SYN-JEM: A Quantitative Job-Exposure Matrix For Five Lung Carcinogens

Susan PETERS, Institute for Risk Assessment Sciences, Utrecht University, Netherlands
VERMEULEN R. 1 , PORTENGEN L. 1 , OLSSON A. 2 , KENDZIA B. 3 , VINCENT R. 4 , SAVARY B. 4 , LAVOUÉ J. 5 , CAVALLO D. 6 , CATTANEO A. 6 , MIRABELLI D. 7 , PLATO N. 8 , FEVOTTE J. 9 , STRAIF K. 2 , KROMHOUT H. 1

1 Environmental Epidemiology Division, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
2 International Agency for Research on Cancer, Lyon, France
3 Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Rurh-Universität Bochum, Germany
4 Institut National de Recherche et de Sécurité, Vandoeuvre lès Nancy, France
5 Research Centre of University of Montreal Hospital Research Centre, Canada
6 Department of Science and High Technology, Università degli Studi dell'Insubria, Como, Italy
7 Cancer Epidemiology Unit, CPO-Piemonte and University of Turin, Italy
8 The Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
9 Département santé travail, Institut de veille sanitaire, St Maurice, France

Objective – The use of measurement data in occupational exposure assessment allows more quantitative analyses of possible exposure-response relations. We describe a quantitative exposure assessment approach for five lung carcinogens (i.e. asbestos, chromium-VI, nickel, polycyclic aromatic hydrocarbons (by its proxy benzo(a)pyrene (BaP)) and respirable crystalline silica). A quantitative job-exposure matrix (JEM) was developed based on statistical modelling of large quantities of personal measurements.
Methods – Empirical linear models were developed using personal occupational exposure measurements (n=102 306) from Europe and Canada, and auxiliary information like job (industry), year of sampling, region, an a priori exposure rating of each job (none, low and high exposed), sampling and analytical method, and sampling duration. The model outcomes were used to create a JEM with a quantitative estimate of the level of exposure by job, year and region.
Results – Decreasing time trends were observed for all agents between the 1970s and 2009, ranging from -1.2% per year for personal BaP and nickel concentrations to -10.7% for asbestos (in the time period before an asbestos ban was implemented). Regional differences in exposure concentrations (adjusted for measured jobs, years of measurement, and sampling method and duration) varied by agent, ranging from a factor 3.3 for chromium-VI up to a factor 10.5 for asbestos.
Conclusion – Time-, job-, and region-specific exposure levels were estimated for four (asbestos, chromium-VI, nickel and RCS) out of five considered lung carcinogens. Large amounts of personal occupational exposure measurement data and statistical modelling, making the best use of all available information, appear to be essential in order to successfully derive a quantitative JEM to be used in community-based studies.