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Rural–Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45+
BACKGROUND AND OBJECTIVES: Chronic conditions and multimorbidity are increasing worldwide. Yet, understanding the relationship between climate change, air pollution, and longitudinal changes in multimorbidity is limited. Here, we examined the effects of sociodemographic and environmental risk factor...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10473454/ https://www.ncbi.nlm.nih.gov/pubmed/37663149 http://dx.doi.org/10.1093/geroni/igad060 |
Sumario: | BACKGROUND AND OBJECTIVES: Chronic conditions and multimorbidity are increasing worldwide. Yet, understanding the relationship between climate change, air pollution, and longitudinal changes in multimorbidity is limited. Here, we examined the effects of sociodemographic and environmental risk factors in multimorbidity among adults aged 45+ and compared the rural–urban disparities in multimorbidity. RESEARCH DESIGN AND METHODS: Data on the number of chronic conditions (up to 14), sociodemographic, and environmental factors were collected in 4 waves of the China Health and Retirement Longitudinal Study (2011–2018), linked with the full-coverage particulate matter 2.5 (PM(2.5)) concentration data set (2000–2018) and temperature records (2000–2018). Air pollution was assessed by the moving average of PM(2.5) concentrations in 1, 2, 3, 4, and 5 years; temperature was measured by 1-, 2-, 3-, 4-, and 5-year moving average and their corresponding coefficients of variation. We used the growth curve modeling approach to examine the relationship between climate change, air pollution, and multimorbidity, and conducted a set of stratified analyses to study the rural–urban disparities in multimorbidity related to temperature and PM(2.5) exposure. RESULTS: We found the higher PM(2.5) concentrations and rising temperature were associated with higher multimorbidity, especially in the longer period. Stratified analyses further show the rural–urban disparity in multimorbidity: Rural respondents have a higher prevalence of multimorbidity related to rising temperature, whereas PM(2.5)-related multimorbidity is more severe among urban ones. We also found temperature is more harmful to multimorbidity than PM(2.5) exposure, but PM(2.5) exposure or temperature is not associated with the rate of multimorbidity increase with age. DISCUSSION AND IMPLICATIONS: Our findings indicate that there is a significant relationship between climate change, air pollution, and multimorbidity, but this relationship is not equally distributed in the rural–urban settings in China. The findings highlight the importance of planning interventions and policies to deal with rising temperature and air pollution, especially for rural individuals. |
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