Relationship Between Long‐Term Exposure to Airborne Particulate Matter and the Intrinsic Capacity of Middle‐Aged and Older Adults in China: A Retrospective Cohort Study Based on
CHARLS
Jiatong Li, Yuxin Wu, Yaru Zhou, Jitong Zhou, Yigeng Huang, Xinyi Sun, Tongtong Ye, Mingxing Xu, Huanqin Wang, Shu Wang ABSTRACT
Background
Intrinsic capacity (IC), proposed by the World Health Organization, reflects the composite of an individual's physical and mental capacities and is considered a key indicator of healthy aging. Although air pollution has been associated with multiple adverse health outcomes, evidence on its relationship with IC—a multidimensional indicator of overall functional ability—remains limited.
Objective
This study aimed to examine the longitudinal associations between long‐term exposure to particulate matter of different sizes (PM 1 , PM 2.5 and PM 10 ) and declines in intrinsic capacity among middle‐aged and older adults in mainland China.
Methods
Data were obtained from the nationally representative longitudinal cohort of the China Health and Retirement Longitudinal Study (CHARLS), including adults aged ≥ 45 years. Annual average concentrations of PM 1 , PM 2.5 and PM 10 were estimated using satellite‐based models based on participants' residential locations. A composite IC score was constructed according to the WHO intrinsic capacity framework. Multivariable logistic regression models were used to evaluate associations between particulate matter exposure and IC decline. Restricted cubic spline models were applied to assess nonlinear dose–response relationships. Mixed‐exposure effects were further evaluated using weighted quantile sum regression, Bayesian kernel machine regression and quantile g‐computation.
Results
Long‐term exposure to PM 1 , PM 2.5 and PM 10 was significantly associated with a higher risk of IC decline and lower composite IC scores. Nonlinear dose–response relationships were observed between particulate matter exposure and IC decline. In mixed‐exposure analyses, PM 10 and PM 2.5 showed the strongest contributions to the joint effects, with PM 10 having the highest weight and posterior inclusion probability. Each one‐quantile increase in the overall pollutant mixture was significantly associated with a decline in composite IC scores.