not significantly improve accuracy, the extra burden to subjects and the extra cost to investigators may not be justified. Seventh, future validation studies should assess accuracy for recalling food items and include both aspects of recall error – omission rates and intrusion rates. These rates characterize different aspects of reporting accuracy. The omission rate is the percentage of items observed eaten that was not reported eaten. The intrusion rate is the percentage of items reported eaten that was not observed eaten. For both omission and intrusion rates, higher values indicate worse reporting accuracy. Although related intrinsically [154,159], omission and intrusion rates, when calculated, have been found to be empirically independent [29,154,159]. Eighth, when analyzing data from validation studies to assess recall accuracy for energy and nutrients, an analytic approach that is sensitive to reporting errors of items and amounts is recommended [19,20,157]. People report their intake in terms of food items, but the accuracy of 24hDRs compared to actual intake is typically assessed indirectly, in terms of energy and nutrients [154,159]. Indirect or conventional approaches to evaluating dietary reporting accuracy typically transform sets of reference information and reported information to energy and nutrients, cumulate values within each set of information for each subject, and then use statistical tests to compare total reported energy and nutrients to total reference energy and nutrients. These conventional approaches ignore reporting errors — intrusions and overreported amounts for matches — because all reported items along with their reported amounts are converted to energy and nutrients. Accuracy assessed using the conventional approaches may appear high for some nutrients but not others because intruded items may be similar to items actually consumed in some nutrients but not others [154,159]. Results from secondary analyses in Studies 17 through 19 [19,20,157] illustrate that conventional approaches which use energy and nutrient variables that disregard reporting errors misrepresent reporting accuracy and mask differences in reporting accuracy. Conventional approaches provide little insight into whether errors in 24hDRs are due to items that are intruded or omitted, or to amounts of matches that are under-reported or over-reported. Insight gained from direct comparisons of items reported to items consumed may guide research to improve methods for assessing intake that yield more accurate 24hDRs, as well as provide practical guidance for eating [10,159,189]. A reporting-error-sensitive analytic approach is recommended in which reported items are identified as matches or intrusions, and amounts of matches are identified as over-reported or under-reported, amounts of intrusions are identified as over-reported, and amounts of omissions are identified as under-reported. Ninth, future dietary-reporting validation studies should use an appropriate validation method. Meal observations are the gold standard for validating dietary reports. Results from observations of school meals are more generalizable than results from observations of

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children eating meals at home, or from observations of meals provided to children in clinical research centers. Relative dietary-reporting validation studies, which compare information from two methods that both rely on self-reports provided by subjects, should be avoided because they fail to provide the truth about actual intake. Tenth, when more than one person conducts observations for a validation study, interobserver reliability should be assessed for training prior to data collection, as well as regularly throughout data collection; this will ensure that information collected does not depend on who conducted observations [2]. Results from interobserver reliability assessed throughout data collection should be included in publications of validation studies. Eleventh, in validation and non-validation studies that utilize dietary recalls, quality control for interviews should be performed regularly to assess interviewer performance during interviews throughout data collection instead of only for training prior to data collection and/or only for data entry. One method of assessing interviewer performance involves having a small number of subjects provide duplicate (back-to-back) recalls to two different interviewers, and comparing information reported during the two recalls [69,70,132]. However, back-to-back recalls impose a burden on subjects, and subjects could report different or additional items in the second recall [149]. Two additional methods of assessing interviewer performance involve (a) taping a small number of interviews and having a supervisor review each audio-recording [163] and (b) having a supervisor observe a small number of interviews [167]. For both of these methods, advance knowledge by interviewers is a concern because interviewers may alter their behaviors when they know interviews are being assessed for quality control, and the presence of a supervisor may alter the behavior of the subject [149]. In contrast, audio-recording each interview encourages each interviewer to follow the protocol for every interview because any interview might be randomly audited for quality control [149]. Digital audio-recordings are recommended because they do not require cassette tapes and can be stored electronically for indefinite lengths of time. Twelfth, because recalls typically cover 24 hours of intake, future validation studies with children should obtain 24hDRs instead of recalls of only one or two meals, even if the validation method involves only one or two meals during the 24-hour target period. This will ensure that the cognitive burden is similar to that of typical 24hDRs.

Recommendations for Maximizing the Accuracy of Children’s Dietary Recalls The purpose of this chapter was not to provide ―the answer‖ to the challenges that plague studies that collect and assess dietary self-reports, nor to identify ―the way‖ to assess children‘s dietary intake. However, results from methodological validation studies summarized in this chapter do allow three recommendations for maximizing children‘s dietary recall accuracy. First, when designing studies that will utilize dietary recalls obtained from children, investigators should make deliberate decisions to minimize the retention interval between intake and report. This is recommended because the retention interval (i.e., the combination of target period and interview time) has profound implications for children‘s recall accuracy.

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 243 Second, data collection efforts should concentrate on having children report the correct food items. This is recommended based on strong evidence that amounts recalled eaten are fairly accurate when children recalled the correct food items, but amount errors were almost a full serving when children omitted food items or intruded food items. In other words, amounts cannot be reported correctly unless food items have been reported correctly first. However, it is important for interviewers to clarify (by asking about the amount eaten for each reported item) that items reported by children were actually eaten rather than items children could have eaten but did not. Third, at this time, it appears inappropriate for several reasons to recommend either the use of food records as memory prompts during recalls or the use of training to improve reporting accuracy. First, results from past research have not been encouraging. For example, in a food-record validation study with fourth-grade children, Lytle and colleagues found that using a food record as a ―memory prompt‖ during a 24hDR did not improve children‘s accuracy [115]. Weber and colleagues provided measurement utensils and trained children ages eight to ten years for 60 to 80 minutes before and after lunch to complete a food record for use as a memory prompt during a 24hDR the next morning; however, there was only 75% agreement between recalled and observed food items for school meals [187]. Second, food records and training eliminate the ability to obtain recalls unannounced (i.e., on any given day), could alter intake, and impose an extra burden on subjects and extra costs to researchers.

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Recommendations for Publications of Studies that Utilize Dietary Recalls The methodological validation studies summarized in this chapter compel us to make two recommendations concerning publications of studies that utilize dietary recalls. First, the profound influence of retention interval on dietary recall accuracy indicates that publications of studies which utilize dietary recalls should specify details concerning target period and interview time. As an analogy, simply indicating that a study‘s data collection included ―dietary recalls‖ or 24hDRs without specifying the target period or interview time would be similar to simply indicating that the study included ―subjects‖ without specifying sex, age, or race. Second, publications of studies which utilize children‘s dietary recalls should clearly indicate whether parents helped children during recalls. When there are numerous publications of a single study, it is crucial that details concerning parental assistance during dietary recalls by children appear in each publication, and that discrepancies do not occur in these details across publications. When parents help children recall their intake, it is impossible to determine whether dietary recall errors are related to children‟s or parents‟ characteristics such as BMI, sex, social desirability, or body image.

Final Remarks This chapter demonstrates the value of dietary-reporting validation studies to conduct formal tests instead of basing decisions on assumptions or expectations. For example, in Study 10 [33], the interaction of sex with order prompts was not anticipated. In Study 11 [32],

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although better recall accuracy was expected with in-person interviews compared to telephone interviews, no significant differences were found between the two interview modalities in the accuracy of children‘s dietary recalls. In Study 12 [18], children‘s recall accuracy was expected to be better with meal interview format than open interview format, but the opposite was found. This chapter also demonstrates the wealth of information available from secondary analyses studies that utilize data from previously conducted dietary-reporting validation studies. Because considerable funding, time, and attention to detail are required to conduct dietary-reporting validation studies, secondary analyses studies are efficient resources to enhance our understanding of dietary reporting errors. Every science progresses to the degree to which its methods have been developed and refined. Additional methodological dietary-reporting validation studies are needed to refine dietary assessment methods that yield more accurate self-reports of intake from children.

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ACKNOWLEDGEMENTS The 26 studies summarized in this chapter were supported by five competitive research grants with Suzanne Domel Baxter as Principal Investigator – grant R29 CA60806 from the National Cancer Institute of the National Institutes of Health; grants R01 HL63189 and R01 HL73081 from the National Heart, Lung, and Blood Institute of the National Institutes of Health; grant 43-3-AEM-2-80101 from the Food Assistance and Nutrition Research Program of the Economic Research Service of the US Department of Agriculture; and a State of Georgia (USA) biomedical grant to the Georgia Center for the Prevention of Obesity and Related Disorders. Grant R01 HL074358 (with Suzanne Domel Baxter as Principal Investigator) funded a large dietary-reporting validation study with a primary aim similar in design to Study 13 and a secondary aim similar in design to Study 14; grant R01 HL074358 helped to support the preparation of this chapter. The content of this chapter is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, and Blood Institute; the National Cancer Institute; the National Institutes of Health; or the Economic Research Service of the US Department of Agriculture. Sincere appreciation is extended (a) to the children and staff of the elementary schools, the School Nutrition Program, and the Richmond County Board of Education (Georgia, USA) for allowing data collection, (b) to the co-authors of publications for the 26 studies, and (c) to Elizabeth J. Herron, MA and Alyssa J. Mackelprang, BS for providing feedback on a draft of this chapter.

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[103] Klesges RC, Eck LH, Ray JW. Who underreports dietary intake in a dietary recall? Evidence from the Second National Health and Nutrition Examination Survey. Journal of Consulting and Clinical Psychology. 63:438-444, 1995. [104] Koehler KM, Cunningham-Sabo L, Lambert LC, McCalman R, Skipper BJ, Davis SM. Assessing food selection in a health promotion program: Validation of a brief instrument for American Indian children in the Southwest United States. Journal of the American Dietetic Association. 100:205-211, 2000. [105] Kohlmeier L. Gaps in dietary assessment methodology: Meal- vs list-based methods. American Journal of Clinical Nutrition. 59:175S-179S, 1994. [106] Kubena KS. Accuracy in dietary assessment: On the road to good science. Journal of the American Dietetic Association. 100:775-776, 2000. [107] Lindquist CH, Cummings T, Goran MI. Use of tape-recorded food records in assessing children's dietary intake. Obesity Research. 8:2-11, 2000. [108] Livingstone MBE, Robson PJ. Measurement of dietary intake in children. The Proceedings of the Nutrition Society. 57:279-293, 2000. [109] Loftus EF. Protocol analysis of responses to survey recall questions. In: Jabine TB, Straf ML, Tanur JM, Tourangeau R, editors. Cognitive Aspects of Survey Methodology: Building a Bridge between Disciplines. Washington: National Academy Press; 1984: 61-64. [110] Loftus EF, Fathi DC. Retrieving multiple autobiographical memories. Social Cognition. 3:280-295, 1985. [111] Loftus EF, Smith KD, Klinger MR, Fiedler J. Memory and mismemory for health events. In: Tanur JM, editor. Questions about Questions: Inquiries into the Cognitive Bases of Surveys. New York: Sage; 1992: 102-137. [112] Lohman TG, Roche AF, Martorell R. Anthropometric Standardization Reference Manual. Champaign, IL: Human Kinetics Books; 1988. [113] Luepker RV, Perry CL, McKinlay SM, Nader PR, Parcel GS, Stone EJ, Webber LS, Elder JP, Feldman HA, Johnson CC, Kelder SH, Wu M. Outcomes of a field trial to improve children's dietary patterns and physical activity: The Child and Adolescent Trial for Cardiovascular Health (CATCH). Journal of the American Medical Association. 275:768-776, 1996. [114] Lytle LA, Dixon LB, Cunningham-Sabo L, Evans M, Gittelsohn J, Hurley J, Snyder P, Stevens J, Weber J, Anliker J, Keller K, Story M. Dietary intakes of Native American children: Findings from the Pathways Feasibility Study. Journal of the American Dietetic Association. 102:555-558, 2002. [115] Lytle LA, Murray DM, Perry CL, Eldridge AL. Validating fourth-grade students' selfreport of dietary intake: Results from the 5-A-Day Power Plus program. Journal of the American Dietetic Association. 98:570-572, 1998. [116] Lytle LA, Nichaman MZ, Obarzanek E, Glovsky E, Montgomery DH, Nicklas T, Zive MM, Feldman H. Validation of 24-hour recalls assisted by food records in third-grade children. Journal of the American Dietetic Association. 93:1431-1436, 1993. [117] Mack KA, Blair J, Presser S. Measuring and improving data quality in children's reports of dietary intake. In: Health Survey Research Methods Conference Proceedings. Hyattsville, MD: US Department of Health and Human Services; 1996:51-55. DHHS publication no. (PHS) 96-1013.

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a cholesterol-lowering diet in children with elevated low-density lipoprotein cholesterol: Seven year results of the Dietary Intervention Study in Children (DISC). Pediatrics. 107:256-264, 2001. [133] Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999-2004. Journal of the American Medical Association. 295:1549-1555, 2006. [134] Ogden CL, Flegal KM, Carroll MD, Johnson CL. Prevalence and trends in overweight among US children and adolescents, 1999-2000. Journal of the American Medical Association. 288:1728-1732, 2002. [135] Paulhus DL. Measurement and control response bias. In: Robinson JP, Shaver PR, Wrightsman LS, editors. Measures of Personality and Social Psychological Attitudes. San Diego, CA: Academic Press; 1991: 17-59. [136] Perks SM, Roemmich JN, Sandow-Pajewski M, Clark PA, Thomas E, Weltman A, Patrie J, Rogol AD. Alterations in growth and body composition during puberty. IV. Energy intake estimated by the Youth-Adolescent Food-Frequency Questionnaire: Validation by the doubly labeled water method. American Journal of Clinical Nutrition. 72:1455-1460, 2000. [137] Presser S, Blair J, Mack K, Ryan C, Van Dyne MA. Final Report on the University of Maryland-USDA Cooperative Agreement to Improve Reporting for Children in the Continuing Survey of Food Intakes by Individuals. Survey Research Center, University of Maryland; 1993. [138] Pryer JA, Vrijheid M, Nichols R, Kiggins M, Elliot P. Who are the 'low energy reporters' in the Dietary and Nutritional Survey of British Adults? International Journal of Epidemiology. 26:146-154, 1997. [139] Rampersaud GC, Pereira MA, Girard BL, Adams J, Metzl JD. Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents. Journal of the American Dietetic Association. 105:743-760, 2005. [140] Raper N, Perloff B, Ingwersen L, Steinfeldt L, Anand J. An overview of USDA's Dietary Intake Data System. Journal of Food Composition and Analysis. 17:545-555, 2004. [141] Regents of the University of Minnesota. NDSR Nutrition Data System for Research 2007. [142] Reger C, O' Neil CE, Nicklas TA, Myers L, Berenson GS. Plate waste of school lunches served to children in a low-socioeconomic elementary school in south Louisiana. School Food Service Research Review. 20(Suppl):13-19, 1996. [143] Rockett HR, Berkey CS, Colditz GA. Evaluation of dietary assessment instruments in adolescents. Current Opinion in Clinical Nutrition and Metabolic Care. 6:557-562, 2003. [144] Rockett HR, Breitenbach M, Frazier AL, Witschi J, Wolf AM, Field AE, Colditz GA. Validation of a youth/adolescent food frequency questionnaire. Preventive Medicine. 26:808-816, 1997. [145] Rockett HR, Wolf AM, Colditz GA. Development and reproducibility of a food frequency questionnaire to assess diets of older children and adolescents. Journal of the American Dietetic Association. 95:336-340, 1995. [146] Ruxton CHS, Kirk TR. Breakfast: A review of associations with measures of dietary intake, physiology and biochemistry. British Journal of Nutrition. 78:199-213, 1997.

