Publication date: January 2019
Source: Social Science & Medicine, Volume 220
Author(s): Clare R. Evans, Natasha Erickson
Depression in adolescents and young adults remains a pressing public health concern and there is increasing interest in evaluating population-level inequalities in depression intersectionally. A recent advancement in quantitative methods—multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA)—has many practical and theoretical advantages over conventional models of intercategorical intersectionality, including the ability to more easily evaluate numerous points of intersection between axes of marginalization. This study is the first to apply the MAIHDA approach to investigate mental health outcomes intersectionally in any population. We examine intersectionality and depression among adolescents and young adults in the U.S. along dimensions of gender, race/ethnicity, immigration status, and family income using a large, nationally representative sample—the National Longitudinal Study of Adolescent to Adult Health. We find evidence of considerable inequalities between social strata, with women, racial/ethnic minorities, immigrants, and low income strata experiencing elevated depression scores. Importantly, the majority of between-strata variation is explained by additive main effects, with no strata experiencing statistically significant residual “interaction” effects. We compare these findings to previous intersectional research on depression and discuss possible sources of differences between MAIHDA and conventional intersectional models.