Eating Disorders 3031166906, 9783031166907

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Vinood B. Patel Victor R. Preedy Editors

Eating Disorders

Eating Disorders

Vinood B. Patel • Victor R. Preedy Editors

Eating Disorders With 147 Figures and 125 Tables

Editors Vinood B. Patel School of Life Sciences University of Westminster London, UK

Victor R. Preedy School of Life Course and Population Sciences Faculty of Life Sciences and Medicine King’s College London London, UK

ISBN 978-3-031-16690-7 ISBN 978-3-031-16691-4 (eBook) https://doi.org/10.1007/978-3-031-16691-4 © Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Dedicated to Adrianne Bendich for her unfailing support, encouragement, and advice.

Preface

Eating disorders can profoundly affect the individual, family unit, and local community. Changes in the individual include disturbances in body perception, organ damage, and increased risk factors leading to ill-health in later years. The family unit is affected by the psychological burdens imposed by eating disorders, including increased anxiety and depression in siblings or spouses. There is also the cost burden to consider: for example, in some countries, without a free health service, family members or insurance underwriters are expected to pay for treatments. Local communities are saddled with poor productivity, reduced attainment, and discordant interactions with colleagues and friends. There is thus a fundamental requirement to adequately diagnose, treat, and manage those individuals with eating disorders. However, this is problematic as there are many types of eating disorders, which the American Psychiatric Association have recently categorized (DSM-5) into Anorexia Nervosa, Bulimia Nervosa, Binge Eating Disorder, Other Specified and Unspecified Feeding or Eating Disorders. The categorization of Binge Eating Disorders is new and the previous category of Eating Disorders Not Otherwise Specified has been removed from DSM-5. Nevertheless, in some circumstances, there is continual usage of old terminology, and some groups use their own categorizations. There are numerous types of instruments and questionnaires which are used for categorizing or studying eating disorders. Some have been rigorously scrutinized and tested, whereas others are new and may eventually become “gold standard” instruments. Treatment regimens are also varied as there are complex relationships between physiological, nutritional, and psychological facets of eating disorders. Treatment protocols can include nutritional supplements or psychobehavioral modifications but will of course depend on the consequences of the eating disorder. In some cases, organs are directly affected, growth is impacted, and fetuses compromised in utero. Treatment regimens can address the multiple concerns, involving both psychiatry and dietetics. It is thus apparent that there is a wide range of eating disorders, methods of diagnoses, and treatments. The impact of eating disorders are extensive. Thus, finding all the relevant information in a single coherent publication has hitherto

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Preface

been problematic since there is a wide range of material. This, however, is comprehensively addressed in Handbook of Eating Disorders which embraces a holistic approach. It has six main parts: 1. 2. 3. 4. 5. 6.

General Aspects, Overviews, and Setting the Scene Anorexia Nervosa Bulimia Nervosa Binge Eating Disorder Other Specified and Unspecified Feeding or Eating Disorders Diagnosis, Delective Questionnaires, and Resources

There are unique features in each chapter, with sub-sections on the following: • • • •

Applications to Other Eating Disorders Key Facts Mini-Dictionary of Terms Summary Points

Applications to Other Eating Disorders is particularly important as it highlights the translational aspect of research into eating disorders; their causes, impact, and treatments. Key Facts give important information about individual components in each chapter. The Mini-Dictionary of Terms is suited for both the non-expert and also those working in other fields or areas. Summary Points encapsulate the entire chapter in brief sets of simple sentences. Handbook of Eating Disorders is designed for dieticians, nutritionists, psychologists, healthcare workers, and research scientists. The audience is multi-intellectual: from undergraduates, masters, and doctoral students to research scientists, lecturers, professors, and heads of groups. Contributions are from leading national and international experts including those from world renowned institutions. London, UK

Vinood B. Patel Victor R. Preedy The Editors

Contents

Volume 1 Part I 1

General Aspects, Overviews, and Setting the Scene . . . . . . .

1

Enhanced Cognitive Behavior Therapy for Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Riccardo Dalle Grave

3

2

Eating Disorders During Pregnancy . . . . . . . . . . . . . . . . . . . . . . . . Maria G. Grammatikopoulou, Konstantinos Gkiouras, Tonia Vassilakou, and Dimitrios G. Goulis

25

3

Eating Habits During Pregnancy . . . . . . . . . . . . . . . . . . . . . . . . . . Irene Cetin, Chiara Bianchi, and Arianna Laoreti

37

4

Stress and Disordered Eating Patterns . . . . . . . . . . . . . . . . . . . . . . Fotini Tsofliou, Chloe Casey, and Christina Hughes

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5

Gene Variants Involved in the Etiopathogenesis of Eating Disorders: Neuropeptides, Neurotransmitters, Hormones, and Their Receptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maria Rachele Ceccarini, Matteo Bertelli, Elisabetta Albi, Laura Dalla Ragione, and Tommaso Beccari

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6

Genes and Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Beatriz Camarena and Sandra Hernández-Muñoz

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7

Eating Disorders in Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Melda Pelin Yargic and Faik Ozdengul

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8

Eating Disorders in Children and Adolescents with Attention Deficit Hyperactivity Disorder . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zahra Saif and Haitham Jahrami

9

Insomnia in Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kara A. Christensen, Ellen Klaver, and Nicole A. Short

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10

Uric Acid Levels and Eating Disorders . . . . . . . . . . . . . . . . . . . . . Tanya Goltser Dubner, Ruth Giesser, Amit Shalev, Shikma Keller, Ronen Segman, and Esti Galili-Weisstub

11

The Virtually Delivered Body Project (vBP): A Viable Option for Large-Scale Prevention of Eating Disorders . . . . . . . . . Ata Ghaderi

12

Time-Related Changes in Eating Disorders . . . . . . . . . . . . . . . . . . Tomoko Harada, Dai Miyawaki, and Tsuneo Yamauchi

13

The Connection Between Eating Disorders and Substance Use Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kimberly Claudat, Courtney C. Simpson, Brittany K. Bohrer, and Gina M. Bongiornio

14

Fluid Restriction in Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . Elizabeth Hamlin

15

Features of Medical Consultations Before the Onset of Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Francisco Ruiz Guerrero, Leticia Castro Fuentes, Carla Cobo Gutierrez, Cristina Hernández Jimenez, and Andrés Gómez del Barrio

16

The Role of Parents and Other Caregivers in the Early Detection of Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anna Ciao, Summer Pascual, and Gabbrielle Hodges

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Alexithymia in Eating Disorders: A Narrative Review . . . . . . . . . Cecilia Serena Pace, Stefania Muzi, and Wanda Morganti

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18

Eating Disorder and Quality of Life . . . . . . . . . . . . . . . . . . . . . . . . Jelena Milic, Dunja Stankic, and Dona Stefanovic

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19

The Role of Denial in Eating Disorder Development, Assessment, and Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lindsay M. Howard, Anna K. Olson, Brianna N. Pitz, and Kristin E. Heron

20

The Role of the Dietitian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Caitlin M. McMaster, Janet Franklin, Melissa Hart, Kylie MatthewsRensch, Kirrilly Pursey, and Susan Hart

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Contents

Part II 21

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Anorexia Nervosa

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A Research Approach to Self-Report and Objective Measurements of Physical Activity in Eating Disorders . . . . . . . . . Olivia Wons, Elizabeth Lampe, Laura Boyajian, Anna Gabrielle Patarinski, and Adrienne Juarascio

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22

Body Mass Index and Body Fat in Anorexia Nervosa . . . . . . . . . . Marwan El Ghoch

439

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Modeling Anorexia Nervosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maria Scherma, Roberto Collu, Simona Dedoni, Walter Fratta, and Paola Fadda

451

24

Anorexia Nervosa and Impact After Three Decades . . . . . . . . . . . Elisabet Wentz

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Linking Anorexia Nervosa with the Gut Microbiota . . . . . . . . . . . Radka Roubalova, Petra Prochazkova, and Hana Papezova

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Gender Aspects of Anorexia Nervosa: the Male . . . . . . . . . . . . . . . Hiral Kotadia

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The Biology of Anorexia Nervosa . . . . . . . . . . . . . . . . . . . . . . . . . . Kamil Skowron, Magdalena Kurnik-Łucka, and Krzysztof Gil

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The Hippocampus in Anorexia Nervosa . . . . . . . . . . . . . . . . . . . . . Enrico Collantoni, Valentina Meregalli, Elena Tenconi, Meneguzzo Paolo, and Angela Favaro

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Endocrine Disturbances in Anorexia Nervosa . . . . . . . . . . . . . . . . Magnus Sjögren

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Anorexia Nervosa and Eye Movements . . . . . . . . . . . . . . . . . . . . . Andrea Phillipou

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Anorexia Nervosa: Reproduction and Consequences for Mother and Child . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ängla Mantel and Angelica Lindén Hirschberg

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Anorexia Nervosa in the Acute Hospitalization Setting . . . . . . . . . Matteo Martini, Marta Lepora, Paola Longo, Laura Amodeo, Enrica Marzola, and Giovanni Abbate-Daga

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Anorexia Nervosa and Comorbidities . . . . . . . . . . . . . . . . . . . . . . . Antonia Parmeggiani and Jacopo Pruccoli

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The Electrocardiogram in Anorexia Nervosa . . . . . . . . . . . . . . . . . Mikyla Janzen, Julia Raudzus, and Andrew Krahn

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Anorexia Nervosa and Concurrent Psychiatric Comorbidity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gennaro Catone

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Volume 2 Part III

Bulimia Nervosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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The Growth Hormone-IGF-1 Axis in Anorexia Nervosa . . . . . . . . Anamil Khiyami and Pouneh K. Fazeli

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Relationship Between Bulimia Nervosa and Psychological Problems in Period of Adolescence . . . . . . . . . . . . . . . . . . . . . . . . . Gordana Stankovska, Imran Memedi, and Nexhibe Nuhii

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Visuospatial Abilities in Eating Disorders . . . . . . . . . . . . . . . . . . . Elena Tenconi, Valentina Meregalli, Paolo Meneguzzo, Enrico Collantoni, and Angela Favaro

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Androgens and Their Role in Bulimia Nervosa and Eating Disorder Not Otherwise Specified of Purging Type (EDNOS-P) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sabine Naessén

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Bulimic Symptomatology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ana Paula Hermont, Isabela Almeida Pordeus, and Sheyla Márcia Auad

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Emotion Regulation in Bulimia Nervosa and Purging Disorder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Danielle E. MacDonald, Shauna Solomon-Krakus, Rachel Jewett, Rachel E. Liebman, and Kathryn Trottier

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723 747

767 785

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Pharmacology Options for Bulimia Nervosa . . . . . . . . . . . . . . . . . Aaron Keshen, Susan Gamberg, Sara Bartel, Victoria Taylor, Shannon Smith, Victoria Brown, and Anastasia Harris

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Linking Embodiment Disorder and Bulimia Nervosa . . . . . . . . . . Livio Tarchi, Eleonora Rossi, Marco Faldi, Emanuele Cassioli, Valdo Ricca, and Giovanni Castellini

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Treating Adolescent Bulimia Nervosa . . . . . . . . . . . . . . . . . . . . . . . Sasha Gorrell, Leigh Brosof, Lisa Hail, and Daniel Le Grange

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Contents

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A Narrative Review on the Dual Pathway Model of Bulimic Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Isabel Krug, Francis Puccio, Jade Potingale, and An Binh Dang

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Bulimia Nervosa: Reproduction and Consequences for Mother and Child . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ängla Mantel and Angelica Lindén Hirschberg

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Binge Eating Disorder

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Long-Term Outcome of Inpatients and Outpatients with Bulimia Nervosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Norbert Quadflieg

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Parental Care and Binge-Eating Disorder . . . . . . . . . . . . . . . . . . . Federico Amianto and Benedetto Vitiello

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DeltaFosB and Preclinical Binge Eating . . . . . . . . . . . . . . . . . . . . . Richard Quansah Amissah and Igor Timofeev

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Characterization of Binge Eating Days in Daily Life . . . . . . . . . . . 1003 Julia Reichenberger, Ann-Kathrin Arend, and Jens Blechert

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Cancer and Binge Eating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1025 Anna Dolgon-Krutolow and Tyler B. Mason

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Fat Mass and Obesity-Related Gene (FTO) and Binge Eating Disorder in Adults and Adolescents . . . . . . . . . . . . . . . . . . . . . . . . 1043 Luzia Jaeger Hintze, Éric Doucet, and Gary S. Goldfield

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Neuroimaging in Binge Eating Disorder . . . . . . . . . . . . . . . . . . . . . 1063 Serkan Turan

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Binge Eating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1083 Fabiana Salatino Fangueiro and Patrícia Colombo-Souza

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Linking Sleep Deprivation and Binge Eating: Empirical Evidence and Underlying Mechanisms . . . . . . . . . . . . . . . . . . . . . . 1103 Silvia Cerolini

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The Criterion B Binge-Eating Symptoms . . . . . . . . . . . . . . . . . . . . 1121 Brianne N. Richson, Kayla A. Bjorlie, Danielle A. N. Chapa, and Kelsie T. Forbush

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Contents

Part V Other Specified and Unspecified Feeding or Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Cognitive-Behavioral Therapy and Purging Disorder . . . . . . . . . . 1143 Zaida Agüera, Isabel Baenas-Soto, and Fernando Fernández-Aranda

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Purging Disorder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1157 Sarrah I. Ali, Sophie R. Abber, and Pamela K. Keel

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Purging Disorder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1173 Rachel E. Liebman, Vincent A. Santiago, Sarah Mccomb, Danielle E. MacDonald, and Kathryn Trottier

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Body Weights and Mass and Links with Nighttime Eating . . . . . . 1191 Cigdem Koroglu and Leslie J. Baier

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Night Eating Syndrome and Network Analysis of Features . . . . . . 1207 Marshall T. Beauchamp

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Avoidant/Restrictive Food Intake Disorder in Children . . . . . . . . . 1235 Yaara Shimshoni and Eli R. Lebowitz

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The Brain in Prader-Willi Syndrome . . . . . . . . . . . . . . . . . . . . . . . 1261 Kenichi Yamada

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Behavioral Phenotype of Patients with Prader-Willi Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1287 Maja Krefft and Maria Libura

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Body Dysmorphic Disorder: Links with Eating Disorders and Gender-Related Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1305 Amy Malcolm

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Orthorexic Eating and Addictions: Links with Substance Use, Behavioral Addictions, and Research Gaps . . . . . . . . . . . . . . . . . . 1327 Jana Strahler, Lillith Moser, and Hanna Wachten

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Linking Orthorexia and Obsessive-Compulsive Symptoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1353 Lut Tamam and Hamdi Yılmaz

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Cardiac Vagal Imbalance and Emotional Eating . . . . . . . . . . . . . . 1381 Nerkis Fuentes, Gabriela Nazar, and Miguel Enrique SánchezHechavarría

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Biologic Aspects of Rumination Syndrome, Eosinophils, and Beyond . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1399 Hunter J. Friesen, Jennifer V. Schurman, and Craig A. Friesen

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Picky Eating in Normally Developing Children and Young Adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1417 Ada H. Zohar

Contents

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Part VI Diagnosis, Delective Questionnaires, and Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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. . . . . . . . . . . . . 1435

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Assessing Orthorexia Nervosa by Questionnaires Melda Pelin Yargic and Murat Cenk Celen

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The Eating Disorder Quality of Life (EDQoL) Scale . . . . . . . . . . . 1451 Paolo Meneguzzo, Enrico Collantoni, Valentina Meregalli, Elena Tenconi, and Angela Favaro

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Binge Eating Scoring Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1465 Natália Luiza Kops and Rogério Friedman

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Conceptualizing and Evaluating the Healthy Orthorexia Dimension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1479 Wanderson Roberto da Silva, Angela Nogueira Neves, Giovanna Soler Donofre, Steven Bratman, Paula Costa Teixeira, and Juliana Alvares Duarte Bonini Campos

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The Binge Eating Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1503 Sagar Karia, Shorouq Motwani, and Avinash Desousa

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Health-Related Quality of Life Questionnaires . . . . . . . . . . . . . . . . 1517 Jelena Milic, Dunja Stankic, and Dona Stefanovic

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Resources in Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1529 Rajkumar Rajendram, Daniel Gyamfi, Vinood B. Patel, and Victor R. Preedy

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1541

About the Editors

Vinood B. Patel, BSc, PhD, FRSC, is currently Reader in Clinical Biochemistry at the University of Westminster. He presently directs studies on metabolic pathways involved in liver disease, particularly related to mitochondrial energy regulation and cell death. Research is being undertaken to study the role of nutrients, antioxidants, phytochemicals, iron, alcohol, and fatty acids in the pathophysiology of liver disease. Other areas of interest are identifying new biomarkers that can be used for the diagnosis and prognosis of liver disease and understanding mitochondrial oxidative stress in Alzheimer’s disease and gastrointestinal dysfunction in autism. Dr. Patel graduated from the University of Portsmouth with a degree in Pharmacology and completed his PhD in protein metabolism from King’s College London in 1997. His postdoctoral work was carried out at Wake Forest University Baptist Medical School studying structural-functional alterations to mitochondrial ribosomes, where he developed novel techniques to characterize their biophysical properties. In 2014, he was elected as a Fellow to The Royal Society of Chemistry. Dr. Patel is a nationally and internationally recognized researcher and was involved in several NIH-funded biomedical grants related to disease. Dr. Patel has edited biomedical books in the area of diet, nutrition, and health prevention. He has published over 150 articles. Victor R. Preedy, BSc, PhD, DSc, FRSB, FRSPH, FRCPath, FRSC, is Emeritus Professor of Nutritional Biochemistry at King's College London. He is also Professor of Clinical Biochemistry and Pathology at Kings College Hospital (Hon) and Honorary Professor at the University of Hull. He was Director of the Genomics Centre of King’s College London from 2003 to 2020. Professor Preedy has an Honours Degree in Biology and Physiology with Pharmacology. He gained his University of London PhD on protein metabolism and later gained his second doctorate (DSc) for his outstanding contribution to protein metabolism in health and disease. Professor Preedy has been elected as a Fellow to The Royal College of Pathologists, The Royal Society for the Promotion of Health, The Royal Institute of Public Health, The Royal Society for Public Health, The Royal Society of Chemistry, and The Royal Society of Medicine. Professor Preedy has carried out research at the National Heart Hospital (part of Imperial College London), The School of xvii

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About the Editors

Pharmacy (now part of University College London), and the MRC Centre at Northwick Park Hospital. Prof Preedy is a leading expert on the science of health and has a long-standing interest in diet, nutrition, and disease. He has lectured nationally and internationally. To his credit, Professor Preedy has published over 750 articles, which includes peer-reviewed manuscripts based on original research, abstracts and symposium presentations, reviews, and numerous books and volumes.

Contributors

Giovanni Abbate-Daga Eating Disorders Center, Department of Neuroscience, University of Turin, Turin, Italy Sophie R. Abber Department of Psychology, Florida State University, Tallahassee, FL, USA Zaida Agüera Departament d’Infermeria de Salut Pública, Salut Mental i Maternoinfantil, Escola d’Infermeria, Facultat de Medicina i Ciéncies de la Salut (UB). Psychoneurobiology of Eating and Addictive Behaviors Group, Neurosciences Programme (IDIBELL), University of Barcelona, IDIBELL and CIBEROBN, Barcelona, Spain Elisabetta Albi Department of Pharmaceutical Science, University of Perugia, Perugia, Italy Sarrah I. Ali Department of Psychology, Florida State University, Tallahassee, FL, USA Juliana Alvares Duarte Bonini Campos Department of Biological Sciences, Graduate Program in Food, Nutrition and Food Engineering, School of Pharmaceutical Sciences, São Paulo State University (UNESP), Araraquara, Brazil Federico Amianto Department of Neurosciences, University of Torino, Torino, Italy Laura Amodeo Eating Disorders Center, Department of Neuroscience, University of Turin, Turin, Italy Ann-Kathrin Arend Department of Psychology, Centre for Cognitive Neurosciences, Paris-Lodron University of Salzburg, Salzburg, Austria Sheyla Márcia Auad Department of Pediatric Dentistry, Faculty of Dentistry, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil Isabel Baenas-Soto Department of Psychiatry, Psychoneurobiology of Eating and Addictive Behaviors Group, Neurosciences Programme (IDIBELL), Bellvitge University Hospital–IDIBELL and CIBEROBN, Barcelona, Spain xix

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Contributors

Leslie J. Baier Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, USA Sara Bartel Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada Marshall T. Beauchamp Applied Psychological Science Program, School of Graduate Psychology, Pacific University, Hillsboro, OR, USA Tommaso Beccari Department of Pharmaceutical Science, University of Perugia, Perugia, Italy Matteo Bertelli MAGI EUREGIO, Bolzano, Italy Chiara Bianchi Department of Biomedical and Clinical Sciences “L. Sacco”, Unit of Obstetrics and Gynecology, ASST Fatebenefratelli Sacco – Buzzi Children’s Hospital, University of Milan, Milan, Italy Kayla A. Bjorlie Department of Psychology, University of Kansas, Lawrence, KS, USA Jens Blechert Department of Psychology, Centre for Cognitive Neurosciences, Paris-Lodron University of Salzburg, Salzburg, Austria Brittany K. Bohrer Eating Disorders Center for Treatment and Prevention, Department of Psychiatry, UC San Diego Health, San Diego, CA, USA Gina M. Bongiornio Eating Disorders Center for Treatment and Prevention, Department of Psychiatry, UC San Diego Health, San Diego, CA, USA Laura Boyajian Center for Weight Eating and Lifestyle Science (WELL Center), Drexel University, Philadelphia, PA, USA Steven Bratman Albany, NY, USA Leigh Brosof Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA Victoria Brown Department of Psychiatry, Dalhousie University, Halifax, NS, Canada Beatriz Camarena Departamento de Farmacogenética, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City, Mexico Chloe Casey Department of Rehabilitation and Sport Sciences, Faculty of Health and Social Sciences, Bournemouth University, Bournemouth, UK Emanuele Cassioli Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy Giovanni Castellini Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy

Contributors

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Gennaro Catone Department of Educational, Psychological and Communication Sciences, Suor Orsola Benincasa University, Naples, Italy Maria Rachele Ceccarini Department of Pharmaceutical Science, University of Perugia, Perugia, Italy Murat Cenk Celen Department of Biophysics, Ankara Medipol University, Ankara, Turkey Silvia Cerolini Department of Psychology, Sapienza University of Rome, Rome, Italy Irene Cetin Department of Biomedical and Clinical Sciences “L. Sacco”, Unit of Obstetrics and Gynecology, ASST Fatebenefratelli Sacco – Buzzi Children’s Hospital, University of Milan, Milan, Italy Danielle A. N. Chapa Department of Psychology, University of Kansas, Lawrence, KS, USA Kara A. Christensen Department of Psychology, University of Nevada, Las Vegas, Las Vegas, NV, USA Anna Ciao Western Washington University, Bellingham, WA, USA Kimberly Claudat Eating Disorders Center for Treatment and Prevention, Department of Psychiatry, UC San Diego Health, San Diego, CA, USA Enrico Collantoni Department of Neurosciences, University of Padua, Padova, Italy Padua Neuroscience Center, University of Padua, Padova, Italy Roberto Collu Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA Patrícia Colombo-Souza Post Graduation Program in Health Science, Santo Amaro University, Sao Paulo, SP, Brazil Paula Costa Teixeira Neuroscience and Behavior Department, University of São Paulo’s Psychology Institute (USP), São Paulo, Brazil AMBULIM – Eating Disorder Department, University of São Paulo’s Psychiatry Institute (IPq-HC-FMUSP), São Paulo, Brazil Wanderson Roberto da Silva Graduate Program in Food, Nutrition and Food Engineering, School of Pharmaceutical Sciences, São Paulo State University (UNESP), Araraquara, Brazil Graduate Program in Nutrition and Longevity, School of Nutrition, Federal University of Alfenas (UNIFAL-MG), Alfenas, Brazil Laura Dalla Ragione Food Science and Human Nutrition Unit, University Campus Biomedico of Rome, Rome, Italy

xxii

Contributors

Riccardo Dalle Grave Department of Eating and Weight Disorders, Villa Garda Hospital, Garda, Italy An Binh Dang Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia Simona Dedoni Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy Andrés Gómez del Barrio Department of Psychiatry, Marqués de Valdecilla University Hospital, Eating Disorders Unit, Santander, Spain IDIVAL, Santander, Spain CIBER Mental Health, Madrid, Spain Avinash Desousa Department of Psychiatry, L.T.M.M.C. & G.H., Sion, Mumbai, Maharashtra, India Anna Dolgon-Krutolow Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA Éric Doucet School of Human Kinetics, University of Ottawa, Ottawa, ON, Canada Marwan El Ghoch Department of Nutrition and Dietetics, Faculty of Health Sciences, Beirut Arab University, Beirut, Lebanon Paola Fadda Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy Marco Faldi Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy Fabiana Salatino Fangueiro Post Graduation Program in Health Science, Santo Amaro University, Sao Paulo, SP, Brazil Angela Favaro Department of Neurosciences, University of Padua, Padova, Italy Padua Neuroscience Center, University of Padua, Padova, Italy Pouneh K. Fazeli Neuroendocrinology Unit, Division of Endocrinology and Metabolism, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Fernando Fernández-Aranda Department of Psychiatry, Psychoneurobiology of Eating and Addictive Behaviors Group, Neurosciences Programme (IDIBELL), Bellvitge University Hospital–IDIBELL and CIBEROBN, Barcelona, Spain Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain Kelsie T. Forbush Department of Psychology, University of Kansas, Lawrence, KS, USA

Contributors

xxiii

Janet Franklin Metabolism and Obesity Service, Royal Prince Alfred Hospital, Sydney, NSW, Australia Sydney Nursing School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia Walter Fratta Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy Rogério Friedman Endocrinology Division, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, RS, Brazil Craig A. Friesen Division of Gastroenterology, Hepatology, and Nutrition, Children’s Mercy Kansas City, University of Missouri Kansas City School of Medicine, Kansas City, MO, USA Hunter J. Friesen University of Kansas School of Medicine, Kansas City, MO, USA Leticia Castro Fuentes Department of Psychiatry, Marqués de Valdecilla University Hospital, Eating Disorders Unit, Santander, Spain Nerkis Fuentes Doctorado en Psicología. Facultad de Ciencias Sociales, Universidad de Concepción, Concepción, Chile Esti Galili-Weisstub Herman-Dana Division of Child and Adolescent Psychiatry, Department of Psychiatry, Hadassah, Hebrew University Medical Center, Jerusalem, Israel Susan Gamberg Department of Psychiatry, Dalhousie University, Halifax, NS, Canada Ata Ghaderi Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden Ruth Giesser Herman-Dana Division of Child and Adolescent Psychiatry, Department of Psychiatry, Hadassah, Hebrew University Medical Center, Jerusalem, Israel Krzysztof Gil Department of Pathophysiology, Collegium Medicum Jagiellonian University, Krakow, Poland Konstantinos Gkiouras Faculty of Medicine, School of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece Gary S. Goldfield School of Human Kinetics, University of Ottawa, Ottawa, ON, Canada Healthy Active Living & Obesity (HALO) Research Group, Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada Department of Pediatrics, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada

xxiv

Contributors

School of Psychology, University of Ottawa, Ottawa, ON, Canada Tanya Goltser Dubner Herman-Dana Division of Child and Adolescent Psychiatry, Department of Psychiatry, Hadassah, Hebrew University Medical Center, Jerusalem, Israel Molecular Psychiatry Laboratory, Department of Psychiatry, Hadassah – Hebrew University Medical Center, Jerusalem, Israel Sasha Gorrell Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA Dimitrios G. Goulis Unit of Reproductive Endocrinology, 1st Department of Obstetrics and Gynecology, Medical School, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece Maria G. Grammatikopoulou Department of Rheumatology & Clinical Immunology, Faculty of Medicine, University of Thessaly, Larissa, Greece Unit of Reproductive Endocrinology, 1st Department of Obstetrics and Gynecology, Medical School, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece Carla Cobo Gutierrez Department of Psychiatry, Marqués de Valdecilla University Hospital, Eating Disorders Unit, Santander, Spain Daniel Gyamfi The Doctors Laboratory Ltd, London, UK Lisa Hail Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA Elizabeth Hamlin Department of Psychiatry and Behavioral Medicine, Medical College of Wisconsin, Milwaukee, WI, USA Tomoko Harada Department of Neuropsychiatry, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan Anastasia Harris Department of Psychiatry, Abbie J. Lane Memorial Hospital, Halifax, NS, Canada Melissa Hart Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW, Australia Eating Disorder and Nutrition Research Group (ENRG), Translational Health Research Institute, Faculty of Medicine, Western Sydney University, Sydney, Australia Susan Hart Eating disorder and Nutrition Research Group (ENRG), Translational Health Research Institute, Faculty of Medicine, Western Sydney University, Sydney, NSW, Australia Nutrition and Dietetics, St Vincent’s Hospital, Sydney, NSW, Australia

Contributors

xxv

Ana Paula Hermont Department of Pediatric Dentistry, Faculty of Dentistry, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil Sandra Hernández-Muñoz Departamento de Farmacogenética, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City, Mexico Kristin E. Heron Department of Psychology, Old Dominion University, Norfolk, VA, USA Angelica Lindén Hirschberg Division of Neonatology, Obstetrics and Gynecology, Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden Gabbrielle Hodges Western Washington University, Bellingham, WA, USA Lindsay M. Howard Department of Psychology, Augustana University, Sioux Falls, SD, USA Christina Hughes Department of Rehabilitation and Sport Sciences, Faculty of Health and Social Sciences, Bournemouth University, Bournemouth, UK Luzia Jaeger Hintze School of Human Kinetics, University of Ottawa, Ottawa, ON, Canada Haitham Jahrami Ministry of Health, Kingdom of Bahrain, Manama, Bahrain Department of Psychiatry, College of Medicine and Medical Sciences, Arabian, Manama, Bahrain Mikyla Janzen Hearts in Rhythm Organization, Vancouver, BC, Canada Division of Cardiology, Center for Cardiovascular Innovation, University of British Columbia, Vancouver, BC, Canada Rachel Jewett Centre for Mental Health, University Health Network, Toronto, ON, Canada Department of Psychology, Toronto Metropolitan University, Toronto, ON, Canada Cristina Hernández Jimenez Department of Psychiatry, Marqués de Valdecilla University Hospital, Eating Disorders Unit, Santander, Spain Adrienne Juarascio Department of Psychology, Center for Weight Eating and Lifestyle Science (WELL Center), Drexel University, Philadelphia, PA, USA Sagar Karia Department of Psychiatry, L.T.M.M.C. & G.H., Sion, Mumbai, Maharashtra, India Pamela K. Keel Department of Psychology, Florida State University, Tallahassee, FL, USA Shikma Keller Molecular Psychiatry Laboratory, Department of Psychiatry, Hadassah – Hebrew University Medical Center, Jerusalem, Israel

xxvi

Contributors

Aaron Keshen Department of Psychiatry, Dalhousie University, Halifax, NS, Canada Anamil Khiyami Neuroendocrinology Unit, Division of Endocrinology and Metabolism, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Department of Internal Medicine, College of Medicine, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia Ellen Klaver Department of Educational Psychology, University of Alberta, Edmonton, AB, Canada Natália Luiza Kops Post-Graduate Program in Endocrinology, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil Cigdem Koroglu Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, USA Hiral Kotadia Department of Psychiatry, Sri Aurobindo Medical College & PG Institute, Indore, Madhya Pradesh, India Andrew Krahn Hearts in Rhythm Organization, Vancouver, BC, Canada Division of Cardiology, Center for Cardiovascular Innovation, University of British Columbia, Vancouver, BC, Canada Maja Krefft Department of Medical Genetics, Institute of Mother and Child, Warsaw, Poland Diagnostic and Therapeutic Center for Rare Disorders, Wroclaw, Poland Isabel Krug Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia Magdalena Kurnik-Łucka Department of Pathophysiology, Collegium Medicum Jagiellonian University, Krakow, Poland Elizabeth Lampe Department of Psychology, Center for Weight Eating and Lifestyle Science (WELL Center), Drexel University, Philadelphia, PA, USA Arianna Laoreti Department of Biomedical and Clinical Sciences “L. Sacco”, Unit of Obstetrics and Gynecology, ASST Fatebenefratelli Sacco – Buzzi Children’s Hospital, University of Milan, Milan, Italy Daniel Le Grange Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA Eli R. Lebowitz Yale University Child Study Center, New Haven, CT, USA Marta Lepora Eating Disorders Center, Department of Neuroscience, University of Turin, Turin, Italy

Contributors

xxvii

Maria Libura University of Warmia and Mazury in Olsztyn, Collegium Medicum, Olsztyn, Poland Rachel E. Liebman Centre for Mental Health, University Health Network, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, ON, Canada Department of Psychology, Toronto Metropolitan University, Toronto, ON, Canada Eating Disorder Program, Toronto General Hospital, University Health Network, Toronto, ON, Canada Angelica Lindén Hirschberg Division of Neonatology, Obstetrics and Gynecology, Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden Paola Longo Eating Disorders Center, Department of Neuroscience, University of Turin, Turin, Italy Danielle E. MacDonald Centre for Mental Health, University Health Network, Toronto, ON, Canada Eating Disorder Program, Toronto General Hospital, University Health Network, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, ON, Canada Toronto General Hospital Research Institute, Toronto, ON, Canada Amy Malcolm Centre for Mental Health, Swinburne University of Technology, Hawthorn, VIC, Australia Ängla Mantel Clinical Epidemiology Division, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden Matteo Martini Eating Disorders Center, Department of Neuroscience, University of Turin, Turin, Italy Enrica Marzola Eating Disorders Center, Department of Neuroscience, University of Turin, Turin, Italy Tyler B. Mason Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA Kylie Matthews-Rensch Nutrition and Dietetics, Royal Brisbane and Women’s Hospital, Brisbane, QLD, Australia Eating Disorder and Nutrition Research Group (ENRG), Translational Health Research Institute, Faculty of Medicine, Western Sydney University, Sydney, Australia Sarah Mccomb Eating Disorder Program, Toronto General Hospital, University Health Network, Toronto, ON, Canada Department of Psychology, York University, Toronto, ON, Canada

xxviii

Contributors

Caitlin M. McMaster Faculty of Medicine and Health, University of Sydney, University of Sydney Children’s Hospital at Westmead Clinical School, Sydney, NSW, Australia Illawarra Eating Disorder Service, Wollongong, NSW, Australia Eating Disorder and Nutrition Research Group (ENRG), Translational Health Research Institute, Faculty of Medicine, Western Sydney University, Sydney, Australia Imran Memedi Department of Psychiatry Faculty of Medical Sciences, University of Tetovo, Tetovo, Macedonia Paolo Meneguzzo Department of Neuroscience, University of Padova, Padova, Italy Valentina Meregalli Department of Neurosciences, University of Padua, Padova, Italy Padua Neuroscience Center, University of Padua, Padova, Italy Jelena Milic Department for Methodological Principles and Standards of Integrated Health Information System and Reporting, Institute of Public Health of Serbia “Dr Milan Jovanovic Batut”, Belgrade, Serbia Dai Miyawaki Department of Neuropsychiatry, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan Wanda Morganti Department of Educational Sciences, University of Genoa, Genoa, Italy Lillith Moser Faculty Psychology, University of Koblenz-Landau, Landau, Germany Shorouq Motwani Department of Psychiatry, L.T.M.M.C. & G.H., Sion, Mumbai, Maharashtra, India Stefania Muzi Department of Educational Sciences, University of Genoa, Genoa, Italy Sabine Naessén Department of Women’s, and Children’s Health, Karolinska Institutet, Stockholm, Sweden Gabriela Nazar Departamento de Psicología, Universidad de Concepción y Centro de Vida Saludable, Universidad de Concepción, Concepción, Chile Angela Nogueira Neves Division of Research, Physical Education School of Brazilian Army, Rio de Janeiro, Brazil Nexhibe Nuhii Faculty of Pharmacy, University of Tetovo, Tetovo, Macedonia Anna K. Olson Department of Psychology, Augustana University, Sioux Falls, SD, USA

Contributors

xxix

Faik Ozdengul Physiology Department, Meram Medical School, Necmettin Erbakan University, Konya, Turkey Cecilia Serena Pace Department of Educational Sciences, University of Genoa, Genoa, Italy Meneguzzo Paolo Department of Neurosciences, University of Padua, Padova, Italy Padua Neuroscience Center, University of Padua, Padova, Italy Hana Papezova Department of Psychiatry, First Faculty of Medicine of Charles University and General University Hospital in Prague, Prague, Czech Republic Antonia Parmeggiani IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Neuropsichiatria dell‘Età Pediatrica, Centro Regionale per i Disturbi della Nutrizione e dell’Alimentazione in età evolutiva, Bologna, Italy DIMEC Dipartimento di Scienze Mediche e Chirurgiche, Bologna, Italy Summer Pascual Western Washington University, Bellingham, WA, USA Anna Gabrielle Patarinski Center for Weight Eating and Lifestyle Science (WELL Center), Drexel University, Philadelphia, PA, USA Vinood B. Patel School of Life Sciences, University of Westminster, London, UK Andrea Phillipou Centre for Mental Health, Swinburne University of Technology, Melbourne, VIC, Australia Brianna N. Pitz Department of Psychology, Augustana University, Sioux Falls, SD, USA Isabela Almeida Pordeus Department of Pediatric Dentistry, Faculty of Dentistry, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil Jade Potingale Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia Victor R. Preedy Faculty of Life Science and Medicine, School of Life Course and Population Sciences, King’s College London, Franklin-Wilkins Building, London, UK Petra Prochazkova Laboratory of Cellular and Molecular Immunology, Institute of Microbiology, Czech Academy of Sciences, Prague, Czech Republic Jacopo Pruccoli IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Neuropsichiatria dell‘Età Pediatrica, Centro Regionale per i Disturbi della Nutrizione e dell’Alimentazione in età evolutiva, Bologna, Italy DIMEC Dipartimento di Scienze Mediche e Chirurgiche, Bologna, Italy Francis Puccio Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia

xxx

Contributors

Kirrilly Pursey School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia Eating disorder and Nutrition Research Group (ENRG), Translational Health Research Institute, Faculty of Medicine, Western Sydney University, Sydney, NSW, Australia Norbert Quadflieg Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich (LMU), Munich, Germany Richard Quansah Amissah Department of Biomedical Sciences, University of Guelph, Guelph, ON, Canada Rajkumar Rajendram College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia Department of Medicine, King Abdulaziz Medical City, King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia Julia Raudzus Division of Cardiology, Center for Cardiovascular Innovation, University of British Columbia, Vancouver, BC, Canada St. Paul’s Hospital, Vancouver, BC, Canada Julia Reichenberger Department of Psychology, Centre for Cognitive Neurosciences, Paris-Lodron University of Salzburg, Salzburg, Austria Valdo Ricca Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy Brianne N. Richson Department of Psychology, University of Kansas, Lawrence, KS, USA Eleonora Rossi Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy Radka Roubalova Laboratory of Cellular and Molecular Immunology, Institute of Microbiology, Czech Academy of Sciences, Prague, Czech Republic Francisco Ruiz Guerrero Department of Psychiatry, Marqués de Valdecilla University Hospital, Eating Disorders Unit, Santander, Spain IDIVAL, Santander, Spain Zahra Saif Ministry of Health, Kingdom of Bahrain, Manama, Bahrain Miguel Enrique Sánchez-Hechavarría Programa de Promoción de la Salud y Prevención de la Enfermedad (PROSALUD) de Núcleo Científico Tecnológico para el Desarrollo Costero Sustentable. Departamento de Ciencias Clínicas y Preclínicas. Facultad de Medicina, Universidad Católica de la Santísima Concepción, Concepción, Chile

Contributors

xxxi

Vincent A. Santiago Eating Disorder Program, Toronto General Hospital, University Health Network, Toronto, ON, Canada Department of Psychology, Toronto Metropolitan University, Toronto, ON, Canada Maria Scherma Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy Jennifer V. Schurman Division of Gastroenterology, Hepatology, and Nutrition, Children’s Mercy Kansas City, University of Missouri Kansas City School of Medicine, Kansas City, MO, USA Ronen Segman Herman-Dana Division of Child and Adolescent Psychiatry, Department of Psychiatry, Hadassah, Hebrew University Medical Center, Jerusalem, Israel Molecular Psychiatry Laboratory, Department of Psychiatry, Hadassah – Hebrew University Medical Center, Jerusalem, Israel Amit Shalev Herman-Dana Division of Child and Adolescent Psychiatry, Department of Psychiatry, Hadassah, Hebrew University Medical Center, Jerusalem, Israel Yaara Shimshoni Yale University Child Study Center, New Haven, CT, USA Nicole A. Short Department of Anesthesiology, Institute for Trauma Recovery, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Department of Psychology, University of Nevada, Las Vegas, Las Vegas, NV, USA Courtney C. Simpson Eating Disorders Center for Treatment and Prevention, Department of Psychiatry, UC San Diego Health, San Diego, CA, USA Magnus Sjögren Research Unit Eating Disorders, Psychiatric Center Ballerup, Ballerup, Denmark Kamil Skowron Department of Pathophysiology, Jagiellonian University, Krakow, Poland

Collegium

Medicum

Shannon Smith Department of Nursing, Abbie J. Lane Memorial Hospital, Halifax, NS, Canada Giovanna Soler Donofre Graduate Program in Food, Nutrition and Food Engineering, School of Pharmaceutical Sciences, São Paulo State University (UNESP), Araraquara, Brazil Shauna Solomon-Krakus Department of Psychology, Toronto Metropolitan University, Toronto, ON, Canada Dunja Stankic Faculty of Medicine, Editorial Office of Journal “Medicinar”, University of Belgrade, Belgrade, Serbia Gordana Stankovska Department of Psychiatry Faculty of Medical Sciences, University of Tetovo, Tetovo, Macedonia

xxxii

Contributors

Dona Stefanovic Center for Anesthesiology and resuscitation at Clinical Center of Serbia, School of Medicine, University of Belgrade, Belgrade, Serbia Jana Strahler Sport Psychology, Institute of Sport and Sport Science, University of Freiburg, Freiburg, Germany Lut Tamam Department of Psychiatry, School of Medicine, Cukurova University, Adana, Turkey Livio Tarchi Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy Victoria Taylor Department of Medicine, Dalhousie University, Halifax, NS, Canada Elena Tenconi Department of Neurosciences, University of Padua, Padova, Italy Padua Neuroscience Center, University of Padua, Padova, Italy Igor Timofeev Faculté de Médecine, Département de Psychiatrie et de Neurosciences, Centre de Recherche du CERVO, Université Laval, Québec, QC, Canada Kathryn Trottier Centre for Mental Health, University Health Network, Toronto, ON, Canada Eating Disorder Program, Toronto General Hospital, University Health Network, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, ON, Canada Toronto General Research Institute, Toronto, ON, Canada Fotini Tsofliou Department of Rehabilitation and Sport Sciences, Faculty of Health and Social Sciences, Bournemouth University, Bournemouth, UK Serkan Turan Department of Child and Adolescent Psychiatry, Uludag University, Bursa, Turkey Tonia Vassilakou Department of Public Health Policy, School of Public Health, University of West Attica, Athens, Greece Benedetto Vitiello Department of Public Health and Paediatric Sciences, University of Torino, Torino, Italy Hanna Wachten Sport Psychology, Institute of Sport and Sport Science, University of Freiburg, Freiburg, Germany Elisabet Wentz Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Vastra Frolunda, Sweden Olivia Wons Department of Psychology, Center for Weight Eating and Lifestyle Science (WELL Center), Drexel University, Philadelphia, PA, USA Hamdi Yılmaz Department of Psychiatry, Mersin City Hospital, Mersin, Turkey

Contributors

xxxiii

Kenichi Yamada Pediatrics, Hayakawa Children’s Clinic, Niigata, Japan Centre for Integrated Human Brain Science, Brain Research Institute, Niigata University, Niigata, Japan Tsuneo Yamauchi Department of Neuropsychiatry, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan Melda Pelin Yargic Faculty of Medicine, Ankara Medipol University, Ankara, Turkey Ada H. Zohar Graduate Program in Clinical Psychology, Ruppin Academic Center, Emek Hefer, Israel Lior Zfaty Center for Suicide and Mental Pain Research, Emek Hefer, Israel

Part I General Aspects, Overviews, and Setting the Scene

1

Enhanced Cognitive Behavior Therapy for Eating Disorders Riccardo Dalle Grave

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Origins of CBT-E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Transdiagnostic Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Overview of CBT-E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Goals of CBT-E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . General Treatment Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Forms of CBT-E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Versions of CBT-E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Status of CBT-E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Implications for Clinical Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Remaining Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Applications in Other Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mini-Dictionary of Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Key Facts of Enhanced Cognitive Behavior Therapy for Eating Disorders . . . . . . . . . . . . . . . . . . . . Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 5 8 9 12 13 14 15 18 19 19 20 20 21 21 22

Abstract

Enhanced Cognitive Behavior Therapy (CBT-E) is a psychological treatment specifically designed for eating disorders. Based upon the original cognitive behavior therapy for bulimia nervosa (CBT-BN), it has been termed “enhanced” because it uses various innovative strategies and procedures to maximize its effectiveness. It addresses flexibly and individually the transdiagnostic processes maintaining the eating-disorder psychopathology. CBT-E was initially designed for adult outpatients with eating disorders, but has subsequently been adapted for adolescents, intensive settings of care (i.e., intensive outpatients and inpatients), and complex cases featuring medical and psychiatric comorbidities. CBT-E has been trialed in both research and real-world clinical settings, and is recommended R. Dalle Grave (*) Department of Eating and Weight Disorders, Villa Garda Hospital, Garda, Italy © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_1

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R. Dalle Grave

as the most effective treatment for all clinical presentations of eating disorders in adults, and the most valid alternative to Family-Based Treatment for the management of eating disorders in adolescents. Future challenges are to further establish the validity of CBT-E, increase its effectiveness, improve its promotion, and maximize its availability. Keywords

Cognitive behavior therapy · Treatment · Eating disorders · Anorexia nervosa · Bulimia nervosa · Binge-eating disorder Abbreviations

AN BED BMI BN CBT-BN CBT-E FBT IPT MANTRA SSCM

Anorexia nervosa Binge-eating disorder Body mass index Bulimia nervosa Cognitive Behavior Therapy for Bulimia Nervosa Enhanced Cognitive Behavior Therapy Family-Based Treatment Interpersonal therapy Maudsley Model Anorexia Nervosa Treatment for Adults (MANTRA) Specialist Supportive Clinical Management

Introduction Enhanced Cognitive Behavior Therapy (CBT-E) is a form of cognitive behavior therapy (CBT) specifically developed for eating disorders (Fairburn et al. 2003). Based on the original CBT for Bulimia Nervosa (CBT-BN) it is a transdiagnostic treatment designed to address in a flexible and individualized way the key cognitive and behavioral processes maintaining eating-disorder psychopathology, rather than targeting a single diagnostic classification. In other words, it is equally suitable for treating anorexia nervosa, bulimia nervosa, binge-eating disorder, or “other eating disorders” (a broad term used to encompass the eating disorders that do not fit neatly into the above). CBT-E is termed “enhanced” because it introduces a variety of innovative, evidence-based strategies and procedures specifically developed to enhance the effectiveness of the original CBT-BN. Though designed initially for adult outpatients with eating disorders (Fairburn et al. 2003; Fairburn 2008), it has now been adapted to be suitable for adolescents (Dalle Grave and Calugi 2020; Dalle Grave 2019; Dalle Grave and Cooper 2016), day-hospital patients and inpatients (Dalle Grave et al. 2008; Dalle Grave 2012, 2013), and complex cases involving medical and psychiatric comorbidities (Dalle Grave et al. 2021a). CBT-E has been assessed in numerous clinical trials, and is recommended as both the most effective treatment for

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Enhanced Cognitive Behavior Therapy for Eating Disorders

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all clinical eating-disorder presentations in adults (National Guideline Alliance 2017), and the most valid alternative to Family-Based Treatment (FBT) for the management of eating disorders in adolescents (National Guideline Alliance 2017). This chapter begins by describing the origin of CBT-E. It goes on to provide an overview of transdiagnostic cognitive behavior theory and treatment and its current status, and then concludes by discussing the main challenges that still remain to be addressed.

The Origins of CBT-E The rationale behind CBT-E is closely linked with early reports describing recurrent objective binge-eating episodes and self-induced vomiting in normal-weight persons. This abnormal eating behavior pattern, initially called “bulimarexia” (BoskindLodahl and White 1978), was proposed as a specific eating disorder diagnosis by Gerald Russell in his landmark 1979 paper Bulimia nervosa: An ominous variant of anorexia nervosa (Russell 1979). In this, Russell described 30 normal-weight patients who, in addition to a fear of becoming fat, displayed recurrent binging and purging behavior. He gave the name “bulimia nervosa” to the disorder, and, intriguingly, claimed that the disorder was “intractable.” In the same period, Christopher Fairburn, a young psychiatrist working in Oxford, started to see cases with similar features to those described by Russell, and observed that these patients had three specific behaviors and concerns, specifically: 1. Unusual form of dieting, characterized by sustained attempts to follow extreme, rigid dietary rules 2. Recurrent episodes of loss of control over eating (binges) followed by selfinduced vomiting or laxative misuse (purging); the binges tended to be triggered by dietary rule-breaking 3. Extreme concerns about shape and weight (which he termed “overvaluation of shape, weight and their control”) He noted that these three common features appeared to interact, serving to reinforce, or “maintain,” the eating disorder, which led him to propose a theory focused on the psychology “maintaining,” rather than causing, bulimia nervosa (illustrated in Fig. 1). He then developed a psychological treatment designed to address each of the maintenance mechanisms described in the theory. The outpatient treatment, called “CBT-BN,” consisted of 20 sessions over 20 weeks, focused on addressing binge-eating episodes, dietary restraint and concerns about shape and weight, and achieving a full and lasting response (Fairburn 1981, 1985). Multiple studies evaluated the efficacy of CBT-BN, and by 2004 over 30 randomized control trials had been conducted. These demonstrated that CBT-BN is more effective than all the treatments with which it had been compared, including a wide range of psychological therapies (e.g., supportive psychotherapy, focal

6 Fig. 1 The cognitivebehavioral theory of bulimia nervosa. (From Fairburn et al. (2003). Reprinted with the permission of Elsevier)

R. Dalle Grave

Overvaluation of shape, weight, eating and their control

Strict dieting and other weight-control behavior

Binge eating

Compensatory vomiting/ laxative misuse

psychotherapy, supportive-expressive psychotherapy, hypnobehavioral treatment, stress management, nutritional counseling, and behavioral versions of CBT-BN), as well as various forms of exposure with response prevention, and pharmacological treatments (Wilson and Fairburn 2002). The only treatment with comparable effects to CBT-BN was interpersonal psychotherapy (IPT), but that was much slower to act (Agras et al. 2000; Fairburn et al. 1993). Summarizing the findings, 40–50% of adult patients with bulimia nervosa treated with CBT-BN displayed a complete response, which appeared to be well maintained over time. These results led the National Institute for Health and Clinical Excellence to recommend CBT-BN for adults with bulimia nervosa – a grade A recommendation (i.e., strong empirical support from well-conducted randomized trials) (National Collaborating Centre for Mental Health 2004). Despite this, the research into the efficacy of CBT-BN made clear that the treatment is not effective enough as, at best, only half of the patients achieve full and lasting remission. Analysis of the reasons for this yielded two main clinical observations (Fairburn et al. 2003): 1. Many of the clinical features present in bulimia nervosa are also present in anorexia nervosa and the other eating disorders (i.e., eating disorders share a specific psychopathology – see Table 1), and many patients’ eating disorder diagnosis shifts from one to another (e.g., from anorexia nervosa to bulimia nervosa or vice versa, the so-called “diagnostic migration” – see Fig. 2). This observation led to the idea that many of the processes that maintain bulimia nervosa, and are targeted by CBT-BN, also maintain the other eating disorders. 2. There were consistent reasons for a lack of response to CBT-BN. A case-by-case analysis of non-response led to the conclusion that the efficacy of CBT-BN might be extended to more patients in two main ways:

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Table 1 Eating disorders share the same features Overvaluation of shape, weight, and eating control Strict dieting Binge eating Self-induced vomiting Laxative misuse Diuretic misuse Excessive exercising Food checking Body checking Body avoidance Feeling fat Low weight and starvation syndrome

AN +++ +++ + + + + ++ +++ +++ + +++ +++

BN +++ ++ +++ ++ ++ + + + +++ ++ +++ +

OEDs ++ ++ ++ + + + + + ++ ++ +++ +

AN anorexia nervosa, BN bulimia nervosa, OEDs other eating disorders

AN OEDs BN

Fig. 2 Diagnostic migration of the eating disorder diagnosis. AN anorexia nervosa, BN bulimia nervosa, OEDs other eating disorders

a) By developing more effective strategies and procedures to address not only extreme concerns about shape and weight, but also ambivalence to change. b) By addressing the co-existing psychopathology that appeared to maintain some patients’ eating disorders (identified as clinical perfectionism, core low self-esteem, marked interpersonal difficulties, and/or mood intolerance). Accordingly, a “transdiagnostic” theory of the maintenance of eating disorders was proposed, and a transdiagnostic treatment based on this theory, called “CBT-E,” was developed (Fairburn et al. 2003).

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Transdiagnostic Theory The transdiagnostic theory accounts for the range of processes that maintain any eating disorder diagnosis, irrespective of its presentation. According to this theory, a distinctive self-evaluation scheme, termed the overvaluation of shape, weight, eating and their control is the “core,” or central feature maintaining eating disorders. People who display this trait judge their self-worth mainly, or even exclusively, on their shape, weight, and ability to control them. This psychopathological preoccupation with eating, weight, shape, and control seems to drive the other clinical features characteristic of eating disorders, including extreme weightcontrol behaviors (e.g., dietary restraint and restriction, purging and excessive exercising), feeling fat, and various forms of body checking and avoidance. From the transdiagnostic perspective, these features of eating disorders are expressions of an individual’s belief that controlling their weight, shape, and eating is vital to their self-evaluation. The one behavior that is not a direct expression of this core eating disorder feature is binge eating. A large subgroup of people with eating disorders experience bingeeating episodes, which seem to stem indirectly from the overvaluation of shape, weight, and eating through the following mechanisms: 1. Severe undereating. The overvaluation of shape, weight, eating and their control can lead an individual to undereat. Doing so produces several neuroendocrine signals that control food intake, messaging hunger over satiety. 2. Extreme and rigid dietary rules. People with eating disorders tend to react in a negative and extreme (often all-or-nothing) way when these extreme and rigid dietary rules are, almost inevitably, broken, and even small transgressions tend to be interpreted as evidence of a personal failing and lack of self-control. This often results in a temporary abandonment of the effort to restrict the diet, triggering a binge-eating episode. In turn, this episode intensifies concerns and beliefs regarding their lack of control over shape, weight, and eating, and encourages further dietary restriction, thereby increasing the risk of subsequent binge-eating episodes. 3. Self-induced vomiting or other compensatory behaviors. The false belief that purging behaviors effectively prevent calorie absorption removes a major deterrent (i.e., the fear of gaining weight) to relaxing the dietary rules and binge eating. 4. Events and associated mood changes. These seem to maintain binge-eating episodes through three main mechanisms: a) It is more difficult to maintain a high level of dietary restriction when life difficulties and associated emotional changes inevitably occur, and such events facilitate the breaking of extreme and rigid dietary rules. b) Binge eating distracts from problems and temporarily improves mood. It may therefore be adopted as a dysfunctional means of coping with life’s difficulties and uncomfortable emotions. c) Binge eating may be used to gratify and reward oneself (a common process reported by people with binge-eating episodes and obesity).

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In persons with the anorexia nervosa presentation, binge-eating episodes are usually subjective or absent, while undereating and being underweight predominate. These lead to the development of several starvation symptoms, such as hunger, dizziness, weakness, feeling cold, early sense of fullness, irritability, mood swings, social withdrawal, reduced sexual desire, and preoccupation with food (Keys et al. 1950). These, like undereating, binge-eating and the other eating-disorder features, perpetuate the preoccupation with and overvaluation of shape, weight, and eating control, ensuring that the eating-disorder mindset becomes locked in place. This occurs through several mechanisms (see Table 2). This vicious and debilitating cycle can be conceptualized and illustrated to patients via a transdiagnostic formulation, featuring the core processes involved in the maintenance of eating disorders according to transdiagnostic cognitivebehavioral theory (Fig. 3). This can be adapted to reflect any diagnostic category of eating disorders, or rather individual manifestations of the eating-disorder psychopathology, with minimal changes. For example, the formulation of a person with bulimia nervosa does not contain the box “low weight and starvation symptoms,” but may include all the other characteristics described in the array of possible eating disorder symptoms. In contrast, the formulation of a patient with anorexia nervosa restricting type will always include the box “low weight and starvation symptoms,” but not the “binge-eating” and “self-induced vomiting and “misuse of laxatives” boxes. A patient with anorexia nervosa of the binge-eating/purging type will display the greatest number of maintenance processes, while those with binge-eating disorder will have the smallest number. As mentioned briefly above, in addition to the core eating-disorder maintenance processes, transdiagnostic cognitive behavioral theory proposes that one or more of the following additional mechanisms may be operating in some patients (Fig. 4) (Fairburn et al. 2003): (i) clinical perfectionism, (ii) core low self-esteem, (iii) marked interpersonal difficulties, and (iv) mood intolerance. If present and marked, these “external” maintenance mechanisms interact with the core processes, perpetuating the eating disorder and hindering its treatment (see Table 3).

Overview of CBT-E CBT-E is a specialized psychological treatment for eating disorders based on the transdiagnostic cognitive behavioral theory described above. It was initially devised by Fairburn and colleagues at the Centre for Research on Eating Disorders at Oxford (CREDO) to treat eating disorders in adults with a body mass index (BMI) of between 15.0 and 39.9 (Fairburn et al. 2003; Fairburn 2008). It was then adapted by Dalle Grave and colleagues at the Villa Garda Hospital Department of Eating and Weight Disorders, Italy, to be suitable for both adolescents of at least 12 years of age (Dalle Grave and Calugi 2020; Dalle Grave 2019) and more intensive settings of care (Dalle Grave 2012, 2013), such as day-hospital and residential units, where patients with severe eating disorders and or BMI 35 Kg/m2 associated with comorbidities (Associação Brasileira Para o estudo da obesidade e da síndrome metabólica (ABESO) 2016). Adolescents aged 16 to 18 years can be operated on as long as there is pediatric follow-up by the multidisciplinary team and that they respect the consolidation of the epiphyses cartilage of the wrist. In Brazil, the most recent Resolution of the Federal Council of Medicine (2172/2017) expanded the indication of bariatric surgery for patients with diabetes mellitus type 2 between 30 and 70 years of age and BMI from 30 to 34.9 Kg/m2, as long as the disease has not

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been controlled with clinical treatment. Furthermore, it is necessary that the diagnosis has been defined for at least 10 years. Contraindications for bariatric surgery are Cushing’s syndrome; dependence on alcohol or illicit drugs during surgery; severe uncontrolled psychiatric illness; moderate to severe dementia; a recent history of myocardial infarction, stroke, and cardiac stent; current cardiac ischemia or severe valve dysfunction; and the difficulty of understanding risks, benefits, expected results, treatment alternatives, and lifestyle changes required after the procedure (Associação Brasileira Para o estudo da obesidade e da síndrome metabólica (ABESO) 2016). According to the American Society for Metabolic and Bariatric Surgery (ASMBS), a patient who is unable to achieve weight loss and maintain it for a period of time and who has a BMI  40 kg/m2 or is more than 100 pounds overweight is eligible for bariatric surgery. Patients with a BMI  35 kg/m2 and at least one or more obesity-related comorbidities, such as type 2 diabetes (DM2), hypertension, sleep apnea and other respiratory disorders, nonalcoholic fatty liver disease, osteoarthritis, lipid abnormalities, gastrointestinal disorders, or heart disease, are also eligible for BMS. In adolescents, the recommendation to perform BMS is for those with a BMI  35 kg/m2 and who present the following comorbidities: DM2, moderate or severe sleep apnea, pseudotumor cerebri, or severe fatty liver disease. Those with a BMI  40 kg/m2 and those with less severe comorbidities such as high blood pressure, high cholesterol, and mild or moderate sleep apnea are also qualified. The surgeries are differentiated by the working mechanism. There are three basic procedures in BMS, which can be didactically divided and classified as restrictive procedures, malabsorptive procedures, or mixed procedures. Restrictive procedures are those that reduce gastric capacity, leading the patient to consume less food and inducing a quick feeling of satiety. Among these procedures, there are those that are purely restrictive, those that do not stop the patient’s hunger, and those that are restrictive and metabolic, such as sleeve gastrectomy, which, in addition to inducing early satiety, also reduce the degree of hunger (de Oliveira et al. 2019). Malabsorptive procedures, currently in disuse, slightly alter the gastric capacity and drastically alter the absorption of nutrients. These are surgical techniques that cause a large intestinal diversion, reducing the time the food is in the intestinal transit and, consequently, also reducing its absorption capacity, which will lead to weight loss (Associação Brasileira Para o estudo da obesidade e da síndrome metabólica (ABESO) 2016). Mixed procedures, considered the gold standard, are those that cause restriction in gastric capacity and a mild reduction in nutrient absorption capacity, such as the RYGB technique. Currently, the laparoscopic approach is the most widely used method for performing BMS, with only a small percentage of all procedures performed in open access. The most commonly performed BMSs are the laparoscopic sleeve gastrectomy, also known as the sleeve, and the laparoscopic RYGB (Wolfe et al. 2016; Sociedade Brasileira de Cirurgia Bariátrica e Metabólica (SBBMS) 2017).

