Temporal trend and attributable risk factors of cardiovascular diseases burden for adults 55 years and older in 204 countries/territories from 1990 to 2021: an analysis for the Global Burden of Disease Study 2021.

IF 8.4 2区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
Ming-Si Wang, Jing-Wen Deng, Wan-Yue Geng, Rui Zheng, Hui-Lin Xu, Ying Dong, Wei-Dong Huang, Yi-Lan Li
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Abstract

Aims: The aging global population and overall population growth have significantly increased the burden of cardiovascular diseases (CVDs). This study aims to examine global temporal trends in the incidence, disability-adjusted life years (DALY), and mortality rates of both overall and type-specific CVDs among adults aged 55 and older from 1990 to 2021, with a focus on identifying changes over time, regional disparities, and the key risk factors contributing to this burden.

Methods and results: We analyzed data from the Global Burden of Disease (GBD) Study 2021, covering 204 countries and territories. Trends in age-standardized rates of incidence, DALY, and mortality for both overall and specific types of CVDs were assessed, alongside the impact of key risk factors. Between 1990 and 2021, global age-standardized incidence, DALY, and mortality rates showed a declining trend, with estimated annual percentage changes (EAPCs) of -0.39, -1.30, and -1.11, respectively. However, due to overall population growth and aging, the absolute number of CVD cases continued to rise. Regions with high-middle Socio-demographic Index (SDI) exhibited the highest incidence and mortality rates, while high SDI regions saw the greatest declines. Men had higher age-standardized rates of CVDs incidence, DALY, and mortality compared to women. The burden increased with age, with the oldest age groups (80+ years) showing the highest rates. High systolic blood pressure was the leading modifiable risk factor, contributing to more than half of the CVD-related DALY globally. Other major risk factors included high low-density lipoprotein cholesterol, smoking, and ambient particulate matter pollution.

Conclusions: While age-standardized rates of CVD incidence, DALY, and mortality have declined over the past three decades, the total burden of CVDs continues to rise due to population aging and growth. These findings highlight the need for targeted prevention strategies in regions with high CVD burden, particularly those with lower socioeconomic status.

1990 年至 2021 年 204 个国家/地区 55 岁及以上成年人心血管疾病负担的时间趋势和可归因风险因素:2021 年全球疾病负担研究分析。
目的:全球人口老龄化和总体人口增长大大增加了心血管疾病(CVDs)的负担。本研究旨在探讨1990年至2021年期间全球55岁及以上成年人总体心血管疾病和特定类型心血管疾病的发病率、残疾调整生命年(DALY)和死亡率的时间趋势,重点是确定随时间推移的变化、地区差异以及造成这一负担的主要风险因素:我们分析了 2021 年全球疾病负担(GBD)研究的数据,涵盖 204 个国家和地区。我们评估了总体和特定类型心血管疾病的年龄标准化发病率、残疾调整生命年和死亡率的趋势,以及主要风险因素的影响。1990 年至 2021 年期间,全球年龄标准化发病率、残疾调整寿命年数和死亡率呈下降趋势,估计年度百分比变化(EAPC)分别为-0.39、-1.30 和-1.11。然而,由于总体人口增长和老龄化,心血管疾病病例的绝对数量持续上升。社会人口指数(SDI)中高的地区发病率和死亡率最高,而社会人口指数高的地区下降幅度最大。与女性相比,男性的心血管疾病发病率、残疾调整寿命年数和死亡率的年龄标准化比率更高。随着年龄的增长,负担也在增加,年龄最大的人群(80 岁以上)发病率最高。高收缩压是最主要的可改变风险因素,造成了全球一半以上与心血管疾病相关的残疾调整寿命年数。其他主要风险因素包括高低密度脂蛋白胆固醇、吸烟和环境颗粒物污染:结论:虽然心血管疾病发病率、残疾调整寿命年数和死亡率的年龄标准化比率在过去 30 年中有所下降,但由于人口老龄化和增长,心血管疾病的总负担仍在继续上升。这些发现突出表明,在心血管疾病负担较重的地区,尤其是社会经济地位较低的地区,需要采取有针对性的预防策略。
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来源期刊
European journal of preventive cardiology
European journal of preventive cardiology CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
12.50
自引率
12.00%
发文量
601
审稿时长
3-8 weeks
期刊介绍: European Journal of Preventive Cardiology (EJPC) is an official journal of the European Society of Cardiology (ESC) and the European Association of Preventive Cardiology (EAPC). The journal covers a wide range of scientific, clinical, and public health disciplines related to cardiovascular disease prevention, risk factor management, cardiovascular rehabilitation, population science and public health, and exercise physiology. The categories covered by the journal include classical risk factors and treatment, lifestyle risk factors, non-modifiable cardiovascular risk factors, cardiovascular conditions, concomitant pathological conditions, sport cardiology, diagnostic tests, care settings, epidemiology, pharmacology and pharmacotherapy, machine learning, and artificial intelligence.
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