Background
Sexual networks may
place U.S. Black men who have sex with men (MSM) at increased HIV risk.
Methods
Self-reported egocentric
sexual network data from the prior six months were collected from 1,349
community-recruited Black MSM in HPTN 061, a multi-component HIV prevention
intervention feasibility study. Sexual network composition, size, and density
(extent to which members are having sex with one another) were compared by
self-reported HIV serostatus and age of the men. GEE models assessed network
and other factors associated with having a Black sex partner, having a partner
with at least two age category difference (age difference between participant
and partner of at least two age group categories), and having
serodiscordant/serostatus unknown unprotected anal/vaginal intercourse (SDUI)
in the last six months.
Results
Over half had
exclusively Black partners in the last six months, 46% had a partner of at
least two age category difference, 87% had ≤5 partners. Nearly 90% had sex
partners who were also part of their social networks. Among HIV-negative men,
not having anonymous/exchange/ trade partners and lower density were associated
with having a Black partner; larger sexual network size and having non-primary
partners were associated with having a partner with at least two age category
difference; and having anonymous/exchange/ trade partners was associated with
SDUI. Among HIV-positive men, not having non-primary partners was associated
with having a Black partner; no sexual network characteristics were associated
with having a partner with at least two age category difference and SDUI.
Conclusions
Black MSM sexual
networks were relatively small and often overlapped with the social networks.
Sexual risk was associated with having non-primary partners and larger network
size. Network interventions that engage the social networks of Black MSM, such
as interventions utilizing peer influence, should be developed to address
stable partnerships, number of partners, and serostatus disclosure.
Sex Partner Characteristics, Condom Use, and HIV Serostatus Disclosure of Community-Recruited Black MSM, Partner-Level Data (N = 4,449 Partners).
| Characteristic, n (%)a | Total | Self-Reported HIV-Positive Participant | Self-Reported HIV-Negative Participant | P-value |
|---|---|---|---|---|
| Partner Level | ||||
| Gender of sex partners | <0.01 | |||
| Male | 3464 (78) | 308 (92) | 3156 (77) | |
| Female | 800 (18) | 18 (5) | 782 (19) | |
| Transgender | 172 (4) | 7 (2) | 165 (4) | |
| Partner type | <0.01 | |||
| Primary partner | 707 (16) | 80 (24) | 627 (15) | |
| Steady, non-primary partner/casual partner | 3003 (68) | 210 (63) | 2793 (68) | |
| Exchange or trade partner/anonymous partner | 716 (16) | 42 (13) | 674 (16) | |
| HIV serostatus of sex partners | <0.01 | |||
| Among all participants (N = 4446 partners): | 2284 (51) | 67 (20) | 2217 (54) | |
| HIV-negative | 311 (7) | 142 (43) | 169 (4) | |
| HIV-positive | 1841 (41) | 124 (37) | 1717 (42) | |
| HIV serostatus of sex partners | <0.01 | |||
| Among participants age 18–30 years (N = 1659 partners): | 1023 (62) | 17 (23) | 1006 (63) | |
| HIV-negative | 66 (4) | 22 (30) | 44 (3) | |
| HIV-positive | 570 (34) | 35 (47) | 535 (34) | |
| HIV serostatus of sex partners | <0.01 | |||
| Among participants age 31+ years (N = 2777 partners): | 1261 (45) | 50 (19) | 1211 (48) | |
| HIV-negative | 245 (9) | 120 (46) | 125 (5) | |
| HIV-positive | 1271 (46) | 89 (34) | 1182 (47) | |
| Frequency of condom use with sex in past 6 months (N = 4361 partners) | 0.01 | |||
| Never | 1899 (44) | 171 (52) | 1728 (43) | |
| Sometimes | 740 (17) | 52 (16) | 688 (17) | |
| Most of the time | 398 (9) | 18 (5) | 380 (9) | |
| Always | 1324 (30) | 88 (27) | 1236 (31) | |
| Disclosure of HIV status to sex partners by self-reported HIV-positive participants (N = 309 partners) | - | - | - | |
| No | 106 (34) | |||
| Yes | 191 (62) | |||
| Don’t know/refused to answer | 12 (4) |
Numbers may not add up to column total due to missing data.
a P-value <0.05 for all variables compared by study city. Site-specific differences may be reflective of different recruitment strategies used by the study sites, rather than of overall differences between cities.
Full article at:
By:
William M. Switzer, Editor
1Laboratory of Infectious Disease
Prevention, Lindsley F. Kimball Research Institute, New York Blood Center, New
York, NY, United States of America
2Division of Infectious Diseases,
Department of Medicine, Columbia University Medical Center, New York, NY,
United States of America
3Vaccine and Infectious Disease Division,
Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
4Division of Infectious Diseases, Emory
School of Medicine, Atlanta, GA, United States of America
5Bridge HIV, San Francisco Department of
Public Health, San Francisco, CA, United States of America
6Department of Human Development, State
University of New York at Binghamton, Binghamton, NY, United States of America
7Faculty of Humanities, University of
Johannesburg, Johannesburg, South Africa
8Department of Epidemiology, School of
Public Health, Division of InfectiousDiseases, David Geffen School of Medicine,
University of California, Los Angeles, Los Angeles, CA, United States of
America
9Fenway Community Health Center, Boston,
MA, United States of America
10FHI 360, Research Triangle Park, NC,
United States of America
11Division of AIDS, National Institute of
Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD,
United States of America
12The George Washington University School of
Public Health and Health Services, Department of Epidemiology and
Biostatistics, Washington, DC, United States of America
13Johns Hopkins University School of
Medicine, Baltimore, MD, United States of America
14Johns Hopkins Bloomberg School of Public
Health, Baltimore, MD, United States of America
Centers for
Disease Control and Prevention, UNITED STATES
Competing Interests: The
authors have declared that no competing interests exist.
Conceived and designed the experiments: HVT BAK CL.
Performed the experiments: HVT TYL LW SB LW PG KM SG CK VE GP VC BAK CL.
Analyzed the data: HVT TYL LW MC BAK CL. Wrote the paper: HVT SH BAK CL.
* E-mail: gro.retnecdoolbyn@ueith
More at: https://twitter.com/hiv insight
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