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1990 - 2021年工作年龄人群酒精性心肌病的全球、区域和国家负担:一项系统分析

Global, regional and national burdens of alcoholic cardiomyopathy among the working-age population, 1990-2021: a systematic analysis.

作者信息

Wang Zhongkai, Wu Changyong, Zhang Bingqing, Sun Huang, Liu Wenjie, Yang Yuan, Gu Ying, Pu Lifei, Zheng Lihui, Bao Suli, Luo Yihua, Li Ruijie, Peng Yunzhu

机构信息

Cardiovascular Clinical Medical Center, Department of Cardiology, the First Affiliated Hospital of Kunming Medical University, Kunming, China.

Department of Clinical Pharmacy, the First Affiliated Hospital of Kunming Medical University, Kunming, China.

出版信息

J Health Popul Nutr. 2025 May 24;44(1):170. doi: 10.1186/s41043-025-00920-4.

DOI:10.1186/s41043-025-00920-4
PMID:40413455
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12103052/
Abstract

OBJECTIVES

Alcoholic cardiomyopathy (ACM) results from chronic alcohol misuse and primarily affects the working-age population (15-64 years). The global age-standardized rates (ASRs) of ACM disease burden declined slightly from 1990 to 2021, but the absolute cases increased, especially in high‒medium sociodemographic index (SDI) regions such as Eastern Europe. The aim of this study was to inform strategies to combat this preventable yet escalating health issue.

METHODS

We calculated estimated annual percentage changes (EAPCs) to quantify the dynamics of prevalence, deaths, and disability-adjusted life years (DALYs) for ACM. Decomposition analysis quantifies the contributor of disease burden in ACM. Additionally, we employed a health inequality analysis with two core indicators, the slope index (SI) and the concentration index (CIN), to assess national differences in the burden of ACM in relation to the SDI. Frontier analysis was used to identify preventable burdens with respect to optimized alcohol policies, particularly in high-middle SDI countries. Finally, we applied a Bayesian age‒cohort (BAPC) model to project the ACM burden to 2035.

RESULTS

This study revealed that the ASRs of prevalence, deaths, and DALYs decreased slightly from 1990 to 2021, whereas absolute cases of ACM continued to increase globally. Global income-based health disparities in ACM have intensified over the past 32 years, with high SDI populations disproportionately favoured. Population growth was the main driver of the increased ACM burden. The global burden of ACM is expected to increase in the future according to the BAPC model.

CONCLUSIONS

The global burden of ACM continues to rise, primarily due to population ageing and insufficient prevention policies. This burden disproportionately impacts working-age populations, who face heightened vulnerability due to alcohol accessibility, premature mortality, and reduced workforce productivity. Moreover, economic growth paradoxically coincides with increased alcohol-related harm in regions with high-middle socioeconomic development-the alcohol control paradox. Projections highlight an urgent need for tailored alcohol control strategies, including stricter regulation and early cardiac screening in high-risk groups, to mitigate workforce productivity loss and align public health priorities with sustainable development goals.

摘要

目的

酒精性心肌病(ACM)由长期酗酒所致,主要影响工作年龄人群(15 - 64岁)。1990年至2021年期间,全球ACM疾病负担的年龄标准化率(ASR)略有下降,但绝对病例数有所增加,尤其是在东欧等社会人口统计学指数(SDI)为中高的地区。本研究旨在为应对这一可预防却不断升级的健康问题提供策略依据。

方法

我们计算了估计年变化百分比(EAPC),以量化ACM的患病率、死亡率和伤残调整生命年(DALY)的动态变化。分解分析量化了ACM疾病负担的促成因素。此外,我们采用了一种健康不平等分析方法,使用两个核心指标,即斜率指数(SI)和集中指数(CIN),来评估各国在ACM负担方面与SDI相关的差异。前沿分析用于确定与优化酒精政策相关的可预防负担,特别是在中高SDI国家。最后,我们应用贝叶斯年龄队列(BAPC)模型预测到2035年的ACM负担。

结果

本研究表明,1990年至2021年期间,患病率、死亡率和DALY的ASR略有下降,而全球ACM的绝对病例数持续增加。在过去32年中,基于收入的全球ACM健康差距有所加剧,高SDI人群受益过多。人口增长是ACM负担增加的主要驱动因素。根据BAPC模型,预计未来全球ACM负担将增加。

结论

全球ACM负担持续上升,主要原因是人口老龄化和预防政策不足。这一负担对工作年龄人群的影响尤为严重,他们因酒精易获得性、过早死亡和劳动力生产率下降而面临更高的脆弱性。此外,在社会经济发展为中高的地区,经济增长与酒精相关危害增加这一矛盾现象同时出现——即酒精控制悖论。预测结果凸显了迫切需要制定针对性的酒精控制策略,包括在高危人群中加强监管和早期心脏筛查,以减轻劳动力生产率损失,并使公共卫生优先事项与可持续发展目标保持一致。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/301d/12103052/8358eb4fa7ca/41043_2025_920_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/301d/12103052/29ff23c4b697/41043_2025_920_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/301d/12103052/927e840b510b/41043_2025_920_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/301d/12103052/8358eb4fa7ca/41043_2025_920_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/301d/12103052/29ff23c4b697/41043_2025_920_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/301d/12103052/b93d462221e6/41043_2025_920_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/301d/12103052/1238e87f80cf/41043_2025_920_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/301d/12103052/9eac4c6c5d8f/41043_2025_920_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/301d/12103052/927e840b510b/41043_2025_920_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/301d/12103052/8358eb4fa7ca/41043_2025_920_Fig6_HTML.jpg

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