Exposure Levels and Determinants of Softwood Dust Exposures in BC Lumber Mills, 1981-1997

Measurements of personal exposure to wood dust (n = 1237) collected by the Workers' Compensation Board of British Columbia, Canada, over the period 1981-1997 were used to construct an empirical model to identify broad determinants of softwood dust exposure. Potential determinants of exposure examined included species of tree processed; company; geographic location of lumber mill; department; job title; calendar year; and production factors such as board feet of lumber produced per year. A determinants of exposure model was built using multiple linear regression. Nested within this compliance database was a subset of samples collected for a research study. These enabled the authors to explore whether differences in exposure measurements can in part be explained by sampling strategy (research versus compliance). Potential differences were examined by examining differences in means for each job title, stratified by sampling strategy; and by offering "sampling strategy" as a categorical predictor variable to the empirical model. Multiple linear regressions revealed the most important determinants of increased wood dust exposure to be mill location away from the coast, earlier calendar year, and indoor jobs. The empirical model had an R2 of 0.39 and a predictive range from 0.02 to 25.45 mg/m3. Research and compliance sampling strategies showed no difference in mean exposure and distribution in the empirical model (p < 0.05), suggesting that regulatory exposure databases may be of utility for exposure assessment in epidemiology. This research indicates that compliance-sampling strategies do not result in an overestimation of mean exposure levels within jobs, but they do focus on a biased sample of jobs-those most highly exposed.