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Objective <p>HIV infection rises rapidly in YMSM (young men who have sex with men). Despite extensive promotion of risk-reduction measures, existing research lacks categorical analysis of multidimensional prevention combinations, limiting precise interventions. This study uses latent class analysis (LCA) to identify prevention behavior patterns, analyze influencing factors, and evaluate association with HIV.</p> Methods <p>From January 2021 to December 2024, 2,685 YMSM aged 15–24 in Tianjin were recruited through online and offline methods. 13 HIV-prevention indicators (one cognitive, twelve behavioral) were classified using LCA. Multinomial logistic regression analyzed associations between latent classes and demographics/intervention services factors, while differences in HIV infection across prevention behavior patterns were compared.</p> Results <p>Four distinct HIV prevention classes emerged: “High-Risk Perception with Biomedical Reliance” (Class 1; 16.61%), “Low-Risk Perception with Condom Reliance” (Class 2; 16.72%), “Low-Risk Perception with Low Protection” (Class 3; 29.39%), and “High-Risk Perception with Partner &amp; Barrier Strategy” (Class 4; 37.28%). Multinomial logistic regression showed that students were less likely to be classified into Class 1 (aOR = 0.56, 95%CI: 0.42–0.76) and Class 2 (aOR = 0.75, 95%CI: 0.57–0.97), and more likely to belong to Class 3. Online partner-seekers were less likely to fall into Class 2 (aOR = 0.58, 95%CI: 0.37–0.90) and Class 4 (aOR = 0.24, 95%CI: 0.17–0.36), and more prone to Class 3. For intervention services, those who received condom promotion or HIV counseling and testing were more likely to be categorized into Class 1 (aOR = 6.78, 95%CI: 4.20–10.95), Class 2 (aOR = 2.65, 95%CI: 1.86–3.77), and Class 4 (aOR = 10.64, 95%CI: 7.65–14.80), whereas peer education was negatively associated with Class 2 (aOR = 0.63, 95% CI: 0.44–0.91) and Class 4 (aOR = 0.34, 95% CI: 0.25–0.47). HIV analysis revealed Class 3 had the highest HIV positivity rate (6.60%, 95% CI: 5.08–8.77), followed by Class 1 (2.26%, 95% CI: 1.11–4.54) and Class 4 (2.20%, 95% CI: 1.20–3.32), with Class 2 showing the lowest rate (0.83%, 95% CI: 0.28–2.45).</p> Conclusion <p>Among YMSM, HIV prevention behavior is highly heterogeneous. The highest-risk subgroup—“Low-Risk Perception with Low Protection”—should be prioritized, particularly among students and online partner-seekers. Peer education programs may require further optimization, while integrated prevention strategies should combine condom use, biomedical tools, and both online and offline delivery channels.</p>

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The impact of HIV prevention behavior patterns on infection risk among young men who have sex with men: a latent class analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月30日

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  • Xiaoyan Zhang,
  • Jingran Dong,
  • Miaomiao Li,
  • Xiaoping Zhan,
  • Zhan Lin,
  • Junfeng Zhang,
  • Jie Yang,
  • Maohe Yu,
  • Jianyun Bai,
  • Yi Liu,
  • Changping Li,
  • Zhuang Cui

摘要

Objective

HIV infection rises rapidly in YMSM (young men who have sex with men). Despite extensive promotion of risk-reduction measures, existing research lacks categorical analysis of multidimensional prevention combinations, limiting precise interventions. This study uses latent class analysis (LCA) to identify prevention behavior patterns, analyze influencing factors, and evaluate association with HIV.

Methods

From January 2021 to December 2024, 2,685 YMSM aged 15–24 in Tianjin were recruited through online and offline methods. 13 HIV-prevention indicators (one cognitive, twelve behavioral) were classified using LCA. Multinomial logistic regression analyzed associations between latent classes and demographics/intervention services factors, while differences in HIV infection across prevention behavior patterns were compared.

Results

Four distinct HIV prevention classes emerged: “High-Risk Perception with Biomedical Reliance” (Class 1; 16.61%), “Low-Risk Perception with Condom Reliance” (Class 2; 16.72%), “Low-Risk Perception with Low Protection” (Class 3; 29.39%), and “High-Risk Perception with Partner & Barrier Strategy” (Class 4; 37.28%). Multinomial logistic regression showed that students were less likely to be classified into Class 1 (aOR = 0.56, 95%CI: 0.42–0.76) and Class 2 (aOR = 0.75, 95%CI: 0.57–0.97), and more likely to belong to Class 3. Online partner-seekers were less likely to fall into Class 2 (aOR = 0.58, 95%CI: 0.37–0.90) and Class 4 (aOR = 0.24, 95%CI: 0.17–0.36), and more prone to Class 3. For intervention services, those who received condom promotion or HIV counseling and testing were more likely to be categorized into Class 1 (aOR = 6.78, 95%CI: 4.20–10.95), Class 2 (aOR = 2.65, 95%CI: 1.86–3.77), and Class 4 (aOR = 10.64, 95%CI: 7.65–14.80), whereas peer education was negatively associated with Class 2 (aOR = 0.63, 95% CI: 0.44–0.91) and Class 4 (aOR = 0.34, 95% CI: 0.25–0.47). HIV analysis revealed Class 3 had the highest HIV positivity rate (6.60%, 95% CI: 5.08–8.77), followed by Class 1 (2.26%, 95% CI: 1.11–4.54) and Class 4 (2.20%, 95% CI: 1.20–3.32), with Class 2 showing the lowest rate (0.83%, 95% CI: 0.28–2.45).

Conclusion

Among YMSM, HIV prevention behavior is highly heterogeneous. The highest-risk subgroup—“Low-Risk Perception with Low Protection”—should be prioritized, particularly among students and online partner-seekers. Peer education programs may require further optimization, while integrated prevention strategies should combine condom use, biomedical tools, and both online and offline delivery channels.