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首页> 外文期刊>Environmental Health: A Global Access Science Source >Projections of temperature-attributable premature deaths in 209 U.S. cities using a cluster-based Poisson approach
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Projections of temperature-attributable premature deaths in 209 U.S. cities using a cluster-based Poisson approach

机译:使用基于聚类的Poisson方法预测美国209个城市中温度引起的过早死亡

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Background A warming climate will affect future temperature-attributable premature deaths. This analysis is the first to project these deaths at a near national scale for the United States using city and month-specific temperature-mortality relationships. Methods We used Poisson regressions to model temperature-attributable premature mortality as a function of daily average temperature in 209 U.S. cities by month. We used climate data to group cities into clusters and applied an Empirical Bayes adjustment to improve model stability and calculate cluster-based month-specific temperature-mortality functions. Using data from two climate models, we calculated future daily average temperatures in each city under Representative Concentration Pathway 6.0. Holding population constant at 2010 levels, we combined the temperature data and cluster-based temperature-mortality functions to project city-specific temperature-attributable premature deaths for multiple future years which correspond to a single reporting year. Results within the reporting periods are then averaged to account for potential climate variability and reported as a change from a 1990 baseline in the future reporting years of 2030, 2050 and 2100. Results We found temperature-mortality relationships that vary by location and time of year. In general, the largest mortality response during hotter months (April – September) was in July in cities with cooler average conditions. The largest mortality response during colder months (October–March) was at the beginning (October) and end (March) of the period. Using data from two global climate models, we projected a net increase in premature deaths, aggregated across all 209 cities, in all future periods compared to 1990. However, the magnitude and sign of the change varied by cluster and city. Conclusions We found increasing future premature deaths across the 209 modeled U.S. cities using two climate model projections, based on constant temperature-mortality relationships from 1997 to 2006 without any future adaptation. However, results varied by location, with some locations showing net reductions in premature temperature-attributable deaths with climate change.
机译:背景技术气候变暖将影响未来因温度造成的过早死亡。该分析首次使用城市和月份特定的温度-死亡率关系,以接近全国的规模预测了这些死亡人数。方法我们使用Poisson回归模型对美国209个城市的温度引起的过早死亡与每日平均温度之间的关系进行了建模。我们使用气候数据将城市分组为一组,并进行了经验贝叶斯调整,以提高模型的稳定性并计算基于组的特定月份的温度-死亡率函数。使用来自两个气候模型的数据,我们根据“代表浓度路径6.0”计算了每个城市的未来日平均温度。在保持人口稳定在2010年水平的基础上,我们将温度数据和基于聚类的温度死亡率函数相结合,以预测对应于单个报告年度的多个未来年份特定于城市的温度引起的过早死亡。然后将报告期内的结果取平均值以说明潜在的气候变异性,并报告为未来2030、2050和2100年的报告年份中1990年基线的变化。结果我们发现温度与死亡率的关系随位置和时间的不同而变化。 。一般而言,在炎热月份(4月至9月)中,最大的死亡率响应发生在平均条件较凉爽的城市中的7月。在较冷的月份(10月至3月)中,死亡率响应最大的时期是该时期的开始(10月)和结束(3月)。利用来自两个全球气候模型的数据,我们预测与1990年相比,未来209个城市的过早死亡人数将净增加,与1990年相比。但是,变化的幅度和迹象因城市和城市而异。结论我们发现,根据1997年至2006年的恒定温度与死亡率的关系,并且没有任何未来的适应措施,使用两个气候模型预测,在209个模拟的美国城市中,未来的过早死亡人数正在增加。但是,结果因地点而异,一些地点显示由于气候变化而导致的过早温度造成的死亡人数净减少。

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