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RYGB is characterized by the creation of a gastric reservoir (with a capacity of 40 to 50 ml) close to the small gastric curvature. The remainder of the stomach is excluded, including the entire fundus and the gastric antrum, the duodenum, and the initial portion of the jejunum. The reconstruction of the transit is carried out by forming a Roux-en-Y loop, with a length that varies from 75 to 150 cm. In addition, a silicone band can be placed a few centimeters above the gastrojejunal anastomosis to calibrate the passage of food. Thus, nutrients are shifted from the upper to the middle of the small intestine. As a consequence, there is a feeling of satiety more quickly and less absorption of nutrients due to the formation of the Y-shaped transit. This technique promotes weight loss equivalent to approximately 70% of the patient’s total weight, which is greater than that found in techniques that are only restrictive, such as the sleeve, for example, as well as having a low mortality rate (0.5%). However, supplementation with vitamins and minerals, such as vitamin B12, is necessary, in addition to frequent monitoring of serum levels of vitamin D, calcium, and iron (Associação Brasileira Para o estudo da obesidade e da síndrome metabólica (ABESO) 2016). Sleeve gastrectomy is an anatomically simple but irreversible operation in which 80% of the greater curvature of the stomach is excluded, leaving the anatomy of the small intestine unchanged. A probe is passed into the pylorus against the small curvature of the stomach, and a laparoscopic stapler positions a line of staples that follows the length of the probe to the angle of His. Although the process does not involve anastomosis, the length of the staple line puts the patient at risk for bleeding or fistula, particularly as it is a high-pressure chamber, which differs from RYGB. This surgical technique causes the stomach to reduce its storage capacity to 60–100 ml. Due to the removal of the bottom of the stomach, ghrelin levels decrease, consequently decreasing the feeling of hunger, thus characterizing the restrictive metabolic technique (Wolfe et al. 2016; Stein and Silverberg 2015). The degree of weight loss that patients experience varies according to individual, the surgical technique applied, and the time elapsed since the surgical procedure. The SBBMS considers obesity recurrence when, in the long term, there is a recovery of 50% of the weight loss or 20% of the weight regained associated with the reappearance of comorbidities. The controlled relapse of obesity, on the other hand, is when the patient recovers, in the long term, between 20% and 50% of the weight loss (Buchwald et al. 2004; Berti et al. 2015; Bryant et al. 2020). Throughout its history, BMS has undergone major advances related to patient safety and the development of more reliable and effective surgical techniques. However, 25% of daily caloric intake occurring after the evening meal, which might be accompanied or replaced by regular nocturnal awakenings (
2 per week) for food intake. Sleep disturbances and morning anorexia are listed as possible features along with the other symptoms like depressed mood and a strong urge to eat before sleep onset (Allison et al. 2010). The proposed diagnostic checklist also included criteria for differential diagnosis: awareness of nocturnal eating episodes to distinguish NES from sleep-related eating disorder, not having another medical or psychiatric disorder as a primary diagnosis, and maintenance of nocturnal eating for over 3 months. The prevalence of NES is estimated to be 1.5% in the general population (Vander Wal 2012) but is reported to be much higher in different study cohorts for obesity. In a study of bariatric surgery candidates by Allison et al. (2006), and a study of patients with obesity by Gluck et al. (2001), 9% and 14%, respectively, of the participants met the criteria for NES. However, most studies do not characterize individuals for NES, but instead only consider the core feature of NES, namely, the nighttime eating (NE) habit. Studies on NE showed an even higher prevalence (14%–36%) for this eating pattern among people with obesity (Adami et al. 2002; Cerú-Björk et al. 2001; Gluck et al. 2008), suggesting that NE might be causative for obesity. In support of a causative role for obesity, NE behavior as part of NES or as an isolated phenotype has been shown to predict weight gain (Gluck et al. 2008). This correlation is not surprising given the previous findings from out-of-phase eating and sleep restriction experiments. Out-of-phase food intake resulted in obesity in mice (Arble et al. 2009), while sleep restriction has been shown to increase food intake (Spaeth et al. 2013). It is important that the daily rhythms of food intake and sleep should be in harmony to maintain healthy weight.

Circadian Rhythm of Food Intake and Changes in Nighttime Eating Food intake is regulated by homeostatic processes and circadian rhythm in the body. Homeostatic regulation of food intake is under control of two opposing pathways: orexigenic and anorexigenic pathways. These pathways involve the actions of anorexigenic and orexigenic agents such as leptin, ghrelin, insulin, neuropeptide Y (NPY), and α-MSH, as well as anorexigenic and orexigenic neuronal populations residing in the hypothalamus (Huvenne and Dubern 2014). Anorexigenic pathways act after meals by increasing satiety. The adipocyte-derived hormone leptin binds to the leptin receptors in the hypothalamus and activates POMC-expressing neurons while inhibiting NPY expressing neurons. POMC is cleaved into α-MSH peptides,

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Fig. 1 Circadian control of feeding by the master and the secondary clocks. Circadian clock systems and their interaction with each other and the environmental cues. The master clock and its entrainment pathway are shown in blue. The secondary clocks and their entrainment pathways are shown in green. Circadian rhythmicity enabled by the master and food clocks enables the organism to predict food availability and engage in food anticipatory behavior. SCN ¼ suprachiasmatic nuclei. Created with BioRender.com

which can bind to MC4R and MC3R. This interaction results in a suppression of food intake (Zegers et al. 2012). Orexigenic pathways are predominant in the fasted state, during which ghrelin is released from the gastric cells and activates the NPY and Agouti-related peptide expressing neurons in the hypothalamus (Nakazato et al. 2001). In addition to hormonal regulation, circadian rhythm is one of the main systems in the regulation of food intake. Circadian rhythm is the internal process of organisms that predict the day-night cycle to regulate physiological functions accordingly. Circadian rhythmicity is enabled by endogenous clocks including a master clock located in the suprachiasmatic nuclei (SCN) of the hypothalamus and several secondary clocks in the brain and peripheral organs (Challet 2019) (Fig. 1). The master clock is synchronized by light; however, when light is absent, the master clock sustains itself and generates ~24 h cycles (Froy 2011). The secondary clock system in the brain and periphery can be reset by other environmental and physiological clues (Fig. 1). The secondary circadian system involved in food intake is referred as the food clock, and it can be readjusted by the timing of food intake via a feedback mechanism. The food clock together with the master clock sets daily windows for food intake that mostly occur during the daily active phase of an animal. Within these feeding windows, animals present behavioral anticipation for the food (Challet 2019). Secretion of many hormones involved in metabolism oscillate in sync with feeding windows, showing peak levels during anticipated feeding or fasting phases (Challet 2015).

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Delayed Timing in NE and Its Consequences The sleep-wake cycles of people with NES are typically undisturbed despite regular nocturnal awakenings (O’Reardon et al. 2004). However, their circadian rhythm of food intake is delayed. These observations suggested a dissociation of the circadian clocks of sleep and food intake (O’Reardon et al. 2004). Delayed timing of eating seen in NES and NE may reset the secondary circadian clocks, since these can be entrained by meal timing. However, the master clock in the SCN cannot be reset by habitual late eating because it is synchronized only by light (Challet 2019). Therefore, out-of-phase eating results in desynchronization of circadian clocks. For example, meal anticipation triggers an increase in plasma cortisol levels, yet a major cortisol peak always occurs early in the morning regardless of eating or skipping breakfast (Bogdan et al. 2001). Out-of-phase eating, such as Muslims practice during Ramadan, results in a totally different pattern of cortisol oscillation rather than a simple delay (Bogdan et al. 2001). As a result of the complex interactions between circadian clocks and metabolic hormones, out-of-phase eating can have adverse effects on metabolism (Challet 2019), such as increased adiposity or metabolic syndrome (Allison et al. 2014). It has been shown that night shift workers have a higher prevalence of obesity, type 2 diabetes, and cardiovascular disease (Akerstedt and Wright Jr 2009). Circadian disruptions in shift work give rise to decreased insulin sensitivity and increased blood pressure (Scheer et al. 2009). Similarly, NE behavior results in a change in neuroendocrine profiles leading to weight gain (Birketvedt et al. 1999; Gluck et al. 2008).

Hormone Profiles in NE Many hormones involved in metabolism exhibit circadian oscillation, and their rhythms and plasma levels change in NES. In a study of neuroendocrine profiling in NES, daily phases of ghrelin were similar between NES cases and controls, but the nocturnal levels were significantly lower in NES cases (Allison et al. 2005). The same study reported that leptin, melatonin, and cortisol did not show a significant difference between NES and control groups; however, an earlier study reported lower nocturnal plasma levels for leptin and melatonin and higher plasma levels for cortisol throughout the day (Birketvedt et al. 1999). Based on their findings, Allison et al. (2005) concluded that the differences in plasma hormone levels between NES and control groups were likely to be the result of the altered timing of food intake rather than the cause. A 2009 study (Goel et al. 2009) focused more on the pattern of circadian rhythms of the hormones rather than plasma concentrations. They found that people with NES have 1–3 h phase delays for circadian rhythms of leptin and insulin and about 5 h phase advance for ghrelin. These studies showed that the general pattern of daily peaks and lows was similar for both NES and control groups with a variation on the timing and the amplitude of the plasma level peaks, suggesting that the circadian disruption is not as prominent as more drastic changes

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in eating patterns such as fasting during Ramadan. Although neuroendocrine characteristics have been reported only for people with NES, as opposed to people with NE habit with or without the additional phenotypes of NES, similar circadian changes may be predicted for NE phenotypes in general based on our current knowledge on the relation of meal timing and circadian rhythms.

Assessment of NE As mentioned above, NE is characterized by the consumption of at least 25% of daily caloric intake after dinner and/or at least two episodes of nocturnal eating per week. However, in the absence of nocturnal eating episodes, it can be difficult to be certain of the NE phenotype because different cultures/societies eat dinner at different times in the evening. Allison et al. have proposed that dinner be defined as the first meal occurring between 5 pm and 8 pm (Allison et al. 2010), and subsequent food ingestions are regarded as calories consumed after dinner. However, in many parts of the Mediterranean, Asia, and South America, the standard dinner time is well after 8 pm, the most well-known examples being Spain and India. Therefore, nocturnal eating seems to be more reliable factor in characterization of NE. The time frame for nocturnal ingestion is usually taken as the 6–8 h period starting after 10 pm or 11 pm ((Gluck et al. 2008; O’Reardon et al. 2006). The Night Eating Questionnaire (NEQ) is a widely used tool to assess the presence and the severity of NE. The original 9-item NEQ was later expanded to include 14 questions about daily food intake and sleeping pattern (Allison et al. 2008; Gluck et al. 2001; Marshall et al. 2004), and modified versions of NEQ have been developed to be used in children (Lundgren et al. 2012) or to include additional phenotypical assessments related to NES (Innamorati et al. 2018). In outpatient study settings, diary data logged by the participants frequently accompanies NEQ for NE assessment. Participants keep daily logs about their food intake as well as sleep and mood (Birketvedt et al. 1999; Lundgren et al. 2008; O’Reardon et al. 2004). In addition to diaries, some studies include the use of motion sensors to keep track of an individual’s nightly awakenings (Birketvedt et al. 1999; O’Reardon et al. 2004). After the first description of NES (Stunkard et al. 1955), NE and NES have rarely been assessed in inpatient settings, where phenotyping can be done with more accuracy (Allison et al. 2005; Birketvedt et al. 1999; Gluck et al. 2008). One exception is a study by Gluck et al. (2008), which utilized computerized vending machines (Venti et al. 2009) in an inpatient setting to allow for ad libitum access to food 24 h per day. The vending machine recorded both the time of use and the quantity of food selected such that nocturnal ingestions could be precisely recorded, enabling a robust phenotyping within the study group.

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Effects of NE on Weight Management and Diabetes Management NE and BMI Numerous studies have examined whether there is a relationship between NE and BMI. Many studies have reported a positive correlation (de Zwaan et al. 2014; Gluck et al. 2008; Kucukgoncu et al. 2014; Morse et al. 2006); however, other studies have found no association between NE and BMI (Cerú-Björk et al. 2001; Friedman et al. 2006; Melo et al. 2018; Runfola et al. 2014). The main limitation for most of these studies is that the phenotyping depends on questionnaires for NE and self-reported height and weight values for BMI; therefore, there could be differences due to accuracy of the data. In addition, most of these studies are cross-sectional and compare the BMI of NE and non-NE groups at the time of recruitment; therefore, these cross-sectional data cannot be used to predict weight gain over time. The study by Gluck et al. (2008) was one of the few studies that did include follow-up data on weight measurements, and this study concluded that NE is related to weight gain. Nevertheless, this study was listed in a review (Gallant et al. 2012) among those with negative findings for BMI and NE relation because the baseline BMI values did not differ between NE and non-NE groups. Several theories have been proposed to explain the discrepancy in findings of a relationship between NE and BMI. For example, Gallant et al. proposed that the genetic background of a person and/or population could affect the relationship between NE and BMI (Gallant et al. 2012). Another theory has been that weight gain is gradual and cannot be easily observed in cross-sectional studies of young adults (Bruzas and Allison 2019). Supporting this view, Meule et al. (2014a) showed that NE was positively associated with BMI specifically in a sample of middle age to older adults (ages 31–60). Given that the mean ages of individuals differ greatly among studies examining NE and BMI, age could be an important moderator on this relationship. Yet another explanation for the lack of association between NE and BMI in some studies could be differences in compensatory behaviors. For example, some people with NE could participate in excessive exercising and/or calorie restriction during the day (Bruzas and Allison 2019; Lundgren et al. 2008; Runfola et al. 2014). Runfola et al. (2014) found that university students with NES were significantly more likely to have histories of being underweight due to past AN. Therefore, the relationship between NE and BMI may be complex, and although the few studies with BMI follow-up data report gradual weight gain in individuals with NE (Andersen et al. 2004; Gluck et al. 2008), more studies with follow-up data are needed to fully understand the long-term effects of NE.

NE and Diabetes EDs have been suggested to affect individuals with either type 1 diabetes (T1D) or type 2 diabetes (T2D). Among people with T2D, the more prevalent form of diabetes, around 40% of people have an ED. NES and BED are the two most

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common forms of EDs seen in T2D populations (García-Mayor and García-Soidán 2017). A study of NE in relation to T2D found that 7% of participants with T2D met the diagnostic criteria for NES, a prevalence higher than the general population (Hood et al. 2014). Similar to what has been reported among individuals with T2D, NE was observed in about 8.5% of people with T1D (Morse et al. 2006). NE behavior has also been proposed to increase difficulty in diabetes management (Hood et al. 2014; Vander Wal 2012). Poor dietary habits among individuals with NE, such as breakfast skipping, may be one cause of poor glycemic control (Hood et al. 2014). Since NE is a prevalent comorbidity in diabetes and has adverse effects on the disease management, it must be assessed in patients with T1D and T2D along with the other types of EDs.

Etiology of Nighttime Eating and Links to BMI Psychological Factors The original study that describes NES suggested that this disordered pattern of eating was a response to stress (Stunkard et al. 1955). In fact, the NES cases presented in that study suffered from traumatic life events and periods of high stress and anxiety, which coincide with the reoccurrences of NES symptoms. Later studies showed that emotional triggers are associated with NE. Emotional regulation was suggested to be a moderator of the NE and BMI relationship (Meule et al. 2014b). Data from questionnaires indicate that high levels of emotional eating are associated with NE severity and BMI (Meule et al. 2014b). NE has also been found to associate with stress, anxiety, and depression (Borges et al. 2017). Techniques that reduce stress and anxiety were found to be helpful in managing NE, indicating that these psychological factors have a role in NE (Pawlow et al. 2003). Depressed mood and major depressive disorder are highly comorbid with NE (Vander Wal 2012). Although it is not clear that depression, anxiety, and stress have a causative role in NE, the presence of any of these mental conditions is more common among individuals with NE (Bruzas and Allison 2019).

Genetic Components Familial aggregation has been shown for NES indicating that genetic factors contribute to this ED (Lundgren et al. 2006). However, to date, very few genetic studies have been conducted for NE. Since NE can be conceptualized as a disorder of circadian rhythm of food intake, the circadian clock genes (Rijo-Ferreira and Takahashi 2019) have been the most studied candidate genes for NE. Liu et al. (2014) studied the PER1 gene which is a member of the period gene family and one of the main clock genes. PER1 is expressed in the SCN, and in studies of mice, a mutation in this gene caused a change in peak time of food intake.

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Although findings from animal models can help to establish a set of candidate genes to search for variations underlying the heritability of NE, genetic studies of NE in humans are very limited. One study in humans analyzed the VGF gene as a candidate based on a database search (Sabbagh et al. 2016). However, conducting a genome-wide association study for NE, which is the standard method for identifying genetic variants that contribute to a polygenic trait, is challenging because no large cohorts of individuals clinically characterized for NE currently exist. In contrast to NE, common types of EDs, such as AN, do not have these sample size limitations, and genome-wide association studies have been performed on thousands of individuals characterized for AN (Wang et al. 2011). A small study by Köroğlu et al. (2020) is the only genetic study, to our knowledge, that utilized data from humans who were clinically characterized for NE. Rather than conduct a genome-wide association study which lacked power in their small sample of cases and controls, this study assumed a correlation between NE and BMI and therefore only considered a preselected set of variants that have been shown to significantly associate with BMI in large cohorts from the Genetic Investigation of Anthropometric Traits (GIANT) and UK Biobank databases (Yengo et al. 2018). Among these BMI-associated variants, Koroglu et al. determined that variation in HCRTR1 also associated with NE in their sample of inpatients characterized for NE. HCRTR1 encodes hypocretin (also known as orexin), whose physiology (detailed below) gives credibility to the association results. However, future genome-wide studies with large, well-powered sample sizes could uncover the role of additional genes that contribute to NE and NES.

Hypocretin Receptors and NE The hypocretin (also known as orexin) system can be regarded as the junction of the sleep and feeding regulation mechanisms. It has been considered as one of the secondary circadian clocks regulating food intake. Hypocretin 1 and 2 peptides are encoded by HCRT in the hypothalamus. HCRT is a clock-controlled gene, and its expression varies during the day (Challet 2019). Hypocretin neuropeptides are endogenous ligands for two G-protein-coupled receptors, hypocretin receptor 1 encoded by HCRTR1 gene and hypocretin receptor 2 encoded by HCRTR2 gene (Sakurai 2007). Hypocretin-producing neurons originating from the hypothalamus innervate the entire brain and regulate sleep and stimulate feeding. The different types of hypocretins and their distinct receptors are thought to have unique physiological roles (Marcus et al. 2001). Mutations in HCRT and HCRTR2 cause narcolepsy (Hungs and Mignot 2001; Lin et al. 1999; Peyron et al. 2000), whereas no mutation in HCRTR1 was found in human narcolepsy cases, and Hcrtr1 knockout mice, unlike Hcrtr2 knockout mice, did not present disturbed wakefulness and rapid-eye movement sleep patterns (Sakurai 2007). The involvement of HCRTR1 in feeding is better supported than its role in sleep. Intraperitoneal injection of hypocretin receptor 1 antagonist reduced feeding in rats, revealing the important role of Hcrtr1 in mediating food intake (Haynes et al. 2000). It has also been found

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that Hcrtr1, but not Hcrtr2, is upregulated in response to fasting (Lopez et al. 2000). These studies reveal the important functions of hypocretins and their receptors in feeding and sleep regulation and indicate the divergence in functions between the receptors, which makes them intriguing candidates for increased risk of NE.

Applications to Other Eating Disorders In this chapter we have reviewed neuroendocrine changes due to NE and the adverse effects of this habit on weight management and diabetes and discussed the genetic and environmental factors that might contribute to the development of NE. We also described the characteristics of NES, an ED with NE as the main feature, which is included in the Diagnostic and Statistical Manual of Mental Disorders. Although NES was previously considered as a disorder similar to BED (Napolitano et al. 2001), according to the current view, diagnosis of any other ED excludes NES (Cleator et al. 2012). Therefore, NES cannot be comorbid with another ED. On the other hand, NE is reported to be common in individuals with a diagnosis of other EDs (Lundgren et al. 2011). This indicates an overlap in causes, including genetic factors. Therefore, a genetic susceptibility locus identified for NES could be a candidate locus for another ED and vice versa. Identification of genes and/or genetic variants that contribute to ED could help in understanding the underlying physiology and lead to improved therapies and or drug targets. A major challenge for these genetic studies is the lack of large datasets of robustly phenotyped individuals for the less common EDs. Until large samples are collected for the uncommon EDs to allow for adequately powered genome-wide association studies, hypothesis-based studies must be conducted. For example, if a particular eating phenotype is consistently associated with a higher or lower BMI or another anthropometric trait, genetic data from current large biobanks could be used in conjunction with the genotyping results from the limited sample of that ED. This strategy, employed by Köroğlu et al. (2020) who restricted their analysis of genetic determinants for NE to only variants known to affect BMI, uncovered a compelling candidate for NE. Knowledge of risk variants that are unique to a specific ED could aid in the diagnosis. In addition, merging information on metabolic pathways affected by genetic risk factors with knowledge of environmental influences may ultimately lead to better treatment of EDs.

Mini-Dictionary of Terms • Anorexia. Markedly reduced appetite or complete aversion to food • Bariatric surgery. Variety of procedures performed on the stomach or intestines to induce weight loss in people with obesity • Body mass index. A measurement derived from the weight of a person in kilograms divided by the square of their height in meters. It is expressed in units of kg/m2, and it is the most used value to determine adiposity

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• Circadian rhythm. The internal process of the organisms that predicts the day-night cycle and regulates the physiological functions • Genome-wide association study. In this method, the genomes in a sample set including phenotypically different individuals are scanned using genetic markers, and the differences in the allele frequencies of those genetic markers are used in statistical tests to identify associations of genotypes and phenotypes • Hyperphagia. Abnormally increased appetite and excessive hunger • Narcolepsy. A neurological disorder characterized by a disorganization of sleep and wakefulness. Patients with narcolepsy have disturbed sleep during the night and chronically sleepy during the day. They tend to prematurely enter rapid-eyemovement sleep phase

Key Facts of Night Eating Syndrome The main diagnostic criterion is the presence of nighttime eating, which is defined as intake of >25% of daily calories after the evening meal and/or the occurrence of regular nocturnal awakenings (
2 per week) for food intake. The patients are aware of and recall their nocturnal eating episodes. To be diagnosed with night eating syndrome, at least three of the following five symptoms must be present: morning anorexia, strong urge to eat after dinner and before sleep, having sleep onset or sleep maintenance problems at least four nights per week, believing that one must eat to initiate or return to sleep, and depressed mood that worsens in the evening. At least 3 months of nighttime eating must have been maintained to consider night eating syndrome diagnosis. Night eating syndrome diagnosis is considered only if the disordered pattern of eating is not secondary to substance abuse or another psychiatric disorder. The prevalence of night eating syndrome is about 1.5% in the general population. Treatment options include medications such as selective serotonin reuptake inhibitors and nonmedical interventions, mainly cognitive behavioral therapy.

Summary Points • Food intake is regulated by homeostatic processes and circadian rhythm in the body • Nighttime eating is a disruption in circadian rhythm with a dissociation between eating and sleeping rhythms • Out-of-phase eating seen in nighttime eating results in a change in neuroendocrine profiles • Many studies showed that nighttime eating is associated with a higher BMI, and studies with follow-up weight measurements reported gradual weight gain in people with nighttime eating

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• Nighttime eating is also associated with poor glycemic control and poor dietary habits in patients with type 2 diabetes • Assessment of nighttime eating commonly includes questionnaires and food diaries • Familial aggregation indicates genetic factors for nighttime eating, and the genetic background could be one of the major contributors to the NE and BMI relationship • Circadian clock genes and others involved in sleep and feeding regulation such as hypocretin peptides and their receptors have been highlighted as candidate genes for nighttime eating • A genetic susceptibility locus identified for night eating syndrome can be a candidate locus for another eating disorder because of the overlap of symptoms

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Night Eating Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . History of Night Eating Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Development of the Research Diagnostic Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prevalence and Comorbidities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Etiology and Medical Model Conceptualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Network Theory of Psychopathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Weaknesses of the Medical Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Network Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Advantages of Network Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Modeling the Network Approach to Psychopathology: Network Analysis . . . . . . . . . . . . . . . Network Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Network Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Accuracy and Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Network Approach to Psychopathology in Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Outline of Emerging Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Network Approach to Psychopathology in NES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Clinical Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions in Network Analysis of NES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Network Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Temporal Network Analysis Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Refine Intervention Targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Applications to Other Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mini-Dictionary of Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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M. T. Beauchamp (*) Applied Psychological Science Program, School of Graduate Psychology, Pacific University, Hillsboro, OR, USA e-mail: mbeauchamp@pacificu.edu © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_73

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Key Facts of Night Eating Syndrome and Network Analysis of Features . . . . . . . . . . . . . . . . . . . . Key Facts of Night Eating Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Night eating syndrome (NES) is an eating disorder (ED) characterized by a disrupted circadian rhythm that results in aberrant sleep, mood, and eating behaviors. The core features of NES include evening hyperphagia (i.e., consumption of
25% of total daily calories after the evening meal) and/or nocturnal ingestions of food after awakening from sleep. The conceptualization of NES has been informed by the medical model paradigm of disease, which assumes the presence of a distinct, underlying mechanism that causes symptoms. Utilizing this paradigm presents challenges for research and practice related to NES, as the causal mechanisms of NES are relatively unknown and conceptualization of NES has varied considerably over the past few decades. In response to the limitations of the medical model paradigm, recent work on EDs has focused on reconceptualizing ED psychopathology using the network approach to psychopathology. This approach focuses on identifying (a) functional, causal interactions among symptoms and (b) symptoms most important to specific disorders. This chapter provides an exploration on the conceptualization of NES when examined through this network approach. First, this chapter examines the history of NES conceptualization through a medical model lens. Next, it offers an overview of network analysis, emphasizing the methodology used to model the network approach to psychopathology. Findings from recent work on NES using network analysis are also presented. Finally, research and clinical implications from this study will be provided, as well as future directions for network analysis of NES. Keywords

Night eating syndrome · Network analysis · Eating disorders · Network approach to psychopathology · Medical model paradigm of disease · Psychopathology · Eating disorder treatment · Conceptualization of eating disorders · Core features of night eating syndrome · Symptoms Abbreviations

BMI DSM-5 ED EDNOS FGL GLASSO NES OSFED

Body mass index Diagnostic and Statistical Manual of Mental Disorders, 5th edition Eating disorder Eating disorder not otherwise specified Fused graphical lasso Graphical least absolute shrinkage and selection operator Night eating syndrome Other specified feeding and eating disorder

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Introduction Night eating syndrome (NES) is an eating disorder (ED) characterized by a disrupted circadian rhythm that results in aberrant sleep, mood, and eating behaviors (Muscatello et al. 2021). Indeed, individuals with NES experience a delay in their circadian pattern of food intake, which manifests as the two core features of NES: (a) evening hyperphagia (i.e., consumption of
25% of total daily calories after the evening meal) and/or (b) nocturnal ingestions of food after awakening from sleep (Allison et al. 2010). These individuals must also demonstrate awareness of their eating (i.e., they must be awake while eating), experience possible morning anorexia and/or concomitant mood or sleep disturbances, and exhibit distress or impairment for at least 3 months (Allison et al. 2010). Historically, conceptualization of NES has been guided by the medical model paradigm of disease, which assumes the presence of a distinct, underlying mechanism that causes symptom presentation. Therefore, researchers have focused on identifying the exact causal mechanism from which NES symptoms manifest. However, despite advances in understanding the etiology of NES since it was first described in the literature, the underlying causal mechanism is still relatively unknown. In addition, NES criteria have varied considerably over the past few decades, which has contributed to significant challenges in research and clinical examinations of this disorder (Vander Wal 2012). As an alternative to the medical model approach, recent work on other EDs has focused on reconceptualizing ED psychopathology using the network approach to psychopathology (Levinson et al. 2018b). Whereas the medical model paradigm emphasizes casual mechanisms from underlying factors, the network approach to psychopathology focuses on identifying (a) functional, causal interactions among symptoms and (b) symptoms most important to specific disorders (Borsboom and Cramer 2013). The network approach to psychopathology gained popularity in the past decade, with growing number of studies focusing on ED psychopathology and treatment (Monteleone and Cascino 2021). This chapter aims to deliver insight on the conceptualization and unique features of NES when examined through this network approach. First, this chapter examines the history of NES conceptualization through a medical model lens. Next, it offers an overview of network analysis, emphasizing the methodology used to model the network approach to psychopathology. Findings from recent work on NES using network analysis are also presented. Finally, research and clinical implications from this study will be provided, as well as future directions for network analysis of NES.

Night Eating Syndrome History of Night Eating Syndrome NES was first identified in 1955 as a cluster of nonnormative eating behaviors that would arise during periods of stress (Stunkard et al. 1955). Such behaviors included morning anorexia (i.e., lack of morning hunger or eating behavior in the morning),

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evening hyperphagia, and sleep-onset insomnia (i.e., difficulty getting to sleep more than 50% of the time; Stunkard et al. 1955). Since then, the conceptualization and diagnostic criteria of NES have evolved considerably (Striegel-Moore et al. 2006a). Although iterations of NES criteria retained some form of the three original symptoms, amendments to these symptoms – particularly with regard to evening hyperphagia – have led to definitional inconsistencies across studies. Following the proposal of the original NES symptoms in 1955, the first revision to NES criteria occurred in 1996 to better operationalize the symptoms. Subsequently, NES was defined as absence of appetite for breakfast, consumption of 50% or more of total daily calories after 7:00 p.m., and difficulty with sleep onset or maintenance (Stunkard et al. 1996). However, as interest and recognition of NES emerged, researchers often amended or operationalized these symptoms differently. For example, studies have specifically operationalized morning anorexia in terms of food quantity or consumption cutoff times (i.e., “skipping breakfast” or “delay of eating for several hours after awakening”; Geliebter 2002; Gluck et al. 2001; Rand et al. 1997). The definition of evening hyperphagia was interpreted by Rand et al. (1997) simply as “excessive evening eating,” with a proposal to exclude the specified percentage of daily caloric intake (50%) after the evening meal due to claims that persons with obesity were inaccurate at reporting caloric intake. Studies that have retained a percentage-based specification of evening caloric intake have ranged considerably (e.g., >25%, >50%), along with the operationalization of “evening” (e.g., after evening meal, after evening meal but before bed, after 6:00 pm–after 8: 00 pm; Striegel-Moore et al. 2006a). Lastly, several studies failed to define sleep disturbance beyond “insomnia,” and there exist wide ranges of frequencies for number of sleep disturbances (i.e., three times/week, four times/week, more than half the time, or nightly; Striegel-Moore et al. 2006a). Additional NES symptoms were also proposed as research in NES continued to grow. Rand et al. (1997) suggested that symptoms should include delay of eating after awakening for several hours and “evening tension and/or feeling upset” (an early allusion toward negative mood, which would be added later). Spaggiari et al. (1994) examined NES through the lens of a sleep disorder, proposing criteria that were more focused on symptoms that occurred during sleep, including (a) a drive to eat upon awakening in the night, (b) the inability to return to sleep without eating, (c) becoming fully awake during nocturnal eating episodes and full recall of such episodes in the morning, (d) and a quick return to sleep after eating. Nocturnal ingestions of food after awakening from sleep were again referenced in 1999, as was worsening of mood in the evening (Greeno et al. 1995; Birketvedt et al. 1999; Vinai et al. 2008). The variation in operationalized diagnostic criteria for NES has presented a significant challenge in research and clinical examinations of this disorder (Vander Wal 2012). For example, studies reviewing prevalence and epidemiology of NES will often cite the inconsistent diagnostic criteria as possible reasons for high variability in prevalence rates across different populations (Muscatello et al. 2021). In addition, the Diagnostic and Statistical Manual of Mental Disorders, including its most recent edition (DSM-5; American Psychiatric Association [APA] 2013), has

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not recognized NES as a separate diagnosis, likely due in part to these varying definitions (Striegel-Moore et al. 2006a). Currently, NES is subsumed under the “eating disorder not otherwise specified” (EDNOS) or “other specified feeding and eating disorder” (OSFED) categories, with little specification. Criteria for NES in the OSFED category do not include any mention of morning anorexia and conceptualize evening hyperphagia and nocturnal ingestion as “[r]ecurrent episodes of night eating, as manifested by eating after awakening from sleep, or by excessive food consumption after the evening meal. There is awareness and recall of the eating” (APA 2013, p. 354). With such little specification, accurate identification and diagnosis of NES and its distinction from other EDs under OSFED remains a challenge for clinicians.

Development of the Research Diagnostic Criteria To provide a standardized definition for NES, the First Night Eating Symposium was held in Minneapolis in 2008, and from this, Allison and colleagues proposed a set of specific research diagnostic criteria, presented in Table 1 (Allison et al. 2010). Within these criteria, evening hyperphagia, defined as consumption of at least 25% of daily caloric intake after the evening meal; nocturnal ingestion of food, defined as evening awakenings with ingestions at least twice a week; or both must be present for a diagnosis of NES (Criterion A), along with awareness of these eating episodes (Criterion B), at least three of five additional symptoms (Criterion C), and associated distress or impairment in functioning (Criterion D) lasting for at least 3 months (Criterion E). Table 1 Research diagnostic criteria for night eating syndrome (NES) Criterion A

B C

D E F

Definition The daily pattern of eating demonstrates a significantly increased intake in the evening and/or nighttime, as manifested by one or both of the following: 1. At least 25% of food intake is consumed after the evening meal 2. At least two episodes of nocturnal eating per week Awareness and recall of evening and nocturnal eating episodes are present The clinical picture is characterized by at least three of the following features: 1. Lack of desire to eat in the morning and/or breakfast is omitted on four or more mornings per week 2. Presence of a strong urge to eat between dinner and sleep onset and/or during the night 3. Sleep onset and/or sleep maintenance insomnia are present four or more nights per week 4. Presence of a belief that one must eat in order to initiate or return to sleep 5. Mood is frequently depressed and/or mood worsens in the evening The disorder is associated with significant distress and/or impairment in functioning The disordered pattern of eating has been maintained for at least 3 months The disorder is not secondary to substance abuse or dependence, medical disorder, medication, or another psychiatric disorder

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Prevalence and Comorbidities Estimates of prevalence rates for NES are quite varied due to inconsistent criteria and exclusion from DSM. Nonetheless, current estimates include ranges between 0.5% and 1.5% in the general population (Rand et al. 1997; Striegel-Moore et al. 2005), 5.7% in university students (Nolan and Geliebter 2012), 12.3–22.4% in psychiatric outpatient populations (Saraçlı et al. 2015), 6–16% among those patients visiting obesity clinics (Cerú-Björk et al. 2001; Gluck et al. 2001; McCuen-Wurst et al. 2018), and up to 55% in patients undergoing bariatric surgery for obesity (de Zwaan et al. 2015). There are little differences in rates of NES between gender, age, and ethnicity (Aronoff et al. 2001; Striegel-Moore et al. 2006b; Colles et al. 2007). Individuals with NES also show high comorbidity with major depressive disorder (Küçükgöncü and Beştepe 2014), substance use disorder (Lundgren et al. 2006; Küçükgöncü and Beştepe 2014), sleep-wake disorders (Lundgren et al. 2011; Hood et al. 2014), and other EDs (Colles et al. 2007; Allison et al. 2007; Vander Wal 2012; Tu et al. 2019). NES has shared close ties with overweight/obesity since its inception, as the syndrome was first identified through the clinical observation of individuals with obesity and was thought to be a behavioral expression of this weight status (Stunkard et al. 1955; Gluck et al. 2017). Prevalence rates for NES are higher in populations with obesity (6–16%; Küçükgöncü et al. 2015), and individuals with obesity in psychiatric outpatient settings are five times more likely to meet criteria for NES compared to individuals without obesity (Lundgren et al. 2006). Despite this relationship between obesity and NES, however, extant research has suggested that not all individuals with NES are persons with overweight/obesity (Birketvedt et al. 1999; Striegel-Moore et al. 2006b; de Zwaan et al. 2006; Lundgren et al. 2008). In addition, Vander Wal (2012) noted that obesity may be associated with NES, but the directionality of this relationship is not known, and symptoms of NES may balance out the likelihood of potential weight gain (i.e., morning anorexia compensating for evening hyperphagia and nocturnal ingestion of food).

Etiology and Medical Model Conceptualization As is the case with many disorders, the evolution of NES conceptualization and etiology have been heavily influenced by the medical model paradigm of disease. This paradigm (Lilienfeld and Treadway 2016) posits that mental health disorders are causal entities that result in myriad dysfunctional symptoms (Borsboom and Cramer 2013). In other words, the medical model proposes that psychiatric disorders have underlying causes that (1) lead to the expression of certain symptoms and (2) explain the co-occurrence of certain symptoms in related clusters. For NES, the proposed core mechanism is a circadian rhythm shift, and several causes have been suggested, including genetic (Root et al. 2010), biobehavioral (Stunkard et al. 2006; Lundgren et al. 2013; Pollack and Lundgren 2014), neuroendocrine (Birketvedt et al. 1999, 2014), and psychosocial (Allison et al. 2007; Takeda et al. 2004; Vander Wal

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2012; Sevincer et al. 2016; He et al. 2018) factors. Despite these proposals, the cause of NES is still relatively unknown (Lundgren et al. 2012b), but current conceptualizations suggest that NES has an underlying common cause, and research to date has been focused on identifying causal mechanisms of NES.

Network Theory of Psychopathology Weaknesses of the Medical Model One of the major weaknesses of the medical model paradigm when applied to conceptualizing psychiatric disorders is the reliance on a latent variable theory. This theory proposes that unseen factors give rise to observable phenomenon. This concept is applied to psychiatry insomuch that mental health disorders are thought to precipitate dysfunctional mental health symptoms. For example, major depression is posited as the manifestation of specific observable symptoms (e.g., depressed mood, loss of interest, fatigue, difficulty concentrating, etc.) that are caused by an underlying unobserved factor, much like how an infection would give rise to a fever, headache, and respiratory symptoms (Borsboom and Cramer 2013). While these symptoms are distinct (i.e., seen as separate symptoms), they are causally homogeneous, and the removal of the underlying factor (i.e., depression, the infection) will result in symptom alleviation. Furthermore, in the medical model, symptoms are distinct from the underlying condition (i.e., medical conditions can occur asymptomatically). When applying the medical model to psychopathology, it seems reasonable to suggest that a psychiatric disorder like depression should (a) have an underlying cause that is independent from the symptoms, and (b) this underlying cause should give rise to all related depressive symptoms (Borsboom and Cramer 2013). Therefore, such a theory asserts that an individual could have depression without any symptoms. It is highly unlikely that this scenario exists, and it remains unlikely that any future measurement techniques will be developed to detect disorders independent of their symptoms. Indeed, the medical model of disease as the cause of symptoms does not appear to hold true with psychiatric disorders, and the relationship between symptoms and disorders needs to be conceptualized differently (Borsboom and Cramer 2013).

Network Theory Network theory presents an alternative approach to this conceptualization. It suggests that symptoms are not the result of an underlying latent cause, but that psychiatric disorders result from a functional, causal interaction among symptoms (i.e., symptoms cause each other; Borsboom and Cramer 2013; Borsboom 2017). This interaction is conceptualized as connections between, and dynamic relationships among, a network of symptoms. This has been referred to as the “network

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approach to psychopathology” (Borsboom 2017). Indeed, interest in the network approach to psychopathology has grown considerably since Borsboom and Cramers’ (2013) seminal article (Contreras et al. 2019; Robinaugh et al. 2020), with Robinaugh et al. (2020) identifying 363 articles on this topic across myriad psychiatric disorders. Figure 1 illustrates this approach through a visual representation of a proposed network structure. The external field represents circumstances from outside the network that have direct influences on symptoms (i.e., adverse life events). These circumstances can “activate” symptoms within the network, which may activate neighboring symptoms, leading to the presentation of psychiatric disorders (Borsboom and Cramer 2013). Some symptoms may be more strongly connected to others, or clustered closely with others, and these symptoms are likely to impact each other to a greater degree. Indeed, such connections can lead to symptoms becoming self-sustaining and the disorder persisting even with the removal of the original influence (see Fig. 2; Borsboom 2017).

Fig. 1 A symptom network of four symptoms. Symptoms that have a tendency to activate each other are connected by a line (e.g., S1–S2). Symptoms can also indirectly activate each other (e.g., S1–S4) through a shared symptom (e.g., S3). External factors (e.g., adverse life events) exist in the external field and can directly affect one or more symptoms. S symptom, E external factor. (From Borsboom (2017) with permission)

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Fig. 2 The development of psychiatric disorders according to network theory. Phase 1 represents a dormant network. An external event occurs that triggers the activation of select symptoms (phase 2), which spreads to connected symptoms (phase 3). If the network is strongly connected, the network may become self-sustaining after the external event is removed (phase 4). S symptom, E external factor. (From Borsboom (2017) with permission)

Advantages of Network Theory Network theory presents several advantages over latent variable theory. Chief among these advantages is that network theory more closely models how clinicians instinctively conceptualize, diagnose, and treat psychopathology (Borsboom 2017). For example, in contemporary cognitive-behavioral models of psychopathology, there is an emphasis on how patterns of thoughts, behaviors, and emotions might be selfreinforcing within a triangular system. Thus, cognitive-behavioral therapists employ techniques to elucidate how these patterns are functionally linked together and how they may perpetuate a disorder (DuBois et al. 2017). Interventions are then chosen based on this interaction of symptoms, rather than identifying and addressing an underlying cause (Borsboom 2017). Therefore, an examination of a disorder through network theory appears to best match this approach, whereby a clinician conceptualizes a network that identifies which symptoms are present and which interactions are sustaining each other. As a result, a clinician would ideally identify the most important or most influential symptoms – based on how that symptom maintains or activates other symptoms – as a target for treatment.

Modeling the Network Approach to Psychopathology: Network Analysis Networks can be both graphically and quantitatively modeled using network analysis (Borsboom and Cramer 2013; Epskamp et al. 2018a). This method is a

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data-driven approach used to determine the network structure of a particular disorder. Techniques for network analysis have been derived from methodology used on social networks (Otte and Rousseau 2002) and neural networks (de Haan et al. 2009). A brief primer on the basic concepts of network analysis as applied to the network approach to psychopathology is presented below.

Network Structure Within a given network, symptoms are represented as nodes, and the connection between symptoms is referred to as an edge. These edges can either represent the presence of a correlation (unweighted) or can be used to indicate both the presence and the magnitude of the correlation (weighted). In a weighted network, the size of an edge denotes the strength of the correlation (thicker lines indicate stronger correlations and vice versa), and the color reflects the sign of the correlation. In addition, edges can also be used to determine the directionality of relationships between symptoms, with directed models using arrows on the edges to represent the direction of the association (i.e., symptom A predicting symptom B in the order toward the arrow’s end, suggesting possible causation) and undirected models using lines with no arrows (i.e., indicating a relationship but not modeling directionality or possible bidirectionality).

Approaches to Modeling Network Structure There exist various approaches to modeling network structure using cross-sectional data that assess relationships between symptoms at one point in time, often using self-report questionnaires or structured clinical interviews (McNally 2021). These approaches include association, concentration, relative importance, and Bayesian networks and differ on their use of undirected versus directed models and whether their edges represent zero-order correlations or partial correlations (Borsboom and Cramer 2013). As concentration networks are more commonly used in psychopathology research, this approach will be explored in depth, and readers are encouraged to review McNally (2016, 2021) for more information on the other approaches. Concentration networks utilize a matrix of partial correlations as a means to determine direct or indirect relationships (Borsboom and Cramer 2013). These networks are also known as Gaussian graphical models (Lauritzen 1996) and are part of a more general class of models called pairwise Markov random fields (Epskamp and Fried 2018). As partial correlations are correlations between nodes that remain after all other nodes are controlled for, this approach may assist in determining the causal structure of a network. Data used to model these networks are typically continuous, but there exist options to model binary (Ising model; van Borkulo et al. 2014) and mixed continuous and categorical (mixed graphical model; Haslbeck and Waldorp 2020) data. These networks, however, are vulnerable to sampling error, which may result in artificially inflated or spurious edge estimates (Epskamp and Fried 2018).

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One strategy to solve the issue of many small and potentially spurious correlations is the use of regularization, which sets a penalty on network estimation based on model complexity (Epskamp and Fried 2018). The graphical least absolute shrinkage and selection operator technique (GLASSO; Friedman et al. 2008) is one such regularization method. This reduces the overall number of edges by fixing a penalty on small values, shrinking them to zero, and dropping them from the model. This leads to the estimation of a sparse model with relatively few (i.e., presumably true) edges. Such parsimonious models are considered more interpretable (Epskamp et al. 2018a). Recent studies, however, have called into question the use of GLASSO, as this technique was originally developed for networks where the number of nodes exceeded the number of cases, which is unusual in psychopathology networks (Williams et al. 2019; Williams and Rast 2020). These studies suggest through simulations that GLASSO could eliminate true edges in the effort to estimate a sparse model. They suggest instead using confidence intervals to determine nonzero edges (Williams and Rast 2020).

Network Properties Centrality Network analysis can also be used to identify the core symptoms that are most important to maintaining the structure of the network (Borsboom and Cramer 2013). By adapting methodology from social network analysis (McNally 2021), these core symptoms are identified by assessing centrality indices, which work by determining the relative influence of specific nodes within the network. While centrality indices identify nodes that are of the greatest importance to the overall network structure (i.e., they can be considered the driving or maintaining force in the network provided certain conditions are met), these nodes do not have to represent hallmark symptoms of a disorder (i.e., depressed mood in major depressive disorder; McNally 2016; Borsboom 2017). Indeed, there are several indices used to determine centrality, all of which differ slightly in their approach, but they all represent how interconnected a specific symptom is to other symptoms within the network. Such indices include degree, betweenness, closeness, strength, and expected influence. As strength and expected influence are the most widely used indices in psychopathology networks (as well as the most stable indices; Epskamp et al. 2012), readers are encouraged to see McNally (2021) for more information on the other three. Strength centrality is measured by the sum of the absolute value of the edge weights between a particular node and all other nodes directly connected to it and represents how strong the direct connections are between that node and all other in the network. This is a useful index because it is likely that activation of symptoms with high strength centrality will trigger the activation of other symptoms (McNally 2016). This represents an accurate measure of relative importance if all edges in a network are positive; however, the accuracy of this index can become distorted by the increasing presence of negative edges (McNally 2021). Expected influence

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centrality arose as a response to this limitation and takes the sign of the edge weights into account, thus providing a more accurate measure of centrality as the number of negative edges in a network increases, or one identical to strength if the network only contains positive edges (Robinaugh et al. 2016). In order to state accurately that a node is more central than other nodes in a network, a high centrality value on a specific node should be statistically significantly different from centrality values on most, if not all, other nodes in the network (Fried 2016, 2018). This is assessed via bootstrapped difference tests (Epskamp et al. 2018a). To date, there are no established rules for how many significant differences between nodes are sufficient to consider a node highly central, and some studies have stated that a highly central node is meaningfully interpretable if its centrality indices are significantly different from at least half of the other nodes (Forrest et al. 2019; Beauchamp et al. 2021).

Accuracy and Stability After estimating the network structure based on one of the above approaches and analyzing the network structure with regard to its parameters (i.e., presenting a graphical representation to reveal relationship density between nodes, assessing node centrality, determining clustering of nodes into communities), the next step is to evaluate the accuracy and stability of these network parameters before a thorough interpretation of the network can be made. As networks are based on sample data and given the relatively small sample sizes used in some psychopathology research (Hevey 2018), network analysis can be susceptible to sampling variation as network complexity increases (Epskamp et al. 2018a). Thus, researchers using network analysis are encouraged to follow three steps to assess for accuracy (i.e., how prone the network is to sample variation) and stability (i.e., how similar the network interpretation remains with fewer observations): (1) use bootstrapped confidence intervals to assess the accuracy of the estimated edge weights, (2) assess the stability of centrality indices that are estimated on subsets of the data, and (3) explore significant differences between edge weights and centrality indices using bootstrapped difference tests (Epskamp et al. 2018a). These steps, in addition to methods that determine if differences in network parameters between samples are genuine (Jones et al. 2021), have been used to address concerns regarding the replicability of findings in network analysis (McNally 2021). Readers are suggested to review Epskamp et al. (2018a) for a tutorial on these procedures.

Network Approach to Psychopathology in Eating Disorders Outline of Emerging Research The application of network analysis in psychopathology research has extended to EDs within recent years. Indeed, network analysis has been used in over two dozen studies to estimate network models among individuals with anorexia nervosa,

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bulimia nervosa, binge eating disorder, and OSFED (Monteleone and Cascino 2021). Although researchers have continued to advocate for efforts to reconceptualize EDs from the network approach to psychopathology (Smith et al. 2018; Levinson et al. 2018b), recent work has also been done to derive other clinical applications from this approach, namely, the prediction of treatment outcomes in EDs (Smith et al. 2019; Vanzhula et al. 2019; Hilbert et al. 2020; Elliott et al. 2020; Brown et al. 2020; Monteleone et al. 2021). Despite this growing literature, however, only one study has been done that has specifically examined this approach with relation to NES (Beauchamp et al. 2021).

Network Approach to Psychopathology in NES Beauchamp et al. (2021) examined the psychopathology network of NES in a community sample of individuals diagnosed with NES recruited over 5 years. One hundred and forty-four participants were included in the study, participants were between 20 and 85 years of age (Mage ¼ 43.97, SD ¼ 12.14), and the majority were female (67.6%), were White (60.1%), and had a body mass index (BMI) score that put them in the obese range (56.1%). NES diagnoses, based on the research diagnostic criteria (Allison et al. 2010), were confirmed using the Night Eating Syndrome History and Inventory (Lundgren et al. 2012a), and participants also completed the Night Eating Questionnaire (Allison et al. 2008) and the Eating Disorder Examination (Fairburn et al. 2008). To further capture behavioral symptoms associated with NES (i.e., morning anorexia, nocturnal awakenings, nocturnal ingestions of food, and evening hyperphagia), participants completed 10-day, 24-h food and sleep diaries. In addition, participants were asked about non-NES-specific symptoms (i.e., symptoms that have been associated with NES but are not part of the diagnostic criteria) to broaden the potential plausible causal network of symptoms. Based on the proposed etiology and maintenance of NES in the literature thus far, this included depressed mood, circadian rhythm patterns, sleep quality and daytime sleepiness, and perceived stress. Symptoms were assessed via the Beck Depression Inventory-II (Beck et al. 1996), Morningness-Eveningness Questionnaire (Horne and Östberg 1976), Pittsburgh Sleep Quality Index (Buysse et al. 1989), Epworth Sleepiness Scale (Johns 1991), and Perceived Stress Scale-10 (Cohen and Williamson 1988), respectively. After the removal of one symptom that was found to be capturing a similar construct of another (i.e., number of awakenings removed, as this was captured by the number of nocturnal ingestions which inherently suggests nocturnal awakenings), there were 17 symptoms included in network estimation. Results from this study found that the psychopathology network of NES was sparsely connected (i.e., relatively few connections between symptoms; see Fig. 3), though the estimates of symptom centrality were stable. Surprisingly, neither evening hyperphagia nor nocturnal ingestions of food were found to be central symptoms in the network, which are necessary symptoms for a diagnosis of NES to be made as per the research diagnostic criteria. Instead, depressed mood, poor sleep quality, and a strong urge to eat during the night (all represented by Criterion C in the

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Fig. 3 The psychopathology network of NES. Blue and red lines indicate positive and negative associations, respectively, and line thickness indicates strength (e.g., thicker line equals stronger association). (From Beauchamp et al. (2021) with permission)

research diagnostic criteria) were found to be the most central symptoms (i.e., symptoms with the greatest importance to the network; see Fig. 4) and statistically more central than most other symptoms in the network (see Fig. 5). The authors stated in their conclusions that these results call into question the conceptualization of NES as presented by the research diagnostic criteria,

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Fig. 4 Centrality plot for the psychopathology network of NES. Plot is standardized on z-scores (M ¼ 0, SD ¼ 1) and higher numbers mean greater centrality. (From Beauchamp et al. (2021) with permission)

particularly that both evening hyperphagia and nocturnal ingestion of food – both symptoms in Criterion A and considered defining features of NES – were not the most central symptoms. Other researchers of network theory, however, have emphasized that central symptoms do not have to be hallmark symptoms of a disorder and are instead conceptualized as having greater importance (i.e., driving or maintaining forces in a network; Borsboom 2017; McNally 2021). Beauchamp et al. (2021) claimed that perhaps evening hyperphagia and nocturnal ingestion of food are not the most important symptoms, but are instead resulting behaviors in a symptom chain that begin with depressed mood and urge to eat during the night, respectively. In examining the connections between symptoms in the NES network model to determine this potential symptom chain, Beauchamp et al. (2021) found that depressed mood was directly associated with disturbances in sleep, stress, circadian rhythm patterns, and the urge to eat between dinner and sleep, with no other direct connections to remaining NES symptoms. Of course, this would mean that if depressed mood was indeed the most central symptom, it appeared that increases in depressed mood would correlate with poorer sleep quality (which was also the

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Fig. 5 Bootstrapped strength difference results. Values on the diagonal indicate unstandardized strength centrality values for the corresponding symptom. Black boxes represent significant differences in strength between symptoms, and gray boxes represent nonsignificant differences. (From Beauchamp et al. (2021) with permission)

second most central symptom), increased stress, a preferred evening circadian pattern, and increased urges to eat between dinner and sleep. Indeed, this connection eventually leads to evening hyperphagia. In addition, urge to eat during the night (the third most central symptom) was directly associated with the need to eat in order to sleep and nocturnal eating (i.e., nocturnal ingestion of food). Therefore, it is likely that two symptom chains exist, whether alone or concurrently, and are ordered such that (a) an individual may feel that they have an urge to eat during the night which makes returning to sleep virtually impossible, and so they engage in nocturnal ingestions of food, and/or (b) a combination of depressed mood and poor sleep, along with an urge to eat between dinner and sleep, cascades through additional symptoms and eventually results in evening hyperphagia. The authors caution that

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the directionality and temporal ordering of these associations are unclear due to the cross-sectional nature of the data and that these results need to be confirmed with longitudinal studies.

Clinical Implications The conceptualization of NES through the lens of network theory presents several advantages from a clinical standpoint. Beauchamp et al. (2021) indicated that the three central symptoms (i.e., depressed mood, poor sleep quality, and urge to eat during the night) can be considered primary intervention targets, as treating these symptoms may lead to disruptions in the symptom chain that maintain NES. Indeed, researchers exploring EDs with network analysis postulate that interventions that target highly central symptoms may also greatly impact other symptoms in the network (Levinson et al. 2018b). In addition, changes to the most central symptoms seen in psychopathology networks have been strongly associated with changes in overall symptom severity compared to changes in less central symptoms (Robinaugh et al. 2016). Researchers have cautioned, however, that it is also possible that central symptoms may arise as the consequence of other symptoms, or a bidirectional relationship may occur and central symptoms may be both a cause and consequence (Levinson et al. 2018b; McNally 2021). In addition, it is questionable if current psychological treatments could target a specific symptom without simultaneously impacting adjacent symptoms in the network (McNally 2021). Nevertheless, extant literature supports targeting highly central symptoms as a means to provide treatment (Levinson et al. 2018b) or predict treatment outcomes (Hilbert et al. 2020; Elliott et al. 2020; Brown et al. 2020). An additional domain of conceptual and clinical utility explored by Beauchamp et al. (2021) was NES symptom heterogeneity as determined by network structure and density. The authors stated that, under current research diagnostic criteria, only three of five symptoms in Criterion C are necessary for a diagnosis of NES. This is consistent with several other DSM-5 diagnoses (e.g., major depressive disorder requiring five or more symptoms from a list of nine), and such heterogeneity is considered another limitation of the medical model paradigm (van Borkulo et al. 2015). As network structure is concerned with the clustering and/or ordering of symptoms (i.e., “where” the symptoms are in the network) and network density is connections between symptoms (i.e., “how” symptoms are connected, how sparse or densely connected is the overall network, and how strong is each individual connection), how might the activation of one symptom (and its connection with core and distal symptoms) lead to differences in presentation and levels of clinical impairment/distress in an individual with NES? In addition, are certain clusters of symptoms more likely than others to sustain NES or might influence prognosis or recovery? Beauchamp et al. (2021) recommended comparisons of different network models between samples (i.e., the network comparison test; van Borkulo et al. 2022). Indeed, such a technique has been used to suggest that (a) network density, as well as certain clusters of symptoms, can predict response to treatment (van Borkulo et al.

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2015; Smith et al. 2019) and (b) network density, but not network structure, is different (i.e., stronger) when comparing clinical versus nonclinical samples (Vanzhula et al. 2019). Therefore, clinical assessments and treatments may wish to target select clusters of symptoms, as well as focus on ways to weaken symptom connections as whole. In addition, network comparisons may be especially useful when evaluating samples of individuals that meet clinical versus subclinical thresholds of NES, particularly with symptoms that require specific occurrence rates (i.e., episodes of nocturnal ingestions of food per week).

Future Directions in Network Analysis of NES This chapter provided a brief overview of NES, an ED presently characterized by a disrupted circadian rhythm resulting in a shifted pattern of food intake in individuals with concomitant alterations in sleep, mood, and eating behaviors. Research to date has conceptualized NES through a medical model paradigm of disease, which suggests that symptoms of NES are the result of an underlying common cause, though this causal mechanism remains poorly understood, and the functional relationships between symptoms are relatively unknown. In addition, the numerous variations in diagnostic criteria for NES have presented a significant challenge in accurately conceptualizing this disorder from a research and clinical perspective. Beauchamp et al. (2021) presented an alternative approach to conceptualization of NES by examining the core symptoms using the network approach to psychopathology. Results from this study suggested that depressed mood, poor sleep quality, and a strong urge to eat during the night after the initiation of sleep were found to be the core symptoms of NES, rather than evening hyperphagia and nocturnal ingestion of food, the key symptoms presented by Allison et al. (2010). Lastly, research and clinical implications of these results were presented. Of course, results from this one study have propagated numerous research questions, and the emergence of network analysis as a technique in the field of psychopathology over the past decade has resulted in several novel methods to allow such further exploration into the psychopathology network of NES. Thus, this chapter closes with a discussion on future directions for network analysis of NES.

Network Comparisons First, among one of the next steps in further exploring the conceptualization of NES using the network approach to psychopathology is to include a larger, more diverse sample. However, it might also be of great benefit to examine group differences with a somewhat different network analysis technique. Recently, Costantini et al. (2019) outlined a new method for estimating and analyzing psychopathology networks, particularly when estimating networks between different groups (e.g., clinical versus nonclinical samples, males versus females, etc.), called the fused graphical lasso (FGL) method. These researchers state that estimating a single network that includes

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all groups will fail to illustrate inter-group differences, but also that estimating a separate network for each group would fail to capture inter-group similarities. In addition, they report that differences observed are likely to arise as much from sampling fluctuations as from true differences. This FGL method more accurately estimates different networks for each group by including group similarities as they occur among the different groups. This technique has also been used in other ED network analysis literature to compare diagnosis and age differences between networks (Schlegl et al. 2021). In addition to making comparisons between demographic variables, it would be important to explore differences in weight status among individuals with NES. As stated above, NES can occur in individuals with and without overweight/obesity. While some studies have found no differences in symptomatology between these two groups, others have found (a) higher incidences of nocturnal awakenings and food consumption, (b) that populations with NES who were persons without overweight/obesity were younger, and (c) that NES symptoms preceded obesity. Indeed, it is unknown if network structure and/or density differs between individuals with and without overweight/obesity. Also, it is possible that BMI does not represent the appropriate cutoff that differentiates such network differences between those with and without overweight/obesity. These classifications are based on a BMI cutoff of 25 kg/m2. Future studies can explore this by identifying where networks differ on a BMI continuum through the use of model-based recursive partitioning. This technique uses decision trees to detect optimal splits on selected variables by assessing parameter instability and is seen as similar to a moderation analysis (e.g., examining how parameters differ based on subgroups; Jones et al. 2020). This technique could more accurately explore exactly where network differences are on a continuum of BMI, rather than by cutoff.

