Department of Epidemiology and Biostatistics, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan, 430065, China; Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan, 430065, China.
Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China.
Environ Res. 2019 Dec;179(Pt A):108771. doi: 10.1016/j.envres.2019.108771. Epub 2019 Sep 23.
Temperature variability (TV) is closely associated with climate change, but there is no unified TV definition worldwide. Two novel composite TV indexes were developed recently by calculating the standard deviations of several days' daily maximum and minimum temperatures (TV), or hourly mean temperatures (TV).
This study aimed to compare the mortality risks and burden associated with TV and TV using large time-series datasets collected from multiple locations in China, United Kingdom and United States.
We collected daily mortality and hourly temperature data through 1987 to 2012 from 63 locations in China (8 communities, 2006-2012), United Kingdom (10 regions, 1990-2012), and USA (45 cities, 1987-2000). TV-mortality associations were investigated using a three-stage analytic approach separately for China, UK, and USA. First, we applied a time-series regression for each location to derive location-specific TV-mortality curves. A second-stage meta-analysis was then performed to pool these estimated associations for each country. Finally, we calculated mortality fraction attributable to TV based on above-described location-specific and pooled estimates.
Our dataset totally consisted of 23, 089, 328 all-cause death cases, including 93, 750 from China, 7,573,716 from UK and 15, 421, 862 from USA, respectively. In despite of a relatively wide uncertainty in China, approximately linear relationships were consistently identified for TV and TV. In the three countries, generally similar lag patterns of TV effects were consistently observed for TV and TV. A 1 °C rise in TV and TV at lag 0-7 days was associated with mortality increases of 0.93% (95% confidence interval [CI]: 0.12, 1.74) and 0.97% (0.18, 1.77) in China, 0.33% (0.15, 0.51) and 0.41% (0.21, 0.60) in UK, and 0.55% (0.41, 0.70) and 0.51% (0.35, 0.66) in USA, respectively. Larger attributable fractions were estimated using TV than those using TV, with estimates at 0-10 days of 3.69% (0.51, 6.75) vs. 2.59% (0.10, 5.01) in China, 1.14% (0.54, 1.74) vs. 0.98% (0.55, 1.42) in UK, and 2.57% (1.97, 3.16) vs. 1.67% (1.15, 2.18) in USA, respectively. Our meta-regression analyses indicated higher vulnerability to TV-induced mortality risks in warmer locations.
Our study added multi-country evidence for increased mortality risk associated with short-term exposure to large temperature variability. Daily and hourly TV exposure metrics produced generally comparable risk effects, but the attributable mortality burden tended to be higher using TV instead of TV.
温度变化(TV)与气候变化密切相关,但全球范围内没有统一的 TV 定义。最近,通过计算数天的日最高和最低温度(TV)或每小时平均温度(TV)的标准偏差,开发了两种新的复合 TV 指数。
本研究旨在使用来自中国、英国和美国多个地点的大型时间序列数据集,比较与 TV 和 TV 相关的死亡率风险和负担。
我们通过 1987 年至 2012 年从中国(8 个社区,2006-2012 年)、英国(10 个地区,1990-2012 年)和美国(45 个城市,1987-2000 年)的 63 个地点收集了每日死亡率和每小时温度数据。我们分别使用三个阶段的分析方法研究了 TV 与死亡率的关联,分别是中国、英国和美国。首先,我们为每个地点应用时间序列回归,得出地点特异性 TV 与死亡率曲线。然后进行第二阶段的荟萃分析,以汇总每个国家的这些估计关联。最后,我们根据上述描述的地点特异性和汇总估计,计算 TV 引起的死亡率负担。
我们的数据集总共包括 23089328 例全因死亡病例,其中包括来自中国的 93750 例、英国的 7573716 例和美国的 15421862 例。尽管中国的不确定性相对较大,但 TV 和 TV 之间始终一致地确定了近似线性关系。在这三个国家,TV 和 TV 的影响滞后模式大致相同。TV 和 TV 在 0-7 天的滞后期内每升高 1°C,与死亡率分别增加 0.93%(95%置信区间:0.12,1.74)和 0.97%(0.18,1.77)有关,在中国,英国和美国分别增加 0.33%(0.15,0.51)和 0.41%(0.21,0.60),增加 0.55%(0.41,0.70)和 0.51%(0.35,0.66)。使用 TV 估计的归因分数大于使用 TV 的归因分数,0-10 天的估计值在中国为 3.69%(0.51,6.75)与 2.59%(0.10,5.01),英国为 1.14%(0.54,1.74)与 0.98%(0.55,1.42),美国为 2.57%(1.97,3.16)与 1.67%(1.15,2.18)。我们的荟萃回归分析表明,在较温暖的地区,对 TV 引起的死亡率风险的脆弱性更高。
本研究为与短期暴露于大的温度变化相关的死亡率风险增加提供了多国家证据。每日和每小时 TV 暴露指标产生了大致可比的风险效应,但使用 TV 而不是 TV 时,归因于死亡率的负担往往更高。