Dataset Information

The Binge Eating Genetics Initiative (BEGIN): study protocol.

ABSTRACT:

Background

The Binge Eating Genetics Initiative (BEGIN) is a multipronged investigation examining the interplay of genomic, gut microbiota, and behavioral factors in bulimia nervosa and binge-eating disorder.

Methods

1000 individuals who meet current diagnostic criteria for bulimia nervosa or binge-eating disorder are being recruited to collect saliva samples for genotyping, fecal sampling for microbiota characterization, and recording of 30 days of passive data and behavioral phenotyping related to eating disorders using the app Recovery Record adapted for the Apple Watch.

Discussion

BEGIN examines the interplay of genomic, gut microbiota, and behavioral factors to explore etiology and develop predictors of risk, course of illness, and response to treatment in bulimia nervosa and binge-eating disorder. We will optimize the richness and longitudinal structure of deep passive and active phenotypic data to lay the foundation for a personalized precision medicine approach enabling just-in-time interventions that will allow individuals to disrupt eating disorder behaviors in real time before they occur.

Trial registration

The ClinicalTrials.gov identifier is NCT04162574. November 14, 2019, Retrospectively Registered.

SUBMITTER: Bulik CM

PROVIDER: S-EPMC7298834 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Binge Eating Genetics Initiative (BEGIN): study protocol.

Bulik Cynthia M CM Butner Jonathan E JE Tregarthen Jenna J Thornton Laura M LM Flatt Rachael E RE Smith Tosha T Carroll Ian M IM Baucom Brian R W BRW Deboeck Pascal R PR

BMC psychiatry 20200616 1

<h4>Background</h4>The Binge Eating Genetics Initiative (BEGIN) is a multipronged investigation examining the interplay of genomic, gut microbiota, and behavioral factors in bulimia nervosa and binge-eating disorder.<h4>Methods</h4>1000 individuals who meet current diagnostic criteria for bulimia nervosa or binge-eating disorder are being recruited to collect saliva samples for genotyping, fecal sampling for microbiota characterization, and recording of 30 days of passive data and behavioral phe ...[more]

PMID: 32546136

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Project description:BackgroundData that can be easily, efficiently, and safely collected via cell phones and other digital devices have great potential for clinical application. Here, we focus on how these data could be used to refine and augment intervention strategies for binge eating disorder (BED) and bulimia nervosa (BN), conditions that lack highly efficacious, enduring, and accessible treatments. These data are easy to collect digitally but are highly complex and present unique methodological challenges that invite innovative solutions.ObjectiveWe describe the digital phenotyping component of the Binge Eating Genetics Initiative, which uses personal digital device data to capture dynamic patterns of risk for binge and purge episodes. Characteristic data signatures will ultimately be used to develop personalized models of eating disorder pathologies and just-in-time interventions to reduce risk for related behaviors. Here, we focus on the methods used to prepare the data for analysis and discuss how these approaches can be generalized beyond the current application.MethodsThe University of North Carolina Biomedical Institutional Review Board approved all study procedures. Participants who met diagnostic criteria for BED or BN provided real time assessments of eating behaviors and feelings through the Recovery Record app delivered on iPhones and the Apple Watches. Continuous passive measures of physiological activation (heart rate) and physical activity (step count) were collected from Apple Watches over 30 days. Data were cleaned to account for user and device recording errors, including duplicate entries and unreliable heart rate and step values. Across participants, the proportion of data points removed during cleaning ranged from <0.1% to 2.4%, depending on the data source. To prepare the data for multivariate time series analysis, we used a novel data handling approach to address variable measurement frequency across data sources and devices. This involved mapping heart rate, step count, feeling ratings, and eating disorder behaviors onto simultaneous minute-level time series that will enable the characterization of individual- and group-level regulatory dynamics preceding and following binge and purge episodes.ResultsData collection and cleaning are complete. Between August 2017 and May 2021, 1019 participants provided an average of 25 days of data yielding 3,419,937 heart rate values, 1,635,993 step counts, 8274 binge or purge events, and 85,200 feeling observations. Analysis will begin in spring 2022.ConclusionsWe provide a detailed description of the methods used to collect, clean, and prepare personal digital device data from one component of a large, longitudinal eating disorder study. The results will identify digital signatures of increased risk for binge and purge events, which may ultimately be used to create digital interventions for BED and BN. Our goal is to contribute to increased transparency in the handling and analysis of personal digital device data.Trial registrationClinicalTrials.gov NCT04162574; https://clinicaltrials.gov/ct2/show/NCT04162574.International registered report identifier (irrid)DERR1-10.2196/38294.

