Dominant narratives of prescription opioid misuse (POM) in the U.S. have portrayed it as an issue primarily affecting White communities. In this study we explore POM as reported in data from the 2015 National Survey on Drug Use and Health, using an intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). We map the risk of POM through a series of multilevel models with individuals (N = 43,409) nested within strata formed by the intersections of gender, race/ethnicity, income, and age. We find meaningful heterogeneity between and within strata. The ten strata with the greatest risk for POM were comprised of individuals identifying as White, African American, and non-White Hispanic, and included individuals of low, medium, and high income. We uncover intersections of social position with high risk for POM that are often excluded from dominant narratives, including young high-income African American women. Intersectional approaches are essential for advancing our understanding of health inequalities and unfolding epidemics such as that of POM in the U.S.
- SoE Centre for Multilevel Modelling
- opioid misuse
- health inequalities