Fine particulate matter, physical activity and cardiovascular disease in middle-aged and older Chinese adults
- PMID: 40612920
- PMCID: PMC12215110
- DOI: 10.1136/bmjsem-2024-002358
Fine particulate matter, physical activity and cardiovascular disease in middle-aged and older Chinese adults
Abstract
Objectives: This study aimed to estimate the combined effects of long-term fine particulate matter (PM2.5) exposure and physical activity (PA) on cardiovascular disease (CVD) risk and to assess whether the cardiovascular benefits of PA outweigh the potential adverse effects of PM2.5 exposure.
Methods: Data were obtained from the China Health and Retirement Longitudinal Study and the ChinaHighAirPollutants datasets. Cox proportional hazards models were used to assess the independent and combined effects of PA and long-term PM2.5 exposure on CVD. Interaction analyses were conducted to determine whether the cardiovascular effects of PM2.5 or PA were modified by each other.
Results: PA was negatively associated with CVD risk. Each IQR increase in PA significantly reduced the risk of CVD by 10% (HR=0.90, 95% CI 0.83 to 0.98). While PM2.5 exposure was positively associated with CVD, a 10 μg/m3 increase in PM2.5 significantly increased 5% risk of CVD (HR=1.05, 95% CI 1.00 to 1.09). Compared with participants with high PA and low PM2.5 exposure, those with low PA and high PM2.5 exposure had the highest risk of CVD (HR=1.56, 95% CI 1.15 to 2.13). Long-term PM2.5 exposure increased the risk of CVD in participants with low and moderate PAs, but not high PA.
Conclusion: The beneficial effects of high levels of PA may mitigate the detrimental effects of PM2.5 exposure, indicating that PA is an effective strategy for reducing the risk of CVD, even among individuals living in areas with elevated PM2.5 concentrations.
Keywords: Cardiovascular; Environment; Physical activity.
Copyright © Author(s) (or their employer(s)) 2025. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ Group.
Conflict of interest statement
None declared.
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References
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- Huang Q, Jiang Z, Shi B, et al. Characterisation of cardiovascular disease (CVD) incidence and machine learning risk prediction in middle-aged and elderly populations: data from the China health and retirement longitudinal study (CHARLS) BMC Public Health . 2025;25:518. doi: 10.1186/s12889-025-21609-7. - DOI - PMC - PubMed
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