title: A novel approach to the characterization of cumulative exposure for the study of chronic occupational disease.
abstract: Inappropriate parameterization of an exposure metric for the study of occupational and environmental hazards may lead to significant misclassification and biased results. A model for identification of an optimal expression for cumulative exposure that includes exponentiated terms for concentration and time was developed. When the values of the exponents are allowed to vary, an optimal expression for cumulative exposure may be identified. The approach has advantages for the study of chronic hazards, in that it is flexible, limits the number of assumptions, and incorporates many of the models generally suggested in the literature. In addition, the model results may be interpreted to suggest particular pathophysiologic mechanisms. The model was implemented with data from a previously studied cohort of underground coal miners, and the associations between the exposure metric and measures of obstructive lung disease were identified. The results demonstrated that the exposure metric can improve the association of dust exposure histories with various outcomes over the usual measure of cumulative exposure. However, in the particular data set used, the overall predictive power of alternative models was similar and the interpretability of the results was limited.
authors.affiliation: Department of Environmental Health, University of Washington, Seattle 98195.
authors.forename: N S
authors.initials: NS
authors.lastname: Seixas
authors.forename: T G
authors.initials: TG
authors.lastname: Robins
authors.forename: M
authors.initials: M
authors.lastname: Becker
mesh_terms: D000328:Adult; D002908:Chronic Disease; D003032:Coal Mining; D015331:Cohort Studies; D004784:Environmental Monitoring / Q000379:methods*; D004812:Epidemiologic Methods; D062665:Epidemiological Monitoring; D006801:Humans; D008173:Lung Diseases, Obstructive / Q000453:epidemiology*; D008875:Middle Aged; D008962:Models, Theoretical; D009784:Occupational Diseases / Q000453:epidemiology*; D016273:Occupational Exposure / Q000032:analysis*; D012044:Regression Analysis