Øystein Vedaa1,2, Ståle Pallesen3,4, Eilin K Erevik3, Erling Svensen5, Siri Waage4,6, Bjørn Bjorvatn4,6, Børge Sivertsen7,8,9, Anette Harris3. 1. Department of Mental Health, Norwegian University of Science and Technology, PO Box 8905, MTFS, 7491, Trondheim, Norway. oystein.vedaa@ntnu.no. 2. Department of Health Promotion, Norwegian Institute of Public Health, Zander Kaaes Gate 7, 5018, Bergen, Norway. oystein.vedaa@ntnu.no. 3. Department of Psychosocial Science, University of Bergen, Christiesgt 12, 5015, Bergen, Norway. 4. Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Jonas Lies vei 65, 5021, Bergen, Norway. 5. Haukeland University Hospital, Bergen, Jonas Lies vei 65, 5021, Bergen, Norway. 6. Department of Global Public Health and Primary Care, University of Bergen, Post Box 7807, 5020, Bergen, Norway. 7. Department of Mental Health, Norwegian University of Science and Technology, PO Box 8905, MTFS, 7491, Trondheim, Norway. 8. Department of Health Promotion, Norwegian Institute of Public Health, Zander Kaaes Gate 7, 5018, Bergen, Norway. 9. Department of Research and Innovation, Helse Fonna HF, Møllervegen 22, Haugesund, Norway.
Abstract
PURPOSE: The aim of this study was to investigate the effects of long working hours (≥ 12 h shifts) on sick leave using objective records of shift work exposure and of sick leave. METHODS: A total of 1538 nurses (mean age 42.5, SD 12.0; response rate 42%) participated. Payroll and archival sick leave data over a 4-year period were retrieved from employers' records and aggregated over every third calendar month. A multilevel negative binomial model was used to investigate the effects of exposure to long working hours, on subsequent sick leave rates the following 3 months. Covariates included prior sick leave, number of shifts worked, night and evening shifts, personality, and demographic characteristics. RESULTS: Exposure to long working hours was associated with fewer sick leave days in the subsequent 3 months [adjusted model, incidence rate ratio (IRR) = 0.946, 95% CI 0.919-0.973, p < 0.001]. The interaction long working hours by a number of work days showed that sick leave days the subsequent 3 months was higher by long shifts when number of shifts was high compared to when number of shifts was low [adjusted model, IRR 1.002, 95% CI 1.000-1.004, p < 0.05]. DISCUSSION: Long working hours was associated with fewer sick leave days. The restorative effects of extra days off with long working hours are discussed as possible explanations to this relationship.
PURPOSE: The aim of this study was to investigate the effects of long working hours (≥ 12 h shifts) on sick leave using objective records of shift work exposure and of sick leave. METHODS: A total of 1538 nurses (mean age 42.5, SD 12.0; response rate 42%) participated. Payroll and archival sick leave data over a 4-year period were retrieved from employers' records and aggregated over every third calendar month. A multilevel negative binomial model was used to investigate the effects of exposure to long working hours, on subsequent sick leave rates the following 3 months. Covariates included prior sick leave, number of shifts worked, night and evening shifts, personality, and demographic characteristics. RESULTS: Exposure to long working hours was associated with fewer sick leave days in the subsequent 3 months [adjusted model, incidence rate ratio (IRR) = 0.946, 95% CI 0.919-0.973, p < 0.001]. The interaction long working hours by a number of work days showed that sick leave days the subsequent 3 months was higher by long shifts when number of shifts was high compared to when number of shifts was low [adjusted model, IRR 1.002, 95% CI 1.000-1.004, p < 0.05]. DISCUSSION: Long working hours was associated with fewer sick leave days. The restorative effects of extra days off with long working hours are discussed as possible explanations to this relationship.
Keywords:
Extended daily working hours; Long shifts; Long working hours; Sick leave; Sickness absence
Authors: Tom Rosenström; Mikko Härmä; Mika Kivimäki; Jenni Ervasti; Marianna Virtanen; Tarja Hakola; Aki Koskinen; Annina Ropponen Journal: Scand J Work Environ Health Date: 2021-03-31 Impact factor: 5.024