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 255 [147] Samuelson G. An epidemiological study of child health and nutrition in a northern Swedish county. II. Methodological study of the recall technique. Nutrition and Metabolism. 12:321-340, 1970. [148] Schmidt LR, Frohling H. Lay concepts of health and illness from a developmental perspective. Psychology & Health. 15:229-238, 2000. [149] Shaffer NM, Baxter SD, Thompson WO, Baglio ML, Guinn CH, Frye FHA. Quality control for interviews to obtain dietary recalls from children for research studies. Journal of the American Dietetic Association. 104:1577-1585, 2004. PMCID: PMC1435375. [150] Simon JA, Obarzanek E, Daniels SR, Frederick MM. Dietary cation intake and blood pressure in black girls and white girls. American Journal of Epidemiology. 139:130140, 1994. [151] Simons-Morton BG, Baranowski T. Observation in assessment of children's dietary practices. Journal of School Health. 61:204-207, 1991. [152] Simons-Morton BG, Forthofer R, Huang IW, Baranowski T, Reed DB, Fleishman R. Reliability of direct observation of schoolchildren's consumption of bag lunches. Journal of the American Dietetic Association. 92:219-221, 1992. [153] Simons-Morton BG, Parcel GS, Baranowski T, Forthofer R, O'Hara NM. Promoting physical activity and a healthful diet among children: Results of a school-based intervention study. American Journal of Public Health. 81:986-991, 1991. [154] Smith AF. Cognitive Processes in Long-term Dietary Recall. Series 6, No 4. Hyattsville, MD: National Center for Health Statistics, Vital and Health Statistics, Series 6, No. 4; 1991. [155] Smith AF. Concerning the suitability of recordkeeping for validating and generalizing about reports of health-related information. Review of General Psychology. 3:133-150, 1999. [156] Smith AF, Baxter SD, Hardin JW, Guinn CH, Royer JA, Litaker MS. Validation-study conclusions from dietary reports by fourth-grade children observed eating school meals are generalisable to dietary reports by comparable children not observed. Public Health Nutrition. 10:1057-1066, 2007. PMCID: PMC2615668. [157] Smith AF, Baxter SD, Hardin JW, Nichols MN. Conventional analyses of data from dietary validation studies may misestimate reporting accuracy: Illustration from a study of the effect of interview modality on children's reporting accuracy. Public Health Nutrition. 10:1247-1256, 2007. PMCID: PMC2587272. [158] Smith AF, Baxter SD, Hardin JW, Royer JA, Guinn CH. Some intrusions in dietary reports by fourth-grade children are based on specific memories: data from a validation study of the effect of interview modality. Nutrition Research. 28:600-608, 2008. NIHMSID: NIHMS52236. [159] Smith AF, Jobe JB, Mingay DJ. Retrieval from memory of dietary information. Applied Cognitive Psychology. 5:269-296, 1991. [160] Sobo EJ, Rock CL. "You ate all that!" Caretaker-child interaction during children's assisted dietary recall interviews. Medical Anthropology Quarterly. 15:222-244, 2001. [161] Sobo EJ, Rock CL, Neuhouser ML, Maciel TL, Neumark-Sztainer D. Caretaker-child interaction during children's 24-hour dietary recalls: Who contributes what to the recall record? Journal of the American Dietetic Association. 100:428-433, 2000.

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[162] Srinivasan SR, Bao W, Wattigney WA, Berenson GS. Adolescent overweight is associated with adult overweight and related multiple cardiovascular risk factors: The Bogalusa Heart Study. Metabolism: Clinical and Experimental. 45:235-240, 1996. [163] Stone EJ, Osganian SK, McKinlay SM, Wu MC, Webber LS, Luepker RV, Perry CL, Parcel GS, Elder JP. Operational design and quality control in the CATCH multicenter trial. Preventive Medicine. 25:384-399, 1996. [164] Strickland BR. Approval motivation. In: Blass T, editor. Personality Variables in Social Behavior. Hillsdale, NJ: Lawrence Erlbaum Associates; 1977: 315-356. [165] Subar AF, Krebs-Smith SM, Cook A, Kahle LL. Dietary sources of nutrients among US children, 1989-1991. Pediatrics. 102:913-923, 1998. [166] Taren DL, Tobar M, Hill A, Howell W, Shisslak C, Bell I, Ritenbaugh C. The association of energy intake bias with psychological scores of women. European Journal of Clinical Nutrition. 53:570-578, 1999. [167] Tippett KS, Cypel YS, editors. Design and Operation: The Continuing Survey of Food Intakes by Individuals and the Diet and Health Knowledge Survey, 1994-96: US Department of Agriculture, Agricultural Research Service. No. 96-1; 1998. [168] Todd KS, Kretsch MJ. Accuracy of the self-reported dietary recall of new immigrant and refugee children. Nutrition Research. 6:1031-1043, 1986. [169] Troiano RP, Flegal KM. Overweight children and adolescents: Description, epidemiology and demographics. Pediatrics. 101:497-504, 1998. [170] Tulving E. Episodic and semantic memory. In: Tulving E, Donaldson, W, editor. Organization of Memory. New York: Academic Press; 1972: 381-403. [171] US Department of Agriculture, Agricultural Research Center. USDA Automated Multiple-Pass Method. Available at: http://www.ars.usda.gov/Services/docs.htm?docid=7710. Accessed April 4, 2009. [172] US Department of Agriculture, Agricultural Research Service. Food and Nutrient Intakes by Children 1994-96, 1998 Online. Available at: http://www.ars.usda.gov/SP2UserFiles/Place/12355000/pdf/scs_all.PDF. Accessed April 4, 2009. [173] US Department of Agriculture, Economic Research Service. The Food Assistance Landscape, FY 2007 Annual Report. Available at: http://www.ers.usda.gov/Publications/EIB6-5. Accessed April 4, 2009. [174] US Department of Agriculture, Food and Nutrition Service. Road to SMI Success - A Guide for School Foodservice Directors. Available at: http://www.fns.usda.gov/tn/Resources/roadtosuccess.html. Accessed April 4, 2009. [175] US Department of Agriculture, Food and Nutrition Service, Office of Research, Nutrition, and Analysis. School Nutrition Dietary Assessment Study-III: Volume II: Student Participation and Dietary Intakes, by A Gordon, et al., Project Officer: P McKinney, Report No. CN-7-SNDA-III. Alexandria, VA; 2007. Available at: http://www.fns.usda.gov/oane/menu/Published/CNP/FILES/SNDAIIIVol2.pdf#xml=http://65.216.150.153/texis/search/pdfhi.txt?query=SNDA+III&pr=FNS &order=r&cq=&id=48236e0811. Accessed April 4, 2009. [176] US Department of Health and Human Services. The Surgeon General's Call to Action to Prevent and Decrease Overweight and Obesity. Rockville, MD: US Department of Health and Human Services, Public Health Service, Office of the Surgeon General;

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Methodological Research Concerning the Accuracy of Children‘s Dietary Recalls 257 2001. Available from US GPO, Washington and online at http://www.surgeongeneral.gov/topics/obesity/. Accessed April 4, 2009. [177] US Department of Health and Human Services. Healthy People 2010: Volume II (second edition) Objectives for Improving Health (Part B: Focus Areas 15 - 28). Washington, DC: US Government Printing Office; November 2000. Available online at http://www.healthypeople.gov/Publications/. Accessed April 4, 2009. [178] US Department of Health and Human Services, US Department of Agriculture. Dietary Guidelines for Americans, 2005 (6th edition). Washington, DC: US Government Printing Office; 2005. Available at: www.healthierus.gov/dietaryguidelines. Accessed April 4, 2009. [179] Van Horn LV, Stumbo P, Moag-Stahlberg A, Obarzanek E, Hartmuller VW, Farris RP, Kimm SY, Frederick M, Snetselaar L, Liu K. The Dietary Intervention Study in Children (DISC): Dietary assessment methods for 8- to 10-year-olds. Journal of the American Dietetic Association. 93:1396-1403, 1993. [180] Vereecken CA, Maes L. A Belgian study on the reliability and relative validity of the Health Behaviour in School-Aged Children food-frequency questionnaire. Public Health Nutrition. 6:581-588, 2003. [181] Voss S, Kroke A, Klipstein-Grobusch K, Boeing H. Is macronutrient composition of dietary intake data affected by underreporting? Results from the EPIC-Potsdam Study: European Prospective Investigation into Cancer and Nutrition. European Journal of Clinical Nutrition. 52:119-126, 1998. [182] Vuckovic N, Ritenbaugh C, Taren DL, Tobar M. A qualitative study of participants' experiences with dietary assessment. Journal of the American Dietetic Association. 100:1023-1028, 2000. [183] Wang G, Dietz WH. Economic burden of obesity in youths aged 6-17 years: 19791999. Pediatrics 109:e81, 2002. Available at: http://www.pediatrics.org/cgi/content/ full/109/5/e81. Accessed April 4, 2009. [184] Wang Y, Lobstein T. Worldwide trends in childhood overweight and obesity. International Journal of Pediatric Obesity. 1:11-25, 2006. [185] Warren JM, Henry CJK, Livingstone MBE, Lightowler HJ, Bradshaw SM, Perwaiz S. How well do children aged 5-7 years recall food eaten at school lunch? Public Health Nutrition. 6:41-47, 2003. [186] Wattigney WA, Webber LS, Srinivasan SR, Berenson GS. The emergence of clinically abnormal levels of cardiovascular disease risk factor variables among young adults: The Bogalusa Heart Study. Preventive Medicine. 24:617-626, 1995. [187] Weber JL, Lytle L, Gittelsohn J, Cunningham-Sabo L, Heller K, Anliker JA, Stevens J, Hurley J, Ring K. Validity of self-reported dietary intake at school meals by American Indian children: The Pathways Study. Journal of the American Dietetic Association. 104:746-752, 2004. [188] Whitten WB, Leonard JM. Directed search through autobiographical memory. Memory and Cognition. 9:566-579, 1981. [189] Willett WC. Nutritional Epidemiology, 2nd edition. New York: Oxford University Press; 1998. [190] Worsley A, Baghurst KI, Leitch DR. Social desirability response bias and dietary inventory responses. Human Nutrition: Applied Nutrition. 38A:29-35, 1984.

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In: Appetite and Nutritional Assessment Editors: S. J. Ellsworth, R. C. Schuster

ISBN: 978-1-60741-085-0 © 2009 Nova Science Publishers, Inc.

Chapter 9

CONTEMPORARY ASSESSMENT OF CHILD DIETARY INTAKE IN THE CONTEXT OF THE OBESITY EPIDEMIC Anthea M. Magarey1, Annabelle M. Wilson1 and Emma Goodwin1 1

Department of Nutrition and Dietetics, Flinders University of South Australia, Bedford Park, South Australia 5042

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ABSTRACT Dietary intake has received considerable interest as part of understanding and addressing the global obesity epidemic. Food intake has an important role in the aetiology of overweight and obesity and interventions targeting communities and individuals for either prevention or management invariably include a nutrition component. An important element in evaluating the effectiveness of such interventions is assessment of dietary intake. Traditionally dietary assessment has focussed on energy, micro and macro nutrient intakes and consequent deficiency. In the 1970s this view expanded to consider the role of nutrition in chronic disease and included both deficient and excessive intakes but remained focussed on energy, macro and micro nutrients. As nutrition research turned more to prevention and management of chronic disease, the concept of a healthy diet (usually based on official dietary guidelines and recommendations) increasingly became useful and assessment tools were developed and continue to be, to classify individuals accordingly. In the last two decades and particularly the last decade, interest has progressively turned to food patterns. In the context of the rising prevalence of obesity, the characterisation of food patterns that increase the risk of positive energy balance and thus accumulation of excess weight and those associated with a protective effect against obesity will inform development and evaluation of prevention and management strategies. In addition there is increasing interest in identifying and describing those factors which influence food behaviour such as knowledge, attitudes and environments. As researchers explore the most effective way to prevent and manage the obesity epidemic there is simultaneous interest in dietary assessment as a component of impact evaluation of such interventions. Traditional methods of dietary assessment are associated with high subject burden and/or high administrative and/or analysis costs

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Anthea M. Magarey, Annabelle M. Wilson and Emma Goodwin which are often not appreciated by funding bodies and thus beyond the scope of many studies. Alternative less costly methods of dietary assessment, more relevant to contemporary dietary issues and that also consider factors influencing dietary intake behaviour, are of increasing value. This review assesses the relevance to obesity of traditional and contemporary child dietary outcomes and their methods of assessment. Recent developments in dietary assessment tools, including those that assess factors influencing behaviour (i.e. intake) namely knowledge, attitudes and environments are reviewed. The important issue of tool validation will be addressed and how this might be achieved for contemporary tools.

