Enrichment of the Canadian Longitudinal Study on Aging with the CANJEM occupational exposure data

Project Summary

The CLSA offers enormous opportunities to better characterize the exposure of Canadians to harmful substances in the workplace and their influence on healthy aging. However, in order to estimate the workplace exposure of the CLSA participants, their employment information, which is in text, needs first to be coded into job category numbers. We aim to enrich the CLSA with occupational exposure data to harmful substances. We will use automated approaches (e.g. machine learning) to code the jobs of the CLSA participants. The job codes will then be linked to harmful substances from a database (i.e. the job exposure matrix CANJEM). Once jobs are coded and exposures linked, we will describe the proportions of CLSA participants (retired and employed) exposed at work to harmful substances by province and characteristics such as sex, immigration status and across time periods.