title: Impact of aggregating exposure information from cases and controls when building a population-based job-exposure matrix from past expert evaluations.
abstract: To assess whether the inclusion of data from cases would bias a job-exposure matrix (JEM), we evaluated whether exposures were systematically different between cases and controls from a large historical case-control study.
  
  
  
  Data included 10 381 jobs assessed for occupational exposure to 294 agents within a lung cancer case-control study. For each sex, 1 JEM was developed from case jobs, and 1 from control jobs: with occupation (four-digit occupational codes), time period (1945-1959, 1960-1984, 1985-1995) and agent axes. We estimated concordance in exposure status (defined as probability of exposure threshold ≥5%) and exposure metrics of probability and intensity of exposure, between the 2 JEMs.
  
  
  
  Of all hypothetical occupation-period-agent combinations, most had no or few observations. Among males there were 8136 common cells (24-occupational codes, 3-periods, 226-agents), containing sufficient observations for comparison with 92% concordance in exposure status; discordance was equally likely to be towards cases or controls. Females had 1710 common cells (9-occupational codes, 3-periods, 114-agents) with 93% concordance in exposure status; discordant cells were more likely to reflect greater exposure among cases. Among concordantly exposed cells, probability and intensity of exposures were highly correlated between the case JEM and control JEM (Kendall τ>0.50), and absolute differences were small (median difference in probability <1.5%, median ratio in intensity=1.00) for both sexes.
  
  
  
  Agreement between the case JEM and control JEM was high, suggesting that aggregating the case and control information in our study into a single JEM is justifiable given the benefits of increased sample size.
authors.affiliation: University of Montreal Hospital Research Center (CRCHUM), Montréal, Quebec, Canada.
authors.forename: Tracy L
authors.initials: TL
authors.lastname: Kirkham
authors.affiliation: University of Montreal Hospital Research Center (CRCHUM), Montréal, Quebec, Canada.
authors.forename: Jack
authors.initials: J
authors.lastname: Siemiatycki
authors.affiliation: Institut de recherche Robert-Sauvé en santé et en sécurité du travail du Québec (IRSST), Direction de la recherche, Montréal, Quebec, Canada Department of Environmental and Occupational Health, University of Montréal, Montréal, Quebec, Canada.
authors.forename: France
authors.initials: F
authors.lastname: Labrèche
authors.affiliation: University of Montreal Hospital Research Center (CRCHUM), Montréal, Quebec, Canada Department of Environmental and Occupational Health, University of Montréal, Montréal, Quebec, Canada.
authors.forename: Jérôme
authors.initials: J
authors.lastname: Lavoué
mesh_terms: D000328:Adult; D000368:Aged; D015982:Bias; D016022:Case-Control Studies; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007407:Interviews as Topic; D008175:Lung Neoplasms; D008297:Male; D008875:Middle Aged; D009010:Monte Carlo Method; D016273:Occupational Exposure / Q000032:analysis*; D009790:Occupations / Q000145:classification*; D011792:Quebec; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors
keywords: Case-control studies; Epidemiologic methods; Occupational health