ArticleInfectious diseases of poverty2015
Geographical variations in risk factors associated with HIV infection among drug users in a prefecture in Southwest China.
Article in Infectious diseases of poverty, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Prevalence of HIV Infection in Minority Indigenous Populations of the South-East Asia and Western Pacific Regions: A Systematic Review and Meta-analysis.AIDS and behavior · 2023Pooled it
- Trial
- The effect of sociodemographic factors on COVID-19 incidence of 342 cities in China: a geographically weighted regression model analysis.BMC infectious diseases · 2021Article
- Exploring spatially varying demographic associations with gonorrhea incidence in Baltimore, Maryland, 2002-2005.Journal of geographical systems · 2020Article
- Article
- What motivates or demotivates injecting drug users to participate in hypothetical HIV vaccine efficacy trials? A qualitative study from urban Tanzania.The East African health research journal · 2020Article
- Impact of maternal HIV infection on pregnancy outcomes in southwestern China - a hospital registry based study.Epidemiology and infection · 2019Article
- Risk factors for HIV infection among 15 to 25-year-old rural unmarried Yi adolescents in an ethnic minority region of China.Medicine · 2018Article
- Article
- Prevalence of and risk factors associated with Cryptosporidium infection in an underdeveloped rural community of southwest China.Infectious diseases of poverty · 2017Article
- Analysis of HIV prevalence among pregnant women in Liangshan Prefecture, China, from 2009 to 2015.PloS one · 2017Article
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13 authors.
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Abstract
backgroundPrevious studies have shown inconsistent or even contradictory results for some risk factors associated with HIV infection among drug users, and these may be partially explained by geographical variations.
methodsData were collected from 11 methadone clinics in the Liangshan Yi Autonomous Prefecture from 2004 to 2012. A non-spatial logistical regression model and a geographically weighted logistic regression model were fitted to analyze the association between HIV infection and specific factors at the individual level.
resultsThis study enrolled 6,458 patients. The prevalence of HIV infection was 25.1 %. The non-spatial model indicated that being divorced was positively associated with HIV infection. The spatial model also showed that being divorced was positively associated with HIV infection, but only for 49.4 % of individuals residing in some northern counties. The non-spatial model suggested that service sector work was negatively associated with HIV infection. However, the spatial model indicated that service work was associated with HIV infection, but only for 23.0 % of patients living in some western counties. The non-spatial model did not show that being married was associated with HIV infection in our study field, but the spatial model indicated that being married was negatively associated with HIV infection for 12.0 % of individuals living in some western counties. For other factors, the non-spatial and spatial models showed similar results.
conclusionThe spatial model may be useful for improving understanding of geographical heterogeneity in the relationship between HIV infection and individual factors. Spatial heterogeneity may be useful for tailoring intervention strategies for local regions, which can consequently result in a more efficient allocation of limited resources toward the control of HIV transmission.
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