Temporal Network Analysis Models Second, future studies should also include longitudinal analyses of individuals with NES via temporal time-series networks. Network analysis models developed from cross-sectional data are limited in their ability to model within-subject variance or to account for changes across time. Newer methods that can assess for intraindividual differences have been developed to capture this within-subject variation and more accurately how symptoms maintain disorders at both group and individual levels (Fisher et al. 2017; Epskamp et al. 2018b). These temporal group-level models (i.e., multilevel vector autoregression models) can assess for intraindividual differences across time, between-subjects similarity, and differences between the withinand between-subjects networks. This would require large amounts of frequent longitudinal datapoints, and such methods have been used in prior ED network analysis research by adopting ecological momentary assessment (Levinson et al. 2018a) or perceived causal relations (Klintwall et al. 2021) techniques. Notably, Levinson and colleagues (Levinson et al. 2018a) claim that better understanding how symptoms maintain themselves at both group and individual levels will lead to

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(1) the development of novel, personalized treatments and (2) explaining the large amounts of heterogeneity among EDs.

Refine Intervention Targets Lastly, newer literature on network theory has called into question the usefulness of identifying central symptoms as effective treatment targets, particularly among models using cross-sectional data (Henry et al. 2021; Lunansky et al. 2021). These researchers have argued that symptom centrality is based on structure/density of the network, but do not account for network dynamics (i.e., how symptoms influence one another; Lunansky et al. 2021). While they do not rule out the usefulness of temporal time-series networks, these authors suggest using concepts from control theory (a discipline from the field of mathematics that deals with controlling dynamic systems; Henry et al. 2021) to facilitate the selection of intervention targets. Indeed, such an approach can not only identify the best symptom (or set of symptoms) to target for intervention, but can estimate how effective the intervention might be on affecting other symptoms in the network (Henry et al. 2021). Conversely, this technique can also estimate which symptom would have the most profound effect on activating other symptoms (i.e., which symptom, after being influenced by an external event, would set off the cascade of symptoms leading to the presentation of a disorder; Lunansky et al. 2021). In light of these potential findings, the utilization of such an approach in a sample of individuals with NES should be prioritized.

Applications to Other Eating Disorders This chapter reviewed the application of the network approach to psychopathology on NES to explore the core features and symptom relationships in an NES network. This approach has already been used to estimate network models among other EDs, particularly to explore the reconceptualization of ED psychopathology, to predict treatment outcomes, and to develop novel, personalized treatments. However, the NES network is unique among other ED networks in that it included symptoms that are related to, but not specific to, ED behavior (e.g., mood, circadian rhythm, sleep, and stress). Indeed, few other ED networks include such nonspecific symptoms (Monteleone and Cascino 2021), and including a broader range of these symptoms in network estimation may help refine ED conceptualization, explore symptom connections between EDs and comorbid disorders, and capture central symptoms more accurately. In addition, given the high rates of heterogeneity in ED symptom presentation and response to treatment, researchers have suggested including more general psychopathology symptoms, as well as external field factors, to help explain interindividual differences in treatment response (Levinson et al. 2018a; Monteleone and Cascino 2021). While these clinical applications have yet to be explored with an NES network, efforts to conceptualize NES with the network approach to

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psychopathology have found that NES-specific symptoms (i.e., evening hyperphagia and nocturnal ingestion of food) were not of great importance to the network. Rather, non-NES-specific symptoms (e.g., depressed mood, poor sleep quality) were found among the most central symptoms in the network.

Mini-Dictionary of Terms • Centrality. A relative measure of a node’s overall importance (i.e., influence) within a network. • Concentration networks. Networks that are estimated using partial correlations. Edges between nodes can be interpreted as relationships that exist when the effects of all other nodes are accounted for. • Network approach to psychopathology. An approach to conceptualizing psychiatric disorders that focuses on how a network of causal interactions among symptoms influences the development and maintenance of the disorder. • Night eating syndrome (NES). An eating disorder currently characterized by a delayed circadian pattern of eating that results in increased consumption of food after the evening meal and/or eating during the night after awakening from sleep. Individuals with NES may also experience reduced eating behavior during the morning, as well as changes in sleep and mood. • Strength and expected influence. Two widely used centrality indices that determine how strongly a node is directly connected with all other nodes in a network. Expected influence accounts for the valence of a connection and is more accurate than strength when networks have negative edges.

Key Facts of Night Eating Syndrome and Network Analysis of Features Key Facts of Night Eating Syndrome Night eating syndrome (NES) was first identified in 1955 by Stunkard and colleagues as a cluster of nonnormative eating behaviors that came during periods of stress in individuals with obesity. Prevalence rates for NES are about 1.5% for the general population and are higher in populations with obesity (6–16%; up to 55% in patients undergoing bariatric surgery for obesity), but not all individuals with NES are persons with overweight/ obesity. NES has not been recognized as a separate diagnosis in the Diagnostic and Statistical Manual of Mental Disorders and is subsumed under the “other specified feeding and eating disorder” category. Specified diagnostic criteria were proposed in 2010 by Allison and colleagues to provide as standardized definition of NES for clinical and research purposes.

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Core features of NES include the consumption of
25% of total daily calories after the evening meal (i.e., evening hyperphagia) and/or nocturnal ingestions of food after awakening from sleep. When conceptualized with the network approach to psychopathology, these core features are not the most important symptoms in the NES network model. Depressed mood, poor sleep quality, and a strong urge to eat during the night after the initiation of sleep were considered the most important symptoms. According to the network approach to psychopathology, these symptoms may cause evening hyperphagia and nocturnal ingestions of food and should be considered primary intervention targets.

Summary Points • Night eating syndrome (NES) is an eating disorder characterized by the consumption of
25% of total daily calories after the evening meal (i.e., evening hyperphagia) and/or nocturnal ingestions of food after awakening from sleep. • Conceptualizations of NES have been based on the medical model paradigm of disease, which assumes an underlying mechanism that causes symptoms. • Other eating disorders have been reconceptualized using the network approach to psychopathology, which assumes a functional, causal network of symptoms. • Network analysis can be used to model the network approach to psychopathology and can assess for symptoms that are most important or influential to the network. • Evening hyperphagia and nocturnal ingestions are not the most important symptoms in an NES model; rather depressed mood, poor sleep quality, and a strong urge to eat during the night are considered most important. • These three important symptoms may be the cause of evening hyperphagia and nocturnal ingestions and should be considered primary intervention targets. • Beyond more accurately conceptualizing NES, network analysis can also be used to examine group differences (i.e., gender, weight status), understand how symptoms maintain themselves, and facilitate the selection of intervention targets.

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Yaara Shimshoni and Eli R. Lebowitz

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ARFID in Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prevalence of ARFID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Impact of ARFID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Differential Diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Etiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Assessment of ARFID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Treatment of ARFID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mini-Dictionary of Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1236 1237 1237 1238 1239 1240 1241 1242 1243 1251 1251 1253 1254

Abstract

Avoidant/restrictive food intake disorder (ARFID) is characterized by dietary restrictions that are not based on weight or shape concerns but that result in marked interference in feeding, growth, or psychosocial functioning (American Psychiatric Association, Diagnostic and statistical manual of mental disorders, 5th edn. American Psychiatric Publishing, Arlington, 2013; Eddy et al., Int J Eat Disord 52(4):361–366. https://doi.org/10.1002/eat.23042, 2019). ARFID was introduced as a diagnostic category in the 5th edition of the DSM in 2013, and research into ARFID remains limited and provides only partial understanding of the different aspects of the problem such as its prevalence, characteristics and driving factors, assessment, and treatment. The aim of this chapter is to summarize and discuss this knowledge with a focus on childhood ARFID. Y. Shimshoni (*) · E. R. Lebowitz Yale University Child Study Center, New Haven, CT, USA e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_74

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Keywords

Avoidant/restrictive food eating disorder · Assessment · Children · Prevalence · Clinical presentation · Treatment · Etiology · Differential diagnosis

Introduction Avoidant/restrictive food intake disorder (ARFID) was introduced in the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM) in 2013 as an expansion of the DSM-4 diagnosis of feeding and eating disorder of infancy and early childhood (American Psychiatric Association 2013). This change allowed for individuals – children and adults – with significant food selectivity who previously did not meet diagnostic criteria for feeding and eating disorder of infancy and early childhood to receive recognition in the DSM. The main changes were the removal of restrictions on the age of onset (which was previously before age 6 years) and on weight (which previously had to be low). A similar diagnosis of ARFID has been recently included in the newest version of the International Classification of Diseases (ICD-11), which is the World Health Organization’s comprehensive classification system for all diseases and health problems (Claudino et al. 2019). The inclusion of ARFID in the ICD-11 indicates that this eating problem is gaining universal recognition. Individuals with ARFID limit the variety or quantity of foods they eat to the extent that these limitations are associated with marked interference in feeding, growth, or psychosocial functioning (American Psychiatric Association 2013). While many young children, especially between the ages of 2 and 5, exhibit picky eating which is usually not severe and tends to resolve over time (Taylor et al. 2015), ARFID is different. To meet a diagnosis of ARFID, the restricted eating must persist and lead to meaningful interference in at least one of the following ways: (a) weight loss or failure to gain weight; (b) nutritional deficiency; (c) dependence on nutritional supplements or enteral feeding (e.g., tube feeding); or (d) psychosocial impairment such as difficulty with friends, at school, in the family domain or experiencing personal feelings of distress (DSM-5, criteria A1–A4). There are also several exclusion criteria. First, the restricted eating cannot be driven by fear of gaining weight or by distorted body image. If this is the case, a different eating disorder such as anorexia nervosa or bulimia nervosa might be considered. Additionally, the restricted eating cannot be due to lack of available foods or cultural norms. It is possible for ARFID to co-occur with other psychiatric or medical conditions, although to qualify for an ARFID diagnosis in addition to other conditions, the eating problem must meet criterion A and be severe enough to require specific clinical attention, beyond what would be expected for the co-occurring problem (DSM-5 criteria B–D). Although seemingly clear, the operationalization of these diagnostic criteria has ambiguities, potentially contributing to inconsistent findings on various aspects of ARFID, including assessment, prevalence, correlates, course, and treatment, all of

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which impede our understanding of this problem. For example, one recently published study sought to examine the degree to which different operationalizations of the diagnostic criterion A for ARFID contributed to differences in the frequency of individuals who were eligible for an ARFID diagnosis (Harshman et al. 2021). These researchers identified 19 different potential operational definitions and determined how many individuals in a sample of 80 individuals enrolled in an avoidant/ restrictive eating study (children, adolescents, and young adults) would meet for ARFID using each of the definitions. They found considerable differences in ARFID diagnosis eligibility depending on the operational definition utilized. Using the strictest definition, 50.0% (n ¼ 40) of participants met criteria for ARFID, while the application of the most lenient definition led to nearly double that number, resulting in 97.5% (n ¼ 78) meeting criteria for ARFID. For an in-depth account of the challenges relating to the diagnosis and operationalization of the ARFID diagnostic criteria, see a summary by the Radcliffe ARFID Workgroup, a cohort of international experts in the field of feeding and eating disorders (Eddy et al. 2019), and a systematic review of diagnostic validity in ARFID (Strand et al. 2019). Although there are many aspects of ARFID that are not well understood, since its official introduction in 2013, research into this eating disorder has been rapidly expanding. This chapter aims to provide a summary of current evidence-based understanding of ARFID – its characteristics, impact, etiology, assessment, and available treatments. Of note, although ARFID can be diagnosed throughout the lifespan, the vast majority of publications to date focus on ARFID in children and adolescents (Strand et al. 2019). For this reason, this chapter will focus on findings relating to ARFID in this population.

ARFID in Children Characteristics Current research into the clinical characteristics of ARFID highlights its heterogeneity. For example, some children with ARFID are underweight, while others maintain average and even above-average weight, often due to supplements intake, tube feeding, or consuming mostly energy-dense processed foods. Some have a long-lasting history of difficulty with food intake, often dating back to infancy, while others may have started only recently to restrict their intake, perhaps following a choking incident or severe stomach bug. Some have additional medical or mental problems that impact their eating, such as gastrointestinal problems, oral-sensory motor problems, autism spectrum disorder (ASD), or anxiety, while others do not. For some, the ARFID manifests in significant nutritional deficiency (e.g., low levels of minerals like iron, zinc, and magnesium and vitamins A, C, and D), while for others most ARFID-related impairment occurs in the psychosocial domain (e.g., interfering with the ability to function well with friends and family members and at school).

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The DSM provides examples of factors that may be driving the restriction in eating: (a) apparent limited interest in eating or poor appetite; (b) selectivity of foods based on their sensory properties such as smell, texture, color, and temperature; and (c) fear of aversive consequences from eating such as choking, vomiting, or gastrointestinal pain (American Psychiatric Association 2013). The validity of these three distinct presentations has been examined and is gaining support (Norris et al. 2018; Zickgraf et al. 2019a). Based on these phenomenological distinctions, Thomas et al. (2017c) proposed a three-dimensional model of the neurobiology of ARFID, rooting these phenomenological distinctions in neurobiological abnormalities in sensory perception, homeostatic appetite, and negative valence systems (for further elaboration see below under “Etiology”). It is important to note that these three presentations are not mutually exclusive, and it is not rare to encounter children whose symptoms fit more than one of these presentations. For example, one paper reported on the case of an 11-year-old boy who showed features of all three ARFID presentations. This child presented with a lifelong history of sensory sensitivity, apparent limited interest in food, and phobia of vomiting, all resulting in him restricting his diet to a single food item (yogurt) for more than 5 years (Dolman et al. 2021). Additionally, Zickgraf et al. (2019a) identified a fourth subgroup of patients who exhibited both poor appetite and selective eating. This group had the longest history of growth faltering and was least likely to present with acute weight loss. Further, the DSM recognizes that there could be additional factors driving the restricted eating, though these are not yet well described. For example, one study of children and adolescents referred to a hospitalbased pediatric eating disorder service and diagnosed with ARFID (N ¼ 102, ages 8–18 years) identified age, weight, and duration of illness as factors influencing the presentation of ARIFD. In this sample, adolescents (ages 12–18 years) presented with higher rates of depression compared with children (ages 8–11 years); those with chronic ARFID symptoms (12 months) presented with significantly lower weight than those with acute symptoms (5

Alcohol (yes, no) Tobacco (yes, no) Drugs (yes, no)

ORTO-15 (35)

32.8
11.6

Smoking (yes, no) Alcohol (yes, no)

ORTO-15

Addiction measure used (cutoff)

38.8
10.7 26.8
5.0 30.0
11.2

1899 high school 17.3
1.0 students (52.5% f)

118 yoga practitioners (92.4% f) 787 medical students (40.9% f)

44 opera singers (54.5% f) 28 ballet dancers (71.4% f) 22 symphony orchestra (50.0% f) 193 gym members (58.5% f)

Turkey

Portugal

Sample

Country

Almeida et al. (2018)

Authors Substance use Aksoydan and Camci (2009)

OrNe Total sample measure age used (M
SD) (cutoffa)

Table 2 Summary of study characteristics included in the narrative review

(continued)

No sig. differences between OrNe cases (n ¼ 100) and non-cases (n ¼ 93) in alcohol consumption, tobacco use, and drug use No sig. differences between nonsmokers and smokers (n ¼ 12) in ORTO-11 Lower ORTO-11 (¼higher OrNe) in smokers The more packs the lower ORTO-11 Higher risk for cutoff 40 (but not 35 or 33) when nonsmoking (odds ratio ¼ 1.44)

No sig. lower ORTO-15 (¼higher OrNe) in nonsmokers (n ¼ 52) and non-alcohol consumers (n ¼ 55)

Main findingsb

66 Orthorexic Eating and Addictions: Links with Substance Use,. . . 1333

Turkey

Poland

Karakus et al. (2017)

Łucka et al. (2019a); Łucka et al. 2019b)

Oberle et al. (2021) United States of America

Country

Authors

Table 2 (continued)

?

ORTO-11

847 adults (82% f) 21.72
6.74 ONI

864 junior f: 20.2
3.3 ORTO-15 secondary, senior m: (35) secondary, and 18.93
3.67 university students (69% f)

208 nutrition and dietetics students (86% f)

Sample

OrNe Total sample measure age used (M
SD) (cutoffa)

Smoking status (earlier, current, never) Alcohol (never, 1–3 x/month, 1–2 x/wk, more often) Drugs (never, few times in my life, 1–3 x/month, 1–2 x/wk, more often) Psychoactive substances used by relatives (none, alcohol, cigarettes, drugs) Alcohol (x drinks/wk) Smoking (yes, no)

x/wk) Drugs (never, occasionally, 1–5 x/month, 1–5 x/wk, >5 x/wk) Smoking (never smoked, quit smoking, current smoker) Alcohol (yes, no)

Addiction measure used (cutoff)

Sig. correlation with alcohol (r ¼ 0.09) No sig. differences between smokers (n ¼ 212) and nonsmokers in ONI

No sig. differences between nonsmokers (n ¼ 181) and smokers in ORTO-11 No sig. differences between alcohol nonconsumers (n ¼ 170) and consumers in ORTO-11 No sig. difference between OrNe cases (n ¼ 240) and non-cases in alcohol, smoking, drugs, and substance use of relatives

ORTO-15 sig. related to nonsmoking (direction not shown) Alcohol and drugs not reported

Main findingsb

1334 J. Strahler et al.

Yılmaz et al. (2020)

63 patients with OCD (63.5% f)

810 students (89.4% f)

Varga et al. (2014)

Hungary

328 adults of a clinical sample (56.7% f)

Sample 2: 242 adults (63.2% f)

Spain

Vaccari et al. (2021) Italy

1120 students (70.4% f)

Poland

Plichta and JezewskaZychowicz (2020) Roncero et al. (2017)

454 students (65.0% f)

Spain

Parra-Fernández et al. (2018)

ORTO-15

ORTO-11Hu

ORTO-11

32.4
10.4

34.7
10.5

ORTO-15 ORTO-11

ORTO-15 (35)

ORTO-11ES (25)

36.5
13.8

18–35, categorical 93.3% 25 24.9
7.1

Median: 20 (19–22)

Smoking (no, 20 cigarettes) Alcohol (yes, everyday or almost everyday, sometimes (maximum 1–2 x/wk), never or almost never) Smoking status (current, former, never) Alcohol (never, rarely, monthly, weekly, several times per wk, daily) Smoking (details missing) Alcohol (details missing)

Smoking (yes, no) Alcohol (yes, no)

Food frequency questionnaire (FFQ-6)

Smoking (yes, no)

No sig. correlations (continued)

No sig. differences between smoking statuses in ORTO-11-Hu Sig. lower ORTO-11-Hu (¼higher OrNe) with less alcohol consumption

Sig. differences (direction not reported) between smokers (n ¼ 92) and nonsmokers in ORTO-11-ES No sig. difference in OrNe prevalence between smokers (18%) and nonsmokers (12%) Alcohol consumption categories equally distributed among OrNe cases (n ¼ 317) and non-cases Lower ORTO-11 (¼ lower OrNe) in consumers of alcohol than in nonconsumers (d ¼ 0.29) No sig. effects for ORTO-15 and smoking in ORTO-11 No sig. difference between OrNe cases (n ¼ 195) and non-cases in smoking and alcohol consumption

66 Orthorexic Eating and Addictions: Links with Substance Use,. . . 1335

Behavioral addictions Exercise addiction Freire et al. (2020) Brazil

Strahler et al. (2018) Germany

Authors Country Substance abuse Oberle et al. (2022) United States of America

Table 2 (continued)

60 exercise practitioners (63.3% f)

713 adults (79.8% f)

26.6
7.8

29.4
11.2

Addiction measure used (cutoff)

ORTO-15

SDE

Alcohol (yes, no) Smoking status (yes, no) Drugs (yes, no) Alcohol (5-p scale never to 4+ x/wk) Smoking (5-p scale 0–5 cigarettes to 30+ cigarettes/d) Drugs (5-p scale not at all to >20x/12 mo) CDS AUDIT UNCOPE DOS (30) Fagerström current smoker (yes, no) AUDIT drug use (yes, no)

471 adults (86% f) 19.98
3.56 ONI

Sample

OrNe Total sample measure age used (M
SD) (cutoffa)

No sign. correlation (r ¼ 0.14)

Addiction measures did not predict DOS No sig. differences between OrNe cases (n ¼ 27) and non-cases in number of smokers, degree of dependence to tobacco smoking, AUDIT, current drug use

No sig. differences between users and nonusers (alcohol, smoke, drugs) No sig. correlation with smoking, alcohol, marijuana, illicit stimulant, opiate, or hallucinogen drugs Sig. correlation with illicit depressant drugs (r ¼ 0.12) No sig. correlation with CDS, AUDIT, and UNCOPE

Main findingsb

1336 J. Strahler et al.

Hungary

Greece

United States

White et al. (2020)

Food addiction Grammatikopoulou et al. (2018)

Germany

Rudolph (2018)

Oberle et al. (2018) United States of America (ethnically diverse, 38% white) Oberle et al. (2021) United States of America Strahler et al. (2021) Germany

Kiss-Leizer and Rigo (2019)

DOS

672 adults (75.5% 27.7
11.1 f) 1008 fitness club 29.4
11.6 members (44.5% f) 103 male students 19.8
1.7

176 undergraduate 21.7
1.9 students (79.6% f) BOT (4)

ORTO-7

DOS

ONI

847 adults (82% f) 21.7
6.7

Sample 20.3
1.9 1: 228 psychology students (89.5% f)

ORTO-11Hu (low risk 35, medium risk 30–34, high risk 29) EHQ

739 adults with 29.7
10.2 interest in sport and diet (79.2% f)

mYFAS

EDS

EAI

EAI

CET subscales rule-driven behavior and exercise rigidity

EAI CET subscales rule-driven behavior and exercise rigidity

Guilt if skipping training (5-p scale always to never)

(continued)

No sig. difference between OrNe cases (n ¼ 120) and non-cases in mYFAS

Sig. correlation (r ¼ 0.519)

Sig. correlation with CET exercise rigidity (r ¼ 0.37), CET rule-driven (r ¼ 0.59) Gender-specific sig. correlations (rf ¼ 0.337, rm ¼ 0.500 Sig. correlation (r ¼ 0.421)

Sig. correlation with EAI (r ¼ 0.37), CET rule-driven behavior (r ¼ 0.41), CET exercise rigidity (r ¼ 0.42)

Guilt: low risk < medium risk < high risk

66 Orthorexic Eating and Addictions: Links with Substance Use,. . . 1337

969 medical and nursing students using social media (63.9% f)

Sample Social Media Addiction Scale

21.4
3.2 ORTO-15 (40)

Addiction measure used (cutoff)

OrNe Total sample measure age used (M
SD) (cutoffa)

Higher risk for cutoff ORTO-15  40 when high/very high addicted (odds ratio ¼ 1.37)

Main findingsb

Abbreviations: M, mean; SD, standard deviation; OrNe, orthorexia nervosa; ORTO-15/11/11Hu/8/R, questionnaire for the assessment of orthorexia nervosa and its versions; EHQ, Eating Habits Questionnaire; DOS; Düsseldorf Orthorexia Scale; BOT; Bratman Orthorexia Test; ONI, Orthorexia Nervosa Inventory; SDE, Scale of Dedication to Exercise; EDS, Exercise Dependence Scale; EAI, Exercise Addiction Inventory; CET, Compulsive Exercise Test; AUDIT, Alcohol Use Disorders Identification Test; Fagerström, the Fagerström Test for Nicotine Dependence; CDS, Cigarette Dependence Scale; UNCOPE, brief screen for DSM–5 substance use disorders; mYFAS, modified Yale Food Addiction Scale;?, not reported; f, females; wk., week; h, hours; x, times; r, correlation; sig., significant a Cutoff only shown if of relevance for analyses b Reports refer to findings and analyses from primary study

Authors Country Social media addiction Yılmazel (2021) Turkey

Table 2 (continued)

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Comorbidity Between Orthorexia Nervosa and Substance-Related Addictions The obsessivity, marked rigidity, and overcontrol with which individuals with orthorexic tendencies pursue their dietary behaviors despite profound negative consequences are similar to a maladaptive cycle seen in individuals with addictions. Addictive disorders were originally inextricably linked to the use of psychotropic substances. Those are defined as naturally occurring, synthetically produced, or chemically prepared substances that affect the central nervous system resulting in the alteration of perception, cognition, emotion, and behavior as well as the increase of the subjective psychical and physical well-being (American Psychiatric Association 2013). Discussing OrNe as a possible addiction, the question arises on what substance those affected are addicted to? Since the diets, which individuals with orthorexic eating behaviors follow and perceive as healthy, and the beliefs regarding the overestimated effects of foods vary, no specific foods or substances seem to be intertwined with OrNe (Bratman and Knight 2000; Barthels et al. 2015). Hence, there is no substance of abuse in OrNe; rather, some individuals may report emotional reward from the absence of the intake of unhealthy foods (Singh 2014). Individuals with OrNe seem to be “addicted” to the sensation of controlling their health and diet. Thus, excessive control over food intake, self-control in particular, may somehow become reinforcing. This is in stark contrast to substance-related addiction where indulgence of psychotropic substances culminates in high-risk consumption, and a loss of control over the usage may occur. The substance may be used more frequently, in larger quantities, or for longer durations than intended, thus interfering with areas of social or occupational activities and leading to conflicts. Moreover, a substantial time investment may be required to obtain the substance, intoxication, or recovery from said intoxication (American Psychiatric Association 2013). To some extent, the aspect of substance abuse seems applicable to OrNe. Since orthorexic eating behavior is characterized by high cognitive and behavioral occupation, the time invested in meal planning and preparation may lead to impairments in other areas of life. In addition, individuals affected by OrNe may refuse dinner invitations or have conflicts with friends or family because of a sense of moral superiority (Cena et al. 2019). Thus, similar to substance abuse, there is a loss of control over the preoccupation with healthy eating. While attempts to reduce or control usage of psychotropic substances fail, consumption is continued in order to achieve the state of intoxication – despite its negative consequences such as interpersonal conflicts or decrease of mental and physical health. Hence, a substance use disorder is considered present when a maladaptive pattern of substance use leads to clinically significant distress or impairment in social, occupational, or other important areas of functioning. Furthermore, physical addiction is given in a substance use disorder when tolerance has developed, i.e., an elevated dose is required to achieve the same extent of intoxication, or withdrawal symptoms occur (American Psychiatric Association 2013). Indeed, the diets of individuals affected by OrNe are assumed to get more rigid over time (Bratman and Knight 2000; Barthels et al. 2015). However, there is no study investigating the time course of said dietary

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restriction, to date. Overall, the characteristics of OrNe and substance use disorders do not appear to coincide sufficiently to classify OrNe as the latter. Empirical evidence regarding this hypothesis is sparse, and comorbidity between orthorexic behaviors and substance abuse is currently unknown.

Empirical Evidence for a Link Between Orthorexia Nervosa and Substance (Ab)Use Our literature search revealed only a few reports on legal (and illegal) substance use mostly suggesting similar orthorexic behaviors between smokers and nonsmokers (12 studies) and no relation to alcohol consumption (8 studies). For more study details, the reader is referred to Table 2. For smoking, two further studies reported significant differences, one showing a higher prevalence of orthorexic behaviors (Hyrnik et al. 2016) and one showing a lower prevalence in nonsmokers (Fidan et al. 2010). Two additional reports indicated higher orthorexic behaviors to be related to less alcohol consumption (Varga et al. 2014; Roncero et al. 2017). Furthermore, (illicit) drug use has been examined in four studies producing mainly null findings. The only significant result was a positive but small correlation with illicit depressant drug use (r ¼ 0.12). Substance abuse and substance-related addictions have been examined in only two cross-sectional studies. There was no relation with the Fagerström Test for Nicotine Dependence or the Cigarette Dependence Scale, the Alcohol Use Disorders Identification Test, and the brief screen for DSM-5 substance use disorders (Strahler et al. 2018; Oberle et al. 2022). Considering the characteristics of OrNe, i.e., consuming only foods of highest nutritional quality, makes alcohol, tobacco, medication, or illegal drug use very unlikely in these individuals. Previous null findings are therefore rather unsurprising. Importantly, due to the instruments used, most previous research only allows a limited conclusion on actual orthorexic behavior, which goes beyond the interest in healthy eating. In addition, investigated samples, i.e., students, young adults, and patients of limited age ranges, do not permit generalization.

Comorbidity Between Orthorexia Nervosa and Behavioral Addictions Somewhat more appropriate than substance-related disorders seem to be the comparison of orthorexic behaviors with the so-called behavioral addictions. In the case of behavioral addictions, a behavior is exhibited excessively and is experienced as “out of control.” In analogy to substance use disorders, six components of behavioral addictions can be described as follows: Salience refers to the elevated importance the behavior has for the individual. Thus, a high amount of emotional, cognitive, and behavioral preoccupation is involved leading to symptoms such as craving or social isolation. Negative emotional or physical consequences are experienced when the behavior is discontinued or reduced (i.e., withdrawal). In contrast, positive changes in mood are the consequences to the additive behavior which may be used as a

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coping strategy in emotion regulation (i.e., mood modification). Furthermore, tolerance develops as the desired effects can solely be achieved by exhibiting more of the behavior. Hence, conflicts with others (e.g., friends and family), with other activities (e.g., occupation and education), or with the individuals themselves (intrapsychic conflicts) arise. Despite possible insight to the negative consequences, attempts to reduce the behavior fail or relapses to initial problematic quantity or intensity of behavior occur (Griffiths 2005). But not every behavior seems to have the potential to lead to an addiction. So far, evidence for gambling and computer gaming has been sufficient for both to be considered in international classification systems (DSM-5, ICD-11). In addition, other potentially addictive behaviors are currently discussed to be of pathological relevance, e.g., excessive and compulsive exercising or internet use (Griffiths 2005).

Phenomenological Overlap of Orthorexia Nervosa and Behavioral Addictions Orthorexia nervosa has also been considered as a possible behavioral addiction (Strahler and Stark 2019). While some symptoms of orthorexic eating seem to be compatible with the components of behavioral addictions as healthy eating occupies the highest priority in daily life, there is neither evidence for tolerance nor withdrawal symptoms to date. Withdrawal symptoms in substance-related addictions are rather severe and may comprise physical (e.g., sweating, flushes, nausea, vomiting) as well as psychological symptoms (e.g., depression, anxiety, hallucinations). There are no such reports for orthorexia nervosa so far. Tolerance is theoretically assumed, i.e., increasingly rigid eating, but has not yet been studied. Nevertheless, orthorexic tendencies have been studied in relation to exercise addiction, food addiction, and social media addiction. The Link Between Orthorexia Nervosa and Exercise (Addiction) A balanced diet and physical activity are two essential lifestyle factors for maintaining physical and mental health and well-being. Just as for the quality of the diet, regular exercise can become an obsession, and the pursuit of health and fitness can become the focus of one’s life. Due to the high importance of health and fitness for people with orthorexia nervosa, it was assumed that this behavior is also associated with increased physical activity and exercise behaviors. For example, studies in at-risk populations show that people who are active in sports, such as gym members, sports students, or yoga practitioners, should be considered as a risk group for developing orthorexic eating behaviors (Eriksson et al. 2008; Rudolph 2018). Correlative studies of individuals from the general population or students paint a rather inconsistent picture with some studies finding exercise and sports activity associated with orthorexia nervosa and others finding no associations. A recent meta-analysis summarized data from 21 studies and quantified the relationship between physical activity behaviors and orthorexic tendencies as r ¼ 0.09 to r ¼ 0.19 (Strahler et al. 2022). Regular exercise can also evolve from a healthy habit to an excessive, limitless, repetitive addiction to physical activity. In terms of clinical classification, exercise addiction (alternatively also compulsive exercise) should be

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classified as a non-substance-related behavioral addiction (Hausenblas and Downs 2002; Griffiths 2005; Colledge et al. 2020). Comorbidity between orthorexic eating and addictive exercise behaviors has been examined in seven studies thus far (summarized in Table 2). Findings predominantly indicate moderate correlations between r ¼ 0.34 and r ¼ 0.59 (Rudolph 2018; Oberle et al. 2021; Strahler et al. 2021), and only one study found no correlation (Freire et al. 2020). The metaanalysis mentioned above puts the mean effect at r ¼ 0.29 (Strahler et al. 2022). There is initial evidence for gender-specific correlations with higher scores in men as compared to women (Strahler et al. 2021) suggesting separate pathological mechanisms among genders. Research on factors contributing to this difference does not exist yet. Theoretical assumptions range from differences in health beliefs (Courtenay et al. 2002) to personality (Strahler et al. 2021), body image (BrytekMatera et al. 2015; Brytek-Matera et al. 2017), and coping (Matud 2004). Overall, OrNe and exercise addiction appear as overlapping conditions with idiosyncratic clinical hallmarks. Another clinical syndrome that co-occurs with exercise addiction is disordered eating. More precisely, the presence of an eating disorder increases the risk for a comorbid exercise addiction by 3.71 times according to a recent metaanalysis (Trott et al. 2021). Hence, eating pathology seems to be linked with addictive exercising. Additionally, addictive behaviors might co-occur (Sussman 2017).

The Link Between Orthorexia Nervosa and Food Addiction Hauck et al. (2020) investigated to what extent compulsive exercising and food addiction correlate within an athlete sample. In fact, both behavioral addictions were positively associated. According to the authors, it is questionable, however, whether highly processed and energy providing foods may be used to fuel one’s body for the excessive amounts of exercise and optimize performances or whether they were overconsumed due to their addictive potential. It is controversially discussed whether food itself may be addictive at all (Fletcher and Kenny 2018). Bingeing might be equated with excessive consumption under loss of control triggered by craving or confrontation with a food stimulus. Therefore, specific food groups, e.g., highly processed foods or foods high in sugar and fat, seem to potentially be addictive “substances.” A neurotransmitter system under suspicion to mediate the addictiveness of both food and psychotropic substances is the dopaminergic system. There are a few findings indicating alterations in the mesolimbic dopaminergic systems altering the reward value of food intake. For example, an association between reduced dopamine receptor density and obesity has been found in some (Wang et al. 2001) but not all studies (Ziauddeen and Fletcher 2013). Next to the assumptions of underlying neuronal processes, some researchers emphasize the proximity of high caloric or processed foods and substances, hence favoring the classification of food addiction as a substance use disorder. In fact, one particular macro food group is suspected of triggering addiction-like craving. Carbohydrate craving was established as a construct defined by an overwhelming desire to consume carbohydrate foods in order to increase one’s negative mood as a form of self-medication (Wurtman 1990). It has been hypothesized that this effect for

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carbohydrate foods occurs due to increased serotonin levels and synthesis that result from heightened tryptophan (Wurtman and Wurtman 1995). Currently, however, this hypothesis must be strongly doubted. A recent meta-analysis of the carbohydrate consumption-mood relationship showed no positive effect on any mood measure at any time after their consumption (Mantantzis et al. 2019). Rather, carbohydrate insertion was associated with higher fatigue and less alertness. Others argue that no specific molecule or substance of food groups clearly identifies as addictive and food addiction is thus to be regarded as behavioral addiction. Third, the validity and added value of the food addiction concept over already established eating disorders is questioned (Ziauddeen et al. 2012). Overall, the ongoing debate does not seem to lead to the inclusion of the concept of food addiction in the international classification systems anytime soon (Meule 2019). In regard to commonalities between food addiction and OrNe, there is only one report in Greek undergraduate students revealing no difference between OrNe cases and non-cases in terms of food addiction (Grammatikopoulou et al. 2018). Food groups discussed in regard to food addiction are predominantly of high fat and sugar. Reducing their consumption is commonly recommended (WHO 2000) which makes a ban more likely in the context of orthorexic eating behaviors. Nevertheless, the beliefs and assumptions about which foods are beneficial and detrimental to health are very subjective in OrNe. Not only scientifically based sources of information are used for this purpose, but others as well, such as social media (Bratman and Knight 2000; Håman et al. 2015).

The Link Between Orthorexia Nervosa and Social Media Addiction Some authors argue that orthorexia is not a disorder with pathological value but a lifestyle phenomenon (Håman et al. 2015). In the context of this debate, it has been suggested that social media contributes to an unhealthy fixation with health. Whereas the influence of problematic internet use on eating disorders, such as bulimia nervosa and anorexia nervosa, as well as food preoccupation, is already known (Padín et al. 2021), there is little evidence regarding the effect on orthorexic tendencies. In terms of social media use, two previous studies linked more frequent Instagram use with greater level of orthorexic eating (Turner and Lefevre 2017; Lanitis and Raspin 2020). An effect is not found or at a much lower level found for other social media channels, such as Facebook, Twitter, Pinterest, Google+, Tumblr, and LinkedIn. Initial considerations regarding causal mechanisms about the general relation between problematic internet use and orthorexic tendencies proposed an effect called “echo-chamber” (Turner and Lefevre 2017). This effect describes the tendency of people to assess their mindset and worldview as more common than it really is. This is assumed to happen due to selective usage habits, i.e., predominantly consuming contents that support one’s own assumptions. In this regard, one study employed a thematic analysis to examine individuals’ understanding of the possible links between social media use and eating patterns (Lanitis and Raspin 2020). Qualitative analyses indicated “The Importance of Belonging,” “Health as Art,” and “Craving” as the three main themes suggesting an appeal of healthy eating practices which could generate an overestimation of orthorexic behaviors (Brytek-

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Matera et al. 2015). Furthermore, there are considerations about questionable advices cutting out various food groups. These advices can lead to unbalanced nutrition and even promote the development of an eating disorder (Turner and Lefevre 2017). Using social networks in a nonfunctional way, that is, excessively, experiencing lack of control, and with negative consequences, has parallels with other internet-related behavioral addictions and substance-related disorders. Like OrNe, social media addiction has not yet been accepted as a separate diagnosis in the clinical classification systems (Andreassen 2015). Taking the lack of diagnostic certainty into account, global estimates report prevalences of problematic social media use ranging from 8.6% to 41.9% (Guedes et al. 2016). Studies highlight predisposing factors including depression, anxiety, attention deficit hyperactivity disorder, parallel substance abuse, social deficits, feelings of loneliness, lower selfesteem, and also increased stress vulnerability (Clayton et al. 2013; Moreau et al. 2015; Wegmann and Brand 2019). This parallels findings in OrNe. Research on the association between OrNe and social media addiction is sparse with, to our knowledge, only one study on this topic. Yılmazel (2021) found that orthorexic tendencies occur more frequently in nurses and doctors with high or very high social media addiction. To date, there are many theories but a lack of empirical evidence for an association between social media addiction and orthorexic tendencies.

Conclusion Addictions or substance use disorders are commonly understood as self- and healthharming behaviors. Hence, the missing association of OrNe, in which the optimization of health is aimed through dietary behavior, with substance use and abuse is not surprising. On the conceptual level, known commonalities of OrNe with substance abuse consist in the modulation of anxiety and dysphoric mood as motivational background for obsessive healthy eating and addictive behaviors, respectively (American Psychiatric Association 2013; Koven and Abry 2015; Cena et al. 2019). Whereas the nonconsumption of substances leads to physical and psychological withdrawal symptoms (American Psychiatric Association 2013), the intake of “unhealthy” or forbidden foods is followed by in some way similar negative emotions such as guilt in OrNe (Cena et al. 2019). In contrast, there are no specific “substances” or food groups of interest in OrNe; rather, the control over the subjectively healthy diet itself seems to be addictive even if said diet is inappropriate and malnourishing. Usually, no awareness of the impairment due to orthorexic behaviors arises (Bratman and Knight 2000), while individuals affected by substance use disorders acknowledge the desire to stop substance use and suffer from relapses when impairment becomes noticeable (Raftery et al. 2020). Possibly, but currently unexplored, OrNe is also associated with insight, depending on symptom severity. Moreover, different cultural consequences of performing the behavior occur as maintaining a healthy diet is usually socially accepted and reinforced. In contrast, addictions are particularly stigmatized even compared to other mental disorders (Barry et al. 2014).

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Open Questions and Future Directions But there are still many open questions, the answers to which will contribute to a deeper understanding of the onset and development of orthorexic eating behaviors. For example, are factors that initiate the onset of orthorexic eating distinct from factors that maintain the behavior once started to eat only selected foods (Walsh and Devlin 1998)? Furthermore, the neurobiological mechanisms involved are unknown. Weight loss produced alterations in the neuronal reward system enhancing the reward of weight loss and starvation (Kaye 2008; Keating et al. 2012). Similar effects may contribute to OrNe. Since the reward system is further crucially involved in substance use (MacNicol 2017), this may resemble effects by OrNe and substance abuse. Overall, it is difficult to understand similarities between OrNe and addictions without grater knowledge of the complex etiology and pathogenesis that characterize OrNe. This also applies to the behavioral addictions discussed here in the chapter. While some neurobiological mechanisms are suspected to play a role in exercise addiction and food addiction, their contribution is still unclear and controversial (Hausenblas and Downs 2002; Fletcher and Kenny 2018; McComb and Mills 2019). Nevertheless, OrNe appears to be moderately associated with exercise addiction suggesting the possibility of shared or related underlying mechanisms (Strahler et al. 2022). The evidence on food and internet addiction is too limited to allow any conclusion, but negligible associations currently appear likely (Grammatikopoulou et al. 2018; Yılmazel 2021). In terms of substance-related and behavioral addiction, OrNe is similar in the excessive levels of cognitive, behavioral, and emotional preoccupation. However, there are crucial features of addictions, such as tolerance, lacking empirical evidence in orthorexic eating behaviors. Despite many unanswered questions, the compilation of findings in this chapter makes a close link to addictions unlikely. Rather, OrNe’s closeness to the eating disorders suggest its classification within this category (Bartel et al. 2020). Practically, a deeper understanding regarding the etiology of OrNe is not only needed to indicate its clinical relevance and justification as a disorder on its own right but is also necessary to identify appropriate therapy methods and strategies. Nowadays, it is therefore recommended that therapy may be based on the guidelines for eating disorders rather than those for addictions.

Application to Other Eating Disorders In this chapter, we have systematically reviewed current evidence about the link between orthorexia nervosa and addictive behaviors. Orthorexia nervosa is not included in current psychiatric classification systems, but above all, a closeness to eating disorders is considered most likely (Bartel et al. 2020). Hence, this chapter’s question was also based on the assumption from the field of eating disorders, according to which the known eating disorders are also related to substance abuse. For the known eating disorders, a relation with, e.g., smoking has been reported as a strategy to control weight and appetite (Devoe et al. 2021). However, the harmful

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consequences of such substances would contrast with the motives for pursuing orthorexic eating behaviors. The goal of maintaining and optimizing long-term health instead of weight loss makes an association seem unlikely. Based on the present literature review, there was no link between OrNe and substance use and abuse. Behavioral addictions, defined as compulsive and excessive non-substance-related behaviors, have only rarely been studied so far. The most likely conclusion to be drawn here is a link with compulsive and excessive exercise behavior and sports. This corresponds to the known comorbidity of additive exercising and eating disorders. Research on other additive behaviors (food addiction, internet addiction) does not permit any conclusions. One of the most important research questions, beyond this behaviors’ pathological relevance, at present is the establishment of ON as an independent disorder category and thus differentiation from established disorders. The few studies that look at anorectic and orthorexic eating behavior in the course of therapy could also offer an auspicious approach in differentiating eating disorder and orthorexic symptomatology. Such studies demonstrate that while there is improvement of anorexic symptoms, orthorexic eating increases throughout therapy (Segura-Garcia et al. 2015; Barthels et al. 2017). This has been interpreted in terms of orthorexic eating to be a compensatory weight regulation strategy in patients with AN. Clinicians should be aware of orthorexic behaviors as compensatory behaviors in individuals with eating disorders and should consider screening for OrNe. In addition, possible links with social media use provide another relevant aspect not only in understanding risk factors but also in establishing prevention and intervention strategies. Overall, pathological eating behaviors are public health concerns that need to be understood in a multidimensional model of risk factors and determinants, i.e., genetic vulnerability, biological needs, cognitive-affective motives, psychosocial demands, and environmental factors.

Mini-Dictionary of Terms • Behavioral addictions. Defined as a compulsion to engage in rewarding, nonsubstance-related behavior despite negative consequences and with the presence of functional impairment. The most recent version of the International Classification of Diseases (ICD-11) considers gambling disorder and gaming disorder. A number of other behavioral addictions are proposed, including buying-shopping disorder, pornography use disorder, and social networks use disorder. • Carbohydrate craving. An overwhelming desire to eat carbohydrate foods as a self-medication to increase one’s mood. • Exercise addiction. Also exercise dependence or pathological exercising. Excessive volumes and feelings of lost control with exercising and sports, exercise is priority in life and is continued despite injuries and impairments in other important areas of life.

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• Obsessive-compulsive symptoms/disorder (OCD). A group of symptoms characterized by recurrent unwanted thought (¼ obsessions) and/or repetitive behaviors that a person feels the urge to do repeat over and over (¼ compulsions). OCD is an anxiety disorder. • Orthorexia nervosa. The obsessive fixation on healthy eating. Self-imposed rigid dietary rules aim at optimizing and maintaining health. • Psychotropic substances. Substances whose intake alters the perception, cognition, emotion, and behavior as well as increases acute physical and psychological well-being of the consumer. Different psychotropic substances lead to specific states of intoxication. • Substance use disorder. A mental disorder in which the maladaptive pattern of substance use leads to clinically significant distress or impairment in social, occupational, or other important areas of functioning.

Key Facts of Orthorexia Nervosa Within the Debate of Categorization as New Mental Disorder • Orthorexia nervosa is a newly proposed harmful eating behavior where the individual is obsessed with the quality of diet and restricts his/her diet. • Orthorexia nervosa can lead to severe weight loss, malnutrition, emotional distress, and impairments in daily functioning. • Orthorexia nervosa shares features with known eating disorders (e.g., need for control, anxiety, perfectionism, overvalued ideas concerning diet) but is also different (e.g., focus on quality vs. quantity of diet, less consumption of legal drugs). • Addictive exercise is usually linked to an eating disorder. Similar associations are seen for orthorexia nervosa. • So far, it is unclear whether orthorexia nervosa is an illness adversely affecting a person or how much it differs from known disorders. • Current therapeutic approaches resemble those used in the treatment of eating disorders.

Summary Points • Orthorexia nervosa and substance use disorders seem to share phenomenological commonalities leading to maladaptive cycles: modulation of anxiety and dysphoric mood, high time investment, and cognitive and behavioral preoccupation. • Since orthorexic eating behaviors are aimed at optimizing health, the consumption of psychotropic substances seems unlikely in orthorexia nervosa. • The systematic literature search found no evidence for an unequivocal link between orthorexic eating behaviors and substance use or abuse to date.

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• Orthorexia nervosa has been suspected to be a behavioral addiction, but its placement within the eating disorder spectrum seems more appropriate. • Orthorexia nervosa is moderately and positively related to exercise addiction. • There are research gaps regarding the link of orthorexia nervosa with other behavioral addictions such as food and internet addiction.

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Symptoms of Orthorexia Nervosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Negative Effects of Orthorexia on Health and Functionality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prevalence of Orthorexia Nervosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Diagnostic Criteria of Orthorexia Nervosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Definition of Obsessive-Compulsive Disorder and Its Relationship with Eating Disorders . . . Association of Orthorexia Nervosa with Obsessive-Compulsive Disorder . . . . . . . . . . . . . . . . . . . Obsessive-Compulsive Disorder-Related Cognitive Features of Orthorexia Nervosa . . . . . . . . Association of Orthorexia Nervosa with Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Association of Orthorexia Nervosa with Anorexia Nervosa and Bulimia Nervosa . . . . . . . Distinguishing Features of Orthorexia Nervosa from Anorexia Nervosa and Bulimia Nervosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Association of Orthorexia Nervosa with Avoidant-Restrictive Food Intake Disorder . . . . Association of Orthorexia Nervosa with Other Mental Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . Association of Orthorexia Nervosa with Obsessive-Compulsive Personality Disorder . . . Association of Orthorexia Nervosa with Somatoform Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . Association of Orthorexia Nervosa with Psychotic Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Unique Features of Orthorexia Nervosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Orthorexia Nervosa and Healthy Living Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Orthorexia Nervosa and Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Orthorexia Nervosa and Social Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Smoking and Alcohol Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vegetarian Diet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Is Orthorexia Nervosa a Separate Mental Disorder? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Treatment and Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Applications to Other Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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L. Tamam (*) Department of Psychiatry, School of Medicine, Cukurova University, Adana, Turkey e-mail: [email protected] H. Yılmaz Department of Psychiatry, Mersin City Hospital, Mersin, Turkey © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_80

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Key Facts of Orthorexia Nervosa with Obsessive-Compulsive Symptoms . . . . . . . . . . . . . . . . . . . 1375 Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1375 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1375

Abstract

Orthorexia nervosa is a phenomenon defined as a pathological focus on healthy eating. It is assumed that it shares some common features and possibly overlaps with other mental disorders, especially eating disorders and obsessivecompulsive disorder. Research on orthorexia nervosa has been increasing recently. In this section, the definition of orthorexia nervosa, its clinical and sociodemographic characteristics, and its relationship with other mental disorders, especially obsessive-compulsive disorder, are evaluated. Keywords

Orthorexia nervosa · Obsessive-compulsive disorder · ED · Ritual · Exercise · Healthy eating Abbreviations

AN ARFID BN DSM EDs OCD OCPD ON

Anorexia nervosa Avoidant-restrictive food intake disorder Bulimia nervosa Diagnostic and Statistical Manual of Mental Disorders Eating disorders Obsessive-compulsive disorder Obsessive-compulsive personality disorder Orthorexia nervosa

Introduction The nature of the relationship between diet and health has long been debated. In recent years, awareness of healthy eating has increased markedly and has become one of the primary concerns of developed and developing societies (Brytek-Matera et al. 2017). Currently, the World Health Organization recommends reducing sugar, fat, and salt intake, eating plenty of fruits and vegetables, and frequently exercising to lead a healthy life (Norum 2005). The craving for healthy food is not a disorder in itself. However, among some people, interest in healthy eating can turn into obsessive symptoms. The concept of orthorexia nervosa (ON) was first defined by Bratman in 1997 to express the pathological focus on consuming healthy foods and was later elaborated in a book written by Bratman (Bratman and Knight 2000). As a word, “Ortho” means “true, real, complete, valid.” The word “Orexis” means “hunger, appetite.” Bratman coined the term ON to describe pathological fixation associated

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with the consumption of appropriate, healthy food. Bratman, in his book Health Food Junkies, defines diets as a disease that people do to feel more attentive and clean (Bratman and Knight 2000). ON was first defined as a “maniacal obsession in pursuit of healthy foods” by Donini et al. (2004). This chapter has given credibility to this case and term used to define ON, implying that ON is a concept worthy of scientific research. In the following years, the term ON has spread all over the world, and the number of studies on ON has increased. Researchers debated whether ON should be incorporated into DSM-5 (Diagnostic and Statistical Manual of Mental Disorders Fifth Edition). However, a conjoint expert consensus could not be reached. As a result, it has not been included in the DSM-5 (2013) due to the absence of necessary and vigorous practical data for proper diagnosis. However, some researchers have established some criteria from their clinical experience (Barthels et al. 2015a; Moroze et al. 2015; Setnick 2013).

Symptoms of Orthorexia Nervosa ON is defined as a pathological obsession with healthy eating and nutrition. It is characterized by a restrictive diet, marked eating patterns, and intense evasion of foods alleged to be unhealthy or impure. ON’s focus is on achieving optimum health through strict dietary control (Lucka et al. 2019). Orthorexic individuals who are concerned about the choice of food regarding its purity, origin, whether it contains artificial ingredients or preservatives, etc. become hugely selective about it (Catalina Zamora et al. 2005). They obsessively avoid foods high in artificial colors, genetically modified components, preservatives, flavors, unhealthy salt, fats, or sugar. Since they want their food to be highly pure and free of additives, they can consume many foods raw. The preparation phase, preparation of kitchen utensils and other utensils, is also part of the obsessive ritual (Bartrina 2007). Orthorexic individuals show obsessive thoughts about food while performing tasks such as rituals for stacking and weighing or measuring food products and planning meals (Lucka et al. 2019). Over time, they develop their own unique food rules and eventually fall into a strict diet regimen. Excessive focus on foods and health can lead to the emergence of particularly complex eating patterns that take an unusually long time to execute (e.g., beliefs that one type of food should be taken after a certain amount of time for optimal digestion) (Koven and Abry 2015). This obsession can increase obsessive food-related anxiety, leading to disruptions in social relationships and emotional problems. The change in daily behavior in orthorexic individuals has been defined in four stages (Mathieu 2005). In the first stage, people have excessive thoughts about their food that day and the following days. In the next stage, excessive control and criticism of food products occur. In the third stage, efforts are made to prepare meals following the principles of healthy eating. In the fourth stage, a feeling of success or failure is experienced according to the outcome of previous stages. In ON,

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while the person’s primary purpose is to improve health or lose weight, over time, diet becomes the most central part of their life (Catalina Zamora et al. 2005). When orthorexic individuals feel they are violating a personal food rule by consuming wrong or unhealthy foods, they suffer under morbid thought and psychological torture, punishing themselves with stricter dietary restrictions. Some may think that sticking to a proper diet will help them achieve a sense of perfection by feeling better, pure, or clean (Chaki et al. 2013). This behavior pattern affects a person’s quality of life over time and plays a restrictive role. Finally, the controlled diet they apply to change their lives becomes something that controls their whole life (Getz 2009).

Negative Effects of Orthorexia on Health and Functionality Compulsive obsessions with certain types of food present in ON influence the physiological health of those affected and have significant psychosocial consequences. Orthorexic individuals often spend an excessive amount of time researching their food concerns. They may exhibit behaviors such as long-term research on food and health on the Internet; buying and reading excessive amounts of food, health, and nutrition books; and almost constantly reviewing food labels while shopping at the grocery store (OCD Center of LA 2011). So much so that the quality of the food they consume may become more critical than personal values, interpersonal and social relationships, and career plans (Bağcı Bosi et al. 2007). Bratman noted that orthorexic individuals tend to maintain their diet based on a theory (e.g., macrobiotic diets or diets created for a particular blood type). When diet becomes more restrictive and complex, it will severely affect the person (Bratman and Knight 2000). The strict diet dependency in ON can lead to the removal of many essential nutrients from the diet and various nutrient and mineral deficiencies that may harm the health of individuals and ultimately reduce their quality of life (Bağcı Bosi et al. 2007). Depending on the individual’s beliefs about healthy eating, the resulting diet may follow a vegetarian, gluten-free, or any other diet type (Bratman 2017). Extreme cases of ON may choose to starve rather than eat foods they consider tainted, unsanitary, and unhealthy (Bratman and Knight 2000). Orthorexic individuals dislike letting go of control when it comes to food. They also follow strict, self-imposed rules that determine which and how the combination of foods can be eaten at certain times of the day (Varga et al. 2013). Such rigid eating habits can make it challenging to participate in social activities that revolve around food, such as dinner parties or dining out. This perspective can influence one’s interpretations of others. It may cause different evaluations of people who do not have the same food habits as themselves. Orthorexic individuals do not share the same eating habits as other people and carry certain foods wherever they go. For this reason, social isolation may be inevitable in these individuals over time (Bratman and Knight 2000). An intense feeling of guilt may occur in orthorexic individuals, sometimes when they think they have failed to maintain their rigid eating habits. Over time, food

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choices can become very limited in both variety and calories. These choices may endanger the health of the individual (Costa et al. 2017). Various health problems can be seen after dietary restriction, ranging from nutrient deficiencies to osteopenia, hyponatremia, metabolic acidosis, reduced testosterone levels, and heart rate, as in severe anorexia nervosa (AN) cases (Moroze et al. 2015). One of the most worrisome situations associated with ON is when children inherit orthorexic tendencies similar to their parents. Children who observe their parents’ obsession with certain types of food might imitate this behavior. Sometimes, parents harshly limit their children’s sugar intake or feed their children only with organic food. These restrictions may raise fears in children’s minds that some foods are “bad and dangerous” and that eating these foods can cause damage to them (Getz 2009). Several case studies reported children with orthorexic parents who developed metabolic problems due to orthorexic feeding behavior (Hunter and Crudo 2018).

Prevalence of Orthorexia Nervosa In the general population, AN has a lifetime prevalence rate of 0.5–0.9%, and for bulimia nervosa (BN), this rate is approximately 1.5% (Favaro et al. 2003; Hudson et al. 2007). Since ON is still not accepted as a separate psychiatric diagnosis and there are currently no specific widely accepted diagnostic criteria, we do not know its frequency with certainty. Prevalence rates vary widely based on the scales used and the sample. Most of the studies were conducted using the ORTO-15 scale, and prevalence rates in these studies ranged from 6.9% to 75.2% (Donini et al. 2004; Haddad et al. 2019). The prevalence of ON reaches 90.6% in some groups (Turner and Lefevre 2017). Previous studies primarily evaluated the prevalence of ON in high-risk groups. Kinzl et al. (2006) evaluated ON in dietitians using the Bratman orthorexia test and found the level of orthorexic tendency to be 34.9% and showed that 12.8% of the sample had a higher risk of developing ON. Bağcı Bosi et al. (2007) determined a 45.5% ON trend in Turkey in his study with the ORTO-15 scale. In a study with ORTO-15 scale, Aksoydan and Camci (2009) reported ON prevalence rate as 56.4% among performance artists, 81.8% among opera singers, 32.1% among ballet dancers, and 36.4% among symphony orchestra musicians. Fidan et al. (2010) calculated the ON risk rate in medical students as 43.6% with the ORTO-11 scale. Ramacciotti et al. (2011) found the prevalence rate of ON to be 57.6% in the general population with the ORTO-15 scale. This figure, which is much higher than the prevalence of other EDs, might be because of the inability of the ORTO-15 scale to differentiate healthy eating from orthorexic behaviors (Fig. 1) (Table 1). Later, many scales evaluating ON were developed, and prevalence rates were examined. In studies conducted with the Düsseldorf Orthorexia Scale in a healthy population, consistent results were observed between 2.5% and 6.9% in Germany (Barthels et al. 2015a; Depa et al. 2017; Luck-Sikorski et al. 2019; Rudolph et al.

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Health concerns

Time-consuming research on food and healthy living

Exclusion of certain foods from the diet on the grounds that they are 'unhealthy' or 'impure'

Prolonged meal preparation ritual

Impairment in social functions

Deterioration in metabolic parameters and malnutrition due to strict dietary rules

Fig. 1 Pathways to orthorexia

2017; Strahler et al. 2018) and as 8% in the UK (Chard et al. 2019). In another study with the Orthorexia Nervosa Inventory, the prevalence was found to be 4.5% (Oberle et al. 2021). Orthorexic tendencies might be more common in some specific groups. The literature reports a higher prevalence of ON in specific groups, such as professional artists and ashtanga yoga practitioners (Herranz-Valera et al. 2014). The risk of ON might be higher in physicians, medical students, and dietitians (Herranz-Valera et al. 2014; Segura-Garcia et al. 2012). Besides, regular sports individuals have a higher orthorexic tendency (Bağcı Bosi et al. 2007). In many studies, ON symptomatology was higher among vegetarians and vegans than omnivorous individuals (BrytekMatera et al. 2019; Brytek-Matera 2021). In addition, there are no consistent results on the relationship between ON and age, sex, level of education, and BMI (body mass index), suggesting the presence of cultural influences on orthorexia (Arusoğlu et al. 2008; Varga et al. 2013).

Diagnostic Criteria of Orthorexia Nervosa ON does not yet have a widely accepted clinical definition and diagnostic criteria. However, some researchers have suggested possible valid diagnostic criteria for ON (Barthels et al. 2015b; Dunn and Bratman 2016; Moroze et al. 2015; Setnick 2013). Studies that propose diagnostic criteria for ON include the following standard criteria: (a) obsessive thoughts, preoccupation with healthy eating, and strictly following a restrictive diet (which is believed to be healthy) while strongly evading foods thought to be unhealthy; (b) feelings of high emotional distress accompanying feelings of guilt, shame, and/or anxiety when restrictive dietary guidelines are

Volunteers of Hacettepe University Performance artists, opera singers, ballet dancers, and symphony orchestra musicians

Medical students

Users of social networks University students

General population School-age youth and young adults

University students and social media users

Fidan et al.

Barthels Brytek-Matera et al.

Strahler et al. Lucka et al.

Oberle et al.

