Evidence map›Paper›PMID 30832592›Full record

ArticleBMC infectious diseases2019

Identifying high risk subgroups of MSM: a latent class analysis using two samples.

M Kumi Smith, Gabriella Stein, Weibin Cheng, William C Miller, Joseph D Tucker

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2019. 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 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 11% of its field
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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 2 countries.

M Kumi SmithDivision of Epidemiology & Community Health, School of Public Health, University of Minnesota Twin Cities, 1300 South 2nd Street, Minneapolis, MN, 55454, USA. smi00831@umn.edu.ORCID http://orcid.org/0000-0001-5861-8100
Gabriella SteinDepartment of Biostatistics, University of North Carolina at Chapel Hill, 135 Dauer Drive, 3101 McGavran-Greenberg Hall, CB #7420, Chapel Hill, NC, 27599, USA.
Weibin ChengGuangzhou Center for Disease Control and Prevention, Department of AIDS/STD Control and Prevention, 1 Jiaochang E Rd, Guangzhou Shi, 510000, Guangdong Sheng, China.
William C MillerDivision of Epidemiology, The Ohio State University, College of Public Health, 1841 Neal Ave., 302 Cunz Hall, Columbus, OH, 43210, USA.
Joseph D TuckerDivision of Infectious Diseases, University of North Carolina at Chapel Hill, 130 Mason Farm Road, 2nd Floor, Chapel Hill, NC, 27599, USA.
University of North Carolina at Chapel Hill · USGuangzhou Center for Disease Control and Prevention · CNThe Ohio State University · USUniversity of Minnesota · US

Funding

Virology, Immunology, and Microbiology CoreP30AI050410 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVID M. MARGOLIS · 2001 to 2026
$76.9M
Spurring Innovation in HIV Testing and Linkage: A Crowdsourcing Approach -Diversity SupplementR01AI114310 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI TUCKER, JOSEPH DAVID, WEI, CHONGYI · 2014 to 2018
$3.3M
UNC-South China STD Research Training CenterD43TW009532 · FIC · UNIV OF NORTH CAROLINA CHAPEL HILL · PI COHEN, MYRON SCOTT, TUCKER, JOSEPH DAVID · 2013 to 2017
$1.3M
FIC NIH HHS D43 TW009532Fogarty Health Fellows Program R25 TW00934005S2Foundation for the National Institutes of Health R01 AI114310NIAID NIH HHS P30 AI050410NIAID NIH HHS R01 AI114310The Project for Key Medicine Discipline Construction of Guangzhou Muniscipality 2017-2019-07UNC-South China STD Research Training Centre/United States D43 TW009532
6 · The paper itself

Abstract

backgroundLatent class analyses (LCA) are increasingly being used to target specialized HIV interventions, but generalizability of emergent population structures across settings has yet to be considered. We compare LCA performed on two online samples of HIV negative Chinese men who have sex with men (MSM) to detect more generalizable latent class structures and to assess the extent to which sampling considerations impact the validity of LCA results.

methodsLCAs were performed on an 1) nationwide online survey which involved no in-person contact with study staff and a 2) sentinel surveillance survey in which participants underwent HIV and syphilis testing in the city of Guangzhou, both conducted in 2014. Models for each sample were informed by risk factors for HIV acquisition in MSM that were common to both datasets.

resultsAn LCA of the Guangzhou sentinel surveillance data indicated the presence of two relatively similar classes, differing only by the greater tendency of one to report group sex. In contrast an LCA of the nationwide survey identified three classes, two of which shared many of the same features as those identified in the Guangzhou survey, including the fact that they were mainly distinguished by group sex behaviors. The final latent class in the nationwide survey was composed of members with notably few risk behaviors.

conclusionsComparisons of the latent class structures of each sample lead us to conclude that the nationwide online sample captured a larger, possibly more representative group of Chinese MSM comprised of a larger, higher risk group and a small yet distinct lower group with few reported behaviors. The absence of a lower risk group in the Guangzhou sentinel surveillance dataset suggests that MSM recruited into studies involving free HIV/STI testing may oversample MSM with higher risk behaviors and therefore greater risk perception. Lastly, two types of higher risk MSM were emergent across both samples distinguished largely by their recent group sex behaviors. Higher odds not only of self-reported HIV infection but also of closeted tendencies and gender fluid identities in this highest risk group suggest that interacting factors drive individual and structural facets of HIV risk.

Indexed as

Homosexuality, MaleAdultChinaHIV InfectionsHumansLatent Class AnalysisMaleRisk AssessmentSelf ReportSentinel SurveillanceSexual and Gender MinoritiesSurveys and QuestionnairesSyphilis SerodiagnosisYoung AdultHIV infectionLCAMSMVulnerable populations

Identifiers

PMID30832592
PMCPMC6399860
OpenAlexW2943722140

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.