Two assumptions have underpinned environmental justice over the past several decades: (1) uneven environmental exposures yield correspondingly unequal health impacts and (2) these effects are stable across space. To test these assumptions, relationships for residential pest and PM2.5 exposures with children’s wheezing severity are examined using global (ordinary least squares) and local [geographically weighted regression (GWR)] models using cross-sectional observational survey data from El Paso (Texas) children. In the global model, having pests and higher levels of PM2.5 were weakly associated with greater wheezing severity. The local model reveals two types of asthmogenic socio-environments, where environmental exposures more powerfully predict greater wheezing severity. The first is a lower-income context where children are disproportionately exposed to pests and PM2.5, and the second is a higher-income socio-environment where children are exposed to lower levels of PM2.5, yet PM2.5 is counterintuitively associated with more severe wheezing. Findings demonstrate that GWR is a powerful tool for understanding relationships between environmental conditions, social characteristics, and health inequalities.
- El Paso, Texas
- Environmental health justice
- Geographically weighted regression
- Health disparities
ASJC Scopus subject areas
- Environmental Science (miscellaneous)