Evidence map›Paper›PMID 38769474›Full record

ArticleBMC public health2024

Factors associated with antiretroviral treatment adherence among people living with HIV in Guangdong Province, China: a cross sectional analysis.

Jun Liu, Yao Yan, Yan Li, Kaihao Lin, Yingqian Xie, Zhimin Tan, Qicai Liu, Junbin Li, Lihua Wang, Yi Zhou and 13 more

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Predictors of depression and suicidality among children and adolescents living with HIV and AIDS.The South African journal of psychiatry : SAJP : the journal of the Society of Psychiatrists of South Africa · 2025
    Article
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

23 authors.

Jun Liu *Department of HIV/AIDS Control and Prevention, Guangdong Provincial Center for Disease Control and Prevention, No. 160 Qunxian Road, Panyu District Guangzhou, Guangzhou, China.
Yao Yan *Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, No. 283 Jianghai Road, Haizhu District, Guangzhou, 510310, China.
Yan LiDepartment of HIV/AIDS Control and Prevention, Guangdong Provincial Center for Disease Control and Prevention, No. 160 Qunxian Road, Panyu District Guangzhou, Guangzhou, China.
Kaihao LinDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, No. 283 Jianghai Road, Haizhu District, Guangzhou, 510310, China.
Yingqian XieDepartment of HIV/AIDS Control and Prevention, Guangdong Provincial Center for Disease Control and Prevention, No. 160 Qunxian Road, Panyu District Guangzhou, Guangzhou, China.
Zhimin TanDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, No. 283 Jianghai Road, Haizhu District, Guangzhou, 510310, China.
Qicai LiuGuangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
Junbin LiGuangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
Lihua WangJiangmen Center for Disease Control and Prevention, Jiangmen, China.
Yi ZhouZhuhai Center for Disease Control and Prevention, Zhuhai, China.
Gang YaoZhuhai Center for Disease Control and Prevention, Zhuhai, China.
Shanzi HuangZhuhai Center for Disease Control and Prevention, Zhuhai, China.
Chenglong YeYangjiang Center for Disease Control and Prevention, Yangjiang, China.
Meixi CenYunfu Center for Disease Control and Prevention, Yunfu, China.
Xiaowen LiaoYunfu Center for Disease Control and Prevention, Yunfu, China.
Lu XuShantou Center for Disease Control and Prevention, Shantou, China.
Chi ZhangShantou Center for Disease Control and Prevention, Shantou, China.
Yubin YanHuizhou Center for Disease Control and Prevention, Huizhou, China.
Lin HuangHuizhou Center for Disease Control and Prevention, Huizhou, China.
Fang YangDepartment of HIV/AIDS Control and Prevention, Guangdong Provincial Center for Disease Control and Prevention, No. 160 Qunxian Road, Panyu District Guangzhou, Guangzhou, China.
Yi YangDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, No. 283 Jianghai Road, Haizhu District, Guangzhou, 510310, China.
Xiaobing FuDepartment of HIV/AIDS Control and Prevention, Guangdong Provincial Center for Disease Control and Prevention, No. 160 Qunxian Road, Panyu District Guangzhou, Guangzhou, China. 923717488@qq.com.
Hongbo JiangDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, No. 283 Jianghai Road, Haizhu District, Guangzhou, 510310, China. hongbojiang3@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnderstanding factors associated with antiretroviral treatment (ART) adherence is crucial for ART success among people living with HIV (PLHIV) in the "test and treat" era. Multiple psychosocial factors tend to coexist and have a syndemic effect on ART adherence. We aimed to explore factors associated with ART adherence and the syndemic effect of multiple psychosocial factors on ART adherence among PLHIV newly starting ART in Guangdong Province, China.

methodsNewly diagnosed PLHIV from six cities in Guangdong Province were recruited between May 2018 and June 2019, and then followed up from May 2019 to August 2020. Baseline and follow-up data were collected from a questionnaire and the national HIV surveillance system, the follow-up data of which were analyzed in this study. A Center for Adherence Support Evaluation (CASE) index > 10 points was defined as optimal ART adherence, which was measured via participants' self-reported adherence during follow-up survey. Multivariable logistic regression was used to identify factors associated with ART adherence. Exploratory factor analysis (EFA) and multi-order latent variable structural equation modeling (SEM) were performed to explore the syndemic effect of multiple psychosocial factors on ART adherence.

resultsA total of 734 (68.53%) follow-up participants were finally included in this study among the 1071 baseline participants, of whom 91.28% (670/734) had self-reported optimal ART adherence. Unemployment (aOR = 1.75, 95%CI: 1.01-3.02), no medication reminder (aOR = 2.28, 95%CI: 1.09-4.74), low medication self-efficacy (aOR = 2.28, 95%CI: 1.27-4.10), low social cohesion (aOR = 1.82, 95%CI: 1.03-3.19), no social participation (aOR = 5.65, 95%CI: 1.71-18.63), and ART side effects (aOR = 0.46, 95%CI: 0.26-0.81) were barriers to optimal ART adherence. The EFA and second-order latent variable SEM showed a linear relationship (standardized coefficient = 0.43, P < 0.001) between ART adherence and the latent psychosocial (syndemic) factor, which consisted of the three latent factors of medication beliefs and self-efficacy (standardized coefficient = 0.65, P < 0.001), supportive environment (standardized coefficient = 0.50, P < 0.001), and negative emotions (standardized coefficient=-0.38, P < 0.01). The latent factors of medication beliefs and self-efficacy, supportive environment, and negative emotions explained 42.3%, 25.3%, and 14.1% of the variance in the latent psychosocial factor, respectively.

conclusionsAbout nine out of ten PLHIV on ART in Guangdong Province self-reported optimal ART adherence. However, more efforts should be made to address barriers to optimal ART adherence.

Indexed as

Drug MonitoringHIV InfectionsMedication AdherenceAdultAnti-HIV AgentsAnti-Retroviral AgentsChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultAnti-HIV AgentsAnti-Retroviral AgentsAdherenceAntiretroviral treatmentAssociated factorsPeople living with HIVPsychosocial effectStructural equation modeling

Identifiers

PMID38769474
PMCPMC11106959

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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.