Evaluation of potential confounding by smoking in the presence of misclassified smoking data in a cohort study of workers exposed to acrylonitrile.

Abstract

OBJECTIVES:

To evaluate the extent to which lung cancer mortality risk estimates in relation to acrylonitrile (AN) exposure may have been confounded by smoking in the presence of misclassified smoking data.

METHODS:

Subjects were 992 white men employed for three or more months between 1960 and 1996 at a chemical plant in Lima, Ohio. We used Monte Carlo-based sensitivity analysis to address possible confounding by smoking.

RESULTS:

In Monte Carlo simulations that accounted for the relationship between smoking and AN exposure, mean relative risks for lung cancer mortality in relation to AN exposure decreased and we observed somewhat less evidence of an exposure-response relationship.

CONCLUSIONS:

Our simulations suggest that the relationship between AN exposure and lung cancer mortality was positively confounded by smoking in the original Lima cohort study.

• Authors: Sarah Downing Zimmerman, Gary M Marsh, Ada O Youk, Evelyn Talbot
• Journal: Journal of occupational and environmental medicine (J Occup Environ Med) Vol. 57 Issue 2 Pg. 146-51 (Feb 2015) ISSN: 1536-5948 [Electronic] United States
• PMID: 25612297 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)

Chemical References

• Air Pollutants, Occupational
• Carcinogens
• Acrylonitrile

Topics

• Acrylonitrile (toxicity)
• Air Pollutants, Occupational (toxicity)
• Carcinogens (toxicity)
• Case-Control Studies
• Chemical Industry
• Cohort Studies
• Computer Simulation
• Confounding Factors, Epidemiologic
• Data Collection (standards)
• Humans
• Lung Neoplasms (etiology, mortality)
• Male
• Monte Carlo Method
• Occupational Diseases (etiology, mortality)
• Occupational Exposure (adverse effects)
• Ohio (epidemiology)
• Prevalence
• Smoking (epidemiology)