Spatial cluster detection of air pollution exposure inequities across the United States

PLoS One. 2014 Mar 19;9(3):e91917. doi: 10.1371/journal.pone.0091917. eCollection 2014.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Air Pollution / analysis*
  • Air Pollution / economics
  • Benzene / analysis
  • Cluster Analysis
  • Demography
  • Educational Status
  • Environmental Exposure / analysis*
  • Environmental Exposure / economics
  • Geography
  • Healthcare Disparities* / economics
  • Humans
  • Income
  • Middle Aged
  • Odds Ratio
  • Racial Groups
  • United States
  • Young Adult

Substances

  • Benzene

Grants and funding

The research reported in this paper was funded by the National Natural Science Foundation of China (Project No. 41201384, http://www.nsfc.gov.cn/Portal0/default152.htm), the Hunan Provincial Natural Science Foundation of China (Project No. 12JJ3034, http://www.hnst.gov.cn/zzjg/nsjg/hnszrkxjjwyhbgs/), the State Key Laboratory of Resources and Environmental Information System (http://www.lreis.ac.cn/sc/index.aspx). Bin Zou would also like to thank the grant from the Key Laboratory of Geo-informatics of State Bureau of Surveying and Mapping (Project No. 201328, http://www.casm.ac.cn/), as well as the NieYing Talent Program of Central South University (www.csu.edu.cn). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.