HPTN Bibliographic Record
Momplaisir, F., Hussein, M., Tobin-Fiore, D., Smith, L., Bennett, D., Latkin, C., Metzger, D. S.. Racial Inequities in HIV Prevalence and Composition of Risk Networks Among People Who Inject Drugs in HIV Prevention Trial Network 037. J Acquir Immune Defic Syndr. 2018, 76: 394-401. PMC5884106
BACKGROUND: HIV prevention interventions in the United States have failed to eliminate racial inequities. Here, we evaluate factors associated with racial inequities in HIV prevalence among people who inject drugs using HIV Prevention Trial Network 037 data. METHODS: We measured racial homophily (ie, all members share the same race), being in an HIV+ network (network with >/=1 HIV+ member), and drug and sex risk behaviors. A 2-level logistic regression with a random intercept evaluated the association between being in an HIV+ network and race adjusting for individual-level and network-level factors. RESULTS: Data from 232 index participants and 464 network members were included in the analysis. Racial homophily was high among blacks (79%) and whites (70%); 27% of all-black, 14% of all-white, and 23% of racially mixed networks included HIV+ members. Sex risk was similar across networks, but needle sharing was significantly lower in all-black (23%) compared with all-white (48%) and racially mixed (46%) networks. All-black [adjusted odds ratio (AOR), 3.6; 95% confidence interval (CI), 1.4 to 9.5] and racially mixed (AOR, 2.0; 95% CI: 1.1 to 3.7) networks were more likely to include HIV+ network members; other factors associated with being in HIV+ network included homelessness (AOR, 2.0; 95% CI, 1.2 to 3.2), recent incarceration (AOR, 0.4; 95% CI, 0.2 to 0.7), and cocaine injection (AOR, 1.7; 95% CI, 1.0 to 2.7). Risk behaviors were not associated with being in an HIV+ network. CONCLUSION: Despite having lower drug risk behavior, all-black networks disproportionately included HIV+ members. HIV prevention interventions for people who inject drugs need to go beyond individual risk and consider the composition of risk networks.