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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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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 |
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author | Hu, Kai He, Qingqing |
author_facet | Hu, Kai He, Qingqing |
author_sort | Hu, Kai |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10473454 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-104734542023-09-02 Rural–Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45+ Hu, Kai He, Qingqing Innov Aging Original Research Article 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. Oxford University Press 2023-06-23 /pmc/articles/PMC10473454/ /pubmed/37663149 http://dx.doi.org/10.1093/geroni/igad060 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Research Article Hu, Kai He, Qingqing Rural–Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45+ |
title | Rural–Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45+ |
title_full | Rural–Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45+ |
title_fullStr | Rural–Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45+ |
title_full_unstemmed | Rural–Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45+ |
title_short | Rural–Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45+ |
title_sort | rural–urban disparities in multimorbidity associated with climate change and air pollution: a longitudinal analysis among chinese adults aged 45+ |
topic | Original Research Article |
url | 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 |
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