Can platform use patterns be an indicator of HIV-related risk and sub-group heterogeneity among men who have sex with men in Singapore

A latent class analysis

Bibliographic Data

ID22078738
AuthorsIsabel Tavitian-Exley (0000-0002-5202-0041, National Centre for Infectious Diseases, corresponding author), Hao Ying (0000-0003-0824-9348, National Centre for Infectious Diseases), Ying Hao (0000-0001-5053-4850), Mark I-Cheng Chen (0000-0001-9369-5830, National Centre for Infectious Diseases), Chen Seong Wong (0000-0003-3127-2853, National Centre for Infectious Diseases), Chronos Kwok, Matthias Paul Han Sim Toh (National University of Singapore)
Year2024
Volume12
Pages1330282-1330282
Publication date2024-04-26
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2024.1330282
PMID38737858
OpenAlexW4395674802
LanguageEN
References cited35

Introduction Low-level HIV epidemic settings like Singapore face the challenge of reaching men at-risk who have less contact with programmes. We investigated patterns of meeting platform use by men seeking male sexual partners (MSM) as potential marker of risk to differentiate sub-groups for interventions. Methods Latent Class Analysis (LCA) was applied to a survey sample of MSM recruited from bars/clubs, saunas and a smartphone application, using purposive sampling. The best-fit LCA model which identified homogeneous sub-groups with similar patterns of meeting platform was factored in multivariable regression to identify associations with risk behaviors on the pathway to HIV infection. Results Overall 1,141 MSM were recruited from bars/clubs ( n = 426), saunas ( n = 531), and online ( n = 184). Five patterns emerged, reflecting salient platform use characteristics: Sauna-centric (SC; n = 413), App-centric (AC; n = 276), Multiple-platforms (MP; n = 123), Platform-inactive (PI; n = 257), and “Do not hook up” (DNH; n = 72) classes. Men in the SC and MP classes had high probabilities of using saunas to meet partners; SC were older and less likely to have disclosed their sexual orientation. The MP class had high probabilities of connecting across all platforms in addition to saunas and more likely to have disclosed their sexual orientation, than the PI class. Men in the SC and MP classes had twice the odds of reporting multiple sex partners (aOR SC = 2.1; 95%CI: 1.33.2; aOR MP = 2.2; 95%CI: 1.14.6). Single/non-partnered MSM and those using alcohol/drugs during sex had 1.7 (95%CI: 1.22.5) and 3.2 (95%CI: 2.05.1) the odds respectively, of reporting multiple sex partners. The SC and MP classes had higher odds of engaging in group sex while MSM using alcohol/drugs during sex had twice the odds of reporting group sex. Alcohol/drugs and group sex were independently associated with condomless sex (as was lower education). Group sex, alcohol/drugs during sex, disclosure of sexual orientation or being Singaporean/permanent resident were associated with recent testing for HIV. Discussion The five distinct risk profiles identified can help tailor differentiated HIV interventions—combined with field knowledge and other prevention—to expand HIV self-testing, Pre-Exposure Prophylaxis and other services (e.g., Mpox vaccination) to sub-groups at risk

Family medicine · Latent class model · Machine learning · Men who have sex with men · Sociology · Adolescent Sexual and Reproductive Health · Computer Science · Demography · HIV/AIDS Research and Interventions · Medicine · Mobile Health and mHealth Applications · Psychology · Gerontology

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