Environmental Health Services, British Columbia Centre for Disease Control, 655 West 12th Avenue, Vancouver, BC V5Z 4R4, Canada.
Department of Land Surveying and Geo-informatics, Hong Kong Polytechnic University, 181 Chatham Road South, Kowloon, Hong Kong.
Environ Int. 2017 Dec;109:42-52. doi: 10.1016/j.envint.2017.09.011. Epub 2017 Sep 18.
Mortality attributable to extreme hot weather is a growing concern in many urban environments, and spatial heat vulnerability indexes are often used to identify areas at relatively higher and lower risk. Three indexes were developed for greater Vancouver, Canada using a pool of 20 potentially predictive variables categorized to reflect social vulnerability, population density, temperature exposure, and urban form. One variable was chosen from each category: an existing deprivation index, senior population density, apparent temperature, and road density, respectively. The three indexes were constructed from these variables using (1) unweighted, (2) weighted, and (3) data-driven Heat Exposure Integrated Deprivation Index (HEIDI) approaches. The performance of each index was assessed using mortality data from 1998-2014, and the maps were compared with respect to spatial patterns identified. The population-weighted spatial correlation between the three indexes ranged from 0.68-0.89. The HEIDI approach produced a graduated map of vulnerability, whereas the other approaches primarily identified areas of highest risk. All indexes performed best under extreme temperatures, but HEIDI was more useful at lower thresholds. Each of the indexes in isolation provides valuable information for public health protection, but combining the HEIDI approach with unweighted and weighted methods provides richer information about areas most vulnerable to heat.
归因于极端炎热天气导致的死亡率是许多城市环境中日益关注的问题，空间热脆弱性指数通常用于识别风险相对较高和较低的区域。加拿大大温哥华地区开发了三个指数，使用了一组 20 个潜在的预测变量，这些变量分为反映社会脆弱性、人口密度、温度暴露和城市形态的类别。从每个类别中选择一个变量：现有贫困指数、老年人密度、明显温度和道路密度。这三个指数是使用（1）非加权、（2）加权和（3）数据驱动的热暴露综合贫困指数（HEIDI）方法从这些变量中构建的。使用 1998-2014 年的死亡率数据评估了每个指数的性能，并比较了地图以识别空间模式。三个指数的人口加权空间相关性在 0.68-0.89 之间。HEIDI 方法生成了脆弱性的分级地图，而其他方法主要确定了高风险区域。所有指数在极端温度下表现最佳，但 HEIDI 在较低的阈值下更有用。每个指数的单独使用都为公共卫生保护提供了有价值的信息，但将 HEIDI 方法与非加权和加权方法结合使用，可以提供有关对热最脆弱的区域的更丰富信息。
