Hurricane Harvey and people with disabilities: Disproportionate exposure to flooding in Houston, Texas
Hurricane Harvey and people with disabilities: Disproportionate exposure to flooding in Houston, Texas
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DOI：
10.1016/j.socscimed.2019.02.039
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发表时间：
2019-04-01
影响因子：
5.4
通讯作者：
Collins, Timothy W.
中科院分区：
文献类型：
--
作者：
Chakraborty, Jayajit;Grineski, Sara E.;Collins, Timothy W.
虽然许多环境正义（EJ）研究发现，社会弱势群体，如种族/少数民族和低收入个体，受到环境危害的影响不成比例，但以前的EJ研究并没有检查残疾人是否不成比例地暴露于自然灾害。我们的文章通过对哈里斯县的哈维飓风引起的洪水与残疾人所在地之间的关系进行了首次分布式EJ研究，从而解决了这一差距。哈里斯县是德克萨斯州人口最多的县，受到了这场灾难的严重影响。我们的目标是在控制相关的社会人口因素后，确定社区（人口普查区）水平的洪水面积范围是否与任何残疾人和特定类型的残疾人不成比例地分布。我们的研究将美国联邦紧急事务管理局开发的哈维淹没足迹的地图信息与2012-2016年美国社区调查的残疾和社会人口特征数据相结合。统计分析基于二元相关性和多元广义估计方程，这是一种适合聚类数据的建模技术。结果表明，在控制了种族/民族、社会经济因素和聚类之后，在残疾人比例较高的社区，哈维引发的洪水的面积范围明显更大。与面临其他类型困难的人相比，有认知和行动困难的残疾人更有可能居住在洪水面积比例较高的社区。这些结果为更详细地调查哈维飓风对残疾人造成的不成比例的影响提供了一个重要的起点。我们的研究结果还强调，在未来的EJ研究以及自然灾害的规划和管理中，越来越需要考虑身体和精神残疾的个体。
While numerous environmental justice (EJ) studies have found socially disadvantaged groups such as racial/ethnic minorities and low-income individuals to be disproportionately affected by environmental hazards, previous EJ research has not examined whether disabled individuals are disproportionately exposed to natural hazards. Our article addresses this gap by conducting the first distributive EJ study of the relationship between flooding caused by Hurricane Harvey and locations of people with disabilities in Harris County, the most populous county in Texas that was severely impacted by this disaster. Our objective is to determine whether the areal extent of flooding at the neighborhood (census tract) level is disproportionately distributed with respect to people with any disability and with specific types of disabilities, after controlling for relevant socio-demographic factors. Our study integrates cartographic information from Harvey's Inundation Footprint developed by the U.S. Federal Emergency Management Agency with data on disability and socio-demographic characteristics from the 2012-2016 American Community Survey. Statistical analyses are based on bivariate correlations and multi-variate generalized estimating equations, a modeling technique appropriate for clustered data. Results indicate that the areal extent of Harvey-Induced flooding is significantly greater in neighborhoods with a higher proportion of disabled residents, after controlling for race/ethnicity, socioeconomic factors, and clustering. Disabled individuals with cognitive and ambulatory difficulties are more likely to reside in neighborhoods with a higher proportion of flooded area, compared to those facing other types of difficulties. These results represent an important starting point for more detailed investigation on the disproportionate impacts associated with Hurricane Harvey for people with disabilities. Our findings also highlight the growing need to consider individuals with physical and mental disabilities in future EJ research, as well as planning and management of natural disasters.