Decomposition Analysis of High BMI-Attributable Stroke Burden in China: Population Aging as the Dominant Driver.

Authors

Xiaoxue Liu, Haoyun Zhou, Runtang Meng, Chuanhua Yu, Fang Wang, Yongchao Liu

Published in

Journal of obesity. Volume 2026. Issue 1. Pages e6789331.

Abstract

High body-mass index (BMI) is the second largest contributor to stroke burden and the fastest-growing risk factor for stroke globally. Given China's rapidly aging population and the increasing obesity epidemic, understanding the long-term trends and drivers of stroke burden is critical.
High BMI is a chief risk factor for stroke. We aim to evaluate the long-term trends and population risk on stroke mortality burden caused by high BMI in Chinese population between 1990 and 2023.
The decomposition analysis and linear regression were utilized to determine the contribution of population aging and other risk factors to the changing trends in the mortality and disability-adjusted life year (DALYs) of stroke caused by high BMI.
In China, the mortality rate of stroke caused by high BMI increased by 1.640/100,000 during the study period of 1990-2023. The increase was decomposed as 1.180/100,000 due to population aging and 0.460/100,000 due to other risk factors, with population aging contributing 72% and other risk factors contributing 28%. The DALYs rate increased by 52.228/100,000, of which 32.999/100,000 was due to population aging and 19.229/100,000 was due to other risk factors. Notably, population aging contributed 63% of the increase. These findings confirm that population aging was the dominant driver of the increased stroke burden attributable to high BMI, whether measured by mortality or DALY.
Population aging is the dominant driver of the increasing stroke burden attributable to high BMI in China. Effective burden reduction will require integrated prevention strategies targeting both the elderly population and modifiable metabolic risk factors.

PMID:
42813392
Bibliographic data and abstract were imported from PubMed on 30 Sep 2026.

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