跳到主要导航 跳到搜索 跳到主要内容

The burden of cardiovascular diseases attributable to metabolic risk factors and its change from 1990 to 2019: a systematic analysis and prediction

科研成果: 期刊稿件文章同行评审

13 引用 (Scopus)

摘要

Background: Metabolic disorders are the most important risk factors for cardiovascular diseases (CVDs). The purpose of this study was to systematically analyze and summarize the most recent data by age, sex, region, and time, and to forecast the future burden of diseases. Methods: Data on the burden of CVDs associated with metabolic risk factors were obtained from the Global Burden of Disease (GBD) Study 2019; and then the burden of disease was assessed using the numbers and age-standardized rates (ASR) of deaths, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) and analyzed for temporal changes, differences in age, region, sex, and socioeconomic aspects; finally, the burden of disease was predicted using an autoregressive integrated moving average (ARIMA) model. Results: From 1990 to 2019, the numbers of deaths, DALYs, YLDs, and YLLs attributed to metabolic risk factors increased by 59.3%, 51.0%, 104.6%, and 47.8%, respectively. The ASR decreased significantly. The burden of metabolic risk factor-associated CVDs was closely related to socioeconomic position and there were major geographical variations; additionally, men had a significantly greater disease burden than women, and the peak shifted later based on the age group. We predicted that the numbers of deaths and DALYs would reach 16.5 million and 324.8 million, respectively, by 2029. Conclusions: The global burden of CVDs associated with metabolic risk factors is considerable and still rising, and more effort is needed to intervene in metabolic disorders.

源语言英语
文章编号1048515
期刊Frontiers in Epidemiology
3
DOI
出版状态已出版 - 2023

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 3 - 良好健康与福祉
    可持续发展目标 3 良好健康与福祉

学术指纹

探究 'The burden of cardiovascular diseases attributable to metabolic risk factors and its change from 1990 to 2019: a systematic analysis and prediction' 的科研主题。它们共同构成独一无二的指纹。

引用此