Project description:BackgroundBinge eating (BE), characterized by eating a large amount of food accompanied by a sense of loss of control over eating, is a public health crisis. Negative affect is a well-established antecedent for BE. The affect regulation model of BE posits that elevated negative affect increases momentary risk for BE, as engaging in BE alleviates negative affect and reinforces the behavior. The eating disorder field's capacity to identify moments of elevated negative affect, and thus BE risk, has exclusively relied on ecological momentary assessment (EMA). EMA involves the completion of surveys in real time on one's smartphone to report behavioral, cognitive, and emotional symptoms throughout the day. Although EMA provides ecologically valid information, EMA surveys are often delivered only 5-6 times per day, involve self-report of affect intensity only, and are unable to assess affect-related physiological arousal. Wearable, psychophysiological sensors that measure markers of affect arousal including heart rate, heart rate variability, and electrodermal activity may augment EMA surveys to improve accurate real-time prediction of BE. These sensors can objectively and continuously measure biomarkers of nervous system arousal that coincide with affect, thus allowing them to measure affective trajectories on a continuous timescale, detect changes in negative affect before the individual is consciously aware of them, and reduce user burden to improve data completeness. However, it is unknown whether sensor features can distinguish between positive and negative affect states, given that physiological arousal may occur during both negative and positive affect states.ObjectiveThe aims of this study are (1) to test the hypothesis that sensor features will distinguish positive and negative affect states in individuals with BE with >60% accuracy and (2) test the hypothesis that a machine learning algorithm using sensor data and EMA-reported negative affect to predict the occurrence of BE will predict BE with greater accuracy than an algorithm using EMA-reported negative affect alone.MethodsThis study will recruit 30 individuals with BE who will wear Fitbit Sense 2 wristbands to passively measure heart rate and electrodermal activity and report affect and BE on EMA surveys for 4 weeks. Machine learning algorithms will be developed using sensor data to distinguish instances of high positive and high negative affect (aim 1) and to predict engagement in BE (aim 2).ResultsThis project will be funded from November 2022 to October 2024. Recruitment efforts will be conducted from January 2023 through March 2024. Data collection is anticipated to be completed in May 2024.ConclusionsThis study is anticipated to provide new insight into the relationship between negative affect and BE by integrating wearable sensor data to measure affective arousal. The findings from this study may set the stage for future development of more effective digital ecological momentary interventions for BE.International registered report identifier (irrid)DERR1-10.2196/47098.

