Lifetime exposure to atypical working hours among healthcare professionals compared with the workforce in other sectors: Nationwide cohort study.

Authors

Hanifa Bouziri, Adeline Renuy, Alexis Descatha, Jack Siemiatycki, Marie Zins, Marcel Goldberg, Sofiane Kab, Antoine Duclos

Published in

Journal of epidemiology and population health. Volume 74. Issue 5. Pages 203789. Sep 19, 2026. Epub Sep 19, 2026.

Abstract

Despite well-documented health risks, cumulative exposure to atypical working hours (AWH) over a career remains poorly quantified, especially among healthcare workers.
This study aimed to compare career-long AWH exposure among healthcare professionals and other occupational groups in France.
We analysed 2013-2017 data from the French nationwide CONSTANCES cohort, including participants aged 18-69 with job histories. The longest-held occupation was identified using cumulative job duration. Weighted prevalence estimates of six AWH were calculated, accounting for sampling design and non-response.
A total of 95,827 participants were included. Overall, 63.9% [95% CI, 63.5-64.4] of the workforce experienced at least one AWH, including weekend (37.3% [36.8-37.7]), long working hours (31.3% [30.8-31.7]), extreme shift (29.8% [29.4-30.3]), alternating or irregular schedules (21.5% [21.1-21.9]), night work (11.7% [11.4-12.0]) and insufficient weekly rest (26.4% [25.9-26.8]). Healthcare professionals represented 5.7% [5.4-6.1] of the sample: among them, nurses showed the highest prevalence of exposure to at least one AWH (94.1% [92.9-95.1]) and were mostly exposed to alternating, irregular or extreme shift schedules, weekend and night work, while physicians (85.1% [81.9-87.8]) were particularly exposed to long working hours and insufficient rest.
This study provides the first nationwide estimates of career-long exposure to multiple AWH across the French workforce. Healthcare professionals experienced the highest burden of AWH structurally. By leveraging occupational histories and calibrated survey weights, our approach reduces the underestimation inherent in "current job" assessments and supports prevention policies targeting structural scheduling constraints in healthcare.

PMID:
42762618
Bibliographic data and abstract were imported from PubMed on 20 Sep 2026.

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