Correlates of Prescription Drug Misuse Among Heterosexually Active Homeless Men

ABSTRACT

Objective: Prescription drug misuse (PDM) is an emerging epidemic in the United States. This study examines the prevalence and correlates of PDM among homeless men. Homeless men experience higher risk for substance misuse and associated health problems and are particularly vulnerable to PDM and its negative health consequences. Methods: Participants were a representative probability sample of 305 heterosexually active homeless men interviewed from meal programs in the Skid Row region of Los Angeles. Interviews assessed demographics, substance use, mental health, and social networks. Logistic regression examined correlates of PDM. Results: Twenty-six percent of the study population reported PDM in the past year. PDM was more likely among homeless men suffering from posttraumatic stress disorder (PTSD) (odds ratio [OR] = 2.41, 95% confidence interval [CI]: 1.03–5.61) and among those with more substance-using social network members (OR = 1.07, 95% CI: 1.01–1.14). Decreased PDM was associated with good health (OR = 0.34, 95% CI: 0.16–0.75). Conclusions: The prevalence of PDM is higher among the homeless men in this study than in the general population. Correlates of PDM included PTSD and poor health, suggesting that homeless men may use PDM to self-medicate. PDM was also associated with increased substance-using social network alters. Physical and mental health and social context are important aspects to consider in prevention efforts to reduce PDM among homeless men.

Keywords:

• Homeless men
• mental health
• prescription drug misuse
• PTSD
• social networks

Acknowledgments

This research was supported by grant R01HD059307 from the National Institute of Child Health and Human Development.

The authors thank the men who shared their experiences with the authors, the service agencies in the Skid Row area that collaborated in this study, and the RAND Survey Research Group for assistance in data collection. The authors also thank Daniela Golinelli, PhD, for her contributions to the study sampling design, and David Kennedy, PhD, and Harold Green, PhD, for their contributions to the social network analysis design.