Evidence map›Paper›PMID 41368668›Full record

ArticleFrontiers in public health2025

Analysis and prediction of disease burden related to opioid use disorder in China based on GBD 2021.

RuiYan Wang, Yujia Liu, XingYu Wan, Tianhu Liang, Junxian Zhao, Hao Wang, Yan Ma, Yaolong Chen, Xinghua Lv

Abstract read
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Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

RuiYan WangThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
Yujia LiuThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
XingYu WanThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
Tianhu LiangResearch Centre for Clinical Medicine, The First Hospital of Lanzhou University, Lanzhou, China.
Junxian ZhaoResearch Centre for Clinical Medicine, The First Hospital of Lanzhou University, Lanzhou, China.
Hao WangThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
Yan MaThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
Yaolong ChenResearch Centre for Clinical Medicine, The First Hospital of Lanzhou University, Lanzhou, China.
Xinghua LvThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To analyze the disease burden of opioid use disorder (OUD) in China from 1990 to 2021 and predict its future trends. Methods: Annual data from the Global Burden of Disease (GBD 2021) database were used to describe the disease burden through metrics such as prevalence, incidence, mortality, and disability-adjusted life years (DALYs). Joinpoint regression models were employed to analyze trends in disease burden. The estimated annual percentage change (EAPC) was calculated to quantify the temporal trends in age-standardized rates (ASRs). The age-period-cohort (APC) model explored age, period, and cohort effects on the OUD burden. Health inequality analyses examined the relationship between the OUD burden and the Sociodemographic Index (SDI). The autoregressive integrated moving average (ARIMA) model was used to forecast the OUD disease burden over the next 15 years. Results: Compared to 1990, the OUD-related disease burden in China declined across various indicators by 2021, with a significant decrease in the age-standardized mortality rate (EAPC = -5.26). Meanwhile, the global disease burden of OUD increased. In China, females, individuals aged 15-24 years, and recent birth cohorts showed higher disease burdens. Over time, the relationship between DALYs and SDI gradually weakened. Projections suggest that the burden of OUD in China is expected to increase over the next 15 years. Conclusion: Opioid misuse is a significant factor contributing to the global disease burden and challenges in anesthetic and surgical care. Effective measures are urgently needed to reduce the burden of opioid dependence and promote advancements in pain-free medical care.

Indexed as

Cost of IllnessGlobal Burden of DiseaseOpioid-Related DisordersAdolescentAdultChinaDisability-Adjusted Life YearsFemaleHumansIncidenceMaleMiddle AgedPrevalenceYoung Adultanesthesiadisease burdendrugs use disorderepidemiologyopioid drugspublic health

Identifiers

PMID41368668
PMCPMC12682747

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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.