Heaton Matthew J, Sain Stephan R, Greasby Tamara A, Uejio Christopher K, Hayden Mary H, Monaghan Andrew J, Boehnert Jennifer, Sampson Kevin, Banerjee Deborah, Nepal Vishnu, Wilhelmi Olga V
Department of Statistics, Brigham Young University, 223 TMCB, Provo, UT 84602, United States.
Institute for Mathematics Applied to Geosciences, National Center for Atmospheric Research, Box 80307-3000, Boulder, CO, United States.
Spat Spatiotemporal Epidemiol. 2014 Apr;8:23-33. doi: 10.1016/j.sste.2014.01.002. Epub 2014 Jan 24.
Identifying and characterizing urban vulnerability to heat is a key step in designing intervention strategies to combat negative consequences of extreme heat on human health. This study combines excess non-accidental mortality counts, numerical weather simulations, US Census and parcel data into an assessment of vulnerability to heat in Houston, Texas. Specifically, a hierarchical model with spatially varying coefficients is used to account for differences in vulnerability among census block groups. Socio-economic and demographic variables from census and parcel data are selected via a forward selection algorithm where at each step the remaining variables are orthogonalized with respect to the chosen variables to account for collinearity. Daily minimum temperatures and composite heat indices (e.g. discomfort index) provide a better model fit than other ambient temperature measurements (e.g. maximum temperature, relative humidity). Positive interactions between elderly populations and heat exposure were found suggesting these populations are more responsive to increases in heat.
识别和表征城市热脆弱性是设计干预策略以应对极端高温对人类健康负面影响的关键一步。本研究将非意外超额死亡人数、数值气象模拟、美国人口普查和地块数据结合起来，对德克萨斯州休斯顿的热脆弱性进行评估。具体而言，使用具有空间变化系数的分层模型来解释人口普查街区组之间的脆弱性差异。通过向前选择算法从人口普查和地块数据中选择社会经济和人口变量，在每一步中，其余变量相对于所选变量进行正交化以考虑共线性。每日最低温度和综合热指数（如不适指数）比其他环境温度测量值（如最高温度、相对湿度）提供了更好的模型拟合。研究发现老年人群体与热暴露之间存在正相关，表明这些人群对热度增加更为敏感。
