# Reducing Black Men's Drug Use and Co-Occurring Negative Mental and Physical Health Outcomes: Intersectionality, Social-Structural Stressors, and Protective Factors

> **NIH NIH R01** · GEORGE WASHINGTON UNIVERSITY · 2021 · $632,829

## Abstract

PROJECT SUMMARY/ABSTRACT
Health inequities among Black men in the U.S. are stark. Drug use contributes to six of the top ten leading
causes of death among Black men ages 18 to 54. Social-structural stressors such as discrimination, based on
race or race and sexual identity, and drug use to cope with stress, are well-documented pathways to drug use
among Black adults. Empirical evidence that drug use co-occurs with other negative health outcomes
underscores an urgent public health need to examine drug use and other co-occurring negative health
outcomes associated with social-structural stressors. Single-axis perspectives—either race or sexual identity—
dominate drug use and health disparities research. Apart from HIV/AIDS research, research on the effects of
social-structural stressors on Black men’s drug use and co-occurring negative health outcomes at the
intersection of sexual identity (i.e., heterosexual, sexual minority) and socioeconomic position (SEP) is virtually
nonexistent. Critical gaps also exist about how protective factors (e.g., resilience, religiosity, positive
racial/sexual identity) influence the effects of social-structural stressors on Black men’s drug use and co-
occurring negative health outcomes. To address these critical gaps, a longitudinal cross-lagged explanatory-
sequential (QUANT→qual) mixed methods study is proposed to test, via structural equation modeling, a
conceptual model of social-structural stressors, protective factors, and drug use (alcohol, marijuana, nicotine,
illicit drug use) and co-occurring negative mental (e.g., psychological distress) and physical (e.g., blood
pressure) health outcomes among Black men at the intersection of sexual identity and SEP. Purposive quota
sampling will be used to recruit 960 Black men, ages 18-54, stratified by sexual identity and SEP (240/group)
in Washington, DC. Phase I includes the collection of self-reported social-structural stressors, protective
factors, drug use, and mental health data, and objective drug use (i.e., urine toxicology) and physical health
(e.g., blood pressure) data at Time 1, and 3 months later at Time 2 (Aims 1, 2). Blood samples will be collected
at Time 2 only to assess cardiovascular disease biomarkers (e.g., total cholesterol). Phase II includes 4 focus
groups with 6-8 Phase I participants (total n = 24 to 32) purposively sampled to explain Phase I results (Aim 3).
Phase III involves a synthesis and validity assessment of the quantitative and qualitative results (Aim 3). The
proposed research uses intersectionality, social-structural stress, and resilience theoretical frameworks to
advance new and important knowledge about the extent to which social-structural stressors and protective
factors influence drug use and co-occurring negative health outcomes among Black men at the intersection of
sexual identity and SEP. This intersectional focus represents a paradigmatic shift from conventional single-axis
and one-size-fits-all intervention approaches....

## Key facts

- **NIH application ID:** 10149978
- **Project number:** 5R01DA045773-04
- **Recipient organization:** GEORGE WASHINGTON UNIVERSITY
- **Principal Investigator:** Ingrid Alisa Bowleg
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $632,829
- **Award type:** 5
- **Project period:** 2018-07-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10149978

## Citation

> US National Institutes of Health, RePORTER application 10149978, Reducing Black Men's Drug Use and Co-Occurring Negative Mental and Physical Health Outcomes: Intersectionality, Social-Structural Stressors, and Protective Factors (5R01DA045773-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10149978. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*