Impact of aggregating exposure information from cases and controls when building a population-based job-exposure matrix from past expert evaluations

Objectives

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.

Methods

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.

Results

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 >0.50), and absolute differences were small (median difference in probability <1.5%, median ratio in intensity=1.00) for both sexes.

Conclusions

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.

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from #Med Blogs by Alexandros G.Sfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/1UAGpiZ
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