Intersectional inequalities in health anxiety: multilevel analysis of individual heterogeneity and discriminatory accuracy in the SOMA.SOC study.

Abstract

Intersectional approaches are needed to disaggregate the complex interaction of social identities contributing to (mental) health disparities. Health anxiety represents an overlooked public mental health issue. Therefore, intersectional inequalities in health anxiety were examined using multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). Analyses are based on cross-sectional data of the adult population living in Germany (N = 2,413). Health anxiety was assessed with the Whiteley Index-7. Applying intersectional MAIHDA, health anxiety in the intersectional strata of gender, history of migration, and income was predicted. Discriminatory accuracy was assessed via the intra-class correlation and the proportional change in variance. Analyses revealed additive social inequalities in health anxiety with greatest impact of low income but no clear intersectional gradient. Most affected by health anxiety were females who immigrated themselves with low income, males whose parent(s) immigrated with low income, and males who immigrated themselves with medium income. Intersectional approaches contribute to a more comprehensive understanding of (mental) health disparities. In addition to general efforts to counteract health inequalities, combining universal screening and targeted psychotherapeutic treatment seems promising to specifically reduce inequalities in health anxiety.