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DOI: 10.1371/journal.pone.0091917
论文题名:
Spatial Cluster Detection of Air Pollution Exposure Inequities across the United States
作者: Bin Zou; Fen Peng; Neng Wan; Keita Mamady; Gaines J. Wilson
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2014
发表日期: 2014-3-19
卷: 9, 期:3
语种: 英语
英文关键词: Air pollution ; Benzene ; Census ; Educational attainment ; Pollution ; Spatial autocorrelation ; United States ; Age groups
英文摘要: Air quality is known to be a key factor in affecting the wellbeing and quality of life of the general populous and there is a large body of knowledge indicating that certain underrepresented groups may be overexposed to air pollution. Therefore, a more precise understanding of air pollution exposure as a driving cause of health disparities between and among ethnic and racial groups is necessary. Utilizing 52,613 urban census tracts across the United States, this study investigates age, racial, educational attainment and income differences in exposure to benzene pollution in 1999 as a case. The study examines spatial clustering patterns of these inequities using logistic regression modeling and spatial autocorrelation methods such as the Global Moran's I index and the Anselin Local Moran's I index. Results show that the age groups of 0 to 14 and those over 60 years old, individuals with less than 12 years of education, racial minorities including Blacks, American Indians, Asians, some other races, and those with low income were exposed to higher levels of benzene pollution in some census tracts. Clustering analyses stratified by age, education, and race revealed a clear case of disparities in spatial distribution of exposure to benzene pollution across the entire United States. For example, people aged less than 4 years from the western south and the Pacific coastal areas exhibit statistically significant clusters. The findings confirmed that there are geographical-location based disproportionate pattern of exposures to benzene air pollution by various socio-demographic factors across the United States and this type of disproportionate exposure pattern can be effectively detected by a spatial autocorrelation based cluster analysis method. It is suggested that there is a clear and present need for programs and services that will reduce inequities and ultimately improve environmental conditions for all underrepresented groups in the United States.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0091917&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/19907
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: School of Geosciences and Info-Physics, Central South University, Changsha, Hunan, China;School of Geosciences and Info-Physics, Central South University, Changsha, Hunan, China;Department of Geography, University of Utah, Salt Lake City, Utah, United States of America;Department of Epidemiology and Health Statistics, School of Public Health, Central South University, Changsha, Hunan, China;Department of Biological Sciences, Huston-Tillotson University, Austin, Texas, United States of America

Recommended Citation:
Bin Zou,Fen Peng,Neng Wan,et al. Spatial Cluster Detection of Air Pollution Exposure Inequities across the United States[J]. PLOS ONE,2014-01-01,9(3)
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