Geographical Variations in Risk Factors Associated with HIV Infection Among Drug Users in a Prefecture in Southwest China

Overview

Journal Infect Dis Poverty

Publisher Biomed Central

Date 2015 Sep 3

PMID 26329887

Citations 11

Authors

Yi-Biao Zhou

Qi-Xing Wang

Song Liang

Yu-Han Gong

Mei-Xiao Yang

Yue Chen

Shi-Jiao Nie

Lei Nan

Ai-Hui Yang

Qiang Liao

Yang Yang

Xiu-Xia Song

Qing-Wu Jiang

Affiliations

Soon will be listed here.

Abstract

Background: Previous 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.

Methods: Data 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.

Results: This 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.

Conclusion: The 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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