Susan Peters1, Roel Vermeulen2, Lützen Portengen3, Ann Olsson4, Benjamin Kendzia5, Raymond Vincent6, Barbara Savary6, Jérôme Lavoué7, Domenico Cavallo8, Andrea Cattaneo8, Dario Mirabelli9, Nils Plato10, Joelle Fevotte11, Beate Pesch5, Thomas Brüning5, Kurt Straif4, Hans Kromhout3. 1. 1.Environmental Epidemiology Division, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands; 2.Occupational Respiratory Epidemiology, School of Population Health, University of Western Australia, Perth, Australia; h.kromhout@uu.nl. 2. 1.Environmental Epidemiology Division, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands; 3.Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands; 3. 1.Environmental Epidemiology Division, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands; 4. 4.International Agency for Research on Cancer, Lyon, France; 5. 5.Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Rurh-Universität Bochum, Bochum, Germany; 6. 6.Institut National de Recherche et de Sécurité, Vandoeuvre lès Nancy, France; 7. 7.Research Centre of University of Montreal Hospital Research Centre, Canada; 8. 8.Department of Science and High Technology, Università degli Studi dell'Insubria, Como, Italy; 9. 9.Cancer Epidemiology Unit, CPO-Piemonte and University of Turin, Turin, Italy; 10. 10.The Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; 11. 11.Département santé travail, Institut de veille sanitaire, St Maurice, France.
Abstract
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 modeling of large quantities of personal measurements. METHODS: Empirical linear models were developed using personal occupational exposure measurements (n = 102306) from Europe and Canada, as well as 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 methods, 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 exposures 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: We estimated time-, job-, and region-specific exposure levels for four (asbestos, chromium-VI, nickel, and RCS) out of five considered lung carcinogens. Through statistical modeling of large amounts of personal occupational exposure measurement data we were able to derive a quantitative JEM to be used in community-based studies.
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 modeling of large quantities of personal measurements. METHODS: Empirical linear models were developed using personal occupational exposure measurements (n = 102306) from Europe and Canada, as well as 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 methods, 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 exposures 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: We estimated time-, job-, and region-specific exposure levels for four (asbestos, chromium-VI, nickel, and RCS) out of five considered lung carcinogens. Through statistical modeling of large amounts of personal occupational exposure measurement data we were able to derive a quantitative JEM to be used in community-based studies.
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; 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: Calvin B Ge; Melissa C Friesen; Hans Kromhout; Susan Peters; Nathaniel Rothman; Qing Lan; Roel Vermeulen Journal: Ann Work Expo Health Date: 2018-11-12 Impact factor: 2.179
Authors: Calvin Ge; Susan Peters; Ann Olsson; Lützen Portengen; Joachim Schüz; Josué Almansa; Thomas Behrens; Beate Pesch; Benjamin Kendzia; Wolfgang Ahrens; Vladimir Bencko; Simone Benhamou; Paolo Boffetta; Bas Bueno-de-Mesquita; Neil Caporaso; Dario Consonni; Paul Demers; Eleonóra Fabiánová; Guillermo Fernández-Tardón; John Field; Francesco Forastiere; Lenka Foretova; Pascal Guénel; Per Gustavsson; Vikki Ho; Vladimir Janout; Karl-Heinz Jöckel; Stefan Karrasch; Maria Teresa Landi; Jolanta Lissowska; Danièle Luce; Dana Mates; John McLaughlin; Franco Merletti; Dario Mirabelli; Nils Plato; Hermann Pohlabeln; Lorenzo Richiardi; Peter Rudnai; Jack Siemiatycki; Beata Świątkowska; Adonina Tardón; Heinz-Erich Wichmann; David Zaridze; Thomas Brüning; Kurt Straif; Hans Kromhout; Roel Vermeulen Journal: Am J Respir Crit Care Med Date: 2020-08-01 Impact factor: 21.405
Authors: Beate Pesch; Swaantje Casjens; Tobias Weiss; Benjamin Kendzia; Marina Arendt; Lewin Eisele; Thomas Behrens; Nadin Ulrich; Noreen Pundt; Anja Marr; Sibylle Robens; Christoph Van Thriel; Rainer Van Gelder; Michael Aschner; Susanne Moebus; Nico Dragano; Thomas Brüning; Karl-Heinz Jöckel Journal: Ann Work Expo Health Date: 2017-11-10 Impact factor: 2.179