Segregation and Black/White differences in exposure to air toxics in 1990
Segregation and Black/White differences in exposure to air toxics in 1990
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DOI：
10.1289/ehp.02110s2289
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发表时间：
2002-04-01
影响因子：
10.4
通讯作者：
Lopez, R
中科院分区：
文献类型：
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作者：
Lopez, R
我研究了非西班牙裔黑人和非西班牙裔白色人在44个美国人口普查局定义的人口超过100万的大都市地区暴露于非标准空气污染物的差异，使用为美国环境保护局准备的空气有毒物质浓度数据，作为其累积暴露项目的一部分，结合美国人口普查数据。我测量了空气有毒物质暴露的差异;通过计算净差异分数，这是收入不平等分析中使用的统计指标，用于衡量整个暴露范围内的不平等。评分范围为11.52 - 83.60。在每个大都市地区，非西班牙裔黑人比非西班牙裔白人更有可能生活在总模拟空气有毒物质浓度较高的区域。为了评估暴露差异如此广泛变化的潜在原因，我以净差异得分作为因变量进行了多元回归分析。最初包括的自变量如下：相异指数（衡量隔离），黑人贫困/白色贫困（控制黑人/白色经济差异），人口密度和开车上班的人的百分比（单独和拼车），以及制造业就业的劳动力百分比（影响空气质量的因素）。经过初步分析后，我从模型中删除了密度和开车上班的人，因为它们在统计上不重要，它们不会增加模型的预测能力，它们的删除不会影响其他变量。最终模型的R-2为0.56。隔离的增加与潜在暴露于空气污染的差异增加有关。
I examined non-Hispanic Black and non-Hispanic White differences in exposure to noncriteria air pollutants in 44 U.S. Census Bureau-defined metropolitan areas with populations greater than one million, using data on air toxics concentrations prepared for the U.S. Environmental Protection Agency as part of its Cumulative Exposure Project combined with U.S. census data. I measured differences in exposure to air toxics; through the calculation of a net difference score, which is a statistical measure used in income inequality analysis to measure inequality over the whole range of exposures. The scores ranged from 11.52 to 83.60. In every metropolitan area, non-Hispanic Blacks arc more likely than non-Hispanic Whites to be living in tracts with higher total modeled air toxics concentrations. To assess potential reasons for such a wide variation in exposure differences, I performed a multiple regression analysis with the net difference score as the dependent variable. Independent variables initially included were as follows: the dissimilarity index (to measure segregation), Black poverty/White poverty (to control for Black/White economic differences), population density and percentage of persons traveling to work who drive to work (alone and in car pools), and percentage of workforce employed in manufacturing (factors affecting air quality). After an initial analysis I eliminated from the model the measures of density and the persons driving to work because they were statistically insignificant, they did not add to the predictive power of the model, and their deletion did not affect the other variables. The final model had an R-2 of 0.56. Increased segregation is associated with increased disparity in potential exposure to air pollution.