Examining Mental Health in Black Communities Using Intersectional Approaches

Abstract

Few epidemiologic studies have disaggregated U.S. Black populations when exploring the impacts of racism, at multiple levels, on mental health. Intersectionality theory, as developed by Black feminist organizers and scholars, is a useful theoretical framework for understanding the heterogeneity among U.S. Black populations and the multiple systems of power that they engage with. I apply this theory to explore how latent class analysis, grounded in Intersectionality theory, may help to critically engage with the heterogeneity among U.S. Black populations to better understand mental health. I use the 2001-2003 National Survey of American Life (NSAL) data in these studies. In the first chapter, I apply a conventional intersectional approach to explore the effects of age at migration and cultural region on mental health among U.S. Black Caribbean populations. The conventional approach I use focuses on a sample at the intersection of multiple identities and employs traditional regression models with independent exposures. I found that internalized racism, as measured by endorsing negative and rejecting positive stereotypes, was associated with poor mental health. I found the association between rejecting positive Black American and Caribbean stereotypes and psychological distress to be stronger for those who migrated before age 12, compared to U.S. born individuals. Rejecting positive Black American stereotypes was associated with a 1.15 (95% CI: 0.48, 1.81) increase in psychological distress, and for Caribbean stereotypes there was a 1.19 (95% CI: 0.29, 2.09) increase. While chapter 1 disaggregates Black Caribbean populations to an extent, there is still much left unexplored. These limitations set the foundation for the second and third chapters. In the second chapter, I use latent class analysis (LCA) as an intersectional approach to examine regional differences in mental health outcomes among U.S. Black Caribbean populations. I found four latent classes to best fit these data and each class was characterized by variables related to various markers of socioeconomic status and migration history. I found that the people characterized by the foreign-born middle aged latent profile had a lower risk for poor mental health compared to the U.S. born profile (depressive symptoms: -2.20 (95% CI: -3.96, -0.44); psychological distress: -1.12 (95% CI: -2.05, -0.19)) after adjusting for sex. However, this association was not the same across all cultural regions. Compared to the English-speaking region, the foreign-born middle age profile had higher depressive symptoms and psychological distress among people from the Spanish-speaking region and Haiti. In the third chapter, I use LCA as an intersectional approach to examine the impact of criminal legal contact on depression outcomes among African Americans and Black Caribbean people. Four latent profiles best fit these data. I found that more criminal legal contact (no contact, arrest only, arrest and incarcerated) was associated with a higher risk for major depression disorder (MDD) and depressive symptoms (CES-D), after adjusting for demographic latent classes and sex (12-MDD: 1.81 (95% CI: 1.23, 2.65); LT-MDD: 1.69 (95% CI: 1.25, 2.27); CES-D: 1.60 (95% CI: 1.08, 2.10). There were no differences found by latent class for this main association, however we did find that there were differences between latent profiles in the odds of criminal legal system contact. Black people exist at the intersection of multiple systems of oppression and privilege and their identities are not either/or. LCA, grounded in Intersectionality theory, offers nuanced narratives from data that do not reduce people down to components of their identities. This has implications for both the story we tell with data and how data can inform cross-sectional and multilevel interventions.