Jean-François Sauvé1,2, Jack Siemiatycki2,3, France Labrèche1,3,4, Lesley Richardson2, Javier Pintos2, Marie-Pierre Sylvestre2,3, Michel Gérin1, Denis Bégin1, Aude Lacourt5, Tracy L Kirkham6, Thomas Rémen2, Romain Pasquet2,3, Mark S Goldberg7,8, Marie-Claude Rousseau2,3,9, Marie-Élise Parent2,3,9, Jérôme Lavoué1,2. 1. Department of Environmental and Occupational Health, School of Public Health, Université de Montréal, chemin de la Côte Ste-Catherine, Montréal, Québec, Canada. 2. Centre de recherche du CHUM, rue St-Denis, Montréal, Québec, Canada. 3. Department of Social and Preventive Medicine, School of Public Health, Université de Montréal, avenue du Parc, Montréal, Québec, Canada. 4. Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail, Boul. de Maisonneuve Ouest, Montréal, Québec, Canada. 5. Bordeaux Population Health Research Center, Team EPICENE, Université de Bordeaux, UMR, rue Léo Saignat, Bordeaux Cedex, France. 6. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada. 7. Department of Medicine, McGill University, Montréal, Québec, Canada. 8. Division of Clinical Epidemiology, McGill University Health Centre, Montréal, Québec, Canada. 9. INRS-Institut Armand-Frappier, Université du Québec, Laval, Québec, Canada.
Abstract
Objectives: We developed a job-exposure matrix called CANJEM using data generated in population-based case-control studies of cancer. This article describes some of the decisions in developing CANJEM, and some of its performance characteristics. Methods: CANJEM is built from exposure information from 31673 jobs held by study subjects included in our past case-control studies. For each job, experts had evaluated the intensity, frequency, and likelihood of exposure to a predefined list of agents based on jobs histories and descriptions of tasks and workplaces. The creation of CANJEM involved a host of decisions regarding the structure of CANJEM, and operational decisions regarding which parameters to present. The goal was to produce an instrument that would provide great flexibility to the user. In addition to describing these decisions, we conducted analyses to assess how well CANJEM covered the range of occupations found in Canada. Results: Even at quite a high level of resolution of the occupation classifications and time periods, over 90% of the recent Canadian working population would be covered by CANJEM. Prevalence of exposure of specific agents in specific occupations ranges from 0% to nearly 100%, thereby providing the user with basic information to discriminate exposed from unexposed workers. Furthermore, among exposed workers there is information that can be used to discriminate those with high exposure from those with low exposure. Conclusions: CANJEM provides good coverage of the Canadian working population and possibly that of several other countries. Available in several occupation classification systems and including 258 agents, CANJEM can be used to support exposure assessment efforts in epidemiology and prevention of occupational diseases.
Objectives: We developed a job-exposure matrix called CANJEM using data generated in population-based case-control studies of cancer. This article describes some of the decisions in developing CANJEM, and some of its performance characteristics. Methods: CANJEM is built from exposure information from 31673 jobs held by study subjects included in our past case-control studies. For each job, experts had evaluated the intensity, frequency, and likelihood of exposure to a predefined list of agents based on jobs histories and descriptions of tasks and workplaces. The creation of CANJEM involved a host of decisions regarding the structure of CANJEM, and operational decisions regarding which parameters to present. The goal was to produce an instrument that would provide great flexibility to the user. In addition to describing these decisions, we conducted analyses to assess how well CANJEM covered the range of occupations found in Canada. Results: Even at quite a high level of resolution of the occupation classifications and time periods, over 90% of the recent Canadian working population would be covered by CANJEM. Prevalence of exposure of specific agents in specific occupations ranges from 0% to nearly 100%, thereby providing the user with basic information to discriminate exposed from unexposed workers. Furthermore, among exposed workers there is information that can be used to discriminate those with high exposure from those with low exposure. Conclusions: CANJEM provides good coverage of the Canadian working population and possibly that of several other countries. Available in several occupation classification systems and including 258 agents, CANJEM can be used to support exposure assessment efforts in epidemiology and prevention of occupational diseases.
Authors: K Teschke; A F Olshan; J L Daniels; A J De Roos; C G Parks; M Schulz; T L Vaughan Journal: Occup Environ Med Date: 2002-09 Impact factor: 4.402
Authors: Jérôme Lavoué; Javier Pintos; Martie Van Tongeren; Laurel Kincl; Lesley Richardson; T Kauppinen; Elisabeth Cardis; Jack Siemiatycki Journal: Occup Environ Med Date: 2012-04-01 Impact factor: 4.402
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Authors: Jean-François Sauvé; Hugh W Davies; Marie-Élise Parent; Cheryl E Peters; Marie-Pierre Sylvestre; Jérôme Lavoué Journal: Ann Work Expo Health Date: 2019-01-07 Impact factor: 2.179
Authors: Catherine L Callahan; Sarah J Locke; Pamela J Dopart; Patricia A Stewart; Kendra Schwartz; Julie J Ruterbusch; Barry I Graubard; Nathaniel Rothman; Jonathan N Hofmann; Mark P Purdue; Melissa C Friesen Journal: Am J Ind Med Date: 2018-10-06 Impact factor: 2.214