Project description:IntroductionResearch on binge eating disorder continues to evolve and advance our understanding of recurrent binge eating.MethodsThis mixed-methods, cross-sectional survey aimed to collect information from experts in the field about clinical aspects of adult binge eating disorder pathology. Fourteen experts in binge eating disorder research and clinical care were identified based on receipt of relevant federal funding, PubMed-indexed publications, active practice in the field, leadership in relevant societies, and/or clinical and popular press distinction. Anonymously recorded semi-structured interviews were analyzed by ≥2 investigators using reflexive thematic analysis and quantification.ResultsIdentified themes included: (1) obesity (100%); (2) intentional/voluntary or unintentional/involuntary food/eating restriction (100%); (3) negative affect, emotional dysregulation, and negative urgency (100%); (4) diagnostic heterogeneity and validity (71%); (5) paradigm shifts in understanding binge eating disorder (29%); and (6) research gaps/future directives (29%).DiscussionOverall, experts call for a better understanding of the relationship between binge eating disorder and obesity, including a need for clarification around the extent to which the two health issues are separate vs. related/overlapping. Experts also commonly endorse food/eating restriction and emotion dysregulation as important components of binge eating disorder pathology, which aligns with two common models of binge eating disorder conceptualization (e.g., dietary restraint theory and emotion/affect regulation theory). A few experts spontaneously identified several paradigm shifts in our understanding of who can have an eating disorder (beyond the anorexi-centric "thin, White, affluent, cis-gendered neurotypical female" stereotype), and the various factors that can drive binge eating. Experts also identified several areas where classification issues may warrant future research. Overall, these results highlight the continual advancement of the field to better understand adult binge eating disorder as an autonomous eating disorder diagnosis.

Project description:ObjectiveAlthough several effective behavioral treatments for binge-eating disorder (BED) exist, there are racial disparities in treatment access, with African-Americans and/or Black individuals having some of the lowest rates of access to care. Little is known about the experience and treatment of binge eating (BE) and BED among Black women.MethodThis systematic review, conducted according to PRISMA guidelines, synthesizes information related to BE and BED in Black women.ResultsA total of N = 38 studies met our eligibility criteria. We did not identify any systematic risk of bias across studies. The majority of included studies used cross-sectional survey methodology, and relied on interview (EDE) and self-report measures (particularly the Binge Eating Scale, BES) for the assessment of BE. Outcomes were inconsistently measured across trials, and there are limited data on the results of evidence-based treatments for BE/BED in Black women.DiscussionAlthough Black women have similar or higher rates of BE than White women, most research on BE and BED has focused on White women, with Black individuals underrepresented in clinical trials. Future research should examine evidence-based treatments to prevent and treat BED in this population.ObjetivoAunque existen varios tratamientos conductuales que son efectivos para el Trastorno de Atracones (BED, por sus siglas en inglés), existen disparidades raciales en el acceso a tratamiento, con individuos Afroamericanos y/o personas de color teniendo algunas de las tasas más bajas de acceso al cuidado de la salud. Se sabe muy poco acerca de la experiencia y tratamiento del comer en atracones (BE, por sus siglas en inglés) y BED entre mujeres afroamericanas y/o de color. MÉTODO: Esta revisión sistemática, realizada bajo lineamientos de las guías PRISMA, sintetiza información relacionada con BE y BED en mujeres afroamericanas y/o de color.ResultadosUn total de N = 38 estudios cumplieron con nuestros criterios de elegibilidad. No identificamos ningún riesgo sistemático de sesgo entre los estudios. La mayoría de los estudios incluidos utilizaron una metodología de encuesta transversal y se basaron en la entrevista (EDE) y las medidas de autoinforme (en particular, la Binge Eating Scale, BES) para la evaluación de BE. Los resultados se midieron de manera inconsistente entre los ensayos, y hay datos limitados sobre los resultados de los tratamientos basados en la evidencia para BE/BED en mujeres afroamericanas y/o de color. DISCUSIÓN: Aunque las mujeres afroamericanas y/o de color tienen tasas similares o más altas de BE que las mujeres blancas, la mayoría de las investigaciones sobre BE y BED se han centrado en las mujeres blancas, con individuos afroamericanos y/o de color subrepresentados en ensayos clínicos. La investigación futura debería examinar los tratamientos basados en la evidencia para prevenir y tratar el BED en esta población.

Dataset Information

The Binge Eating Genetics Initiative (BEGIN): study protocol.

Background

Methods

Discussion

Trial registration

Publications

The Binge Eating Genetics Initiative (BEGIN): study protocol.

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