Sleep inequities at the intersections of racialized, gender, and sexual identity in the U.S.: An intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA).

OBJECTIVES: Sleep inequities are marked and persistent in the U.S., yet there remains limited research examining the patterning of adverse sleep outcomes across intersecting dimensions of social identity. This study's objective was to estimate the prevalence of short and long sleep duration across population subgroups jointly defined by racialized identity, sex, and sexual identity, and quantify inequities. METHODS: Data came from the 2022 Behavioral Risk Factor Surveillance System (N = 235,326). We implemented Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) by grouping participants into 20 intersectional social strata and fitting Bayesian multilevel logistic models to obtain intersectional social stratum-specific prevalence estimates for each outcome. Intersectional social strata were jointly defined by racialized identity (Black, Latine, White, multiracial/other) and sex/sexual identity (heterosexual-cisgender males, heterosexual-cisgender females, LGBQ-cisgender males, LGBQ-cisgender females, trans and gender nonconforming people). RESULTS: Multiply marginalized groups (e.g., people of color who are also LGBQ+) had the highest prevalence of both short and long sleep duration. CONCLUSIONS: Equity-focused policies and interventions targeting sleep health should center the needs and priorities of multiply marginalized groups who are at particularly elevated risk of both short and long sleep duration.