Longer-Term Impact of High and Low Temperature on Mortality: An International Study to Clarify Length of Mortality Displacement.
Longer-Term Impact of High and Low Temperature on Mortality: An International Study to Clarify Length of Mortality Displacement.
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DOI：
10.1289/ehp1756
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发表时间：
2017-10-27
影响因子：
10.4
通讯作者：
Gasparrini A
中科院分区：
文献类型：
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作者：
Armstrong B;Bell ML;de Sousa Zanotti Stagliorio Coelho M;Leon Guo YL;Guo Y;Goodman P;Hashizume M;Honda Y;Kim H;Lavigne E;Michelozzi P;Hilario Nascimento Saldiva P;Schwartz J;Scortichini M;Sera F;Tobias A;Tong S;Wu CF;Zanobetti A;Zeka A;Gasparrini A
在许多地方，每天的死亡率在气温特别高或特别低的日子之后有所增加，但这种每天的时间序列研究无法确定这种增加是否反映了寿命的大幅缩短或死亡的短期转移（收获）。为了澄清这个问题，我们估计了来自12个国家的278个地点的年度死亡率和年度冷热总结之间的关联。在每个地点的年死亡率回归中，使用年冷热指数作为预测因素，以便了解一段时间内的趋势，按国家对年度计数异常进行聚类，并使用元回归汇总估计数。我们使用了两个基于初步标准每日分析的年度热和寒冷指数：a）高于/低于最低死亡温度（MMT）的平均年度温度，和B）归因于热和寒冷的估计死亡比例。第一个指数更简单，与以前的相关研究相匹配;增加第二个指数是因为它允许解释系数等于0和1与每日分析中没有（0）或所有（1）可归因于至少1年的死亡一致。平均而言，年死亡率对热和冷平均度的回归系数分别为1.7%（95%置信区间（CI）：0.3，3.1）和1.1%（95% CI：0.6，1.6），每日归因分数分别为0.8（95% CI：0.2，1.3）和1.1（95% CI：0.9，1.4）。后一个系数接近1.0提供了证据，表明在日常分析中发现的大多数归因于热和冷的死亡至少提前了1年。估计值对于替代模型假设来说基本上是稳健的。这些结果提供了强有力的证据，表明与热和冷相关的日常分析中的大多数死亡至少被取代了1年。https://doi.org/10.1289/EHP1756
In many places, daily mortality has been shown to increase after days with particularly high or low temperatures, but such daily time-series studies cannot identify whether such increases reflect substantial life shortening or short-term displacement of deaths (harvesting). To clarify this issue, we estimated the association between annual mortality and annual summaries of heat and cold in 278 locations from 12 countries. Indices of annual heat and cold were used as predictors in regressions of annual mortality in each location, allowing for trends over time and clustering of annual count anomalies by country and pooling estimates using meta-regression. We used two indices of annual heat and cold based on preliminary standard daily analyses: a) mean annual degrees above/below minimum mortality temperature (MMT), and b) estimated fractions of deaths attributed to heat and cold. The first index was simpler and matched previous related research; the second was added because it allowed the interpretation that coefficients equal to 0 and 1 are consistent with none (0) or all (1) of the deaths attributable in daily analyses being displaced by at least 1 y. On average, regression coefficients of annual mortality on heat and cold mean degrees were 1.7% [95% confidence interval (CI): 0.3, 3.1] and 1.1% (95% CI: 0.6, 1.6) per degree, respectively, and daily attributable fractions were 0.8 (95% CI: 0.2, 1.3) and 1.1 (95% CI: 0.9, 1.4). The proximity of the latter coefficients to 1.0 provides evidence that most deaths found attributable to heat and cold in daily analyses were brought forward by at least 1 y. Estimates were broadly robust to alternative model assumptions. These results provide strong evidence that most deaths associated in daily analyses with heat and cold are displaced by at least 1 y. https://doi.org/10.1289/EHP1756