Assessing the health impacts of air pollution: a re-analysis of the Hamilton children's cohort data using a spatial analytic approach

Abstract

The objective of this paper was to reassess children's exposure to air pollution as well as investigate the importance of other covariates of respiratory health. We re-examined the Hamilton Children's Cohort (HCC) dataset with enhanced spatial analysis methods, refined in the approximately two decades since the original study was undertaken. Children's exposure to air pollution was first re-estimated using kriging and land-use regression. The land-use regression model performed better, compared to kriging, in capturing local variation of air pollution. Multivariate linear and logistic regression analysis was then applied for the study of potential risk factors for respiratory health. Findings agree with the HCC study-results, confirming that children's respiratory health was associated with maternal smoking, hospitalization in infancy and air pollution. However, results from this study reveal a stronger association between children's respiratory health and air pollution. Additionally, this study demonstrated associations with low-income, household crowding and chest illness in siblings.