Neighborhood community characteristics associated with HIV disease outcomes in a cohort of urban women living with HIV

AIDS Care. 2016 Oct;28(10):1274-9. doi: 10.1080/09540121.2016.1173642. Epub 2016 Apr 21.


Recent studies have found geographic variations in immune and viral human immunodeficiency virus (HIV) disease outcomes associated with census measures of neighborhood poverty and segregation. Although readily available, such aggregate census measures are not based on health behavior models and provide limited information regarding neighborhood effect pathways. In contrast, survey-based measures can capture specific aspects of neighborhood disadvantage that may better inform community-based interventions. Therefore, the aim of this study is to assess the measurement validity of multi-dimensional survey measures of neighborhood disorder compared with census measures as predictors of HIV outcomes in a cohort of 197 low-income women in a major metropolitan area. The multi-dimensional survey measures were related to each other and to census measures of concentrated poverty and racial segregation, but not so highly correlated as to be uniform. We found notable variation between community areas in women's CD4 levels but there was no corresponding geographic variance in viral load, and relationships between community area measures and viral load disappeared after adjustment for individual characteristics, including HIV treatment adherence. In multilevel models adjusting for individual characteristics including substance use, depression, and HIV treatment adherence, one survey measure of neighborhood disadvantage (poor-quality built environment) and one census measure (racial segregation) were significantly associated with greater likelihood of CD4 < 500 (p < .05).

Keywords: HIV/AIDS; immune function; neighborhoods; urban health; women.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • CD4 Lymphocyte Count
  • Censuses*
  • Environment Design
  • Female
  • Forecasting / methods
  • HIV Infections / blood*
  • HIV Infections / drug therapy*
  • Humans
  • Medication Adherence
  • Middle Aged
  • Models, Statistical
  • Poverty
  • Residence Characteristics / statistics & numerical data*
  • Social Segregation
  • Treatment Outcome
  • Urban Population / statistics & numerical data*
  • Viral Load