Job-Exposure Matrix: A Useful Tool for Incorporating Workplace Exposure Data Into Population Health Research and Practice

Abstract

Workplace exposures to physical, chemical, and psychosocial factors account for a large burden of chronic diseases. Obtaining useful estimates of current and past workplace exposures is challenging, particularly in large general population studies. Job-exposure matrices (JEMs) are a useful tool for exposure assessment, particularly when no individual level exposure data are available. A JEM provides a cross-tabulation of job titles (sometimes combined with industry) and estimated exposures to workers carrying out these jobs during different time periods. The major limitation of JEMs is that they do not account for individual variation in exposures within the same job. This limitation is offset by the advantages of low cost, wide applicability, lack of bias from self-reporting, and the ability to estimate exposures based on job titles when no other exposure data exist. There is growing use of JEMs in research examining the role of workplace exposures in the development of chronic diseases, and interest in their application to public health practice. This paper provides a scoping review of JEM use, some examples of JEMs, and brief guidance for the application of JEMs in epidemiological research. In conclusion, JEMs provide a useful tool for researchers and public health practitioners to estimate occupational exposures in large scale epidemiological studies relevant to many health conditions.

Association between COVID-19 infection and work exposure assessed by the Mat-O-Covid job exposure matrix in the CONSTANCES cohort

“…However, one parameter on the Mat-O-Covid JEM considered remote work as a potential prevention measure. As for the exposure assessment, in general, JEMs allow us to have a sense of the group-level exposure but tend to underestimate intra-job (individual-level) variations of exposure, and Mat-O-Covid has only recently been validated 13 21. However, potential measurement errors caused by the JEM assessed exposure should lead to an attenuation bias and the population attributable fraction could be underestimated.…”

“…21 However, potential measurement errors caused by the JEM assessed on September 25, 2022 by guest. Protected by copyright.…”

How to Use Biomechanical Job Exposure Matrices (Jem) On Job History for Musculoskeletal Disorders? Mathematical Modeling on the Example of Severe Knee Pain in Constances

“…This result is also found elsewhere, with non-managerial jobs associated with higher prevalence of knee osteoarthritis and knee symptoms [26]. Third, as we already mentioned, the use of JEMs might also be questioned since it is a global average evaluation that does not consider the differences inside job [27]. However, assessing exposure during long periods of time and for a big number of subjects is challenging and JEMs are appropriate tool to consider.…”

How to Use Biomechanical Job Exposure Matrices with Job History to Access Work Exposure for Musculoskeletal Disorders? Application of Mathematical Modeling in Severe Knee Pain in the Constances Cohort

“…This result is also found elsewhere, with non-managerial jobs associated with higher prevalence of knee osteoarthritis and knee symptoms [ 30 ]. Third, as we already mentioned, the use of JEMs might also be questioned since it is a global average evaluation that does not consider the differences inside job [ 31 ]. However, assessing exposure during long periods of time and for a big number of subjects is challenging and JEMs are appropriate tool to consider.…”