Evidence map›Paper›PMID 35227217›Full record

ArticleBMC infectious diseases2022

HIV testing frequency and associated factors among five key populations in ten cities of China: a cross-sectional study.

Kedi Jiao, Ran Wei, Haochu Li, Eric P F Chow, Eduardo Piqueiras, Taylor Lewis, Zece Xu, Ci Ren, Wei Ma

Open access · greenAbstract read
In one paragraph

Article in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact, top 100% 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

14 citing papers in PubMed, 0 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 3 countries.

Kedi JiaoDepartment of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 West Wenhua Road, Jinan, Shandong, 250012, People's Republic of China.
Ran WeiShandong Provincial Chest Hospital, Jinan, Shandong, People's Republic of China.
Haochu LiDepartment of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 West Wenhua Road, Jinan, Shandong, 250012, People's Republic of China.
Eric P F ChowMelbourne Sexual Health Centre, Alfred Health, Carlton, Australia.
Eduardo PiqueirasDepartment of Anthropology, School of Social Work, Wayne State University, Detroit, MI, USA.
Taylor LewisResearch Triangle Institute (RTI) International, Washington, DC, USA.
Zece XuDepartment of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 West Wenhua Road, Jinan, Shandong, 250012, People's Republic of China.
Ci RenDepartment of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 West Wenhua Road, Jinan, Shandong, 250012, People's Republic of China.
Wei MaDepartment of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 West Wenhua Road, Jinan, Shandong, 250012, People's Republic of China. weima@sdu.edu.cn.
Shandong University · CNRTI International · USShandong Chest Hospital · CNThe University of Melbourne · AUWayne State University · US

Funding

National Health and Medical Research Council (NHMRC) Investigator Grant GNT1172873National Key Research and Development Program of China 2017YFE0103800National Science and Technology Major Project 2018ZX10721102-003-004
6 · The paper itself

Abstract

backgroundRegular HIV testing is the best way to detect people living with HIV promptly, yet not much is known about the characteristics of frequent, voluntary testers. This study explores factors related to HIV testing frequency among five key populations in China including men who have sex with men (MSM), female sex workers (FSWs), people who use drugs (PWUD), men who have casual sex with women (MCSW) and sero-negative partners among sero-discordant couples (SNPs).

methodsWe conducted a cross-sectional study in ten cities of China from November 2018 to September 2019 using convenience sampling to recruit participants. Univariate and multivariate partial proportional odds models were adopted to compare socio-behavioral factors associated with HIV testing frequencies among the five key populations.

resultsAmong the 2022 recruited participants, 36.6% reported not testing for HIV in the past year, whereas 37.0% tested once and 26.4% tested twice. Compared with MSM, FSWs (AOR = 1.97, 95% CI: 1.36-2.86) and SNPs (AOR = 3.63, 95% CI: 2.40-5.49) were more likely to test for HIV, but MCSW (AOR = 0.23, 95% CI: 0.17-0.32) were less likely. Additionally, SNPs (AOR = 4.02, 95% CI: 2.78-5.83) were more likely to be frequent HIV testers, while FSWs (AOR = 0.49, 95% CI: 0.32-0.76) and MCSW (AOR = 0.29, 95% CI: 0.20-0.41) were less likely to be frequent testers. Factors identified as barriers to HIV testing include the following: higher education level and > 5000 CNY monthly income for FSWs; elder age and a married/cohabitating status for PWUD; reported alcohol use for MCSW; and non-Han ethnicity and non-local household for SNPs. Facilitators to frequent testing included the following: higher education level for MSM and SNPs; higher AIDS knowledge score for MSM and PWUD; > 5000 CNY monthly income for FSWs and PWUD; and reporting high-risk sexual behaviors for MSM, FSW and PWUD.

conclusionsHIV testing frequencies and associated factors were not equivalent across the five key populations in China. Public health officials should take heed of the identified high-risk populations reporting high testing rates, perhaps with intensive and tailored behavioral interventions or biochemical prophylaxis.

Indexed as

HIV InfectionsSexual and Gender MinoritiesSex WorkersAgedChinaCitiesCross-Sectional StudiesFemaleHIV TestingHomosexuality, MaleHumansMaleSexual BehaviorAssociated factorsChinaHIV/AIDSHIV testingKey populations

Identifiers

PMID35227217
PMCPMC8883696
OpenAlexW35227217

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.