INTRODUCTION

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Importance of Dietary Assessment in the Context of the Child Obesity Epidemic The global obesity epidemic affecting both developed and developing countries and within these countries both adults and children, is well described, as are the associated health consequences and burden of disease [1]. Of particular concern is the increasing prevalence in children and adolescents as overweight tracks into adulthood and increases the risk of adult morbidity [2]. The World Health Organisation [1] identified obesity as a public health issue requiring public health approaches for prevention and management. Obesity arises as a result of positive energy balance i.e. energy in (food) exceeds energy out (basal metabolic rate plus activity) [1]. Even small amounts of excess energy will result in fat storage. Positive energy balance sustained over time will result in increased body weight and ultimately overweight and then obesity. A clear understanding of the role of dietary intake in the aetiology of overweight is crucial to guide both prevention and management. The importance of dietary modification as an essential component of intervention to prevent and manage childhood overweight is recognised in clinical practice guidelines in Australia the United Kingdom and the United States of America (USA). However, the evidence to inform optimal dietary intake is limited [3-5]. All recommend that dietary counselling/nutrition education should be age-specific and follow healthy eating advice as part of a multi-component intervention. In addition the World Health organisation guidelines for weight management [6] endorse a focus on healthy eating recommendations: • • • •

Eat more fruit and vegetables. Eat a variety of low fat, high fibre foods, Eat more nuts and wholegrains, Cut down fatty and sugary foods in the diet

A range of studies have linked intake of foods or food groups that are targeted in dietary guidelines/ healthy eating recommendations, with risk of obesity [7]. Modelling also shows that diets based on healthy eating recommendations will reduce energy intake [8]. However there remains a lack of intervention research demonstrating that ―food intake inconsistent with these [healthy eating] guidelines promotes excess weight or the converse that promoting intake consistent with dietary guidelines is effective in the prevention and treatment of childhood overweight‖ [8].

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A limitation to advancing understanding of whether healthy eating recommendations are an effective strategy for obesity prevention and management, and of the aetiology of obesity with respect to food and food related behaviours is the lack of appropriate dietary assessment techniques. Thus in order to identify risk factors, develop obesity specific nutrition guidelines and interventions, or assess the effectiveness of novel intervention strategies at the population and/or individual level there is a need for new more relevant dietary assessment techniques. To date dietary intake has primarily been described in terms of energy and /or nutrients although increasingly single foods and food groups have also been reported. This interest in specific foods has evolved more recently into describing food patterns. With the recognition of the complex aetiology of obesity and the need for complex and tailored intervention solutions, there is increasing interest in dietary intake from a broader perspective i.e. the psychosocial and environmental predictors of dietary patterns/intake. Such factors include knowledge (e.g. fat content of specific foods), attitudes (e.g. limiting unhealthy snacks for children is important), beliefs (e.g. fruit and vegetables are good for you), skills (e.g. label reading) and environments (e.g. availability of healthy food in the school canteen). All are potential targets for modification and provide alternative interim outcomes in assessment of intervention strategies. This paper reviews current dietary outcomes and methods of assessment for relevance to the evaluation of interventions for prevention and management of childhood obesity. It discusses the consequences of the limitations of these outcomes and methods and reviews recent developments. In addition the challenges of tool validation will be discussed.

DIETARY OUTCOMES AND METHODOLOGIES

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Key Definitions Due to the wide array of dietary intake outcomes and methodologies we have classified them into traditional and contemporary outcomes and methodologies (Table 1). These definitions reflect their relevance to professionals in the area of childhood obesity research. The term ‗tool‘ is used interchangeably with ‗method‘ or ‗methodology‘ throughout this review as a tool is the method by which dietary outcomes are collected.

Traditional Outcomes Dietary assessment developed in parallel with increasing nutritional science knowledge and thus historically focussed on energy and macro/micro nutrients in an era when deficiency was the major nutritional concern [9]. Of primary interest was whether intake provided sufficient energy and nutrients for growth and prevention of deficiency diseases. The goal of dietary assessment was to describe usual dietary intake which could be compared with energy and nutrient requirements.

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Anthea M. Magarey, Annabelle M. Wilson and Emma Goodwin Table 1. Definitions of key terms

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Key Term Definition Dietary intake outcomes Traditional Primarily energy, macro or micro nutrient focused Single foods or food groups reported in isolation Contemporary Primarily food focused, e.g. fruits and vegetables, high fat/sugar foods Indexes of diet quality Food patterns Diet-related outcomes: attitudes, knowledge, skills, behaviours and environments associated with dietary intake; food availability, food accessibility and food sources Dietary intake methodologies/ tools Traditional Have been used extensively across time and population groups Assess nutrient intake (e.g. food record, recalls, food frequency questionnaires (FFQ), diet history) Predominantly self-reported or parent proxy report May be adapted to fulfil a purpose more similar to that of contemporary methods Contemporary Recent in their development without an extensive history of use Application together with reliability and validity assessment, is limited to smaller population group/s Assess overall diet quality, patterns of food intake and/or intakes of specific foods Include observation and electronic means of dietary assessment Predominantly questionnaire based Questionnaire items may be interpreted by creating a scale which involves summation of multiple item responses to produce a composite score

Relevance of Traditional Outcomes to Obesity Energy In the context of obesity, interpretation of usual energy intake is difficult without a concurrent estimate of energy expenditure that then allows an estimate of energy balance. Assessment of usual energy expenditure is as problematic as estimating usual energy intake [10]. Information about energy balance would be the ultimate outcome for obesity research as the underlying cause of obesity is positive energy balance, but given the limitations we need to rely on proxy outcomes. In childhood obesity research we suggest that measuring the determinants of energy imbalance are potentially of most interest as these proxy outcomes. Micronutrients Micronutrients measured in isolation are of limited use as they provide no direct information about energy balance. While micronutrient intake may be used as an indication of overall diet quality [11] (see later discussion) in the sense that a greater intake of micronutrients can indicate a healthier diet, this is not always the case. However, it is important to acknowledge that determining micronutrient intake is still a valid approach which has provided, for example, information about the role of calcium in obesity [7].

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Macronutrients Macronutrient intake is useful as it provides direct information about energy intake. In addition in adults there has been considerable research investigating the effect on weight loss of iso-caloric diets of varying macronutrient proportions [12]. However there is no clear conclusion from this research and studies in children are limited [3]. In the obesity context fat intake attracts greatest attention because of its high energy density and the potential impact on energy intake of moderating fat intake [8; 13]. Assessment of a single macronutrient in isolation from other macronutrients should be treated with caution, particularly if attempting to extrapolate energy intake. However, macronutrient assessment can be useful in obesity research if it is placed in the context of foods, as changing the macronutrient context of a meal may change eating behaviour. For example, Warren et al [14] found that children who ate a breakfast with a low glycaemic index (with or without 10% added sucrose) had a significantly lower food intake at lunchtime compared to those consuming a high glycaemic index breakfast. Foods and food groups In a traditional sense food/food group outcomes have been used in the context of describing the specific food sources of energy and nutrients in diets [5; 15; 16] and comparing intake with dietary recommendations [17; 18].

Contemporary Outcomes

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Relevance of Contemporary Outcomes to Obesity Specific Foods/ Food Groups Intake of a number of foods/food groups (e.g. fruit and vegetables, sweetened beverages, takeaway food, high fat/sugar foods) have been identified as risk factors for positive energy balance or associated with overweight in children [19]. Assessing intake of these foods/food groups is thus relevant to dietary assessment in relation to childhood obesity research. Healthy Eating Indexes Recognition of nutrition related non-communicable disease in developed affluent countries prompted description of nutritional requirements in a broader context encompassing the concept of nutrition for optimal health. These were defined by dietary guidelines (e.g. eat a diet high in fibre, choose a variety of foods) as well as nutrient requirements (e.g. importance of iron and calcium intake and decreasing saturated fat) [9]. The natural progression from here was the development of healthy eating indexes that identified individuals and groups who met this proposed definition of a healthy diet [11]. Healthy eating indexes are generally used for two reasons. First, to get an overall measure of diet quality which incorporates micronutrient adequacies and macronutrient recommendations, for example the Youth Healthy Eating Index [20]. Second, as a short cut to assess overall adequacy, i.e. a quick method, for example the Variety Index for Toddlers [21] and the Dietary Diversity Score [22]. Kant [11] reviewed diet quality indexes and identified two main types: (a) those based on nutrients and (b) those based on foods or food groups.

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Healthy eating indexes are examples of outcomes based on traditional methods that provide information of more relevance to obesity researchers than do most traditional outcomes. Healthy eating indexes assess more than single foods or nutrients thus accounting for the complexity of human diets and that some nutrient intakes can be correlated with each other [11]. An index includes multiple factors and a score reflecting diet quality or adequacy is produced; if the index is indicative of diet quality with respect to foods of interest in obesity, it can be useful. However, healthy eating indexes have several limitations. Invariably they become outdated when healthy eating guidelines change and hence need regular revision to ensure they truly reflect the latest nutrition science and policy. Some healthy eating guidelines are country specific and thus not necessarily transferable to other countries. Third there has been little research to identify whether or not healthy eating indexes predict obesity risk, energy intake, weight gain and similar factors. Kant [11] identifies some indexes, based on (a) nutrients only, (b) foods or food groups only and (c) both (a) and (b), that have been tested for their relationship to health outcomes. However, in the majority this research was done with adults and none of the indexes considered obesity as a health outcome. As current guidelines for dietary management and prevention incorporate many of the elements of healthy eating indexes, these are potentially useful outcomes for assessing dietary intake in the context of overweight. Macronutrient intake may be relevant if the intervention targets change in consumption of specific macronutrient/s, for example fat but with the limitations described previously, but measuring adequacy of micronutrient intake, whether it be direct or through an index, has limited use. Hence, healthy eating indexes that are based on nutrients are of little relevance in childhood obesity prevention programs. In contrast, healthy eating indexes that give an indication of food group adequacy, particularly if they target foods/food groups of interest, such as fruit, vegetables, sweetened beverages and non-core foods, could be useful tools in dietary assessment of children in the context of the obesity epidemic, especially if associated with a less burdensome methodology.

Food Patterns While healthy eating indexes can be applied in dietary assessment for a range of chronic diseases, food patterns can be used to look at obesity specific outcomes. A food pattern attempts to capture the complex nature of dietary intake [23] and while used loosely in the literature, can be defined as dietary choices in terms of food groups (e.g. fruit, dairy) and food types (e.g. high fat, low fat). The association of specific food patterns with health outcomes (including specific conditions such as obesity), behavioural outcomes and socio-demographic factors has been investigated [23]. Identifying food patterns can be a useful step in development of an obesity-specific intervention. For example, McNaughton et al [23] using data from the 1995 Australian National Nutrition Survey (n=764 12-18 year olds who completed a 108-item FFQ) identified several food patterns and investigated their association with factors including obesity and hypertension. Results from this study could be used to develop program-specific messages for an obesity-specific intervention targeting a similar population. Togo et al [24] reviewed 30 studies reporting on patterns of food intake and their associations with body mass index or obesity. Only one of these reported on children aged two and above while another two included 16 and 17 year olds. While ten of the thirty studies found that fatty, sweet or energy dense patterns were associated with BMI, four other studies found that similar patterns were negatively associated with BMI [24]. The authors concluded

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that there is a lack of consistency of associations between food patterns and BMI or obesity prevalence in adults. This review highlights the need for additional research to confirm findings arising from this relatively new methodology as well as to determine the application of findings in children.

The ‘Obesogenic’ Environment The ‗obesogenicity‘ of an environment has been defined as ―the sum of influences that the surroundings, opportunities, or conditions of life have on promoting obesity in individuals or populations‖ [25]. This acknowledges that there is an interdependence between the individual, their health and the environment, and that obesity prevention at the population level is unlikely to occur unless environmental influences are identified and modified [25]. Thus measuring environmental parameters relevant to obesity development, particularly those related to dietary intake and physical activity is highly relevant.

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Methodologies for Assessing Dietary Outcomes Special Consideration of Dietary Assessment in Children Selection of a methodology for assessing dietary intake in children requires special consideration [26; 27]. A child‘s age affects their literacy and numeracy skills, cognition, concept of time, memory, attention span and knowledge of foods. Until the age of eight to nine years, children are unable to provide reliable data on the previous day‘s intake and below the age of 10 years children do not have the conceptual skills to provide reliable information on serve sizes, frequency of behaviours and usual intake. As children get older their dietary patterns become more variable and increasingly influenced by factors outside the home thus affecting the number of days that may be required to describe usual intake. These factors should be considered whatever the outcome and methodology. In many instances parent/caregiver proxy report will be required. Traditional Methodologies The traditional methods of dietary assessment are the food record (weighed or using household measures), the 24 hour recall, or a food frequency questionnaire (FFQ) [28; 29]. The number of days that are collected by record or recall can vary and will depend on the outcome of interest and whether group or individual level data are required and is often a compromise between ideal and what is practical with respect to resources and subject burden that minimises drop-out and maximises validity [26]. For energy and macronutrients between three and nine days have been suggested but for other nutrients including cholesterol up to 18 days may be required [30]. A FFQ is a defined food list the details of which are dependent on the outcome of interest. Frequency of consumption of each food is assessed over a specified time which is usually greater that the previous 24 hours and can be up to the previous year. The diet history is a less common method with varying approaches but generally combines information on current intake with usual intake over a longer period. These traditional methods provide comprehensive outcomes with respect to usual energy and nutrient intake with the scope dependent on the data base that is used to convert foods eaten to nutrients. Absolute intake of foods and/or food groups, their relative contribution to energy and nutrients, number of serves and energy/nutrient density of foods/food groups can

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be generated also. Such methods and outcomes are common in national population wide surveys that monitor dietary trends and assess intake against nutrient reference values and dietary guidelines [15; 16; 31]. The traditional methods have been extensively discussed in previous publications [28; 29]. Briefly, limitations of the 24 hour recall or record are the potential high subject burden particularly if multiple days of intake are required, and the high researcher burden for interviewing and data entry. The resultant high costs are often beyond the budget of research studies. While a self-administered (or parent reported) food frequency has lower subject and researcher burden there is considerable researcher time required for the initial development, the questionnaire can become out-dated as the food supply changes and completion requires moderate level conceptual skills. Despite these limitations, traditional methods form the basis of all dietary intake assessment methodologies and as such are still important in the context of the obesity epidemic as they are often used as standards against which to validate other methods. In particular, the weighed food record is considered the gold standard for collecting dietary intake information. In addition many contemporary methods are derived from traditional methods, for example, some contain components of a FFQ or 24-hour recall [32-34] while others are based on FFQs [35], with a focus on frequency with which foods are consumed rather than the overall quantity. Furthermore, traditional methods are being applied in new ways that increase their relevance in obesity research such as describing food patterns. In their review Togo et al [24] identified three principal ways this was done namely indexes, factor analysis and cluster analysis and these used data from 24-hour recalls, FFQs or weighed food records. Whilst novel application of traditional methodologies has a place within obesity research, this does not overcome the associated subject and researcher burden. For example, healthy eating indexes and other ways of characterising food patterns predominantly rely on secondary analysis of intake data collected by traditional methods. While these outcomes broaden the scope of investigating the relationship between healthy eating and disease they provide little advancement in overcoming the cost and subject burden associated with assessing dietary intake. The need for obesity relevant outcomes and methodologies, applicable to intervention evaluation at the population and individual level, remains.

