DeVine Aubrey C, Vu Phuong T, Yost Michael G, Seto Edmund Y W, Busch Isaksen Tania M
Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98105, USA.
Department of Biostatistics, University of Washington, Seattle, WA 98105, USA.
Int J Environ Res Public Health. 2017 Aug 20;14(8):937. doi: 10.3390/ijerph14080937.
This research analyzed the relationship between extreme heat and Emergency Medical Service (EMS) calls in King County, WA, USA between 2007 and 2012, including the effect of community-level characteristics. Extreme heat thresholds for the Basic Life Support (BLS) data and the Advanced Life Support (ALS) data were found using a piecewise generalized linear model with Akaike Information Criterion (AIC). The association between heat exposure and EMS call rates was investigated using a generalized estimating equations with Poisson mean model, while adjusting for community-level indicators of poverty, impervious surface, and elderly population (65+). In addition, we examined the effect modifications of these community-level factors. Extreme-heat thresholds of 31.1 °C and 33.5 °C humidex were determined for the BLS and ALS data, respectively. After adjusting for other variables in the model, increased BLS call volume was significantly associated with occurring on a heat day (relative rate (RR) = 1.080, < 0.001), as well as in locations with higher percent poverty (RR = 1.066, < 0.001). No significant effect modification was identified for the BLS data on a heat day. Controlling for other variables, higher ALS call volume was found to be significantly associated with a heat day (RR = 1.067, < 0.001), as well as in locations with higher percent impervious surface (RR = 1.015, = 0.039), higher percent of the population 65 years or older (RR = 1.057, = 0.005), and higher percent poverty (RR = 1.041, = 0.016). Furthermore, percent poverty and impervious surface were found to significantly modify the relative rate of ALS call volumes between a heat day and non-heat day. We conclude that EMS call volume increases significantly on a heat day compared to non-heat day for both call types. While this study shows that there is some effect modification between the community-level variables and call volume on a heat day, further research is necessary. Our findings also suggest that with adequate power, spatially refined analyses may not be necessary to accurately estimate the extreme-heat effect on health.
本研究分析了2007年至2012年美国华盛顿州金县极端高温与紧急医疗服务(EMS)呼叫之间的关系,包括社区层面特征的影响。使用带有赤池信息准则(AIC)的分段广义线性模型确定基础生命支持(BLS)数据和高级生命支持(ALS)数据的极端高温阈值。使用带有泊松均值模型的广义估计方程研究热暴露与EMS呼叫率之间的关联,同时对贫困、不透水表面和老年人口(65岁及以上)的社区层面指标进行调整。此外,我们还研究了这些社区层面因素的效应修正。分别为BLS和ALS数据确定了31.1℃和33.5℃热指数的极端高温阈值。在对模型中的其他变量进行调整后,BLS呼叫量增加与高温日显著相关(相对率(RR)=1.080,<0.001),以及与贫困率较高的地区相关(RR=1.066,<0.001)。对于BLS数据,在高温日未发现显著的效应修正。在控制其他变量后,发现较高的ALS呼叫量与高温日显著相关(RR=1.067,<0.001),以及与不透水表面比例较高的地区相关(RR=1.015,=0.039)、65岁及以上人口比例较高的地区相关(RR=1.057,=0.005)以及贫困率较高的地区相关(RR=1.041,=0.016)。此外,发现贫困率和不透水表面显著修正了高温日与非高温日之间ALS呼叫量的相对率。我们得出结论,与非高温日相比,两种呼叫类型在高温日的EMS呼叫量均显著增加。虽然本研究表明社区层面变量与高温日呼叫量之间存在一些效应修正,但仍需进一步研究。我们的研究结果还表明,在有足够效力的情况下,可能无需进行空间细化分析来准确估计极端高温对健康的影响。