BACKGROUND: Substantial racial disparities exist in HIV infection among young men who have sex with men (YMSM). However, evidence suggests black YMSM do not engage in greater levels of risk behavior. Sexual networks may help explain this paradox. This study used egocentric exponential random graph models to examine variation in concurrency (ie, 2 or more simultaneous partners) and homophily (ie, same race/ethnicity partners) across race/ethnicity groups in a diverse sample of YMSM. METHODS: Data for this study come from a longitudinal cohort study of YMSM. Participants (n = 1012) provided data regarding their sexual contacts during the 6 months before their first study visit. A series of egocentric exponential random graph models examined how providing separate estimates for homophily and concurrency parameters across race/ethnicity improved the fit of these models. Networks were simulated using these parameters to examine how local network characteristics impact risk at the whole network level. RESULTS: Results indicated that homophily, but not concurrency, varied across race/ethnicity. Black participants witnessed significantly higher race/ethnicity homophily compared with white and Latino peers. Extrapolating from these models, black individuals were more likely to be in a connected component with an HIV-positive individual and closer to HIV-positive individuals. However, white individuals were more likely to be in large connected components. CONCLUSIONS: These findings suggest that high racial homophily combined with existing disparities in HIV help perpetuate the spread of HIV among black YMSM. Nonetheless, additional work is required to understand these disparities given that homophily alone cannot sustain them indefinitely.
BACKGROUND: Substantial racial disparities exist in HIV infection among young men who have sex with men (YMSM). However, evidence suggests black YMSM do not engage in greater levels of risk behavior. Sexual networks may help explain this paradox. This study used egocentric exponential random graph models to examine variation in concurrency (ie, 2 or more simultaneous partners) and homophily (ie, same race/ethnicity partners) across race/ethnicity groups in a diverse sample of YMSM. METHODS: Data for this study come from a longitudinal cohort study of YMSM. Participants (n = 1012) provided data regarding their sexual contacts during the 6 months before their first study visit. A series of egocentric exponential random graph models examined how providing separate estimates for homophily and concurrency parameters across race/ethnicity improved the fit of these models. Networks were simulated using these parameters to examine how local network characteristics impact risk at the whole network level. RESULTS: Results indicated that homophily, but not concurrency, varied across race/ethnicity. Black participants witnessed significantly higher race/ethnicity homophily compared with white and Latino peers. Extrapolating from these models, black individuals were more likely to be in a connected component with an HIV-positive individual and closer to HIV-positive individuals. However, white individuals were more likely to be in large connected components. CONCLUSIONS: These findings suggest that high racial homophily combined with existing disparities in HIV help perpetuate the spread of HIV among black YMSM. Nonetheless, additional work is required to understand these disparities given that homophily alone cannot sustain them indefinitely.
Authors: Patrick Janulis; Brian A Feinstein; Gregory Phillips; Michael E Newcomb; Michelle Birkett; Brian Mustanski Journal: Arch Sex Behav Date: 2017-02-13
Authors: Gregorio A Millett; John L Peterson; Stephen A Flores; Trevor A Hart; William L Jeffries; Patrick A Wilson; Sean B Rourke; Charles M Heilig; Jonathan Elford; Kevin A Fenton; Robert S Remis Journal: Lancet Date: 2012-07-20 Impact factor: 79.321
Authors: Jocelyn T Warren; S Marie Harvey; Isaac Joel Washburn; Diana Maria Sanchez; Victor J Schoenbach; Christopher R Agnew Journal: Sex Transm Dis Date: 2015-04 Impact factor: 2.830
Authors: Moira McNulty; J D Smith; Juan Villamar; Inger Burnett-Zeigler; Wouter Vermeer; Nanette Benbow; Carlos Gallo; Uri Wilensky; Arthur Hjorth; Brian Mustanski; John Schneider; C Hendricks Brown Journal: Ethn Dis Date: 2019-02-21 Impact factor: 1.847
Authors: Sophia A Hussen; Kamini Doraivelu; Daniel M Camp; Shamia J Moore; Ameeta S Kalokhe; Ryan Wade; Traci Leong; Mohammed K Ali; Eugene W Farber Journal: AIDS Behav Date: 2022-02-23
Authors: Kayo Fujimoto; Aditya Khanna; Alan G Nyitray; Jacky Kuo; Jing Zhao; Lu-Yu Hwang; Elizabeth Chiao; Anna R Giuliano; John A Schneider Journal: Sex Transm Infect Date: 2022-02-19 Impact factor: 4.199
Authors: Ann M Dennis; Andrew Cressman; Dana Pasquale; Simon D W Frost; Elizabeth Kelly; Jalila Guy; Victoria Mobley; Erika Samoff; Christopher B Hurt; Candice Mcneil; Lisa Hightow-Weidman; Monique Carry; Matthew Hogben; Arlene C Seña Journal: Clin Infect Dis Date: 2022-02-11 Impact factor: 9.079
Authors: Stephen Uong; Eli S Rosenberg; Steven M Goodreau; Nicole Luisi; Patrick Sullivan; Samuel M Jenness Journal: Epidemiology Date: 2020-03 Impact factor: 4.860
Authors: Brian Mustanski; Ethan Morgan; Richard DʼAquila; Michelle Birkett; Patrick Janulis; Michael E Newcomb Journal: J Acquir Immune Defic Syndr Date: 2019-01-01 Impact factor: 3.731