| Title: | Shift work and the risk of incident hospital-treated infections: quantifying the role of lifestyle factors |
| Journal: | BMC Infectious Diseases |
| Published: | 10 Mar 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41808041/ |
| DOI: | https://doi.org/10.1186/s12879-026-12979-3 |
| URL: | http://dx.doi.org/10.1186/s12879-026-12979-3 |
Publication 17421
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Abstract
BackgroundWhile the adverse effects of shift work on non-communicable diseases are widely recognized, research on its impact on infectious diseases is limited. We aim to investigate the association of shift work with hospital-treated infections through a large cohort, and to explore the mediating role of lifestyles in this association.MethodsThis cohort study included employed workers from the UK Biobank. Work status was self-reported at baseline (2006-2010). A total of 866 types of hospital-treated infectious diseases were identified through hospital inpatient records. Lifestyle factors included smoking, alcohol consumption, body mass index, sedentary behavior, sleep duration, diet, and physical activity. We performed Cox proportional hazards regression models to examine the association of shift work with infections, and cause mediation analyses to explore the mediating role of lifestyles.ResultsOf 266,450 employed workers, 45,406 (17.04%) reported working shifts. During a median follow-up of 12.47 years (IQR 11.55-13.25), 40,684 workers (15.27%) developed severe infections that required hospital treatment. Shift work was associated with a higher risk of infectious diseases (HR 1.10, 95% CI 1.07-1.13), and comparable risks were observed across different shift frequencies (sometimes: HR 1.09, 95% CI 1.05-1.13; usually/always: HR 1.10, 95% CI 1.07-1.14).ConclusionsIn this cohort study, shift work was associated with higher risks of hospital-treated infections, with lifestyle variables mediating this association. It is recommended to consider shift work as an occupational hazard and implement individual-level and organizational-level interventions to mitigate vulnerability to infectious diseases.</p>
5 Authors
- Ying Zhou
- Yan Chen
- Minzhi Xu
- Hongyu Yan
- Xiaoxv Yin
1 Application
| Application ID | Title |
|---|---|
| 88159 | Fine-mapping, genetic correlation and genetic risk prediction for complex traits in different populations |
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