Ban Jie, Xu Dandan, He Mike Z, Sun Qinghua, Chen Chen, Wang Wentao, Zhu Pengfei, Li Tiantian
National Institute for Environmental Health, Chinese Center for Disease Control and Prevention, No.7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, 722 West 168th Street, New York, NY 10032, USA.
Environ Int. 2017 Sep;106:19-26. doi: 10.1016/j.envint.2017.05.019. Epub 2017 May 27.
Although existing studies have linked high temperature to mortality in a small number of regions, less evidence is available on the variation in the associations between high temperature exposure and cause-specific mortality of multiple regions in China. Our study focused on the use of time series analysis to quantify the association between high temperature and different cause-specific mortalities for susceptible populations for 43 counties in China. Two-stage analyses adopting a distributed lag non-linear model (DLNM) and a meta-analysis allowed us to obtain county-specific estimates and national-scale pooled estimates of the nonlinear temperature-mortality relationship. We also considered different populations stratified by age and sex, causes of death, absolute and relative temperature patterns, and potential confounding from air pollutants. All of the observed cause-specific mortalities are significantly associated with higher temperature. The estimated effects of high temperature on mortality varied by spatial distribution and temperature patterns. Compared with the 90th percentile temperature, the overall relative risk (RR) at the 99th percentile temperature for non-accidental mortality is 1.105 (95%CI: 1.089, 1.122), for circulatory disease is 1.107 (95%CI: 1.081, 1.133), for respiratory disease is 1.095 (95%CI: 1.050, 1.142), for coronary heart disease is 1.073 (95%CI: 1.047, 1.099), for acute myocardial infarction is 1.072 (95%CI: 1.042, 1.104), and for stroke is 1.095 (95%CI: 1.052, 1.138). Based on our findings, we believe that heat-related health effect in China is a significant issue that requires more attention and allocation of existing resources.
尽管现有研究已将高温与少数地区的死亡率联系起来,但关于中国多个地区高温暴露与特定病因死亡率之间关联的差异,证据较少。我们的研究聚焦于使用时间序列分析来量化中国43个县易感人群的高温与不同特定病因死亡率之间的关联。采用分布滞后非线性模型(DLNM)的两阶段分析和荟萃分析使我们能够获得特定县的估计值以及全国范围内非线性温度-死亡率关系的汇总估计值。我们还考虑了按年龄和性别分层的不同人群、死因、绝对和相对温度模式以及空气污染物的潜在混杂因素。所有观察到的特定病因死亡率均与较高温度显著相关。高温对死亡率的估计影响因空间分布和温度模式而异。与第90百分位数温度相比,第99百分位数温度下非意外死亡率的总体相对风险(RR)为1.105(95%置信区间:1.089,1.122),循环系统疾病为1.107(95%置信区间:1.081,1.133),呼吸系统疾病为1.095(95%置信区间:1.050,1.142),冠心病为1.073(95%置信区间:1.047,1.099),急性心肌梗死为1.072(95%置信区间:1.042,1.104),中风为1.095(95%置信区间:1.052,1.138)。基于我们的研究结果,我们认为中国与高温相关的健康影响是一个重大问题,需要更多关注和现有资源的分配。