Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, 185 Donghu Road, Wuchang District, Wuhan 430071, China.
Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, 185 Donghu Road, Wuchang District, Wuhan 430071, China; Global Health Institute, Wuhan University, 8 Donghunan Road, Wuchang District, Wuhan 430072, China.
Sci Total Environ. 2017 Jun 1;587-588:196-203. doi: 10.1016/j.scitotenv.2017.02.117. Epub 2017 Feb 24.
Compared with cold- and heat-related health impacts, the evidence was very limited in assessing the mortality effects of temperature variation (TV) accounting for both intra-day and inter-day changes in temperature.
We used a newly proposed composite indicator of intra-day and inter-day TV and evaluated TV-mortality associations in Hubei, China at the provincial level.
Daily mortality and meteorological data during 2009-2012 were obtained from 12 urban and rural counties across Hubei Province in China. TV was calculated using the standard deviation of the minimum and maximum temperatures during the exposure days. A quasi-Poisson generalized linear regression combined with distributed lag non-linear model was first applied to estimate county-specific relationship between mortality and TV, adjusting for long-term trend and seasonality, mean temperature, relative humidity, public holiday, and day of the week. A meta-analysis was then conducted to pool the county-specific estimates of TV-related mortality effects.
A significant positive association was observed between TV and cause-specific mortality (except for respiratory mortality and ischemic heart disease mortality). The effect estimates varied by exposure days, with the highest at 0-7days. Season-stratified analyses showed similar results, while stronger TV-mortality associations were found in warm season than in cold season. The elderly were more susceptible to TV-related mortality effects than younger groups. Some slight differences in effect estimates were also observed in subgroups stratified by gender, education attainment, place of death, and urban/rural areas.
Our study strengthened the evidence that temperature variation was an independent risk factor for non-accidental mortality. Some preventive and intervention strategies should be efficiently developed in response to global climate change, so as to minimize public health burden due to unstable weather patterns.
相较于冷、热相关健康影响，评估温度波动（TV）对死亡率影响的证据非常有限，这一影响同时考虑了日内和日间温度变化。
本研究使用一种新提出的日内和日间 TV 综合指标，并在中国湖北省省级层面评估 TV 与死亡率的关系。
本研究从中国湖北省 12 个城乡县获取了 2009-2012 年期间的逐日死亡率和气象数据。TV 采用暴露日最小和最大温度的标准差计算。首先，应用准泊松广义线性回归结合分布式滞后非线性模型，在调整长期趋势和季节性、平均温度、相对湿度、节假日和星期几的基础上，估计死亡率与 TV 之间的县级特异性关系。然后，进行荟萃分析以汇总 TV 相关死亡率效应的县级特异性估计值。
TV 与特定原因死亡率（除呼吸和缺血性心脏病死亡率外）呈显著正相关。暴露天数的效应估计值存在差异，最高的是 0-7 天。季节分层分析得到了相似的结果，且在暖季中观察到的 TV 与死亡率之间的关联更强。与年轻群体相比，老年人更容易受到 TV 相关死亡率效应的影响。按性别、教育程度、死亡地点和城乡地区划分的亚组分析中，效应估计值也存在一些细微差异。
本研究加强了证据表明，温度波动是非意外死亡率的一个独立危险因素。应针对全球气候变化制定有效的预防和干预策略，以尽量减少不稳定天气模式对公共卫生的负担。
