Wenjun Ma1, Lijun Wang2, Hualiang Lin3, Tao Liu3, Yonghui Zhang4, Shannon Rutherford5, Yuan Luo3, Weilin Zeng3, Yewu Zhang6, Xiaofeng Wang6, Xin Gu6, Cordia Chu5, Jianpeng Xiao7, Maigeng Zhou8. 1. Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; Center for Environment and Population Health, Griffith University, Brisbane 4111, Australia. 2. The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050,China. 3. Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China. 4. Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China. 5. Center for Environment and Population Health, Griffith University, Brisbane 4111, Australia. 6. Chinese Center for Disease Control and Prevention, Beijing 102206, China. 7. Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China. Electronic address: jpengx@163.com. 8. The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050,China. Electronic address: maigengzhou@126.com.
Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Authors: Kai Chen; Radley M Horton; Daniel A Bader; Corey Lesk; Leiwen Jiang; Bryan Jones; Lian Zhou; Xiaodong Chen; Jun Bi; Patrick L Kinney Journal: Environ Pollut Date: 2017-02-22 Impact factor: 8.071