Chenzhi Wang1, Zhao Zhang2, Maigeng Zhou3, Pin Wang4, Peng Yin5, Wan Ye6, Lingyan Zhang7. 1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China. Electronic address: chenzhiwang@mail.bnu.edu.cn. 2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China. Electronic address: zhangzhao@bnu.edu.cn. 3. The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China. Electronic address: maigengzhou@126.com. 4. Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, No.1378, Wenyi West Street, Hangzhou 311121, China. Electronic address: wangpin@hznu.edu.cn. 5. The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China. Electronic address: yinpengcdc@163.com. 6. State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China. Electronic address: yewan@mail.bnu.edu.cn. 7. State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China. Electronic address: zhanglingyan@mail.bnu.edu.cn.
Abstract
BACKGROUND: The environmental variation in mortality due to extreme temperatures has been well-documented by many studies. Mortality to extreme temperatures (MoET) was recognized to vary geographically, either by countries within a region or by areas within a country. However, so far, little attention has been paid to rural residents, with even lesser attention on the potential rural-urban differences. The aim of our study was to offer a quite comprehensive analysis on the differences in temperature-mortality relationship between rural and urban areas across China. METHOD: A distributed lag nonlinear model was built to describe the temperature-mortality relationship, based on the mortality data and meteorological variable of 75 communities in China from 2007 to 2012. Subsequently, a meta-analysis was applied to compare the differences in the temperature-mortality relationship between rural and urban areas at various levels. RESULTS: Distinct responses regarding MoET between rural and urban areas were observed at different spatial scales. At regional level, more U-shaped curves were observed for temperature-mortality relationships in urban areas, while more J-shaped curves were observed in rural areas. At national scale, we found that the cold effect was stronger in rural areas (RR: rural 1.69 vs. urban 1.51), while heat effect was stronger in urban areas (RR: rural 1.01 vs. urban 1.12). Moreover, the modifying influence of air pollution on temperature-mortality relationship was found to be very limited. CONCLUSION: The difference in response of MoET between rural and urban areas was noticeable, cold effect is more significant in China both in rural and urban areas. Additionally, urban areas in southern China and rural areas in northern China suffered more from extreme temperature events. Our findings suggest that differences in rural-urban responses to MoET should be taken seriously when intervention measures for reducing the risks to residents' health were adopted.
BACKGROUND: The environmental variation in mortality due to extreme temperatures has been well-documented by many studies. Mortality to extreme temperatures (MoET) was recognized to vary geographically, either by countries within a region or by areas within a country. However, so far, little attention has been paid to rural residents, with even lesser attention on the potential rural-urban differences. The aim of our study was to offer a quite comprehensive analysis on the differences in temperature-mortality relationship between rural and urban areas across China. METHOD: A distributed lag nonlinear model was built to describe the temperature-mortality relationship, based on the mortality data and meteorological variable of 75 communities in China from 2007 to 2012. Subsequently, a meta-analysis was applied to compare the differences in the temperature-mortality relationship between rural and urban areas at various levels. RESULTS: Distinct responses regarding MoET between rural and urban areas were observed at different spatial scales. At regional level, more U-shaped curves were observed for temperature-mortality relationships in urban areas, while more J-shaped curves were observed in rural areas. At national scale, we found that the cold effect was stronger in rural areas (RR: rural 1.69 vs. urban 1.51), while heat effect was stronger in urban areas (RR: rural 1.01 vs. urban 1.12). Moreover, the modifying influence of air pollution on temperature-mortality relationship was found to be very limited. CONCLUSION: The difference in response of MoET between rural and urban areas was noticeable, cold effect is more significant in China both in rural and urban areas. Additionally, urban areas in southern China and rural areas in northern China suffered more from extreme temperature events. Our findings suggest that differences in rural-urban responses to MoET should be taken seriously when intervention measures for reducing the risks to residents' health were adopted.
Authors: Emmanuel A Odame; Ying Li; Shimin Zheng; Ambarish Vaidyanathan; Ken Silver Journal: Int J Environ Res Public Health Date: 2018-07-27 Impact factor: 3.390