Niu Yanlin, Li Zhichao, Gao Yuan, Liu Xiaobo, Xu Lei, Vardoulakis Sotiris, Yue Yujuan, Wang Jun, Liu Qiyong
State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping, Beijing, 102206 China.
Beijing Center for Disease Prevention and Control, Institute for Nutrition and Food Hygiene, Beijing, China.
Curr Clim Change Rep. 2021;7(3):87-97. doi: 10.1007/s40641-021-00173-3. Epub 2021 Apr 27.
This review aims to identify the key factors, methods, and spatial units used in the development and validation of the heat vulnerability index (HVI) and discuss the underlying limitations of the data and methods by evaluating the performance of the HVI.
Thirteen studies characterizing the factors of the HVI development and relating the index with validation data were identified. Five types of factors (i.e., hazard exposure, demographic characteristics, socioeconomic conditions, built environment, and underlying health) of the HVI development were identified, and the top five were social cohesion, race, and/or ethnicity, landscape, age, and economic status. The principal component analysis/factor analysis (PCA/FA) was often used in index development, and four types of spatial units (i.e., census tracts, administrative area, postal code, grid) were used for establishing the relationship between factors and the HVI. Moreover, although most studies showed that a higher HVI was often associated with the increase in health risk, the strength of the relationship was weak.
This review provides a retrospect of the major factors, methods, and spatial units used in development and validation of the HVI and helps to define the framework for future studies. In the future, more information on the hazard exposure, underlying health, governance, and protection awareness should be considered in the HVI development, and the duration and location of validation data should be strengthened to verify the reliability of HVI.
The online version contains supplementary material available at 10.1007/s40641-021-00173-3.
本综述旨在确定热脆弱性指数（HVI）开发与验证过程中使用的关键因素、方法和空间单元，并通过评估HVI的性能来探讨数据和方法的潜在局限性。
共确定了13项描述HVI开发因素并将该指数与验证数据相关联的研究。确定了HVI开发的五种因素类型（即灾害暴露、人口特征、社会经济状况、建成环境和基础健康状况），其中排名前五的是社会凝聚力、种族和/或民族、景观、年龄和经济状况。主成分分析/因子分析（PCA/FA）常用于指数开发，四种空间单元类型（即普查区、行政区、邮政编码、网格）用于建立因素与HVI之间的关系。此外，尽管大多数研究表明较高的HVI通常与健康风险增加相关，但这种关系的强度较弱。
本综述回顾了HVI开发与验证过程中使用的主要因素、方法和空间单元，并有助于确定未来研究的框架。未来，在HVI开发中应考虑更多关于灾害暴露、基础健康、治理和保护意识的信息，并应加强验证数据的持续时间和地点，以验证HVI的可靠性。
在线版本包含可在10.1007/s40641-021-00173-3获取的补充材料。
