TY - JOUR
T1 - Individual and neighborhood correlates of membership in drug using networks with a higher prevalence of HIV in New York City (2006-2009)
AU - Rudolph, Abby E.
AU - Crawford, Natalie D.
AU - Latkin, Carl
AU - Fowler, James H.
AU - Fuller, Crystal M.
N1 - Funding Information:
This work was supported by the National Institute on Drug Abuse at the National Institutes of Health (grant numbers R01 DA019964, K01 DA033879-01A1, and T32 DA023356 ).
PY - 2013/5
Y1 - 2013/5
N2 - Purpose: To identify individual- and neighborhood-level correlates of membership within high HIV prevalence drug networks. Methods: We recruited 378 New York City drug users via respondent-driven sampling (2006-2009). Individual-level characteristics and recruiter-recruit relationships were ascertained and merged with 2000 tract-level U.S. Census data. Descriptive statistics and population average models were used to identify correlates of membership in high HIV prevalence drug networks (>10.54% vs. <10.54% HIV). Results: Individuals in high HIV prevalence drug networks were more likely to be recruited in neighborhoods with greater inequality (adjusted odds ratio [AOR], 5.85; 95% confidence interval [CI], 1.40-24.42), higher valued owner-occupied housing (AOR, 1.48; 95% CI, 1.14-1.92), and a higher proportion of Latinos (AOR, 1.83; 95% CI, 1.19-2.80). They reported more crack use (AOR, 7.23; 95% CI, 2.43-21.55), exchange sex (AOR, 1.82; 95% CI, 1.03-3.23), and recent drug treatment enrollment (AOR, 1.62; 95% CI, 1.05-2.50) and were less likely to report cocaine use (AOR, 0.40; 95% CI, 0.20-0.79) and recent homelessness (AOR, 0.32; 95% CI, 0.17-0.57). Conclusions: The relationship between exchange sex, crack use, and membership within high HIV prevalence drug networks may suggest an ideal HIV risk target population for intervention. Coupling network-based interventions with those adding risk-reduction and HIV testing/care/adherence counseling services to the standard of care in drug treatment programs should be explored in neighborhoods with increased inequality, higher valued owner-occupied housing, and a greater proportion of Latinos.
AB - Purpose: To identify individual- and neighborhood-level correlates of membership within high HIV prevalence drug networks. Methods: We recruited 378 New York City drug users via respondent-driven sampling (2006-2009). Individual-level characteristics and recruiter-recruit relationships were ascertained and merged with 2000 tract-level U.S. Census data. Descriptive statistics and population average models were used to identify correlates of membership in high HIV prevalence drug networks (>10.54% vs. <10.54% HIV). Results: Individuals in high HIV prevalence drug networks were more likely to be recruited in neighborhoods with greater inequality (adjusted odds ratio [AOR], 5.85; 95% confidence interval [CI], 1.40-24.42), higher valued owner-occupied housing (AOR, 1.48; 95% CI, 1.14-1.92), and a higher proportion of Latinos (AOR, 1.83; 95% CI, 1.19-2.80). They reported more crack use (AOR, 7.23; 95% CI, 2.43-21.55), exchange sex (AOR, 1.82; 95% CI, 1.03-3.23), and recent drug treatment enrollment (AOR, 1.62; 95% CI, 1.05-2.50) and were less likely to report cocaine use (AOR, 0.40; 95% CI, 0.20-0.79) and recent homelessness (AOR, 0.32; 95% CI, 0.17-0.57). Conclusions: The relationship between exchange sex, crack use, and membership within high HIV prevalence drug networks may suggest an ideal HIV risk target population for intervention. Coupling network-based interventions with those adding risk-reduction and HIV testing/care/adherence counseling services to the standard of care in drug treatment programs should be explored in neighborhoods with increased inequality, higher valued owner-occupied housing, and a greater proportion of Latinos.
KW - Drug use
KW - HIV
KW - Inequality
KW - Neighborhoods
KW - Networks
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U2 - 10.1016/j.annepidem.2013.02.006
DO - 10.1016/j.annepidem.2013.02.006
M3 - Article
C2 - 23523090
AN - SCOPUS:84876903656
SN - 1047-2797
VL - 23
SP - 267
EP - 274
JO - Annals of Epidemiology
JF - Annals of Epidemiology
IS - 5
ER -