Acute myocardial infarctions identified in the Manitoba Occupational Disease Surveillance System: A linkage of worker's compensation and provincial health data

INTRODUCTION: The purpose of this study was to identify jobs and industries that may be associated with increased or decreased risk of myocardial infarction. METHODS: We linked provincial health care data with Workers Compensation Board (WCB) of Manitoba claims data to create the Manitoba Occupational Disease Surveillance System (MODSS). Workers were eligible for inclusion in this study if their WCB claim listed an occupation, their claim could be linked to health data, they had an accepted non-acute myocardial infarction (AMI) compensation time loss claim and were free of a recent (<1 year) AMI diagnosis at the start of disease follow-up. AMI cases were identified as the most-responsible diagnosis in the hospitalization file (ICD-9 410 or ICD-10 I20). Cases were included if they occurred after the WCB record injury date until end of coverage, either through moving out of province, reaching age 65, death, or the end of the study period (March 1, 2020). RESULTS: We identified 1880 incident AMIs amongst 150,022 claims recorded in the MODSS (1.25%). A number of industries and occupations were found to have higher and lower AMI rates. Care providers and educational, legal, and public protection support occupations had a lower hazard ratio (HR; 0.64; 95% confidence interval [CI]: 0.44-0.92) compared to the overall cohort. Female chefs and cooks, and male butchers and bakers had elevated AMI HRs. Both male and female transport and heavy equipment operators and related maintenance occupations had increased HRs (1.48; 95% CI: 1.30-1.67). Often male and female workers employed in the same occupations had congruent AMI risks, but this was not always the case. CONCLUSIONS: The linkage of a WCB data set with provincial health claims data led to the identification of a number of occupations with elevated risks of AMI in Manitoba. This was most notable in the transportation industry. Identifying work areas with increased risk of AMIs could lead to targeted educational efforts and potential workplace modifications to lower this risk.