Eating Disorder Severity and Treatment Outcome Across Race/Ethnicity, Sexual Orientation, and Socioeconomic Status: Intersectional Inequities in a Clinical Sample
Drury, C. R.; Beccia, A.; Shaqour, S.; Riddle, M.; Gorrell, S.; Singh, S.; Duffy, A.; Mehler, P. S.; Zucker, K.; Le Grange, D.; Rienecke, R.; Reilly, E. E.
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BackgroundMarginalized populations experience increased eating disorder (ED) risk and encounter significant barriers to treatment. Intersectionality provides a framework for understanding how systemic oppression contributes to inequities in EDs; however, intersectional approaches have yet to be applied to a clinical ED sample. The current study examined inequities in ED severity and treatment outcome across the intersections of race/ethnicity, sexual orientation, and socioeconomic status (SES). MethodsAdult women (N=3,016; M=27.2 years) with transdiagnostic EDs presenting to affiliated treatment sites across the United States completed the Eating Disorder Examination-Questionnaire (EDE-Q) at admission and discharge. Race/ethnicity and sexual orientation were self-reported; SES was measured using the area deprivation index of participants neighborhoods. Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) was used to estimate baseline EDE-Q global score; change in EDE-Q global score and binge eating, self-induced vomiting, laxative use, and driven exercise frequency from admission to discharge; and reason for discharge (routine or non-routine) across intersectional subgroups. ResultsIn this sample of women with access to treatment, MAIHDA models predicted higher baseline levels of overall ED pathology among sexual minorities (predicted M=4.10). There were few differences in ED symptom improvement across intersectional subgroups, with some small yet potentially meaningful inequities. Racially/ethnically minoritized subgroups were slightly less likely to complete treatment (predicted percent non-routine discharge=41.50%). ConclusionsFuture research should build on these findings by analyzing other dimensions of inequity (e.g., gender, weight status, disability status) to further characterize and address intersecting systems of oppression that disparately influence ED outcomes.
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