The temperature–mortality relationship in China: An analysis from 66 Chinese communities. Ma, W.; Wang, L.; Lin, H.; Liu, T.; Zhang, Y.; Rutherford, S.; Luo, Y.; Zeng, W.; Zhang, Y.; Wang, X.; Gu, X.; Chu, C.; Xiao, J.; and Zhou, M. Environmental Research, 137(Supplement C):72–77, February, 2015.
The temperature–mortality relationship in China: An analysis from 66 Chinese communities [link]Paper  doi  abstract   bibtex   
Previous studies examining temperature–mortality associations in China focused on a single city or a small number of cities. A multi-city study covering different climatic zones is necessary to better understand regional differences in temperature risk on mortality in China. Sixty-six communities from 7 regions across China were included in this study. We first used a Distributed Lag Non-linear Model (DLNM) to estimate community-specific effects of temperature on non-accidental mortality during 2006–2011. A multivariate meta-analysis was then applied to pool the estimates of community-specific effects. A U-shaped curve was observed between temperature and mortality at the national level in China, indicating both low and high temperatures were associated with increased mortality risk. The overall threshold was at about the 75th percentile of the pooled temperature distribution. The relative risk was 1.61 (95% CI: 1.48–1.74) for extremely cold temperature (1st percentile of temperature), and 1.21 (95% CI: 1.10–1.34) for extreme hot temperature (99th percentile of temperature) at lag0–21 days. The temperature–mortality relationship is different for different regions. Compared with north China, south China had a higher minimum mortality temperature (MMT), and there was a larger cold effect in the more southern parts of China and a more pronounced hot effect in more northern parts. Both cold and hot temperatures increase mortality risk in China, and the relationship varies geographically. Our findings suggest that public health policies for climate change adaptation should be tailored to the local climate conditions.
@article{ma_temperaturemortality_2015,
	title = {The temperature–mortality relationship in {China}: {An} analysis from 66 {Chinese} communities},
	volume = {137},
	issn = {0013-9351},
	shorttitle = {The temperature–mortality relationship in {China}},
	url = {http://www.sciencedirect.com/science/article/pii/S0013935114004319},
	doi = {10.1016/j.envres.2014.11.016},
	abstract = {Previous studies examining temperature–mortality associations in China focused on a single city or a small number of cities. A multi-city study covering different climatic zones is necessary to better understand regional differences in temperature risk on mortality in China. Sixty-six communities from 7 regions across China were included in this study. We first used a Distributed Lag Non-linear Model (DLNM) to estimate community-specific effects of temperature on non-accidental mortality during 2006–2011. A multivariate meta-analysis was then applied to pool the estimates of community-specific effects. A U-shaped curve was observed between temperature and mortality at the national level in China, indicating both low and high temperatures were associated with increased mortality risk. The overall threshold was at about the 75th percentile of the pooled temperature distribution. The relative risk was 1.61 (95\% CI: 1.48–1.74) for extremely cold temperature (1st percentile of temperature), and 1.21 (95\% CI: 1.10–1.34) for extreme hot temperature (99th percentile of temperature) at lag0–21 days. The temperature–mortality relationship is different for different regions. Compared with north China, south China had a higher minimum mortality temperature (MMT), and there was a larger cold effect in the more southern parts of China and a more pronounced hot effect in more northern parts. Both cold and hot temperatures increase mortality risk in China, and the relationship varies geographically. Our findings suggest that public health policies for climate change adaptation should be tailored to the local climate conditions.},
	number = {Supplement C},
	urldate = {2017-11-30},
	journal = {Environmental Research},
	author = {Ma, Wenjun and Wang, Lijun and Lin, Hualiang and Liu, Tao and Zhang, Yonghui and Rutherford, Shannon and Luo, Yuan and Zeng, Weilin and Zhang, Yewu and Wang, Xiaofeng and Gu, Xin and Chu, Cordia and Xiao, Jianpeng and Zhou, Maigeng},
	month = feb,
	year = {2015},
	keywords = {CK, Untagged},
	pages = {72--77}
}
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