Background A recent estimation of carcinogen exposure among Quebec workers was received with interest by stakeholders, who wanted refined estimates. This analysis aimed to produce industry-specific estimates indicating priority occupations.
Methods For 41 agents considered carcinogenic or probably carcinogenic to humans in the Quebec legislation and the IARC classification (groups 1 and 2A), we computed estimates of potential exposures by industry and occupational group using two provincial population surveys, data produced by CAREX Canada, and data from the French SUMER survey and MATGÉNÉ job-exposure matrices project. Exposure proportions by industry and occupation were then applied to labour force data calculated from the 2011 Canadian National Household Survey, after adjustment for monthly fluctuations.
Results The most common exposures among Quebec workers are: night work (519 000 exposed; with larger numbers in Manufacturing, Health Care, Transportation/Warehousing, Accommodation/Food Services, Public Administration), solar radiation (242 000 exposed; Construction, Agriculture/Forestry/Fishing/Hunting, Public Administration) and diesel engine exhaust (DEE) (178 000 exposed; Transportation/Warehousing, Construction). The majority of carcinogen exposures appear to be at low or moderate levels. Multiple exposures are common in metal, chemical and plastics industries (among machine operators and labourers) and in the construction sector (trades helpers and labourers); several sectors with a high proportion of very small enterprises are considered multi-exposed. More than 110,000 young Quebecers work in industries where 15 carcinogens or more are present. Senior workers are employed in different industries, including Transit/Ground Passenger Transportation and Personal/Laundry Services, where solar radiation, DEE, benzene and formaldehyde exposures are reported.
Conclusion Exposure estimates obtained with different data sources allow identification of research and intervention priorities for cancer. More detailed analyses highlight special populations that need specific targeting in terms of age groups, level of exposure or sex, and taking into account the enterprise size can also help adjust intervention strategies.
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