Occupational risks of COVID-19: a case-cohort study using health insurance claims data in Germany
Year: 2024
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Studies on occupation and COVID-19 infection that cover a range of occupational groups and adjust for important confounders are lacking. This study aimed to estimate occupational risks of hospitalization with COVID-19 by taking into account sociodemographic factors and previous comorbidities. METHODS: We applied a case-cohort design using workers insured with one of Germany's largest statutory health insurers as a data source for occupational and demographical information as well as for information on comorbidities. Cox regression models with denominator weights for cases and controls assessed relative risks of hospitalization with COVID-19 in 2020. RESULTS: The study consisted of 11,202 COVID-19 cases and 249,707 non-cases. After adjusting for age, sex, number of pre-existing comorbidities, and socioeconomic status, we found at least doubled risks for occupations in theology and church work (HR = 3.05; 95% CI 1.93-4.82), occupations in healthcare (HR = 2.74; 95% CI 2.46-3.05), for bus and tram divers (HR = 2.46; 95% CI 2.04-2.97), occupations in meat processing (HR = 2.16; 95% CI 1.57-2.98), and professional drivers in passenger transport (e.g. taxi drivers) (HR = 2.00; 95% CI 1.59-2.51). In addition, occupations in property marketing and management, social workers, laboratory workers, occupations in personal care (e.g. hairdressers), occupations in housekeeping and occupations in gastronomy all had statistically significantly increased risks compared to the reference population (administrative workers). CONCLUSIONS: We identified occupations with increased risks for hospitalization with COVID-19. For those having a doubled risk it can be assumed that COVID-19 diseases are predominantly occupationally related. By identifying high-risk occupations in non-healthcare professions, effective measures to prevent infections in the workplace can be developed, also in case of a future pandemic.
Source: BMC Public Health
Authors: Karla Romero Starke, René Mauer, Janice Hegewald, Ulrich Bolm-Audorff, Gabriela Brückner, Katrin Schüssel, Helmut Schröder, Andreas Seidler
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,190
Funder: Technische Universität Dresden
OpenAlex ID: W4404604782
