Using geographically weighted regression for environmental justice analysis: Cumulative cancer risks from air toxics in Florida
Using geographically weighted regression for environmental justice analysis: Cumulative cancer risks from air toxics in Florida
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DOI：
10.1016/j.ssresearch.2010.08.006
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发表时间：
2011-01-01
影响因子：
2.5
通讯作者：
Chakraborty, Jayajit
中科院分区：
文献类型：
--
作者：
Gilbert, Angela;Chakraborty, Jayajit
以前对环境正义的定量研究一直受到用于测量健康风险的简单假设和传统回归技术的限制，这些假设和传统回归技术无法识别统计关系中的空间变化。我们通过案例研究来解决这些差距，该案例研究探讨（a）佛罗里达暴露于有害空气污染物的潜在健康风险是否与种族/民族和社会经济地位有关，以及（B）健康风险和种族之间的统计关联的重要性各州的种族或社会经济地位各不相同这项研究将EPA编制的人口普查区水平的累积癌症风险估计与2000年人口普查数据和称为地理加权回归的空间统计技术相结合，使我们能够探索分析结果的空间变异性我们的发现表明虽然种族和民族与佛罗里达的癌症风险显著相关，但传统回归可能会隐藏与环境正义分析相关的统计关系中的重要局部变化（C）2010 Elsevier Inc.
Previous quantitative research on environmental Justice has been limited by simplistic assumptions used to measure health risks and traditional regression techniques that fail to discern spatial variations in statistical relationships We address these gaps through a case study that examines (a) whether potential health risks from exposure to hazardous air pollutants in Florida are related to race/ethnicity and socioeconomic status and (b) how the significance of statistical associations between health risk and race/ethnicity or socioeconomic status vary across the state This study integrates census tract level estimates of cumulative cancer risk compiled by the EPA with Census 2000 data and a spatial statistical technique known as geographically weighted regression that allows us to explore spatial variability in analytical results Our findings indicate that while race and ethnicity are significantly related to cancer risks in Florida, conventional regression can hide important local variations in statistical relationships relevant to environmental justice analysis (C) 2010 Elsevier Inc All rights reserved