USA

Germany Poland

Germany Poland

Turkey

Turkey Turkey

847

713 864

1307 327

878

944 94

692/125

569/144 599/265

904/393 283/44

359/464

578/416 55/39

Gender rates (f/m) 41.9/ 58.1 100

ONI

DOS Polish version of ORTO-15 DOS ORTO-15

ORTO-11

Bratman orthorexia test ORTO-11 ORTO-15

Measure ORTO-15

%3.8 Cutoff 40 point: %76.7 Cutoff 35 point: %27.8 %4.5

Orthorexia nervosa, % 12.8; orthorexic behavior, %34.9 Tool adaptation (no data) Total: %56.4 Opera singers: %81.8 Ballet dancers: %32.1 Symphony orchestra musicians: %36.4 Cutoff points for ORTO11: 27 %36.9 %3.13 %65.1

Prevalence %6.9

Result

Linking Orthorexia and Obsessive-Compulsive Symptoms

Abbreviation: ON, orthorexia nervosa; DOS, Dusseldorf Orthorexia Scale; ONI, Orthorexia Nervosa Inventory

2020

2018 2019

2014 2015a

2010

2008 2009

283

Arusoğlu et al. Aksoydan and Camci

Germany

Female dieticians

Kinzl et al.

2006

Sample size 404

Country Italy

Sample General population sample

Source Donini et al.

Year 2004

Material

Study

Table 1 Prevalence rates of orthorexia nervosa among healthy sample

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violated; (c) physical disorders in which nutritional deficiencies can result in substantial weight loss, malnutrition, and complications of physical health; and (d) psychosocial disorders related to social, occupational, and academic functioning that may result from other diagnoses (Dunn and Bratman 2016; Moroze et al. 2015; Setnick 2013). According to Dunn and Bratman (2016), diagnostic criteria for ON should be as follows in Tables 2, 3, and 4). Table 2 Diagnostic criteria for orthorexia nervosa according to Dunn and Bratman (2016) A. Presence of excessive mental preoccupation with healthy eating, a diet theory, or a set of beliefs whose details may vary individual to individual; overstated emotional distress associated with food choices considered unhealthy; and weight loss, which might occur as a result of dietary choices (this should not be the primary goal): 1. Compulsive behavior and preoccupation with positive and restrictive eating patterns that the individual believes best promote health 2. Violation of the dietary instructions that the individual imposes on himself leads to exaggerated illness fear, a sense of contamination, and negative physical sensations, along with feelings of anxiety and embarrassment 3. Restrictions on nutrition that a person imposes on himself increase over time. Such restriction may involve eliminating all nutrition groups and increasingly frequent “cleanses” (partial fasts) that are considered cleansing/detox. There is no desire to lose weight, but this often leads to weight loss B. Compulsive behavior and preoccupation is defined as a clinical disorder with one of the following: 1. Malnutrition, severe weight loss, and/or other medical complications resulting from a restrictive diet 2. Disruption of social, academic, or professional functioning due to beliefs and behaviors related to healthy eating 3. Evaluation of positive body image, self-esteem, identity, and/or satisfaction with compliance with self-determined “healthy” eating behavior

Table 3 Common and distinguishing features of orthorexia nervosa and OCD Orthorexia nervosa Symptoms associated with healthy eating

Common features Intrusive thoughts (e.g., preparing food) and repetitive behaviors

Egosyntonic intrusive thoughts and repetitive behaviors The main motivation is for pure and healthy nutrition

Excessive time spent on thoughts and behaviors (e.g., on food selection and preparation) Impairment in social functioning

Perfectionism Need to exert control High anxiety levels Abbreviation: OCD, obsessive-compulsive disorder

OCD Nonspecific obsessions and compulsions that may be unrelated to food Obsessions and compulsions that are often perceived as egodystonic

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Table 4 Common and distinguishing features of orthorexia nervosa and eating disorders Orthorexia nervosa No fear of weight loss

Common features Excessive worry about food and eating

Focus on the quality of the food Clear, rationalized rules about eating No disturbances in body image No gender differences

Life and behaviors are arranged to serve special eating habits Impairment in social functioning Malnutrition and weight loss Egosyntonic intrusive thoughts and repetitive behaviors Perfectionism Cognitive rigidity High anxiety levels

Eating disorders Fear of gaining weight Focus of quantity of food Secret rules about eating Disturbances in body image Female>male

Definition of Obsessive-Compulsive Disorder and Its Relationship with Eating Disorders Obsessive-compulsive disorder (OCD) is characterized by time-consuming, usually chronic, and sometimes episodic course, accompanied by obsessions and compulsions (Rasmussen and Tsuang 1986). OCD is usually comorbid with other psychiatric disorders such as depression, anxiety disorders, EDs, OCPD (obsessivecompulsive personality disorder), and suicidal thoughts (Costa and Hardan-Khalil 2019). OCD is a common psychiatric disorder like phobias, major depressive disorder, and substance use (El-Sayegh et al. 2003). The lifetime prevalence rate of OCD is 2.3%, and a 12-month prevalence is 1.2% (Ruscio et al. 2010). The lifetime prevalence of OCD comorbid with EDs was 13.9%, and the current prevalence rate was 8.7%. In fact, cases diagnosed with ED are at 8.9 times more lifetime risk for OCD than healthy controls (Drakes et al. 2021). The lifetime prevalence of comorbid AN among OCD cases ranges from 3 to 17%, and the current prevalence rate ranges between 0% and 2.4% (du Toit et al. 2001; LaSalle et al. 2004; Pinto et al. 2006). The prevalence of comorbid BN among OCD has not been studied extensively as AN, but lifetime prevalence rates range from 3.1% to 10%, and reported current prevalence rates are between 1% and 3.5% (Altman and Shankman 2009). Murphy et al. (2004) found that cases with comorbid OCD and EDs have higher cerebral glucose metabolism, preventing them from effectively completing tasks requiring the prefrontal cortex and caudate nucleus work. They reported similar neurophysiological functioning in OCD and orthorexia. Available data suggest that EDs, including ON, and OCD may share some common underlying features (Table 5).

ED

OCD and ED

Barthels et al.

Patient group OCD, panic disorder, and generalized anxiety disorder

SeguraGarcia et al.

Study Source Poyraz et al.

Italy

Country Turkey

32 (AN, 18; BN, 14)

Material Sample size OCD: 49 PD: 44 GAD: 37

2017a Germany OCD: 30 ED: 40

2015

Year 2015

Relationship with ON Tool OC symptomatology ORTO-11 Checking and dressing/grooming compulsions. There was significant difference between OC symptom severity and orthorexia nervosa. There was no significant difference between patient groups in the mean scores of orthorexia symptom severity ORTO-15 Longitudinal study. OC symptom severity was higher in eating disorder patients than the control group. After 3 years of follow-up, OC symptoms regressed despite an increase in orthorexic tendencies DOS The prevalence of orthorexia in OCD patients was similar to the healthy control group

Table 5 The relationship of orthorexia with obsessive-compulsive symptoms and eating attitude in clinical samples

The prevalence of orthorexia was found to be higher in the patient group with ED compared to the patient group with OCD

Eating disorder patients were followed for 3 years, and a significant increase in orthorexic tendencies was found after treatment

ED Orthorexic tendencies were found to increase as impaired eating attitudes increased in patient groups

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OCD and anxietydepressive spectrum disorder Somatoform disorders

Vaccari et al.

2021

2021

2020

63

OCD: 50 Anxietydepressive spectrum disorder: 42 Germany 31

Italy

Turkey

DOS

Not evaluated

ORTO-11 Current order symmetry obsessions. There was no significant difference between OC symptom severity and orthorexia nervosa ORTO-15 There was no significant difference between patient groups in the mean scores of orthorexia symptom severity

The patients displayed higher levels of orthorexic eating behavior than the control group

Orthorexic tendencies were found to increase as impaired eating attitudes increased in patients with OCD It was found to be associated with a restrictive dietary regime

Abbreviation: ON, orthorexia nervosa; OCD, obsessive-compulsive disorder; DOS, Dusseldorf Orthorexia Scale; EDs, eating disorders; AN, anorexia nervosa; BN, bulimia nervosa; GAD, generalized anxiety disorder; PD, panic disorder; OC, obsessive-compulsive

Barthels et al.

OCD

Yılmaz et al.

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Association of Orthorexia Nervosa with Obsessive-Compulsive Disorder ON shares some common features with other psychiatric disorders such as OCD, AN, OCPD, illness anxiety disorder, somatic symptom disorder, and psychotic disorders (Koven and Abry 2015). Obsessive-compulsive tendencies are one of the most valuable and reliable features of ON. The previous studies consistently show that as obsessive-compulsive tendencies increase, orthorexic symptoms also increase. This trend is independent of the relationship of obsession and compulsion content with food (Poyraz et al. 2015; Roncero et al. 2017; Segura-Garcia et al. 2015). Nevertheless, Moroze et al. (2015) suggested that obsession may be the root of ON. They stated that there might be a continuum between obsessive preoccupation with health and the distress caused by obsessive thoughts and beliefs about healthy eating. Koven and Abry (2015) reported that a potential relationship between ON symptoms and OCD might be considered if repetitive and ritualistic behaviors focus primarily on eating. The symptomatology of ON may be present when a person with an obsessive-compulsive tendency tends to ritually check their nutritional knowledge and increasingly has repetitive thoughts about attaining a better diet (Costa and Hardan-Khalil 2019). ON was defined by the Los Angeles OCD Center (2011) as a hybrid of ED and OCD. Like OCD, ON is characterized by obsessive thoughts (thoughts about certain foods that are dangerously unhealthy) and compulsive behaviors (in this case, avoiding food, doing more research) to minimize the anxiety caused by these obsessive thoughts. Similar to individuals with OCD, repetitive, intrusive thoughts about food and health, excessive worry, order symmetry, contamination and cleanliness obsessions at inappropriate times, as well as dressing, following ritualized and rule-based patterns, arranging food, washing, and controlling compulsions can be seen (Hayles et al. 2017; Yılmaz et al. 2020). Obsession with food intake is the most prominent behavioral association between ON and OCD (Costa et al. 2017). Also, as in individuals with OCD, the frequency of ON in men and women is similar (McComb and Mills 2019) (Table 6).

Table 6 Some magical thoughts about diet and eating If we don’t clean our body somehow, harmful toxins remain inside It’s good for a person to detoxify their body once in a while An incorrect diet causes food to rot in the body The idea that red foods raise hemoglobin is probably valid Since 70% of our body is water, we should have a diet that is approximately 70% water Vegetarian food is spoilt if it has been in contact with meat Animal blood contaminates food

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Obsessive-Compulsive Disorder-Related Cognitive Features of Orthorexia Nervosa Orthorexic individuals have cognitive characteristics similar to individuals diagnosed with AN and OCD. In particular, themes of anxiety, perfectionism, impairment in external observation, and cognitive rigidity are common features of ON, EDs, and OCD. Like patients with OCD, orthorexic individuals devote most of their time to firm rules and overwork, and therefore, a decline in social functions may occur over time. In orthorexic individuals, meal preparation can take much time and may involve ritualistic features such as preparing food to represent compulsive behaviors, whether wood or ceramic materials are used. Similarly, a feature of OCD is the thought that if rituals are not completed, catastrophic consequences will occur in proportion to the perceived threat (Altman and Shankman 2009). This feature can also appear in orthorexic people because they might be uncomfortable when they think they are not following healthy eating instructions adequately. Like patients with OCD, orthorexic cases have restricted time for other activities because adherence to an inflexible eating style affects regular agendas (Dunn and Bratman 2016). In contrast, patients with OCD exhibit obsessions and compulsions that are not limited to eating or food and generally have egodystonic features (Koven and Abry 2015). DSM-5 (2013) stated that the symptoms should not be better explained by the ritualized eating behavior observed in EDs to diagnose OCD. However, although a relationship was found between orthorexic symptoms and obsessive-compulsive tendencies in many studies among the general population, there was no significant increase in orthorexic symptoms in any of the studies conducted with OCD groups (Poyraz et al. 2015; Vaccari et al. 2021; Yılmaz et al. 2020).

Association of Orthorexia Nervosa with Eating Disorders Association of Orthorexia Nervosa with Anorexia Nervosa and Bulimia Nervosa There is some symptomatic overlap between ON and EDs, such as AN and BN. Catalina Zamora et al. (2005) emphasize that in orthorexic individuals, there are obsessive-compulsive mechanisms (rigidity, perfectionism, need to control one’s life overeating), phobic mechanisms (intense anxiety about certain foods and avoidance of these foods), and hypochondriac mechanisms with personality traits similar to restrictive anorexia. In both orthorexic and anorectic individuals, lack of pleasure and control over one’s life shifts to food when it comes to eating. Eating-related behavior dominates one’s life, and one is overly concerned about it. They regulate their behavior and life to serve their particular eating habits. They face weight changes and malnutrition. Both orthorexic and anorectic individuals are achievement-oriented. They interpret sticking to their diet as a sign of self-discipline

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and noncompliance as a failure of self-control. Obsessive-compulsive symptoms in ED and orthorexic individuals are egosyntonic and often do not accept functional disorders associated with their disease (Varga et al. 2013). It has been shown in many studies that as the worsening in eating attitude increases, orthorexic symptoms increase (Arusoğlu et al. 2008, Poyraz et al. 2015, Yılmaz et al. 2020). However, orthorexic individuals focus on food quality, display unrealistic beliefs about food, and exhibit behaviors and desires to maximize health, while anorexic individuals focus on food quantity, and by the time, body image deteriorates and weakens (Brytek-Matera et al. 2015a). However, some authors state that fixation on food quality and type can also be seen in AN because these patients may follow specific strict dietetic instructions (Kummer et al. 2008; Misra et al. 2006). Therefore, adherence to the type of food might not be an essential criterion for ON. In addition, severe weight loss and malnutrition can occur in ON due to selective eating, which may follow a similar course to AN (Brytek-Matera 2012). On the other hand, while AN cases are prone to hide their anorexic behavior, orthorexic individuals are characteristically pleased with their lifestyle and eating choices and often do not hesitate to show it because of their sense of moral superiority (Koven and Abry 2015). In ON, individuals are reported to be motivated by the necessity to accomplish a sense of personal perfection or pureness, in contrast to AN, in which primary motivation is weight loss (Bratman and Knight 2000). However, some studies have suggested that motivation to achieve perfection is also the case for AN (Lilenfeld et al. 2006; Shafran et al. 2002).

Distinguishing Features of Orthorexia Nervosa from Anorexia Nervosa and Bulimia Nervosa Unlike other EDs, ON is not associated with the desire to be thin. The underlying urge appears to be the desire to follow an excellent, healthy, or untainted diet. For example, organic vegetables and fruits might be considered safe foods for both anorexic and orthorexic individuals because they are viewed as healthy and low-calorie foods. However, frozen diet meals often seem acceptable for anorexic individuals but not for cases with orthorexic tendencies. Conversely, while pressed canola oil is an acceptable food for orthorexic individuals, it is seen as an unacceptable food for anorexic individuals who are afraid of gaining weight when they eat it due to its fat content (Getz 2009). In addition, ON differs from AN concerning BMI and gender variables. According to DSM-5 (2013), AN cases have low body weight. AN is more common in women than men, with a ratio of 9:1. On the contrary, symptoms of ON are not negatively correlated with BMI, and there are no differences in prevalence with regard to gender (Mccomb and Mills 2019). Some studies indicate that ON and AN should be considered as disorders at various levels in the continuum of the same psychopathological dimension (SeguraGarcia et al. 2015). It has been proposed that ON symptoms are common among ED patients after treatment. These shared symptoms may be defined as the

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transformation of ED, an undesirable side effect of psychotherapy, or the intellectualization of symptoms evolving into a socially acceptable behavior (Segura-Garcia et al. 2015). Another problem with the relationship between ON and EDs is that they occur together or in succession over time. ON may occur before the onset of ED or may manifest during remission and recovery. On the other hand, ED experts in the UK argue that ON is not currently defined as ED because patients initially do not have low self-esteem, but can lead to eating disorders over time as dieting becomes more challenging (Mac Evilly 2001). Eating habits observed during the course of ON can lead to EDs as they become more restrictive and compulsive. One study suggested that ON is a risk factor for developing an ED, and it should be considered an initial stage rather than a separate disorder (Mac Evilly 2001). Other studies indicate that ON may be a comorbid disorder or a coping strategy to deal with an ED (Brytek-Matera et al. 2015b; Barthels et al. 2017b; Segura-Garcia et al. 2015). According to this view, focusing on healthy foods and reducing reliance on calorie intake may paradoxically lead to increased food variety and reduced risk of weight loss. Although patients continue to be meticulous when choosing their food, they begin to eat more calories which may be the first step toward recovery in EDs.

Association of Orthorexia Nervosa with Avoidant-Restrictive Food Intake Disorder Several studies classified ON as an avoidant-restricted food intake disorder (ARFID) (Moroze et al. 2015, Brytek-Matera et al. 2015b). Both ARFID and ON may be associated with weight loss, malnutrition, and impairment in psychosocial functioning. Some findings common to both ARFID and ON may include increased stress at mealtimes, avoidance or feeling nervous when eating with relatives or friends, inability to maintain relationships due to conflicts about eating habits, and impairments in psychosocial functioning. The ED features in ARFID do not occur during AN or BN, and similar to ON, there is no evidence of body image disturbance or weight anxiety. Like ON, there is no difference in gender prevalence of ARFID, and common comorbidities are anxiety disorders and OCD (APA 2013). These findings partially support the claim that ON might be a subtype of ARFID. However, clinical definitions of ARFID suggest that this disease develops in infancy or early childhood, usually after a traumatic experience with eating. Besides, ON appears to be more influenced by cultural health models learned in early adulthood. ARFID is characterized by avoidance of certain types of food (based on shapes, colors) and fear of the consequences of eating (Kreipe and Palomaki 2012). However, in ARFID, anxiety associated with eating may be the consequence of a traumatic experience (e.g., drowning) or an aversive experience (e.g., regular vomiting) rather than a result of the focus on improving health seen in ON (Bryant-Waugh and Kreipe 2012). The aforementioned risk factors of ARFID are not comprehensive; therefore, the possibility that the addition of food quality-related

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factors or concerns about health loss encountered in ON to future updates of ARFID should not be disregarded.

Association of Orthorexia Nervosa with Other Mental Disorders Association of Orthorexia Nervosa with Obsessive-Compulsive Personality Disorder ON shares some features that overlap with other diagnostic categories, including OCPD. OCPD is a personality disorder manifested by fear and behavioral inhibition. It has prominent similarities with ON like perfectionism, rigid thinking, excessive commitment, extreme morality, and preoccupation with details and perceived rules (Koven and Abry 2015). No studies have examined association rates between OCPD and ON to date, but comorbidity between OCPD and OCD and between OCPD and ED has been comprehensively studied. Studies have shown that OCPD symptoms are closely related to EDs, especially AN, and noticeably predict the development of pathological eating habits (Anderluh et al. 2003; Lilenfeld et al. 2008). Perfectionism, a feature of OCPD, has been accused in the psychopathology of AN and BN (Bardone-Cone et al. 2007). Perfectionism also plays a role in the course of developing and maintaining EDs (Bardone-Cone et al. 2007; Barnes and Caltabiano 2017). The previous studies suggest that cases with ON are also characterized by perfectionism and that perfectionism is a potential risk factor for ON (Koven and Abry 2015; Mathieu 2005; McComb and Mills 2019). The individuals with ON aim to have a perfect diet and to follow strict dietary instructions. Thus, it seems reasonable to think they have perfectionist character traits. Adherence to eating instructions was found to mediate the relationship between perfectionism and EDs (Brown et al. 2012).

Association of Orthorexia Nervosa with Somatoform Disorders The symptoms of ON may also be similar to the health anxiety seen in somatoform disorders. In somatic symptom disorder, patients experience one or more chronic somatic symptoms which can or cannot be explained by medical evaluations, about which they are disproportionately preoccupied or fearful, leading to recurrent use of conventional and sometimes unconventional healthcare services. In illness anxiety disorder, individuals may experience bodily sensations and are extremely worried about the likelihood of an undiagnosed illness, often spending disproportionate time and energy on health problems. Either way, preoccupation with illness can lead to a secondary preoccupation with food and diet to deal with real or perceived illness. The individual may get into a compensatory dietetic program upon dissatisfaction with the conventional medical institutions or on specific advice from healthcare professionals to manage the disease with diet. Although there are few studies investigating the link between somatoform disorders and ON, it is known that health

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anxiety is positively associated with food preoccupation, and there is evidence that health anxiety leads to significant problems in eating patterns (Koven and Abry 2015; Quick et al. 2012). However, longitudinal studies are warranted to further investigate whether health anxiety and somatic symptoms are risk factors for orthorexic eating behavior.

Association of Orthorexia Nervosa with Psychotic Disorders Although there are no robust empirical data on this subject, ON is likely to indicate more severe psychopathology such as psychotic disorders. It is estimated that comorbidity of schizophrenia and eating disorders is generally low. However, the large number of anecdotal cases reporting the development of AN before the first psychotic episode has led to theories stating that the obsessive features of anorexia have the potential to evolve into more precise delusions over time. These theories also claim that nutritional deficiencies from food restriction might trigger psychosis. As ON is a relatively novel concept, prospective studies are needed to decide to what extent ON increases the likelihood of developing schizophrenia, delusional disorder, and related disorders. However, one of the most distinctive features of ON is control over food, which is considered as an attempt to possibly neutralize the loss of internal control experienced in the prodromal phase of schizophrenia (Møller and Husby 2000). In addition, some researchers thought disordered eating might act as a defense mechanism against psychosis (Hugo and Lacey 1998). At the theoretical level, the most related feature of ON with psychotic spectrum is magical thoughts about food, erroneous beliefs based on instinctive laws of contagion (i.e., real or imagined contact with objects continues to influence each other over time or space) (Aarnio and Lindeman 2004; Lindeman et al. 2000). Regardless of their origins (cultural or religious), magical beliefs about food are a medical concern as they can lead to severe nutritional deficiencies through the exclusion and rejection of food. Koven and Abry (2015) stated that independent of its content, high magical thinking is a commonly seen symptom of schizotypal personality disorder and might be a good indicator for possible psychosis.

Unique Features of Orthorexia Nervosa While ON has some commonalities with OCD, EDs, and many other mental illnesses, some emergent symptoms are unique and equivocal to ON. Prominent among the specific symptoms of ON is an extreme obsession with regaining health or getting healthier. People with this disorder are unaware or may not accept the idea that this healthy diet may not be as beneficial for their health as they think. Another unique symptom of ON is that orthorexics are not obsessed with being thin or losing weight. Finally, as Bratman (2000) defines, the notion of being more accurate and superior to other individuals is a symptom not associated with other EDs or OCD.

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Orthorexia Nervosa and Healthy Living Behaviors Orthorexia Nervosa and Exercise In the description of ON, the focus is mostly on eating habits, while other aspects of a healthy lifestyle indicative of ON have not been stated. For example, regular sports activities indisputably play an essential role in maintaining a healthy life, weight management, improving heart function, lowering cholesterol levels, and lowering stress and depression levels. However, its extreme forms may sometimes be associated with EDs (Bratland-Sanda et al. 2010; Ströhle, 2009). Considering that thoughts and behaviors in ON stem from the desire to be in excellent physical health, a commitment to healthy eating may also lead individuals to cover exercise activity as part of a more broad healthy lifestyle. More frequent and moderate physical activity may reveal motivation to pursue a healthy lifestyle. However, it is still possible to consider exercise as a part of the symptom cluster of ON (Kiss-Leizer et al. 2019). Obsessive thought content of ON may be related to sport activities along with healthy eating (Kiss-Leizer et al. 2019). Indeed, higher levels of sport and physical activity are observed among ON symptomatology, which can also transform into exercise dependence to follow a compulsively rigid exercise regimen even during physical illness, injury, or other problems (Malmborg et al. 2017; Segura-García et al. 2012; Varga et al. 2014). Excessive preoccupation with standards, duties, and instructions and need to follow a firm order contribute to the development of both ON and exercise addiction (Strahler and Stark 2019). Interestingly, however, it was revealed that orthorexic people’s motivation to exercise was to manage stress, rejuvenate, and increase positive impact by using exercise as a tool to improve physical health and avoid illness and improve their psychological health (Oberle et al. 2018). However, the association between ON and exercise is very complex and longitudinal studies are needed.

Orthorexia Nervosa and Social Media Several mental health issues are closely related to Instagram and social media use. For example, higher levels of depression, EDs, and related behaviors are seen in young adults compulsively using social media (Carrotte et al. 2015; Lin et al. 2016). Without any scientific evidence, individuals are encouraged to eliminate several food groups from their diets on social media, potentially leading to an unbalanced diet and nutritional problems. In addition, this condition can aggravate psychological complications related to recommended food and, in some cases, lead to EDs such as AN or ON (Turner and Lefevre 2017). The researchers note that Instagram use can result in ON as Instagram allows users to follow mostly food accounts based on their selections. Such selective exposure may make users believe healthy eating is more normative than it is and feel the need to conform to eating habits promoted on Instagram (Turner and Lefevre 2017). Instagram

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users can use different diets (such as Paleo, vegan diet) to meet their compulsive control needs over original eating habits (Santarossa et al. 2019b). Research suggests that ED groups create an environment where they connect and support each other through social media. Attitudes and behaviors of individuals with an unhealthy diet can be endorsed and promoted on social networks and eatingrelated websites. Such attitudes may lead individuals to develop EDs (Borzekowski et al. 2010). Social networking sites provide an almost limitless source for social comparison. Research indicates that especially young and female social media users compare their bodies with the bodies of celebrities and athletes and give them inspiration for a slim and ideal body (Santarossa et al. 2019a; Tiggemann and Zaccardo, 2015). However, studies on the relationship between ON and social media use are still in infancy, and more research is needed in the future.

Smoking and Alcohol Use The obsession with wellness will likely require avoiding smoking and alcohol and including nutritional supplements and other complementary medicine ingredients into the diet. Studies supporting this hypothesis show that ON symptoms are observed more frequently in people who use nutritional supplements, do not smoke, and drink alcohol (Hyrnik et al. 2016; Varga et al. 2014). However, several other studies did not find any relationship between smoking and orthorexic symptoms (Aksoydan and Camci 2009; Fidan et al. 2010). In conclusion, studies to date did not report conclusive findings of a relationship between smoking and alcohol and ON.

Vegetarian Diet The majority of studies show that vegetarians have more orthorexic behavior than those following an omnivorous regime (Brytek-Matera 2021; Brytek-Matera et al. 2019). Elimination of large micro- and macronutrients from a vegetarian diet may cause an increased risk of developing orthorexic behavior (Bratman and Knight 2000). A vegetarian diet is also another acceptable way to cover up disordered eating behaviors in public (Barnett et al. 2016). However, we should conduct more longitudinal studies to find out the role of a vegetarian diet in the development of ON.

Is Orthorexia Nervosa a Separate Mental Disorder? Many people, especially in developed countries, have increased awareness of healthy nutrition, which becomes their primary focus. The increasing incidence of obesity has led to a significant increase in cardiovascular diseases, diabetes, hypertension, osteoarthritis, cancer, and many other health problems, mainly due to a

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sedentary lifestyle. Therefore, concerned people start to be selective about the quality, quantity, and type of food they consume as a key to stay fit and healthy. But there is a subtle difference between being selective about food consumed and developing an obsession with a diet to be healthier. The development of such obsessions about the amount or type of food often leads to abnormal eating patterns and, in some cases, to psychological EDs (Chaki et al. 2013). Orthorexic tendencies can be mentioned when a person restricts himself to a specific diet regimen with an obsessive urge to eat healthy (Getz 2009). In general, ON may come to mind when this condition is long-lasting, and this behavior has serious adverse effects on the person’s quality of life (Bratman and Knight 2000). With the growing media attention to ON, researchers have investigated the validity of ON as a unique disorder. Many have chosen to define ON as a variant of anxiety disorders or EDs (Mathieu 2005). Nevertheless, Bratman has proposed ON to be categorized as a specific ED. Bratman stated that ON and current EDs share many common features, but ON also has several important differences from other EDs (Bratman and Knight 2000). The diagnostic classification of ON is currently unknown. However, Robins and Guze’s (1970) seminal article suggests several steps for a mental disorder to reach diagnostic validity. The first step is the clinical definition currently available for ON. The second step is laboratory studies in which chemical, physiological, anatomical, and radiological findings are included, and psychological tests can be evaluated in this context. There is no generally accepted psychometric scale for ON and more research is needed on this topic. In addition, the neurobiological and neurophysiological basis of orthorexic eating has not been searched thoroughly, and like many other mental disorders, there is no specific laboratory test for diagnosing ON. The third step is differential diagnosis to prove the distinctiveness of a newly proposed diagnostic category and exclusion of other disorders. There has been an overlap between ON, EDs, and OCD in previous studies (Mccomb and Mills 2019). However, mental disorders could often exist together (Kessler 1994). Therefore, the simultaneous comorbidity of different disorders does not eliminate their distinctiveness. Thus to exclude other disorders, the person’s distress should be proved to be caused by ON, not another mental disorder. The fourth and fifth steps, respectively, include follow-up and family studies, none of which were performed for ON. In summary, caution is advised when extending the diagnosis to ON based on the available evidence. Discussions continue in the literature to decide whether ON, for which there are no formal diagnostic criteria yet, should be considered a separate disorder, a variant of another ED, an OCD-related disorder, or just an impaired eating habit (BrytekMatera 2012; Ryman et al. 2019).

Treatment and Management Although there are some recommendations for ON treatment, no studies have been conducted to date on treatment efficacy, other than case studies. The question regarding the classification of ON (a separate syndrome or a manifestation of another

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disorder group) remains unresolved. However, the best intervention requires a multidisciplinary team approach that should include physicians, psychotherapists, and dietitians (Bartrina 2007; Koven and Abry 2015). A combination of drug therapy, psychoeducation, and cognitive-behavioral therapy could be implemented in outpatient settings with close monitoring (Mathieu 2005). In cases of significant malnutrition and weight loss, inpatient treatment may be required (Moroze et al. 2015). During treatment, the individual is encouraged to eat a healthy diet. Orthorexic individuals may believe that giving up orthorexic eating behavior is the same as eating a bad diet. The goal is not to help the individual learn that all foods are healthy. Indeed, there are also foods that can harm health, especially if eaten in excess. The main purpose is to help the individual have a more balanced perspective toward food and learn to eat healthily and with pleasure. In other words, the goal is not to teach the individual to consume potato chips or sodas but to enable them to eat by choice rather than fear. Regarding psychotropic drugs, selective serotonin reuptake inhibitors are reported to be beneficial for ON (Mathieu 2005), which also show some efficacy for both AN and OCD (Simpson et al. 2013). In one study, olanzapine was successfully used to reduce the obsessive nature of thoughts about magic food, and mirtazapine was successfully used in another case study followed up with a diagnosis of ON with comorbid depression (Moroze et al. 2015; Lopes et al. 2020). However, it should be noted that patients with ON may reject psychotropic drugs as they may be viewed as unnatural substances. In psychotherapy, individualized interventions should be used by targeting the symptoms that are evident to the patient. Goals should focus on what patients eat, how they shop, and how they feel about the food they prepare and consume. Exposure and response prevention, together with habit reversal training, may be the most successful approach for treating the obsessive and compulsive aspects of ON (Koven and Abry 2015). Apart from that, providing psychoeducation about valid, current dietary science can help discourage orthorexic individuals from false beliefs about food. According to LA OCD Center (2012), some parts of exposure and response prevention, which is the primary behavioral component of ON therapy, may be as follows: – Gradually adding more types of food to the individual’s diet, comprising healthy foods that she formerly deemed improper – Reducing and eventually eliminating time spent investigating food – Reducing and eventually eliminating the time spent arguing the health impact of food – Return to everyday social life, including eating with others Attention should be paid to refeeding syndrome, which is caused by disturbances in fluid and electrolyte balance. This syndrome occurs when nutrition is quickly reinstated after the body has adapted to hunger and malnutrition in patients who were

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treated as inpatients due to significant weight loss and malnutrition. Refeeding syndrome can progress with sudden cardiac death and seizures and can be fatal. Other symptoms in this syndrome are hypertension, dyspnea, fatigue, weakness, confusion, and arrhythmias. Symptoms typically appear within 4 days of resumption of food intake. The first clinical manifestation of refeeding syndrome is low phosphate level (refeeding hypophosphatemia). Clinicians should be familiar with the signs and symptoms of fatal refeeding syndrome (Zickgraf 2020).

Conclusion ON is an important and growing problem that needs serious consideration. While ON is not yet officially recognized as a disorder, failure to properly identify and treat the condition will cause serious problems for many people who suffer from these symptoms. However, making the patient aware of the extreme and distorted nature of their thoughts and behaviors regarding food purity may respond well to treatment with cognitive behavioral therapy.

Applications to Other Eating Disorders In this section, ON symptoms are defined, and the relationship of ON with OCD and other mental disorders is discussed. ON is a unique phenomenon with distinct features. The obsessive-compulsive mechanisms underlying ON are interesting. Obsessive-compulsive mechanisms have been shown in other EDs, especially in AN and BN. However, it is interesting how critical obsessive mechanisms are under ARFID, which draws attention with some similar aspects to ON. It has been reported that ON can be seen together with other EDs. It is intriguing what the initiating factor is, which mechanisms sustain the process, what are the treatment options in comorbid conditions, or whether ON is a step in the recovery process. Although research on ON has increased, studies on the neurobiological aspects of ON are limited. In the future, revealing the neurobiological basis of ON and showing whether it is associated with OCD and EDs may help to illuminate the place of ON in classification systems. Conducting family and genetic studies related to ON may contribute to elucidating its relationship with other EDs. The prevalence of ON was evaluated in different populations with diverse rating scales and showed inconsistent results. ON prevalence rates seem inconsistent when considering other EDs with more balanced prevalence rates. When standardized assessment tools are developed for ON, prevalence rates of ON can be determined consistently, and the prevalence rates can be compared with other EDs. Consequently, more research conducted with a similar methodology on ON will define the diversity and changes in different cultures and populations.

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Key Facts of Orthorexia Nervosa with Obsessive-Compulsive Symptoms • Orthorexia nervosa is not currently included in the DSM-5. However, research continues to determine its place in diagnosis and classification systems. • The main goal of orthorexia nervosa is to reach optimum health with a healthy and pure diet. • Obsessive-compulsive symptoms are present in many eating disorders, including ON. • It was found that as the severity of obsessive-compulsive symptoms increased, orthorexic symptoms also increased. • The most prominent behavioral association between orthorexia nervosa and OCD is obsessions about food intake.

Summary Points • Orthorexia nervosa is associated with impairment in social, occupational, and academic functioning and physical ailments due to nutrient deficiencies. • Orthorexia nervosa shares some behavioral and cognitive features with OCD and EDs. • Some important common features of orthorexia nervosa and OCD are perfectionism, impaired external observation, high anxiety levels, and deterioration in social functions. • Some overlapping points of orthorexia nervosa with eating disorders are lack of enjoyment of eating, shifting control over life to food, weight changes, and facing malnutrition. • The distinguishing features of orthorexia nervosa are that the main motivation for eating is a sense of perfection and purity, and they see themselves as superior to other people.

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Nerkis Fuentes, Gabriela Nazar, and Miguel Enrique Sa´nchez-Hechavarría

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emotional Eating and Body Mass Index (BMI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emotional Eating and Food Image Stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emotional Eating and Food Craving . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emotional Eating and Loss of Control Eating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emotional Eating and Hunger Inhibitory Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neural Basis of Emotional Eating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emotional Eating and HRV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Applications to Other Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mini Dictionary of Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Emotional eating is a maladaptive generalized behavior to regulate emotions as a momentary solution, and it is characterized by excessive food intake during states of emotional excitement or stress. The heart rate variability (HRV) as an N. Fuentes Doctorado en Psicología. Facultad de Ciencias Sociales, Universidad de Concepción, Concepción, Chile e-mail: [email protected] G. Nazar Departamento de Psicología, Universidad de Concepción y Centro de Vida Saludable, Universidad de Concepción, Concepción, Chile e-mail: [email protected] M. E. Sánchez-Hechavarría (*) Programa de Promoción de la Salud y Prevención de la Enfermedad (PROSALUD) de Núcleo Científico Tecnológico para el Desarrollo Costero Sustentable. Departamento de Ciencias Clínicas y Preclínicas. Facultad de Medicina, Universidad Católica de la Santísima Concepción, Concepción, Chile e-mail: [email protected] © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_81

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evaluative parameter of emotional regulation indicates that the decrease of the vagal tone in the HRV is positively related to deficient self-regulation that might be associated with dysfunctional styles such as emotional eating. The explanatory emotional eating theory sustains this physiological mechanism by suggesting the sympathetic nervous system’s activation and the existence of physiological incompatibilities between the action of eating and the presence of negative emotions which, instead of inhibiting the intake, boosts it. Nevertheless, evidence on the relation between the HRV and emotional eating demonstrates a predominance of the vagal response against the lower food stimulus under stress conditions. Keywords

Emotional eating · Heart rate variability · Cardiac autonomic imbalance

Introduction Emotional eating is characterized by an excessive food intake in states of emotional excitement or stress (Evers et al. 2010; Ouwens et al. 2003; Torres and Nowson 2007). This eating style is conceived as a maladaptive generalized behavior that operates as a momentary response to the regulation of emotions; however, it usually leads to different health problems such as weight gain, obesity, and behavioral eating disorders (Frayn and Knäuper 2018; van Strien et al. 2013). From a physiological point of view, emotional eating has been described as a surprising behavior considering that negative emotions are expected to induce states similar to satiety since they activate the autonomic nervous system (ANS) and appetite-suppressing hormone release. This is the proposal of Kaplan and Kaplan’s psychosomatic hypothesis (1957) which poses that a normal response toward emotional excitement or stress is loss of appetite. Schachter (1968) sustained the same when explaining that negative emotions induce an increase in appetite-suppressing hormones such as catecholamine. Notwithstanding, some people tend to overeat when facing stress conditions or discomfort (Ouwens et al. 2003), contrary to the signals of the organism. Among the explanatory hypotheses of this phenomenon, there are proposals of psychological nature that suggest that food intake induced by uncomfortable emotions derives from a confusion between internal excitement states and hunger, probably due to neglected signals from the organism in early learning experiences during early childhood (Bruch 1964). In this same line, van Strien (2000) claims that among the predictors of emotional eating would be the lack of interoceptive awareness or complications in the identification and recognition of the internal signals of the organism, in this case, hunger or satiety and being able to overeat in front of a certain state of excitement. Another proposal comes from Heatherton and Baumeister (1991), who states the escape theory in which food and eating would be the mechanisms used to escape or divert attention during a negative self-evaluation redirecting it toward more pleasurable stimuli or experiences as the ones that come

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from eating. Besides, a different approach to emotional eating has been described as an inhibited behavior that occurs under dietary restrictions. Polivy and Herman say that dietary restriction sustained over time is translated as exaggerated responsiveness toward external cues such as food characteristics and limited responsiveness toward the external signals of the organism. That is, when intake is permanently under cognitive control (rather than physiological) and is restricted, the sensitivity to the internal cues of hunger and satiety is reduced, resulting in disinhibition and overeating in situations where cognitive control is hampered (Herman and Polivy 1980). Emotional activation, such as stress or negative mood states, would act as inhibitors or disruptors of the restriction. This disinhibition not only occurs when facing dysphoric emotions but also as a response to sensory cues from palatable foods and alcohol consumption or in situations where self-regulatory abilities are reduced with high-stress moments, for instance (Ouwens et al. 2003). There are parameters of physiological nature that function as emotional dysregulation predictors when anticipating maladaptive eating behavior. In this sense, heart rate variability (HRV) is positioned as one of the noninvasive and highly useful measures in clinical research, which allows the analysis of the changes that occur in the balance of the ANS, which facilitates information about certain abnormal physiological conditions (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology 1996). HRV assessment has been conceived as the beat-to-beat rate variation within the heart rate, measured through the R-R intervals of the electrocardiogram over 24 h (Billman et al. 2015). Two indicators of the frequency domain emerge from this analysis: high-frequency power (HF) as an indicator of vagal activity and low-frequency power (LF) as a marker of sympathetic activity. However, LF has gained controversial appreciation since it has also been considered a parameter that includes sympathetic and vagal influence (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology 1996; Reyes del Paso et al. 2013). In general terms, sympathetic activation has been associated with an increase in the LF and a decrease in HRV (Reyes del Paso et al. 2013). This reduction in HRV has been reported in several abnormalities in stress-related emotional regulation (Rodas et al. 2008). According to this, the presence of a link between eating behavior disorders and the presence of cardiac dysautonomia has been proposed (Jelinek et al. 2018; Mazurak et al. 2011), with a connection between this biological maladjustment and the emotional disturbance that leads to food intake. Thus, the diagnostic capacity of HRV allows us to understand the emotional dysregulations of behaviors concerning the decreased ability to regulate cardiac function, which leads to emotional eating (Moore 2018).

Emotional Eating and Body Mass Index (BMI) A relationship between BMI, depression, and emotional eating has been found and is the last one that acts as a mediator which, at the same time, is related to future body weight gain. Likewise, people with dietary difficulties normally present a higher BMI and are more likely to acquire emotional eating disorders (Lazarevich et al.

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2016). In this regard, the dysregulation of emotions exerts an indirect effect on BMI through emotional eating. Therefore, higher levels of emotional dysregulation might be associated with higher levels of emotional eating, which is also associated with higher levels of BMI (Jones et al. 2019). These results are consistent with different studies that suggest that emotional eating is tightly related to emotional dysregulation (Gianini et al. 2013) and weight gain (Grant and Boersma 2005; Koenders and van Strien 2011; Sung et al. 2009; van Strien and Koenders, 2012, 2016). Even though obese people usually present higher rates of emotional eating, this dysfunctional eating style is not exclusive to people with obesity since it is also present in normal-weight population (Palomino Pérez 2020). Other relationships have been established between emotional eating in people who are overweight and a series of negative emotional states such as depression, stress, anxiety, attention deficit, and dysfunctional regulation of emotions. In addition to this, symptomatology in certain eating disorders, body acceptance difficulties, eating self-regulation, and eating self-efficacy in the presence of obesity can be named (Nightingale and Cassin 2019). This indicates a higher susceptibility in people with obesity toward uncontrolled emotional eating provoked by a subjective perception of stress (Wilson et al. 2015). In the analysis of the physiological responses to stress, higher levels of impulsivity, cognitive restraint, uncontrolled emotional eating, and a higher reduction in the HRV have been reported as a response to food stimuli in patients with obesity. The urge for food in the absence of caloric need is thus construed as a vagal disbalance and lack of inhibitory control. These difficulties lead to the perpetuation of unhealthy eating behaviors associated with low HRV in response to stimuli relevant to subjects with psychopathological disorders and obesity (Spitoni et al. 2017) (Fig. 1). Fig. 1 HRV in the relationship between BMI and emotional eating

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Emotional Eating and Food Image Stimuli Visual food stimuli produce brain responses in the limbic centers (Ziv et al. 2020) as well as the activation of SNS under abnormal dietary conditions inducing emotional states in the subject, some of which should inhibit the eating response. By comparing a group of healthy women to others with bulimia nervosa, high caloric food craving in the clinical sample was bigger under the induction of negative emotions. Therefore, a negative mood was associated with higher brain activity in reward-related brain areas when anticipating food intake. In this way, bulimia nervosa is linked to eating in response to negative emotions during the induction of negative emotional stimuli (Lutz et al. 2021). In the analysis of biological and psycho-affective correlates of food image processing in emotional eating and as a response to the induction of negative images, an increased desire for food occurs in individuals with high levels of intake compared to individuals with low levels of intake. Additionally, the image of appetizing food influences the improvement of the emotional state, reducing negative affect (Blechert et al. 2014). It indicates that craving for food increases due to stress, which is contradictory considering that the sympathetic nervous system (SNS) is a suppressor of the digestive response regarding food intake. On the other hand, when relating BMI with food cue responses and HRV, a significant increase in food reactivity of HRV with a sympathetic predominance regarding highly caloric content in subjects with high BMI compared to subjects with low BMI. It proposes that subjects with high BMI have weaker cognitive restraint to food stimuli with high caloric content being more susceptible to food intake in response to appetizing characteristics of food, which is also common in emotionally induced feeding. It may indicate that people who are overweight are more vulnerable to identifying hunger cues and experience dysregulations in eating behaviors; this is verified through HRV (Chang et al. 2021) (Fig. 2).

Emotional Eating and Food Craving Food craving is understood as an intense desire for one specific food (Meule 2018). Several studies report a relationship between highly palatable food cravings, external eating, and emotional eating behaviors (Blau et al. 2018). Different studies have established associations between emotional eating and food craving in individuals at risk of eating disorders, specifically in subjects with binge eating disorders and anorexia nervosa. Also, food craving can be linked to external eating behaviors in people with symptoms of anorexia nervosa, bulimia nervosa, and binge eating (El Archi et al. 2020). Hence, what eating styles such as food craving, emotional eating, external eating, and have in common is the pursuit of emotional rewards instead of responding to biological needs. Thus, an increment in emotional eating might boost a significant increase in the frequency of food cravings (Shnepper 2020). On the other hand, it is coherent with biological cues that food intake gets properly motivated by interoceptive cues of hunger or satiety since it does not depend on inaccurate mechanisms influenced by mood to be triggered. Concerning

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Fig. 2 Relationship between food stimuli and eating behavior. Autonomic response

HF values of HRV in the analysis of maladaptive style, Wu et al. (2020) discovered significant relationships between loss of control in eating and food craving. In this respect, an increased food craving is associated with a lower HF-HRV. This phenomenon responds to the influence that stress exerts on SNS activation over the parasympathetic nervous system (PSNS) in which the individual becomes motivated by the intake instead of suppressing the desire for food. Moreover, food craving has also been found to be associated with this HRV pattern through the lack of control over food intake. In palatable food like chocolate, a lower HRV has been found which precedes increased craving. It means that, due to a lower HRV, deficient automatic regulation plays an important role, relevant in food craving and uncontrolled eating behaviors (Rodríguez-Ruiz et al. 2009) (Fig. 3).

Emotional Eating and Loss of Control Eating Loss of control eating is often a feature in individuals with binge eating episodes. These individuals are characterized by two different components: (a) eating an unusually large amount of food, known as overeating, and (b) feeling unable to

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Fig. 3 Relationship between eating styles and food craving. Autonomic response

stop or resist eating, which is called “loss of control eating” (LOC) (American Psychiatric Association 2013; Vannucci et al. 2013). Emotional eating has been linked to LOC eating when predicting binge eating behavior. Also, emotional eating is usually associated with higher levels of depression, anxiety, and stress (Conceição et al. 2018). Such emotional alterations underlying food intake are commonly driven by the lack of control in eating to avoid negative emotions. In this sense, it has been identified that emotional eating is moderated by LOC eating in association with a significant increase in disordered eating patterns, BMI, and long-term adiposity (Stojek et al. 2017). Responding to stress, HRV informs how emotional regulation behaves concerning LOC eating which may lead to binge eating episodes. In this way, overeating has been associated with a lack of emotional balance and LOC as well as the nonacceptance of emotions. The high severity of these conditions is related to poor flexibility in the ANS with increased LF-HRV and decreased HF-HRV (Godfrey et al. 2019). Young et al. (2017) analyzed LOC eating as the mediator between negative emotional states and HRV. A depressed mood was connected to a lower HF-HRV rate with higher levels of disinhibited eating. For entropy effects, findings were similar to HF-HRV, connecting a reduction of it to emotional states and disinhibited eating. It is important to highlight that minor entropy indicates a minor regulatory capacity of the organism which will affect self-regulation and the control of emotions that leads to eating. It evidences HRV capacity as a stress biomarker in the identification of dysfunctional patterns of emotional regulation and food intake. Lastly, Ranzenhofer et al. (2016) determined that a critical low HRV during the 30 min before emotional eating is associated with eating and LOC (Fig. 4).

Emotional Eating and Hunger Inhibitory Control Lack of inhibitory control impacts the suppression of food cues which causes an inability of individuals to recognize hunger cues and becomes influenced by emotions to execute food intake. The latter can be expressed by an impulsive behavior as a hasty response toward the stimuli or the lack of competence to amend inadequate

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Fig. 4 Relationship between loss of control in feeding and emotional eating. Autonomic response

behaviors (response inhibition). So, this pattern has been associated with obesity and low self-control during food intake (Spitoni et al. 2017). More specifically, a higher negative affect predicts an inability to suppress desirable food cues, implying disinhibition in eating or loss of control associated, at the same time, with a higher level of emotional eating (Zhang et al. 2020). On another side, van Strien et al. (2014) found that inhibitory control moderates emotional eating over food intake. This pattern perpetuates in people who did not experience the typical hungerreduction response after a stress episode. In this regard, inhibitory control has been related to emotional eating (Nelson et al. 2020). Different findings support these assumptions stipulating that emotional eating is connected to major behavioral inhibitory control difficulties, while negative emotions are being suppressed. Aligned to this, it is concluded that inhibiting behavioral responses during the regulation of negative emotions would contribute to a disinhibited intake (Wolz et al. 2021). Rodríguez-Ruiz et al. (2011) examined the loss of inhibitory control through food stimulation to evaluate physiological reactivity in HRV. The results confirmed a lower HF leading to a higher defensive and appetitive reflex toward food stimuli assessed as threatening (high-calorie foods) for women with bulimia nervosa. In this sense, HRV appears to modulate these reactions, which include appetite, food aversive reflex, and loss of control over eating, and supports the assumption that poor emotional and autonomic regulation plays a significant role in lack of inhibitory control (Fig. 5).

Neural Basis of Emotional Eating Emotional eating is related to the hedonic dimension of eating behavior which has its structural and functional basis in the appetite reward systems located in the cerebral cortex and subcortex. From this neural mechanism, the search for gratification follows through food in order to relieve emotional discomfort, which is associated

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Fig. 5 Relationship between loss of inhibitory control and emotional eating. Autonomic response

with a deficit in the capacity for self-control (Suárez Palazón and Mayoral Babiano 2019). Considering this, the findings suggest that it is a tendency in people with emotional eating behaviors to have higher neural activation in response to rewards in front of food stimuli and rewards reinforcing food intake (Bohon et al. 2009). This is evident during the experience of negative emotions and during the anticipation of rewards, where activation of the right frontal lobe has been found, which could reflect the learned resource of food craving as an emotional regulator (Bletcher et al. 2014). During highly appetizing food choices, the visual system is the principal roleplayer, which reacts to food stimuli so the received information can travel through afferent pathways vias and activates structures such as bilateral posterior fusiform gyrus (FG), left orbitofrontal cortex (OFC), and the left mid-insula (van der Laan et al. 2011). Besides, different activation patterns have been discovered specifically in the anterior cingulate cortex (ACC), globus pallidus (GP), thalamus (Bohon et al. 2009), medial OFC, insular cortex (Killgore and Yurgelun-Todd 2006), dorsolateral prefrontal cortex (DL-PFC), and bilateral prefrontal cortex (Wood et al. 2016). Specifically, the activation of the insular cortex has been directly linked to information processing related to food’s taste and its hedonic assessment, and, at the same time, it is involved in impulse control deficit in response to food incentives (Kenny 2011; Wood et al. 2016). Also related to self-control, the activation of subcortical structures such as the tonsil and basal ganglia occurs (Chechlacz et al. 2009; van Bloemendaal et al. 2015). In emotional eating condition there is styles, higher functional connectivity between the OFC - lateral hypothalamus (LH), ventral striatum, anterior insula, and medial temporal lobe networks - medial hypothalamus (MH), LH networks - nucleus accumbens, and the LH of the mesencephalon or midbrain has been detected, with the latter being also associated with the stress response. Moreover, a higher connection in the LF of the mesencephalon has been

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related to a greater presence of an emotional eating style. Thus, the relationship between functional connectivity alterations in both networks, LH and MH, in eating patterns induced by emotions, particularly LH network alterations, has also been associated with higher levels of response toward stress (Martín Pérez et al. 2019). To summarize, evidence demonstrates a tendency to increase neural reactivity under induced stress conditions in the presence of food cues, which, at the same time, appears to be the basis of different background information related to binge eating as clinical symptomology (Fischer et al. 2017) (Fig. 6).

Fig. 6 Relationship between emotional eating with and without BMI mediation. Autonomic response under stress condition

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Emotional Eating and HRV In the theoretical approach to emotional eating, Kaplan and Kaplan’s (1957) psychosomatic approach is positioned as one of the main explanatory theories. From this point of view, it can be established the existence of a tendency to handle negative emotions through eating concerning people who are overweight. In this regard, reference is made to SNS activation (Kaplan and Kaplan 1957), which is associated with a reduction in vagal tone, being the physiological process that would explain an adaptive difficulty of the organism when dealing with stress and that would be related to this dysfunctional eating style (Thayer and Lane 2000). Consistent with this approach, the neurovisceral integration model poses that HRV is an indicator of the self-regulation capacity in the organism in response to external demands meaning that the vagal tone reduction in HRV is connected to a deficient emotional regulation, which might be associated with dysfunctional behaviors such as emotional eating (Thayer and Lane 2000). Nonetheless, considering current findings when HRV is analyzed in people with emotional eating disorder, their physiological response is associated with an activation of the PSNS instead of the SNS. This is demonstrated through the HF band predominance in the HRV (González Velázquez et al. 2020). On another hand, Juarascio et al. (2020) found similar results in relation to changes associated with HRV in response to emotional eating episodes. In this respect, HF bands were predominating in previous moments of emotional eating episodes, suggesting vagal predominance and emerging as a principal and mainly predictive characteristic (Juarascio et al. 2020). This paradoxical response toward a stressful factor could be interpreted as a coping strategy and inadequate compensation associated with positive emotional responses in food intake (González Velázquez et al. 2020). Also, these results imply that people with emotional eating disorders apparently have higher activation of the reward centers in front of food stimuli and negative emotions induced intake (Bohon et al. 2009), explaining that the parasympathetic predominance would be linked to hedonism considering emotional eating behaviors. Likewise, the results remind us that when emotional eating is studied without BMI mediation, the psychophysiological response addressed by these theoretical references is not successfully obtained (Kaplan and Kaplan 1957; Thayer and Lane 2000). Contrary to these assumptions, the vagal response predominates from the activation of the PSNS, which would question the paradigm of psychosomatic theory in the analysis of emotional eating behaviors. Other results support Kaplan’s approach (1957), where the BMI appears to mediate the relationship between food stimuli reactions and HRV, resulting in a predominance of the SNS and a reduction in HRV. In this way, these psychophysiological responses is a mechanism of emotional eating. However, this finding got restrained to people with a high BMI (Chang et al. 2021) resulting in a discrepancy between empirical evidence and theoretical information when trying to explain the psychophysiological mechanism of emotional eating behaviors. On the one hand, the psychological mechanisms involved in the interaction between HRV and emotional eating, which are associated with the self-regulation of emotions, interoception, and inhibitory control, have not yet been studied in depth. On the other hand, the approach to

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emotional eating and the psychophysiological response associated with this eating disorder is restricted to people with obesity. Thus, it is concluded that explanatory reasons for emotional eating are not yet clear, and this explanation remains pending considering the limitations named above (Suárez Palazón and Mayoral Babiano 2019).

Applications to Other Areas Los hallazgos actuales permiten sentar las bases para comprender el mecanismo a través del cual la VFC repercute en la autorregulación que conlleva a la ingesta alimentaria (Meule et al. 2012). En relación a las implicaciones clínicas, este conocimiento permite el diagnóstico de las desregulaciones emocionales que conllevan a comportamientos alimentarios compulsivos como el comer emocional. En este sentido, a través del uso de las nuevas tecnologías como es el caso de los sensores de machine learning, se incluyen métodos eficaces para detectar en tiempo real, los cambios en la VFC y el riesgo de episodios de comer emocional y de conductas alimentarias desadaptativas (Juarascio et al. 2020). Además, se pueden diseñar e implementar intervenciones como biorretroalimentación del hambre como estrategia de afrontamiento que permite a las personas con alimentación emocional, identificar sus sensaciones físicas de hambre (Kalogiratou et al. 2021; Ledoux et al. 2014). En consonancia con esto, la HRV-biofeedback podría ser una herramienta beneficiosa para atenuar el comportamiento alimentario disfuncional (Meule et al. 2012), pues posibilita el desarrollo de estrategias de regulación emocional y locus de control, lo que a su vez genera cambios favorables en el control del peso, teniendo en cuenta el alto índice de obesidad y el riesgo de enfermedades crónicas que existe hoy en día (Ledoux et al. 2014; Meule et al. 2012).

Mini Dictionary of Terms • Biofeedback: Es una técnica de reconocimiento del hambre desarrollada por Mario Ciampolini. Consiste en la le administración de dispositivos portátiles de autocontrol con el que se les indica a los individuos que coman cuando confirmen el hambre física, con el objetivo de controlar el estado de peso. • Comer emocional: Se considera como una tendencia a comer en respuesta a emociones negativas, siendo los alimentos elegidos principalmente ricos en energía y palatables. • Estrés: Se define como una perturbación de la homeostasis e incluye el estresor, la respuesta al estresor y los cambios fisiológicos entre el estresor y la reacción corporal. • Índice de Masa Corporal (IMC): Valor que se obtiene del cálculo en base al peso y la talla y que funciona como indicador para establecer las categorías de peso.

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• Variabilidad de la Frecuencia Cardiaca (VFC): Es un índice de la actividad de la actividad del SNA. Se refiere a la variación latido a latido en la frecuencia cardíaca o la duración del intervalo R-R. • Machine learning: Se basa en el algoritmo de funciones estadísticas a partir de conjuntos de datos multidimensionales que permiten hacer predicciones generalizables sobre individuos.

Summary Points • The psychological mechanisms involved in the interaction between heart rate variability (HRV) and emotional eating are associated with the self-regulation of emotions, interoception, and inhibitory control. • The approach to emotional eating and the psychophysiological response associated with this eating disorder are restricted to people with obesity. • The evidence on the relation between the HRV and emotional eating demonstrates a predominance of the vagal response against the lower food stimulus under stress condition.

