• Jun Yang, Peng Yin, Maigeng Zhou, Chun-Quan Ou, Mengmeng Li, Yunning Liu, Jinghong Gao, Bin Chen, Jiangmei Liu, Li Bai, and Qiyong Liu.
• State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China. Electronic address: smart_yjun@163.com.
• Sci. Total Environ. 2016 Feb 1; 543 (Pt A): 75-82.

AbstractFew multi-city studies have been conducted to investigate the acute health effects of low and high temperatures on diabetes mortality worldwide. We aimed to examine effects of ambient temperatures on city-/gender-/age-/education-specific diabetes mortality in nine Chinese cities using a two-stage analysis. Distributed lag non-linear model was first applied to estimate the city-specific non-linear and delayed effects of temperatures on diabetes mortality. Pooled effects of temperatures on diabetes mortality were then obtained using meta-analysis, based on restricted maximum likelihood. We found that heat effects were generally acute and followed by a period of mortality displacement, while cold effects could last for over two weeks. The pooled relative risks of extreme high (99th percentile of temperature) and high temperature (90th percentile of temperature) were 1.29 (95%CI: 1.11-1.47) and 1.11 (1.03-1.19) over lag 0-21 days, compared with the 75th percentile of temperature. In contrast, the pooled relative risks over lag 0-21 days were 1.44 (1.25-1.66) for extreme low (1st percentile of temperature) and 1.20 (1.12-1.30) for low temperature (10th percentile of temperature), compared to 25th percentile of temperature. The estimate of heat effects was relatively higher among females than that among males, with opposite trend for cold effects, and the estimates of heat and cold effects were particularly higher among the elderly and those with low education, although the differences between these subgroups were not statistically significant (P>0.05). These findings have important public health implications for protecting diabetes patients from adverse ambient temperatures.Copyright © 2015 Elsevier B.V. All rights reserved.

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