• Yonghong Li, Li Lan, Yulin Wang, Chao Yang, Wenge Tang, Guoquan Cui, Shuquan Luo, Yibin Cheng, Yingchun Liu, Jingyi Liu, and Yinlong Jin.
• Institute of Environmental Health and Related Product Safety, Chinese Center for Disease Control and Prevention, 29 Nanwei Road, Beijing 100021, China.
• Environ. Res. 2014 Oct 1;134:91-7.

BackgroundNumerous studies have reported the association between ambient temperature and mortality. However, few studies have focused on the effects of extreme temperatures on diabetes mortality, particularly in China. The objective of the present study was to assess the effects of extremely cold and hot temperatures on diabetes mortality in urban areas of Harbin and Chongqing in China to provide scientific evidence for public health policy implementation to respond to challenges in diabetes mortality because of extreme temperature events.MethodsA double threshold B-spline distributed lag non-linear model (DLNM) was used to investigate the effects of extremely cold and hot temperatures on diabetes mortality from lag 0 to 30 days, after controlling for potential confounders including air pollutants. The unit risk, which is the elevated cumulative risk of diabetes mortality caused by each 1 °C change in extremely cold and hot temperatures during certain lag days, was estimated for extreme cold and heat using simple regression analysis.ResultsSignificant associations between both extreme hot and cold temperatures and diabetes mortality were observed in Harbin and Chongqing for different lag lengths. In Harbin, the extreme cold effects on diabetes mortality were delayed by three days and lasted for six days (lag 3-8), with the highest risk (RR 95% CI: 1.223,1.054-1.418 for -23 °C) at lag 5. The hot effects were delayed one day and lasted for three days (lag 1-3), with the peak RR (1.343: 1.080-1.670 for 37 °C) at lag 2. In Chongqing, the cold effects on diabetes mortality were delayed by seven days and lasted for four days (lag 7-10), with the highest risk (1.201: 1.006-1.434 for 4 °C) at lag 7. The hot effects peaked (1.811: 1.083-3.027 for 41 °C) at lag 0 and lasted for 2 days (lag 0-1). The unit risk for cold and hot effects was 12.9% (95% CI: 2.5-33.7%) and 16.5% (95% CI: 3.8-39.1%) in Harbin and 12.5% (95% CI: -4.7 to 47.5%) and 19.7% (95% CI: 3.9-48.5%) in Chongqing, respectively.ConclusionsThe results indicate that both extremely cold and hot temperatures increase diabetes mortality in different manners in Harbin and Chongqing. Diabetes education programs should include information on either managing or combating the effects of extreme hot and cold weather.Copyright © 2014 Elsevier Inc. All rights reserved.

13 keywords...

hide…