Contemporary Methodologies Contemporary methodologies are predominantly questionnaire based and may include creation of scales from one or more items. The definition of contemporary relates more to the outcome and recent use than to the methodology. Specific Questionnaires (Mostly Around Foods) In the last 10 years a number of questionnaires have been developed that target a subset of foods/food groups. Examples of these are those targeting general food groups [36-40], fruit and vegetables [35; 41-49] or foods relevant to obesity [32; 34; 35; 42; 44; 47; 50-52]. While some of those assessing fruit and vegetable intake were not developed specifically for obesity related studies they are relevant as low fruit and vegetable intake is a risk factor for obesity [53]. The format of these questionnaires varies from a modified food frequency questionnaire that quantifies usual intake of the specified foods to a more simple approach that assesses frequency of intake in the previous week.

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The advantages of targeting specific food group/s is the immediate relevance of the data to obesity research questions, the low burden on subject and researcher, less cumbersome analyses, and because foods in groups may have similar nutrients, an indirect, crude analysis of micronutrient and macronutrient intake may be possible. The contemporary nature of these questionnaires however requires validity and reliability studies to be conducted.

Scales Scales, sometimes called scores, are a relatively new method of analysing dietary, psychosocial and environmental data in the context of the obesity epidemic [34; 35; 54; 55] although there is a long tradition of use by psychologists [56]. Scales are created when single questionnaire items that measure the same construct are summed together resulting in a summary score. Advantages of creating scores from raw data are (1) a ‗target healthy score‘, based on healthy eating (or other) guidelines, can be created and this serves as a reference to which data can be compared, (2) scores are more sensitive to change than individual response items, hence when used for evidence of effectiveness of a childhood obesity intervention, small changes are more likely to be identified [34], (3) scores provide a way of summarising data into less items more appropriate for multivariate regression analysis and (4) scores represent an avenue for analysing the ‗obesogenic‘ environment because multiple environmental factors can be combined. An example of such a score is ‗fruit attitude‘ in the Child Nutrition Questionnaire [34]. This five-item score was composed of agreement with the following five items (each using a 5-point likert scale): makes me feel healthy, tastes good, easy snack, I like tasting new fruits, cheap. Each level of agreement was given a sub-score, based on how much it reflected a positive fruit attitude (strongly agree, agree, not sure, disagree, strongly disagree, given values 5-1 respectively). While the contemporary methods discussed above are important in theory, it is useful to consider to what extent they have been used in obesity intervention research and the implications of this for progressing the field of dietary assessment in the context of child obesity in the future.

The Limitations of Current Outcomes and Methodologies Two recent systematic reviews evaluating the effectiveness of dietary interventions for the prevention [57] and treatment [58] of childhood overweight highlight limited meaningful reporting of dietary outcomes. This is likely to be a barrier to the progression of obesity research in the areas of evaluation and effectiveness. Of 88 studies cited in a systematic review to identify best practice for the dietetic treatment of overweight and obese children and adolescents only 23 reported dietary outcomes and these were of varying detail [58]. Instead, most studies used an indication of weight change (e.g. BMI) to assess the effectiveness of the dietary intervention. Energy and macronutrient intake were the most commonly reported dietary outcomes, with food, food group and psychosocial outcomes reported less often (either in isolation or in addition to energy and macronutrient outcomes) (Table 2). The authors conclude that the quality of most studies was poor in terms of assessing changes in dietary intake in response to the interventions [58]. This is likely to be a reflection of the dietary methodology used rather than the real results. The limited relevance and associated cost to both subject and researcher of

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traditional dietary assessment methods and the lack of alternative methods is probably a major reason for these limited data. Until these issues are addressed by researchers, it is unlikely that a high level of evidence for the optimal dietary treatment of childhood overweight and obesity will be achieved. In contrast a systematic review assessing the effectiveness of interventions designed to prevent obesity in children through diet, physical activity and/or lifestyle, identified 16 studies that included a dietary component and 14 of these reported at least one dietary outcome [57]. While most studies reported energy and macronutrient intake, a sizeable proportion of these also reported intake of food/food groups relevant to the obesity epidemic (e.g. intake of fruit and vegetables, confectionary and fast food) and dietary related psychosocial outcomes (e.g. knowledge and behaviours) (Table 2). At least one traditional method of dietary assessment was used in each of the 14 studies and half of these also used at least one contemporary method. For example, Warren et al [59] used a validated nutrition knowledge questionnaire in addition to 24-hour recalls and food frequency questionnaires to evaluate a school and family based intervention. Dietary outcomes reported were fat and fibre scores, nutrition knowledge, intake of fruit, vegetable, confectionary and crisps, and nutrient intake. The collection of this large amount of dietary data from multiple assessment methods led to more informative dietary results, however this would certainly have come at a cost to both researcher and subject in terms of burden and its value could be questioned. One contemporary method of dietary assessment focusing on answering key dietary questions in the study may have reduced this burden. As presented earlier, expert groups recommend that healthy eating patterns rather than energy and macronutrient intake should be the focus of prevention and management strategies. The shift towards a greater proportion of studies in this review reporting food, food group and food related psychosocial outcomes in the area of prevention reflects this recommendation. Table 2. Number of studies reporting dietary intake outcomes according to the method of data collection in a review of dietetic treatments [58] and a review of prevention studies [57] Dietary Assessment method Traditional Assessment only Contemporary Assessment only Both Traditional and Contemporary assessment

Review of treatment studies [58] 20 1

Review of prevention studies [57] 7 0

2

7

In conclusion the evaluation of dietary intake is critical in interventions designed to treat or prevent childhood obesity. In order to assess intervention effectiveness and to inform others with respect to implementation, this task must be completed in a way which is meaningful in relation to desired outcomes of the intervention. It must also take account of the subject and researcher cost and burden to ensure that any resource investment in the study is rewarded by the delivery of real and plausible results. This summary of key reviews in the treatment and prevention of childhood overweight and obesity highlights the general inadequacy of dietary assessment in this area and the over-reliance on traditional methods of

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assessment. The need for relatively simple, easy to administer and analyse, reliable and valid tools specifically designed to assess the effectiveness of dietary components in treatment and prevention studies of childhood overweight and obesity is obvious.

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Dietary Assessment and Child Obesity – Moving Contemporary Outcomes Forward The development of dietary assessment to date for both contemporary and traditional methods has been summarised above. While useful progress has been made, for example, moving from measuring nutrients to foods, it is clear further advancement is required to enable better evaluation of the expanding range of public health and population intervention approaches. Establishing why interventions do/ do not work and identifying the most cost and resource effective interventions is crucial for further progress in managing the obesity epidemic and in order to do this, a broader range of outcomes need to be measured, as outlined in Figure 1. Similarly, a better understanding of the aetiology of obesity will provide more opportunities for intervention and hence evaluation. In order to measure these broader outcomes, appropriate tools are needed. Despite the relative simplicity of the energy balance equation, the aetiology of overweight is complex and a large range of factors influence both sides of the energy balance equation. Environments (home, school, community) are key determinants of food availability but knowledge and attitudes are important factors in food choice (Figure 1). While knowledge alone tends to be a weak predictor of human behaviour [60], it remains important and individual attitudes e.g. to healthy eating and physical activity, can help explain behaviour. Thus there is interest in obesity prevention/ management strategies that target environments, knowledge and attitudes as impact (interim) factors influencing food intake. This identifies the importance of contemporary tools which measure these psychosocial and environmental outcomes and that can be used to evaluate effectiveness of population, group and individual level programs.

Figure 1. Factors influencing energy balance.

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Review of Recent Developments While research to date has provided considerable information on describing and determining the prevalence of dietary patterns and behaviours that increase risk of positive energy balance and/or overweight, in order to change behaviour we need to understand why individuals engage in this risk behaviour and how it might be changed. There are no reviews to date which summarise tools designed (a) specifically to measure effectiveness of child obesity intervention programs or (b) to measure outcomes of interest to the obesity epidemic. The purpose of this limited review is to identify studies that support key points made in this chapter and provide a snapshot of existing tools relevant to child obesity research. In order to identify recent development a broad search was performed for studies that met one or more of three criteria: (1) primary focus to describe or evaluate a dietary intake methodology used in evaluation of a childhood obesity prevention or management program (children 0 to 18 years), (2) primary focus to describe a child obesity intervention which uses a tool to evaluate dietary intake in evaluating effectiveness of the program, or (3) primary focus to report on a tool assessing contemporary dietary outcomes in children 0 to 18 years. A range of tools were identified that measured one or more of the following dietary outcomes: micronutrients, macronutrients, foods, food groups, food patterns and psychosocial or environmental factors. Of the 38 studies reviewed, only one solely measured traditional dietary outcomes [61]. This suggests that the majority of recent studies performed in the context of obesity measure (a) contemporary dietary outcomes only or (b) contemporary and traditional outcomes. None of the studies reviewed measured only micronutrients or macronutrients in isolation. One study reported micro and macronutrients alone [61] while four reported microand macronutrients as well as food groups [36; 38; 39; 46]. A number of studies reported macronutrients in addition to contemporary outcomes including food habits, behaviours, preferences and availability [54]; preferences for bottled water and sweetened beverages [48]; fruit, water and soft drink consumption [62] and selected food groups of relevance to obesity [36-39; 46; 63]. Fifteen studies described tools measuring contemporary, dietary-related psychosocial or environmental outcomes [32-34; 41; 42; 44; 47; 48; 52; 55; 64-68]. Psychosocial and environmental variables were usually collected in conjunction with dietary intake variables, either using the same tool [34] or a different one [44]. Some of the psychosocial and environmental outcomes reported in the literature include: food availability, eating environments and policies [65]; food preference [32]; parental food providing behaviours [47]; barriers to healthy eating, child food preparation habits, social desirability and preference for sweetened beverages [54]; intention, perceived social support and self-efficacy to choose healthy food [52]; attitudes, knowledge, behaviours and environments associated with healthy eating [34; 69]; knowledge, attitudes, liking, intention to eat, habits, preferences and availability of fruit and vegetables [66]; knowledge of nutritional terms and health value of certain foods [64]; attitudes, including those regarding diet-disease relationship [44] and eating related to hunger and eating style [55]. The majority of the studies used traditional methods to derive psychosocial or environmental outcomes in most cases a self- or parent-proxy completed questionnaire. Some examples of contemporary methodologies used to collect such outcomes are: the ‗Healthy Home Survey‘ [65], a questionnaire measuring personal, social and environmental correlates

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of fruit and vegetables [66], a card-sorting task with picture cards representing 64 food items [32], a ‗Physical and Nutritional Home Environment Inventory‘ [47] and the ‗Family Eating and Activity Habits Questionnaire‘ [55] which measures four factors affecting obesity in children, including eating related to hunger and eating style. These can be considered contemporary because they are more recent methodologies without an extensive history of use and assess patterns of food intake or behaviours, in particular foods that are of relevance to obesity (Table 1). Studies that describe tools measuring foods or food groups have been cited in this review. Foods of interest to the obesity epidemic include: sweetened beverages, noncore foods, fruits and vegetables. Analysis of individual foods or specific food groups allows foods known to be associated with obesity risk to be assessed. Similar to tools measuring psychosocial and/ or environmental outcomes, the majority of tools used to collect food group information used traditional methodologies, including 24-hour recalls [36-38; 40; 45; 46; 48; 54], food records [36; 44; 46], food frequency questionnaires [38; 39; 41; 44; 45; 49] and standard questionnaires [52; 54]. Of the 38 studies reviewed, only 10 had as the primary purpose to report on tools designed to measure dietary intake or behaviours specifically in the context of the obesity epidemic [32; 34; 35; 47; 48; 50; 52; 54; 55; 65]. Within the limitations of this search this highlights the lack of reporting of tools developed to assess diet relevant to obesity research. The publication of tools for evaluation of dietary components of childhood obesity prevention and management programs is thus a priority for professionals in the area to enable high quality evaluation of such programs. Such evaluation is essential for establishing effectiveness [57; 58; 70]. Despite the lack of tools specific to obesity, many of the outcomes of interest in obesity research are also relevant for overall health. Hence there are tools that can still be used for evaluation of programs targeting overweight, although they were not designed specifically for this purpose [33; 36-41; 44; 45; 49; 54; 64; 67; 71]. Relevance of these existing tools to overweight could be increased if necessary. For example, the Youth Food Checklist used by Koehler et al [72] in evaluation of a school-based cancer prevention programme asks about the consumption of 33 high-fat, high-fibre food items consumed yesterday. Any of these food items not relevant to obesity could be changed. Equally tools used to assess dietary outcomes in the context of obesity could have wider application [62; 69]. Data from tools that provide information about food/food group consumption and patterns of intake can be compared to food guidelines allowing identification of dietary excesses and deficiencies. These outcomes can guide intervention strategies and the associated tools used to evaluate the effect of the resulting intervention. However such data provide no insight into the underlying reasons for the observed differences nor why changes following an intervention do or do not occur. Simultaneous collection of psychosocial or environmental outcomes with dietary intake data will assist this understanding and thus guide development and refinement of intervention programs. For example, Befort et al [41] investigated the association between fruit, vegetable and fat intake and availability of 17 fruits, 15 vegetables and 13 regular-fat foods in the home and food consumption settings. Several important relationships were identified for example ‗fastfood and buffet restaurant use and eating while watching television were the strongest predictors of fat intake‘ [41]. The authors concluded that ―intervention programs may

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consider including additional tactics other than just having healthful foods present in the home environment‖ [41].

Summary This review highlights recent developments in dietary assessment tools appropriate for use in the context of the obesity epidemic. It demonstrates that there are tools reporting on contemporary outcomes of interest including food groups, food patterns and specific foods. However, it also highlights the lack of tools providing insight into why obesity-specific behaviours do or do not occur. Hence, exploration and reporting of psychosocial and/ or environmental factors simultaneously with dietary intake data, in order to identify and address determinants of the obesogenic environment, are crucial areas for development. Other important research areas include (a) development of tools designed specifically to measure child dietary intake and psychosocial/ environmental factors relevant to obesity and (b) development of tools that measure the obesogenic environment and that simultaneously include measures of both dietary intake and physical activity. Advances in these areas will assist in design and evaluation of childhood obesity prevention and management programs, and hence contribute to the evidence for effectiveness of such programs. Another critical step in this process of tool development is the determination of reliability and validity. This is potentially challenging for contemporary outcomes and methodologies.

