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Updated: Mar 15, 2026

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
Published on: May 10, 2022
Testing for interactive and non-linear effects of risk factors for binge eating and purging eating disorders
Karina L Allen1, Susan M Byrne2, Ross D Crosby3
1School of Psychology, The University of Western Australia, Australia; Eating Disorders Service, Maudsley Hospital, South London and Maudsley NHS Foundation Trust, UK; Institute of Psychiatry, Psychology and Neuroscience, Kings College London, UK.
Abstract:
Almost no research has tested whether risk factors interact in the prediction of future eating disorder onset, which might suggest qualitatively distinct etiologic pathways. Accordingly, this prospective study tested for possible interactions between risk factors in the prediction of binge eating and purging eating disorders in adolescents. It also examined sex differences in pathways to risk. Two analytical approaches were used: (1) classification tree analysis (CTA), which is ideally suited to identifying non-linear interactions and the optimal cut-points for defining risk, with follow-up random forest analyses; and (2) two-way interaction terms in a series of logistic regression models. Data were drawn from the Western Australian Pregnancy Cohort (Raine) Study, a population-based study that followed participants from pre-birth to young adulthood. This study involved 1297 adolescents (49% male), 146 (11%) of whom developed bulimia nervosa, binge eating disorder or purging disorder in late adolescence. In CTA, sex was the first and most potent predictor of eating disorder risk with females showing a 5-fold increase in risk relative to males. For males and females, weight and eating concerns were the next most potent predictor of risk and three risk groups emerged, reflecting non-linear risk. For females with intermediate weight and eating concerns, externalizing problems emerged as an additional predictor. Interaction terms in logistic regression models did not produce significant results after correcting for multiple testing. Findings advance knowledge on risk pathways to eating disorder onset, highlight non-linear risk processes, and provide cut-points for prospectively identifying high-risk youth for prevention programs.
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