This project investigates the associations of chronic obstructive pulmonary disease (COPD) with occupational exposures through respiratory symptoms and lung function measures for the Canadian Obstructive Lung Disease (COLD) study. We illustrate the methodology using the relevant data from the study. We begin with multiple linear/logistic regression analyses of the COLD data from all the nine Canadian sites of the study. The analyses show how the respiratory symptoms and lung function measures are associated with occupational exposures overall after adjusting for a few other factors/exposures. To address potential heterogeneity across the nine sites, data from the individual sites are separately analyzed and pooled together for the whole study by a meta-analysis approach. Further, we consider an alternative approach based on multi-level modeling, and analyze the COLD data via mixed-effects regression models. The three sets of analyses are summarized and compared in the project. We report new insights into understanding of associations of COPD with occupational exposures.
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Thesis advisor: Hu, Joan
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