DIET ASSESSMENT METHODOLOGY – VALIDITY AND RELIABILITY Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

What Are Validity and Reliability? The validity of a tool is a measure of whether it captures the intended concept, exposure or outcome that it is thought to measure, that is, a tool is valid if the findings can be taken to be a reasonable representation of the true situation [73]. Reliability, also referred to as repeatability or precision, is an indication of the consistency with which a tool measures an exposure or outcome [73]. If a tool is reliable then differences between repeat measures on the same person should be due to true subject variation [73]. Assessment of reliability is an important first step as a tool cannot be valid if it is not reliable [56]. In the context of dietary intake methodology, relative validity and test-retest reliability are the most widely reported measures of diet assessment tool validation in the literature.

Importance of Validity and Reliability Data collected from a valid and reliable tool will itself be valid and reliable. If a tool is not valid or reliable, then the researcher cannot be sure that the tool (a) measures what it is thought to measure and (b) is able to give the same result from any one person when applied on more than one occasion. Only a valid and reliable tool can provide valid and reliable data.

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Valid and reliable data strengthen the conclusions drawn from program evaluation. Table 3 defines key concepts associated with validity and reliability of dietary assessment tools. Table 3. Definitions of tool properties [74-77] Key Term Validity Concurrent validity (also known as construct validity)

Content validity Criterion validity^ Predictive validity/ utility Relative validity^; construct validity

Reliability

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Test-retest reliability (TRR)

Homogeneity of items

Definition • A tool‘s ability to measure food intake accurately • Used in cases when a gold standard is not available • Extent to which a questionnaire predicts a disease (e.g. obesity) classified using an objective measure (e.g. BMI) • Extent to which a test agrees with another test in a way that is expected • Extent to which a dietary assessment tool covers the research areas of interest • A tool‘s ability to measure food intake as defined by a gold standard • The ability of a questionnaire to predict the gold standard test result at some time in the future • The extent to which a test method of dietary assessment produces results that agree with those measured by a reference method, taken as the validation standard • Analysis requires a measure of agreement in addition to correlation • General term used to encompass all types of reliability, including test-retest, inter-observer, intra-observer, internal consistency • Refers to whether a tool can elicit the same results on repeated administrations a) across different times, b) between different observers, c) by the same observer • Measured by the intra-class correlation coefficient • Assesses the degree to which items in a scale are different aspects of the attribute the scale measures, also called internal consistency • Measured by Cronbach‘s ά

^ Dietary intake cannot be measured with absolute precision in free-living populations, hence there is no true validation standard [77] and it can only be determined how one method compares with another.

Validity and Reliability in the Context of the Obesity Epidemic To What Extent Have Tools Used in the Context of the Obesity Epidemic Been Assessed for Validity and Reliability? There are a relatively large number of valid and reliable tools that measure energy and nutrient intake in school-aged children [26]. However, there is a lack of valid and reliable tools that assess outcomes of interest to the obesity epidemic, particularly psychosocial factors, and that are setting specific. For example, Finch et al [78] state that evaluation of

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school-based interventions for primary school children is limited by the availability of valid, reliable and acceptable methods for gathering self-reports of dietary intake in a school-setting. Of the 38 studies reviewed in this paper, 23 assessed one or more validation properties of the reported tool (Table 4). While it is beyond the scope of this limited review to critically appraise the methods used to validate diet assessment tools and the reported results, a few comments are warranted. In many cases the most appropriate tests were not used to measure validity and test-retest reliability, the most commonly reported properties. A common method of testing these properties is to use the correlation coefficient but this measures the degree to which the two measures are related not their agreement. Two values may be strongly related but not agree. For continuous outcomes the most appropriate test for reliability is the intraclass correlation coefficient. For relative validity the strength and limits of agreement according to the method of Bland and Altman [74] at both individual and group level is the preferred method. For dichotomous data the kappa statistic assesses agreement and if more than two categories weighted kappa can be used [56; 73]. Readers are advised to critically appraise the statistical tests used and the interpretation of the results, and make their own assessment of the reliability and validity of a tool. It is not uncommon for authors to state that reliability and validity of a tool have been determined and although the outcomes of that testing may not support the tool‘s reliability and validity, the tool is accepted for wider use. One of the problems in interpreting results of reliability and validity testing is that there are no widely agreed cut-points for determining acceptability of results. Table 4. Summary of studies measuring validity and reliability

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Tool property/ properties reported Relative validity only

Test-retest reliability* only Relative validity^ & test-retest reliability*

Test-retest reliability & internal consistency Test-retest reliability, internal consistency & relative validity (other)

Study (author, year) Edmunds & Ziebland 2002; Koehler et al 2000; Lytle et al 1998; Magnusson et al 2005; Smith & Fila 2006; Van Assema et al 2002 Buzzard et al 2001; Finch et al 2007 Andersen et al 2004; Bryant et al 2008; Cullen et al 2001; De Bourdeaudhuij et al 2005; Haraldsdottir et al 2005; Hoelscher et al 2003, Kremer et al 2006; Taylor et al 2004; Yaroch et al 2000 Stevens et al 1999; Turconi et al 2003 Cullen et al 2008 (construct validity); Magarey et al 2008 (criterion validity & ability to detect change); Wilson et al 2008; Golan & Weizman 1998 (content, concurrent & predictive validity)

* Includes studies reporting ‗reproducibility‘ ^ Includes studies reporting ‗calibration‘ of instruments.

Reliability and Validity Assessment of Indexes of Overall Diet Quality It is relatively straightforward to determine the reliability of indexes of diet quality and given their complex derivation, determining inter- and intra- researcher reliability in addition to reliability over time are important parameters to assess. Determining validity however is more complex. If the purpose of the index is a short cut to overall dietary adequacy, the diet quality index score can be compared to a known measure of diet adequacy. For example, the

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variety index for toddlers (VIT) is compared to the Mean Adequacy Ratio, a measure of nutrient adequacy [21]. When there is no gold standard or similar measure available, construct validity, which links the attribute being measured to another attribute/construct, can be considered [56]. For example, the VIT is linked to energy intake [21] and a moderate to good correlation was found, indicating that as energy intake increases, so does dietary variety. This is to be expected and hence validates the design of the VIT.

Complications of Assessing Validity in the Context of the Obesity Epidemic It is relatively straightforward to determine all forms of reliability of tools using both contemporary and traditional methodologies. For example, an assessment of test-retest reliability involves administration of the dietary assessment tool on two occasions. While assessment of relative validity is reasonably straightforward for tools with traditional methods, it can be more difficult to assess in tools with contemporary methods and/ or outcomes. A number of shorter, more contemporary tools measuring child dietary intake in the context of the obesity epidemic [34; 35; 50] have been validated using modified, traditional methodologies [34; 35]. In these cases the reference method was a modified food diary where respondents recorded intake of foods of interest only (those in the questionnaire) covering a period of similar length to that in the questionnaire. For example, the Child Dietary Questionnaire [35] asks about child dietary intake over the past seven days, hence the reference method (modified food diary) was completed for seven days. Measuring actual intake over the period specified by questionnaires (7 days) accounts for within-person variation [73] and hence it can be determined whether the questionnaire provides a true representation of dietary intake (validation). Similarly, the School Food Checklist was validated using a weighed food record where all foods in the child‘s lunchbox were weighed (or estimated if already consumed) [50]. Again, this reference method only covered the period of intake time measured by the SFC (school recess and lunch). In both examples, subject burden is minimised as only the dietary information needed within a specified time frame is collected. As has been demonstrated throughout this review, tools which measure psychosocial and/ or environmental factors associated with the obesity epidemic are of high relevance to professionals in the area. However, determining relative validity of such tools is challenging because external validators are not available for mental constructs [79]. Hence assessment must rely on more subtle indicators of coherence and consistency such as predictive validity [79] (Table 3). In the case of obesity research, this could be the ability of a questionnaire about availability of fruit and vegetable in the home to predict fruit and vegetable intake. Golan and Weizman [55] highlight that there was no ‗gold standard‘ for validating the Family Eating and Activity Habits questionnaire, hence emphasis was placed on measures of validity alternative to criterion validity, including content, concurrent and predictive validities. Future Avenues for Assessment of Validity and Reliability in the Context of the Obesity Epidemic Use of scales as contemporary outcomes may convert categorical data into continuous data which then enables use of intra-class correlation and strength of agreement to test relative validity and reliability. If it is not possible to assess the relative validity of a tool, it

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becomes even more important to assess those properties that can be assessed (such as testretest reliability).

Use of Alternative Tool Properties

Internal Consistency While relative validity of scales relating to mental constructs cannot be determined, such scales can be subjected to an internal consistency analysis. Internal consistency (Cronbach‘s alpha) can assess reliability of more abstract scales [76] by identifying (a) how well the individual items of a scale fit together and (b) whether they assess the same construct [76; 80]. It is important to note that Cronbach‘s alpha values are sensitive to the number of items in a scale and low values may be obtained if the scale has less than 10 items [80] which may often be the case with food related scales. For each item within a scale the impact on the alpha value of removing that item from the scale is determined. An alpha value higher than the final value suggests the removed item is unnecessary. Such items should be removed from the scale and any data analysis, including the target healthy scores, re-calculated using the modified scale.

Content Validity In the context of the obesity epidemic, content validity is an important property to consider. Many traditional tools do not have appropriate content validity as discussed above. However many contemporary tools have been designed with obesity and other chronic diseases in mind and hence cover outcomes of interest and therefore have better content validity.

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Agreement between Tools Asking Similar Questions in Related Subject Groups The extent to which two tools asking similar questions in two or more subject groups agree is an alternative to relative validity. For example, both children and parents could assess the healthy eating environment at home using separate questionnaires. The agreement between the single answers (or devised scales) from each could be determined using a correlation coefficient (or paired t-test for a scale). A similar process could be done with children and teachers about the healthy eating environment at school.

Summary As in many areas of research, professionals in obesity research often have limited time and resources. Determining validity and reliability of tools is not only time and resource intensive, but requires a certain degree of expertise, particularly in the case of the more complex and contemporary tools. The consequent reality is that tool validation is often not performed prior to use or in some cases not at all. It is important for researchers to (a) seek assistance if required (b) appreciate how validity and reliability assessment of a tool adds to the strength and robustness of any results obtained using that tool and (c) report on such assessments so others can benefit from their work.

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IMPORTANT ISSUES Inconsistent Terminology A potential barrier to advancement of dietary assessment in its broadest sense, in the context of obesity is the inconsistent use of common nutritional terms. The terms ‗dietary behaviour‘ and ‗diet quality‘ are two examples (Table 5). Some authors in identifying that their paper reports ‗dietary behaviours‘ are referring to outcomes such as energy intake, percent of calories from fat and average number of servings of fruit, vegetables and fruit juice [48]. While consumption of food groups or foods can be described as a dietary behaviour, energy intake and percent of calories from fat are not behaviours but outcomes of a behaviour (i.e. eating certain foods). In other contexts, ‗dietary behaviours‘ are taken to be food-related behaviours such as food purchasing and preparation practices [34]. ‗Diet quality‘ is defined in one study to be serves of food groups, calorie and micronutrient intakes, total sugar intake and percent of calories from sweets [39]. While such information may give a good overview of the quality of a person‘s diet, it is a different type of overview to a study using a ‗diet quality‘ index such as those studies reviewed by Kant [11]. Inconsistencies within papers have also been noted with ‗food and exercise habits‘, ‗habitual dietary intake and meal pattern quality and quantity‘, and ‗dietary patterns‘ all used to describe what was measured although the only ‗habit‘ or ‗pattern‘ discussed in any detail was breakfast [51]. Careful and consistent use of terms will aid the reader in identifying relevant studies.

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Table 5. Common terms used in the obesity literature, various uses and suggested use/s Term Dietary behaviour

Diet quality

Various uses 1. Energy intake, percent of calories from fat and average number of servings of fruit, vegetables and fruit juice [48] 2.Food-related behaviours including: preparation, consumption, purchasing 1. Food groups, calorie and micronutrient intakes, total sugar intake and percent of calories from sweets [39] 2. Extent to which a diet meets food intake guidelines 3. Indexes based on nutrients, foods or food groups that assess intake against guidelines

Suggested use/s 2

Quality of diet needs to be assessed against a standard (such as healthy eating guidelines ) i.e. 2 or 3

CONCLUSION In the last 10 to 20 years there has been considerable progress in the area of dietary assessment. Outcomes of interest have expanded from the traditional energy, nutrients and foods to consider total diet outcomes, such as healthy eating indexes, relevant to chronic disease. However most of these outcomes have limited use in the context of the obesity epidemic and tend to have high subject burden, administrative and analysis costs. The

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consequence is a lack of data on the impact of prevention and management strategies for childhood obesity on dietary outcomes. This in turn is a barrier to the progression of obesity research in the areas of program evaluation and effectiveness. There is a clear need for relatively simple, easy to administer and analyse tools specifically designed to assess the effectiveness of dietary components in treatment and prevention studies of childhood obesity. Further, as interest broadens in obesity research to consider the psychosocial and environmental factors which influence dietary behavior the need for new tools to measure these outcomes is evident. An essential component in developing such tools is the testing of validity and reliability to establish that meaningful data are collected. Clearly the development of tools more relevant to dietary assessment in the context of childhood obesity and the testing of reliability and validity of these tools are areas requiring considerable research effort.

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[71] Andersen, L; Bere, E; Kolbjornsen, N; Klepp, KI. Validity and reproducibility of selfreported intake of fruit and vegetables among 6th graders. European Journal of Clinical Nutrition, 2004 58, 771-77. [72] Koehler, KM; Cunningham-Sabo, L; Lambert, LC; McCalman, R; Skipper, BJ; Davis, SM. Assessing food selection in a health promotion program: validation of a brief instrument for American Indian children in the southwest United States. Journal of the American Dietetic Association, 2000 100, 205-11. [73] Nelson, M. The validation of dietary assessment. In: Margetts BM & Nelson M. Design Concepts in Nutritional Epidemiology. New York: Oxford University Press; 1997; 241272. [74] Bland, M; Altman, D. Measuring agreement in method comparison studies. Statistical Methods in Medical Research, 1999 8, 135-60. [75] Frank, GC. Taking a bite out of eating behaviour: food records and food recalls of children. Journal of School Health, 1991 61, 198-200. [76] Peat, J. Health Science Research: A handbook of quantitative methods. Crows Nest: Allen & Unwin; 2001. [77] Serdula, MK; Alexander, MP; Scanlon, KS; Bowman, BA. What are preschool children eating? A review of dietary assessment. Annual Review of Nutrition, 2001 21, 475-98. [78] Finch, M; Begley, A; Sutherland, R; Harrison, M; Collins, C. Development and reproducibility of a tool to assess school food practices and lifestyle habits of Australian primary school-aged children. Nutrition and Dietetics, 2007 64, 86-92. [79] Baranowski, T; Simons-Morton, BG. Dietary and physical activity assessment in school-aged children: measurement issues. Journal of School Health, 1991 61, 195-97. [80] Pallant, J. SPSS Survival Manual. Crows Nest Allen & Unwin; 2004.