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Biologic Aspects of Rumination Syndrome, Eosinophils, and Beyond

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Hunter J. Friesen, Jennifer V. Schurman, and Craig A. Friesen

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Physiology of a Rumination Episode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pathophysiology of Rumination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . GERD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Functional Dyspepsia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rumination Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mini-Dictionary of Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Rumination syndrome is characterized by repeated regurgitation with re-swallowing or spitting. It is associated with both medical and psychosocial complications. It is a disorder of gut-brain interaction resulting from complex and heterogenous interactions across biologic, psychologic, and social systems. Diaphragmatic breathing to compete with abdominal wall contractions is the current mainstay of treatment but is often only associated with partial improvement and high relapse rates. As such, there is a need to develop other treatments to supplement the current behavioral approach, particularly addressing other targets of therapy as defined within the biopsychosocial model. The purpose of this chapter is to describe current knowledge of the biology of rumination syndrome, suggesting other potential therapeutic targets including both mechanical and H. J. Friesen University of Kansas School of Medicine, Kansas City, MO, USA J. V. Schurman · C. A. Friesen (*) Division of Gastroenterology, Hepatology, and Nutrition, Children’s Mercy Kansas City, University of Missouri Kansas City School of Medicine, Kansas City, MO, USA e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_82

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immune dysfunction. Frequent coexistence of GERD and functional dyspepsia has been demonstrated in both adults and children with rumination syndrome, and both may be triggers for rumination. Thus, the biology of both is relevant to rumination, and, as such, the biologic mechanisms of both may represent viable treatment targets in rumination syndrome. Immune dysfunction is now highly implicated in other disorders of gut-brain interaction with emerging data implicating a role in rumination syndrome independent of the presence of functional dyspepsia. Keywords

Rumination syndrome · Gastroesophageal reflux · Functional dyspepsia · Diaphragmatic breathing · Mast cells · Eosinophils · Biopsychosocial model

Introduction Although some variability exists across criteria defining rumination syndrome (see Table 1), rumination syndrome is generally characterized by repeated regurgitation with re-swallowing or spitting of the regurgitated material (Drossman 2016; APA 2013; Hyams et al. 2016). It usually begins shortly after eating, does not occur at Table 1 Rome and DSM-5 criteria for rumination syndrome Adult Rome IV: All of the following: 1. Persistent or recurrent regurgitation of recently ingested food into the mouth with subsequent spitting or remastication and swallowing 2. Regurgitation is not preceded by retching Supportive: effortless regurgitation events are usually not preceded by nausea; regurgitant contains recognizable food which may have a pleasant taste; the process tends to cease when the regurgitated material becomes acidic Pediatric Rome IV: All of the following: 1. Repeated regurgitation and rechewing or expulsion of food that: (a) Begins soon after ingestion of a meal (b) Does not occur during sleep 2. Not preceded by retching 3. After appropriate evaluation, the symptoms cannot be fully explained by another medical condition. An eating disorder must be ruled out DSM-5: Criteria for rumination disorder are: 1. Repeated regurgitation of food for a period of at least 1 month. Regurgitated food may be rechewed, re-swallowed, or spit out 2. The repeated regurgitation is not due to a medication condition (e.g., gastrointestinal condition) 3. The behavior does not occur exclusively in the course of anorexia nervosa, bulimia nervosa, BED, or avoidant/restrictive food intake disorder 4. If occurring in the presence of another mental disorder (e.g., intellectual developmental disorder), it is severe enough to warrant independent clinical attention

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night, and is not preceded by retching. Like other conditions defined by Rome criteria, it is believed to be a disorder of gut-brain interaction. Previously referred to as functional gastrointestinal disorders under Rome criteria, disorders of gut-brain interaction are defined as unique symptom clusters of gastrointestinal symptoms which result from any combination of dysmotility, visceral hypersensitivity, altered mucosal barrier, immune dysfunction, dysbiosis, and/or aberrant central nervous system processing (Drossman 2016). As such, they are the result of complex interactions across biologic, psychologic, and social systems. Rumination syndrome is believed to be underdiagnosed and quite often misdiagnosed as another gastrointestinal condition, particularly gastroesophageal reflux disease (GERD). Reported prevalence in community samples varies from 0.8% to 10.6% in adults and 0% to 9.7% in children and adolescents (Murray et al. 2019; Martinez et al. 2021). The prevalence appears to be much higher in patients seeking evaluation for gastrointestinal symptoms, particularly in pediatrics. Rumination syndrome has been found in 12.8% of adults presenting with “gastric symptoms” (Murray et al. 2019). Rumination syndrome has been reported in 44% of children believed to have treatment-refractory GERD and in 60% of children with chronic vomiting (Nikaki et al. 2020; Malik et al. 2020). These studies suggest that rumination should be considered in all patients seeking care for reflux or dyspeptic symptoms. There is often a large delay between onset of symptoms and diagnosis of rumination syndrome with associated high costs for medical tests and ineffective treatments (O’Brien et al. 1995; Chial et al. 2003; Alioto et al. 2017). There are also high psychosocial costs with school absenteeism and avoidance of work and social settings (Murray et al. 2019; Chial et al. 2003; Malik et al. 2020; Alioto et al. 2017). Additionally, there are medical complications including dental erosions, weight loss, and electrolyte disturbances (Murray et al. 2019; Chial et al. 2003; Malik et al. 2020; Alioto et al. 2017). Disorders of gut-brain interaction are best understood through a biopsychosocial model which states that they are the result of biologic, psychologic, and social factors which are all interactive with each other (see Fig. 1), communicating through neurologic, immunologic, and endocrinologic pathways. These disorders are more likely to respond to treatment packages that identify and treat multiple factors across the full spectrum of the biopsychosocial model. To date, most treatment approaches to rumination syndrome have been directed at psychologic aspects with behavioral interventions to create responses that compete with the abdominal contractions that initiate a rumination episode (as will be discussed). Diaphragmatic breathing is considered the mainstay of treatment for rumination syndrome with very few studies to support other treatments currently (Murray et al. 2019). Diaphragmatic breathing, also known as abdominal breathing, involves engaging the abdominal wall muscles and diaphragm while breathing. As will be discussed, rumination episodes follow strong contractions of the abdominal wall muscles pushing stomach contents into the esophagus and mouth. Diaphragmatic breathing is believed to create a competing response to these contractions (Murray et al. 2019). The evidence for diaphragmatic breathing is meager, including three

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Biologic Genetics Dysmotility/Hypersensitivity Inflammation

Psychologic

Social

Anxiety

Family/Peers

Depression

Teachers/Bosses

Coping/Resilience

Social Determinants of health

Fig. 1 The biopsychosocial model involves interactions between biologic, psychologic, and social factors in the generation of symptoms

prospective trials: two open trials containing a total of 38 patients and one randomized trial of 23 patients (Murray et al. 2019). Diaphragmatic breathing results in a decrease in rumination episodes, but most often some rumination continues, and the relapse rate is rather high, particularly in pediatrics (Murray et al. 2019; Chial et al. 2003; Malik et al. 2020; Alioto and Di Lorenzo 2018). Thus, there is a need to develop other treatments to supplement the current behavioral approach, particularly addressing other targets of therapy as defined within the biopsychosocial model. To date, there has only been one prospective trial of a medication directed at biological aspects of rumination syndrome (Pauwels et al. 2018). The purpose of this chapter is to describe current knowledge of the biology of rumination syndrome.

Physiology of a Rumination Episode The physiologic changes which occur during a rumination episode have been well described in youth and adults during antroduodenal motility evaluations and more recently high-resolution esophageal manometry (Singendonk et al. 2017; Grunder et al. 2017; Rosen et al. 2017; Halland et al. 2020; Tucker et al. 2013; Rommel et al. 2010). Although the trigger for rumination may vary (as discussed later), the final events resulting in regurgitation are quite consistent. Episodes result from strong

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voluntary (but generally unconscious) contraction of abdominal muscles which significantly increases intragastric pressure. An intragastric pressure increase greater than 30 mmHg is specific for rumination, differentiating it from a reflux episode, though a lower pressure may be seen in pediatric patients (Singendonk et al. 2017; Grunder et al. 2017; Halland et al. 2020; Tucker et al. 2013; Rommel et al. 2010). This pressure increase propels gastric contents into the esophagus and into the mouth. On manometry, rumination episodes appear as “R” or retrograde waves. Other features seen on manometry demonstrate overlapping physiology with GERD but also differentiating features. Additionally, reflux may be a triggering event for rumination. Rumination is generally divided into primary rumination, where rumination is not associated with reflux, and secondary rumination where rumination is preceded by reflux which presumably triggers the rumination episode (Rosen et al. 2017; Tucker et al. 2013; Rommel et al. 2010). In adults with rumination syndrome, Rommel and colleagues demonstrated a consistent pattern in 86% of episodes where an initial small increase in gastric pressure was followed by retrograde flow of gastric contents with a subsequent large increase in gastric pressure due to abdominal wall muscle contraction (Rommel et al. 2010). In youth, Rosen and colleagues reported primary rumination in 55.5% and secondary in 44.5% of rumination episodes (Rosen et al. 2017). However, even in those episodes not preceded by reflux, there was often physiology similar to GERD, specifically relaxation of the lower esophageal sphincter (LES). Three patterns were noted in those with primary rumination: LES relaxation followed by an R wave before regurgitation in 51%, an initial R wave followed by LES relaxation in 20%, and an R wave without LES relaxation in 29% (Rosen et al. 2017). Whether different patterns have clinical significance remains to be determined. Rumination episodes differ from reflux episodes in that they are more likely to reach the proximal esophagus and mouth, are more frequently nonacidic postprandial events, and are more likely to be sensed by the patient and associated with symptoms (Nikaki et al. 2020). As the physiology of a rumination episode has been well described, one pathway for treatment involves interventions to disrupt the episodes by inducing competing responses to abdominal wall contractions or to retrograde waves. This is the strategy behind diaphragmatic breathing which is performed to counteract the abdominal contractions. Hard swallows or inducing swallowing by sucking on mints or hard candy or chewing gum has been used to counteract retrograde waves. An alternative strategy would be to attempt to disrupt the pathophysiology that precedes the initiation of the abdominal wall muscle contractions.

Pathophysiology of Rumination Three primary pathways have been proposed for development and maintenance of rumination including (1) a primary pathway where premonitory urges (uncomfortable psychologic or physical symptoms) precede and are relieved by rumination; (2) a pathway involving comorbid pathology, such as GERD; and (3) a pathway

1404 Fig. 2 There is significant overlap in the occurrence of rumination syndrome with functional dyspepsia and/or gastroesophageal reflux

H. J. Friesen et al.

Rumination Syndrome

Functional Dyspepsia

Gastroesophegeal Reflux

involving psychosocial mechanisms where rumination initially relieves an unpleasant physical sensation due to a related condition, such as functional dyspepsia, and continues after the related condition resolves as a learned behavior to contextual clues, such as eating (Murray et al. 2019). There is significant overlap in the presence of rumination syndrome, GERD, and functional dyspepsia which would suggest shared pathophysiology or that GERD and FD are triggers for rumination (see Fig. 2). There is evidence that both are true to differing degrees. Frequent coexistence of GERD and functional dyspepsia has been demonstrated in both adults and children (Geeraerts et al. 2020; Fujiwara and Arakawa 2014; De Bortoli et al. 2018; Friesen et al. 2016). In adults with GERD symptoms occurring at least weekly, there is a nearly sevenfold increase in the prevalence of dyspepsia (Eusebi et al. 2018). Overlap is associated with worse physical and mental health, including increased sleep disturbance, anxiety, and depression (Lee and Chang 2021; Colombo et al. 2021). Significant overlap has been demonstrated between rumination syndrome and GERD with a substantial proportion of rumination syndrome patients having rumination secondary to reflux (Rosen et al. 2017). Significant overlap between rumination syndrome and functional dyspepsia has been demonstrated in population studies (Zand Irani et al. 2021a). In one study of children with rumination syndrome, 18% fulfilled Rome criteria for another functional gastrointestinal disorder (Rajindrajith et al. 2012). In youth with rumination syndrome, concurrent abdominal pain is reported in 23–38%, nausea in 17–30%, and constipation in 21–28% (Chial et al. 2003; Malik et al. 2020). Adults with rumination syndrome report increased postprandial nausea and discomfort as compared to healthy controls (Hoshikawa et al. 2020). Also, in adults with rumination syndrome, postprandial dyspepsia has been reported in 29% and treatment-resistant GERD in 24% (Tucker et al. 2013). As GERD and functional dyspepsia may provide the

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stimulus for rumination episodes, the two conditions represent viable treatment targets in patients with rumination syndrome. As will be discussed, GERD and rumination syndrome share common mechanical features and rumination syndrome, and GERD and functional dyspepsia share common features related to mucosal inflammation. Additionally, reflux and postprandial symptoms seen in functional dyspepsia may be triggers for rumination, with regurgitation providing temporary symptom relief. For example, over 70% of adults report symptoms such as dyspepsia before onset of a rumination episode, symptoms which resolve once the regurgitant reaches the mouth (Tucker et al. 2013). Given the significant links between rumination syndrome, GERD, and functional dyspepsia, further discussion of GERD and functional dyspepsia is warranted.

GERD Rumination syndrome significantly overlaps with GERD in terms of both symptoms and pathophysiology. Most often, patients with rumination syndrome are initially diagnosed with GERD and treated with acid-reducing medications (Murray et al. 2019). The clinical similarities prompted pediatric Rome III criteria to include the requirement that patients not respond to GERD treatment; this requirement was dropped under the current Rome IV criteria (Hyams et al. 2016; Rasquin et al. 2006). “GERD” patients who continue to have symptoms despite treatment are often labeled as refractory GERD before the diagnosis of rumination syndrome is entertained. There are multiple possible explanations for why patients presumed to have GERD may be refractory to acid reduction therapy. Symptoms may be unrelated to GERD. For example, they may be the result of esophageal hypersensitivity (Clarke et al. 2018). This may be more likely with concurrent functional dyspepsia or irritable bowel syndrome which is associated with a decreased rate of symptomatic response to acid-reducing medications (e.g., proton pump inhibitors, PPIs) (Zerbib et al. 2021). As medications are not perfect, acid reflux may continue despite aggressive acid reduction therapy (e.g., twice daily PPIs) (Zerbib et al. 2021). Ultimately, a significant proportion of treatment-refractory “GERD” patients with predominantly post-prandial regurgitation will have rumination syndrome, either primary or secondary to reflux. Up to 90% of gastroesophageal reflux episodes are initiated by transient lower esophageal sphincter relaxations (TLESRs) (Tack and Pandolfino 2018). These are both myogenic and neurogenic phenomena, most often resulting from a vagalmediated reflex initiated by distension of the gastric fundus (proximal stomach) (Clarke et al. 2018; Tack and Pandolfino 2018). TLESRs are also influenced by intraabdominal pressure, neuro-mediators, hormones, and dietary components (Tack and Pandolfino 2018). GABAB receptors, which can be moderated by baclofen (a GABAB agonist), have been assessed in several studies; baclofen decreases TLESRs and increases LES pressure (Clarke et al. 2018; Pauwels et al. 2018;

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Blondeau et al. 2012). Baclofen has been reported to be beneficial in pediatric GERD patients with a sustained response in 81% (Vadlamudi et al. 2013). GERD may also be associated with gastric motor dysfunction. GERD is associated with delayed gastric emptying in up to 45% of patients (Jehangir and Parkman 2020; Gonlachanvit et al. 2006). GERD is associated with proximal gastric retention of both solids and liquids and has been associated with altered gastric accommodation in some, but not all, studies (Gonlachanvit et al. 2006; Penagini 1998; Patcharatrakul et al. 2020; Pauwels et al. 2014). One method for assessing accommodation and gastric sensitivity is to inflate a gastric balloon to increasing volumes in the proximal stomach while measuring pressure and assessing symptoms. With gastric balloon distension, patients with GERD report fullness and discomfort at lower pressures and/or volumes than do controls (Penagini et al. 1998). GERD is also associated with increased esophageal sensitivity which may be relevant given that a significant proportion of rumination episodes are preceded by reflux. Sensitivity plays an important role in symptoms generated by reflux (Tack and Pandolfino 2018). GERD is associated with disruptions in the esophageal epithelial barrier, increased nerve fiber density, and increased expression of TRPV1, a channel associated with hypersensitivity in patients with other functional gastrointestinal disorders (Tack and Pandolfino 2018). Together, these result in hypersensitivity to esophageal distension (Tack and Pandolfino 2018). GERD can also be associated with inflammation, both in the esophagus and downstream within the gastrointestinal tract. While gastric acid may induce a chemical burn, much of the reaction resulting in esophagitis appears to be immune mediated with T cells central to the inflammatory mechanism (Rieder et al. 2007, 2010; Zavala-Solares et al. 2021; Souza et al. 2009; Zand Irani et al. 2021b; Moiseff et al. 2021). The immune response is associated with production of cytokines that can reduce esophageal muscle cell contractions (Rieder et al. 2007). It is likely that inflammation contributes to the altered mucosal barrier and increased sensitivity. GERD has also been associated with duodenal inflammation with eosinophils, in particular, and as will be discussed, this represents an area of commonality with functional dyspepsia and rumination syndrome. In patients with functional dyspepsia, duodenal eosinophilia is associated with up to a sixfold increase in GERD (Ronkainen et al. 2019).

Functional Dyspepsia Like GERD, rumination syndrome significantly overlaps with functional dyspepsia in terms of both symptoms and pathophysiology. Dyspeptic symptoms are frequently reported by patients with rumination syndrome; often, patients report these symptoms before a rumination episode with symptom relief once the regurgitant reaches the mouth (Tucker et al. 2013). Functional dyspepsia has been associated with a variety of mechanical disturbances including delayed gastric emptying, decreased gastric accommodation, and visceral hypersensitivity (Rosen et al. 2014; Tack and Pandolfino 2018; Simrén et al.

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2018). Approximately half of adults with FD exhibit delayed gastric emptying, and patients tend to exhibit increased retention in both the proximal and distal stomach (Park et al. 2017; Gonlachanvit et al. 2006). Delayed gastric emptying can be associated with nausea, pain, early satiety, and fullness (Vijayvargiya et al. 2019). Abnormal accommodation has been reported in over 40% of adults with functional dyspepsia and can be associated with early satiety (Park et al. 2017; Tack and Pandolfino 2018). Over 20% of adults with functional dyspepsia have both abnormal accommodation and delayed gastric emptying (Park et al. 2017). Functional dyspepsia has been associated with inflammation including chronic inflammation involving Th17 cells (Singh et al. 2020). A large and continually growing body of literature has demonstrated increased density and activation of eosinophils and mast cells in the antrum and duodenum of both adults and youth with functional dyspepsia (Wauters et al. 2017; Friesen et al. 2013, 2021a; Singh et al. 2018; Du et al. 2018). Pesek and colleagues found mucosal eosinophilia in over 80% of patients undergoing endoscopy for moderate to severe gastrointestinal symptoms (Pesek et al. 2020). This increase occurs even in patients with mucosa that appears normal on gross endoscopic examination (Dellon et al. 2021). In particular, early satiety has been associated with mucosal eosinophilia. Nausea is also associated with increased mast cell density in children with dyspepsia, independent of abdominal pain (Friesen et al. 2020). Inflammation appears to be an important link between functional dyspepsia and known triggers including stress and infections. Anxiety and stress have been highly implicated in the development and maintenance of disorders of gut-brain interaction, including functional dyspepsia. The stress response results in inflammation, dysmotility, visceral hypersensitivity, and alteration of central nervous system processing of nociceptive signals (Friesen et al. 2013). Corticotropin-releasing hormone (CRH) is the major mediator of the stress response. CRH receptors are widely expressed on the surface of mast cells, and CRH receptors may be expressed on the surface of eosinophils under stress conditions (as demonstrated in a rodent model), or eosinophils may be recruited and activated by mediators released from mast cells (Wallon 2009; Zheng et al. 2009). Antral mast cell density is positively correlated with anxiety and depression scores in youth with functional dyspepsia (Schurman et al. 2010b). Anxiety is common in patients with mucosal eosinophilia, and duodenal eosinophilia is associated with anxiety independent of functional dyspepsia (Reed et al. 2021; Ronkainen et al. 2021). Biofeedback-assisted relaxation training has been shown to enhance the clinical response in youth with functional dyspepsia and duodenal eosinophilia with decreased pain intensity and decreased duration of pain episodes providing further evidence for a link between eosinophilia and stress (Schurman et al. 2010a). Mast cells appear to be an important pathway between stress and pain in adults as well (Wouters et al. 2016; Santos et al. 1998). Under physical stress conditions, adults have demonstrated jejunal intraluminal release of tryptase and histamine at a magnitude similar to that released by antigen exposure in food allergic patients (Santos et al. 1998). Upon activation, mast cells and eosinophils can release mediators which induce gastrointestinal symptoms (Friesen et al. 2013). Mast cell

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infiltration and activation has been shown to induce hypersensitivity with histamine as an important mediator (Zheng et al. 2009; Wouters et al. 2016; Hou et al. 2001). Mast cell-derived histamine, which is released at biologically important rates in adults under stress, may be of particular importance as it can directly stimulate sensory nerves or lead to hypersensitivity (Coruzzi et al. 2012; Wouters et al. 2016; Santos et al. 1998). Functional dyspepsia can be induced by an enteric infection with higher reported prevalence following both bacterial and parasitic infections (Zanini et al. 2012; Saps et al. 2008; Hanevik et al. 2009). Postinfectious functional dyspepsia appears to be due to an inability to end the inflammatory response after the pathogen is eliminated (Zanini et al. 2012). Postinfectious functional dyspepsia is associated with chronic inflammation as well as increased duodenal eosinophils, increased gastric mast cells, and increased gastric release of histamine and 5-hydroxytryptamine (Walker et al. 2011; Li et al. 2010; Lan et al. 2011; Futagami et al. 2010).

Rumination Syndrome The overlap between GERD, functional dyspepsia, and rumination creates challenges in distinguishing which motility and inflammatory processes are directly related to rumination and which are due to an associated condition. As previously discussed, rumination episodes are frequently triggered by gastroesophageal reflux and share pathophysiology related to TLESRs. Like GERD, rumination episodes can be decreased by baclofen which decreases TLESRs and increases LES pressure (Blondeau et al. 2012; Pauwels et al. 2018). Other pathophysiologic motility processes reported in GERD and particularly in functional dyspepsia have been evaluated in several studies with mixed or inconclusive results. This should not be surprising as findings could be significantly altered by whether patients have overlapping GERD and/or functional dyspepsia. Most often, gastric mechanical function is normal in patients with rumination, and there is a belief that medications to increase accommodation or emptying are ineffective; however, placebo-controlled trials are lacking (Murray et al. 2019; Absah et al. 2017). In one study, impaired accommodation was reported in less than 10% of adults with rumination syndrome (Bredenoord et al. 2003). In adults with rumination, balloon distension in the proximal stomach was associated with increased nausea and bloating as compared to healthy controls with no differences in accommodation at a group level (Thumshirn et al. 1998). However, decreased accommodation was demonstrated in 50% (6/12) of patients, and these patients reported increased pain with distensions (Thumshirn et al. 1998). Rumination syndrome patients do not appear to be a homogeneous group with regard to accommodation, and at an individual patient level, decreased accommodation may contribute to rumination in some patients. This is an important area for future research. Delayed gastric emptying is not uncommon in rumination syndrome and has been reported in 30–46% of children and adolescents (Chial et al. 2003; Alioto et al. 2017). It is not known whether delayed gastric emptying as measured by a

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scintigraphic emptying study represents decreased gastric motor function or is an artifact created by excessive regurgitation. Again, there are no controlled trials of gastric pro-motility agents in rumination syndrome. Similar to GERD, an altered mucosal barrier has been reported in rumination syndrome (Halland et al. 2020). Inflammation has also been more recently implicated in rumination syndrome. Abnormal upper endoscopic findings have been reported in over 30% of youth with rumination syndrome (Alioto et al. 2017). In another pediatric series, esophagitis (generally consistent with reflux esophagitis) was found in 32%, gastritis (generally chronic gastritis) in 32%, and eosinophilic duodenitis in 18% of patients (Friesen et al. 2021b). In functional dyspepsia, though there is not universal agreement in the upper limit of mucosal eosinophils, an increase in gastric or duodenal eosinophils appears to be common even in the absence of a formal pathologic diagnosis of eosinophilic gastritis or duodenitis; histologic criteria continue to evolve, and thus the 18% prevalence may represent an underestimation of the prevalence of duodenal eosinophilia in rumination syndrome (Dellon et al. 2021). Halland and colleagues studied mucosal inflammation in adults and found an increase in eosinophil density and intraepithelial lymphocytes in rumination syndrome patients as compared to controls (Halland et al. 2019). It was not known whether this was accounted for by overlapping functional dyspepsia which is highly associated with increased mucosal eosinophils (Halland et al. 2019; Du et al. 2018). A subsequent pediatric study confirmed these increases in duodenal eosinophils and intraepithelial lymphocytes while also demonstrating increases in eosinophil and mast cell densities in the gastric antrum (Friesen et al. 2021b). This study also demonstrated that increased inflammation occurred independent of the presence of abdominal pain or early satiety, hallmark symptoms of functional dyspepsia (Friesen et al. 2021b). The significant prevalence of chronic gastritis in these patients may also be relevant as chronic gastritis in children is associated with increases in mucosal eosinophils and mast cells (Singh et al. 2020). Immune activation involving mast cells and eosinophils may be a pathway for factors that can exacerbate rumination, particularly known triggers of illness and stress (Alioto and Di Lorenzo 2018). Rumination syndrome is associated with anxiety and depression (O’Brien et al. 1995; Amarnath et al. 1986; Barba et al. 2015, 2016). Inflammation may be an important path between stress and rumination as has been demonstrated in other disorders of gut-brain interaction. As previously discussed, stress may be of particular importance in patients with concomitant rumination syndrome and functional dyspepsia. The role of inflammation in stress exacerbation of rumination syndrome is another important area for future research.

Summary Like most disorders of gut-brain interaction, rumination syndrome is a complex and heterogenous entity. There is significant variability regarding mechanical functioning, both gastric motor function and functioning of the LES, particularly with its relationship to the onset of abdominal wall muscular contractions. Additional

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heterogeneity is introduced by whether there is concomitant GERD or functional dyspepsia. It also seems likely that variation is introduced by varying triggers and differences in psychosocial factors. Consequently, patients may develop rumination syndrome by widely divergent pathophysiologic processes which may impact treatment responses. The paucity of controlled trials along with the pathophysiologic variability between patients which has not been controlled for in these studies limits the options for treating rumination syndrome in an evidence-based fashion. There currently appear to be two treatment strategies: one directly targeting rumination episodes with competing responses (directed either at abdominal wall contractions or counteracting retrograde waves) and another identifying associated conditions with an attempt to identify relevant biologic, psychologic, and social factors. The two strategies are not mutually exclusive, and frequently both strategies are utilized, in part, in clinical practice. Diaphragmatic breathing has the most literature support, although somewhat meager, as a competing response. Other competing responses utilized in clinical practice (e.g., hard swallows, sucking on mints or hard candy, chewing gum), which are directed at counteracting retrograde waves, have not been studied prospectively nor compared to diaphragmatic breathing in treatment trials. Unfortunately, with diaphragmatic breathing, many or most patients have some residual rumination, albeit at a reduced rate, and relapse can be high. The other intervention which has been studied in a controlled trial is baclofen which improves LES function, preventing TLESRs as a trigger for some patients (Pauwels et al. 2018). With baclofen, although improvement has been noted in rumination syndrome, a significant proportion of patients continue to have symptoms. No studies have assessed combined treatment with diaphragmatic breathing and baclofen to determine if they have complementary effects. There have also not been controlled trials assessing either intervention in association with relaxation training although diaphragmatic breathing may induce a relaxation response in some patients if done properly. Teaching diaphragmatic breathing utilizing biofeedback may have the added benefit of being able to assure that it is also inducing relaxation. Treatment utilizing a biopsychosocial model, identifying and treating relevant biologic, psychologic, and social factors, might represent a more efficacious pathway (as appears true for other disorders of gut-brain interaction), but this remains to be proven in this patient group. We have found it useful to classify patients by whether associated GERD and/or FD is still present or whether rumination syndrome represents a residual set of symptoms following adequate treatment and resolution of GERD and/or functional dyspepsia. In some patients, treatment of GERD or functional dyspepsia may be able to resolve rumination syndrome. In others, it may be helpful or even necessary but not sufficient to eliminate it. Within the biopsychosocial model, there is an implied need to identify relevant biologic contributors which is the focus of the present chapter. Similar to other disorders of gut-brain interaction, mechanical dysfunction (visceral hypersensitivity, accommodation defects, and possibly delayed gastric emptying) may be relevant in some patients and represent therapeutic targets. Immune dysfunction, particularly increased density and activation of mucosal eosinophils and mast cells, is now highly implicated in other disorders of gut-brain interaction, particularly functional

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dyspepsia and irritable bowel syndrome, with emerging data implicating a role in rumination syndrome independent of the presence of functional dyspepsia (Du et al. 2018; Friesen et al. 2021a; Halland et al. 2019; Friesen et al. 2021b). Treatments targeting mast cells and eosinophils have shown benefit in other disorders of gut-brain interaction and are an important area for future studies in rumination syndrome (Dellon et al. 2020). Much of the current knowledge pertaining to rumination syndrome is related to pathophysiology; studies assessing treatments targeting the wide variety of maintaining pathways across biopsychosocial factors are strongly needed.

Mini-Dictionary of Terms Rumination syndrome: A syndrome characterized by repeated regurgitations with swallowing or spitting which begins shortly after eating and is not preceded by retching. Disorders of gut-brain interaction: Gastrointestinal symptom clusters resulting from any combination of aberrant motility, sensitivity, microbiome composition, intestinal barrier function, and neural processing. Biopsychosocial model: A model explaining symptoms as resulting from variable contributions from and interactions between biologic, psychologic, and social factors. Competing responses: Motor behaviors that oppose a habit in order to suppress the habit. Gastroesophageal reflux: The return of stomach contents into the esophagus generally due to an incompetent sphincter or, most often, transient relaxation of the LES. Functional dyspepsia: A disorder defined by the presence of epigastric pain, epigastric burning, early satiety, and/or postprandial bloating without a clear medical cause.

Summary Points • The physiology of rumination episodes is well described with strong abdominal wall muscle contractions initiating retrograde or R waves; both muscle contractions and R waves are targets of current therapies utilizing competing responses • Diaphragmatic breathing is the current mainstay of treatment but only has meager support from controlled studies, often leaves residual rumination, and is associated with significant rates of relapse • GERD and functional dyspepsia frequently coexist with rumination syndrome and may trigger rumination episodes; as such, they represent viable treatment targets utilizing a biopsychosocial framework • A growing body of evidence supports a role for mast cells and eosinophils in other disorders of gut-brain interaction including functional dyspepsia; emerging

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data may implicate a role for inflammation in the pathophysiology of rumination syndrome • There is a great need for controlled studies of current commonly utilized treatment strategies as well as interventions targeting biologic contributors to rumination syndrome

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Definitions of Picky Eating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Measurement of Picky Eating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . What Is Not Eaten by Picky Eaters? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prevalence of Picky Eating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Continuity from Childhood to Young Adulthood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Trajectories of PE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Parental Feeding Practices: Pressure to Eat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sensory Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Temperament, Fearfulness, and Inhibition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Less-Studied Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Practical Advice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Applications to Other Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mini Dictionary of Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Key Facts of Picky Eating in Children and Young Adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

This chapter deals with picky eating (PE) in normally developing children and adults. PE is a central component of avoidant/restrictive food intake disorder (ARFID) but not an eating disorder in itself. A large proportion of children go through a phase of PE, which usually resolves itself. A minority of children continue to be highly selective and neophobic. Extreme and consistent restricted eating in children can arrest development and cause severe health problems. There is (arguable) evidence that consistent picky eating from early childhood A. H. Zohar (*) Graduate Program in Clinical Psychology, Ruppin Academic Center, Emek Hefer, Israel Lior Zfaty Center for Suicide and Mental Pain Research, Emek Hefer, Israel e-mail: [email protected] © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_83

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into preadolescence is a risk factor for restrictive eating disorders such as ARFID and anorexia nervosa. There is a growing body of research on PE in young adults; there is some evidence that adult PE is related to a less healthy lifestyle and is associated with emotional and social dysfunction and distress. This chapter reviews the definition, extent, duration, precursors, and repercussions of PE in children and young adults. It uses vignettes of picky eaters to illustrate some of the points raised in the review. In conclusion, it summarizes some of the lessstudied issues that require further research and offers practical advice. Keywords

Picky eating · Neophobia · Food fussiness · Intergenerational transmission · Children · Young adults · Parental feeding practices · Pressure to eat · Appetitive tendencies Abbreviations

AN ARFID BMI FF Pe PE Pes

Anorexia nervosa Avoidant restrictive food intake disorder Body mass index Food fussiness Picky eater Picky eating Picky eaters

Introduction Picky eating may constitute a health hazard, and at the very least can permeate the parent–child relationship with frustration, distrust, guilt, and anger, which may generalize to other aspects of the parent–child relationship and alter family dynamics. It is a nondiagnostic but salient problem in autism spectrum disorder (ASD); and in the absence of language in children and adults with ASD can be particularly tragic and difficult to deal with. There is a wealth of research on picky eating in the context of ASD. However, this chapter focuses on typically developing children and young adults, which is in itself a field of study that is gaining momentum and is worthy of review.

Definitions of Picky Eating The criterion of avoidant restrictive food intake disorder (ARFID) in the DSM5 (APA 2013) includes apparent lack of interest in food, avoidance of foods based on their sensory characteristics, and concern about aversive consequences of eating, which leads to a significant weight loss or to nutritional deficiencies. Some of these have been suggested as elements of picky eating (PE). Dovey et al. (2008) include in

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their definition of PE an inadequate variety of foods, rejecting many familiar and unfamiliar foods, and an aversion to specific food textures. A different definition was suggested by Brown and Perrin (2020) to include the refusal to taste new foods (neophobia), eating very little, and having one’s food prepared separately or differently from other people present at the meal. Other definitions of PE include emotional responses having to do with food – such as showing no interest in food or meals, or displaying negative emotions before or during eating. These behaviors are better described as emotional undereating, although they are usually associated with PE (Tharner et al. 2014; Zickgraf and Ellis 2018; Zohar et al. 2020; Wolstenholme et al. 2020). In a systematic review of child PE and neophobia, Brown et al. (2016) conclude that the inconsistency of the definition of PE leads to great difficulty in drawing conclusions about prevalence of PE and its relationship to BMI and obesity in children.

Measurement of Picky Eating The measurement of picky eating has evolved as interest in the phenomenon has grown. Some studies of young children (e.g., Cardona Cano et al. 2015; Zohar et al. 2019) rely on parental report via the Pre-School Child Behavior Checklist (Achenbach 1992), which includes an item on eating problems answered on a 3-point severity scale, and an open item for describing the eating difficulties. A more detailed parental report is the Child Eating Behavior Questionnaire (Wardle et al. 2001), which includes the six-item Food Fussiness (FF) subscale, with a focus on refusal to taste new foods, and can be used for children up to the age of 18. The FF score is sometimes used to define a cutoff point above which the child is defined as a picky eater (Sandvik et al. 2019; Zohar et al. 2020). Another measure is the objective tool for assessing picky eating (OTAPE; Finder 2020) for parental report on children 3–6 years of age. Parents report on the availability of various food items from a frequent foods list at meals in their home, and then on which of these were actually eaten by their child. Since it yields a quantitative ratio, it is deemed objective. However, since all these measures depend on parental report, there is potential for bias. Observational tools are used in some studies and have the highest face validity. However, the observed behavior is study-specific, and the expense and labor involved limit the sample size studied (e.g., Abebe et al. 2017; Adamson and Morawska 2017; Jordan et al. 2020). As children grow older, self-report becomes possible. Zohar et al. (2020) developed a scale based on a frequent foods list presented by name and picture. Children 7–9 years of age self-reported online to produce two variables: “never,” the number of food items the child scores as not to be eaten; and “last week,” the number of items the child endorses as having eaten over the last week. The two variables are negatively correlated and are strongly related to maternal reports of PE at earlier developmental stages as well as concurrently. Ellis et al. (2017) developed a 16-item self-report adult picky eating questionnaire (APEQ), with excellent psychometric

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properties measuring sensitivity to meal presentation, the limitation of food items eaten, lack of appetite or interest in food, and aversion to sour and bitter tastes, which is in wide use in the growing research on adult PE. Zickgraf and Ellis (2018) composed a nine-item avoidant/restrictive screen (NIAS), with three items on PE, three on low appetite (Appetite, A), and three on anxiety pertaining to the gastrointestinal consequences of eating (Fear, F). The items on PE are “I am a picky eater”; “I dislike most of the foods that other people eat”; and “The list of foods that I like and will eat is shorter than the list of foods I won’t eat.” Each of the items is rated on a 6-point scale from strongly disagree (0) to strongly agree (5). The score on the PE subscale of the NIAS is the sum of responses, ranging potentially from 0 to 15. The NIAS has excellent psychometric properties, but as yet a cutoff point for PE has not been identified. The PE score correlates positively with food neophobia and with the food fussiness subscale of the adult eating behavior questionnaire, and negatively with the food enjoyment subscale. It does not correlate with measures of anxiety, depression, and stress (Zickgraf and Ellis 2018).

What Is Not Eaten by Picky Eaters? Although the definitions of PE offered at the beginning of this chapter did not include what picky eaters (Pes) are not eating, this is of course of medical and health concern. By definition, the more selective a picky eater (Pe) is, the more foods she will not eat. However, a recurring theme in PE is avoiding vegetables and fruit. Most children who are Pes will not eat vegetables of any kind (Zohar et al. 2019) or will only eat a restricted range or amount of raw vegetables (van der Horst et al. 2016) and fruit. Because vegetables and fruit are crucial for vitamins and dietary fiber, this may have developmental repercussions and may also contribute to constipation (Taylor et al. 2016), which in turn will affect appetite and food enjoyment, thus constituting a positive feedback loop for PE. Ellis et al. (2018a) found that college students who self-reported as Pes were more likely to eat less vegetables and fruits. Thus, the association between PE and low vegetable and fruit consumption is found throughout the developmental span studied. Many PE interventions are targeted at extending the consumption of vegetables and fruit (e.g., Bennett et al. 2020; Jordan et al. 2020). The avoidance of all or most vegetables and fruit is mentioned in all five vignettes included at the end of this chapter.

Prevalence of Picky Eating Prevalence estimates of transient picky eating, present in one phase of childhood and not in another, vary from study to study, possibly because of cultural influences. A meta-analysis concluded that about 22% of children go through a picky eating phase (Cole et al. 2017a). There is some consistency, however, in the estimate of persistent picky eating over childhood, which derives from longitudinal studies. Zohar et al.

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(2020) found that 3.9% of typically developing children in Israel were persistently Pes between 3 and 8 years of age. Taylor et al. (2015) found in a longitudinal study in the west of England that 3.5% of children 2–7 years of age were persistently Pes. In the Netherlands, a longitudinal study that followed children from their first year of life until they were 6 found that 4% of the children were persistent Pes (Cardona Cano et al. 2015). The prevalence of PE in young adults has been less studied. However, He et al. (2020) found that 19.4% of the Chinese college students studied could be defined as picky eaters and 3.3% as severe Pes. Ellis et al. (2018b) studied young adults in the United States and found that 18.1% could be described as picky eaters; this group also reported more social anxiety related to eating and more depressive symptoms. Thus, currently, there is a discrepancy in the prevalence estimates of PE in children and adults. While less than 5% of children are persistently picky eaters from infanthood to school age, about a fifth of young adults selfreport as picky eaters. It is likely that different criteria are being used at different developmental stages; however, only extended longitudinal studies, with welldefined criteria for picky eating at the different developmental stages, can resolve this discrepancy.

Continuity from Childhood to Young Adulthood Do individuals who are persistently picky as children become adult picky eaters? Or, are they at increased risk to develop restrictive eating disorders such as ARFID or restrictive AN? Van Tine et al. (2017) followed a small sample of children from infancy until the age of 23 and found continuity between persistent picky eating at 11 and remaining a selective eater at 23, with no evidence for increased eating pathology or obesity in the persistent picky eaters. Retrospective studies of adolescents diagnosed with ARFID (Menzel 2019) or AN (Dellava et al. 2012) suggest that childhood PE increases the risk for developing these disorders; however, there are no prospective studies showing this association. Moreover, a retrospective qualitative study of adolescents with restrictive AN (Scolnick et al. 2015) found that as children they were particularly good eaters, eating healthy, varied, vegetable-rich diets. The onset of their eating disorder could best be attributed to school-based obesity intervention programs. In young adults, PE is associated with more disordered eating, obsessive-compulsive symptomatology, and social anxiety surrounding eating (Wildes et al. 2012). Barnhart et al. (2021) found that PE as self-reported by undergraduates was correlated with overall eating pathology, with binge eating, as well as with social anxiety about eating, and symptoms of stress, anxiety, depression, and OCD. However, Zickgraf and Ellis (2018), in their validation of the NIAS, did not find that PE correlated with any measures of psychopathology in healthy young adults. For the adult picky eaters represented in the vignettes in this chapter, there does not appear to be associated psychopathology, but there is discomfort around social eating.

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Trajectories of PE Different lines of research find partial support for a variety of antecedents and risk factors that can best be grouped as distinct trajectories to PE. In reality, they may not be mutually exclusive, but are described separately for clarity.

Parental Feeding Practices: Pressure to Eat The dance of feeding and eating begins in the first few hours of the baby’s life as both mother and child are recovering from the trauma of birth (Brody and Siegel 1992). Some studies support the protective role of exclusive breastfeeding until 6 months of age against PE in later childhood (Shim et al. 2011; de Barse et al. 2017; Emmett et al. 2018); however, systematic review does not bear out this association (Bąbik et al. 2021). Self-weaning, letting the infant pick up and eat solid and lumpy foods when over 6 months of age rather than spoon-feeding her smooth pureed food, in the process of weaning the infant from an exclusive diet of milk or milk substitutes, is also found to be protective against later picky eating (Bąbik et al. 2021). However, waiting to begin doing so until the child is over 9 months of age is a risk factor for PE (Emmett et al. 2018), particularly so if the mother is worried or very worried about the child’s eating. A possible integration of these early feeding findings is that babies and toddlers do best when they can regulate their food intake to suit their actual needs and appetite: Therefore, breastfeeding has an advantage over bottle feeding; self-weaning over spoon-feeding, but these are proxies and thus found in some studies and not in others, because the underlying protective factor is the absence of parental worry or fussing, trusting the baby/toddler to eat what and how much she needs. In an extraordinary longitudinal study of maternal feeding that followed mother–child dyads from the first year of life until the children were 18, Brody and Siegel (1992) found that mothers who were relaxed and enjoyed breastfeeding had long-term better outcomes for their children and for their children’s eating behavior when they were young adults. Steinsbekk et al. (2017) found that parents offering their Pe child new foods in a calm, assertive way helped against continued PE; while responding emotionally to the child’s food rejection “parental sensitivity” and accommodating to the child’s food avoidance increased the risk of continued PE. This conclusion, that a relaxed confident parent who feeds her child without too much worry, fuss, or pressure has the greatest odds of not having a child who is a PE, has further corroboration in that first-born children are more likely to be described by their mother as PE than non-first-born children (van der Horst et al. 2016; Zohar et al. 2019), so that inexperienced and more anxious parenting may be the underlying factor. Parents who identify their children as Pes self-report that they pressure their child to eat (e.g., Kutbi 2020). Common sense dictates that if the child eats less than the parent or the culture deems appropriate, or rejects many of the foods that are readily available in the home environment, a parent will try to discharge her responsibility toward the child by trying to increase the child’s food intake or the range of foods the

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child will eat. However, a low-appetitive child who is pressured to eat might respond to pressure by further reduced appetite and develop the attitude that eating is a chore that must be undertaken to satisfy the parent. Zohar et al. (2021) found that mothers of 6-year-old children, who were authoritarian, and practiced overt control of their child’s diet, pressured their child to eat more, while the children ate less (high food satiety), had a more restricted diet (food fussiness), were slower eaters, and did not enjoy their food as much. Authoritative parenting, both loving and structured, is protective against PE (Steinsbekk et al. 2017; Jordan et al. 2020; Zohar et al. 2021). There is also evidence that parental pressure to eat in childhood is a stronger predictor of adult PE than childhood PE (Ellis et al. 2016); this ironic reversal was noted in a retrospective study of adult eating behavior, BMI, and body image (Lev-Ari and Zohar 2013). Parental pressure to eat on children is a major predictor of adult PE (Cole et al. 2018). So, although pressure to eat is a common and understandable parental response to a child who is eating or is perceived to be eating very little, it does not seem helpful in the long run. In the short term, if meals become conflictual, with parents seeking to forcefully control their children’s eating behavior, the parent–child relationship is negatively affected and the risk for continued PE and the development of eating disorders is elevated, while maintaining a positive atmosphere at family meals is moderately protective (Cole et al. 2018; Emmett et al. 2018). It is unfortunate that particular parental feeding practices, including pressure to eat, undergo intergenerational transmission (Lev-Ari et al. 2021); so, young adults who were adversely affected by being pressured to eat when children find themselves in turn pressuring their own children to eat.

Sensory Sensitivity Sensory sensitivity can be described as having an aversive or lacking response to stimuli that are tactile, visual, auditory, kinetic, the body’s spatial orientation (proprioception), as well as to taste, smell, and food texture (Schoen et al. 2008). In the context of PE, sensory sensitivity is measured in all these domains excluding those that pertain directly to food (taste, smell, and food texture). Children who react aversely to sensory stimuli are more likely to be Pes at age 4, and sensory sensitivity at age 4 predicts continued PE at age 6, even when controlling for PE at age 4 (Steinsbekk et al. 2017). Sensory sensitivity seems to be congenital or genetic to some degree (van Hulle et al. 2012; Kalig-Amir et al. 2019), as does neophobia (Cooke et al. 2007; Smith et al. 2017). Pes are more prone to disgust, probably mediated by sensory sensitivity (Harris et al. 2019). It has been suggested that individual differences in sensitivity to bitter taste may mediate PE (Jani et al. 2020; Patel et al. 2020). These differences are partly genetically determined as the ability to taste 6-n-propylthiouracil (PROP) is a Mendelian trait (Wooding et al. 2004). Cole et al. (2017b) found that variations in chemosensory genes were associated with elevated PE in preschool children. Bell and Tepper (2006) found that preschool children who were phenotypically

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non-PROP tasters consumed more vegetables such as raw broccoli and black olives than PROP tasters. Moreover, Bell and Tepper (2008) found that parents of tasters and nontasters were no different in their feeding practices, suggesting that sensitivity to bitter taste contributes to PE in young children irrespective of parental influence. This line of research seems promising, but is relatively undeveloped. This relationship between sensory sensitivity and PE has been found in preschool children (Steinsbekk et al. 2017), school-age children, adolescents, and young adults (Zickgraf and Ellis 2018). In school-age children with a diagnosed anxiety disorder, Zickgraf and Ellis (2018) found that aversive sensory sensitivity mediated completely between anxiety levels and PE; they found a similar pathway in healthy college students in their early twenties – the young adults’ aversive sensory sensitivity mediated between their anxiety level and their PE. Kauer et al. (2015) found that adult Pes had more obsessive-compulsive symptoms and disgust propensity. To summarize, across development from young childhood to young adulthood, having strong aversion to sensory stimuli in realms unrelated to food is a considerable contributor to PE. Sensory sensitivity is quite marked in vignettes I and III; in the other accounts, the sensory sensitivity is limited to taste and smell.

Temperament, Fearfulness, and Inhibition An initial influence on the child’s appetitive behavior can be due to temperament. Negative emotionality in toddlers is predictive of PE in later childhood (Hafstad et al. 2013) and cross-sectionally differentiates between toddlers who are PE and those who are not (Zohar et al. 2019). Obesity-prone children who exhibit high levels of PE have many more behavioral and emotional difficulties (Lepinioti et al. 2021). Behavioral problems are elevated in young children who are described as PE. These include externalizing behavioral problems (Jacobi et al. 2008), as well as internalizing behavioral problems, and in particular affective problems (Zohar et al. 2019). This is also true in school-age children (Machado et al. 2016) and adolescents up to the age of 18 (Machado et al. 2021). Typically developing children develop fears of imaginary characters, of harm to themselves or others, fear of strangers and strange situations, and may also suffer from night terrors (Zohar and Felz 2001). Children who were identified as PE at age 3 were elevated for all these normative childhood fears compared to typically developing children who were not PE (Zohar et al. 2019). Deficiency in executive function, particularly in emotional regulation and shifting, differentiates children with PE at 3 from children without PE (Zohar et al. 2019) and predicts the persistence of PE to 8 years of age (Zohar et al. 2020). Although executive function is crucial for behavior regulation (Isquith et al. 2004), it has not been much studied in relationship to PE in children, and not at all in adults.

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Children who are Pes and young adults who self-report as Pes may have a greater tendency to be shy, inhibited, anxious, and/or depressed, and these tendencies may characterize the individual and contribute to low appetite and PE.

Less-Studied Issues Although the literature on PE is large and growing, there are several outstanding issues that bear additional scrutiny. Although there is a plethora of research on risk factors, there is less on protective factors. It is still difficult when examining a 3-yearold Pe child to predict if the individual child will outgrow this PE phase or whether the child is set on a trajectory of persistent and potentially dangerous PE. In vignette I, the mother assumed that her baby son’s extreme pickiness was a phase; sadly, she was mistaken. There is a need to better understand the continuity between childhood PE and adult PE. The sensory and genetic underpinnings of PE and neophobia bear further study. And the contribution of difficulties with executive function, in children and young adults to PE, is a promising line of research that has not been pursued.

Practical Advice For children who are low in appetite and restrictive in their food choices, and are low on their developmental trajectory, parents should first seek a medical evaluation to rule out health complications. When and if ruled out, parental common sense should prevail. Parents should avoid keeping foods in the house that they prefer their children not to eat. Parents should avoid power struggles over food and let the children lead in what and how much they eat out of the available foods that the parents deem healthy. If parents find themselves regularly pressuring, cajoling, or preparing special and different meals for their child, or for each of their children, then they are accommodating their children’s pickiness and reinforcing it (Shimshoni et al. 2020). Treatment of extreme PE in children and adults can be sought in serious cases, and treatment follows the general principles of exposure (to more foods) and anxiety reduction. Young adults who seek treatment for their PE can be treated by dieticians who specialize in PE along the same principles. In the absence of distress or adverse health implications of PE, Pes should be left to enjoy their choices and their PE should not turn into a personal or social issue. (1) A mother’s account. The only picky eater among my children was and is my youngest and fourth child. When he started sitting in a high chair and eating solids, I would put different vegetables on his tray for him to pick up and eat. He would try to pick them up and was obviously repelled by their texture. When I tried to spoon feed him he would look disgusted, and push the food out with his tongue. He absolutely rejected all vegetables and fruit, and to this day (at 26 years of age) will not eat any fruit. He was very sensitive to textures – of food and other things. He would not wear anything

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with a label. I didn’t concern myself too much about his diet – he was a fourth child, I was an experienced mother, and I expected it was just a phase. Our family is not particularly focussed on eating a healthy diet, and I didn’t enter into conflicts with him or go to extraordinary lengths to look for vegetables and fruit that he would eat. There was a process of adaptation in which we discovered the limited list of foods that he was willing to eat, and made sure that some of them were available at meals. Sometimes I feel guilty I didn’t try harder, and think he would have grown taller if he had eaten a more varied and nutritious diet. Even as an adult man, he eats very few vegetables and no fruit, but any kind of meat. I don’t think he is much inconvenienced by his limited diet, except when people start fussing about it, or when he is out of the house and has difficulty finding foods that he can eat. (II) A mother’s account. My eldest (now 27) was a very good eater as a baby and a young child. She nursed well, and loved the pureed food which at that time was the first non-milk food offered to very young children. To this day one of her favourite foods is apple puree. When she was in nursery school and kindergarten she ate with the other children and the staff never complained about her eating. I first noticed how restricted her diet was when she was a schoolchild (over 6). She would not eat any raw vegetables, very few fruits, and preferred potatoes, (white) rice, pasta and (white) bread. She would eat some proteins, chicken or beef if they were processed and had a smooth texture, and eggs in any form. Some hummus and tahini. She would eat vegetable soup if it was pureed, and particularly liked pumpkin. The restriction of her diet was a problem for her mainly when adults tried to pressure her to eat “healthy” food she could not eat. Then as now, she loved fried food. I worried about her nutrition and health. When she was about 10 or 11 years old, I consulted our paediatrician as well as a dietician. They did not have much constructive advice. As she matured, she was able to extend her diet. She has adopted tomatoes, raw, cooked, chopped and pureed. She loves basil pesto. She eats onions. She can mostly get by with food she cooks herself and eating with friends is part of her very active social life. She is very overweight, but I think this is mostly the result of not having enough physical activity, and does not result from her picky eating. (III) A picky eater’s account (30 years old at interview) I was a picky eater from day one – my mother likes to say from the moment I was hatched. There was a wide range of things I couldn’t eat – most fruit and all vegetables repelled me. When I first went to kindergarten my mother told the teacher that I could not eat tomatoes. The teacher was not deterred but several hours later had to call my mom to come and pick me up because I was vomiting so violently. Our house had a traditional cuisine, with a lot of meat, rice, and fried food, which I loved. There wasn’t great emphasis on healthy eating, or on fruits and vegetables. I was a plump child, with a preference for processed food, dry hard food, and an aversion from anything that was or felt wet. Cucumbers I cannot stand to this daythey are wet and they smell. The smell of melon, watermelon, banana, can make me gag. The texture of soft fruits like plum or peach is unbearable for me. I can eat hard cheese, but it leaves my mouth feeling like sandpaper. I remember the adults around me being frustrated and angry about my pickiness, and also worrying that I was

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gaining weight because I was eating a lot of junk food, and rejecting fruit and vegetables. I think it affected my body image even as a child; I also felt I was harming myself by not eating most of the foods. In the family I was ridiculed and tagged as a problem eater. When I left the house as a young adult I started working to extend my diet. I can now eat tomatoes; I can eat strawberries, and certain sautéed vegetables like broccoli. My boyfriend and his family are into healthy eating and that exposed me to more foods, some of which I now eat. My sensitivity is not restricted to food – loud sounds and especially loud talking actually hurt my ears; Although I enjoy being touched I am also extremely sensitive to touch, and this may mean that I will not be able to nurse my baby when she is born. I worry now that I am pregnant that the baby may not be getting the nutrition she needs and will suffer because of my pickiness. (IV) An adult man’s picky eater’s account (55 years of age) I am second out of four children, and although my sister is also picky, I have always been, and still am the most extreme picky eater in the family. As a child I was very sensitive and prone to moods. I would only eat a very limited number of foods; no vegetables, for fruit – only apples and carrots (laughs). I would eat processed meat, rice, and potatoes. Bread with chocolate spread. Very little else. There is a big category of foods that I call sour; I cannot abide sour food. Melon and watermelon are sour, as are many other things. When I was twelve we moved to a Kibbutz with a communal dining room. So not only was I a skinny runt (he is still extremely thin, AHZ), but there was no accommodation for my restricted diet and I had great difficulty finding things I could eat. My pickiness made me even less acceptable to my new peers and I was bullied by them. When I was in college living in the dorms I extended my diet a little – I learned to eat eggs cooked in certain ways as well as toasted cheese sandwiches. When I taste food that is unacceptable to me, I gag and spit it out. Today, my picky eating is less of a problem because I can usually determine what I will eat. I have problems when attending a social event, when I have to find things that I can eat. Being a guest in someone’s home requires a lot of preparation and explanation, and sometimes is embarrassing for me and disappointing or hurtful to my hosts. However, when I go out to a restaurant with friends I can nearly always find something on the menu to eat. (V) A young woman’s account (26 years of age) I have always been a picky eater. The list of things I can eat is very limited. My younger brother – is the opposite, he is omnivorous and a very large man. I have always been very small and skinny for my age. To be drafted into the army I made a special effort and gained weight to meet the minimal weight – 37 kilograms (81.6 pounds). I am known as a problem eater in the family. I cannot eat beef, only chicken breast; I can eat rice and potatoes. I avoid most vegetables and fruit. I love sweet processed foods like breakfast cereals, and certain candy bars. I am not very motivated to eat – I can forget to eat or not be bothered to for a whole day. During corona, when studies were on zoom, I forgot to get out of my chair and eat for entire days. But I am a nibbler and always have snacks in my backpack (shows a bag of cereal she has taken along). My best cooked food is pasta, and I can eat it with tomato sauce or with a cream sauce as long as no vegetables are included. That is

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what I ate during my army service. When the family goes out for a meal, I try to study the menu in advance to identify things that I can eat. Sometimes there is a children’s meal that is appropriate. My family complains a lot about my limited eating and the difficulties it poses for family events. I do not like to have my eating focused on, and find it unpleasant at family meals and social events when my restricted eating is noticed. I don’t know if it effects my health, I am phobic about needles I am not monitored regularly.

Applications to Other Eating Disorders Picky eating is not an eating disorder, yet it is linked to the restrictive eating disorders. ARFID includes aspects of picky eating in its first diagnostic criterion. AN is characterized by eating very limited amounts of food within a highly restricted range. So, picky eating can be conceived as a component of these disorders. There is some literature linking picky eating in childhood to eventual obesity, but the evidence is weak and arguable. The impulsive urges salient in bulimia and binge eating disorder seem to be in direct contradiction to the inhibited behavior seen in picky eating, and there is no research linking picky eating to the bingeing disorders. Picky eating in children is often the focus of parental feeding practices that do not promote healthy eating habits and can increase risk for the development of restrictive eating disorders.

Mini Dictionary of Terms Appetitive tendency • A tendency present early in development to approach and consume food; children with a low appetitive tendency are likely to eat small amounts, enjoy food less, and eat slowly, while children with a high appetitive tendency will do the reverse. Picky eating • Eating behavior characterized by low intake of food, rejection of new foods, food rejection because of texture or smell, and is usually exhibited by individuals with low appetitive tendencies. Pressure to eat • Parental feeding behavior intended to influence the child to eat greater amounts or to eat particular foods that the child rejects. The pressure might manifest in exerting parental authority, evoking guilt and shame in the child, or using food as reward or punishment,

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Key Facts of Picky Eating in Children and Young Adults • Picky eating is one of the most common presenting problems brought to the clinical attention of pediatricians in wealthy countries. • It is difficult to untangle parental feeding behavior from child eating behavior in regard to child picky eating. • It can cause social and emotional impairment in both children and young adults.

Summary • About 20% of children go through a phase of picky eating, although there is great cultural variation. • Most children will outgrow this behavior over development. • Although cross-sectional studies show that children with picky eating are more prone to emotional and behavioral problems than their nonpicky peers, these problems tend to remit as picky eating wanes. • Only about 4% of children persist in picky eating throughout childhood. • Self-described picky eating is common in young adults and is associated with emotional and social dysfunction. • There is retrospective evidence that persistent picky eating throughout childhood increases risk for restrictive eating disorders. • Individuals who are consistently picky eaters from childhood into adulthood tend to be either under- or overweight as adults. • Adults picky eating is a relatively new but fast-growing field of study.

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Part VI Diagnosis, Delective Questionnaires, and Resources

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Which Questionnaires Are Used in Orthorexia Nervosa Studies? . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bratman Orthorexia Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ORTO-15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Body Image Screening Questionnaire (BISQ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Düsseldorf Orthorexia Scale (DOS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Orthorexia Nervosa Scale (ONS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Burda Orthorexia Risk Assessment (B-ORA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Teruel Orthorexia Scale (TOS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Barcelona Orthorexia Scale (BOS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Orthorexia Nervosa Inventory (ONI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Test of Orthorexia Nervosa (TON-17) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Application to Other Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mini-Dictionary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Key Facts of Assessing Orthorexia Nervosa by Questionnaires . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

With a growing research interest directed at orthorexia nervosa (ON), specifically at measuring it accurately, today there are many measurement tools available in the scientific literature. Due to the lack of a consensus on the diagnostic criteria of ON for many years, the early scales, which are the most commonly used ones, lack questioning some key features of the disease, in addition to lacking adequate M. P. Yargic (*) Faculty of Medicine, Ankara Medipol University, Ankara, Turkey e-mail: [email protected] M. C. Celen Department of Biophysics, Ankara Medipol University, Ankara, Turkey e-mail: [email protected] © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_84

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validity. Researchers who noticed this shortcoming started working on developing new measurement tools. In this chapter, we will review these 10 ON measurement tools and their properties: Bratman Orthorexia Test (BOT), ORTO-15, Body Image Screening Questionnaire (BISQ), Düsseldorf Orthorexia Scale (DOS), Orthorexia Nervosa Scale (ONS), Burda Orthorexia Risk Assessment (B-ORA), Teruel Orthorexia Scale (TOS), The Barcelona Orthorexia Scale (BOS), Orthorexia Nervosa Inventory (ONI), and Test of Orthorexia Nervosa (TON-17). Our aim is to provide researchers and clinicians with the information they require regarding the content, validity, reliability, and other distinct properties of the questionnaires. Keywords

Orthorexia nervosa · ORTO-15 · Bratman Orthorexia Test · Düsseldorf Orthorexia Scale · Teruel Orthorexia Scale Abbreviations

ABOST BISQ B-ORA BOT DOS DSM-5 ON ONI ONS TON-17 TOS

Authorized Bratman Orthorexia Self-Test Body Image Screening Questionnaire Burda Orthorexia Risk Assessment Bratman Orthorexia Test Düsseldorf Orthorexia Scale The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition Orthorexia nervosa Orthorexia Nervosa Inventory Orthorexia Nervosa Scale Test of Orthorexia Nervosa Teruel Orthorexia Scale

Introduction Orthorexia nervosa (ON), which is often referred to as a lifestyle syndrome, is a disordered eating behavior. The word “orthorexia” was put together by Bratman in his article “Health Food Junkie” which was published in Yoga Journal in 1997 (Bratman 1997). The term implies an unhealthy preoccupation with healthy eating. There is an ever-growing interest in orthorexia nervosa, although it lacks the proper recognition in the current diagnostic classifications. Questionnaires are a set of previously determined questions to determine the attitude, behavior, or situation on a particular topic. This topic can be related to all areas of life, as well as human health. For many years, questionnaire research has been used for many of the studies in the field of medicine and has been especially preferred by epistemologists in examining the attitude and behavior dimension of disease and health (Mandal et al. 2000). In general, questionnaires are not a preferred

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Fig. 1 Orthorexia nervosa is an unhealthy preoccupation with healthy eating. (Image: Freepik)

method in the diagnosis phase of patients. It is mostly used in the self-reported, systematic determination of the factors that cause the formation of the disease (Fig. 1). The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM5), published by the American Psychiatric Association is the most up-to-date manual accepted as a reference when defining certain psychiatric conditions as a psychiatric disease (American Psychiatric Association 2013). Although orthorexia nervosa is a condition that is increasingly recognized and of interest as a research topic, it is still not defined as a disease in the DSM-5. Therefore, it is not possible to use the DSM-5 diagnostic criteria for orthorexia nervosa, as we do for other eating disorders. Even so, Dunn and Bratman have suggested diagnostic criteria for the condition: an obsessive focus on “healthy” eating (Criterion A) and clinically impairing compulsive behavior and mental preoccupation (Criterion B) (Dunn and Bratman 2016). In this context, questionnaires assessing orthorexia nervosa are very much needed, not necessarily for making a diagnosis, but to clarify which populations are under higher risk for ON, which clinical conditions are often associated with it, and its many unknown properties (Fig. 2).

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Fig. 2 Association of orthorexia nervosa with other eating-related disorders

In this section, the questionnaires used in studies on orthorexia nervosa, their compatibility with each other, and how inferences are made from the information obtained from these questionnaires will be discussed.

