Marginal Structural Models in Occupational Epidemiology: Application in a Study of Ischemic Heart Disease Incidence and PM2.5 in the US Aluminum Industry

Marginal structural models (MSMs) and inverse probability weighting can be used to estimate risk in a cohort of active workers if there is a time-varying confounder (e.g., health status) affected by prior exposure-a feature of the healthy worker survivor effect. We applied Cox MSMs in a study of incident ischemic heart disease and exposure to particulate matter with aerodynamic diameter of 2.5 mu m or less (PM2.5) in a cohort of 12,949 actively employed aluminum workers in the United States. The cohort was stratified by work process into workers in smelting facilities, herein referred to as smelters and workers in fabrication facilities, herein referred to as fabricators. The outcome was assessed by using medical claims data from 1998 to 2012. A composite risk score based on insurance claims was treated as a time-varying measure of health status. Binary PM2.5 exposure was defined by the 10th-percentile cutoff for each work process. Health status was associated with past exposure and predicted the outcome and sub-sequent exposure in smelters but not in fabricators. In smelters, the Cox MSM hazard ratio comparing those always exposed above the cutoff with those always exposed below the cutoff was 1.98 (95% confidence interval: 1.18, 3.32). In fabricators, the hazard ratio from a traditional Cox model was 1.34 (95% confidence interval: 0.98, 1.83). Results suggest that occupational PM2.5 exposure increases the risk of incident ischemic heart disease in workers in both aluminum smelting and fabrication facilities.