Reviewed by Dr Rebecca K Golley, NHMRC Postdoctoral Research Fellow, Preventative Health Flagship, CSIRO Human Nutrition.

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In: Appetite and Nutritional Assessment Editors: S. J. Ellsworth, R. C. Schuster

ISBN: 978-1-60741-085-0 © 2009 Nova Science Publishers, Inc.

Chapter 10

THE USE OF COMPOSITE SCORES TO ASSESS ADHERENCE TO DIETARY PATTERNS: THE MEDITERRANEAN DIET CASE Angeliki Papadaki* and Manolis Linardakis Preventive Medicine and Nutrition Clinic, Department of Social Medicine, Faculty of Medicine, University of Crete, Greece PO Box 2208, Heraklion 710 03, Crete, Greece

ABSTRACT

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The association of diet with chronic disease has been well documented, and in recent years, research interest has focused on the investigation of whole dietary patterns, instead of single nutrients, for the prevention, and/or treatment of several diseases. The Mediterranean diet is recommended to the Western world as a dietary pattern that is both palatable and healthy, and that can be easily incorporated within a modern lifestyle. Although it is difficult to establish a definition of the ‗typical‘ traditional Mediterranean diet, Mediterranean dietary patterns share eight characteristics that differentiate them from American and northern European food cultures. In particular: a high ratio of monounsaturated to saturated fat (MUFA:SFA); high intake of vegetables; fruits, nuts and seeds; legumes/ pulses; (mainly unrefined) cereals; a low-to-moderate intake of dairy products; low intake of meat, meat products and poultry; and moderate alcohol consumption. In 1995, the use of an 8-unit „a priori‟ dietary score to assess adherence to the Mediterranean diet was proposed, based on the above characteristics of this dietary pattern. This score was later revised to account for fish consumption, the intake of which in the Mediterranean diet was moderate-to-high. Since then, several studies have used adaptations of the original Mediterranean Diet Score, and found significant inverse associations between adherence and overall mortality, disease risk, and biomarkers of health, as well as positive associations with survival. Further, the score has been utilised to detect dietary improvements in nutrition intervention studies. The purpose of this chapter is to describe and investigate the use of the original score and its adaptations in research studies, present the findings of studies utilising such indexes, and discuss validity and reliability issues for dietary assessment purposes. Suggestions for researchers

*

Tel: +30 2810394601; Fax: +30 2810394604; E-mail: [email protected], [email protected]

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Angeliki Papadaki and Manolis Linardakis wishing to employ Mediterranean diet indexes to investigate associations with chronic disease and assess adherence to the Mediterranean diet in the future will also be provided.

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INTRODUCTION The association of diet with chronic disease has been well documented (Willett, 1994), and in recent years, research interest has focused on the investigation of whole dietary patterns, instead of single nutrients, for the prevention, and/or treatment of several diseases (Jacobson & Stanton, 1986; Patterson et al., 1994; Huijbregts et al., 1995; Kant, 1996; Hu et al., 1999; Dixon et al., 2001; Kant, 2004), but also for the description of eating behaviour (Moeller et al., 2007). This is because free-living individuals do not consume isolated nutrients or foods, but complex diets containing a combination of foods, nutrients, and nonnutrient compounds that may be highly correlated, and may act in a synergistic or interactive manner (Jacques & Tucker, 2001; Hu, 2002; Jacobs Jr & Steffen, 2003; Kant, 2004). Investigating the effect of dietary patterns on chronic disease also provides a comprehensive approach to disease prevention or treatment, and to the formulation of dietary guidelines (Krauss et al., 1996; Fung et al., 2001; World Health Organisation, 2002), as well as a more practical means for the public to conceptualise dietary recommendations (Hu, 2002). This can further aid in the design of nutritional assessment trials, nutrition intervention studies, and the provision of education feedback to patients. Research to date has advocated the importance of the whole dietary pattern, in contrast to particular dietary components, with regards to longevity, survival, and reduced rates of chronic disease (Trichopoulou et al., 1995b; Appel et al., 1997; Osler & Schroll, 1997; de Lorgeril et al., 1998; Knoops et al., 2004; Bamia et al., 2007; Panagiotakos et al., 2007a), suggesting that this approach might be more useful in examining the associations of diet with disease. To date, two approaches have been utilised to define dietary patterns. The first approach is based on exploratory statistical methods (namely principal component, factor, and cluster analyses), and uses observed dietary intake data in order to extract, and define actual dietary patterns „a posteriori‟ (Jacques & Tucker, 2001; Bamia et al., 2007). This approach has been used to identify prevailing dietary patterns of populations (Costacou et al., 2003; Bamia et al., 2007) or examine their association with specific health outcomes, such as obesity, and cardiovascular disease (Hu et al., 2000; Fung et al., 2001). „A posteriori‟ methods, however, do not necessarily result in the description of diets that adhere to nutritional recommendations (Kant, 2004). Further, they cannot readily associate dietary patterns with chronic disease, since patterns defined in this manner may not incorporate dietary components for which clear associations with disease exist. In addition, this approach cannot provide useful comparisons between different studies, since actual dietary practices usually differ between different populations or different groups between the same populations. Therefore, patterns prevailing in one population may not be identified in other study populations, and subsequently, the „a posteriori‟ approach is not considered essentially reproducible (Jacques & Tucker, 2001; Kant, 2004). The second approach used to examine dietary exposure, the „a priori‟ approach, is based on existing dietary recommendations or on previous knowledge regarding the favourable or detrimental effects on health of established food patterns or various dietary components (Jacques & Tucker, 2001; Scarmeas et al., 2006b; Moeller et al., 2007). These patterns are

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then operationalised via the construction and calculation of graded dietary scores, which help identify adherents to healthy eating practices, and/or less healthy eaters. Thus, „a priori‟ scores or indexes measure compliance with already defined eating practices by assessing the presence or absence from the diet of certain dietary components (Hu, 2002; Kant, 2004; Bamia et al., 2007). The „a priori‟ approach is useful because it evaluates and describes the total diet (Fung et al., 2005). In addition, „a priori‟ scores are easy to compute, reproducible, allow comparisons between different studies and different populations, and associate dietary patterns with chronic disease more meaningfully, since they reflect already identified diet-disease associations, when compared to „a posteriori‟ methods, thereby also displaying stronger associations with disease biomarkers (Bach-Faig et al., 2006; Moeller et al., 2007). Care, however, must be taken during the definition of the dietary pattern for which compliance is to be assessed, the choice of dietary components to be included in the score, and the choice of cut-off values in order to calculate the score (Trichopoulou et al., 1995b; Hu, 2002; Fung et al., 2005; Moeller et al., 2007). In addition, „a priori‟ scores often depend on the health outcomes evaluated, since a specific food component might be beneficial for one, but detrimental for another type of disease. During the interpretation of such scores, attention should also be focused on considering the health effects of the total score, in addition to the potential health effects of the individual food components contributing to the score (Moeller et al., 2007). This is because individual components might be unrelated with each other and have separate effects on health. Further, these scores do not take into account the range of consumed amounts of foods (when compliance is assessed by dichotomising intakes of food components) (Moeller et al., 2007). Finally, one should always account for the potential under- or over-reporting of consumption of specific food components, due to social desirability issues related to the reporting of certain foods (Kant, 2004). To date, many „a priori‟ dietary scores, based on eating patterns with established health benefits, have been created, and used to assess epidemiological associations and diet-disease relationships (Fung et al., 2005; Bach et al., 2006). An example with much popularity in the scientific community is the Mediterranean diet, a purportedly highly palatable dietary pattern with renowned health benefits, compliance with which could promote good health and prevent chronic disease risk (Bamia et al., 2007).

EPIDEMIOLOGY OF CHRONIC DISEASE IN MEDITERRANEAN COUNTRIES Interest in the health-promoting benefits of the Mediterranean diet derives from the results of the Seven Countries Study that was conducted by Ancel Keys and his colleagues in the early 1960s (Keys, 1970). It was found that overall mortality rates were lower in adult Greek men than in North Americans or northern Europeans (Helsing, 1995). After a followup of 5–15 years, it was found that mortality from all causes in the cohort from Crete, Greece, was much lower when compared with the nine other cohorts from southern Europe and northern countries, as illustrated in Table 1.

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Angeliki Papadaki and Manolis Linardakis Table 1. Ten-year total mortality rates per 10,000 men aged 50-69y, who participated in the Seven Countries Study

Crete Mediterranean1 Netherlands United States

Total mortality 514 1090 1091 1153

CHD mortality 9 184 420 574

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Adapted from: (Renaud et al., 1995). Reprinted with permission from the American Society for Nutrition CHD: Coronary Heart Disease 1 9 Mediterranean cohorts.

The Seven Countries Study specifically reported that diets consumed in Greece and southern Italy in the 1960s protected against the development of coronary heart disease. In particular, the dietary pattern of Crete was considered to be a healthy ideal, being low in saturated fat and rich in fruits, vegetables, legumes, nuts, grains, and olive oil (Kromhout et al., 1989). People in Crete were found to have very low CHD mortality rates compared with other North American and European populations (Table 1) (Keys, 1970). The life expectancy displayed by people in Greece in the early 1960s was also among the highest in the world and the Greek population displayed very low mortality rates from both cardiovascular and coronary heart disease, as presented in Table 2. The Mediterranean diet has also attracted considerable attention because of its apparent cancer-protective role, as evidenced by the relatively low cancer mortality rates in Mediterranean populations (Helsing, 1995). Specifically, it was observed that people living in Mediterranean countries and especially in Greece, displayed mortality rates from cancer that were among the lowest in the world (Table 2). Since socio-economic factors in Mediterranean regions, including financial status, educational levels and medical services, were quite low at the time compared with those of more industrialised countries, diet has been proposed to be the main factor related to the excellent health status and high life expectancies of Mediterranean populations (Kromhout et al., 1995; Gjonca & Bobak, 1997). Longitudinal studies have suggested that people who follow the traditional Mediterranean eating pattern have a 17% to 60% reduced risk of dying from all causes than people with less traditional eating habits (Trichopoulou et al., 1995a; Trichopoulou et al., 1995b; Osler & Schroll, 1997; Kouris-Blazos et al., 1999; Lasheras et al., 2000; van Staveren et al., 2002; Trichopoulou et al., 2003; Knoops et al., 2004). It has also been suggested that adherence to a Mediterranean-style diet could reduce the overall incidence of cancer in northern Europe and the United States by 10% (Trichopoulou et al., 2000; Knoops et al., 2004), reduce cancer mortality risk by 24% to 60% (Knoops et al., 2004), reduce coronary heart disease and cardiovascular disease mortality risk by 31% to 64% (Trichopoulou et al., 2003; Knoops et al., 2004; Trichopoulou et al., 2005a), as well as be protective against obesity and promote greater food variety (Wahlqvist et al., 1999). Although available evidence has mostly been provided by observational studies, these estimates are supported by findings from tertiary (de Lorgeril et al., 1994; Renaud et al., 1995; Singh et al., 2002; Barzi et al., 2003), secondary (McManus et al., 2001; Esposito et al., 2004) and primary (Castagnetta et al., 2002; Goulet et al., 2003; Papadaki & Scott, 2005) prevention trials that have used the Mediterranean diet as an intervention strategy. These studies have shown that the Mediterranean diet can improve blood lipid profiles, protect against both

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Table 2. Life expectancy at 45y and age-standardised chronic disease mortality rates per 100,000 people aged 0-64y in various countries in the 1960s

Greece United States Japan

Life expectancy

CVD mortality

CHD mortality

Total cancers

Gastric Cancer

Colorectal cancer

Females

Breast cancer Females

Males

Females

Males

Females

Males

Females

Males

Males

Females

Males

Females

31 27

34 33

26 30

23 24

33 189

14 54

83 102

61 87

8 22

10 6

6 3

3 11

3 10

27

32

102

57

34

21

98

77

4

48

26

5

5

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Source: (Willett, 1994). Reprinted with permission from the American Association for the Advancement of Science (AAAS) CVD: Cardiovascular Disease CHD: Coronary Heart Disease.

0067.

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In addition to its health benefits, the Mediterranean diet is an eating pattern that is recognised for its palatability and can thus serve as a model for dietary improvement (Nestle, 1995; Willett et al., 1995). This has resulted in its recommendation to the Western world as a dietary pattern that is tasty, healthy and easily incorporated within a modern lifestyle (Willett et al., 1995).

WHAT IS THE MEDITERRANEAN DIET?

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Despite the fact that the Mediterranean diet concept has gained popularity within the scientific community and the population at large, there is no single Mediterranean diet but rather there are as many Mediterranean eating patterns as there are Mediterranean countries (Serra-Majem et al., 2004a). This can be easily explained, since the Mediterranean Sea borders 22 countries (Figure 1), which differ greatly in culture, religion, geography, economic and political status and other factors that may influence food resources and eating habits. For example, the Italian diet is characterised by increased pasta consumption, whereas pulses are more common in Greece and fish intake is relatively high in Spain (Trichopoulou & Lagiou, 1997). Moreover, the nutrient content of the same food item can vary between different countries (Simopoulos, 2001), and differences in the dietary pattern can also exist between different parts of one country (e.g. dietary intakes in southern Italy are more characteristic of the traditional Mediterranean diet compared to the eating habits in northern Italy) (Hill & Giacosa, 1992).

Figure 1. The Mediterranean Sea and 22 surrounding countries.