Which Questionnaires Are Used in Orthorexia Nervosa Studies? The number of orthorexia nervosa questionnaires used in current studies is relatively high. The first of these questionnaires was conducted in 2000 by Bratman, who described this eating disorder condition as orthorexia nervosa (Bratman 2000). At least 10 different questionnaires appear to be used to measure ON nowadays. Although some of these questionnaires are about eating disorders in general, studies show that they can be used in the detection of ON. Important details such as the scope of the questions and the explanations suitable for the person to answer affect the reliability and validity of the scales. Translations of the questionnaires in various languages require new reliability and validity studies, in some cases resulting in extracting certain questions from the scale. Each scale used for the measurement of ON has its strengths and weaknesses. It should not be aimed to decide on one single scale which is “the best” measurement scale for ON in general but to find the best scale for each varying study purpose and condition (Table 1).

Bratman Orthorexia Test Bratman Orthorexia Test, also referred to as Orthorexia Self-Test, was developed by Bratman and Knight, and it consists of 10 questions in dichotomous response format (Bratman 2000). Each positive answer is recorded as one point, and a higher sum score shows a higher tendency towards ON. Although the cutoff value does not have

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Table 1 The scales that will be reviewed in this chapter Name of scale Bratman Orthorexia Test ORTO-15 Body Image Screening Questionnaire Düsseldorf Orthorexia Scale Orthorexia Nervosa Scale Burda Orthorexia Risk Assessment Teruel Orthorexia Scale The Barcelona Orthorexia Scale Orthorexia Nervosa Inventory Test of Orthorexia Nervosa

Abbreviation BOT ORTO-15 BISQ DOS ONS B-ORA TOS BOS ONI TON-17

Reference (Bratman 2000) (Donini et al. 2005) (Jenaro et al. 2011) (Barthels et al. 2015) (Kramer 2016) (Burda 2018) (Barrada and Roncero 2018) (Bauer et al. 2019) (Oberle et al. 2021) (Rogowska et al. 2021a)

a valid basis, patients who score four and higher are considered to suffer from ON by Bratman. Some studies have used the BOT with a 4-point Likert scale instead of a yes/no format, to have more comparable results with other measurement tools (Meule et al. 2020). A good internal reliability was shown for BOT (Cronbach α: 0.79), but its test-retest reliability has not been measured yet. German and Swedish translations are available for the scale (Rössner 2004; Kinzl et al. 2005). BOT is the oldest ON measuring tool available, which makes it difficult to catch up with the conceptual changes about ON. Recognizing this shortcoming, Steven Bratman updated the scale by associating it with the new diagnostic criteria, which were also set forth by him, and published ABOST (Authorized Bratman Orthorexia Self-Test) (Dunn and Bratman 2016; Rogowska et al. 2021b). The ABOST has six items instead of 10, and even one positive answer points out an increased risk of ON. One study investigated the reliability and validity of the ABOST with two answering formats (a dichotomous format and a continuous 5-point Likert scale). The latter showed a good validity and reliability, whereas the former did not meet the reliability and validity criteria (Rogowska et al. 2021b). There has been no validity or reliability studies published regarding the ABOST yet, other than its Polish adaptation study (Rogowska et al. 2021b).

ORTO-15 ORTO-15, a 15-item questionnaire developed by Donini, is scored on a 4-point Likert scale (Donini et al. 2005). ORTO-15 uses some items of the BOT by changing the wording and adding new items to them. Therefore, there is no harm in saying that ORTO-15 was heavily inspired by the BOT. ORTO-15 has six items focusing on the cognitive factors related to eating behavior, five items related to clinical factors, and four items related to emotional factors. However, a sum score is evaluated rather than calculating separate scores for each dimension (Table 2). Items 2, 5, 8, and 9 are scored as always 4, never 1. The rest of the items other than 1 and 13 are scored in reverse. Items 1 and 13 are scored as such: Always ¼ 2,

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Table 2 Number of questions and used Likert scale in questionnaires Name of scale Bratman Orthorexia Test (BOT) ORTO-15 Body Image Screening Questionnaire (BISQ) Düsseldorf Orthorexia Scale (DOS) Orthorexia Nervosa Scale (ONS) Burda Orthorexia Risk Assessment (B-ORA) Teruel Orthorexia Scale (TOS) The Barcelona Orthorexia Scale (BOS) Orthorexia Nervosa Inventory (ONI) Test of Orthorexia Nervosa (TON-17)

# of questions 10 15 24 10 47 21 17 64 24 17

Likert scale 4-point 4-point 5-point 4-point 5-point 4-point 4-point Self-statement 4-point 5-point

Often ¼ 4, Sometimes ¼ 3, and Never ¼ 1. Higher sum scores indicate a lower tendency towards ON behavior (Donini et al. 2005). Creators of the ORTO-15 have also attempted to set a cutoff value for ORTO-15, trying out three different values (2.25

Likelihood for presenting health orthorexia- and orthorexia nervosalike behaviors Extremely unlikely Unlikely Likely Extremely likely

Note. Silva et al. (2021)

a score for each latent factor (i.e., dimension). The TOS has been tested in different contexts, such as Spanish college students (Barthels et al. 2019; Depa et al. 2019; Barrada and Roncero 2018), German and/or Lebanese community (Strahler et al. 2020; Strahler 2020, 2021; Awad et al. 2022a, b), US college students (Chace and Kluck 2021), English-speaking adults from different countries (Domingues and Carmo 2021; Zickgraf and Barrada 2022), adolescents residing in Lebanon (Mhanna et al. 2022), French female adults (Yakin et al. 2022), and Brazilian gym users (Silva et al. 2021). Despite the advance brought by the TOS with the bidimensional approach, the methodology to determine HeOr scores is unclear. At the present, only two studies (Silva et al. 2021; Awad et al. 2022b) used the TOS to show the frequency of HeOr behaviors among participants with distinct approaches. Awad et al. (2022b) indicated the frequency of HeOr for each independent variable studied (e.g., presence of HeOr separated by gender: male ¼ 37.6%, female ¼ 45.2%) based on mean scores; however, the allocation of participants in present/absent HeOr was unclear. Silva et al. (2021) calculated the mean scores for each factor of the TOS and classified participants according to the likelihood of presenting HeOr and OrNe behaviors using percentiles (P) of Likert-type response scale. Table 3 shows this classification. Importantly, the authors emphasized that the strategy used was for the study, which requires future evaluation to verify whether the suggested classification is adequate in other contexts, as this may change when there is a “gold standard,” i.e., an official

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diagnostic criteria. Using their classification, Silva et al. (2021) found that 5.3% of participants were more likely (>P50) to present OrNe. These individuals were extremely preoccupied with healthy eating, and clinical follow-up would be very helpful to confirm and understand the symptomatology. On the other hand, 41.2% of participants were more likely (>P50) to present HeOr. They are people who are interested in healthy eating and seek to follow it but without exaggerations. In addition, the study found that 4.4% of participants exhibited both OrNe and HeOr behaviors (>P50). This overlap may indicate the validity of considering orthorexia as a continuum phenomenon (Strahler 2020), as participants with high OrNe and HeOr scores are probably people interested in healthy eating, but at certain times they may be more preoccupied than usual with the quality of food. EHQ. The EHQ was developed in a US context by Gleaves et al. (2013) based on evidence about orthorexia indicated by Bratman and Knight (2000) and on the importance attributed to healthy eating by undergraduate students in introductory psychology and nutrition classes and apparent symptoms of the phenomenon reported by graduate students in clinical psychology. A pool of 21 items composed the final version of the EHQ, which included 12 items to measure problems associated with healthy eating (e.g., “I am distracted by thoughts of eating healthily”), five items to measure knowledge of healthy eating (e.g., “I am more informed than others about healthy eating”), and four items to measure positive feelings about healthy eating (e.g., “I feel in control when I eat healthily”). A 4-point Likert-type response scale ranging from 1 ( false, not at all true) to 4 (very true) is used to the EHQ items. Individuals with higher scores on the three factors exhibit greater preoccupation with healthy eating. Subsequent studies (Mohamed Halim et al. 2020; Godefroy et al. 2021) evaluated the EHQ in different samples (Australian and French) and found factorial structures and distribution of items per factor not equivalent to the original study, which may indicate some factorial instability of the instrument. DOS. The DOS was created by Barthels et al. (2015a) in Germany. Data for the items came from an inductive procedure that included discussions on different subject areas, such as knowledge about the composition and components of food, nutritional supplements, effects of food on bodily functions, psyche and diseases, and general opinions about health. The authors also used the ideas presented by Bratman and Knight (2000) to create the DOS items. A single-factor final model with 10 items (e.g., “I have the feeling of being excluded by my friends and colleagues due to my strict nutrition rules”) was designed to measure orthorexialike eating behaviors. A 4-point Likert-type response scale ranging from 1 (this does not apply to me) to 4 (this applies to me to) is used in the DOS, and a higher score reflects greater OrNe-like behavior. Psychometric studies (Chard et al. 2019; He et al. 2019) have evaluated the DOS and found inconsistencies regarding the adequacy of the single-factor model, which raises doubts about its dimensionality. Considering the inconsistent data on the dimensionality of both EHQ and DOS, Hallit et al. (2021) conducted a study with a sample of Lebanese adults and found for both instruments two correlated factors interpreted as HeOr and OrNe. Table 2 shows the distribution of items and each factor. The multidimensionality of these

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instruments was discovered from the EFA, which was conducted in a sample of participants. However, to date, psychometric evidence of the bidimensional structure of the EHQ and of the DOS has not been showed in different samples to support the adequacy of the models; therefore, this limitation must be taken into account. Importantly, to elaborate the items of an instrument, a clear theoretical rationale is the main guide for the formation of latent factors (Marôco 2021; Kline 2016). From this perspective, developing items with specific content to capture the symptomatology of each dimension of orthorexia would be the most parsimonious way. ONI. The ONI was proposed in an American context by Oberle et al. (2021) to screen orthorexia-like behaviors from physical, psychosocial, and emotional aspects included in consensual diagnostic criteria for OrNe (Cena et al. 2019). As this instrument was also based on modified items of the EHQ and DOS, speculation emerges as to whether it would also be able to assess HeOr. The ONI encompasses a three-factor model composed of 10 items to assess physical and psychosocial impairments (e.g., “Health professionals have expressed concern that my diet is too restrictive”), nine items to capture behaviors and preoccupation (e.g., “I follow a healthy diet with many rules”), and five items to investigate emotional distress (e.g., “When I stray from my healthy diet, I can only think about what a failure I am”). A 4-point Likert-type response scale, which ranges from 1 (definitely not true) to 4 (definitely true), is used in the ONI with higher scores indicating OrNe symptomatology. The authors proposed a cut-off point using the mean value of >3 to indicate having OrNe (or at least being at high risk for OrNe). What is not clear so far is whether the ONI is an instrument capable of evaluating HeOr, and if it is, it is important to determine how to do this.

What Is the Best Way to Investigate HeOr Symptomatology? At this point, you should be asking yourself this question. In an epidemiological context, the psychometric instruments seem to be the most prominent tools to screen orthorexia-like behaviors in the population, but caution is essential when using these as all have limitations. This is not surprising, because given that there are no official diagnostic criteria for orthorexia, it is unlikely that any instrument will be considered the best to assess the phenomenon. Psychometric evaluation of the existing attitude scales should continue. Future research should focus on clarifying differences and similarities between the TOS, DOS, EHQ, and ONI for screening OrNe and HeOr. Importantly, no psychometric instrument produces results to determine the presence/ absence of orthorexia, as this would require cutoff values to be establish from diagnostic tests. For now, the TOS seems to be the most prominent psychometric tool available. Investing in reviews of available instruments to investigate the dimensions of orthorexia may be more plausible than creating new ones without knowing exactly where HeOr fits. As the understanding of HeOr advances, the possibility of adjusting existing instruments becomes more tangible, such as improving items and factors. In addition, HeOr investigations with qualitative research design – including clinical

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interviews – on healthy eating styles and other related eating habits can be substantially important to generate information to improve the instruments. These data, together with longitudinal and experimental studies (with qualitative and quantitative approaches), may help to increase knowledge about orthorexia, clarify risk factors, and determine the extent to which a pathological obsession exists. This could make preventive and therapeutic intervention strategies more successful (Douma et al. 2021).

What Is the Best Way to Management Symptomatology of Orthorexia? The answer to this question is not clear and objective. As OrNe is not an officially recognized disorder, elaborating a therapeutic plan is a challenge. A pertinent hesitation that emerges is whether both OrNe and HeOr should be treated considering that they refer to pathological and non-pathological dimensions, respectively. In practical terms with the background of the literature, treating OrNe is probably clear and necessary, as it harms different areas of the person’s life. On the other hand, treating HeOr does not seem to be appropriate. Before guiding a patient with symptoms suggestive of orthorexia, it is important to know if you are the “right professional” for this. For example, people commonly go to a nutritionist in search of more information about food and nutrition but with a focus on receiving a “perfect diet (e.g., a list of foods written on a sheet)” that promotes several benefits, especially the control of body weight. If “diet” is the unique therapeutic approach to be followed in a case of orthorexia, treatment is not in line with projections of improvement in the disturbance. Now, if the therapeutic approach includes techniques to change maladaptive eating behaviors, this needs to be clear for that patient to evaluate their level of involvement. Individuals with OrNe symptomatology must be assisted by nutritionists aligned with this phenomenon, i.e., those trained and able to recognize healthy eating practices and when these practices cross the line toward obsession (Mathieu 2005). A multidisciplinary team (e.g., nutritionist, psychologist, psychiatrist, physical education teacher, and social worker) is important for the management of orthorexia, as maladaptive traits can affect different areas of people’s lives. This also allows for the complete treatment of the phenomenon, since “people don’t stay in one spot,” as they may have more than one disorder, as well as change categories such as recovering from bulimia nervosa and manifesting orthorexia-like behaviors together with symptoms of stress and anxiety (Mathieu 2005; McGovern et al. 2021). To date, studies on the effectiveness of treatment have not been identified in the literature, but some works have suggested that cognitive-behavioral therapy, exposure therapy, and group therapy can be useful to reduce extreme fixations with healthy eating. These therapies can be applied by well-trained nutritionists and psychologists who should know what patients eat, how they buy and prepare food, and what they think is important to guide/advise change of habits (McGovern et al. 2021; Walker-Swanton et al. 2020; Mitrofanova et al. 2021). In some cases, the prescription of medication –

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by a properly qualified physician – may be necessary to reduce debilitating sensations, but this strategy is challenging, as the obsession with “purity” or “naturalness” can prevent the consumption of drugs. On the other hand, individuals who experience orthorexia symptomatology might be a bit more responsive to treatment because they are actually concerned about their health (Mathieu 2005; Douma et al. 2021). As for HeOr, what therapeutic approach should be followed? Is this plausible? If a “normal” drive for healthy eating is not a problem per se, when should the therapist act? If the risk factors for OrNe and HeOr were elucidated, the answer to these questions would be clearer. For now, it is believed that public health campaigns aimed at promoting health and individual guidance carried out by trained professionals to understand the guidelines are the best paths. These are not therapeutic approaches but preventive and counseling strategies that may avoid the drive toward healthy eating as an extreme preoccupation on the edge of OrNe. Regardless of whether or not it receives its own diagnostic category, orthorexia appears to be increasingly prominent in society. Knowing the symptomatologic framework involved in this phenomenon is important; however, helping those who suffer from a maladaptive relationship with food is also valuable. Therefore, those involved in the therapeutic process of patients who have healthy eating concerns should be constantly updated on the evolution of the concept of orthorexia. However, they must also be sensitive and empathetic to provide care that goes beyond diagnosis and biomedical therapy, being able to tap into beliefs and emotions that influence and/or determine eating behavior aiming to changing it, when relevant.

Final Considerations Although the focus of this chapter was to describe the non-pathological dimension of orthorexia (i.e., HeOr), it was necessary to introduce the reader to the characteristics of the pathological dimension (i.e., OrNe). The background presented demonstrates a growing effort of the academic community to understand the negative consequences of OrNe and the dearth of data about HeOr. A better understanding of the non-pathological dimension would be useful in managing people’s conscious eating behaviors, offering opportunities to develop prevention and intervention, when the preoccupation with health crosses the line of interest and becomes an obsession. A focused interest on food is not inherently problematic unless maladaptive behaviors occur and cause distress or lead to impairments. In this way, OrNe and HeOr seem to be separable dimensions that individuals may experience to different degrees. Individuals with symptoms of OrNe have food as the center of life and, due to the ability to control, experience a sense of pride and superiority creating identity. This commonly leads to fixation and obsession with physically, socially, and emotionally negative impacts. On the other hand, people with symptoms of HeOr see eating as a way to promote health, but not the only way, so they are interested in eating to change maladaptive eating behaviors. These changes do not cause

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significant damage to these people’s life and should not be considered potentially pathological. Importantly, it is still unclear whether orthorexia represents a disorder, the progression of a disorder, or a lifestyle. It is also unclear whether orthorexia is a multidimensional phenomenon. Therefore, understanding, conceptualizing, and showing how to assess this phenomenon is a challenge that the scientific community will have to unravel, thus making clinical practice assertive and effective. There is still much to discover about orthorexia, especially about HeOr. The conceptualization of this seems to be close to a consensus, finding no associated pathological characteristics. On the other hand, the forms to assess HeOr are still quite unclear, and few tools are available to investigate non-pathological symptoms, with the TOS being the scale that seems to be the most promising. For now, it is worth remembering that following a healthy eating is good, but if obsessive thoughts and fixation behaviors exist, the effects can be reversed, making the person’s life more complicated and less long-lasting. At this point, a final remark is important. Naming HeOr as a non-pathological healthy eating brings it too close to a pathological one. The use of the suffix “orexis” with a negative bias is so common (given to its use to name EDs) that this happens unintentionally. Note in Fig. 3 that when a group of Brazilian students was asked

Fig. 3 Word cloud associated with the terms “healthy eating” (A) and “healthy orthorexia” (B). Note. Answers given by Brazilian students to the questions: “When I say healthy eating, what word comes to your mind?” (A) and “When I say healthy orthorexia, what word comes to your mind?” (B). (This figure was created by the authors of this chapter)

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about the meaning of “healthy eating” and “healthy orthorexia,” the words “health” and “preoccupation” were present in both. Furthermore, the words used by students to characterize HeOr were mostly associated with something problematic. When Bratman (1997) first proposed the existence of orthorexia, he only made reference to what is called today as OrNe to indicate an excessive preoccupation about healthy eating. In research settings, scientists may use the terms OrNe and HeOr to operationalize the supposed bidimensionality of orthorexia in a didactic way. However, despite the theoretical enthusiasm to understand the particular dynamics about orthorexia, the impact that words may cause in the general population should be noted. The use of the term HeOr should always be used with caution, as the suffix “orexsis” may be misinterpreted as something harmful. Therefore, for the general public, HeOr might be translated as interest in healthy eating in order not to cause feelings of inadequacy.

Applications to Other EDs In this chapter, we review the phenomenon of orthorexia focusing on its presumed non-pathological dimension, called healthy orthorexia (HeOr). However, we also had to explore the pathological dimension, called orthorexia nervosa (OrNe), and through this we found suggestions for therapeutic approaches that can reduce extreme fixation on healthy eating. Although OrNe is not recognized as a mental disorder, it is already possible to identify some characteristic aspects of OrNe in the context of EDs. Hence, as more about OrNe is understood, more clinicians and health professionals may add this to their body of knowledge about eating, becoming more resourceful to plan and implement therapeutic plans. Some evidence suggests that OrNe is focused on the quality of food driven by the goal of being as healthy as possible, while EDs can be focused on the quantity of food aiming at body change; however, these two focuses can coexist. Among the therapeutic and preventive approaches mentioned in this chapter for OrNe, psychotherapeutic and psychoeducational strategies stand out, which are also very relevant for the treatment of EDs. The cognitive-behavioral approach is an example of a useful therapy to reduce maladaptive thoughts about healthy eating and, consequently, promote new adaptive eating behaviors, applying to people who exhibit OrNe behaviors, and an official ED (e.g., anorexia nervosa), as they can coexist. Regarding preventive approaches, the chapter provides evidence that may also be considered for other EDs, since it is not clear yet if the controlled and fixated food selection characteristic of OrNe can act as a first sign of other EDs. If OrNe risk factors are divulged, they also may be considered in other ED investigation studies. The chapter also sheds light on a non-pathological healthy eating behavior, HeOr. Although it is conceptually associated with OrNe, the dedication, care, and commitment to healthy eating should not be seen as pathological – even if someone has some weird beliefs regarding what is a good food – if this care and commitment do not cause physical, social, and psychological impacts on one’s life. Therefore, it is recommended that in clinical practice (e.g., during an appointment with a psychologist) people are not labeled as

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“orthorexic” just because they take care with what they eat, as this label carries a negative perception and may cause psychological distress. People diagnosed with EDs may have excessive preoccupation with healthy eating, and in these cases the therapeutic approaches suggested in this chapter for OrNe may be useful.

Mini-Dictionary of Terms • Concern: A state of interest blended with apprehension or uneasy. • Drive: An arousal state that influences beliefs and behaviors related to its aim. • Eating behavior: A set of cognitions and affections that support actions in relation to the act of eating and are strongly related to biological, psychosocial, cultural, and environmental aspects. • Fixation: An obsessive preoccupation or attachment to making something firm or stable. • Healthy orthorexia: A non-pathological interest in healthy eating behavior. • Maladaptive behavior: An action that interferes with everyday activities with potential harmful effects. • Non-orthorexia nervosa: Synonymous with healthy orthorexia. • Obsession: A persistent and disturbing idea or thought. • Orthorexia nervosa: A possible pathological fixation on healthy eating. • Preoccupation: Synonymous with concern with a likely higher degree of alarm. • Psychometric properties: Validity (e.g., factorial) and reliability (e.g., internal consistency) estimates that allow showing data on the capacity of an instrument to measure latent construct(s). • Score: A numerical value that can be used to interpret the magnitude of a phenomenon. • Trigger: Something that sets off a mechanism.

Key Facts of Orthorexia • Orthorexia is represented by the concern with healthy eating that can be obsessive or not. • The term orthorexia nervosa has been used to represent an extreme fixation on healthy eating that can damage various areas of a person’s life. • Orthorexia nervosa is not yet recognized as a mental disorder included in the DSM-5 and ICD-11. • People with pathological behaviors to achieve a healthy diet can experience physical and mental impairments; therefore, therapeutic approaches used in official mental disorders can be useful. • The term healthy orthorexia has been used to represent an interest in healthy eating without obsessive behavior; however, it is not yet consolidated in the literature.

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• People who are interested in eating healthy can benefit from guidelines to direct their eating behaviors; however, these individuals do not have pathological symptoms that require intervention therapy.

Summary Points • Orthorexia is a phenomenon that lies on a continuum, which goes from an interest in healthy eating (non-pathological) to an extreme preoccupation and control (pathological). • Knowing the drive for healthy eating can be helpful for clinical management. • Orthorexia nervosa encompasses an intensification of the preoccupation with healthy eating with disturbing thoughts and stereotypical behaviors. • Healthy orthorexia involves an interest in healthy eating that does not harm the person’s life. • This chapter focuses on the conceptualization of healthy orthorexia and explores its forms of assessment and empirical evidence. • Much is known about orthorexia nervosa behaviors, but little is known about healthy orthorexia. • The use of proper assessment tools is necessity in the field, which is more focused on orthorexia nervosa, but a special look at healthy orthorexia is also helpful.

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He J, Ma H, Barthels F et al (2019) Psychometric properties of the Chinese version of the Dusseldorf Orthorexia Scale: prevalence and demographic correlates of orthorexia nervosa among Chinese university students. Eat Weight Disord 24(3):453–463. https://doi.org/10. 1007/s40519-019-00656-1 Hyrnik J, Janas-Kozik M, Stochel M et al (2016) The assessment of orthorexia nervosa among 1899 polish adolescents using the ORTO-15 questionnaire. Int J Psychiatry Clin Pract 20(3):199–203. https://doi.org/10.1080/13651501.2016.1197271 Kline RB (2016) Principles and practice of structural equation modeling, 4th edn. Guilford Press, New York Koven NS, Abry AW (2015) The clinical basis of orthorexia nervosa: emerging perspectives. Neuropsychiatr Dis Treat 11:385–394. https://doi.org/10.2147/NDT.S61665 Marôco J (2021) Análise de equações estruturais [Structural equation analysis]. ReportNumber, Lda, Pêro Pinheiro Mathieu J (2005) What is orthorexia? J Am Diet Assoc 105(10):1510–1512. https://doi.org/10. 1016/j.jada.2005.08.021 McCartney M (2016) Margaret McCartney: clean eating and the cult of healthism. BMJ 354:i4095. https://doi.org/10.1136/bmj.i4095 McComb SE, Mills JS (2019) Orthorexia nervosa: a review of psychosocial risk factors. Appetite 140:50–75. https://doi.org/10.1016/j.appet.2019.05.005 McGovern L, Gaffney M, Trimble T (2021) The experience of orthorexia from the perspective of recovered orthorexics. Eat Weight Disord 26(5):1375–1388. https://doi.org/10.1007/s40519020-00928-1 Mhanna M, Azzi R, Hallit S et al (2022) Validation of the Arabic version of the Teruel Orthorexia Scale (TOS) among Lebanese adolescents. Eat Weight Disord 27(2):619–627. https://doi.org/ 10.1007/s40519-021-01200-w Mitrofanova E, Pummell EKL, Mulrooney HM et al (2021) Using behavioural reasoning theory to explore reasons for dietary restriction: a qualitative study of orthorexic behavioural tendencies in the UK. Front Psychol 12:685545. https://doi.org/10.3389/fpsyg.2021.685545 Mohamed Halim Z, Dickinson KM, Kemps E et al (2020) Orthorexia nervosa: examining the Eating Habits Questionnaire’s reliability and validity, and its links to dietary adequacy among adult women. Public Health Nutr 23(10):1684–1692. https://doi.org/10.1017/ S1368980019004282 Moroze RM, Dunn TM, Craig Holland J, Yager J, & Weintraub P (2015) Microthinking about micronutrients: a case of transition from obsessions about healthy eating to near-fatal “orthorexia nervosa” and proposed diagnostic criteria. Psychosomatics 56(4):397–403. https://doi.org/ 10.1016/j.psym.2014.03.003 Niedzielski A, Kazmierczak-Wojtas N (2021) Prevalence of orthorexia nervosa and its diagnostic tools: a literature review. Int J Environ Res Public Health 18(10). https://doi.org/10.3390/ ijerph18105488 Oberle CD, de Nadai AS, Madrid AL (2021) Orthorexia Nervosa Inventory (ONI): development and validation of a new measure of orthorexic symptomatology. Eat Weight Disord 26(2): 609–622. https://doi.org/10.1007/s40519-020-00896-6 Roncero M, Barrada JR, Garcia-Soriano G et al (2021) Personality profile in orthorexia nervosa and healthy orthorexia. Front Psychol 12:710604. https://doi.org/10.3389/fpsyg.2021.710604 Segura-Garcia C, Ramacciotti C, Rania M et al (2015) The prevalence of orthorexia nervosa among eating disorder patients after treatment. Eat Weight Disord 20(2):161–166. https://doi.org/10. 1007/s40519-014-0171-y Setnick J (2013) The eating disorders clinical pocket guide: quick reference for healthcare providers. Understanding Nutrition, Dallas Silva WR, Cruz Marmol CH, Nogueira Neves A et al (2021) A Portuguese adaptation of the Teruel Orthorexia Scale and a test of its utility with Brazilian young adults. Percept Mot Skills 128(5): 2052–2074. https://doi.org/10.1177/00315125211029240

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Strahler J (2020) The dark side of healthy eating: links between orthorexic eating and mental health. Nutrients 12(12). https://doi.org/10.3390/nu12123662 Strahler J (2021) Trait mindfulness differentiates the interest in healthy diet from orthorexia nervosa. Eat Weight Disord 26(3):993–998. https://doi.org/10.1007/s40519-020-00927-2 Strahler J, Hermann A, Walter B et al (2018) Orthorexia nervosa: a behavioral complex or a psychological condition? J Behav Addict 7(4):1143–1156. https://doi.org/10.1556/2006.7. 2018.129 Strahler J, Haddad C, Salameh P et al (2020) Cross-cultural differences in orthorexic eating behaviors: associations with personality traits. Nutrition 77:110811. https://doi.org/10.1016/j. nut.2020.110811 Valente M, Syurina EV, Donini LM (2019) Shedding light upon various tools to assess orthorexia nervosa: a critical literature review with a systematic search. Eat Weight Disord 24(4):671–682. https://doi.org/10.1007/s40519-019-00735-3 Varga M, Dukay-Szabo S, Tury F et al (2013) Evidence and gaps in the literature on orthorexia nervosa. Eat Weight Disord 18(2):103–111. https://doi.org/10.1007/s40519-013-0026-y Walker-Swanton FE, Hay P, Conti JE (2020) Perceived need for treatment associated with orthorexia nervosa symptoms. Eat Behav 38:101415. https://doi.org/10.1016/j.eatbeh.2020.101415 World Health Organization (2003). Diet, nutrition and the prevention of chronic diseases. World Health Organ Tech Rep Ser 916: i–viii, 1–149, backcover World Health Organization (2020) Healthy eating. Available at: www.who.int/news-room/factsheets/detail/healthy-diet Yakin E, Raynal P, Chabrol H (2022) Distinguishing between healthy and pathological orthorexia: a cluster analytic study. Eat Weight Disord 27(1):325–334. https://doi.org/10.1007/s40519-02101178-5 Zickgraf HF, Barrada JR (2022) Orthorexia nervosa vs. healthy orthorexia: relationships with disordered eating, eating behavior, and healthy lifestyle choices. Eat Weight Disord 27(4): 1313–1326. https://doi.org/10.1007/s40519-021-01263-9

The Binge Eating Scale Features and Applications

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Sagar Karia, Shorouq Motwani, and Avinash Desousa

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Diagnosis and Scales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Binge Eating Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Scoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Other Uses of BES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Other Versions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Modified Versions of BES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Applications to Other Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mini-Dictionary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Key Facts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Key Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Questions in Binge Eating Scale and Scoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Binge eating disorder (BED) is a type of ED that is characterized by recurrent episodes of binge eating (BE) without subsequent compensatory behaviors, such as self-induced vomiting or over-exercising. The Binge Eating Scale (BES) is one of the most common instruments used to screen binge eating severity. The BES has been found to demonstrate a very good internal consistency (between 0.85 and 0.90) and a good construct validity. There have been various versions developed of BES like French, Persian, Arabic, Spanish, etc. Keywords

Binge eating · Scale · Eating disorder S. Karia (*) · S. Motwani · A. Desousa Department of Psychiatry, L.T.M.M.C. & G.H., Sion, Mumbai, Maharashtra, India © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_88

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Introduction Eating disorder (ED) most frequently affects young Western females within highincome and industrialized Western Europe and North America, but can also occur in diverse countries and cultures worldwide to a lesser extent. The disorder is found to be more common in the population suffering from obesity, and it is usually associated with several psychiatric (anxiety, depression, obsessive-compulsive disorder) and physical comorbidities (diabetes, hypertension). It has been seen that anxiety is the most important associated factor with ED, followed by stress, body image, and depression. Binge eating disorder (BED) is a type of ED that is characterized by recurrent episodes of binge eating (BE) without subsequent compensatory behaviors, such as self-induced vomiting or over-exercising (Zeidan et al. 2019). Very high BED prevalence rates have been reported in adolescents and young adults, with higher prevalence rates in women than in men, and recent neuroimaging studies suggest that this sex differences in binge eating may be due to the presence of some alteration in the female brain’s reward system, such as the lower ability to suppress hunger in women (Escrivá-Martínez et al. 2019; Imperatori et al. 2016). Smink et al. showed that BE has two peak ages of onset, one immediately after puberty at an average age of 14, and the other at the end of adolescence (19–24 years). Average lifetime prevalence is estimated to be 1.9% for BED, making it the most common ED (Escrivá-Martínez et al. 2019). The risk factors associated with BED are similar to those with psychiatric disorders and obesity. The most common risk factors associated with BED are as follows (Zeidan et al. 2019): 1. 2. 3. 4. 5.

Adverse childhood experiences such as sexual/physical abuse. Parental problems like depression. Negative self-evaluation. Vulnerability to obesity. Repeated exposure to negative comments about shape, weight, or eating is associated with BED. 6. A positive correlation has been found between BE and food addiction. 7. Emotional eating has also been found to be positively related to BE. In fact, overeating just for emotional reasons and cravings may turn quickly into BED. 8. Family history of eating disorders is associated with higher BE. BED is found to aggregate strongly within families, which may reflect genetic influences. Tuschen-Caffier and Hilbert model has integrated the triggering and sustaining factors of the BED in addition to the risk factors. Based on this model, different external and internal stressors like relationship conflicts, exposure to food, impulsivity, low self-esteem, and tensions have been identified that can trigger BE. BED also shares characteristics with substance use and addictive disorders (Zeidan et al. 2019).

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Recent research indicates the presence of comorbidity between BE and the use of alcohol and binge drinking in young people. Impulsivity can play an important role in the comorbidity between disordered eating behavior and excessive alcohol consumption in young students and has also been positively associated with BE (Escrivá-Martínez et al. 2019). Despite data suggesting that only a small subset of adolescents 10–13 and even fewer children 14–16 meet full DSM-IV-TR criteria for BED, binge eating and the experience of loss of control (LOC) while eating (regardless of the amount of food ingested) appear to be quite common among youth (Tanofsky-Kraff et al. 2007).

Diagnosis and Scales Diagnosis of BED according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), is based on the occurrence of at least one BE episode per week for three consecutive months; these episodes are characterized by the consumption of larger amounts of food in a short period when compared to the typical amounts for most people under similar circumstances, accompanied by a sense of loss of control over eating and a marked distress during these episodes (Zeidan et al. 2019). Eating Disorder Examination (EDE) interview provides a comprehensive scheme for classifying episodes of overeating using perceived lack of control and amount of food consumed as criteria to distinguish between different types of overeating. Based on these criteria, four different types of overeating are identified: (a) objective binge eating: loss of control and objectively large amount consumed; (b) subjective binge eating: loss of control and small amount consumed even though the individual views intake as excessive; (c) objective overeating: no loss of control and objectively large amount consumed; and (d) subjective overeating: no loss of control and small amount consumed, but individual views amount consumed as excessive. Objective binge eating is used as part of the DSM-IV diagnostic criteria for Binge Eating Disorder (BED; American Psychiatric Association 1994; Timmerman 1999). To assess any psychological disorder including binge eating, structured clinical interview is considered as gold standard. However, it is time-consuming, requires training, and can only be administered to one subject at any particular time (Robert et al. 2013). Several self-report questionnaires have been developed to assess BED to replace the interview and save time. Gormally et al. (1982) developed the BES, Yanovski (1993) developed the Questionnaire on Eating and Weight Patterns (QEWP-R), and Fairburn and Beglin (1994) developed the Eating Disorder Examination Questionnaire (EDE-Q). The Binge Eating Scale (BES) is one of the most common instruments used to screen binge eating severity.

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Binge Eating Scale The Binge Eating Scale (BES) was developed by Gormally et al. to measure severity of binge eating, the uncontrolled consumption of a large amount of food, in overweight binge eaters (Timmerman 1999). It is an interesting tool both in terms of evaluation and monitoring of these patients, as it can be used for the purposes of screening, evaluation of severity, and monitoring of the disorder (Zeidan et al. 2019). Since its inception, the BES has been used widely in research to measure binge eating severity in the non-purge binge eating population and to determine whether potential research participants meet the inclusion criteria of binge eating (Timmerman 1999). Importantly, the BES is not intended to detect presence of Binge Eating Disorder (BED) as it was created before binge eating disorder (BED) was officially recognized as a psychiatric diagnosis (American Psychiatric Association 1994). Rather, it can be used as a brief screening tool to identify the severity of binge eating behavior in overweight and obese adults, to tailor obesity interventions, and to track treatment outcomes (Cotter and Kelly 2015). The BES was designed as a measure of severity rather than diagnosis of BED, with the additional property of evaluating its affective, cognitive, and behavioral manifestations. It has an outstanding role as a screening measure in clinical and nonclinical populations to evaluate BE severity and intervention outcomes (Escrivá-Martínez et al. 2019). It does not specify a time frame and presents a series of differently weighted statements for each item, from which respondents select the statement that best describes their attitudes and behaviors (Celio et al. 2004). Studies carried out in the past decade, mainly with obese patients, have shown that the BES is very sensitive and specific in distinguishing between compulsive and normal eaters (Escrivá-Martínez et al. 2019). The BES has been found to demonstrate a very good internal consistency (between 0.85 and 0.90) and a good construct validity (Zeidan et al. 2019). The BES items were created in accordance with the “Diagnostic and Statistical Manual of Mental Disorders, 3rd edition,” criteria for binge eating. Although the BES is not designed to assess for the presence of binge eating disorder (BED), in one of the few studies that evaluated the concordance between the BES and BED in bariatric surgery candidates, BES was found to have a high sensitivity and adequate specificity in identifying those with BED (Cotter and Kelly 2015). Estimated internal consistency of the measure is generally acceptable across samples, including men and women from the community, college students, treatment-seeking adults, and racially/ethnically diverse groups (Hood et al. 2013). The BES demonstrates a significant association with several indicators of subjective binge eating (SBE) like calories consumed during SBEs, number of SBEs, and number of SBE days. Small-to-moderate, significant correlations have also been noted between the BES and similar indicators of objective binge eating. BES scores do not correlate with overall caloric intake and is not successful in discriminating between SBEs and OBEs, but appears to be a good indicator of severity of LOC eating (Cotter and Kelly 2015).

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The BES is a 16-item self-report measure designed to assess two components of binge eating: behavioral manifestations (e.g., eating quickly, overeating) and emotions/cognitions that precede or follow a binge (e.g., feeling out of control, guilt) (Hood et al. 2013). The initial development of the scale yielded two eight-item factors representing the behavioral and cognitive/emotional aspects of binge eating. More recent examinations of the scale further support this two-factor solution, suggesting that the existing subscales remain appropriate across a range of samples (Cotter and Kelly 2015).

Scoring The BES consists of 16 items, eight describing the behavioral manifestations of binge eating and eight describing feelings and cognitions associated with binge eating. Each item consists of four statements that reflect a range of severity (0 indicates no binge eating problem and 3 indicates a severe binge eating problem). Subjects choose the statement that best describes their perceptions and feelings about their eating behavior. The BES is scored by adding the individual values for the 16 items with the possible range of scores from 0 to 46 (Timmerman 1999). Based on BES scores, the uncontrolled eating behavior is graded into three different levels of severity: subjects scoring 17 and less were considered non-binge eaters, those scoring between 18 and 26 were moderate binge eaters, and those scoring 27 and above were considered severe binge eaters (Robert et al. 2013). Thus, the total score is used to differentiate among those with absent to minimal binge eating, mild to moderate binge eating, and severe binge eating (Hood et al. 2013). Based on the BES total raw scores, Marcus et al. (1988) identified three different levels of severity: individuals scoring 17 or less were considered not reporting significant binge eating, those scoring between 18 and 26 were considered moderate binge eaters, and those scoring 27 and above were considered severe binge eaters. These categories had a 98% concordance rate with a diagnosis using a semistructured interview (Imperatori et al. 2016).

Other Uses of BES BES has been used as a screening measure in prebariatric surgery psychological evaluations (Hood et al. 2013). Administering the BES as part of a comprehensive psychological evaluation can help improve the assessment and treatment of patients presenting for bariatric surgery (Celio et al. 2004). BES is a reliable measure that identifies approximately one third of patients seeking bariatric surgery (Hood et al. 2013). When prescreening potential bariatric surgery patients, clinicians are likely to be interested in identifying patients who endorse significant binge behaviors, even if

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they do not meet full criteria for BED. In other words, identifying false positives is often acceptable as further evaluation and appropriate presurgical cognitive/behavioral interventions can be recommended. Timmerman reported an adequate 2-week test–retest reliability of the BES in a behavioral weight loss sample. BES is an appropriate measure to screen for binge eating behaviors in nonsurgical weight loss treatment, although false positives may be common (Celio et al. 2004).

Limitations 1. Gormally et al. originally proposed a two-dimensional structure, dividing the items of the BES into cognitive and behavioral BE, but the results on its two-dimensionality use are contradictory (Zeidan et al. 2019). Most of the times it is exclusively used as a unidimensional measure of binge eating severity through the measure’s total score, but studies have shown that both the unidimensional and the two-factor models provide an adequate fit to the data, in fact the fit of the two-factor model maybe better (Hood et al. 2013). Of all the models compared, the bi-factor model is more superior in its potential for replication. Various studies have cast doubt on the utility of calculating the behaviors and feelings/cognitions factors as separate scores on the BES (Imperatori et al. 2016; Hood et al. 2013). 2. Though BES questionnaire has been widely used, there is limited research on the factors and properties of the BES in the general population. There is no study examining its psychometric properties in general populations of young men and women. Research has been done to assess the validity in specific samples like clinical samples or samples of women, especially obese women who undergo bariatric surgery to lose weight (Hood et al. 2013; Marek et al. 2016), or obese and overweight patients seeking weight loss treatment (Imperatori et al. 2016). 3. BES may be adequate for screening purposes but its use solely for the diagnosis of BED is not recommended due to the high percentage of misclassifications (Celio et al. 2004).

Other Versions The BES has been translated into a variety of languages and validated in multiple international samples. Spanish version: Spanish version of the BES is a valid and reliable scale for the assessment of BE in a youth sample. This brief, easy-to-administer, self-report questionnaire consists of 16 items on one scale. It provides relevant information about clinically significant symptoms of BE, and it may be especially useful in prevention programs and community interventions for disordered eating behaviors (Escrivá-Martínez et al. 2019). Persian version: The BES showed acceptable reliability and considerable sensitivity (84.8%) and specificity (80.8%). BES, also, effectively distinguished the obese participants from the normal weight subjects. These results suggest that the

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Persian version of BES is a sensitive instrument for screening binge eating among the nontreatment-seeking obese population (Mootabi et al. 2009). Indonesian version: The Indonesian version of BES has good validity. The two-factor BES was revealed to be important in Indonesia, cross-culturally. There were language and cultural differences among Indonesian ethnics, which required a scale that uses standard language. This Indonesian version of BES can be used immediately. Thus, it can help improve planning of health promotion, prevention, and treatment of binge eating (Kusbiantari et al. 2020). French version: The psychometric properties of the French version of the BES are comparable to its original version with a one factor structure. The BES is a useful tool to assess binge eating disorder in obese patients but might not differentiate binge eating disorder and bulimia nervosa in underweight and optimal weight subjects (Brunault et al. 2016). Arabic Version: The Binge Eating Scale in its Arabic version is a suitable instrument to screen for binge eating among the Lebanese population. Some factors (body dissatisfaction, having a history of sexual abuse, a family history of binge eating, greater depressive/anxiety symptoms, and lower self-esteem) seem to be associated with higher binge eating (Zeidan et al. 2019). Malaya Version: A study demonstrated high levels of sensitivity (84.6%) and specificity (94.9%) of the Malay version of BES in detecting binge eating behavior within a Malay-speaking adult population, with a positive predictive value of 81.8%, negative predictive value of 95.7% and Cronbach’s alpha of 0.89. Therefore, the Malay version of the BES is useful as it has been demonstrated to be a valid and reliable instrument that is easy to administer (Robert et al. 2013). Only five of the 16 items were correlated when studies were carried out to determine possible ways to strengthen concordance of the BES with a BED diagnosis. The items that were significantly associated with a BED diagnosis measured preoccupation with eating (item 14), guilt after overeating (item 6), difficulty controlling eating (item 10), preoccupation with food (item 15), and eating when not hungry (item 5) (Celio et al. 2004). When using the BES clinical cutoffs there is tendency to over diagnose BED so it is suggested that the BES be used as a brief screening device and not as a diagnostic indicator (Cotter and Kelly 2015).

Modified Versions of BES 1. The Children’s Binge Eating Disorder Scale (C-BEDS) is a 7-item measure which includes Marcus and Kalarchian’s criteria. For example One item asks, “Do you ever eat because you feel bad, sad, bored, or any other mood?” to which children respond “yes” or “no” (Tanofsky-Kraff et al. 2007). This scale was developed to measure BED in children according to the provisional criteria. Both the provisional criteria and the C-BEDS may be developmentally appropriate for use with children, although the C-BEDS may be a better screening

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instrument as it quickly identified children with subsyndromal BED. If used by physicians and other health providers, this brief measure may assist with identifying early onset binge eating behaviors and avoiding the associated consequences, including adult BED, obesity, and other comorbidities (Shapiro et al. 2007). 2. The Adolescent Binge Eating Scale questionnaire is a potential screening tool to identify adolescents with obesity at high risk of BED and guide referral to a specialist to clarify the diagnosis and provide adequate care. Binge eating disorder (BED) is associated with obesity and high rates of medical and psychopathologic comorbidity, as well as increased healthcare use. Research involving children and adolescents has shown that few meet all the criteria for BED, as described by the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The ADO-BED auto-questionnaire demonstrated a good association with the clinical interview for BED, particularly for question 1, “food seeking in the absence of hunger or after satiation,” which was efficient to exclude adolescents without BED when answered negatively. The first question was more indicative than the second relative to the sense of lack of control over eating (sensitivity 85.7%). This may be explained by the subjectivity of this question and the adolescents’ limited capacity to recognize such a behavior, even when illustrated by a concrete example such as, “Has it ever happened that you started eating biscuits and could not stop before the end of the packet?” However, answering positively to one of these two questions was not in itself predictive of BED (specificity 27.4%) (Chamay-Weber et al. 2017).

Applications to Other Eating Disorders The Binge Eating Scale (BES) has no direct role in the assessment of other eating disorders but may be used as an add-on scale when scales for other eating disorders are applied. This is more so as binge eating behavior may be part of other eating disorders like Bulimia and is worth evaluating in those patients. The BES may provide insights into the binge eating behavior patterns in those patients and may also provide insights into the comprehensive management of these patients. The BES may be of use in patients with obesity where there are binge eating issues, and as a result, there is weight gain and there are many instances that these patients may have guilt and shame related to binge eating. The scale may help in the management of binge eating behavior in patients with obesity and looking at weight management as a part of their treatment. The BES may be useful in patients with borderline personality disorder that may have binge eating as a coping mechanism in these patients. The scale may also be useful in adolescents that have binge eating as mechanism of coping. There is a need to study the usefulness of BES in these populations so that we are able to deduce its utility in these cases and decipher its exact applications. Detailed literature in these conditions is sparse.

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Mini-Dictionary 1. Adolescence: Adolescence is the transitional phase of growth and development between childhood and adulthood. The World Health Organization (WHO) defines an adolescent as any person between ages 10 and 19. 2. Binge: a period of excessive indulgence in an activity, especially eating, drinking, or taking drugs. 3. Disorder: a disturbance of normal functioning of the mind or body. 4. Eat: put (food) into the mouth and chew and swallow it. 5. Obesity: A disorder involving excessive body fat that increases the risk of health problems. 6. Overeat: Eat too much. 7. Screening: the evaluation or investigation of something as part of a methodical survey, to assess suitability for a particular role or purpose.

Key Facts • The Binge Eating Scale (BES) is one of the most commonly used instruments to screen binge eating severity. • There are many versions of scale in many languages like French, Persian, Arabic, Spanish, etc. • The BES has been found to demonstrate a very good internal consistency and reliability. • The scale aids in screening, diagnosis, and to judge improvement in children and adults with binge eating problems. • Apart from binge eating disorder, the BES has uses in other eating disorders and obesity as well as patients undergoing bariatric surgery.

Key Summary Points • The BES is one of the most widely used scales in the screening and diagnosis of binge eating behavior and binge eating disorder. • The scale has greater use in the measurement of severity rather than diagnosis of binge eating disorder. • The BES has a version to assess binge eating severity in children and adolescents as well. • Further studies of the BES in diverse populations of eating disorders are needed to validate its use better. • The BES also has versions in many languages that allow it to be used in national and international populations across research studies.

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Conclusion The BES may identify a significant number of patients with moderate/severe binge eating who do not meet criteria for BED; this is acceptable for a screening instrument, where false positives are more desirable than false negatives. Finally, clinicians can be very confident that a patient with a negative BES screen most likely does not have BED (Grupski et al. 2013).

Questions in Binge Eating Scale and Scoring 1. Self-conscious about weight: • I do not think about my weight or size when I’m around other people. • I worry about my appearance‚ but it does not make me unhappy. • I think about my appearance or weight and I feel disappointed in myself. • I frequently think about my weight and feel great shame and disgust. 2. Eat Quickly: • I have no difficulty eating slowly. • I may eat quickly‚ but I never feel too full. • Sometimes after I eat fast I feel too full. • Usually I swallow my food almost without chewing‚ then feel as if I ate too much. 3. Difficulty controlling Eating Urges: • I can control my impulses towards food. • I think I have less control over food than the average person. • I feel totally unable to control my impulses toward food. • I feel totally unable to control my relationship with food and I try desperately to fight my impulses toward food. 4. Eat when bored: • I do not have a habit of eating when I am bored. • Sometimes I eat when I am bored‚ but I can often distract myself and not think about food. • I often eat when I am bored‚ but I can sometimes distract myself and not think about food. • I have a habit of eating when I am bored and nothing can stop me. 5. Eat when not hungry: • Usually when I eat it is because I am hungry. • Sometimes I eat on impulse without really being hungry. • I often eat to satisfy hunger even when I know I’ve already eaten enough. On these occasions I can’t even enjoy what I eat. • Although I have not physically hungry‚ I feel the need to put something in my mouth and I feel satisfied or only when I can fill my mouth (for example with a piece of bread).

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6. Guilt after overeating: • I do not feel guilty or regretful at all. • I sometimes feel guilty or regretful. • I almost always feel a strong sense of guilt or regret. 7. Diet and Binge: • When I’m on a diet‚ I never completely lose control of food‚ even in times when I eat too much. • When I eat a forbidden food on a diet‚ I think I’ve failed and eat even more. • When I’m on a diet and I eat to much‚ I think I’ve failed and eat even more. • I am always either binge eating or fasting. 8. Eat tilled stuff: • It is rare that I eat so much that I felt uncomfortably full. • About once a month I eat so much that I felt uncomfortably full. • There are regular periods during the month when I eat large amounts of food at meals or between meals. • I eat so much that usually‚ after eating‚ I feel pretty bad and I have nausea. 9. Diet/restrict and binge: • The amount of calories that I consume is fairly constant over time. • Sometimes after I eat too much‚ I try to consume few calories to make up for the previous meal. • I have a habit of eating too much at night. Usually I’m not hungry in the morning and at night I eat too much. • I have periods of about a week in which I imposed starvation diets‚ following periods of when I ate too much. My life is made of binges and fasts. 10. Difficulty controlling eating: • I can usually stop eating when I decide I’ve had enough. • Sometimes I feel an urge to eat that I cannot control. • I often feel impulses to eat so strong that I cannot win‚ but sometimes I can control myself. • I feel totally unable to control my impulses to eat. 11. Eat till stuffed or sometimes vomit: • I have no problems stopping eating when I am full. • I can usually stop eating when I feel full‚ but sometimes I eat so much it feels unpleasant. • It is hard for me to stop eating once I start‚ I usually end up feeling too full. • It is a real problem for me to stop eating and sometimes I vomit because I feel so full. 12. Conceal eating: • I eat the same around friends and family as I do when I am alone. • Sometimes I do not eat what I want around others because I am aware of my problems with food. • I often eat little around other people because I feel embarrassed. • I’m so ashamed of overeating; I only eat at times when no one sees me. I eat in secret.

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13. Eat continually: • I eat three meals a day and occasionally a snack. • I eat three meals a day and I usually snack as well. • I eat many meals‚ or skip meals regularly. • There are times when I seem to eat continuously without regular meals. 14. Preoccupation with eating: • I don’t think about impulses to eat very much. • Sometimes my mind is occupied with thoughts of how to control the urge to eat. • I often spend much time thinking about what I ate or how not to eat. • My mind is busy most of the time with thoughts about eating. • I seem to be constantly fighting not to eat. 15. Preoccupied with food: • I don’t think about food any more than most people. • I have strong desires for food‚ but only for short periods. • There are some days when I think of nothing but food. • Most of my days is filled with thoughts of food. I feel like I live to eat. 16. Uncertain how much food is normal: • I usually know if I am hungry or not. I know what portion sizes are appropriate. • Sometimes I do not know if I am physically hungry or not. In these moments‚ I can hardly understand how much food is appropriate. • Even if I knew how many calories should I eat‚ I would not have a clear idea of what is‚ for me‚ a normal amount of food. Non-binging; less than 17 Moderate binging; 18–26 Severe binging; 27 and greater

References American Psychiatric Association (1994) Diagnostic and statistical manual of mental disorders. 4. Washington, DC: American Psychiatric Association; 1994. (DSM-IV) Brunault P, Gaillard P, Ballon N, Couet C, Isnard P, Cook S, Delbachian I, Réveillère C, Courtois R (2016) Validation of the French version of the binge eating scale: examination of its factor structure, internal consistency and construct validity in a non-clinical and a clinical population. L’encephale 42(5):426–433 Celio AA, Wilfley DE, Crow SJ, Mitchell J, Walsh BT (2004) A comparison of the binge eating scale, questionnaire for eating and weight patterns-revised, and eating disorder examination questionnaire with instructions with the eating disorder examination in the assessment of binge eating disorder and its symptoms. Int J Eat Disord 36(4):434–444 Chamay-Weber C, Combescure C, Lanza L, Carrard I, Haller DM (2017) Screening obese adolescents for binge eating disorder in primary care: the adolescent binge eating scale. J Pediatr 185: 68–72 Cotter EW, Kelly NR (2015) Binge Eating Scale (BES). In: Wade T (ed) Encyclopedia of feeding and eating disorders. Springer, Singapore

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Escrivá-Martínez T, Galiana L, Rodríguez-Arias M, Baños RM (2019) The binge eating scale: structural equation competitive models, invariance measurement between sexes, and relationships with food addiction, impulsivity, binge drinking, and body mass index. Front Psychol 10:530 Fairburn CG, Beglin SJ (1994) Assessment of eating disorders: interview or self‐report questionnaire?. Int J Eat Disord 16(4):363–370 Gormally JIM, Black S, Daston S, Rardin D (1982) The assessment of binge eating severity among obese persons. Addict Behav 7(1):47–55 Grupski AE, Hood MM, Hall BJ, Azarbad L, Fitzpatrick SL, Corsica JA (2013) Examining the Binge Eating Scale in screening for binge eating disorder in bariatric surgery candidates. Obes Surg 23(1):1–6 Hood MM, Grupski AE, Hall BJ, Ivan I, Corsica J (2013) Factor structure and predictive utility of the Binge Eating Scale in bariatric surgery candidates. Surg Obes Relat Dis 9(6):942–948 Imperatori C, Innamorati M, Lamis DA, Contardi A, Continisio M, Castelnuovo G, Manzoni GM, Fabbricatore M (2016) Factor structure of the binge eating scale in a large sample of obese and overweight patients attending low energy diet therapy. Eur Eat Disord Rev 24(2):174–178 Kusbiantari D, Fitriana E, Hinduan ZR, Srisayekti W (2020) Psychometric properties of Binge Eating Scale Indonesian version. Open Psychol J 13(1):310–314 Marcus MD, Wing RR, Hopkins J (1988) Obese binge eaters: affect, cognitions, and response to behavioral weight control. J Consult Clin Psychol 56(3):433 Marek RJ, Heinberg LJ, Lavery M, Merrell Rish J, Ashton K (2016) A review of psychological assessment instruments for use in bariatric surgery evaluations. Psychol Assess 28(9):1142 Mootabi F, Moloodi R, Dezhkam M, Omidvar N (2009) Standardization of the Binge Eating Scale among Iranian obese population. Iran J Psychiatry 4(4):143–146 Robert SA, Rohana AG, Suehazlyn Z, Maniam T, Azhar SS, Azmi KN (2013) The validation of the Malay version of binge eating scale: a comparison with the structured clinical interview for the DSM-IV. J Eat Disord 1(1):1–6 Shapiro JR, Woolson SL, Hamer RM, Kalarchian MA, Marcus MD, Bulik CM (2007) Evaluating binge eating disorder in children: Development of the children’s binge eating disorder scale (C-BEDS). Int J Eat Disord 40(1):82–89 Tanofsky-Kraff M, Theim KR, Yanovski SZ, Bassett AM, Burns NP, Ranzenhofer LM, Glasofer DR, Yanovski JA (2007) Validation of the emotional eating scale adapted for use in children and adolescents (EES-C). Int J Eat Disord 40(3):232–240 Timmerman GM (1999) Binge eating scale: further assessment of validity and reliability 1. J Appl Biobehav Res 4(1):1–12 Yanovski SZ (1993) Questionnaire on eating and weight patterns-revised (QEWP-R). Obes Res 1:319–324 Zeidan RK, Haddad C, Hallit R, Akel M, Honein K, Akiki M, Kheir N, Hallit S, Obeid S (2019) Validation of the Arabic version of the binge eating scale and correlates of binge eating disorder among a sample of the Lebanese population. J Eat Disord 7(1):1–14

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Health-Related Quality of Life Questionnaires Applications to Eating Disorders Jelena Milic, Dunja Stankic, and Dona Stefanovic

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Short Form-36 (SF-36) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Eating Disorder Examination-Questionnaire (EDE-Q) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Short Form-12 Health Status Questionnaire (SF-12) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Weissman Scale of Social Adjustment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . BDI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Eating Disorder Diagnostic Scale (EDDS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Health-Related Quality of Life in ED-Short Form (HeRQoLED-S) . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mini-Dictionary of Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Key Fact of Health-Related Quality of Life Questionnaires: Applications to EDs . . . . . . . . . . . Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

People suffering from eating disorders (EDs) are affected both on the somatic and psychological and social aspects. The World Health Organization used the term quality of life to define individuals’ perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, Dunja Stankic and Dona Stefanovic contributed equally with all other contributors. J. Milic (*) Department for Methodological Principles and Standards of Integrated Health Information System and Reporting, Institute of Public Health of Serbia “Dr Milan Jovanovic Batut”, Belgrade, Serbia D. Stankic Faculty of Medicine, Editorial Office of Journal “Medicinar”, University of Belgrade, Belgrade, Serbia D. Stefanovic Center for Anesthesiology and resuscitation at Clinical Center of Serbia, School of Medicine, University of Belgrade, Belgrade, Serbia © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_89

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expectations, standards, and concerns to express the broad range of changes in a person’s life. Some of these changes are either triggered or suffer consequences from eating habits that are often a form of EDs. In the last few decades, there is an increasing interest in finding adequate questionnaires to help identify and measure the severity of EDs, as well as questionnaires to examine the quality of life in these patients. Several studies have been conducted on this subject, and the evolution and scientific advancement will be elaborated and discussed in the following text in order to identify the most appropriate questionnaire that will aid clinicians in their therapeutic practice. Among the first questionnaires used in practice to assess the quality of life of patients with an ED were Short Form-36 (SF-36) and the Eating Disorder Examination-Questionnaire (EDE-Q). Although the generic questionnaires were applied and yielded good results, a specific questionnaire on the quality of life of individuals with EDs is still lacking in this field. New discoveries are made as the search for highly specialized and sensitive questionnaires continues. Several instruments and questionnaires are used to obtain a final result in several studies investigating the association between the intensity of symptoms induced by EDs and quality of life. The most recent questionnaires specific to the quality of life of a patient with an ED are the Eating Disorders Quality of Life Scale (EDQLS) and the Eating Disorders Quality of Life Scale (EDQOL). We conclude that there has been great progress in evaluating and designing appropriate questionnaires to help clinicians and researchers in the diagnosing, developing treatment strategies, and prognosing EDs, as well as assessing quality of life in these patients. Keywords

Eating disorder · Quality of life · Questionnaire · Instrument Abbreviations

BDI EAT-26 EDDS EDE-Q HADS HeRQoLED-s QoL SF-12 SF-36 WHO

Beck Depression Inventory Eating Attitudes Test The Eating Disorder Diagnostic Scale Eating Disorder Examination-Questionnaire The Hospital Anxiety and Depression Scale Health-Related Quality of Life in ED-short form Quality of Life Short Form-12 Health Status Questionnaire The Short Form-36 The World Health Organization

Introduction People suffering from eating disorders (EDs) are affected both on the somatic and psychological and social aspects. Eating problems are increasingly demonstrating potentials to cause substantial medical, mental, and social consequences. The WHO defines quality of life as the World Health Organization (WHO) defines QoL as an

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individual’s perception of their position in life in the context of the culture and value system in which they live and in relation to their goals, expectations, standards, and concerns (Orley et al. 1998). As a result, a wide range of related domains, such as the connection of physical health with social and psychological functioning, have an impact on quality of life. If EDs progress to a chronic stage, they can have a substantial influence on the patient’s physical, social, psychological, and other aspects of life. As a result, assessing the quality of life of ED patients is an important part of the treatment process and should be incorporated into therapeutic practice. In the last few decades, there has been more and more interest in finding adequate questionnaires to help identify and measure the severity of EDs, as well as questionnaires to examine the quality of life of these patients. Several studies have been conducted on this subject, and the evolution and scientific advancement will be elaborated and discussed in the following text in order to identify the most appropriate questionnaire that will aid clinicians in their therapeutic practice (Fig. 4). Among the first questionnaires used in practice to assess the QOL of patients with an ED were Short Form-36 (SF-36) and the Eating Disorder ExaminationQuestionnaire (EDE-Q).

