Author
Listed:
- Bo Zhang
(Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
National Institute on Drug Dependence, Peking University, Beijing100191, China)
- Xiang-Yu Yan
(Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
National Institute on Drug Dependence, Peking University, Beijing100191, China)
- Yong-Jie Li
(Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
National Institute on Drug Dependence, Peking University, Beijing100191, China)
- Zhi-Min Liu
(National Institute on Drug Dependence, Peking University, Beijing100191, China)
- Zu-Hong Lu
(Biomedical Engineering, Southeast University, Nanjing 211189, China)
- Zhong-Wei Jia
(Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
National Institute on Drug Dependence, Peking University, Beijing100191, China
Center for Drug Abuse Control and Prevention, National Institute of Health Data Science, Peking University, Beijing 100191, China
Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing 100191, China)
Abstract
Background: Heavy drug users was a global consensus high-risk population of HIV infection. However, the specific impact of drug on HIV infection has not yet been established. Depressants and stimulants were most widely used drugs in mainland China, and mix use of the two drugs was also serious. We assessed the HIV infection rate and trends in heavy drug users by analyzing data from the National Dynamic Management and Control Database for Drug Users (NDMCDDU). Methods: All heavy drug users with HIV test results in NDMCDDU from 2008 to 2016 were grouped into depressants only group (DOG), stimulants only group (SOG), and both depressants and stimulants group (DSG). We used joinpoint regression to examine trends of HIV infection rates. Multivariable logistic regression was used to examine factors related to HIV infection. Results: A total of 466,033 heavy drug users with 9522 cases of HIV infection were included in this analysis. HIV infection rate was estimated at 2.97% (95% CI 2.91–3.04%) of 265,774 users in DOG, 0.45% (95% CI 0.42–0.49%) of 140,895 users in SOG, and 1.65% (95% CI 1.55–1.76%) of 59,364 users in DSG. In DOG, a U-shaped curve of HIV infection rate decreased from 3.85% in 2008 to 2.19% in 2010 (annual percent change (APC) −12.9, 95% CI −19.3–−6.0, p < 0.05), then increased to 4.64% in 2016 (APC 8.3, 95% CI 6.1–10.4, p < 0.05) was observed. However, SOG and DSG showed consistent increases from 0.15% in 2008 to 0.54% in 2016 (APC 8.2, 95% CI 4.8–11.8, p < 0.05) and from 0.78% in 2008 to 2.72% in 2016 (APC 13.5, 95% CI 10.7–16.4, p < 0.05), respectively. HIV infection rate of DOG in the southwest region presented a U-shaped trend. All groups showed significant increases in HIV infection in east and central regions. Conclusions: The U-shaped curve for HIV infection rate among DOG users and consistent increases among SOG and DSG users implies drug abuse is still a critical focus of HIV infection in China. It is urgently needed to reassess the effectiveness of current strategies on HIV prevention and control among drug users.
Suggested Citation
Bo Zhang & Xiang-Yu Yan & Yong-Jie Li & Zhi-Min Liu & Zu-Hong Lu & Zhong-Wei Jia, 2020.
"Epidemics of HIV Infection among Heavy Drug Users of Depressants Only, Stimulants Only, and Both Depressants and Stimulants in Mainland China: A Series, Cross-Sectional Studies,"
IJERPH, MDPI, vol. 17(15), pages 1-20, July.
Handle:
RePEc:gam:jijerp:v:17:y:2020:i:15:p:5483-:d:391681
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