Ropponen, Annina;
Gluschkoff, Kia;
Ervasti, Jenni;
Kivimaki, Mika;
Koskinen, Aki;
Krutova, Oxana;
Peutere, Laura;
... Harma, Mikko; + view all
(2023)
Working hour patterns and risk of occupational accidents. An optimal matching analysis in a hospital employee cohort.
Safety Science
, 159
, Article 106004. 10.1016/j.ssci.2022.106004.
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Abstract
Background: Hypothesis-free studies applying advanced statistical analysis of objective working hour patterns and occupational accidents are lacking. This study aimed to identify patterns of working hours among hospital employees and to investigate the associations between the identified patterns and the risk of an occupational accident. Method: In this cohort study of 4419 hospital employees, we collected electronic payroll-based working hour data (i.e., timing and duration) for each participant and linked them to records of occupational accident register between 2008 and 2018. We used optimal matching to assess similarity between individual working hour patterns for a period of 7 days preceding an accident or, for employees without an accident, a random pseudo-accident date. Using cluster analysis, we categorized employees into working hour pattern clusters. Log-binomial regression was used to examine risk ratios (RR) with 95 % confidence intervals (CI) of an occupational accident between cluster memberships. Results: 1626 participants experienced an occupational accident which took place either at the workplace (65 %) or while commuting (35 %). Six clusters of working hour patterns were identified. Compared to the cluster with the fewest accidents, clusters with a higher proportion of accidents were characterized by late work shifts and a high proportion of quick returns (<11-hour shift interval,) and long work shifts (>12-hour shift), RR 1.31, 95 %CI 1.13–1.52 for the cluster with the most accidents. Conclusions: This data-driven study suggests that working late and long with insufficient rest is associated with increased probability of occupational accidents. Working hour arrangements in 24/7 care of hospital merit attention to regularity and sufficient rest to support occupational safety.
| Type: | Article |
|---|---|
| Title: | Working hour patterns and risk of occupational accidents. An optimal matching analysis in a hospital employee cohort |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.ssci.2022.106004 |
| Publisher version: | https://doi.org/10.1016/j.ssci.2022.106004 |
| Language: | English |
| Additional information: | © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Science & Technology, Technology, Engineering, Industrial, Operations Research & Management Science, Engineering, Shift work, Accident, Safety, Health care, Recovery, SHIFT WORK, SLEEPINESS, SCHEDULES, AGE |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry > Mental Health of Older People |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10166861 |
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