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Poly-Drug Use of Prescription Medicine among People with Opioid Use Disorder in China: A Systematic Review and Meta-Analysis

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posted on 2018-05-04, 20:38 authored by Tongyu Wang, Jun Ma, Rujia Wang, Zhimin Liu, Jie Shi, Lin Lu, Yanping Bao

Background: Opioid use disorder (OUD) causes substantial public health and social problems worldwide. Poly-drug use is common in people with OUD and increases morbidity and mortality. Investigation of the patterns and characteristics of poly-drug use of prescription medicine among opioid users is needed to develop appropriate prevention and intervention strategies. Objectives: To estimate the prevalence of poly-drug use of prescription medicine among people with OUD in China using meta-analysis. Methods: We searched relevant epidemiological studies published before February 2017 in English and Chinese databases. The quality of included studies was assessed using the Agency for Healthcare Research and Quality scale. The pooled prevalences of prescription medicine use among people with OUD were estimated. Results: We included 80 eligible studies in the meta-analysis. The main prescription medicines were benzodiazepines (BZDs) and prescription opioid analgesics. The pooled prevalence of unclassified BZDs and prescription opioids was 40.6% and 23.2%, respectively. Diazepam was the most frequently co-used BZD (32.6%), followed by triazolam (32.1%), and estazolam (9.2%). Tramadol was the most commonly used prescription opioid (27.3%), followed by methadone (16.8%), buprenorphine (12.6%), pethidine (8.9%), morphine (6.5%), dihydroetorphine (3.9%), and codeine-containing cough syrup (3.7%). BZDs were mainly used for self-medication (56.1%), whereas prescription opioids were primarily coused for nonmedical purposes (69.4%). Conclusions: The results demonstrate that prescription medicine use is widespread among opioid users in China. There needs to be more consideration of poly-drug use, and early interventions and management strategies are needed to prevent poly-drug use among opioid users in China.

Funding

the Thirteenth Five-Year Program of the Chinese Ministry of Science and Technology (2016YFC0800907)

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