The Short Form-36 (SF-36) A generic health-related quality of life questionnaire, the Short Form-36 (SF-36), examines quality of life (Fairburn and Wilson 1993). The SF-36 comprises questions concerning an individual’s functioning and contentment in several areas of life. The SF-36 is a 36-question survey that examines a person’s happiness with their physical, mental, social, and emotional well-being. The SF-36 scale has a range of 0 to 100 points. A higher score suggests a better quality of life (Fairburn and Wilson 1993) (Fig. 1). Although the generic Short Form-36 (SF-36) questionnaire was applied and yielded good results, a specific questionnaire on the quality of life of individuals with EDs is lacking in this field. The questionnaire was used to assess the quality of life of patients with EDs; nevertheless, issues were found that obscured the true image of the quality of life of these patients. The fundamental concern is that the Short Form-36 is not sensitive or specific enough for patients with EDs – in other words, it does not address enough aspects relevant to how EDs can affect a patient’s quality of life. Specific concerns and common symptoms associated with certain disorders, such as EDs, are assessed using disease-specific questionnaires. Diseasespecific questionnaires are more likely to show substantial differences than generic questionnaires because they are more sensitive. Scientists were inspired by the challenge to create and evaluate new, more sensitive quality of life questionnaires.

Eating Disorder Examination-Questionnaire (EDE-Q) The Eating Disorder Examination-Questionnaire (EDE-Q) is a self-assessment questionnaire adapted by Fairburn (Ware et al. 1993). The questionnaire is structured

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Fig. 1 Components of the Short Form-36 questionnaire. A generic health-related quality of life questionnaire (SF-36) which includes both physical and mental component (Ware and Gandek 1998)

into 36 questions about the patient’s eating habits during the previous 28 days. It includes questions based on DSM-IV criteria for EDs. Feeling obese, fear of gaining weight, bulimic episodes, certain dietary restrictions, compensatory behaviors such as self-induced vomiting or laxative abuse, irrational desire to lose weight, obsessive need for a healthy diet, and the impact of physical appearance on self-esteem are all covered by the questionnaire. In regard to the frequency of symptoms in the previous 28 days, the questions were assessed on a scale of 6 points (Fig. 2). A study published by S. Engel in 2006 was conducted on the development and validation of questionnaires designed to combine the symptoms of EDs with quality of life. In this study, the EDE-Q questionnaire proved to be more specific than the SF-36 questionnaire for determining the severity of the stage of an ED and the consequences that these disorders can contribute to the quality of life of patients (Engel et al. 2006). The EDE-Q questionnaire provides an opportunity for clinicians and researchers treating EDs to assess the degree of reduced quality of life since the questionnaire is designed to address the issues and concerns of people with EDs, and it can be very useful in clinical research to assess treatment outcomes (Figs. 3, 4, 5, and 6). New discoveries are made as the search for highly specialized and sensitive questionnaires continues. Several instruments and questionnaires were used to obtain a final result in several studies investigating the association between the intensity of symptoms induced by EDs and quality of life. What led researchers and scientists to this approach is that a substantial percentage of patients with EDs suffer from other mental disorders in addition to EDs, most often anxiety disorders, mood disorders, depression, and others. A study conducted in 2014 looked at the

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Fig. 2 Eating Disorder Examination-Questionnaire EDE-Q. An example of questionnaire (EDE-Q) (Rø et al. 2015)

quality of life of a large group of people with EDs and discovered potential predictors of quality of life. The Eating Disorder Examination-Questionnaire (EDE-Q), Short Form-12 Health Status Questionnaire (SF-12), the Weissman Social Adjustment Scale, and the Beck Depression Inventory (BDI) were the four types of questionnaires that were utilized in this study (Bamford et al. 2015).

Short Form-12 Health Status Questionnaire (SF-12) The Short Form-12 Health Status Questionnaire (SF-12) (Ware Jr et al. 1996) is a standardized measure that assesses the respondents’ physical and psychological well-being. It is made up of 12 questions separated into two parts: the Physical Component Summary Scale (PCS) and the Mental Component Summary Scale (MCS). The physical component of the health condition questions assesses if the patient’s physical health limits his daily physical activities, as well as his ability to function in society and whether it impacts his productivity at work and in other activities. The mental component of the questionnaire includes questions that examine how an individual’s mental and emotional health affects social functioning and productivity at work, as well as how nervous, sad, or lethargic they are.

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ANOREXIA NERVOSA

UNSPECIFIED FEEDING OR EATING DISORDER

BULIMIA NERVOSA

EATING DISORDERS AVOIDANT/ RESTRICTIVE FOOD INTAKE DISORDER

BINGE EATING DISORDER OTHER SPECIFIED FEEDING AND EATING DISORDERS

Fig. 3 Eating disorders

Weissman Scale of Social Adjustment The Weissman Social Adjustment Scale (Weissman and Bothwell 1976) assesses an individual’s social adjustment in a number of different areas of functioning, including marital, family, work, and leisure. The Weissman scale is a five-item selfassessment measure that assesses the extent to which physical or mental disorders have affected an individual’s work, social and leisure activities, interpersonal relationships, and home management skills. Each item is scored on a scale of 5 points with higher grades, which indicates poorer functioning. The reliability and validity of the questionnaire was well established and used in a wide range of populations.

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THE SHORT FORM-36 EATING DISORDER EXAMINATIONQUESTIONNAIRE SHORT FORM-12 HEALTH STATUS QUESTIONNAIRE WEISSMAN SCALE OF SOCIAL ADJUSTMENT BECK DEPRESSION INVENTORY EATING ATTITUDES TEST THE EATING DISORDER DIAGNOSTIC SCALE

HEALTH-RELATED QUALITY OF LIFE IN EDSHORT FORM THE HOSPITAL ANXIETY AND DEPRESSION SCALE

Fig. 4 Questionnaires that are used today

BDI The BDI (Beck 1981) is a 21-question self-assessment questionnaire designed to assess depressive symptoms. Higher overall scores reflect greater depressive symptomatology. More research into questionnaires for the discovery and prognosis of EDs, as well as the assessment of these patients’ quality of life, leads to the development of new, more specific, and sensitive instruments. Eating Attitudes Test (EAT-26) (Garner et al. 1982) evaluates behavioral and cognitive characteristics of patients with EDs. It comprises of 26 questions divided into three categories: diet, bulimia, and food worries and oral control. The result of the questionnaire might range from 0 to 76. The existence of actions or thoughts typical of people with an ED is indicated by a score of more than 20.

The Eating Disorder Diagnostic Scale (EDDS) The Eating Disorder Diagnostic Scale (EDDS) (Castro et al. 1991) consists of 22 questions that assess the DSM-IV diagnostic criteria for anorexia, bulimia, and

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COGNITION

BEHAVIOUR

EMOTIONS

NUTRITIONAL INTERVENTIONS

BODY IMAGE

SELF-ESTEEM & SELF WORTH

LIFESTYLE

Fig. 5 Aspects affected by EDs

Fig. 6 Eating disorders and co-occurring mental illness (Bould et al. 2014)

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binge-eating disorder. The answers can be used to make a DSM-IV diagnosis of these three disorders. There are both closed and open questions (e.g., questions about height, weight, use of contraceptive pills, etc.). This questionnaire’s benefit is that it has been demonstrated to be trustworthy and valid in a population that includes both adolescents and adults (Stice et al. 2000).

Health-Related Quality of Life in ED-Short Form (HeRQoLED-S) HeRQoLED-s (Las Hayas et al. 2010) has 20 items that are divided into two categories: social maladaptation and mental health and functioning. The higher the result of the questionnaire, the lower the quality of life related to the health condition. The above questionnaires (Eating Attitudes Scale (EAT-26), the Eating Disorder Diagnostic Scale (EDDS), HeRQoLED-s, and the Short Form-12 Health Status Questionnaire (SF-12) described earlier in the text with the Hospital Anxiety and Depression Scale (HADS) were used in a study conducted in 2017, which looked for predictors of quality of life in patients with EDs (Martín et al. 2017). The anxiety and depression scale was employed in the study to detect anxiety and depression symptoms in ED patients in earlier stages. The Hospital Anxiety and Depression Scale (HADS) (Zigmond and Snaith 1983) is a 14-item questionnaire that is used to test for anxiety and depression in the nonpsychiatric population (those who haven’t been diagnosed with a mental illness). It’s divided into two subscales. An absence of anxiety or depression symptoms is indicated by a score of 0 to 7 on any subscale, a score of 8 to 10 indicates a likely case of anxiety or depressive symptoms, and a score of 11 or higher indicates the presence of anxiety or depressive symptoms. Further research suggests that different types of EDs cannot be defined using generic QoL questionnaires like the SF-36 and that ED-specific QOL questionnaires should be used in clinical trials to help clinicians identify behavioral patterns that are common in diseases that meet the definition of EDs. The most recent questionnaires specific to the quality of life of a patient with an ED are the Eating Disorders Quality of Life Scale (EDQLS) and the Eating Disorders Quality of Life Scale (EDQOL). The Eating Disorder Quality of Life Scale (EDQOL) has 25 items and four subscales: psychological, physical/cognitive, financial, and school/work. The EDQLS (Adair et al. 2007) is a 40-item questionnaire that assesses 12 aspects of disordered eating-related quality of life: cognitive, educational/vocational, family and close relationships, interpersonal relationships, future outlook, appearance, leisure, psychological, emotional, values and beliefs, physical, and eating. On a 5-point scale, items are scored from (Orley et al. 1998) strongly disagree to (Bamford et al. 2015) strongly agree. Higher ratings imply a better quality of life. Before we move on to the conclusion, there is one more point to consider when assessing the quality of life of individuals with EDs. Patients were evaluated by

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several specialists in most studies that evaluated the quality of life of patients with an ED prior to the beginning of the research. All patients must undergo a comprehensive physical examination, which involves determining body weight, height, and BMI, as well as discovering any organic chronic diseases such as diabetes, hypertension, obesity, heart diseases, lung diseases, and others. In order to diagnose psychiatric comorbidities such as mood disorders, anxiety disorders, substance addiction disorders, psychotic disorders, and others, a complete psychiatric assessment is also required.

Conclusion There has been great progress in evaluating and designing appropriate questionnaires to help clinicians and researchers in the diagnosing, developing treatment strategies, and prognosing EDs, as well as assessing quality of life in these patients. What emerges in most studies and research is the knowledge that the combination of several questionnaires at the same time is the best choice for detecting and preventing impairment in quality of life in patients with EDs, as well as considering predictive factors related to quality of life. It is important to emphasize that the simultaneous occurrence of other mental illnesses, such as depression and anxiety, is very common and that instruments that help in the early detection of these accompanying disorders must be implemented in the examination.

Mini-Dictionary of Terms • QOL – An individual’s perception of their position in life in the context of the culture and value system in which they live and in relation to their goals, expectations, standards, and concerns. • Questionnaire – A list of questions, usually printed, submitted for replies that can be analyzed for usable information. • Impairment – The state of being diminished, weakened, or damaged, especially mentally or physically. • Instrument – A device for measuring the present value of a quantity under observation. • DSM-IV – A publication by the American Psychiatric Association for the classification of mental disorders using a common language and standard criteria. • Mental disorders – Conditions that affect your thinking, feeling, mood, and behavior. They may be occasional or long-lasting (chronic). • Predictive factor – As any patient characteristic that is predictive of the patient’s response (outcome) to a specified treatment.

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Key Fact of Health-Related Quality of Life Questionnaires: Applications to EDs • Quality of life expresses the broad range of changes in a person’s life as a result of an eating problem; it defines as an individual’s perception of their position in life in the context of the culture and value system in which they live and in relation to their goals, expectations, standards, and concerns. • Questionnaire: A research instrument consisting of a series of questions (or other types of prompts) for the purpose of gathering information from respondents through survey or statistical study. • Evaluation of questionnaires is conducted through many of clinical research and studies in order to find the most suitable questionnaire that could help the clinicians and researchers in future treatment of EDs. • Mental comorbidity is the presence of one or more additional mental conditions co-occurring with a primary condition – ED. Comorbidities are often coexistent with each other. • Instrument represents a tool, often in the form of questionnaire, that is used to aid in diagnosing a variety of symptoms through the questions.

Summary Points • People with EDs are impacted in a variety of ways by a variety of disciplines. There has been a growing interest in identifying appropriate questions to help detect and measure the severity of EDs, as well as questionnaires to assess the quality of life of these patients, throughout the previous several decades. • The Short Form-36 (SF-36) and the Eating Disorder Examination-Questionnaire were among the first questionnaires used in practice to assess the QOL of patients with an ED (EDE-Q). • Significant progress has been made in analyzing and constructing relevant questionnaires to assist clinicians and researchers in diagnosing, developing treatment strategies, and prognosing EDs. • The best method for diagnosing and avoiding deterioration in quality of life in patients with EDs is to use a combination of many surveys at the same time. • It’s crucial to think about the factors that influence the outcome.

References Adair CE, Marcoux GC, Cram BS, Ewashen CJ, Chafe J, Cassin SE et al (2007) Development and multi-site validation of a new condition-specific quality of life measure for eating disorders. Health Qual Life Outcomes 5:23

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Bamford B, Barras C, Sly R, Stiles-Shields C, Touyz S, le Grange D et al (2015) Eating disorder symptoms and quality of life: where should clinicians place their focus in severe and enduring anorexia nervosa?: quality of life and BMI. Int J Eat Disord 48(1):133–138 Beck A (1981) Beck depression inventory. Psychological Corporation, San Antonia Bould H et al (2014) Parental mental illness and eating disorders in offspring. Int J Eat Disord 48(4): 383–391 Castro J, Toro J, Salamero M, Guimera E (1991) The eating attitudes test: validation of the Spanish version. Psychol Assess 7:175–190 Engel SG, Wittrock DA, Crosby RD, Wonderlich SA, Mitchell JE, Kolotkin RL (2006) Development and psychometric validation of an eating disorder-specific health-related quality of life instrument. Int J Eat Disord 39(1):62–71 Fairburn CG, Wilson GT (1993) Binge eating: nature, assessment and treatment. Guilford Press, New York Garner DM, Olmsted MP, Bohr Y, Garfinkel PE (1982) The eating attitudes test: psychometric features and clinical correlates. Psychol Med 12:871–878 Las Hayas C, Quintana JM, Padierna JA, Bilbao A, Munoz P (2010) Use of rasch methodology to develop a short version of the health related quality of life for eating disorders questionnaire: a prospective study. Health Qual Life Outcomes 8:29 Martín J, Padierna A, Loroño A, Muñoz P, Quintana JM (2017) Predictors of quality of life in patients with eating disorders. Eur Psychiatry 45:182–189 Orley J, Saxena S, Herman H (1998) Quality of life and mental illness. Reflections from the perspective of the WHOQOL. Br J Psychiatry 172:291–293 Rø Ø, Reas DL, Stedal K (2015) Eating Disorder Examination Questionnaire (EDE-Q) in Norwegian adults: discrimination between female controls and eating disorder patients. Eur Eat Disord Rev 23(5):408–412 Stice E, Telch CF, Rizvi SL (2000) A psychometric evaluation of the eating disorder diagnostic screen: a brief self-report measure for anorexia, bulimia and binge eating disorder. Psychol Assess 12:123–131 Ware JE, Gandek B (1998) Overview of the SF-36 health survey and the International Quality of Life Assessment (IQOLA) project. J Clin Epidemiol 51(11):903–912 Ware JE Jr, Kosinski M, Keller SD (1996) A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care 34:220–233 Ware JEJ, Snow KK, Kosinski MA, Gandek B (1993) SF-36 health survey, manual and interpretation guide. The Health Institute, New England Medical Center, Boston Weissman MM, Bothwell S (1976) Assessment of social adjustment by patient self-report. Arch Gen Psychiatry 33:1111 Zigmond AS, Snaith RP (1983) The hospital anxiety and depression scale. Acta Psychiatr Scand 67: 361–370

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Resources in Eating Disorders Rajkumar Rajendram, Daniel Gyamfi, Vinood B. Patel, and Victor R. Preedy

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Other Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributions to the Development of This Resource . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Eating disorders are characterized by abnormal eating behavior which may also be associated with a preoccupation with body shape, size, and weight. They cause significant morbidity and mortality. Of all mental disorders, the mortality rate of anorexia nervosa is among the highest. In 1992, The World Health Organization (WHO) published the tenth revision of the International Classification of Diseases and Related Health Problems (ICD; ICD-10. The guidelines on eating disorders in the ICD-10 had several limitations. In 2022, the 11th revision (ICD-11) was R. Rajendram (*) College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia Department of Medicine, King Abdulaziz Medical City, King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia e-mail: [email protected] D. Gyamfi The Doctors Laboratory Ltd, London, UK V. B. Patel School of Life Sciences, University of Westminster, London, UK e-mail: [email protected] V. R. Preedy Faculty of Life Science and Medicine, School of Life Course and Population Sciences, King’s College London, Franklin-Wilkins Building, London, UK © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4_91

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officially released. Many changes had been made in an attempt to rectify these shortcomings. During the intervening 30 years between the release of ICD-10 and ICD-11, the literature on eating disorders and the evidence to inform clinical practice advanced greatly and eating disorders are still actively being studied. Thus, the knowledge and understanding of eating disorders has progressed rapidly in recent years. However, keeping abreast of current research can be difficult so we have compiled tables of the resources recommended by active practitioners and researchers. These include information on regulatory bodies, societies, organizations, and other resources. Keywords

Books · Evidence · Professional societies · Regulatory bodies Abbreviations

DSM ICD ICD-10 ICD-11 WHO

Diagnostic and Statistical Manual of Mental Disorders International Classification of Diseases and Related Health Problems Tenth revision of the ICD 11th revision of the ICD World Health Organization

Introduction Eating disorders are characterized by abnormalities of eating behavior (World Health Organization (WHO) 2022). They may also be associated with a preoccupation with body shape, size, and weight. Examples of eating disorders include binge eating, bulimia, and anorexia nervosa. Eating disorders cause significant morbidity and mortality (Arcelus et al. 2011; Field et al. 2012). Those suffering from eating disorders are at increased risk of death by suicide (Arcelus et al. 2011). Indeed, of all mental disorders, mortality rate of anorexia nervosa is among the highest (Zerwas et al. 2015). The World Health Organization (WHO) published the tenth revision of the International Classification of Diseases and Related Health Problems (ICD; ICD10) in 1992 (WHO 1992). There were several inherent limitations with the guidelines on eating disorders in this version of the ICD (Claudino et al. 2019). However, there are other classifications such as the Diagnostic and Statistical Manual of Mental Disorders (DSM; American Psychiatric Association 2013), and indeed, classifications can change in the light of ongoing scientific dialogue (Rajendram et al. 2022). The management of a mental health disorder is often defined by its classification. Thus, the development of more accurate, clinically relevant tools to classify, identify, prevent, and treat eating disorders is an important public health priority (Claudino et al. 2019).

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In 2022, the 11th revision (ICD-11) was officially released and is available online at https://icd.who.int/browse11/l-m/en (WHO 2022). Many changes were made in an attempt to rectify the shortcomings of the ICD-10 with respect to eating disorders (Claudino et al. 2019). During the intervening 30 years between the release of ICD-10 and ICD-11, the literature on eating disorders and the evidence to inform clinical practice advanced greatly (Claudino et al. 2019). Several areas are covered in Patel and Preedy (2023), but eating disorders are still actively being studied. As we often highlight, even the most experienced researchers and clinicians struggle to stay up-to-date, and some new researchers need some guidance on what online resources they should use. We have therefore produced tables containing resources as recommended by active researchers and practitioners, which draws upon their wealth of experience and acumen acquired over many years. The list below acknowledges all the experts who helped to prepare these valuable resources.

Resources Tables 1, 2, 3, 4, and 5 list the most up-to-date information on the regulatory bodies (Table 1), professional societies (Table 2), books (Table 3), and other resources of interest (Table 4) that are relevant to an evidence-based approach to eating disorders. Some organizations are listed in more than one table as they occasionally fulfill multiple roles.

Other Resources The Wellcome Collection (https://wellcomecollection.org/collections) and The British Library (https://www.bl.uk/) also list material on topics related to eating disorders. Other chapters on resources relevant to nutrition (recommended by authors and practitioners) may also be relevant to eating disorders. These include diet quality (Rajendram et al. 2013a) nutrition and oxidative stress (Rajendram et al. 2020), maternal nutrition (Rajendram et al. 2017), nutrition and the menopause (Rajendram et al. 2013b), biomarkers of nutrition (Rajendram et al. 2022) glutamine (Rajendram et al. 2014), branched chain amino acids (Rajendram et al. 2015), famine, starvation, and nutrient deprivation (Rajendram et al. 2019a), aging (Rajendram et al. 2019b), diet and nutrition in critical care (Alzaid et al. 2015), and the metabolism and physiology of bariatric surgery (Rajendram et al. 2016). Other chapters on resources relevant to mental health (recommended by authors and practitioners) may also be relevant to eating disorders. These include cognitive behavioral therapy (Rajendram et al. 2022), post-traumatic stress disorder (Rajendram et al. 2015), and substance misuse (Rajendram and Preedy 2016a, b, c). This list of material in these tables is included to provide general information only. It does not constitute any recommendation or endorsement of the activities of

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Table 1 Regulatory bodies or organizations dealing with eating disorders Regulatory body or organization Academy for Eating Disorders (AED) Academy of Nutrition and Dietetics Australia & New Zealand Academy for Eating Disorders Body Dysmorphic Disorder Foundation Body Positive Butterfly Foundation Centre for Eating Disorders Management, Inc. (CEDM) Centre for Research on Eating Disorders at Oxford (CREDO) Centre of Excellence in Eating Disorders (CEED) Centre of Mindful Eating Eating Disorder Hope Eating Disorder Resource Centre (EDRC) Eating Disorders Anonymous Eating Disorders Coalition (EDC) Eating Disorders Families Australia Foundation for Prader-Willi Syndrome Research (FPWR) International Eating Disorder Action (IEDaction) International Eating Disorders Action International OCD Foundation International Prader-Willi Syndrome Organization (IPWSO) Mental Health Europe National Alliance for Eating Disorders National Alliance on Mental Illness National Centre of Excellence for Eating Disorders (NCEED) National Eating Disorder Collaboration (NEDC) National Eating Disorder Information Centre (NEDIC)

Web address https://www.aedweb.org/home https://www.eatright.org/ www.anzaed.org.au https://bddfoundation.org/ https://thebodypositive.org/ https://butterfly.org.au/ https://cedm-inc.com/ https://www.credo-oxford.com/index.html#topic0 https://ceed.org.au/ https://www.thecenterformindfuleating.org https://www.eatingdisorderhope.com/ https://edrcsv.org/ https://eatingdisordersanonymous.org/ http://www.eatingdisorderscoalition.org/ www.edfa.org.au https://www.fpwr.org/ https://www.facebook.com/IEDaction.Global/ http://internationaleatingdisorderadvocacy.blogspot.com https://bdd.iocdf.org/ https://ipwso.org/ https://www.mhe-sme.org/ https://www.allianceforeatingdisorders.com/ https://www.nami.org/home https://www.nceedus.org/ https://nedc.com.au/ https://nedic.ca/ (continued)

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Table 1 (continued) Regulatory body or organization National Institute of Mental Health (NIMH) Parents to Parents

Web address https://www.nih.gov/about-nih/what-we-do/nihalmanac/national-institute-mental-health-nimh http://www.parents-to-parents.org/

This table lists the regulatory bodies and organizations involved with eating disorders. The links were accurate at the time of going to press but may move or alter. In these cases, the use of the “Search” tabs should be explored at the parent address or site. In some cases, links direct the reader to pages related to eating disorders within parent sites. Some societies and organizations have a preference for shortened terms, such as acronyms and abbreviations. See also Table 2

Table 2 Professional societies relevant to eating disorders Society name American Psychiatric Association American Society for Nutrition Anorexia-Bulimia Association Austrian Society for Eating Disorders (ASED) Bulimia Anorexia Nervosa Association (BANA) Deutsche Gesellschaft für Essstörungen (German Eating Disorders Society) Eating Disorders Association of Canada Eating Disorders Research Society (EDRS) European Psychiatric Association European Psychiatric Association (EPA) Frisk & Fri (Healthy & Free – The Swedish Association against Eating Disorders) International Association of Eating Disorders Professionals Italian Association for Eating and Weight Disorders Italian Society of Food Psychopathology Multi-Service Eating Disorders Association (MEDA) National Association for Males with Eating Disorders National Association of Anorexia Nervosa and Associated Disorders, Inc. (ANAD) National Association of Eating Disorders (Italy) National Eating Disorders Association (NEDA) Society of Biological Psychiatry (SOBP)

Web address https://www.psychiatry.org/ https://nutrition.org/ http://aabaphila.org/ https://www.oeges.or.at/ https://bana.ca/ https://www.dgess.de/ https://edac-atac.com/ https://edresearchsociety.org/ https://www.europsy.net https://www.europsy.net/ https://www.friskfri.se/ http://www.iaedp.com/ https://www.aidap.org/ https://psicopatologiaalimentazione. it/la-sipa/chi-siamo/ https://www.medainc.org/ https://www.nationaleatingdisorders. org/named-merger http://www.anad.org/ http://www.consultanoidca.it https://www.nationaleatingdisorders. org/ https://sobp.org/

This table lists the professional societies involved with eating disorders. The links were accurate at the time of going to press but may move or alter. In these cases, the use of the “Search” tabs should be explored at the parent address or site. In some cases, links direct the reader to pages related to eating disorders within parent sites. Some societies and organizations have a preference for shortened terms, such as acronyms and abbreviations. See also Table 1

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Table 3 Books on eating disorders Book title Adonis Complex: How to Identify, Treat and Prevent Body Obsession in Men and Boys AED Report 2021 4th Edition Eating Disorders: A Guide to Medical Care Animal Models of Eating Disorders (1st edn)

Year of publication 2002

Authors or editors Pope HG, Phillips KA, Olivardia R

Publisher The Free Press

Academy for Eating Disorders’ Medical Care Standards Committee Avena NM

AED Report

2021

2011

2021 2020

Animal Models of Eating Disorders (2nd edn)

Avena NM

Anorexia and Other Eating Disorders Binge Eating: The Ultimate Guide to Finally Ending Emotional Eating, Bingeing, Overeating, and Food Addiction, Including Tips on Eating Disorder Recovery, and an Introduction to Mindful Eating Body Dysmorphic Disorder: A Treatment Manual Body Dysmorphic Disorder: Advances in Research and Clinical Practice Cassidy and Allanson’s Management of Genetic Syndromes Clinical Guide to Fertility, Motherhood, and Eating Disorders Cognitive Behavior Therapy and Eating Disorders Cognitive Behavior Therapy for Adolescents with Eating Disorders Cognitive-Behavioral Therapy for Body Dysmorphic Disorder: A Treatment Manual Dialectical Behavior Therapy for Binge Eating and Bulimia Eating Disorders

Musby E McClain D

Humana Press, Totowa, NJ Humana Press, New York, NY Booktopia Primasta

Veale D, Neziroglu F

Wiley

2013

Phillips KA

Oxford University Press WileyBlackwell Routledge

2017

Eating Disorders and Obesity (3rd edn) Eating Disorders and Obesity in Children and Adolescents

Carey JC, Cassidy SB, Battaglia A, Viskochil D Daigle K Fairburn C Dalle Grave R, Calugi S Wilhelm S, Phillips KA, Steketee G Safer DL, Telch, CF, Chen EY Keel PK

Brownell KD, Walsh BT Hebebrand J, HerpertzDahlmann B

Guilford Press Guildford Press Guilford Press Guilford Press Oxford University Press Guilford Press Elsevier

2021

2021 2019 2008 2020 2013

2009 2016

2017 2019 (continued)

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Table 3 (continued) Book title Eating Disorders in Boys and Men Eating Disorders in Sport Eating Disorders Sourcebook: A Comprehensive Guide to the Causes, Treatments, and Prevention of Eating Disorders Eating Disorders: Obesity, Anorexia Nervosa, and the Person Within Emotion Regulation for Young People with Eating Disorders: A Guide for Professionals Help Your Teenager Beat an Eating Disorder Hidden and Lesser-known Disordered Eating Behaviors in Medical and Psychiatric Conditions How to Nourish Your Child Through an Eating Disorder Inside Scoop on Eating Disorder Recovery Intuitive Eating: A Revolutionary Anti-Diet Approach Management of Prader-Willi Syndrome Overcoming Bulimia Nervosa and Binge Eating (3rd edn) Oxford Handbook of Eating Disorders (2nd edn)

Authors or editors Nagata JM, Brown TA, Murray SB, Lavender JM Thompson R, Sherman R Costin C

Bruch H

Nesbitt S, Giombini L

Lock J, LeGrange D

Year of publication 2021

Routledge McGrawHill

2010 2006

Routledge and Kegan Paul Routledge

1974

2022

Manzato E, Cuzzolaro M, Donini LM

Guilford Press Springer Nature

Crosbie C

Booktopia

2009

Reichmann C, Rollin J

Routledge

2021

Tribole E, Resch E

Essentials

2020

Butler MG, Lee PDK, Whitman BY Cooper P

Springer

2006

Robinson

2009

Oxford University Press Nova Springer Koudansha Cambridge University Press John HernandezStorr Oxford University Press Springer

2018

Agras WS, Robinson A

Prader-Willi Syndrome Prader-Willi Syndrome Prader-Willi Syndrome (Japanese) Prader-Willi Syndrome: Development and Manifestations

Hoybye C Cassidy SB Hasegawa T Whittington J, Holland T

Prader-Willi Syndrome: How Parents and Professionals Struggled and Coped and Made Genetic History The Void Inside: Bringing Purging Disorder to Light

Hernandez-Storr J

Trauma-Informed Approaches to Eating Disorders

Publisher Springer

Keel PK

Seubert A, Virdi P

2015 2022

2013 1992 2009 2011

2016

2020

2018 (continued)

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Table 3 (continued) Book title What Causes Eating Disorders – And What Do They Cause? Wiley Handbook of Eating Disorders, Assessment, Prevention, Treatment, Policy, and Future Directions Your Dieting Daughter: Antidotes Parents Can Provide for Body Dissatisfaction, Excessive Dieting, and Disordered Eating

Authors or editors Frank GKW Smolak L, Levine MP

Publisher Booklocker. com, Inc. Wiley

Costin C

Routledge

Year of publication 2016 2015

2013/2021

This table lists books relevant to eating disorders

these sites, facilities, or other resources listed in this chapter, by the authors or editors of this book.

Summary Points Eating disorders are characterized by abnormalities of eating behavior. In 2022, the 11th revision of the International Classification of Diseases (ICD-11) was officially released and is available online at https://icd.who.int/browse11/ l-m/en. In the 30 years between ICD-10 and ICD-11, the literature on eating disorders and the evidence to inform clinical practice advanced greatly. Eating disorders are actively being studied. This chapter lists the most up-to-date resources relevant to eating disorders.

Contributions to the Development of This Resource The following authors made valuable contributions to the development of this resource. We apologize if some of the suggested material was not included in this chapter or has been moved to different sections. Ali, Sarrah; Desousa, Avinash; Goldfield, Gary; Howard, Lindsay; Jahrami, Haitham; Karia, Sagar; Keel, Pamela; Malcolm, Amy; Memedi, Imran; Morganti, Wanda; Motwani, Shorouq; Muzi, Stefania; Nuhii, Nexhibe; Pace, Cecilia Serena; Papežová, Hana; Phillipou, Andrea; Procházková, Petra; Quadflieg, Norbert; Richson, Brianne; Roubalová, Radka; Saif, Zahra; Stankovska, Gordana; Strahler, Jana; Wentz, Elisabet; Wons, Olivia; and Yamada, Kenichi.

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Table 4 Other resources of interest or relevance for health care professionals or patients related to eating disorders Name of resource or organization Academy of Nutrition and Dietetics Active Minds AED’s “9 Truths About Eating Disorders” AED’s “Eating Disorders: A Guide to Medical Care” Anorexia – Parents to Parents Anorexia Nervosa Inventory for Self-Rating (ANIS)

Assessment tools Italian versions Disordered Eating Attitude Scale (DEAS) DSM-5 Feeding and Eating Disorders

e-CBT: Digital Treatment for Eating Disorders Eating Disorder Diagnostic Scale (EDDS) Eating Disorder Examination Questionnaire (EDE-Q) Eating Disorder Screening Tools

Eating Disorders – National Alliance on Mental Illness Eating Disorders Examination Interview Eating Disorders: About More Than Food – NIH Healthy and Free (In Czech with English Translation) ESPEN Guidelines for Nutrition Screening 2002 List of Organizations Worldwide Masters in treatments for Eating Disorders (English) Masters in treatments for Eating Disorders (Italian)

Web address https://jandonline.org/article/S2212-2672(20) 30904-7/fulltext https://www.activeminds.org/ https://www.aedweb.org/publications/ninetruths https://www.aedweb.org/publications/ medical-care-standards http://www.parents-to-parents.org/ https://www.lmu-klinikum.de/psychiatrieund-psychotherapie/forschung-research/ working-groups/epidemiology-andevaluation/anis/98aedba0af1c9bf8 http://www.dallegrave.it/category/misure-diassessment/ https://www.midss.org/content/disorderedeating-attitude-scale-deas https://higherlogicdownload.s3.amazonaws. com/AEDWEB/27a3b69a-8aae-45b2-a04c2a078d02145d/UploadedImages/Learn/ DSM5September2016Final.pdf https://www.credo-oxford.com/5.1.html https://qxmd.com/calculate/calculator_562/ eating-disorder-diagnostic-scale-edds https://www.corc.uk.net/outcomeexperience-measures/eating-disorderexamination-questionnaire-ede-q/ https://www.therecoveryvillage.com/mentalhealth/eating-disorders/related/screeningtools/ https://www.nami.org/About-Mental-Illness/ Mental-Health-Conditions/Eating-Disorders https://www.cbte.co/for-professionals/ measures/ https://www.nimh.nih.gov/health/ publications/eating-disorders http://www.healthyandfree.cz/ https://espen.info/documents/screening.pdf https://www.worldeatingdisordersday.org/ get-involved/participating-organisations/ https://www.credo-oxford.com/index. html#topic5 http://www.dallegrave.it/category/corsi/ master/ (continued)

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Table 4 (continued) Name of resource or organization Mindful Eating Resources Munich Eating Disorders Questionnaire (Munich ED-Quest)

National Institute for Health and Care Excellence Guidelines for Eating Disorders: Recognition and Treatment NICE Clinical Guidelines for Obsessive Compulsive and Body Dysmorphic Disorder NSW Eating Disorders Toolkit

Project Heal Questionnaire on Eating and Weight Patterns-5 (Italian version) Recovery Record Resources and links – Centre of Excellence in Eating Disorders (CEED) Screening for Mental Health, Inc. Structured Inventory for Anorexic and Bulimic Eating Disorders (SIAB-EX and SIAB-S)

The SCOFF Questionnaire Screens for Eating Disorders The Yale-Brown Obsessive-Compulsive Scale Modified for Body Dysmorphic Disorder (BDD-YBOCS; used to assess BDD symptom severity) UNICEF Nutrition World Eating Disorders Action Day Worldwide List of Eating Disorders Advocacy Organizations

Web address https://www.thecenterformindfuleating.org/ Mindful-Eating-Resources https://www.lmu-klinikum.de/psychiatrieund-psychotherapie/forschung-research/ working-groups/epidemiology-andevaluation/munich-ed-quest/ 7c7bbcfc393d516d https://www.nice.org.uk/guidance/ng69

https://www.nice.org.uk/guidance/cg31 https://www.health.nsw.gov.au/mentalhealth/ resources/Publications/nsw-eating-disorderstoolkit.pdf https://www.theprojectheal.org/ http://www.dallegrave.it/wp-content/uploads/ 2015/04/QEWP-5-Verisione-Italiana.pdf https://www.recoveryrecord.com/ https://ceed.org.au/resources-and-links/ https://philanthropynewsdigest.org/npospotlight/screening-for-mental-health-inc https://www.lmu-klinikum.de/psychiatrieund-psychotherapie/forschung-research/ working-groups/epidemiology-andevaluation/siab-ex-and-siab-s/ 43c8f5577c4c0c68 https://www.verywellmind.com/the-scoffquestionnaire-1138316 https://pubmed.ncbi.nlm.nih.gov/9133747/

https://www.unicef.org/nutrition http://www.worldeatingdisordersday.org/ https://www.feast-ed.org/worldwide-list-ofed-advocacy-organizations/

This table lists other resources of interest or relevance to eating disorders. Please note, occasionally the location of the websites or web address changes

References American Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders, 5th edn. American Psychiatric Association, Washington, DC Arcelus J, Mitchell AJ, Wales J, Nielsen S (2011) Mortality rates in patients with anorexia nervosa and other eating disorders: a meta-analysis of 36 studies. Arch Gen Psychiatry 68(7):724–731

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Alzaid F, Rajendram R, Patel VB, Preedy VR (2015) Expanding the knowledge base in Diet, Nutrition and Critical Care. Electronic and published resources. In Rajendram R, Preedy VR, Patel VB (Editors). Diet and Nutrition in Critical Care. Springer, Germany Claudino AM, Pike KM, Hay P et al (2019) The classification of feeding and eating disorders in the ICD-11: results of a field study comparing proposed ICD-11 guidelines with existing ICD-10 guidelines. BMC Med 17(1):93 Field AE, Sonneville KR, Micali N, Crosby RD, Swanson SA, Laird NM, Treasure J, Solmi F, Horton NJ (2012) Prospective association of common eating disorders and adverse outcomes. Pediatrics 130(2):e289–e295 Patel VB, Preedy VR (eds) (2023) Eating disorders. Elsevier, New York. (In press) Rajendram R, Preedy VR (2016a) Recommended resources. In: Preedy VR (ed) Neuropathology of drug addictions and substance misuse, vol 1. Elsevier, New York Rajendram R, Preedy VR (2016b) Recommended resources. In: Preedy VR (ed) Neuropathology of drug addictions and substance misuse, vol 2. Elsevier, New York Rajendram R, Preedy VR (2016c) Recommended resources. In: Preedy VR (ed) Neuropathology of drug addictions and substance misuse, vol 3. Elsevier, New York Rajendram R, Rajendram R, Patel VB, Preedy VR (2013a) Diet quality: what more is there to know? In: Preedy VR, Hunter L-A, Patel VB (eds) Diet quality: an evidence-based approach. Springer, Heidelberg, pp 397–401 Rajendram R, Rajendram R, Patel VB, Preedy VR (2013b) Interlinking diet, nutrition, the menopause and recommended resources. In: Hollins-Martin CJ, Watson RR, Preedy VR (eds) Nutrition and diet in menopause. Springer, Heidelberg Rajendram R, Patel VB, Preedy VR (2014) Web based resources and suggested reading. In: Rajendram R, Patel VB, Preedy VR (eds) Glutamine in health and disease. Springer, New York, pp 527–532 Rajendram R, Patel VB, Preedy VR (2015) Web based resources and suggested reading. In: Rajendram R, Patel VB, Preedy VR (eds) Branched chain amino acids in health and disease. Springer, New York Rajendram R, Martin CR, Preedy VR (2016) Recommended resources on metabolism and physiology of bariatric surgery. In: Rajendram R, Martin CR, Preedy VR (eds) Metabolism and physiology of bariatric surgery. Elsevier, London, pp 631–636 Rajendram R, Patel VB, Preedy VR (2017) Recommended resources on maternal nutrition. In: Rajendram R, Patel VB, Preedy VR (eds) Nutrition and diet in maternal diabetes. Springer, New York, pp 495–500 Rajendram R, Patel VB, Preedy VR (2019a) Resources in famine, starvation, and nutrient deprivation. In: Patel VB, Preedy VR (eds) Famine, starvation, and nutrient deprivation. Springer, New York, pp 2399–2406 Rajendram R, Patel VB, Preedy VR (2019b) Resources in diet, nutrition and epigenetics. In: Patel VB, Preedy VR (eds) Nutrition and epigenetics. Springer, New York, pp 2309–2314 Rajendram R, Patel VB, Preedy VR (2020) Recommended resources for nutrition, oxidative stress, and dietary antioxidants. In: Martin CR, Preedy VR (eds) Nutrition, oxidative stress, and dietary antioxidants. Elsevier, New York, pp 393–397 Rajendram R, Gyamfi D, Patel VB, Preedy VR (2022) Recommended resources for biomarkers of nutrition. In: Preedy VR, Patel VB (eds) Biomarkers of nutrition. Elsevier, New York (In press) World Health Organization (1992) The ICD-10 classification of mental and behavioural disorders: clinical descriptions and diagnostic guidelines. World Health Organization, Geneva World Health Organization (2022) Feeding or eating disorders. In: ICD-11 for mortality and morbidity statistics (version 02/2022). https://icd.who.int/browse11/l-m/en#/http://id.who.int/ icd/entity/1412387537. Accessed 4 May 2022 Zerwas S, Larsen JT, Petersen L, Thornton LM, Mortensen PB, Bulik CM (2015) The incidence of eating disorders in a Danish register study: associations with suicide risk and mortality. J Psychiatr Res 65:16–22

Index

A A1 allele, 228 AA-derived eiCs pathways, 455 Academy for Eating Disorders, 274 Accelerometers, 426 Acceptance and Commitment Therapy (ACT), 340, 375, 380 Acculturation, 216 Acid-base balance, 532 Activity-based anorexia (ABA), 558, 559 model, 459 Activity-based rodent model of anorexia (ABA), 547 Acute insomnia, 147 Acute sleep deprivation, 1106 Acylghrelin (AG), 571 Adaptive physical activity, 415 Adaptive preoccupation, 1485 Adaptive response, 703, 704 Adolescent Binge Eating Scale, 1510 Adolescents, 866–868, 870, 874–876 with ADHD, 128, 130 Adrenal hormones, 557 Adrenocorticotropic hormone (ACTH), 54, 67, 85, 776 Adult Autism Subthreshold Spectrum (AdAS), 646 Adult picky eating questionnaire (APEQ), 1419 Adults, 314, 338–341, 345 Affect, 1007 regulation model, 808 Affectionless control, 968, 969, 971, 972, 974, 975 Agouti-related peptide (AgRP), 55, 67, 85, 571, 1470 Agouti-related protein, 543

© Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Eating Disorders, https://doi.org/10.1007/978-3-031-16691-4

Alcohol consumption, 1340 Alexithymia, 648, 649, 651 anorexia nervosa, 339 bulimia nervosa, 339 case-control studies findings, 322 cohort studies, 338, 339 future lines of research, 343 limitations, 343 longitudinal findings, 340, 341 longitudinal variation, 341 research findings, 316, 317 structure and rationale of the current review, 317, 322 synthesis of the previous reviews and meta-analyses, 318 therapeutic implications and applications, 342 types, 315, 316 Alexithymia Questionnaire for Children, 336, 344 Alpha-melanocyte-stimulating hormone (α-MSH), 505 Alpha-methylparatyrosine (AMPT), 563 Amenorrhea, 440, 925 functional hypothalamic, 605, 607 American Psychiatric Association (APA), 203, 206, 1064 γ-aminobutyric acid (GABA), 777 AMP-activated protein kinase (AMPK) signaling, 55, 67 Amphetamine-regulated transcript (CART), 544 Amygdala, 57 Anandamide (AEA), 84, 455 Androgen receptor (AR), 771, 778 Androgens, 770, 780, 836 Androstenedione, 771

1541

1542 Anemia, 929 in pregnancy, 611 Animal model, AN, 558–559 ANKK1 gene, 81 Ankyrin repeat, 78 Ankyrin repeat and kinase domain containing 1 (ANKK1), 81 Anorexia, 685, 686 disease model, 574 disorder, 683, 684 Anorexia nervosa (AN), 96, 99, 201, 202, 208, 250, 254, 256, 265, 270, 317, 323, 338–344, 397–399, 442, 556, 558–562, 624, 686–688, 692, 703, 752, 772, 816, 865, 925, 947, 1004, 1192, 1251, 1306, 1315–1317, 1319, 1320, 1332, 1343, 1365, 1366, 1483, 1530 acute stage of, 571 and adverse perinatal outcomes, 613 applications, 650, 651 attention-deficit/hyperactivity disorder, 130 BF estimation and measurement, 443–445 binge-eating episodes, 9 BMI determination, weight, height and standard for, 441 body composition, 443 characteristics, 571 clinical based studies, 678, 679 clinical implications, 680, 681 clinical study, 645 clinical traits, 648, 649 clinicians, 643 core eating-disorder maintenance processes, 9 depressive disorders, 681–683 development of, 504, 505 discharge and follow up, 635 epidemiology, 646 feeding and eating disorders, 642, 643 and fertility, 605 follow-up studies, 470 gestational, 29 Gothenburg AN study, 470 growth hormone resistance in, 705–709 gut microbiota, 491 hallmark of, 605 health policymakers, 643 hospitalization criteria, 625–626 insomnia disorder, 149 integrated treatment, 626–632 interventions, 650 knockout models for genes encoding, 459 malnutrition, 645

Index management of pregnant women with, 615 mental health comorbidities, 643, 644 motivation to treatment, 632 neurodegenerative findings, 476 neuropsychological impairments, 652 nutritional rehabilitation, 627–628 ominous variant of, 5 osteoporosis and restoration of BMD, 446–447 outcomes, 649, 650 outpatient CBT-E, 18 pathogenesis of, 453 population-based studies, 677, 678 and pregnancy complications, 610, 611 prevalence, 610, 643, 650 probiotics on, 502 psychiatric comorbidities, 650 psychiatric morbidity, 476 psychiatry, 646 psychodiagnostics, 646–648 psychological treatment, 630–631 psychology, 646 psychopathological features, 652 psychopathology, 633 psychopharmacological treatment, 631 quality of life, 634 refeeding process, 628–630 rehospitalization, 634–635 remission, recovery and risk of relapse, 446 renutrition, 632–633 reproductive health, 605 resumption of menses and reproductive functions, 446 starvation symptoms, 9 Sten Theander’s study, 470 theoretical implications, 679, 680 theories, 648, 649 transdiagnostic cognitive-behavioral theory, 9 treatments, 632–635, 649, 650 Anorexia nervosa, binge eating/purging subtype (AN-BP), 1175 Anorexia nervosa (AN), male application, 532 awareness, 531 course, 524 dietary intake, 517 dietitian, 525, 531 environmental (Societal & cultural) risk factors, 515, 516 features, 514 females, 518, 519 genetic factors, 515 hormonal factors, 515

Index medical complications, 522–524 parameters, 517 prevalence, 514, 533 prognosis, 524 psychiatric comorbidities, 518 risk factors, 517 treatment, 525–528 Anorexigenic peptides, 84 Antepartum haemorrhage, 618 Anthropometry, 440 Anti-androgens, 829 Antidepressants, 823, 824 Antiepileptics, 824, 827 Anti-inflammatory dietary pattern, 61 Antisaccade task, 591 Anxiety, 97, 542, 546, 1237, 1294, 1296, 1407 and bulimia nervosa, 733 Anxiety disorders (AD), 253, 643, 680, 684, 685, 688, 691 Anxiolytic medications, 665 Appearance preoccupation, 1307 Appetite, 539, 541, 543–545, 547, 548 regulatory system, 84 Arachidonic acid (AA), 61, 453 2-Arachidonoylglycerol (2-AG), 455 Arcuate nucleus (ARC), 543, 548 ARFID in children assessment, 1242 characteristics, 1237, 1238 cognitive-behavioral approaches, 1243, 1249 differential diagnosis, 1240, 1241 etiology, 1241, 1242 family-based treatment (FBT), 1243 hospital-based feeding programs, 1250 impact, 1239, 1240 parent-based treatments, 1249, 1250 pharmacotherapy, 1250 prevalence, 1238, 1239 treatment, 1243 Arginine-vasopressin (AVP), 1267, 1270 Assessment, 1126 Athlete anorexia nervosa in, 115 ATHLETE questionnaire, 118 binge eating disorder, 116 bulimia nervosa, 116 eating disorders not otherwise specified (EDNOS), 119 ED in female, 113 in male, 113, 115 prevalence studies, 113 risk factors, 113

1543 sports disciplines, 115 male runners obligatory runners, 115 nutrition and eating disorders, 113 orthorexia nervosa in, 116 Attachment style, 848–849 Attachment Styles Questionnaire Relationship, 1049 Attentional bias tasks, 596 Attention-deficit disorder (ADD), 1292 Attention-deficit/hyperactivity disorder (ADHD), 827, 1241 anorexia nervosa, 130 avoidant/restrictive food intake disorder (ARFID), 130 behavioral symptoms, 125 binge eating disorder, 129 body satisfaction and eating behaviors, 134 bulimia nervosa, 130 comorbidities, 126 diagnosis and etiology, 125 eating and weight-related problems, 130 eating patterns of children with, 127–129 ED applications, 138–139 in children and adolescents with, 131 clinical implications/clinical management, 137–138 environmental risk factors, 126 inattention features of, 133 management of, 126 vs. obesity, 128 prevalence, 125 vs. sleep disturbances, 134 Atypical anorexia, 250, 255, 258 Autism, 1273, 1276 Autism Diagnostic Observation Schedule-2nd Edition (ADOS-2), 646–651 Autism quotient (AQ) questionnaire, 646 Autism spectrum disorder (ASD), 475, 644, 645, 651, 1237, 1251 Autism spectrum quotient (AQ), 646, 651 Autonomic nervous system (ANS), 54, 67, 1382 Avoidant/restrictive food intake disorder (ARFID), 216, 279, 354, 404, 1332, 1367, 1368, 1418, 1421, 1455 ARFID in children (see ARFID in children) assessment tools, 1251 attention-deficit/hyperactivity disorder, 130 characteristics, 1251 clinical profiles, 1251 diagnosis, 1236 diagnostic criteria, 1236 early childhood, 1236

1544 Avoidant/restrictive food intake disorder (ARFID) (cont.) eating disorders, 1237 epidemiological research, 1252 family accommodation, 1252 feeding and eating disorder of infancy and early childhood, 1252 heterogeneity, 1251 infancy, 1236 psychosocial domain, 1251 quantity of foods, 1236 restricted eating, 1236 tertiary care, 1253 treatment approaches, 1251

B Balanced diet, 396 Barcelona Orthorexia Scale (BOS), 1444 Bariatric and metabolic surgery (BMS), 1084, 1095 definitions and indications of, 1087–1090 Bariatric surgery, 1084–1089, 1091–1097 Beck Depression Inventory (BDI), 1523 BED’s increased brain reaction to food imagery, 1074 Behavioral addiction, 1340–1346 Behavioral change, during pregnancy, 27 Behavioral interventions, 261, 262 Behavioral phenotype, 1288 Bermond-Vorst Alexithymia Questionnaire (BVAQ), 316, 329, 341 Binge eating (BE), 1004, 1016, 1086, 1504 LOC eating, 128 occurrence of, 1087 Binge eating disorder (BED), 96, 99, 206, 216, 226, 323, 338, 341, 389, 401–404, 749, 754, 816, 823, 947, 1044, 1086, 1090–1092, 1122, 1192, 1251, 1467, 1504, 1506, 1510 adulthood, 972 in athlete, 116 attachment liability, 960 attention-deficit/hyperactivity disorder, 129 behavioral and dietary reorganization, 1096–1098 BES, 1095 bulimia nervosa, 1064 CBT-E, 15 childhood, 974 chi-square test, 962 clinical functional imaging and cognitive studies, 1064

Index clinical implications, 970, 971 clinical interview, 1094 criterion B symptoms, 1125–1127, 1131, 1132 deficit attachment, 975 diagnosis and scales, 1505 diagnostic criteria, 1123, 1124 disgusted, 1130 during pregnancy, 30 eating disorders, 963, 965, 966 EDE-Q, 1094 embarrassment, 1129, 1130 epidemiology, 959 etiopathogenesis, 1064 expression, 969, 970 implications, 973, 974 insomnia disorder, 149 maternal and paternal parenting styles, 968, 969 medical and psychiatric comorbidities, 974 non-authoritative parenting styles, 975 non-pharmacological, 1132, 1133 neuroimaging findings, 1064 obesity, 963, 965, 966, 975 ODD ratio (OR), 964 overprotection, 962, 963, 967, 972 parenting characteristics, 961 parenting influence, 966, 968 parenting styles, 973 physical discomfort, 1128 physical hunger, 1129 prevalence, 958 prevalence of BED in bariatric patients, 1092–1093 prevalence studies, 1064 preventions issues, 972 primary care, 958 psychiatric classification systems, 1031 psychiatric disorders, 962, 963 psychoeducational efforts, 973 psychopathological aspects, 959 QEWP-5, 1095 recurrent binge-eating episodes, 1031 risk factors, 1504 self-administered questionnaires, 1094 self-monitoring instrument, 1094 treatment, 960, 963, 967, 971 voxel-based morphology of brain volume, 1065 Binge Eating Scale (BES), 1094, 1095, 1472, 1506–1507, 1510 ADO-BED, 1510 Arabic version, 1509

Index C-BEDS, 1509 French version, 1509 Indonesian version, 1509 limitations, 1508 Malaya Version, 1509 Persian version, 1508 scoring, 1507 Spanish version, 1508 uses, 1507–1508 Binge eating scoring systems, 1475 anorexigenic neuropeptides, 1475 assessment, 1471–1474 bariatric patients, 1475 bariatric surgery, 1467, 1475 body mass index (BMI), 1466 disorder diagnosis, 1468 eating behavior, 1469–1471 loss of control, 1475 noncommunicable diseases, 1466 non-surgical treatment, 1467 obesity, 1466 orexigenic neuropeptides, 1475 physiological mechanisms, 1470 pre-and post-surgery patients, 1468, 1469 prevalence of disorders, 1467 scoring questionnaires, 1473 scoring systems, 1475 treatment, 1466 types of bariatric surgery, 1469–1471 Binge eating symptomatology, 1111 Binge/purge subtype (AN-BP), 226 Bioelectrical impedance analysis (BIA), 444 Biofeedback-assisted relaxation training, 1407 Biological and neural changes implicated in increased dietary intake or altered eating behavior, 1105 Biology of anorexia nervosa (AN) adolescents, 538 applications, 548 children, 538 clinical manifestations, 540 clinical presentation, 539, 541, 542 depression, 549 DMS-V criteria, 538 energy homeostasis, 543, 544 gastrointestinal symptoms, 549 genetic studies, 549 gonadal function, 546, 547 heterogeneity, 547 hypoleptinemia, 544–546 kisspeptin, 549 metabolic state, 546, 547 multi-organ complications, 539, 549

1545 neurohormonal regulation, 542, 543 NPY/AgRP neurons, 548 pathogenesis, 547 peripheral and central dysregulation, 547 POMC/CART neurons, 548 psychiatric disease, 539 psychiatric diseases, 549 psychotherapy, 549 renourishment, 549 risk of mortality, 539 Biopsychosocial model, 1251, 1401, 1402, 1410 Bipolar disorder, 683, 684 Bisacodyl, 1165 Black and Latinx communities, 377 Block design, 757 Blood brain barrier, 770 Blood-oxygen-level-dependent (BOLD), 994 Body density (BD), 443 Body dissatisfaction, 187–189, 191, 192, 891, 892, 917, 1011, 1180, 1181, 1309, 1312, 1317 Body dysmorphic disorder (BDD), 1306 clinical characteristics, 1315, 1316 comorbidities, 1308 core symptoms, 1307 diagnosis, 1313, 1314 eating disorders, 1312 functional impairment, 1309 gender differences, 1309, 1310 insight, 1308 muscle dysmorphia, 1310 prevalence, 1307 Body fat (BF), 442, 443, 445, 524, 533 AN, 443–445 definition, 441 Body image, 516, 517, 525, 527, 846–848, 852, 1312 disturbance, 847 Body Image Screening Questionnaire (BISQ), 1441 Body mass index (BMI), 38, 206, 415, 442, 445, 446, 517, 533, 647, 737, 888, 890, 917, 1126, 1145 ADHD, 127 AN, 441 definition, 441 eating disorders, 9 and emotional eating, 1383–1384 level after sleep deprivation, 1112 pre-gravid, 29 Body project, 183, 184, 187, 189–191, 193 Body satisfaction and eating behaviors, 134

1546 Body weights and mass, 1192–1201 Bone mineral density (BMD), 447, 709, 710, 713, 714 Books on eating disorders, 1534 Borderline personality disorder, 253, 259 Bradycardia, 660, 662 Brain-derived neurotrophic factor (BDNF), 78, 81, 558 Bratman Orthorexia Test (BOT), 1438, 1439 Buffering capacity, 787, 790 Bulimarexia, 5 Bulimia nervosa (BN), 96, 201–203, 210, 211, 226, 250, 265, 274, 317, 320, 323, 327, 331, 333, 338–340, 342, 399–401, 563–564, 635, 668, 688, 714, 753, 786, 790, 807–815, 942–944, 946, 947, 949, 1004, 1134, 1158, 1161, 1175, 1252, 1307, 1357, 1365 in adolescents, 731, 734 amenorrhea, 927, 928 androgen’s role, 776–778 antiandrogenic treatment, 775, 776 antidepressants, 823, 824 antiepileptics, 824, 827, 828, 837 anxious and depressive experiences, 733 applications, 778 in athlete, 116 attachment style, 848–849 attention-deficit/hyperactivity disorder, 130 biological mechanisms, 769 CBT-BN, 6 CBT-E, 18 characteristics, 9 cholesterol, 769 clinical features, 6 cognitive-behavioral therapy, 865 cognitive distortion, 734 comorbidity, 867, 868 definition, 5, 844 demographics, 866 development of, 725, 726 diagnostic criteria, 865 diagnostic crossover, 877, 878 dietary restriction, 400 as a disorder of embodiment, 846–850 eating disorders, 769, 931 family-based approaches, 868 features, 5 fertility, 925 fluoxetine, 823, 835 during gestation, 29 hormonal, 829, 831 hormonal changes, 773, 774 individual approaches, 868, 870

Index insomnia disorder, 149 key facts, 779, 780 late adolescence, 740 late-luteal phase, 773 LH-stimulated thecal cells, 770 lifetime prevalence, 823 management of pregnant women, 931, 932 medications, 823, 832–834, 836, 837 menstrual cycle, 773 mid-luteal phase, 773 mixed/negative findings, 831 multifactorial etiology, 864 negative feelings, 823 neural correlates, 847–848 open-label trial, 836 pathophysiology, 772 perfectionism and, 732 pharmacology, 834, 835, 837 pharmacology youth, 833, 834 pharmacotherapy, 823, 836, 874 physical and psychosocial impacts, 400 polycystic ovary syndrome, 774, 775, 925, 926 postpartum period, 930, 931 pregnant women, 930 pregnenolone, 770 prevalence, 866 prevalence of pregnancy, 929 primary characteristic of, 733 prokinetic agent, 836 psychiatric disorder, 776–778, 864 psychodynamics of, 727 psychological characteristics, 729 psychotherapy, 823, 834, 835, 837 purgative, 731 randomized control trial, 879 reproduction, 928 self-esteem and, 731 sex steroid hormones, 769, 772 stimulants, 827, 829, 830 tempo-spatial dynamics, 849–850 topiramate, 836, 837 transdiagnostic treatment, 20 transdiagnostic view, 866, 867 treatment, 868, 872 treatment considerations, 400–401 treatment moderators, 874–877 unplanned pregnancies, 27 visceral interoception, 846–847 weight bias, 878, 879 Bulimic Investigatory Test of Edinburg (BITE), 795 Burda Orthorexia Risk Assessment (B-ORA), 1442

