ICES, Toronto, ON, Canada.
Department of Medicine, Western University, London, ON, Canada.
Sci Rep. 2021 Apr 14;11(1):8153. doi: 10.1038/s41598-021-87203-0.
Urban areas have complex thermal distribution. We examined the association between extreme temperature and mortality in urban Ontario, using two temperature data sources: high-resolution and weather station data. We used distributed lag non-linear Poisson models to examine census division-specific temperature-mortality associations between May and September 2005-2012. We used random-effect multivariate meta-analysis to pool results, adjusted for air pollution and temporal trends, and presented risks at the 99th percentile compared to minimum mortality temperature. As additional analyses, we varied knots, examined associations using different temperature metrics (humidex and minimum temperature), and explored relationships using different referent values (most frequent temperature, 75th percentile of temperature distribution). Weather stations yielded lower temperatures across study months. U-shaped associations between temperature and mortality were observed using both high-resolution and weather station data. Temperature-mortality relationships were not statistically significant; however, weather stations yielded estimates with wider confidence intervals. Similar findings were noted in additional analyses. In urban environmental health studies, high-resolution temperature data is ideal where station observations do not fully capture population exposure or where the magnitude of exposure at a local level is important. If focused upon temperature-mortality associations using time series, either source produces similar temperature-mortality relationships.
城市地区的热量分布较为复杂。我们使用两种温度数据源(高分辨率和气象站数据),研究了安大略省城市极端温度与死亡率之间的关系。我们使用分布式滞后非线性泊松模型,研究了 2005 年至 2012 年 5 月至 9 月期间,每个普查分区的具体温度-死亡率关系。我们调整了空气污染和时间趋势因素,使用随机效应多元荟萃分析对结果进行了汇总,并根据 99 百分位数与最低死亡率温度相比,展示了风险。作为额外的分析,我们改变了节点,使用不同的温度指标(湿热指数和最低温度)来研究关联,并使用不同的参考值(最常见温度、温度分布的 75 百分位数)来探索关系。在整个研究期间,气象站的温度都较低。使用高分辨率和气象站数据均观察到温度与死亡率之间呈 U 型关联。尽管温度-死亡率关系没有统计学意义,但气象站的估计值置信区间较宽。在其他分析中也注意到了类似的发现。在城市环境健康研究中,如果气象站观测不能完全捕捉到人群暴露情况,或者在当地层面暴露的程度很重要,那么高分辨率温度数据是理想的。如果使用时间序列重点研究温度-死亡率关联,那么两种数据源都可以产生类似的温度-死亡率关系。