Keith A Hermanstyne1, Harold D Green2,3, Ryan Cook4, Hong-Van Tieu5,6, Typhanye V Dyer7, Christopher Hucks-Ortiz8, Leo Wilton9,10, Carl Latkin11, Steven Shoptaw12. 1. Department of Psychiatry, UCSF Weil Institute for Neurosciences, University of California, San Francisco, CA. 2. Indiana University Network Science Institute, Bloomington, IN. 3. Center for Applied Network Analysis and Systems Science, RAND Corporation, Santa Monica, CA. 4. Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA. 5. Laboratory of Infectious Disease Prevention, New York Blood Center, New York, NY. 6. Division of Infectious Diseases, Department of Medicine, Columbia University Medical Center, New York, NY. 7. Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD. 8. Division of HIV Services, JWCH Institute, Los Angeles, CA. 9. Department of Human Development, State University of New York at Binghamton, Binghamton, NY. 10. Faculty of Humanities, University of Johannesburg, Johannesburg, South Africa. 11. Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. 12. Department of Family Medicine, University of California, Los Angeles, CA.
Abstract
BACKGROUND AND SETTING: Black men who have sex with men (BMSM) in the United States have disproportionately high HIV infection rates. Social networks have been shown to influence HIV risk behavior; however, little is known about whether they affect the risk of HIV seroconversion. This study uses data from the BROTHERS (HPTN 061) study to test whether contextual factors related to social networks are associated with HIV seroconversion among BMSM. METHODS: We analyzed data from the BROTHERS study (2009-2011), which examined a multicomponent intervention for BMSM in 6 US cities. We ran a series of Cox regression analyses to examine associations between time-dependent measures of network support (personal/emotional, financial, medical, and social participation) and time to HIV seroconversion. We ran unadjusted models followed by models adjusted for participant age at enrollment and study location. RESULTS: A total of 1000 BMSM tested HIV negative at baseline and were followed at 6- and 12-month study visits. Twenty-eight men tested HIV positive. In adjusted hazard ratio models, study participants who remained HIV negative had higher proportions of social network members who provided personal/emotional {0.92 [95% confidence interval (CI): 0.85 to 0.99]}, medical [0.92 (95% CI: 0.85 to 0.99)], or social participation [0.91 (95% CI: 0.86 to 0.97)] support. CONCLUSION: Findings suggest that the increased presence of social network support can be protective against HIV acquisition. Future research should explore the processes that link social network support with sexual and other transmission risk behaviors as a basis to inform HIV prevention efforts.
BACKGROUND AND SETTING: Black men who have sex with men (BMSM) in the United States have disproportionately high HIV infection rates. Social networks have been shown to influence HIV risk behavior; however, little is known about whether they affect the risk of HIV seroconversion. This study uses data from the BROTHERS (HPTN 061) study to test whether contextual factors related to social networks are associated with HIV seroconversion among BMSM. METHODS: We analyzed data from the BROTHERS study (2009-2011), which examined a multicomponent intervention for BMSM in 6 US cities. We ran a series of Cox regression analyses to examine associations between time-dependent measures of network support (personal/emotional, financial, medical, and social participation) and time to HIV seroconversion. We ran unadjusted models followed by models adjusted for participant age at enrollment and study location. RESULTS: A total of 1000 BMSM tested HIV negative at baseline and were followed at 6- and 12-month study visits. Twenty-eight men tested HIV positive. In adjusted hazard ratio models, study participants who remained HIV negative had higher proportions of social network members who provided personal/emotional {0.92 [95% confidence interval (CI): 0.85 to 0.99]}, medical [0.92 (95% CI: 0.85 to 0.99)], or social participation [0.91 (95% CI: 0.86 to 0.97)] support. CONCLUSION: Findings suggest that the increased presence of social network support can be protective against HIV acquisition. Future research should explore the processes that link social network support with sexual and other transmission risk behaviors as a basis to inform HIV prevention efforts.
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