Index C Calcium foods, 393 cAMP-response element binding protein (CREB), 986 cAMP-responsive element-binding protein H (CREBH), 706 Cancer, and binge eating alcohol consumption, 1033 behavioral, environmental, and biomedical risk factors, 1026, 1027 behavioral risk factors, 1028, 1032 cigarette smoking, 1030 correlational or causational effects, 1032 directional relationships, 1035 healthcare and screening behaviors, 1033 low and middle-income areas, 1026 maladaptive coping mechanisms, 1032 mental and emotional consequences, 1033–1035 mental and emotional health risks, 1035 metabolic abnormalities, 1033 modifiable risk factors, 1031 nutrition and diet quality, 1028, 1029 obesity, 1028 pathways, 1034 physical activity, 1029, 1030, 1032 physical and mental health impacts, 1026 physical health, 1026 poorer nutrition and dietary intake, 1031 protective effects of exercise, 1032 protective factors, 1030 in psychiatric classification systems, 1036 psychological impacts, 1027 public health issues, 1028 screening behaviors, 1030 screening rates, 1033 secondhand smoke, 1030 shared risk factors, 1036 smoking and alcohol use, 1032 substance use behavior, 1030 utilization of health care, 1033 workplace carcinogens, 1026 Cannabinoid-like G-coupled receptors, 84 Cannabinoids (CNR1) genes, 78 Cannabinoid type 1 receptor (CB1R), 461 Carbohydrates, 396, 522, 1161 Cardiac arrhythmia, 657 Cardiac complications, 541 Caregivers, 294 Case-control study, 322, 338, 339, 345 Catecholamine, 67 Catecholamine-O-methyl transferase (COMT) genes, 78 Catechol-O-methyltransferase (COMT) gene, 229

1547 Center for Disease Control and Prevention (CDC), 645 Central coherence, 751, 753 Central Coherence Index (CCI), 756 Central nervous system, 171 Cerebellar dentate nucleus, 1270 Cerebellum, 1268 Cerebrospinal fluid (CSF), 171 Cerebrum, 1270 Child–Adolescent Perfectionism Scale (CAPS), 736 Child Eating Behavior Questionnaire, 1419 Childhood impulsivity, 136 Childhood obesity and early onset of being overweight, 1031 Children eating patterns with ADHD, 127 school-aged, with ADHD, 125 with ADHD, 128 Children and adolescents, 284, 286, 288, 292, 294, 295, 298, 300, 305, 306, 316, 344 Children’s Binge Eating Disorder Scale (C-BEDS), 1509 Cholecystokinin (CCK), 85, 1160 Cholesterol, 769 Chronicity, 946, 949 Chronic sleep deprivation and binge eating, 1110, 1111 Chronic sleep deprivation and sleep disturbances, 1108 Chronic starvation, 703, 704, 707, 708 Circadian clock genes, 1198 Circadian control of feeding by the master and the secondary clocks, 1194 Circadian disruptions in shift work, 1195 Circadian rhythm of food intake, 1194–1196 Clinical sample, 322, 338, 339 CNR1 and CNR2 genes, 83 Cocaine and amphetamine regulated transcript (CART), 86 Coenaesthesia, 845, 847 Cognitive-behavioral approaches, 1243, 1249 Cognitive behavioral model, 809 Cognitive-behavioral strategies, 370 Cognitive behavioral therapy (CBT), 4, 279, 391, 402, 824, 865, 868, 870, 992, 1150, 1152, 1243, 1252, 1318 Cognitive Behavioral Therapy–Enhanced (CBT-E), 853 Cognitive Behavioral Therapy for eating disorders (CBT-E), 1185 Cognitive-Behavioral Treatment (CBT), 376 Cognitive-behavioral treatment for ARFID (CBT-AR), 1249

1548 Cognitive dissonance (CD), 279 Cognitive functioning, of EDs, 749 Cognitive states, 1011 Cohort study, 338, 345 Collaborative Care Skills Workshops, 301 College Health Related Information Survey (CHRIS-73), 117 Combination devices, 427 Combined oral contraceptives (COC), 776 Community sample, 338, 339 Comorbidity, 633, 634, 867, 1308 Compensatory behavior, 865, 868 Competing response, 1401, 1403, 1410 Compulsive behavior and mental preoccupation, 1437 Compulsive exercise test (CET), 420 Computer gaming, 1341 Computerized Tomography (CT), 1065 Concentration networks, 1216 Confident Body, Confident Child, 296 Consequences of binge eating, 1012 Corticosterone-insulin interaction, 56 Corticotropin-releasing factor (CRF), 54, 67 Corticotropin releasing hormone (CRH), 1407 Cortisol, 85 CREST treatment, 340 Criterion B symptoms, 1123, 1133 Cronbach alpha values of questionnaires, 1442 Culture bound syndrome, 216 Cyclooxygenases (COXs), 455 Cytochrome P450 epoxygenases, 456 Cytochrome P450 monooxygenases (CYP), 455 Cytokines, 67

D Danish National Birth Cohort (DNBC), 43 D-cycloserine (DCS), 1250 Dehydration, 252, 253, 259 Dehydroepiandrosterone sulfate (DHEA-S), 770, 779 Deliberate Denial of Disordered Eating Behaviors Scale (DDEBS), 374, 380 DeltaFosB, 983, 984 binge eating, 983 chronic stimulation, 984 expression, 986 neuronal activity, 987 Denial of disordered eating applications, 378, 379 assessment, 369, 371, 373, 375, 376, 378, 380

Index behaviors, 378 black women, 377 clinical and non-clinical samples, 377 comorbid diagnostic consequences, 372 concealment, 369, 374, 375, 379 definition, 368, 369 diagnosis, 368, 371, 372, 375, 378, 380 diagnostic consequences, 371, 372 eating behaviors, 368 etiology, 369, 370 face stigmatization, 378 factors, 379 health care providers, 377 help-seeking consequences, 371 infancy, 378 insight, 368, 369, 372, 373, 375, 378, 379 interpersonal formulation, 379 legal system, 378 lethal consequences, 370, 371 lying, 373 mental illness, 378 retrospective, 374, 375 self-report, 373, 374 social consequences, 370 underreporting, 373, 379 Dental caries biological and clinical aspects, 792 concepts and epidemiology, 792 dental caries and bulimic symptomatology, 796 etiology, 793 Dentate gyrus, 556, 558, 559 Depression, 542, 546, 678, 776, 777, 918 bulimia nervosa, 733 Depressive and bipolar disorders, 1467 Depressive disorders, 253 Depressive emotional eating consumed overall fewer Kcal and carbohydrates, 1112 Depressive symptoms, 892 Desacyl-ghrelin (DAG), 571 Describe, express, assert, and reinforce (DEAR), 376 Developmental Origins of Health and Disease, 38 Dextroamphetamine, 829 Diagnostical and Statistical Manuals (DSM), 265 Diagnostic and Statistical Manual for Mental Illness (DSM-5), 371 Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5), 643, 689, 1044, 1145, 1505

Index Diagnostic and Statistical Manual of Mental Disorders (DSM), 533, 769, 777, 1123, 1468, 1530 Diagnostic and Statistical Manual of Mental Disorders (DSM)-III, 203 Diagnostic and Statistical Manual of Mental Health Disorders (DSM), 1236, 1252 Diagnostic and Statistical Manual version 5 (DSM-5), 514, 532 Diagnostic criteria, 1482, 1485–1488, 1492, 1493 Diagnostic crossover, 878 Dialectical behavior therapy (DBT), 340, 376, 814, 834, 873, 971 Diaphragmatic breathing, 1401–1403, 1410 Dietary assessment, 389 Dietary cholesterol, 769 Dietary psychopathology, 1086 Dietary restraint, 892, 893, 918, 1009, 1010, 1160, 1161 macronutrient deficiencies, 1163 micronutrient deficiencies, 1162, 1163 Diet-induced hypoglycaemia, 62 Dieting, 1006, 1009 Dietitians, 1165–1167 Differential diagnosis, 1252 Difficulty in Describing Feelings (DDF), 316–318, 322, 325, 330, 338–340, 342 Difficulty to Identifying Feelings (DIF), 316–319, 322, 326, 328, 330, 333, 338–342 Diffusion Tensor Imaging (DTI) study, 563, 1076 Digital media use, 135 Dihydrotestosterone, 770 5-α-Dihydrotestosterone (DHT), 770 Dihydrotestosterone (DHT), 771 Disordered eating, 55, 66, 68, 296, 304, 305 Disordered eating behaviors, 129 and binge eating, 1109 Dissonance-based interventions, 185, 187, 189 Distress tolerance, 814 Diuretic misuse, 1165 Dopamine (DA), 81, 777 function, 136 SUD and ED, 228, 230 Dopamine D3 receptor (DRD3), 82 Dopamine receptor 2, 3 and 4 (DRD2, DRD3 and DRD4) genes, 81 Dopamine receptor family, 78, 81 Dopamine reward pathway, 57 Dopaminergic signaling system, 136

1549 Dorsolateral prefrontal cortex (DLPFC), 994 Dove Parents, 297 Dove Self-Esteem Project Website for Parents, 297 DRD4 gene, 82 Driven exercise, 430 Drospirenone, 776 Dual-energy X-ray absorptiometry (DXA), 444–445 Dual Pathway Model (DPM) applications, 917 bivariate relationships, 893 BN risk factors, 918 body dissatisfaction, 889, 891, 892 bulimia nervosa (BN), 888 caloric deprivation, 889 clinical and prevention implications, 916 cross-lagged model, 913 cross-sectional studies, 893, 894, 901, 902 dietary restraint, 892, 893 disordered eating symptoms, 918 limitations, 914–916 longitudinal studies, 902, 911–913 negative affect, 892, 893 negative mood state, 889 path-modelling, 893 predictive utility, 914 risk factors, 916, 917 sociocultural pressure, 888, 890 thin-ideal internalisation, 888, 891, 918 Duration of untreated ED (DUED), 270 Duration of untreated illness (DUI), 273, 274 Düsseldorfer Orthorexia Scale (DOS), 1441, 1492–1493 Dutch Eating Behaviour Questionnaire, 1445 Dysbiosis, 489 Dysmorphic concern, 1315 Dysmorphophobia, 1306, 1321 Dyspeptic symptoms, 1406 Dysthymia, 689

E Early adolescence anorexia nervosa, 740 bodily changes, 740 psychosexual identity in, 725 Early detection adolescence, 285 adolescents, 290–292, 303 anorexia nervosa, 285 applications, 305 barriers, 292–295, 303

1550 Early detection (cont.) behavioral symptoms, 290, 291, 303 caregivers, 285, 290, 303, 304 categories, 286 childhood, 285 children, 290, 291, 303 COVID-19 pandemic, 303, 305 early cognitive symptoms, 290 early interventions, 286, 288 Eating Disorder Continuum, 287 eating habits, 292 education, 307 energy intake, 292 expenditure changes, 292 family involvement, 284 interventions, 285, 307 linear progression, 287 literature, 303 longitudinal research, 289 mental illnesses, 284 mood changes, 292 online programs, 305 parent-focused early intervention programs, 295 parent-led early detection, 306 parent-led early intervention programs, 295 parent-led early interventions, 304 parent-led prevention, 303 parent-led risk factor reduction, 295–298 parent-led treatments, 298, 299 parents, 284, 285, 292, 294 parent support, 300–302, 307 phases of illness, 286 research and clinical interventions, 302 risk factors, 285, 289, 304 role of parents, 288, 289 symptoms, 285, 289, 303 time-based parameters, 287 treatment, 284 Early disorder phase, 306 Early Metabolic programming, 38 Eating Attitudes Test (EAT-26), 131, 1523 Eating Attitudes Test (EAT), 373 Eating disorder (ED), 250, 251, 254, 255, 257, 258, 261, 263–267, 315, 322, 338–344, 346, 1085, 1504 Eating Disorder Diagnostic Scale (EDDS), 1523 Eating Disorder Examination (EDE), 1505 Eating Disorder Examination-Bariatric Surgery Version (EDE), 1472

Index Eating Disorder Examination-Questionnaire (EDE-Q), 532, 1519–1521 Eating Disorder Inventory (EDI), 373 Eating Disorder Not Otherwise Specified (EDNOS), 338, 340, 769, 943, 1211 Eating Disorder Not Otherwise Specified of Purging type (EDNOS-P), 777 Eating disorder quality of life (EDQoL) questionnaire, 1457 Eating Disorder Quality of Life (EDQoL) scale complications, 1452 domains, 1457, 1458 health-related quality of life, 1452 inpatient treatment, 1456 interpersonal domain, 1458 medical comorbidities, 1456 pro-eating disorder website communities, 1455 psychological approaches, 1456 QoL and body objectification, 1456 quality of life, 1452, 1454 treatment approaches, 1456 weight gain and reductions in ED symptomatology, 1456 Eating disorders (ED), 96, 97, 101, 182–183, 225, 270, 387, 415, 544, 556, 557, 563, 564, 625, 627, 631, 633, 786, 807–810, 812, 881, 942, 945, 1004, 1192, 1314, 1315, 1331, 1332, 1342–1346, 1361 in ADHD, 125 in adolescents, 5 anorexia nervosa, 201, 202, 354 application, 20, 216, 952 in athlete female, 113 male, 113, 115 prevalence studies, 113 risk factors, 113 sports disciplines, 115 beliefs and behaviours, 390 binge, 947 binge eating disorder, 354 body mass index, 9 books on, 1534, 1536 bulimia nervosa, 202, 203, 354 chronicity, 949 clinical features characteristic of, 8 cognitive behavior therapy, 4 culture-bound syndromes, 200 diagnostic category of, 9, 18

Index diagnostic criteria, 203 epidemiological studies, 215 etiological theory, 207 etiology, 270 features of, 8 and fertility, 27 food and nutrient administration, 390 food and nutrient intake, 389 gene-environment interaction studies, 101–102 genetics, 201 health care, 206, 213 incidence, 206, 207 inpatient dietetic treatment, 397–399 laboratory studies recommended and potential findings, 277 maintenance of, 7 medical consultations, features of, 272–276 medication and complementary medicine, 390 men, 214, 215 methodological issues, 206 middle-aged women, 213, 214 mortality, 270, 951 non-Western countries, 200 nutrition assessment, 388–390 nutrition education and counselling, 391 nutrition intervention, monitoring and evaluation, 390–391 and OCD, 1361 and ON, 1365–1368 other resources of interest or relevance to, 1538 outpatient dietetic treatment for, 392–397 in pregnancy, 28–29 prevalence, 206, 207 prevention of eating disorders, intervention programs and impact, 276–279 professional societies, 1533 psychiatric disorders, 201 psychosocial change, 200 regulatory bodies or organisations, 1532 remission, 945 risk factors and prodromes, 271–272 serotonin in, 97 signs and symptoms, 275 sociocultural, 200 SUD and ED, 226 time-related changes, 215, 217 uric acid in, 172–174 validated screening tool, 277

1551 Western countries (see Western countries, EDs) Western culture, 200 Eating Disorders Examination (EDE), 371 Eating Disorders Inventory (EDI), 1445 Eating Disorders in Youth-Questionnaire, 1242 Eating Disorders Quality of Life Scale (EDQLS), 1525 Eating Habits Questionnaire (EHQ), 1492 Eating patterns behavior outcomes, 59 drinking and smoking, 59 eating behavior, 59 food consumption, 59 mood, 59, 60, 62 stress/negative mood, 59 stress, 59, 60, 62 Ecological momentary assessment, 808, 811, 1005, 1015 EDE-Q, 1094, 1095 EDI-2, 1445 ED-related psychopathology, 1150 ED-specific questionnaires for the evaluation of QoL, 1453 Egosyntonicity, 369 Egosyntonic personality, 80 Eicosanoids (eiCs), 67, 453 in ABA model, 460 and neuroinflammation, 457 receptors, 456 Electrocardiogram (ECG) anorexia nervosa (AN), 656 applications, 668 bradycardia, 659, 660, 662, 668 cardiac abnormalities, 659 cardiac manifestations, 656 cardiac risk, 669 clinical care of patients, 667 clinical use, 666, 668 computer-generated parameters, 658 electrolyte imbalances, 668 exercise, 664, 665 heart rate (HR), 657 heart rate variability (HRV), 662 heart rhythm, 657 impact of refeeding, 664 interpretation, 658 normal electrocardiogram values, 659 parameters, 659 patients, 667 prescribing QT prolonging medications, 665

1552 Electrocardiogram (ECG) (cont.) psychopharmacotherapy, 659, 665, 666, 668 QT interval, 663 refeeding, 659 skin electrodes, 657 spatial and temporal information, 659 sudden unexpected death (SUD), 666 symptoms, 657 T-wave changes, 664 Electrophysiological studies, 1272 Embedded Figures Test (EFT), 757 Embodiment, 850, 851 bulimia nervosa, 846–850 clinical perspectives, 853–854 definition, 845 and sexuality, 852–853 Emotional activation, 1383 Emotional eating, 1382 and body mass index, 1383–1384 and food craving, 1385–1387 and food image stimuli, 1385–1386 and HRV, 1391–1392 and hunger inhibitory control, 1387–1389 and loss of control eating, 1386–1388 neural basis of, 1388–1390 Emotional regulation difficulties (ERD), 133 Emotion dysregulation, 808, 810, 815 Emotion regulation, 807, 809–811 in SUD and ED, 236 Emotion Regulation Group Therapy, 340 Emotion-related eating, 64 Empathy, 651 Endocannabinoids (eCBs), 83, 461 pathway, 83–84 Endocrine system, 67 Energy expenditure, 544 Energy intake, 389, 398, 1045, 1051, 1055, 1058 Enhanced Cognitive Behavior Therapy (CBT-E) for adolescents, 15 CBT for Bulimia Nervosa (CBT-BN), 4 challenges, 19 definition, 4 forms of, 14 goals, 12 implications for clinical services, 19 inpatient, 17 integral parts of, 15 intensive outpatient, 15 origin of, 5 outpatient version of, 15

Index post-inpatient outpatient, 18 psychological model, 13 psychological treatment, 9 rationale, 5 status of, 18 transdiagnostic theory, 8 transdiagnostic treatment, 20 treatment, 4 for underweight patients, 15 Enhanced version of CBT (CBT-E), 1150 Ensemble coding findings, 1074 Enteral feeding, 1252 Environment, 98, 102 Enzymatic deficiency, 171 Eosinophils, 1406–1411 EPHX2, 88 Erosive tooth wear (ETW) biological and clinical aspects, 788 concepts and epidemiology, 787, 788 epidemiology, 787 erosive tooth wear and bulimic symptomatology, 794 etiology, 790–791 ESR2, 88 Estradiol, 709 Estrogen receptor (ER), 771, 778 Estrogen Related Receptor Alpha gene (ESRRA), 88 Estrogens, 770 Evening awakenings with ingestions, 1211 Evidence, 1531, 1536 Excessive exercise, 423, 424 Executive function deficits common features of, 234 in SUD and ED, 235 Exercise, 1370 addiction, 1341, 1342, 1345, 1346 chronic physical, 576 Exercise addiction inventory (EAI), 420 Exercise Motivations Inventory-2 (EMI-2), 419 Exogenous GH, 703 Experienced Carers Helping Others (ECHO), 301 Exploratory factor analysis (EFA), 1490 Exposure and response prevention therapy (ERP), 262 Expressive writing, 191, 192 External context, 1011 Externally Oriented Thinking (EOT), 316, 317, 322, 338, 339 Exteroception, 848

Index F Facebook, 911 Facial emotion recognition task, 474, 477 Familial aggregation, 1198 Family-based treatment (FBT), 284, 299, 306, 375, 380, 865, 868, 873, 876, 877, 1243 Fasting, 1009 FAST (The Female Athlete Screening Tool), 118 Fat, 1161 catabolism, 539 Fat mass (FM), 445 Fat mass and obesity-related gene (FTO) adolescents, 1050–1052, 1057 adult and pediatric populations, 1057 adults, 1046–1050 alleles and neural studies, 1054, 1055 anorexia nervosa, 1058 binge Eating, 1058 binge nating, 1058 bulimia nervosa, 1058 children, 1050–1052, 1057 compensatory behavior, 1044 development, 1046 diabetes, 1045 eating disorders, 1044 emotional eating, 1057, 1058 etiology, 1045 food craving, 1058 food enjoyment, 1058 food responsiveness, 1058 food reward, 1058 high-energy food items, 1045 higher food reinforcement, 1045 homeostatic and reward circuits, 1052, 1053, 1056 hypothalamus, 1045 limitations, 1056, 1057 metabolic syndrome, 1045 morbidity, 1045 mortality, 1045 neural systems, 1052 neurobiological evidence, 1057 pediatric and adult population, 1046 relative reinforcing value, 1058 strengths, 1056, 1057 Fatty acid amide hydrolase (FAAH) enzyme, 455 FBT for the anorexia nervosa prodrome, 299 Fecal microbiota transplantation, 500, 501, 503 Feeding and eating disorders, 642, 643

1553 Feeding and Eating Disorders ExaminationBariatric Surgery Version (EDE-BSV), 1472 Feeling and Body Investigators-ARFID Division (FBI-ARFID), 1249 Fertility, 446 anorexia nervosa and, 605 eating disorders in, 615 long-term effect on, 608 Fibroblast growth factor (FGF)-21, 707 First Episode Rapid Early Intervention for Eating Disorders (FREED), 301, 302 First Night Eating Symposium, 1211 Fixation, 1481–1485, 1487, 1488, 1490, 1494–1497 Fluid replacement, 259–261 Fluid restriction in eating disorders behavioral interventions, 261, 262 demographic characteristics, 253 fluid replacement, 259–261 Holliday-Segar formula, 252, 253 inpatient or residential setting, 253 intentional fluid restriction, 251, 252 internet, 254 patient fluid needs, 252, 253 psychiatric symptoms, 255 psychological interventions, 262, 263, 265 water weight, 254 Fluoxetine, 824, 834, 837 Focused ultrasound stimulation (FUS), 993 Follicle stimulating hormone (FSH), 772, 926 Food addiction, 1342–1343, 1345 ADHD, 133 rate of, 136 Food craving, 1006, 1010, 1385, 1387 Food enjoyment, 1050–1052, 1058 Food fussiness (FF), 1419, 1420, 1423 Food insecurity, 390, 400 Food intake, 250, 253, 265, 1193, 1194 Food intake and energy expenditure, 1192 Food literacy, 389 Food responsiveness, 1050, 1052, 1058 Food rewarding, 1057, 1058 FTO (Fat mass and obesity-associated) gene, 86 Functional dyspepsia, 1406–1408, 1410 Functional hypothalamic amenorrhea (FHA), 605, 772, 924, 925, 928 Functional MRI studies (fMRI), 563, 1065, 1068, 1074–1076 Fused Graphical Lasso (FGL) method, 1224

1554 G Gambling, 1332, 1341 Gaming, 1332, 1341 Gamma amino butyric acid (GABA), 1267 Gastric bypass, 1131 Gastroesophageal reflux disease (GERD), 1401, 1403–1406, 1410 Gastrointestinal problems, 1237 Gastrointestinal symptoms, 1241 Gender, 532, 1309 Genetic(s) imprinting, 1264 SUD and ED, 227, 229 variants, 98, 102, 103, 545 Gene variants, in ED, 79 Genomic-wide association studies (GWAS), 79, 1199–1200 Gestation, OFSED during, 28 Gestational anorexia nervosa, 29 Gestational bulimia nervosa, 29–30 Gestational diabetes mellitus (GDM), 39, 42 Gestation weight gain (GWG), 27, 39 Ghrelin, 84, 542, 543, 546, 549, 571, 705–706, 1267 antagonism, 576 chronicity and, 577 clinical evidence of, 575 genetic factors, 576 insomnia disorder, 153 physiological effects, 572 resistance, 576 and reward signaling in AN, 573 Ghrelin gene (GHRL), 84, 571 GHSR1a receptor, 571 Glucocorticoid receptors (GR), 57 Glucocorticoids (GCs), 54–56, 67, 68 Glutamatergic neurotransmission, 83 Glycaemic load (GL), 62 Go/no-go saccade task, 592 Godin Leisure-Time Exercise Questionnaire (GLTEQ)., 418 Gonadotropin, 770 Gonadotropin-releasing hormone (GnRH), 774 Gothenburg anorexia nervosa study, 471 G protein-coupled receptors (GPCRs), 456 Group Embedded Figures Test (GEFT), 757 Growth hormone (GH), 571 Growth hormone (GH) resistance, in anorexia nervosa, 705 bone mineral density, 709 CREBH, 706 estradiol, 709

Index FGF-21, 707 ghrelin, 705–706 insulin, 707 leptin, 708–709 protein deficiency, 705 recombinant human growth hormone, 710 recombinant human IGF-1, 710–714 SIRT1, 706 testosterone, 709 triiodothyronine, 707 Growth hormone-insulin-like growth factor-1 (IGF-1) axis, 703, 706, 714 Growth hormone secretagogue receptor 1a (GHSR1a), 706 Gut microbiome, 62

H Head circumference, 930 Healthful eating, 1329 Health-Related Quality of Life in ED-short form (HeRQoLED-s), 1525 Healthy eating, 1354–1358, 1360, 1364, 1365, 1370 Healthy Girls Project, 296, 297 Healthy orthorexia (HeOr), 1484, 1485, 1489, 1491, 1493–1497 psychometric evaluation, 1493 Heart rate sensors, 427 Heart rate variability (HRV), 662, 1383–1388, 1391 Help-seeking, 379 Heterogeneity, 1237 Hippocampal atrophy, 542 Hippocampal cell proliferation, 557 Hippocampal neurogenesis, 557, 558 Hippocampus, 55 in animal model of AN, 558–559 bulimia nervosa (BN), 563–564 functional studies, 561, 562 in neurobiology, 557 psychiatric disorders, 557 role, 556 structural studies, 559–561 with short (1 year) or long duration of anorexia nervosa, 561 Histone deacetylase 4 (HDAC4), 88 Holliday-Segar formula, 252, 253 Hormonal, 829, 831 disbalance, 359 Hospital Anxiety and Depression Scale (HADS), 1525 Hospital-based feeding programs, 1250

Index 5-HT2A receptor gene (re6311), 80 5-HTTLPR, 97–102, 228 5-HT transporter (5-HTT), 80 Human adipocytes, 546 Hunger hormone, see Ghrelin Hydroloading, 265 5-Hydroxytryptamine (5-HT) system, 80 Hyperactivity, 539, 678 Hypercortisolaemia, 542 Hyperemesis gravidarum, 929 Hyperphagia, 1263, 1264, 1288, 1291, 1293, 1296 Hypocalcaemia, 657 Hypocretin receptors and NE, 1199 Hypokalemia, 657 Hypoleptinemia, 544–546, 548 Hypomagnesemia, 657 Hyponatremia, 657 Hypoproteinaemia, 541 Hypothalamic amenorrhea, 542, 779 Hypothalamic-pituitary-adrenal (HPA) axis, 54, 67, 774, 776 dopamine reward pathway, 57 glucocorticoids, 55, 56 Hypothalamic-pituitary-gonadal (HPG) axis, 546, 774 Hypothalamic–pituitary-ovarian axis, 772 Hypothalamic-pituitary-thyroidal axis, 772 Hypothalamic reactivity, 548 Hypothalamus, 55, 543, 544, 547, 548, 1265 Hypovitaminosis, 541 Hypoxanthine-guanine phosphoribosyltransferase, 171

I ICD-10, 1530, 1531 ICD-11, 1123–1125, 1531 IDentity and EAting disorders (IDEA) questionnaire, 852 Image of one’s own body, 730, 733, 742 Immediate early genes (IEGs), 984 Immune activation, 1409 Implementation, 189–191 Impulsivity, 807, 808, 1182, 1183, 1505 SUD and ED, 233, 234, 236 Incidence, 192, 216 Individualized approaches, 1014 Inflammation, 1407 resolution of, 454 Inhibitory control, 987–989 Inpatient dietetic treatment, for eating disorders goals, 397

1555 nutrition support for inpatients, 398–399 refeeding syndrome, 398 Inpatient treatment, 624, 625, 627, 632–635 Insomnia disorder, 1192 anorexia nervosa, 149 avoidant/restrictive food intake disorder (ARFID), 150 binge eating disorder, 149 bulimia nervosa, 149 categories, 147 characteristics, 146 definition, 147 and eating disorders, 146 hypothesized psychological factors, 151 night eating syndrome, 150 prevalence, 148 social timing and behaviors, 154 and symptoms in eating disorders, 149 as transdiagnostic across psychopathology, 148–149 treatment implications, 155 Insulin, 546, 707, 708 Insulin like growth factor-1 (IGF-1), 571, 703–710, 714 Insulin resistance, 774 Integrative cognitive-affective therapy for bulimia nervosa, 815 Intelligence quotient (IQ), 645 Intentional fluid restriction, 250–252, 254, 265–267 Interaction, 97, 102 Interest, 1483, 1485, 1487 Inter-generational transmission, 1423 International Classification of Diseases 10th Revision (ICD-10), 206 International Classification of Diseases and Related Health Problems (ICD), 1530 International Classification of Diseases (ICD-11), 1236 International Physical Activity Questionnaire (IPAQ), 416 International research meeting, 1193 International Society for Nutritional Psychiatry Research, 60 International units (IU), 829 Internet addiction, 1345, 1346 Interoception, 847, 848, 854 Interpersonal therapy (IPT), 834 Intervention outcomes, 315, 340, 342–344 Interventions, 1015 Intrauterine growth restriction (IUGR), 38 Iodine deficiency disorders, 40

1556 K Kinase domain containing 1 (ANKK1), 78 Kisspeptin (KISS1), 546, 548 Kutcher Adolescent Depressive Scale (KADS), 736

L L-allele, 82 Language revisions of questionnaires, 1443 Laparoscopic adjustable gastric band (LAGB), 1469 Laparoscopic sleeve gastrectomy (LSG), 1469 Large-for-gestational-age (LGA) babies, 30 Late adolescence, bulimia nervosa, 740 Lateral hypothalamic area (LHA), 543 Lateral parabrachial nucleus, 544 Laxatives, 1164 Leptin, 544, 546, 549, 708–709, 1193 in cerebrospinal fluid, 85 insomnia disorder, 153 Leptin gene (LEP), 85 Lesch-Nyhan syndrome)LNS), 171 Leukotrienes, 456 Light neglect obesity (LNO), 965 Likert Scale in questionnaires, 1440 Lipoxygenases (LOXs), 455 Lisdexamfetamine (LDX), 823, 993 Lisdexamfetamine dimesylate (LDX), 829 Lithium, 831 Lived corporeality, 845, 846, 848, 850–853, 855 Liver, 769 Longitudinal Assessment of Bariatric Surgery (LABS) study, 1468 Longitudinal study, 322, 340, 341, 343, 345 Loss of control (LOC), 1468 Loss of control eating binge eating, 128–129 and emotional eating, 1386–1388 Loss of control while eating (LOCE), 1086, 1091–1097 Low-density lipoproteins (LDLs), 769, 926 Low Energy Availability in Females Questionnaire (LEAF-Q), 118 Luteinizing hormone (LH), 772, 926

M Macronutrients, 1163, 1252 Magnesium hydroxide, 1165 Magnetic resonance imaging (MRI), 1065 Magnetic resonance spectroscopy, 1272

Index Magnetoencephalography studies in BED, 1076, 1079 Major depressive disorder (MDD), 557, 560, 689 Maladaptive physical activity, 415 Malnutrition, 358, 387, 388, 399, 440, 539, 542, 546, 547, 549 Mania, 678 Mast cells, 1407–1411 Matching Familiar Figures Test (MFFT), 758 Maternal-fetal relationship, 27 Maternal postnatal depression, 30 Medical conditions, 1241 Medical consultations, 273 eating disorders, 272–276 Medical foods, 629 Medical model paradigm of disease, 1209, 1213 Mediterranean diet (MD), 42, 60 Medium spiny neurons (MSNs), 986 Melanocortin (MC) system, 505 Memory and learning, 1053 Memory-guided saccade task, 593 Menses, 440, 446 Mental Component Summary Scale (MCS), 1521 Mental health of cancer patients, 1027, 1028 eating disorders, 354 protection in, 360 Mesolimbic dopaminergic system, 67 Meta-analysis, 339, 343, 345 Methodological considerations, 1012 Methylamphetamine, 829 Methylphenidate, 829 Microbiome, of AN patients, 493 Microbiota with AN, 492–496 development in infancy, 492 dysbiosis, 489 gut, 489, 492, 493 host relationship, 490 lean, 500 manipulations in animal models, 491 microbiota-gut-brain axis, 490 obese, 500, 506 Microbiota-gut-brain axis, 490–492 Micronutrients, 1163, 1252 Mineral oil, 1165 Minerals, 1161 Minnesota Multiphasic Personality Inventory (MMPI), 374 Model-based recursive partitioning, 1225 Modeling Network structure, 1216

Index Monoamine oxidase inhibitors (MAOI), 824, 836 Monosodium urate (MSU), 169, 170 Mood and substance use disorders, 1467 Mood disorders, 643, 688 Mood intolerance, 809, 813 Morbid obesity and eating disorders, 1079 Morning anorexia, 1192–1193, 1209 Mortality, 942, 951 Motivational interviewing (MI), 375, 380 Motivation to eat, 1059 Multidisciplinary follow-up, 1085 Muscle dysmorphia, 1312 characteristics, 1310, 1311 steroid abuse, 1311

N N-arachidonoylethanolamine (AEA), 84, 455 Narrative review, 317, 345 Nasogastric (NG) feeding, 398 Nasogastric (NG) tube, 260, 1252 Negative affect, 807–809, 892, 893, 918, 983 Nental illness, 368 Neonatal outcomes, 608 AN on, 614 Neophobia, 1419, 1420, 1423, 1425 Nervous vomiting, 202 Network analysis, 1215, 1217 accuracy and stability, 1218 centrality indices, 1217, 1218 models, 1225 Network Approach to Psychopathology in Eating Disorders, 1218 Network Approach to Psychopathology in NES, 1219, 1221, 1223 Network dynamics, 1226 Network structure, 1216, 1217, 1223 Network theory, 1213–1215 Network Theory of Psychopathology, 1213 Neural correlates, 847–848 Neural tube defects (NTDs), 42 Neurobiology of ED, 230, 231 of ED-SUD, 231 of SUD, 230 Neurodevelopmental disorders (NDD), 643, 644 Neurofilament light chain protein (NfL), 473 Neurogenesis, 556 Neuroimaging, 561, 565 Neuroimaging studies, 1064

1557 Neuroinflammation in animal models of AN, 460 eiCs receptors, 456 Neuromodulation, 992, 993, 995, 1274 Neuronatin (NNAT) gene, 87 Neuropeptides, 55 Neuropeptide Y (NPY), 55, 67, 85, 543, 571, 1470 Neuropsychiatric disorders, 171–172 Neuropsychology, 644 Neurotransmitter, 777 intestinal, 492 metabolomic analysis, 503 Nicotine consumption, 1340 Night Eating Questionnaire (NEQ), 1196 Night eating syndrome (NES), 1192 BMI, 1197 bootstrapped strength difference, 1222 centrality plot for the psychopathology network, 1221 clinical impairment/distress, 1223 clinical observation of individuals with obesity, 1212 clinical versus subclinical thresholds, 1224 compensatory behaviors, 1197 conceptual and clinical utility, 1223 conceptualization, 1223, 1224 conceptualization and etiology, 1212 conceptualization and unique features, 1209 daily caloric intake, 1196 daily rhythms of food intake and sleep, 1193 delayed timing of eating, 1195 diabetes, 1197 diabetes management, 1198 disrupted circadian rhythm, 1224 emotional regulation, 1198 environmental influences, 1200 genetic determinants, 1200 genetic studies, 1198, 1199 genetic susceptibility, 1200 history of, 1209 hormone profiles, 1195, 1196 insomnia disorder, 150 isolated phenotype, 1193 long-term effects, 1197 meal anticipation, 1195 and network analysis circadian pattern of food intake, 1209 disrupted circadian rhythm, 1209 medical model approach, 1209 mood or sleep disturbances, 1209 network approach to psychopathology, 1209

1558 Night eating syndrome (NES) (cont.) network approach, 1224 nocturnal awakenings and food consumption, 1225 out-of-phase eating, 1195 phenotyping, 1196 poor sleep quantity and quality, 1111 prevalence, 1193 prevalence rates, 1212 psychological factors, 1198 psychological treatments, 1223 psychopathology network, 1220 recognition of, 1210 research and clinical implications, 1209, 1224 research diagnostic criteria, 1211 sleep-wake cycle, 1195 symptom network, 1214 symptoms, 1210, 1212 treatment, 1200 variation in operationalized diagnostic criteria, 1210 Nighttime eating, 1193, 1198–1200 Nine-item avoidant/restrictive screen (NIAS), 1420 Nocturnal eating, 1196 Nocturnal hyperphagia, 1192 Nocturnal ingestion of food, 1211 Nomophobia, 136 Non-communicable diseases (NCDs), 40 Non-compensatory purging, 1182, 1184 Non-pathological dimension, 1485, 1487, 1489, 1494, 1495, 1497 Non-specific symptoms, 276 Non-suicidal self-injury (NSSI), 370 Non-Western countries, EDs Africa, 213 East Asia, 211, 212 epidemiology, 211 Latin America, 212, 213 West Asia, 212 Norepinephrine (NE), 78 Nucleus accumbens (NAcc), 57 Nutrition, 1293 assessment, 388–390, 440 counselling, 391 deficiencies, 41 education, 391, 392 intervention, 390–393, 397, 400 rehabilitation, 391, 393, 397, 398, 627–628 status, 387, 400 support, for inpatients, 398–399 Nutrition Care Process, 387, 388

Index O Obesity, 1084, 1087, 1089–1093, 1095, 1131, 1294, 1296 ADHD and, 127 and daytime dysfunction, 134 hyperinsulinemia, 774 Object Assembly, 757 Objective binge episodes (OBEs), 226 Objective measures, 1013 Obligatory exercise questionnaire (OEQ), 420 Observation Alexithymia Scale (OAS), 317, 338, 342, 344 Obsession, 1481, 1484, 1485, 1494, 1495 Obsessive-compulsive disorder (OCD), 643, 685, 686, 691, 1241, 1360, 1361 and EDs, 1361 lifetime prevalence rate, 1361 and ON, 1364–1365 Obsessive-compulsive personality disorder (OCPD), 1368 Obsessive-compulsive symptoms, 678 disorder, 1331, 1347 Oculomotor delayed response task, 593 Oestrogen, 515, 532 Oleoylethanolamide (OEA), 461 Opioid antagonists, 83 Opioid delta 1 receptor (OPRD1), 83 Opioid peptides, 83 Opioids (OPRD1) genes, 78 Oppositional defiant disorder (ODD), 1241 Oral-sensory motor problems, 1237 OR eating behavior, 1104 Orexins, 85 Organic alexithymia, 315, 344 Orthorexia, 1436 Orthorexia nervosa (ON), 31, 1328, 1331, 1332, 1339–1344, 1354, 1355, 1359–1361, 1372, 1481–1486, 1489, 1491, 1497 in athletes, 116 definition, 1355 diagnostic criteria, 1358–1360, 1486 DOS, 1492–1493 with eating disorders, 1365–1368 EHQ, 1492 and exercise, 1370 frequency and risk factors, 1488–1490 and healthy living behaviors, 1370–1371 management symptomatology, 1494–1495 with mental disorders, 1368–1369 negative effects of orthorexia on health and functionality, 1356–1357

Index with obsessive-compulsive personality disorder, 1368 and OCD, 1364–1365 ONI, 1493 prevalance, 1357–1358 with psychotic disorders, 1369 questionnaires, 1438 smoking and alcohol use, 1371 and social media, 1370–1371 with somatoform disorders, 1368–1369 symptomatology, 1364, 1486–1488 symptoms of, 1355–1356 TOS, 1490–1492 treatment and management, 1372–1374 unique features, 1369 vegeterian diet, 1371 Orthorexia Nervosa Inventory (ONI), 1444, 1493 Orthorexia Nervosa Scale (ONS), 1442 Orthorexia Self-Test, 1438 Orthorexic eating, 1329–1332, 1339, 1341, 1343, 1345, 1346 ORTO-15, 1439–1441 Osteopenia, 447 Osteoporosis, 447 Other specified feeding and eating disorder (OSFED), 226, 279, 354, 476, 1152, 1252, 1253 categories, 1145, 1211 diagnostic classification, 1176 Outcome, 183–185, 189–193 Out-of-phase eating, 1195 Outpatient dietetic treatment, for eating disorders calcium foods, 393 carbohydrates, 396 diet foods and fillers, 397 fluids, 396 fruit and vegetables, 396 fun foods and social eating, 397 goals, 392 nuts, oils and fats, 396 protein, 393–396 Overeating, 1181 act of, 732 episodic, 733 in respondents, 736 uncontrolled, 728 and vomiting, 728 weight fluctuations and, 726 Overlapping Figures Test, 757 Oxidative stress, 68 Oxytocin (OXT), 829, 836, 1267

1559 P Paffenbarger Physical Activity Questionnaire (PPAQ), 419 Palmitoylethanolamide (PEA), 84, 461 Paranoia, 678 Paraventricular nucleus (PVN), 54 Parental Bonding Instrument (PBI), 962 Parental feeding practices, 1422–1423 Parent-based treatments, 1249, 1250 Parenting style, 962, 963 Parents Act Now, 298 Partial hospitalization program (PHP), 1239 Partial sleep deprivation on executive functions, 1113 Path-analyses, 918 Pathological dimension, 1483, 1484, 1495, 1497 Pediatric autoimmune neuropsychiatric disorders linked to streptococcal infections (PANDAS), 504 Pedometers, 427 Peptide tyrosine tyrosine (PYY), 1161 Perfectionism and bulimia nervosa, 732 Perinatal outcomes, anorexia nervosa and adverse, 613 Peroxisome proliferation-activated receptor α (PPARα), 84 Peroxisome proliferator-activated receptors (PPARs), 456 Persistent insomnia, 147 Personality, 959, 965–968, 971, 973, 974 Personality disorders, 643, 688, 689 Perth Alexithymia Questionnaire, 344 PGE receptor, 456 Pharmacotherapy, 992, 995, 1250 Phenomenological research, 846 Phenomenology, 846, 854 Phoenixin (PNX), 547, 549 Phospholipase A2 (PLA2) superfamily, 455 Physical activity (PA) adaptive, 415 eating disorders, 415 ecological momentary assessment, 421–424 maladaptive, 415, 419, 420 objective components, 415 objective measurement, 426–429 psychological components, 415 reasons for exercise inventory, 419 self-report measurement, 416, 417, 419, 421 semi-structured interview, 424, 425 Physical appearance, 1010 Physical Component Summary Scale (PCS), 1521

1560 Phyto-9 cannabinoid-tetrahydrocannabivarin, 83 Pica, in pregnancy, 30–31 Picky eaters (Pes), 1420 Picky eating (PE), 1418, 1425 childhood to young adulthood, 1421 definitions, 1418–1419 measurement, 1419–1420 parental feeding practices, 1422–1423 prevalence, 1420–1421 sensory sensitivity, 1423–1424 temperament, fearfulness and inhibition, 1424–1425 treatment, 1425 Pituitary disease, 202 Polish adaptation study, 1439 Polycystic ovary syndrome (PCOS), 774, 775, 924–926 Polyunsaturated fatty acids (PUFAs), 40, 453 POMC gene, 86 Positron emission tomography (PET), 1079 Postpartum period depressive and anxiety symptoms, 614 pregnancy and, 611, 616 Post-traumatic stress disorder, 253 Prader–Willi syndrome (PWS), 1263, 1271, 1273, 1288 adulthood, 1293, 1294 behavioral interventions, 1298 behavioral phenotype, 1265, 1266 BP1-BP2 microdeletion syndrome, 1266 brain stem, 1268 cerebellar contribution, eating disorders, 1276 cerebellum, 1268 cerebrum, 1270 diagnostic criteria, 1264 early childhood period, 1290–1292 electrophysiological studies, 1272 functional imaging studies, 1272, 1274 genetic susceptibility, 1265 ghrelin, 1267 5-hydroxytryptamine, 1267 hyperphagia, 1265 hypothalamic dysfunction, 1265 hypothalamus and pituitary gland, 1268 neurochemical alterations, 1267 neurological features, 1264 neuromodulation, 1274 nutritional stages, 1296, 1297 pharmacotherapy, 1299, 1300 phenotype, 1294, 1295 prenatal period, 1289

Index psychiatric comorbidities, eating disorders, 1276 psychiatric disturbances, 1265 schaaf-Yang syndrome, 1266 self-injurious behavior, 1296 structural connectivity, 1270 teenage and adolescent period, 1292, 1293 Prebiotics, 501, 502 Prefrontal cortex (PFC), 57, 985 Pregnancy, 446 anemia in, 611 behavioral change during, 27 binge eating disorder, 30 birth outcomes, 38 complications, 611 dietary patterns, 42–44 disease course in, 611 eating behaviors in, 27 eating disorders in, 28–29 ED/OFSED during, 27 feto-maternal outcomes, 42–44 industrialized countries, 41, 42 macronutrient, 44 maternal anthropometrics, 38–40 maternal nutrition, 38 micronutrients, 44 nausea and vomiting in, 612 nutrition, 38–40 pica during, 30–31 and postpartum period, 605 prevalence of anorexia nervosa in, 610 U/OSFED, 27 in women with ongoing AN, 605 Pregnenolone, 770 Pregorexia, 31 Preoccupation, 1481–1485, 1487, 1492, 1493, 1495, 1497, 1498 Pre-School Child Behavior Checklist, 1419 Pressure to eat, 1423 Preterm delivery, 614 Prevalence, 216 Prevention of eating disorders cognitive dissonance theory and implication for prevention, 185 dissonance-based intervention and Body Project, 187–188 efficacy and effectiveness of Body Project, 189 influencing public health, 189–190 Internet and digital techniques, 190 prevention strategies, 184–185 vBP, 190–193 Primary alexithymia, 315, 344, 345

Index Primary care, 271–274, 276, 279 Primary caregivers, 284, 285, 288, 289, 294, 303, 306 Primary prevention, 278 “Pro-ana” behaviors, 254 Probiotics, 501 on anorexia nervosa, 502 effect of, 502 Prodromal phase, 306 Prodromes, 271–273, 276, 278 Professional societies, 1533 Pro-inflammatory cytokines, 61 Prolactin, 85 Proopiomelanocortin (POMC), 86, 543, 1470 Prosaccade task, 591 PROSPERO, 317 Prostacyclin (PGI2), 456 Prostaglandin (PG)-H2, 455 Prostaglandins, COX-derived, 461 Protein, 393–396, 1161 deficiency, 705 synthesis, 541 Psychiatric comorbidity AN-depression association, 692 anorexia disorder, 683, 684 anorexia nervosa (AN) (see Anorexia nervosa (AN)) anxiety, 692 application, 688, 689 bipolar disorder, 683, 684 bulik hypotheses, 679 clinical and psychopathological fields, 676 clinical setting, 675 definition, 675 depressive disorders, 690 eating core symptoms, 692 eligibility criteria, 687 epidemiological studies, 676 epidemiology, 677 evaluation, 677 hierarchical diagnostic rules, 689 internal medicine, 675 liability spectrum model, 676 mental disorders, 676, 692 mental health professionals and researchers, 675 mortality, 681, 689, 692 multi-axial system, 675 neurodevelopmental disorders, 677 outcome, 678, 681, 683, 684, 689, 692 persistence, 679, 683, 688 psychiatric language, 675 psychopathology, 675

1561 recovery, 690 relapse, 689, 690 substance abuse, 693 suicidality, 690 time limits, 676 transposition, 676 treatments, 675, 677, 678, 680–684, 686, 687, 691, 692 Psychiatric disorders, 202, 556, 557, 560, 962, 963, 1452 Psychiatric illness, QoL and ED, 358 Psychoanalytic theory, 264 Psychological disorder, 1505 Psychological interventions, 262–265 Psychological treatment, 630–631 Psychopathology, 625, 631, 633, 690, 959, 963, 965–968, 970, 973, 974 Psychopharmacological treatment, 631 Psychopharmacotherapy, 665, 666 Psychosis, 686, 687, 691, 692 Psychotherapy, 264, 532 Psychotic disorders, 1369 Purging, 864, 865, 867, 872, 874, 876, 878, 881 analysis, 1184 Purging disorder (PD), 807–810, 812, 813 anorexia nervosa, 1158 anxiety-related traits, 1148 behavioral strategies, 1181 biological correlates, 1160, 1161 biological factors, 1146 bulimia nervosa, 1158 CBT, 1150 with CBT-E, 1184 clinical characteristics, 1180 clinical significance, 1145 clinical techniques, 1184 defined, 1176 demographic characteristics, 1177 development and maintenance, 1175 developmental and socio-cultural factors, 1146 diagnosis, 1176 diagnostic phenotypes, 1152 diagnostic subtype, 1145 diagnostic systems, 1152 differential diagnosis, 1175, 1176 diuretic misuse, 1165 diuretics, 1175 dysfunctional personality traits, 1148 eating disorder, 1158 ED diagnostic subtype, 1145 emotion regulation, 1181

1562 Purging disorder (PD) (cont.) endocrine and psychological factors, 1145 etiopathogenesis, 1147 evidence-based treatment targets, 1151 functional impairment, 1146 general psychopathology and emotional distress, 1147 heterogeneous etiopathogenesis, 1146 hunger and preoccupation with food, 1181 impulse control disorders, 1148 inclusion criteria, 1176 inclusion of loss of control, 1176 laxatives, 1164, 1165, 1176 lifetime prevalence rates, 1145 maladaptive coping, 1181 management, 1150 mass media influence, 1146 medical and pharmacological approach, 1150 medical complications, 1148, 1149, 1177, 1178 medications, 1150 misuse of laxatives, 1175 nutrients, 1178 overarching statements, 1179 parent-perceived childhood overweight, 1146 pervasive weight control strategy, 1180, 1181 physiological processes, 1184 postprandial gut satiety peptide, PYY, 1181 premorbid overweight conditions, 1147 prevalence, 1159, 1177 prevention and intervention modalities, 1152 psychoeducational and motivational aspects, 1150 psychological factors, 1146 psychopathological, and personality features, 1148 recurrent purging behaviors, 1175 risk factors, 1146 salient risk factor, 1182 self-induced vomiting, 1163, 1164, 1175, 1176, 1178 shared psychopathology and personality traits, 1145 subthreshold bulimia nervosa (BN), 1145 topographical similarities, 1175 treatment adherence, 1151 treatment outcome, 1151 treatment response, 1185 treatment studies, 1183, 1184

Index Q Quality of life (QoL), 634 BDI, 1523 definition, 1518 in eating disorders, 1453, 1454 EDDS, 1523 EDE-Q, 1519–1521 HADS, 1525 HeRQoLED-s, 1525 SF-12, 1521 SF-36, 1519 Weissman Social Adjustment Scale, 1522 Quality of life related to health (HRQoL), 361 Questionnaire, 1005 Questionnaire on Eating and Weight Patterns-5 (QEWP-5), 1095 Questionnaire on Eating and Weight PatternsRevised (QEWP-R), 1472 Questionnaires, orthorexia nervosa, 1436–1438 Quetelet Index, 441

R 7R/7R homozygotes, 82 Randomized controlled trials (RCTs), 1243, 1253 Rare genetic variants, 87–88 REAL Food Guide, 393 Reasons for Exercise Inventory (REI), 419 Recombinant human growth hormone, 710 Recombinant human insulin like growth factor-1 (rhIGF-1), 710–714 Refeeding process caloric prescription, 629 nasogastric feeding and parenteral nutrition, 630 nutrient quality and nutrient supplementation, 629–630 Refeeding syndrome, 387, 389, 398 Regional cerebral blood flow (rCBF), 1075 Regulatory bodies, 1532, 1533 Rehospitalization, 634–635 Relative energy deficiency in sport (RED-S), 117 Renutrition, 627, 629, 630, 632–633 Reproduction, after recovery from AN, 608 Resting energy expenditure (REE), 399 Restrictive and dieting goals, 1112 Reward deficiency syndrome (RDS), 136 Reward sensitivity, 233 SUD and ED, 233 Reward system, 988–990, 994, 996

Index Rey-Osterrieth Complex Figure (ROCF), 756 Risk factors, 270–272, 278, 279, 306 Ritual, 1355, 1365 Rorschach Alexithymia Scale, 317 Rosenberg Self–Esteem Scale (RSE), 736 Roux-en-Y gastric bypass (RYGB), 1087–1089, 1469 Rumination disorder impaired QoL of patients, 1455 Rumination syndrome, 1401, 1408–1409 pathophysiology, 1403–1405 physiology, 1402–1403

S Saccade characteristics, 588 tasks, 589 Saliva UA measurement, 170 S-allele, 82 Scan path, 594 Schaaf-Yang syndrome, 1266 Schedule for the Assessment of Insight (SAI), 373 Schizophrenia, 1467 SCOFF questionnaire, 1445 Secondary alexithymia, 315, 344, 345 Secondary prevention, 278 Selective serotonin reuptake inhibitor (SSRI), 665, 775 Self-awareness, 368 Self-disclosure, 368, 376 Self-Disclosure about Body Satisfaction scale (SDBS), 373 Self-Disclosure about Restrained Eating scale (SDRE), 373 Self-esteem, 680, 724, 726, 729–731, 901 and bulimia nervosa, 731 Self-harm, 688 Self-indicating depressive symptoms, 678 Self-induced vomiting, 1163 Self-injurious behavior, 1292, 1296 Self-injury, 256 Self-paced saccade task, 594 Sensor technology, 426 Sensory sensitivity, 1423–1424 Serotine receptor family, 78 Serotonergic system dysfunction, 80 Serotonin (5-HT), 62, 80, 97, 777 pathway, 80 SUD and ED, 230 System, 228 Serotonin reuptake inhibitor (SSRI), 823–825, 827, 836, 837

1563 Serotonin transporter gene SLC6A4 (5-HTTLPR), 80 Serotonin transporter (SERT), 97–99 Serum electrolytes, 657 Serum uric acid (SUA), 169–174 Set shifting, 651 Severe neglect obesity (SNO), 965 Sex hormone-binding globulin (SHBG), 771, 775, 926 Sex steroid hormones, 772 Sexuality, and embodiment, 852–853 Sexual orientation, 515, 532 Short-chain fatty acids (SCFA), 490, 498, 499 Short Form-12 Health Status Questionnaire (SF-12), 1521 Short Form-36 (SF-36), 1519 Simmonds’ disease, 202 Single-frequency BIA (SF-BIA), 444 Single photon emission computed tomography (SPECT), 1079 Sirtuin 1 (SIRT1), 706 Skinfold thickness (ST), 443–444 SLC6A4 gene, 80, 87 SLC6A4 serotonin transporter gene, 98–99 gene-environment interaction studies, in eating disorder, 101–102 genetic association studies, 99–101 psychopathological traits, in eating disorders, 101 studies of sequence, 102 Sleep and eating behavior, 1104 Sleep cycle and intrinsic timing system, 1106 Sleep deprivation, 557 and altered eating behavior, 1110 behavioral factors, 1108 and binge eating bidirectionality, 1114 experimental evidence, 1112 experimental studies, 1114 impairment in inhibitory control in response to food stimuli, 1113 population groups, 1113 biological mechanism, 1106 biological mechanisms, 1106 cognitive and neural mechanisms, 1106 defined, 1105 detrimental long-term effect, 1105 dietary patterns, 1108 and eating behavior, 1109 emotional and behavioral mechanisms, 1108, 1109 emotion regulation and vice versa, 1108 executive and cognitive functioning, 1107

1564 Sleep deprivation (cont.) executive functions and eating selfregulation, 1107 and food intake, 1105 impairment in emotional functioning or sleep quantity, 1108 metabolic consequences, 1106 sleep and the circadian rhythms, 1106 unrecognized sleep loss, 1107 Sleep disturbances, and ADHD, 134 Slow stabilizing eye movements, 586 Small for gestational age (SGA), 29, 43, 614 Smartphone, 1006 Smooth pursuit, 586 Snack-type foods, 64 Social anxiety, 678 Social desirability, 1112 Social functioning, 942, 950 Social media, 1370, 1371 addiction, 1343–1344 Sociocultural pressures, 890, 918 Sociotropy, 894, 911 Somatoform disorders, 1368–1369 South London and Maudsley Foundation Trust, 681 Sports nutrition, 112 Standardized mortality ratio, 951 Starvation-induced protein, 539 State–Trait Anxiety Inventory (STAI), 737 Steroids, 1312, 1318 Strength centrality, 1217 Stress, 546, 557, 1006, 1008 addictive properties of food, 58, 59 adverse health outcomes, 53 applications, 67 coping strategies, 66 eating behavior, 55 eating patterns (see Eating patterns) fight-or-flight pattern, 53 food intake response, 68 gastrointestinal tract, 55 harsh environmental conditions, 53 hedonics, 58, 59 high stress levels, 68 mental health crisis, 53 mental wellbeing and evidence-based recommendations, 53 non-communicable diseases, 53 overeating, 64, 65 physiological and behavioural responses, 55 physiological changes, 54 physiological homeostasis, 54 prevalence, 68

Index pro-inflammatory dietary patterns, 68 responses, 53, 54 self-management approaches, 53 undereating, 63 Stress-related psychological factors, 1028 Structural equation modelling (SEM), 893, 918 Subjective binge eating (SBE), 1147, 1506 Subjective QoL, 1457 Substance abuse, 688 Substance-related disorder, 1340, 1344 Substance use, 1339, 1340 Substance use disorders (SUDs), 225, 227 Sudden unexpected death (SUD), 656, 666 Suicidal ideation, 688 Supporting Carers of Children and Adolescents with Eating Disorders in Austria (SUCCEAT), 301 Supportive therapy (SPT), 872 Surrey Early Intervention, 300 Survey for Eating Disorders (SEDs), 1445 Sympathetic nervous system (SNS), 54 Synbiotics, 501 Systematic review, 317, 340, 345

T TaqIA polymorphism, 229 Temporal group-level models, 1225 Temporal time-series networks, 1225, 1226 Tempo-spatial dynamics, 849–850 Tertiary prevention, 278 Teruel Orthorexia Scale (TOS), 1443, 1490–1492 Test of Orthorexia Nervosa (TON-17), 1444, 1445 Testosterone, 533, 709, 770, 771 deficiency, 771 Theory of mind (TOM), 649, 651 Thin-ideal internalisation, 918 Three Factor Eating Questionnaire (TFEQ), 1045, 1065, 1472 Thromboxane, 461 Thromboxane A2 (TXA2), 456 Thyroid-binding globulin, 542 Thyroxine, 542 Time-to-conception, 27 Time trends, 201, 206, 210, 211, 213, 216, 217 Topiramate, 824 Toronto Alexithymia Scale (TAS), 316, 317, 323, 338, 341–343 Toronto Structured Interview for Alexithymia, 317

Index Total body water (TBW), 444 Total sleep deprivation, 1107 Transcranial alternate current stimulation (tACS), 993 Transcranial direct current stimulation (tDCS), 993 Transcranial magnetic stimulation (TMS), 993 Transcription factor nuclear factor-ĸB, 68 Transdiagnostic approaches, 239 Transdiagnostic cognitive behavioral theory of eating disorders, 1180 Transient lower esophageal sphincter relaxations (TLESRs), 1405, 1408 Trauma, 254–256, 263, 265, 267 Traumatic events, 237 Treatment, denial of disordered eating approach, 376 empirically supported treatment, 375, 376 modality, 376, 377 systematic review, 375 Tricyclic antidepressants (TCA), 824, 835, 836 Triglycerides, 769 Triiodothyronine, 542, 707 Tube feeding, 630, 635

U Underfeeding syndrome, 399 Undernutrition, 614 Underreporting of disordered eating behaviors scale (UDEBS), 374 Underweight, 440–444, 447 Unified Protocol, 340 Uniparental disomy (UPD), 1264 Unspecified feeding or eating disorder (UFED), 354 Unspecified/other specified eating and feeding disorders (U/OSFED) in pregnant women, 27 Uric acid (UA), 168, 174 body fluids, measurement in, 170 in central nervous system, 171 in eating disorders, 172–174 gender effects on SUA, 170–171 in neuropsychiatric disorders, 171–172 physiological roles and general pathophysiological aspects, 169–174

1565 V Vall58Met polymorphism, 229 Vegetarian diet, orthorexia nervosa, 1371 Ventral frontostriatal hypoconnectivity, 1068 Ventral tegmental area (VTA), 57, 544, 574, 985 Vergence, 586 Virtual Body Project (vBP), 187, 188, 191–193 Visceral interoception, 847 Visual attention, 594–596 Visual scan path tasks, 594 Visuospatial difficulties, 748 failure, 749 inefficiencies, 750 and mental rotation, 750 Vitamins, 1161 Voxel-based morphometry (VBM), 563 W Water, 1161 weight, 254, 258, 260 Wearable sensors, 426 Weight, 441, 443, 445–447, 514, 515, 517, 518, 522, 525, 527, 532, 534 gain, 624, 627, 629–633, 635 loss, 1084 normalization, 445–447 regain, 1085, 1086, 1092 restoration, 443, 445–447 Weissman Social Adjustment Scale, 1522 Western countries, EDs anorexia nervosa (AN), 207, 209, 210 bulimia nervosa (BN), 210, 211 epidemiological data, 207 Westernization, 216 Whole-exome sequencing analysis, in AN patients, 87 Whole-exome sequencing (WES), 102 Whole-genome sequencing (WGS), 102 World Health Organization (WHO), 206, 1354, 1530 X Xanthine oxidoreductase (XOR), 169–172 Z Zonisamide, 827