| 重庆和哈尔滨市极端温度对糖尿病所致生命损失年的影响 |
| |
| 引用本文： | 李永红,罗书全,兰莉,金明贵,杨超,和晋渝,李泓冰,李成橙,程义斌,金银龙. 重庆和哈尔滨市极端温度对糖尿病所致生命损失年的影响[J]. 中华流行病学杂志, 2017, 38(3): 303-308 |
| |
| 作者姓名： | 李永红 罗书全 兰莉 金明贵 杨超 和晋渝 李泓冰 李成橙 程义斌 金银龙 |
| |
| 作者单位： | 100021 北京, 中国疾病预防控制中心环境与健康相关产品安全所政策与法规标准室;404000 重庆市疾病预防控制中心公共卫生与安全监测所;150056 哈尔滨市疾病预防控制中心慢病预防控制所;401420 重庆市綦江区疾病预防控制中心;150056 哈尔滨市疾病预防控制中心;404000 重庆市疾病预防控制中心公共卫生与安全监测所;150056 哈尔滨市疾病预防控制中心公共卫生监测所;100021 北京, 中国疾病预防控制中心环境流行病学室;100021 北京, 中国疾病预防控制中心环境与健康相关产品安全所政策与法规标准室;100021 北京, 中国疾病预防控制中心环境与健康相关产品安全所政策与法规标准室 |
| |
| 基金项目： | 国家重点基础研究发展计划（973计划）（2012CB955502）；GEF/UNDP/WHO气候变化专项基金（PIMS3248） |
| |
| 摘 要： | 目的 了解重庆和哈尔滨市极端高温和低温与糖尿病引起的生命损失年之间的关系。方法 利用重庆市（2011-2013年）和哈尔滨市（2008-2010年）的气象和糖尿病死亡数据，采用分布滞后非线性模型（DLNM）分析极端高温和低温对糖尿病引起的生命损失年的滞后效应和累积效应，以相对危险度（RR）表示。结果 在重庆市，冷效应对生命损失年的影响滞后4 d、持续3 d（lag4～6），最大RR值为1.304（95% CI：1.033～1.647），出现在低温发生后第5天（lag5）；热效应滞后1 d，其RR值为1.321（95% CI：1.061～1.646）。在哈尔滨市，极端低温对生命损失年的影响滞后4 d、持续7 d（lag4～10），最大RR值为1.309（95% CI：1.088～1.575），出现在低温发生后第6天（lag6）；热效应滞后1 d、持续4 d（lag1～4），最大RR值为1.460（95% CI：1.114～1.915），出现在高温后第2天（lag2）。重庆市冷效应和热效应的单位风险分别为43.7%（P=0.005 5）和18.0%（P=0.000 2），哈尔滨市冷效应和热效应的单位风险分别为15.0%（P=0.000 8）和29.5%（P=0.001 2）。结论 重庆和哈尔滨市极端高温和低温都可增加糖尿病引起的生命损失年。极端温度对糖尿病的影响应纳入糖尿病健康教育内容。
|
| 关 键 词： | 糖尿病 温度 生命 气候变化 生命损失年 极端温度效应 |
| 收稿时间： | 2016-10-11 |
Influence of extreme weather on years of life lost due to diabetes death in Chongqing and Harbin, China |
| |
| Li Yonghong,Luo Shuquan,Lan Li,Jin Minggui,Yang Chao,He Jinyu,Li Hongbing,Li Chengcheng,Cheng Yibin and Jin Yinlong. Influence of extreme weather on years of life lost due to diabetes death in Chongqing and Harbin, China[J]. Chinese Journal of Epidemiology, 2017, 38(3): 303-308 |
| |
| Authors: | Li Yonghong Luo Shuquan Lan Li Jin Minggui Yang Chao He Jinyu Li Hongbing Li Chengcheng Cheng Yibin Jin Yinlong |
| |
| Affiliation: | Division of Policy, Regulation and Standard, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China;Public Health and Safety Monitoring Department, Chongqing Municipal Center for Disease Control and Prevention, Chongqing 404000, China;Division of Chronic Disease Control and Prevention, Harbin Municipal Center for Disease Control and Prevention, Harbin 150056, China;;Qijiang District Center for Disease Control and Prevention of Chongqing, Chongqing 401420, China;Harbin Municipal Center for Disease Control and Prevention, Harbin 150056, China;Public Health and Safety Monitoring Department, Chongqing Municipal Center for Disease Control and Prevention, Chongqing 404000, China;Public Health and Monitoring Center, Harbin Municipal Center for Disease Control and Prevention, Harbin 150056, China;Environmental Epidemiology Department, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China;Division of Policy, Regulation and Standard, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China;Division of Policy, Regulation and Standard, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China |
| |
| Abstract: | Objective To understand the associations between extremely low and high air temperature and the years of life lost (YLL) due to diabetes deaths in Chongqing and Harbin with different climatic characteristics in China. Methods A double threshold B-spline distributed lag non-linear model (DLNM) was used to investigate the lag and cumulative effects of extremely low and high air temperature on YLL due to diabetes for lag 0-30 days by using the urban meteorological and diabetes mortality data of Chongqing (2011-2013) and Harbin (2008-2010). The effects were expressed as relative risk (RR). Results In Chongqing, the cold effects on YLL due to diabetes were delayed by four days and lasted for three days (lag4-6) with the highest RR of 1.304 (95%CI:1.033-1.647) at lag5. The hot effects were delayed by one day (lag1) with RR of 1.321 (95%CI:1.061-1.646). In Harbin, the extreme cold effects on YLL were delayed by four days and lasted for seven days (lag4-10) with the highest RR of 1.309 (95%CI:1.088-1.575) at lag6. The hot effects were delayed by one day and lasted for four days (lag1-4) with the highest RR of 1.460 (95%CI:1.114-1.915) at lag2. The unit risk for cold and hot effects was 43.7% (P=0.005 5) and 18.0% (P=0.000 2) in Chongqing and 15.0% (P=0.000 8) and 29.5%(P=0.001 2) in Harbin, respectively. Conclusions Both extremely low air temperature and extremely high air temperature might increase the years of life lost due to diabetes in cities with different climate characteristics. Health education about diabetes prevention should provide information about the effects of extreme weather events. |
| |
| Keywords: | Diabetes mellitus Temperature Life Climate change Years of life lost Extreme temperature effects |
|
| 点击此处可从《中华流行病学杂志》浏览原始摘要信息 |
|
点击此处可从《中华流行病学杂志》下载免费的PDF全文 |
|