It is therefore difficult to establish a definition of the ―typical‖ Mediterranean diet, since the variety of dietary patterns in Mediterranean countries leads to differences in terms of food consumption and consequently, nutrient intakes (Tavani & La Vecchia, 1995; Hakim, 1998). Since Ancel Keys found the dietary pattern of the Greek island of Crete to be associated with

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extremely good health in the Seven Countries Study in the early 1960s, it is this pattern that has come to be regarded as the model Mediterranean diet (Keys, 1970; Renaud et al., 1995). Other researchers proposed a definition of the Mediterranean diet as the dietary pattern followed by people living in southern Italy in the 1960s (Ferro-Luzzi & Sette, 1989). Since in that period, olive oil was the principal source of fat in both Crete and southern Italy, the term ―Mediterranean diet‖ has been extended to include dietary patterns similar to olive-growing Mediterranean locations, where olive oil is a major fat source in the diet (Willett et al., 1995). Although it has been difficult to define one kind of Mediterranean diet, traditional Mediterranean dietary patterns share some basic characteristics that differentiate them from American and northern European food cultures. In particular: • • • • • • • • •

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•

High ratio of monounsaturated-to-saturated fat (MUFA: SFA ratio); High consumption of fruits, nuts and seeds; High consumption of vegetables (excluding potatoes); High consumption of legumes (including beans, lentils, chickpeas and peas); High consumption of (mainly unrefined) cereals; Moderate consumption of fish (depending on the proximity to the sea); Low consumption of meat, meat products and poultry; Moderate consumption of eggs (fewer than 4 per week) Low-to-moderate consumption of milk and dairy products (mainly cheese and yoghurt); Moderate alcohol consumption (mostly wine and usually with meals) (Trichopoulou et al., 1995b; Trichopoulou et al., 2003; Serra-Majem et al., 2006).

The high consumption of vegetables, legumes and other plant foods in raw salads, soups and cooked meals is facilitated by the use of olive oil, which is the most important fat source in this dietary pattern (Trichopoulou, 2000; Trichopoulou et al., 2000). The consumption of plant foods is also made easier by the abundant use of garlic, onions and various herbs. In addition, foods consumed are generally seasonally fresh and minimally processed, so in most Mediterranean countries, only moderate amounts of salt are consumed. Fresh fruit is the standard dessert and cakes and puddings are usually consumed on special occasions only. Intake of alcohol is moderate for most people, mainly in the form of wine and almost always with meals (James, 1995; Keys, 1995; Hakim, 1998). Table 3. Dietary fat profile in various countries in the 1960s1

Total fat (% energy) Saturated fat (% energy) Monounsaturated fat (% energy) Polyunsaturated fat (% energy)

Crete

United States

Japan

37.0 8.0 29.0 3.0

39.0 18.0 12.4 8.6

11.0 3.0 5.0 3.0

Adapted from: (Kafatos et al., 1991; Willett, 1994; Kromhout et al., 1995). Reprinted with permission from the American Society for Nutrition and the American Association for the Advancement of Science (AAAS). 1 Based in the average daily intake of men (aged 40-59y) who participated in the Seven Countries Study.

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The minimal processing and usual methods of preparation, as well as the high proportion of fresh, locally grown foods related to Mediterranean diets guarantee a high intake of antioxidants, dietary fibre, monounsaturated fat, n-3 fatty acids, various micronutrients and several non-nutrient substances found in plant foods, as well as a low intake of saturated fat (Renaud et al., 1995; Gjonca & Bobak, 1997; Kafatos et al., 2000). In particular, total fat intake has not necessarily been low in Mediterranean countries. It ranged from approximately 28% in southern Italy to 40% of total energy intake in Crete (Kromhout et al., 1989). Nevertheless, the use of olive oil as the principal fat source, instead of animal and dairy fats typical of American and northern European cultures, led to a high MUFA: SFA ratio (almost ≥2) in most Mediterranean countries (Trichopoulou et al., 1995a). Although the total fat content of the traditional dietary pattern of Crete remains controversial (Ferro-Luzzi et al., 2002), olive oil consumption resulted in an extremely favourable overall dietary fat profile of this eating pattern, as demonstrated in Table 3. Dietary characteristics of some Mediterranean countries in the 1960s are presented in Table 4, compared to the diet of the United States. Some variability can be observed between the different Mediterranean regions studied (three in Italy, five in Yugoslavia, two in Greece) but in general, consumption of plant foods was higher and consumption of foods of animal origin was lower compared to other northern European countries (Netherlands, Finland) or other industrialised countries (Japan, USA).

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Table 4. Dietary characteristics in various countries in the 1960s

Total fat (% energy) Saturated fat (% energy) Vegetables (g/d) Fruit (g/d) Legumes (g/d) Bread & cereals (g/d) Potatoes (g/d) Meat & poultry (g/d) Fish (g/d) Eggs (g/d) Alcohol (g/d)

Greece 37 8 191 463 30 453 170 35 39 15 23

United States 39 18 171 233 1 123 124 273 3 40 6

Japan 11 3 198 34 91 481 65 8 150 29 22

Source: (Willett, 1994). Reprinted with permission from the American Association for the Advancement of Science (AAAS).

The Mediterranean Diet Pyramid presents a graphic indication that daily intake should mainly consist of plant foods, with olive oil as the main source of fat, and a moderate intake of dairy products (preferably non-fat or low-fat versions), and wine. Fish, poultry, eggs, and sweets should be consumed less frequently, and on a weekly basis, whereas meat and meat products (preferably lean versions) should be consumed sparingly, only a few times per month. This pyramid suggests healthy food choices for the general adult population and does not define recommended weights of foods, because good health has been associated with variation within the overall pattern. The pyramid may need to be modified, however, to meet the needs of special population groups.

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To better conceptualise the traditional eating patterns of Mediterranean populations, a pyramid has been developed, based on the principles of the traditional Mediterranean diet (Figure 2).

Figure 2. Mediterranean Diet Pyramid.

Although factors other than diet, such as the after-lunch siesta, reduced stress, increased physical activity, and good climate, may have contributed to the good health of Mediterranean populations (Renaud et al., 1995), the traditional Mediterranean diet appears to supply most of the essential elements identified to promote health (Willett, 1994; Hakim, 1998). The health advantages of the Mediterranean diet are therefore obvious. Thus, the development of nutritional assessment methods to evaluate adherence to this dietary pattern would help determine associations between diet and chronic disease, and also provide useful ground for the design of appropriate nutrition education studies. The construction of „a priori‟ scores, which incorporate food components traditionally consumed in the Mediterranean diet,

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summarises the complex dimension of a healthy dietary pattern by integrating different foods, nutrients and their combinations in a single score in a concise manner (Bach et al., 2006; Bach-Faig et al., 2006).

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METHODS The purpose of this chapter is to review some of the methods that several intervention and epidemiological studies have used to evaluate adherence to the Mediterranean diet. Computerised literature searches were conducted using the databases MEDLINE and OVID. Titles and abstracts were searched for the following terms: Mediterranean diet, Mediterranean diet adherence, Mediterranean diet scores and Mediterranean diet indexes. The search was limited to papers referring to the Mediterranean diet as a whole dietary pattern, according to „a priori‟ evidence, and papers were excluded if they evaluated indexes based on specific foods (e.g. fruits and vegetables) or if they reported „a posteriori‟ analyses (e.g. factor/ cluster analyses). Abstracts were screened for potential relevance and following the identification of suitable journal papers, full texts were sought via electronic libraries or after contacting the authors. All references cited in these papers were also hand-searched to locate appropriate papers. Although a systematic review or meta-analysis of the studies identified would have been preferable in order to combine and analyse results across multiple studies, this was impractical taking into account the considerable variation between these studies in outcome measures, sample characteristics, and different scores/ indexes used to assess adherence to the Mediterranean diet. A further limitation of the present literature search is that searches were limited to papers published in the English language (only one paper in the Spanish language was located and appropriately translated). In addition, although every attempt was made to locate relevant papers, the possibility of missing references, as well as the publication bias (e.g. bias against studies presenting ―negative‖ or ―neutral‖ results) should be acknowledged.

RESULTS Following the reviewing of available literature, thirty-four different „a priori‟ dietary scores were identified, that have been used to assess compliance with the Mediterranean diet. The following part of this chapter presents a detailed description of these scores, along with their methods of calculation.

THE MEDITERRANEAN DIET SCORE (MDS) The first attempt to conceptualise the Mediterranean diet was reported in 1995 (Trichopoulou et al., 1995b), when a composite score was developed and evaluated among a group of elderly Greeks consuming a traditional Greek diet. The Mediterranean Diet Score (MDS) was based on the consumption of eight food components of the traditional Mediterranean diet, namely: high ratio of monounsaturated: saturated fat (MUFA: SFA ratio);

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moderate alcohol intake; high legume intake; high intake of cereals (including bread, starchy roots and potatoes); high intake of fruits (including nuts and seeds); high intake of vegetables (excluding potatoes); low intake of meat and meat products (including eggs); and low-tomoderate intake of milk and dairy products. Sugars and syrups were not included in the calculation of the MDS, since no health implications had been documented for these foods, beyond their contribution to energy intake (Trichopoulou et al., 1995b). The MDS was calculated by using the cut-off point for each food component, representing the median intake specific for sex. Energy intake was adjusted to 10,460 kJ (2,500kcal) for men and 8,368 kJ (2,000 kcal) for women and a score of 1 or 0 was given for each of the food components depending on whether the cut-off point was met or not. Thus, a point was received if intake of protective components (vegetables, fruits, legumes, MUFA: SFA ratio and cereals) was at or above the sample median and below the median for nonprotective components (meat and dairy products). In the case of alcohol, a point was received if consumption was ≤10 g/day for men and 0 g/day for women. The scores for each individual food component were added to calculate the total score. Consequently, the total MDS range was 0 (minimal adherence) to 8 (maximum adherence), with a high score defined as ≥4, since it was a priori hypothesised that a diet with more of these components would have beneficial effects, whereas a diet with fewer of these components would be less healthy (Trichopoulou et al., 1995b). The same food components and food scoring system utilised for the MDS calculation were also used to examine adherence to the Mediterranean diet in seven other studies (de Groot et al., 1996; Kouris-Blazos et al., 1999; Lasheras et al., 2000; van Staveren et al., 2002; Bosetti et al., 2003; Papadaki & Scott, 2005; Knoops et al., 2006). In all these studies, the MDS ranged from 0 (lowest adherence to the Mediterranean diet) to 8 (highest adherence), with a high score defined as ≥4. However, in the study by van Staveren et al. (2002), a high score was defined as >3, and in the study by Bosetti et al. (2003) good adherence to the Mediterranean diet was reflected by a score of ≥6.

THE MEDITERRANEAN DIET SCORE- SECOND VARIANT (MDS-2) The original MDS did not include fish, since intake of this food group in the traditional Mediterranean diet depended on the proximity to the sea (Trichopoulou et al., 2003). To overcome this limitation, the original MDS was modified and a second version (MDS-2) was constructed in 2003, revising the MDS to include fish intake (Trichopoulou et al., 2003). The MDS-2 calculation followed the same pattern with the original MDS. Thus, a value of 0 or 1 was assigned to each of the nine indicated components with the use of the sexspecific median as the cut-off point. For beneficial components (vegetables, fruits and nuts, legumes, MUFA: SFA ratio, cereals -not including potatoes-, and fish), persons whose consumption was below the median were assigned a value of 0, and persons whose consumption was at or above the median were assigned a value of 1. For components presumed to be detrimental (meat products -not including eggs-, and dairy products, which are rarely nonfat or low-fat in Greece), persons whose consumption was below the median were assigned a value of 1, and persons whose consumption was at or above the median were assigned a value of 0. For ethanol, a value of 1 was assigned to men who consumed between

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10 and 50 g/day and to women who consumed between 5 and 25 g/day. Consequently, the total MDS-2 ranged from 0 (lowest adherence) to 9 (highest adherence to the Mediterranean diet), with a high score defined as ≥6 (Trichopoulou et al., 2003). The same food components and food scoring system utilised for the MDS-2 calculation were also used to examine adherence to the Mediterranean diet in eight other studies (Fidanza et al., 2004b; Psaltopoulou et al., 2004; Trichopoulou et al., 2005a; Trichopoulou et al., 2005b; Bach-Faig et al., 2006; Lagiou et al., 2006; Dalvi et al., 2007; Dixon et al., 2007). In all these studies, the total MDS-2 ranged from 0 (lowest adherence to the Mediterranean diet) to 9 (highest adherence), with a high score defined as >6 or ≥6.

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THE MEDITERRANEAN DIET SCORE- THIRD VARIANT (MDS-3) Both the MDS and MDS-2 used the ratio of monounsaturated-to-saturated fatty acids as one of the food components contributing to the total score, since in Greece, monounsaturated fatty acids (mainly derived from olive oil) are used in much higher quantities than polyunsaturated fatty acids. Thus, the MDS-2 (Trichopoulou et al., 2003) was modified to allow the score to be applied to non-Mediterranean populations, where intake of monounsaturates from olive oil is minimal. The resulting score (MDS-3) used the sum of unsaturated (monounsaturated and polyunsaturated) fatty acids, instead of only monounsaturated, as the numerator of the fat ratio (Trichopoulou et al., 2005c), since polyunsaturated fatty acids are the principal unsaturated added dietary lipids in nonMediterranean countries and have beneficial effects on coronary heart disease (de Lorgeril et al., 1994). In addition, the use of monounsaturated fatty acids alone when the score is calculated in non-Mediterranean countries would reportedly strongly depend on meat consumption, since meat is a principal source of monounsaturates in these areas (Trichopoulou et al., 2005c). The definition of cut-off points, and subsequent calculation of the MDS-3 was performed in the same manner as the MDS-2. Thus, similar to the MDS-2, the total MDS-3 ranged from 0 (lowest adherence) to 9 (highest adherence to the Mediterranean diet), with a high score defined as ≥6 (Trichopoulou et al., 2005c). The original MDS, along with the MDS-2 and MDS-3, are the most extensively used indexes due to their ease of application. Consequently, many variants of these scores have been created and evaluated among diverse populations in order to assess multiple diet-health relationships.

THE MEDITERRANEAN DIET SCORE- FOURTH VARIANT (MDS-4) In order to examine whether the results of the study by Trichopoulou et al. (1995b) could be replicated in a population from a Northern European country, the original MDS was adapted to account for the Danish food pattern (Osler & Schroll, 1997). This fourth variant of the MDS (MDS-4) involved seven dietary components, namely: high MUFA: SFA ratio; moderate ethanol consumption; high consumption of cereals; high consumption of fruits; high consumption of vegetables and legumes; low consumption of meat; and low consumption of

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milk and dairy products. The difference with the original MDS was that in the MDS-4 calculation, starchy roots (e.g. potatoes) were grouped with vegetables and not with cereals, and legumes were included in the vegetable group. Following adjustments for energy intake, the median values (g/day) for each component, specific for sex, were used as cut-off points, and a point of 1 or 0 was assigned depending on whether the median intake was met or not. The total MDS-4 range was 0-7 points, with a high score (better adherence) defined as ≥4 and a low score (low adherence) defined as ≤3 (Osler & Schroll, 1997).

