Objectives Previous research has established links between child, family, and neighborhood disadvantages and child asthma. We add to this literature by first characterizing neighborhoods in Houston, TX by demographic, economic, and air quality characteristics to establish differences in pediatric asthma diagnoses across neighborhoods. Second, we identify the relative risk of social, economic, and environmental risk factors for child asthma diagnoses. Methods We geocoded and linked electronic pediatric medical records to neighborhood-level social and economic indicators. Using latent profile modeling techniques, we identified Advantaged, Middle-class, and Disadvantaged neighborhoods. We then used a modified version of the Blinder-Oaxaca regression decomposition method to examine differences in asthma diagnoses across children in these different neighborhoods. Results Both compositional (the characteristics of the children and the ambient air quality in the neighborhood) and associational (the relationship between child and air quality characteristics and asthma) differences within the distinctive neighborhood contexts influence asthma outcomes. For example, unequal exposure to PM2.5 and O3 among children in Disadvantaged and Middle-class neighborhoods contribute to asthma diagnosis disparities within these contexts. For children in Disadvantaged and Advantaged neighborhoods, associational differences between racial/ethnic and socioeconomic characteristics and asthma diagnoses explain a significant proportion of the gap. Conclusions for Practice Our results provide evidence that differential exposure to pollution and protective factors associated with non-Hispanic White children and children from affluent families contribute to asthma disparities between neighborhoods. Future researchers should consider social and racial inequalities as more proximate drivers, not merely as associated, with asthma disparities in children.
Keywords: Asthma; Children and youth; Environmental quality; Neighborhood disadvantage; Quantitative analysis.