Hu Kai, He Qingqing
Department of Sociology, School of Social and Public Administration, East China University of Science and Technology, Shanghai, China.
School of Resource and Environmental Engineering, Wuhan University of Technology, Wuhan, China.
Innov Aging. 2023 Jun 23;7(6):igad060. doi: 10.1093/geroni/igad060. eCollection 2023.
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.
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) concentration data set (2000-2018) and temperature records (2000-2018). Air pollution was assessed by the moving average of PM 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 exposure.
We found the higher PM 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-related multimorbidity is more severe among urban ones. We also found temperature is more harmful to multimorbidity than PM exposure, but PM exposure or temperature is not associated with the rate of multimorbidity increase with age.
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.
慢性病和多种疾病并存的情况在全球范围内日益增加。然而，对于气候变化、空气污染与多种疾病并存的纵向变化之间的关系，人们的了解仍然有限。在此，我们研究了社会人口学和环境风险因素对45岁及以上成年人多种疾病并存情况的影响，并比较了城乡在多种疾病并存方面的差异。
在中国健康与养老追踪调查（2011 - 2018年）的4个调查波次中收集了慢性病数量（最多14种）、社会人口学和环境因素的数据，并与全覆盖的细颗粒物2.5（PM）浓度数据集（2000 - 2018年）以及温度记录（2000 - 2018年）相关联。空气污染通过1年、2年、3年、4年和5年的PM浓度移动平均值进行评估；温度通过1年、2年、3年、4年和5年的移动平均值及其相应的变异系数进行测量。我们使用生长曲线建模方法来研究气候变化、空气污染与多种疾病并存之间的关系，并进行了一系列分层分析，以研究与温度和PM暴露相关的多种疾病并存的城乡差异。
我们发现较高的PM浓度和气温上升与较高的多种疾病并存情况相关，尤其是在较长时期内。分层分析进一步显示了多种疾病并存的城乡差异：农村受访者与气温上升相关的多种疾病并存患病率较高，而与PM相关的多种疾病并存情况在城市居民中更为严重。我们还发现温度对多种疾病并存的危害比PM暴露更大，但PM暴露或温度与多种疾病并存随年龄增长的增加速率无关。
我们的研究结果表明，气候变化、空气污染与多种疾病并存之间存在显著关系，但这种关系在中国城乡环境中分布并不均匀。这些发现凸显了制定应对气温上升和空气污染的干预措施及政策的重要性，特别是对于农村居民而言。
