Racialized Structural Vulnerability: Neighborhood Racial Composition, Concentrated Disadvantage, and Fine Particulate Matter in California

Int J Environ Res Public Health. 2019 Sep 1;16(17):3196. doi: 10.3390/ijerph16173196.

Abstract

This study contributes to previous research by advancing a "racialized structural vulnerability" framework and presenting a new empirical analysis of the relationship between neighborhood Asian, Black, and Latinx composition; extrinsic and intrinsic vulnerability; and PM2.5 exposures in California with secondary data from 2004-2014. Principal component analyses revealed that tract Latinx composition was highly correlated with extrinsic vulnerability (economic disadvantage and limited English-speaking ability), and that tract Black composition was highly correlated with intrinsic vulnerability (elevated prevalence of asthma-related emergency department visits and low birth weight). Spatial lag regression models tested hypotheses regarding the association between Asian, Black, and Latinx population vulnerability factors and the 2009-2011 annual average PM2.5 percentile rankings, net of emissions and spatial covariates. Results indicated that the percent Latinx population, followed by the regional clustering of PM2.5, and the percent of non-Latinx Black and non-Latinx Asian population were the strongest positive multivariable correlates of PM2.5 percentile rankings, net of other factors. Additional analyses suggested that despite shifting demographic and spatial correlates of 2012-2014 PM2.5 exposures, the tracts' Black and Latinx composition and location in the San Joaquin Valley remain important vulnerability factors with implications for future research and policy.

Keywords: CalEnviroScreen; California; environmental inequality; particulate matter; population vulnerability; race; segregation; spatial analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollutants
  • Air Pollution / statistics & numerical data*
  • Asthma
  • California
  • Cluster Analysis
  • Emergency Service, Hospital
  • Hispanic or Latino / statistics & numerical data*
  • Humans
  • Infant, Low Birth Weight
  • Infant, Newborn
  • Particulate Matter*
  • Principal Component Analysis
  • Racial Groups / statistics & numerical data*
  • Residence Characteristics / statistics & numerical data*
  • Risk Factors
  • Vulnerable Populations

Substances

  • Air Pollutants
  • Particulate Matter