Estimating exposures in the asphalt industry for an international epidemiological cohort study of cancer risk.
Publication year
2003Source
American Journal of Industrial Medicine, 43, 1, (2003), pp. 3-17ISSN
Publication type
Article / Letter to editor
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Organization
Health Evidence
Journal title
American Journal of Industrial Medicine
Volume
vol. 43
Issue
iss. 1
Page start
p. 3
Page end
p. 17
Subject
EBP 1: Determinants in Health and Disease; UMCN 1.5: Interventional oncologyAbstract
BACKGROUND: An exposure matrix (EM) for known and suspected carcinogens was required for a multicenter international cohort study of cancer risk and bitumen among asphalt workers. METHODS: Production characteristics in companies enrolled in the study were ascertained through use of a company questionnaire (CQ). Exposures to coal tar, bitumen fume, organic vapor, polycyclic aromatic hydrocarbons, diesel fume, silica, and asbestos were assessed semi-quantitatively using information from CQs, expert judgment, and statistical models. Exposures of road paving workers to bitumen fume, organic vapor, and benzo(a)pyrene were estimated quantitatively by applying regression models, based on monitoring data, to exposure scenarios identified by the CQs. RESULTS: Exposures estimates were derived for 217 companies enrolled in the cohort, plus the Swedish asphalt paving industry in general. Most companies were engaged in road paving and asphalt mixing, but some also participated in general construction and roofing. Coal tar use was most common in Denmark and The Netherlands, but the practice is now obsolete. Quantitative estimates of exposure to bitumen fume, organic vapor, and benzo(a)pyrene for pavers, and semi-quantitative estimates of exposure to these agents among all subjects were strongly correlated. Semi-quantitative estimates of exposure to bitumen fume and coal tar exposures were only moderately correlated. EM assessed non-monotonic historical decrease in exposures to all agents assessed except silica and diesel exhaust. CONCLUSIONS: We produced a data-driven EM using methodology that can be adapted for other multicenter studies.
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- Academic publications [245263]
- Faculty of Medical Sciences [93208]
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