Local variability in the impacts of residential particulate matter and pest exposure on children’s wheezing severity: a geographically weighted regression analysis of environmental health justice

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 PM_2.5 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 PM_2.5 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 PM_2.5, and the second is a higher-income socio-environment where children are exposed to lower levels of PM_2.5, yet PM_2.5 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.