Jean-François Sauvé1, Hugh W Davies2, Marie-Élise Parent3,4,5, Cheryl E Peters6,7,8, Marie-Pierre Sylvestre4,5, Jérôme Lavoué1,5. 1. Department of Environmental and Occupational Health, School of Public Health, Université de Montréal, Montréal, Québec, Canada. 2. School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada. 3. INRS-Institut Armand-Frappier, Université du Québec, Laval, Québec, Canada. 4. Department of Social and Preventive Medicine, School of Public Health, Université de Montréal, Montréal, Québec, Canada. 5. Centre de recherche du CHUM, Montréal, Québec, Canada. 6. CAREX Canada, Vancouver, British Columbia, Canada. 7. Department of Cancer Epidemiology and Prevention Research, Alberta Health Services, Calgary, Alberta, Canada. 8. Preventive Oncology & Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Abstract
Objectives: The CANJEM general population job-exposure matrix summarizes expert evaluations of 31 673 jobs from four population-based case-control studies of cancer conducted in Montreal, Canada. Intensity in each CANJEM cell is represented as relative distributions of the ordinal (low, medium, high) ratings of jobs assigned by the experts. We aimed to apply quantitative concentrations to CANJEM cells using Canadian historical measurements from the Canadian Workplace Exposure Database (CWED), taking exposure to wood dust as an example. Methods: We selected 5170 personal and area wood dust measurements from 31 occupations (2011 Canadian National Occupational Classification) with a non-zero exposure probability in CANJEM between 1930 and 2005. The measurements were taken between 1981 and 2003 (median 1989). A Bayesian hierarchical model was applied to the wood dust concentrations with occupations as random effects, and sampling duration, year, sample type (area or personal), province, and the relative proportion of jobs exposed at medium and high intensity in CANJEM cells as fixed effects. Results: The estimated geometric mean (GM) concentrations for a CANJEM cell with all jobs exposed at medium or high intensity were respectively 1.3 and 2.4 times higher relative to a cell with all jobs at low intensity. An overall trend of -3%/year in exposure was observed. Applying the model estimates to all 198 cells in CANJEM with some exposure assigned by the experts, the predicted 8-hour, personal wood dust GM concentrations by occupation for 1989 ranged from 0.48 to 1.96 mg m-3. Conclusions: The model provided estimates of wood dust concentrations for any CANJEM cell with exposure, applicable for quantitative risk assessment at the population level. This framework can be implemented for other agents represented in both CANJEM and CWED.
Objectives: The CANJEM general population job-exposure matrix summarizes expert evaluations of 31 673 jobs from four population-based case-control studies of cancer conducted in Montreal, Canada. Intensity in each CANJEM cell is represented as relative distributions of the ordinal (low, medium, high) ratings of jobs assigned by the experts. We aimed to apply quantitative concentrations to CANJEM cells using Canadian historical measurements from the Canadian Workplace Exposure Database (CWED), taking exposure to wood dust as an example. Methods: We selected 5170 personal and area wood dust measurements from 31 occupations (2011 Canadian National Occupational Classification) with a non-zero exposure probability in CANJEM between 1930 and 2005. The measurements were taken between 1981 and 2003 (median 1989). A Bayesian hierarchical model was applied to the wood dust concentrations with occupations as random effects, and sampling duration, year, sample type (area or personal), province, and the relative proportion of jobs exposed at medium and high intensity in CANJEM cells as fixed effects. Results: The estimated geometric mean (GM) concentrations for a CANJEM cell with all jobs exposed at medium or high intensity were respectively 1.3 and 2.4 times higher relative to a cell with all jobs at low intensity. An overall trend of -3%/year in exposure was observed. Applying the model estimates to all 198 cells in CANJEM with some exposure assigned by the experts, the predicted 8-hour, personal wood dust GM concentrations by occupation for 1989 ranged from 0.48 to 1.96 mg m-3. Conclusions: The model provided estimates of wood dust concentrations for any CANJEM cell with exposure, applicable for quantitative risk assessment at the population level. This framework can be implemented for other agents represented in both CANJEM and CWED.
Authors: Susan Peters; Roel Vermeulen; Lützen Portengen; Ann Olsson; Benjamin Kendzia; Raymond Vincent; Barbara Savary; Jérôme Lavoué; Domenico Cavallo; Andrea Cattaneo; Dario Mirabelli; Nils Plato; Joelle Fevotte; Beate Pesch; Thomas Brüning; Kurt Straif; Hans Kromhout Journal: J Environ Monit Date: 2011-10-14
Authors: Karen S Galea; Martie Van Tongeren; Anne J Sleeuwenhoek; David While; Mairi Graham; Annette Bolton; Hans Kromhout; John W Cherrie Journal: Ann Occup Hyg Date: 2009-07-14
Authors: Benjamin Kendzia; Beate Pesch; Dorothea Koppisch; Rainer Van Gelder; Katrin Pitzke; Wolfgang Zschiesche; Thomas Behrens; Tobias Weiss; Jack Siemiatycki; Jerome Lavoué; Karl-Heinz Jöckel; Roger Stamm; Thomas Brüning Journal: J Expo Sci Environ Epidemiol Date: 2017-01-18 Impact factor: 5.563
Authors: Jean-François Sauvé; Jack Siemiatycki; France Labrèche; Lesley Richardson; Javier Pintos; Marie-Pierre Sylvestre; Michel Gérin; Denis Bégin; Aude Lacourt; Tracy L Kirkham; Thomas Rémen; Romain Pasquet; Mark S Goldberg; Marie-Claude Rousseau; Marie-Élise Parent; Jérôme Lavoué Journal: Ann Work Expo Health Date: 2018-08-13 Impact factor: 2.179