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Evidence for Urban–Rural Disparity in Temperature–Mortality Relationships in Zhejiang Province, China

BACKGROUND: Temperature-related mortality risks have mostly been studied in urban areas, with limited evidence for urban–rural differences in the temperature impacts on health outcomes. OBJECTIVES: We investigated whether temperature–mortality relationships vary between urban and rural counties in C...

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Autores principales: Hu, Kejia, Guo, Yuming, Hochrainer-Stigler, Stefan, Liu, Wei, See, Linda, Yang, Xuchao, Zhong, Jieming, Fei, Fangrong, Chen, Feng, Zhang, Yunquan, Zhao, Qi, Chen, Gongbo, Chen, Qian, Zhang, Yizhe, Ye, Tingting, Ma, Lu, Li, Shanshan, Qi, Jiaguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Environmental Health Perspectives 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6768324/
https://www.ncbi.nlm.nih.gov/pubmed/30822387
http://dx.doi.org/10.1289/EHP3556
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author Hu, Kejia
Guo, Yuming
Hochrainer-Stigler, Stefan
Liu, Wei
See, Linda
Yang, Xuchao
Zhong, Jieming
Fei, Fangrong
Chen, Feng
Zhang, Yunquan
Zhao, Qi
Chen, Gongbo
Chen, Qian
Zhang, Yizhe
Ye, Tingting
Ma, Lu
Li, Shanshan
Qi, Jiaguo
author_facet Hu, Kejia
Guo, Yuming
Hochrainer-Stigler, Stefan
Liu, Wei
See, Linda
Yang, Xuchao
Zhong, Jieming
Fei, Fangrong
Chen, Feng
Zhang, Yunquan
Zhao, Qi
Chen, Gongbo
Chen, Qian
Zhang, Yizhe
Ye, Tingting
Ma, Lu
Li, Shanshan
Qi, Jiaguo
author_sort Hu, Kejia
collection PubMed
description BACKGROUND: Temperature-related mortality risks have mostly been studied in urban areas, with limited evidence for urban–rural differences in the temperature impacts on health outcomes. OBJECTIVES: We investigated whether temperature–mortality relationships vary between urban and rural counties in China. METHODS: We collected daily data on 1 km gridded temperature and mortality in 89 counties of Zhejiang Province, China, for 2009 and 2015. We first performed a two-stage analysis to estimate the temperature effects on mortality in urban and rural counties. Second, we performed meta-regression to investigate the modifying effect of the urbanization level. Stratified analyses were performed by all-cause, nonaccidental (stratified by age and sex), cardiopulmonary, cardiovascular, and respiratory mortality. We also calculated the fraction of mortality and number of deaths attributable to nonoptimum temperatures associated with both cold and heat components. The potential sources of the urban–rural differences were explored using meta-regression with county-level characteristics. RESULTS: Increased mortality risks were associated with low and high temperatures in both rural and urban areas, but rural counties had higher relative risks (RRs), attributable fractions of mortality, and attributable death counts than urban counties. The urban–rural disparity was apparent for cold (first percentile relative to minimum mortality temperature), with an RR of 1.47 [95% confidence interval (CI): 1.32, 1.62] associated with all-cause mortality for urban counties, and 1.98 (95% CI: 1.87, 2.10) for rural counties. Among the potential sources of the urban–rural disparity are age structure, education, GDP, health care services, air conditioners, and occupation types. CONCLUSIONS: Rural residents are more sensitive to both cold and hot temperatures than urban residents in Zhejiang Province, China, particularly the elderly. The findings suggest past studies using exposure–response functions derived from urban areas may underestimate the mortality burden for the population as a whole. The public health agencies aimed at controlling temperature-related mortality should develop area-specific strategies, such as to reduce the urban–rural gaps in access to health care and awareness of risk prevention. Future projections on climate health impacts should consider the urban–rural disparity in mortality risks. https://doi.org/10.1289/EHP3556
