Contribution of job-exposure matrices for exposure assessment in occupational safety and health monitoring systems: application from the French national occupational disease surveillance and prevention network.

OBJECTIVES: To detect new hazards ("signals"), occupational health monitoring systems mostly rest on the description of exposures in the jobs held and on reports by medical doctors; these are subject to declarative bias. Our study aims to assess whether job-exposure matrices (JEMs) could be useful tools for signal detection by improving exposure reporting.
METHODS: Using the French national occupational disease surveillance and prevention network (RNV3P) data from 2001 to 2011, we explored the associations between disease and exposure prevalence for 3 well-known pathology/exposure couples and for one debatable couple. We compared the associations measured when using physicians' reports or applying the JEMs, respectively, for these selected diseases and across non-selected RNV3P population or for cases with musculoskeletal disorders, used as two reference groups; the ratio of exposure prevalences according to the two sources of information were computed for each disease category.
RESULTS: Our population contained 58,188 subjects referred with pathologies related to work. Mean age at diagnosis was 45.8 years (95% CI 45.7; 45.9), and 57.2% were men. For experts, exposure ratios increase with knowledge on exposure causality. As expected, JEMs retrieved more exposed cases than experts (exposure ratios between 12 and 194), except for the couple silica/silicosis, but not for the MSD control group (ratio between 0.2 and 0.8).
CONCLUSIONS: JEMs enhanced the number of exposures possibly linked with some conditions, compared to experts' assessment, relative to the whole database or to a reference group; they are less likely to suffer from declarative bias than reports by occupational health professionals.