Evidence map›Paper›PMID 39829637›Full record

ArticleOpen forum infectious diseases2025

Identifying High-Risk Populations for Sexually Transmitted Infections in Chinese Men Who Have Sex With Men: A Cluster Analysis.

Fang Lu, Bingyang She, Rui Zhao, Gaixia Li, Yawu Hu, Yi Liu, Min Zhao, Lei Zhang

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Article in Open forum infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
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  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Fang LuDepartment of Infectious Diseases, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.ORCID https://orcid.org/0009-0009-1194-9784
Bingyang SheDepartment of Infectious Diseases, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Rui ZhaoDepartment of Infectious Diseases, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Gaixia LiDepartment of Infectious Diseases, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Yawu HuDepartment of Infectious Diseases, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Yi LiuDepartment of Infectious Diseases, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Min ZhaoDepartment of Infectious Diseases, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Lei ZhangDepartment of Infectious Diseases, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.ORCID https://orcid.org/0000-0003-2343-084X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aimed to identify subpopulations of Chinese men who have sex with men (MSM) with distinct sexual behavioral patterns and explore their correlations with sexually transmitted infections (STIs). Methods: We recruited 892 eligible MSM in Xi'an, China, collecting sociodemographic, sexual behavior, and STI data. Cluster analysis identified distinct sexual behavioral patterns, allowing us to examine STI differences across clusters. Results: Among the 892 MSM analyzed, 3 clusters were identified. Cluster 1 (n = 157) exhibited high-risk sexual behavioral patterns, including the highest median number of sexual partners (5 vs 1 in cluster 2 vs 3 in cluster 3, Conclusions: This study identified 3 subpopulations of Chinese MSM with distinct sexual behavioral patterns. Targeted public health interventions to the most at-risk subpopulations of MSM are essential for STI prevention.

Indexed as

cluster analysismen who have sex with menprevalencesexual behavioral patternssexually transmitted infections

Identifiers

PMID39829637
PMCPMC11739803

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.