Association between air pollution exposure and multimorbidity among middle-aged and older adults in China: a cross-sectional study

As the world's population ages, multimorbidity is becoming an increasingly significant burden in the elderly population. Environmental exposures, particularly air pollution, may influence the patterns and distribution of multimorbidity, but evidence in older adults in China remains limited. This study aims to investigate the association between various air pollutants and multimorbidity patterns in Chinese adults aged 60 and above, while considering spatial structure and sex differences. This study is a cross-sectional analysis using data from the 2020 China Health and Retirement Longitudinal Study (CHARLS) for individuals aged 60 and above. Four multimorbidity patterns were analyzed: neurocognitive and emotional disorders (NED), cardiometabolic multimorbidity (CMM), respiratory system (RES), and articular-visceral organ (AVO). A linear mixed-effects model was used to evaluate the associations between five air pollution indicators and each multimorbidity pattern, expressed as odds ratio (OR) with corresponding 95% confidence interval (CI). Sex-stratified analyses were further conducted to explore potential sex-specific effect modifications. Spatial analysis was performed to examine clustering patterns between air pollution and multimorbidity. In addition, an online prediction platform based on machine learning was developed to assist in sexually transmitted disease screening. For NED, each 10 µg/m³ increase in O₃ exposure was associated with an OR of 0.866 (95% CI: 0.769-0.974). For CMM, each 10 µg/m³ increase in PM2.5 exposure was associated with an OR of 1.214 (1.143-1.291), each 10 µg/m³ increase in NO₂ exposure with an OR of 1.175 (1.104-1.251), and each 10 µg/m³ increase in O₃ exposure with an OR of 1.115 (1.047-1.186). For RES, there was no significant correlation observed with any of the five air pollution indicators. For AVO, each 10 µg/m³ increase in PM2.5 exposure was associated with an OR of 0.869 (0.817-0.923), each 10 µg/m³ increase in NO₂ exposure with an OR of 0.839 (0.789-0.892), each 0.1 mg/m³ increase in CO exposure with an OR of 0.892 (0.839-0.948), each 10 µg/m³ increase in SO₂ exposure with an OR of 0.931 (0.875-0.991), and each 10 µg/m³ increase in O₃ exposure with an OR of 0.804 (0.758-0.853). Sex-stratified analysis revealed a significant sex effect modification for PM2.5 and O₃ exposure in CMM, with higher ORs in females. Spatial autocorrelation analysis showed a significant positive correlation between NED, CMM, and AVO and air pollution, while no spatial autocorrelation was observed for the RES. In older Chinese adults, air pollution is significantly associated with multimorbidity patterns, with variations depending on sex and geographic factors.

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Journal
Scientific Reports
Published
2026-03-11
DOI
https://doi.org/10.1038/s41598-026-43757-5
Primary Topic
Air Quality and Health Impacts
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article
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article

Association between air pollution exposure and multimorbidity among middle-aged and older adults in China: a cross-sectional study

Jie Zhu, Youde Ding, Bangzheng Yin, Rui Jiang et al.
Scientific Reports
Air Quality and Health Impacts
article

Association between air pollution exposure and multimorbidity among middle-aged and older adults in China: a cross-sectional study

Jie Zhu, Youde Ding, Bangzheng Yin, Rui Jiang, Chan Yin, Zhenhang Zhao, Xi Chen
article en

Abstract

As the world's population ages, multimorbidity is becoming an increasingly significant burden in the elderly population. Environmental exposures, particularly air pollution, may influence the patterns and distribution of multimorbidity, but evidence in older adults in China remains limited. This study aims to investigate the association between various air pollutants and multimorbidity patterns in Chinese adults aged 60 and above, while considering spatial structure and sex differences. This study is a cross-sectional analysis using data from the 2020 China Health and Retirement Longitudinal Study (CHARLS) for individuals aged 60 and above. Four multimorbidity patterns were analyzed: neurocognitive and emotional disorders (NED), cardiometabolic multimorbidity (CMM), respiratory system (RES), and articular-visceral organ (AVO). A linear mixed-effects model was used to evaluate the associations between five air pollution indicators and each multimorbidity pattern, expressed as odds ratio (OR) with corresponding 95% confidence interval (CI). Sex-stratified analyses were further conducted to explore potential sex-specific effect modifications. Spatial analysis was performed to examine clustering patterns between air pollution and multimorbidity. In addition, an online prediction platform based on machine learning was developed to assist in sexually transmitted disease screening. For NED, each 10 µg/m³ increase in O₃ exposure was associated with an OR of 0.866 (95% CI: 0.769-0.974). For CMM, each 10 µg/m³ increase in PM2.5 exposure was associated with an OR of 1.214 (1.143-1.291), each 10 µg/m³ increase in NO₂ exposure with an OR of 1.175 (1.104-1.251), and each 10 µg/m³ increase in O₃ exposure with an OR of 1.115 (1.047-1.186). For RES, there was no significant correlation observed with any of the five air pollution indicators. For AVO, each 10 µg/m³ increase in PM2.5 exposure was associated with an OR of 0.869 (0.817-0.923), each 10 µg/m³ increase in NO₂ exposure with an OR of 0.839 (0.789-0.892), each 0.1 mg/m³ increase in CO exposure with an OR of 0.892 (0.839-0.948), each 10 µg/m³ increase in SO₂ exposure with an OR of 0.931 (0.875-0.991), and each 10 µg/m³ increase in O₃ exposure with an OR of 0.804 (0.758-0.853). Sex-stratified analysis revealed a significant sex effect modification for PM2.5 and O₃ exposure in CMM, with higher ORs in females. Spatial autocorrelation analysis showed a significant positive correlation between NED, CMM, and AVO and air pollution, while no spatial autocorrelation was observed for the RES. In older Chinese adults, air pollution is significantly associated with multimorbidity patterns, with variations depending on sex and geographic factors.

Scientific Reports
Sun Yat-sen University (CN), Guangzhou University (CN), Guangzhou Experimental Station (CN), Guangzhou Railway Polytechnic (CN), The Central Hospital of Shaoyang (CN), Guangzhou Medical University (CN)
Good health and well-being
Openalex Percentile: Top 30%
Air Quality and Health Impacts
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