Suppr超能文献

1990年至2021年全球、区域和国家层面糖尿病性视网膜病变所致失明和视力丧失负担:全球疾病负担研究2021的系统分析

Global, regional and national burden of blindness and vision loss attributable to diabetic retinopathy, 1990-2021: A systematic analysis for the Global Burden of Disease Study 2021.

作者信息

Pan Yujie, Li Yunkuo, Cui Mengzhao, He Guangyu, Wang Guixia

机构信息

Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, Jilin, China.

Department of Urology, The First Hospital of Jilin University, Changchun, Jilin, China.

出版信息

Diabetes Obes Metab. 2025 Oct;27(10):5464-5477. doi: 10.1111/dom.16588. Epub 2025 Jul 22.

Abstract

AIMS

Diabetes is increasingly reported as a cause of blindness and vision loss. However, the trends in the burden of blindness and vision loss attributed to diabetic retinopathy (DR) have yet to be fully elucidated.

MATERIALS AND METHODS

Utilizing the latest data from the Global Burden of Disease Study 2021, we extracted prevalence and years lived with disability (YLD) data for these conditions, including their respective age-standardized rate (ASR) indicators. The data were categorized by time, location, age and sociodemographic index (SDI). This study conducted comprehensive analyses over a span of 32 years (1990-2021) to identify trends in blindness and vision loss attributed to DR, employing advanced statistical methods such as estimated annual percentage change (EAPC), health inequity analysis (slope index and concentration index), decomposition analysis, frontier analysis, and predictive modelling using the Bayesian age-period-cohort method.

RESULTS

From 1990 to 2021, the global burden of blindness and vision loss attributed to DR (measured by prevalence and YLD) increased rapidly, and this trend was projected to remain stable until 2046. The age-standardized prevalence rates (ASPR) and age-standardized YLD rates (ADYR) in all five SDI regions exhibited an upward trend. Notably, the high and high-middle SDI regions surpassed global levels, with their EAPC and 95% CI values all greater than 0. In 2021, the prevalence cases, YLD cases, prevalence rates and YLD rates for females across all age groups were generally higher than those for males, and were approximately 1.4 times those of males. Health inequality analysis indicates that over the past 32 years, there have been significant disparities in the distribution of prevalence rates and YLD rates associated with the SDI across 204 countries and regions. Decomposition analysis on a global and cross-SDI regional scale indicated that ageing, population growth and epidemiological changes had all increased the burden of prevalence and YLD. The frontier analysis showed that high SDI regions had greater potential for improvement. In 2021, compared with the relatively stable trend of type 1 diabetes, the prevalence and YLD rates of blindness and vision loss attributable to type 2 diabetes rapidly increased with age.

CONCLUSIONS

Blindness and vision loss attributed to DR pose significant global health and economic challenges. It is imperative for health system managers to formulate strong strategies to address these growing issues effectively.

摘要

目的

糖尿病作为失明和视力丧失的一个病因,其报告日益增多。然而,糖尿病性视网膜病变(DR)所致失明和视力丧失的负担趋势尚未完全阐明。

材料与方法

利用《2021年全球疾病负担研究》的最新数据,我们提取了这些疾病的患病率和残疾生存年数(YLD)数据,包括各自的年龄标准化率(ASR)指标。数据按时间、地点、年龄和社会人口指数(SDI)进行分类。本研究在32年(1990 - 2021年)期间进行了全面分析,以确定DR所致失明和视力丧失的趋势,采用了先进的统计方法,如估计年百分比变化(EAPC)、健康不平等分析(斜率指数和集中指数)、分解分析、前沿分析以及使用贝叶斯年龄 - 时期 - 队列方法的预测建模。

结果

从1990年到2021年,DR所致全球失明和视力丧失负担(以患病率和YLD衡量)迅速增加,预计这一趋势将持续稳定至2046年。所有五个SDI区域的年龄标准化患病率(ASPR)和年龄标准化YLD率(ADYR)均呈上升趋势。值得注意的是,高SDI区域和高中等SDI区域超过了全球水平,其EAPC和95%置信区间值均大于0。2021年,各年龄组女性的患病率病例、YLD病例、患病率和YLD率普遍高于男性,约为男性的1.4倍。健康不平等分析表明,在过去32年中,204个国家和地区与SDI相关的患病率和YLD率分布存在显著差异。全球和跨SDI区域尺度的分解分析表明,老龄化、人口增长和流行病学变化均增加了患病率和YLD的负担。前沿分析表明,高SDI区域有更大的改善潜力。2021年,与1型糖尿病相对稳定的趋势相比,2型糖尿病所致失明和视力丧失的患病率和YLD率随年龄迅速增加。

结论

DR所致失明和视力丧失给全球健康和经济带来了重大挑战。卫生系统管理者必须制定强有力的策略来有效应对这些日益严重的问题。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验