Abstract
Research on older HIV-positive (HIV+) adults finds that minorities with HIV are less educated and report less stable incomes than whites with HIV and the general population. This study assesses to what extent perceived financial hardships contributes to life satisfaction for HIV+aging African Americans. Participants were 377 African American HIV+individuals over age 50 (35% women) living in New York City. A three-step hierarchical linear regression analysis indicated that perceived financial strain for aging HIV+African Americans is a significant and independent predictor of life satisfaction (p < .001). Outreach to African Americans aging with HIV should consider how financial strain is associated with life satisfaction. Outreach should also address systemic economic disparities for African American communities that have high infection rates and a greater number of people living with HIV; these communities face a burden towards accessing effective health care and preventative care that is partially driven by limited economic resources.
Acknowledgments
This research was supported by the AIDS Community Research Initiative of America (ACRIA) and was approved by the Copernicus Group IRB (ACR01-05-018). The authors gratefully acknowledge the contributions of the research team: Philana Rowell, for her effective recruiting and assistance with testing participants; Allison Applebaum and David Ward for their assistance with data collection and entry; and Nicola Di Pietro for his assistance with data collection, entry, and analysis. The contributions of Dr. Longmire-Avital were supported through a postdoctoral fellowship in the Behavioral Sciences Training in Drug Abuse Research program sponsored by Public Health Solution of New York City at the National Development and Research Institutes (NDRI) with funding from the National Institute on Drug Abuse (5T32 DA07233).
Notes
Note. Working includes those who volunteer and/or are homemakers.
p < .05, **p < .01.
*p < .05, **p < .01, ***p < .001.
Note. Sample size due to incomplete data.