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spelling pubmed-67683242019-10-02 Evidence for Urban–Rural Disparity in Temperature–Mortality Relationships in Zhejiang Province, China Hu, Kejia Guo, Yuming Hochrainer-Stigler, Stefan Liu, Wei See, Linda Yang, Xuchao Zhong, Jieming Fei, Fangrong Chen, Feng Zhang, Yunquan Zhao, Qi Chen, Gongbo Chen, Qian Zhang, Yizhe Ye, Tingting Ma, Lu Li, Shanshan Qi, Jiaguo Environ Health Perspect Research BACKGROUND: Temperature-related mortality risks have mostly been studied in urban areas, with limited evidence for urban–rural differences in the temperature impacts on health outcomes. OBJECTIVES: We investigated whether temperature–mortality relationships vary between urban and rural counties in China. METHODS: We collected daily data on 1 km gridded temperature and mortality in 89 counties of Zhejiang Province, China, for 2009 and 2015. We first performed a two-stage analysis to estimate the temperature effects on mortality in urban and rural counties. Second, we performed meta-regression to investigate the modifying effect of the urbanization level. Stratified analyses were performed by all-cause, nonaccidental (stratified by age and sex), cardiopulmonary, cardiovascular, and respiratory mortality. We also calculated the fraction of mortality and number of deaths attributable to nonoptimum temperatures associated with both cold and heat components. The potential sources of the urban–rural differences were explored using meta-regression with county-level characteristics. RESULTS: Increased mortality risks were associated with low and high temperatures in both rural and urban areas, but rural counties had higher relative risks (RRs), attributable fractions of mortality, and attributable death counts than urban counties. The urban–rural disparity was apparent for cold (first percentile relative to minimum mortality temperature), with an RR of 1.47 [95% confidence interval (CI): 1.32, 1.62] associated with all-cause mortality for urban counties, and 1.98 (95% CI: 1.87, 2.10) for rural counties. Among the potential sources of the urban–rural disparity are age structure, education, GDP, health care services, air conditioners, and occupation types. CONCLUSIONS: Rural residents are more sensitive to both cold and hot temperatures than urban residents in Zhejiang Province, China, particularly the elderly. The findings suggest past studies using exposure–response functions derived from urban areas may underestimate the mortality burden for the population as a whole. The public health agencies aimed at controlling temperature-related mortality should develop area-specific strategies, such as to reduce the urban–rural gaps in access to health care and awareness of risk prevention. Future projections on climate health impacts should consider the urban–rural disparity in mortality risks. https://doi.org/10.1289/EHP3556 Environmental Health Perspectives 2019-03-01 /pmc/articles/PMC6768324/ /pubmed/30822387 http://dx.doi.org/10.1289/EHP3556 Text en EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted.
spellingShingle Research
Hu, Kejia
Guo, Yuming
Hochrainer-Stigler, Stefan
Liu, Wei
See, Linda
Yang, Xuchao
Zhong, Jieming
Fei, Fangrong
Chen, Feng
Zhang, Yunquan
Zhao, Qi
Chen, Gongbo
Chen, Qian
Zhang, Yizhe
Ye, Tingting
Ma, Lu
Li, Shanshan
Qi, Jiaguo
Evidence for Urban–Rural Disparity in Temperature–Mortality Relationships in Zhejiang Province, China
title Evidence for Urban–Rural Disparity in Temperature–Mortality Relationships in Zhejiang Province, China
title_full Evidence for Urban–Rural Disparity in Temperature–Mortality Relationships in Zhejiang Province, China
title_fullStr Evidence for Urban–Rural Disparity in Temperature–Mortality Relationships in Zhejiang Province, China
title_full_unstemmed Evidence for Urban–Rural Disparity in Temperature–Mortality Relationships in Zhejiang Province, China
title_short Evidence for Urban–Rural Disparity in Temperature–Mortality Relationships in Zhejiang Province, China
title_sort evidence for urban–rural disparity in temperature–mortality relationships in zhejiang province, china
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6768324/
https://www.ncbi.nlm.nih.gov/pubmed/30822387
http://dx.doi.org/10.1289/EHP3556
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