THE MEDITERRANEAN DIET SCORE-FIFTH VARIANT (MDS-5) Woo et al. (2001) used the original MDS (Trichopoulou et al., 1995b) and the original median values, specific for sex, as the cut-off points for the scoring of each food component, in order to assess adherence to the Mediterranean diet among Chinese adults living in four diverse geographic regions. Thus, the total score was 8 for men. However, the authors noted that very few Chinese women consume alcohol. Ethanol consumption was therefore not included in the total MDS-5, so that a total score for women was equal to 7, instead of 8. A high score, representing a dietary pattern that is beneficial for cardiovascular health was defined as ≥4 for men and ≥3 for women (Woo et al., 2001). This study showed that a high MDS-5 was observed in the 35-54 age group (P P50 (2 g/day) < P75 (8 g/day) < ~P75 (130 g/day) P25-P75 (159-465 g/day)

Source: (van Staveren et al., 2002). Reprinted with permission from Cambridge University Press P25, P50, P75: 25th, 50th (median) and 75th percentiles.

THE MEDITERRANEAN DIETARY PATTERN ADHERENCE INDEX The Mediterranean Dietary Pattern Adherence Index differed from all other indexes assessing adherence to the Mediterranean diet in that its calculation involved the summing of standardised residuals of nutrients and foods after adjusting a regression model using total energy intake as the independent variable (i.e. the index calculated a value of adherence as a percentage) (Sánchez-Villegas et al., 2002). The index took into account the consumption of 9 food components and it was calculated as follows: 1

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2 3 4

5

Daily intakes of legumes, cereals (including bread and potatoes), fruits, vegetables, meat (including meat products), and milk (including dairy products) were adjusted for energy intake; The energy-adjusted intakes of the above food groups were standardised as a z values [(observed - mean)/standard deviation]; The MUFA: SFA ratio and the intake of trans fatty acids (TRANS) were also directly standardised as a z values; ‗Moderate‘ alcohol consumption was scored based on a transformation centred at the level of consuming 30 g/day for men [30 - (30 - absolute alcohol intake)], and 20 g/day for women [20 - (20 - absolute alcohol intake)], which was used to obtain the highest value for men consuming 30 g/day or women consuming 20 g/day, and progressive lower values as the consumption was lower or higher than these values. These transformations of alcohol intake were also standardised as z values; and The index considered legumes, cereals, fruits, vegetables, moderate alcohol consumption and MUFA/SFA ratio to be beneficial components and meat, dairy products and trans fatty acids to be detrimental components:

ΣZi = Zlegumes + Zcereals + Zfruit + Zvegetables + Zalcohol + ZMUFA: SFA - ZTRANS - Zmeat and products Zmilk and products Thus, a relative percentage of adherence was calculated, using the range of values of the sample, following the equation:

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Adherence (Percentagei) = [(ΣZi - ΣΖmin) x 100] / (ΣZmax - ΣΖmin) A participant with a maximum value of adherence obtained 100% of adherence. A participant with a minimum value of adherence obtained 0% in the relative percentage. This index was applied in a cohort study of Spanish University students, in order to identify lifestyle and socioeconomic characteristics associated with the consumption of a Mediterranean dietary pattern. The results suggested a progressive abandonment of the traditional Mediterranean diet in younger individuals. In addition, women and individuals who led an active lifestyle had greater adherence to this eating pattern (Sánchez-Villegas et al., 2002).

THE MEDITERRANEAN DIETARY PATTERN ADHERENCE INDEX- SECOND VARIANT The second variant of the Mediterranean Dietary Pattern Adherence Index created by Sánchez-Villegas et al. (2002) involved slight modifications in the food components involved but utilised the same scoring pattern (Tur et al., 2004). In particular, nuts were included with fruits, trans fatty acids were excluded and fish consumption was added as a component contributing to the index. Similar to the original index, the total variant index was computed by adding up all the z values obtained for the beneficial food components and subtracting the z values obtained for the consumption of the detrimental components:

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ΣZi = Zlegumes + Zcereals and roots + Zfruit and nuts + Zvegetables + Zfish + Zmoderate alcohol + ZMUFA: SFA Zmeat and products - Zmilk and products A relative percentage of adherence, using the range of values of the sample, was calculated, ranging from 100 (maximum adherence) to 0 (minimum adherence): Adherence (Percentagei) = [(ΣZi - ΣΖmin) x 100] / (ΣZmax - ΣΖmin) This variant was utilised in a cross-sectional survey assessing the influence of lifestyle and socioeconomic characteristics on Mediterranean diet adherence among the population of the Balearic Islands (Tur et al., 2004). It has also been used in a study examining the effect of Mediterranean diet adherence on biomarkers of diet and disease (Bach-Faig et al., 2006). The findings of the former study showed that men, older and more active individuals were more likely to adhere to the Mediterranean diet (Tur et al., 2004).

THE OLDWAYS MEDITERRANEAN DIET PYRAMID SCORE The Oldways Mediterranean Diet Pyramid Score was based on the 11 food components of the Mediterranean Diet Pyramid created by the Oldways Preservation Trust (Goulet et al., 2003; Goulet et al., 2007). The foods included: grains, fruits, vegetables, legumes, nuts and

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seeds, olive oil, dairy products, fish, poultry, eggs, sweets and red meat/ processed meat. A partial score of 0 to 4 was attributed to each food component, with the total score ranging from 0 (lowest adherence to the Mediterranean diet) to 44 (highest adherence) points. Foods found at the base of the pyramid (grains, fruits, vegetables, legumes, nuts and seeds, olive oil, and fish) received a high score when consumed frequently. In contrast, food components found at the top of the pyramid (meats, sweets, and eggs) were assigned a high score when consumed less frequently (Goulet et al., 2003). For dairy products, an intake of 2-3 portions/ day was considered as a typical Mediterranean intake and 4 points were assigned for such an intake. For poultry, 4 points were assigned when the mean intake was 3 portions/ week (Table 7). The same food components and food scoring system utilised for the calculation of the Oldways Mediterranean Diet Pyramid Score were also used to examine adherence to the Mediterranean diet in one other study (Dalvi et al., 2007).

THE MEDITERRANEAN DIET PATTERN SCORE The calculation of the Mediterranean Diet Pattern Score was based on the consumption of 14 food components, according to their potential beneficial or harmful influence on coronary heart disease risk (Ciccarone et al., 2003). Thus, this score was developed by assigning 1 point for foods with sufficient evidence of their beneficial effect on CHD (cooked vegetables, raw vegetables, carrots, fruits, fish, and olive oil). Zero points were assigned for foods that have potentially harmful effects (eggs, meat, processed meats, cheese, vegetable oils, butter, milk cream, and margarine). A high score was defined as ≥11.

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THE MEDITERRANEAN DIETARY SCORE Another score assessing adherence to the Mediterranean diet was created according to the Mediterranean Diet Pyramid suggested by a Harvard-led group (Willett et al., 1995). The Mediterranean Dietary Score contained 11 components and was calculated according to the placement of these foods in the Pyramid and taking into account the median value of the average monthly intake. Based on the Pyramid, the dietary pattern consists of: 1

2

3

daily consumption of: non-refined cereals and products (wholegrain bread, pasta, brown rice, etc.), vegetables (2-3 servings/day), fruits (4-6 servings/day), olive oil (as the main added lipid) and non-fat or low-fat dairy products (1-2 servings/day); weekly consumption of: fish (4-5 servings/week), poultry (3-4 servings/week), olives, pulses, and nuts (3 servings/week), potatoes, and less frequently eggs, and sweets (1-3 servings/week); and monthly consumption of: red meat and meat products (4-5 servings/month).

The diet is also characterised by moderate consumption of wine (1-2 wineglasses/day). The frequency of consumption was quantified according to the number of times/month each food component was consumed. Each food was assigned a score of 0 to 5 points (higher

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scores were assigned for frequent consumption of foods present at the bottom of the Pyramid, which are commonly consumed in the Mediterranean diet, and lower scores for frequent consumption of foods at the top of the Pyramid, which are consumed less frequently in the traditional diet), resulting in a total score that ranged from 0 (lowest adherence to the Mediterranean diet) to 55 (highest adherence) (Panagiotakos et al., 2003; Chrysohoou et al., 2004; Panagiotakos et al., 2004). In particular, for the consumption of items presumed to be close to this pattern (i.e., those suggested on a daily basis or more than 4 servings/week), a score of 0 was assigned when a participant reported no consumption, a score of 1 for consumption of 1-4 times/month, 2 for 5-8 times/month, 3 for 9-12 times/month, 4 for 13-18 times/month, and 5 when consumption was more than 18 times/month. On the other hand, for the consumption of foods presumed not to closely adhere to this diet (e.g. meat and dairy products), the opposite scores were assigned (i.e., a score of 0 when a participant reported almost daily consumption and a score of 5 when there was no consumption or when a food was consumed rarely). With regards to alcohol, a score of 5 was assigned for consumption of 2 portions/day

4 portion/day Never

4 portions/day

1 portion/day

2-3 portions/day

< 1 portion/week

1 portion/week

2 portions/week

≥ 3 portions/week

Never

< 1 portion/week

2 portions/week

3 portions/week

≥ 7/week ≥ 7 times/week ≥ 7 portions/week

5-6 times/week 5-6 portions/week

1 or ≥4 portions/week 5-6/week 3-4 times/week 3-4 portions/week

1-2 times/week 1-2 portions/week

0-4/week < 1/week < 1 portion/week

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Source: (Goulet et al., 2003). Reprinted with permission from Elsevier. http://www.sciencedirect.com/science/journal/00219150

0067.

Table 8. Construction of the Mediterranean Dietary Score Score criteria: frequency of consumption in servings/month (or otherwise stated) Non-refined cereals (whole grain bread, pasta, rice, etc) Potatoes Fruits Vegetables Legumes Fish Red meat and products Poultry Full fat dairy products (cheese, yoghurt, milk) Use of olive oil in cooking (times/week) Alcoholic beverages (ml/day, 100 ml=12 g ethanol)

0

1

2

3

4

5

Never

1-6

7-12

13-18

19-31

>32

Never Never Never Never Never >10 >10 >30

1-4 1-4 1-6 22 >33 >6 >6 ≤1 ≤3 ≤10

Never

Rare

700 or 0

600-700

500-600

400-500

300-400

8 indicated the optimal Mediterranean diet, whereas a score of 4-7 indicated a need for improvement, and a score of ≤3 suggested a very low diet quality (Serra-Majem et al., 2004a). When diet was evaluated using this index it was shown that adherence to the Mediterranean diet was greater in children from higher socioeconomic classes, larger cities, and northeast areas of Spain, when compared to northern areas (Serra-Majem et al., 2004a).

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Table 10. Construction of the KIDMED index Scoring +1 +1 +1 +1 +1 -1 +1 +1 +1 +1 +1 -1 +1 -1 +1 -1

Questions on Mediterranean diet quality Takes a fruit or fruit juice every day Has a second fruit every day Has fresh or cooked vegetables regularly once a day Has fresh or cooked vegetables more than once a day Consumes fish regularly (at least 2-3 times per week) Goes more than once a week to a fast-food (hamburger) restaurant Likes pulses and eats them more than once a week Consumes pasta or rice almost every day (5 or more times per week) Has cereals or grains (bread, etc.) for breakfast Consumes nuts regularly (at least 2–3 times per week) Uses olive oil at home Skips breakfast Has a dairy product for breakfast (yoghurt, milk, etc.) Has commercially baked goods or pastries for breakfast Takes two yoghurts and/or some cheese (40 g) daily Takes sweets and candy several times every day

Source: (Serra-Majem et al., 2004a). Reprinted with permission from Cambridge University Press.

THE KIDMED INDEX- SECOND VARIANT (KIDMED-2) An adaptation of the original KIDMED index (Serra-Majem et al., 2004a) was created and applied in a population of children in Crete (Chatzi et al., 2007). The KIDMED-2 included 12 items: one fruit or fruit juice daily; two or more fruits daily; one vegetable daily; two or more vegetables daily; fish (≥2 times per week); cereals for breakfast daily; brown bread daily; one dairy product daily; two or more dairy products daily; nuts (≥3 times per week) (positive components); margarine > once/week and red meat > white meat (consumption per week) (detrimental components). In this modified variant, olive oil intake was not included in the total score, since olive oil is the principal source of fat in all Cretan families (Hassapidou et al., 1996). In addition, consumption of fast foods, sweets, and legumes were not considered in the score calculation,

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Angeliki Papadaki and Manolis Linardakis

since these food items were not included in the diet questionnaire used in the study (Chatzi et al., 2007). Weekly consumption of dietary compounds positively associated with the Mediterranean diet was assigned a value of +1, whereas weekly consumption of compounds with a negative association was assigned a value of -1. Weekly consumption of more red than white meat was considered a detrimental component and was assigned a value of -1. Thus, the total KIDMED-2 ranged from 0 to 10 points, with a score of ≥6 indicating the optimal Mediterranean diet, a score of 4-5 indicating a medium-quality Mediterranean diet, and a score of ≤3 suggesting a low-quality Mediterranean diet.

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THE KIDMED INDEX- THIRD VARIANT (KIDMED-3) A second adaptation of the KIDMED index was created following the exclusion of two questions concerning breakfast intake (skipping breakfast and consumption of baked goods/ pastries for breakfast). In addition, the KIDMED-3 did not specify whether fast foods (hamburgers) were prepared at home or at a fast-food restaurant (Chatzi et al., 2008). The KIDMED-3 included 14 items: fruit or fruit juice daily; second serving of fruit daily; fresh or cooked vegetables daily; fresh or cooked vegetables (>1/day); legumes (≥1/week); regular fish consumption (at least 2–3 times per week); cereals for breakfast (≥1/day); pasta or rice almost daily (≥5/week); dairy product (milk, yogurt or cheese) daily; two dairy products daily; regular nut consumption (2-3 times per week); use of olive oil at home daily (positive components); fast food consumption (hamburger) >1/week and sweets-pastries (≥1/day) (detrimental components). The scoring system followed the same pattern with the original KIDMED index (SerraMajem et al., 2004a). The total KIDMED-3 ranged from -2 to 12 points, with a score of ≥ 7 indicating the optimal Mediterranean diet, a score of 4-6 indicating a medium-quality Mediterranean diet, and a score of ≤3 suggesting a low-quality Mediterranean diet (Chatzi et al., 2008). Table 11. Construction of the Med-DQI Score

SFA (% energy)

Cholesterol (mg)

Meats (g)

Olive oil (ml)

Fish (g)

Cereals (g)

Vegetables + fruit (g)

0 1

700 700-400

>13

>400

>60 6030 300 300-100

2

125