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澳大利亚 2000-2009 年热、冷及温度变化对死亡率的影响

Impacts of heat, cold, and temperature variability on mortality in Australia, 2000-2009.

机构信息

School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia.

Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Anhui, China.

出版信息

Sci Total Environ. 2019 Feb 15;651(Pt 2):2558-2565. doi: 10.1016/j.scitotenv.2018.10.186. Epub 2018 Oct 15.

Abstract

OBJECTIVES

Evidence is limited on the relative contribution of different temperature exposures (i.e., heat, cold and significant temperature variability) to mortality. This study aims to examine mortality risk and associated mortality burden from heat, cold, and temperature variability in Australia.

METHODS

We collected daily time-series data on all-cause deaths and weather variables for the five most populous Australian cities (Sydney, Melbourne, Brisbane, Adelaide, and Perth), from 2000 to 2009. Temperature variability was calculated from the standard deviation of hourly temperatures between two adjacent days. Three-stage analysis was used. We firstly used quasi-Poisson regression models to model the associations of mortality with heat (mean temperature) during the warm season, with cold (mean temperature) during the cold season, and with temperature variability all year round, while controlling for long-term trend and seasonality, day of week, and population change over time. We then estimated the effects of different non-optimum temperatures using the simplified log-linear regression model. Finally, we computed and compared the fraction (%) of deaths attributable to different non-optimum temperatures.

RESULTS

The greatest percentage increase in mortality was for cold (2.0%, 95% confidence interval (CI): 1.4%, 2.6%), followed by heat (1.2%, 95% CI: 0.7%, 1.7%), and temperature variability (0.5%, 95% CI: 0.3%, 0.7%). There was no clear temporal pattern in mortality risk associated with any temperature exposure in Australia. Heat, cold and temperature variability together resulted in 42,414 deaths during the study period, accounting for about 6.0% of all deaths. Most of attributable deaths were due to cold (61.4%), and noticeably, contribution from temperature variability (28.0%) was greater than that from heat (10.6%).

CONCLUSIONS

Exposure to either cold or heat or a large variation in temperature was associated with increased mortality risk in Australia, but population adaptation appeared to have not occurred in most cities studied. Most of the temperature-induced deaths were attributable to cold, and contributions from temperature variability were greater than that from heat. Our findings highlight that, in addition to heat and cold, temperature variability needs to be considered in assessing and projecting the health impacts of climate change.

摘要

目的

有关不同温度暴露(即热、冷和显著温度变化)对死亡率的相对贡献的证据有限。本研究旨在检验澳大利亚因热、冷和温度变化导致的死亡率风险及其相关死亡负担。

方法

我们收集了 2000 年至 2009 年澳大利亚五个人口最多的城市(悉尼、墨尔本、布里斯班、阿德莱德和珀斯)的全因死亡和天气变量的每日时间序列数据。温度变异性是通过相邻两天每小时温度的标准差计算得出的。采用三阶段分析。我们首先使用拟泊松回归模型,在控制长期趋势和季节性、周几和随时间变化的人口变化的情况下,对热(暖季平均温度)、冷(冷季平均温度)和全年温度变异性与死亡率的关联进行建模。然后,我们使用简化的对数线性回归模型估计不同非最佳温度的影响。最后,我们计算并比较了不同非最佳温度导致的死亡比例(%)。

结果

死亡率增加最多的是冷(2.0%,95%置信区间(CI):1.4%,2.6%),其次是热(1.2%,95%CI:0.7%,1.7%)和温度变异性(0.5%,95%CI:0.3%,0.7%)。在澳大利亚,任何温度暴露与死亡率风险之间都没有明显的时间模式。在研究期间,热、冷和温度变异性共同导致 42414 人死亡,约占所有死亡人数的 6.0%。归因于死亡的大部分是由于冷(61.4%),值得注意的是,温度变异性(28.0%)的贡献大于热(10.6%)。

结论

在澳大利亚,暴露于热、冷或温度大幅波动均与死亡率风险增加有关,但研究中的大多数城市似乎没有发生人群适应。大部分由温度引起的死亡归因于冷,而温度变异性的贡献大于热。我们的研究结果强调,除了热和冷之外,在评估和预测气候变化对健康的影响时,还需要考虑温度变异性。

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