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M Virtanen, M Jokela, IE Madsen, LL Magnusson Hanson, T Lallukka, ST Nyberg, L Alfredsson, D Batty, JB Bjorner, M Borritz, H Burr, N Dragano, R Erbel, JE Ferrie, K Heikkilä, A Knutsson, M Koskenvuo, E Lahelma, ML Nielsen, T Oksanen, JH Pejtersen, J Pentti, O Rahkonen, R Rugulies, P Salo, J Schupp, MJ Shipley, J Siegrist, A Singh-Manoux, SB Suominen, T Theorell, J Vahtera, GG Wagner, JL Wang, V Yiengprugsawan, H Westerlund and M Kivimäki
Abstract
Objectives This systematic review and meta-analysis combined published study-level data and unpublished individual-participant data with the aim of quantifying the relation between long working hours and the onset of depressive symptoms. Methods We searched PubMed and Embase for published prospective cohort studies and included available cohorts with unpublished individual-participant data. We used a random-effects meta-analysis to calculate summary estimates across studies. Results We identified ten published cohort studies and included unpublished individual-participant data from 18 studies. In the majority of cohorts, long working hours was defined as working ≥55 hours per week. In multivariable-adjusted meta-analyses of 189 729 participants from 35 countries [96 275 men, 93 454 women, follow-up ranging from 1-5 years, 21 747 new-onset cases), there was an overall association of 1.14 (95% confidence interval (CI) 1.03-1.25] between long working hours and the onset of depressive symptoms, with significant evidence of heterogeneity (I 2=45.1%, P=0.004). A moderate association between working hours and depressive symptoms was found in Asian countries (1.50, 95% CI 1.13-2.01), a weaker association in Europe (1.11, 95% CI 1.00-1.22), and no association in North America (0.97, 95% CI 0.70-1.34) or Australia (0.95, 95% CI 0.70-1.29). Differences by other characteristics were small. Conclusions This observational evidence suggests a moderate association between long working hours and onset of depressive symptoms in Asia and a small association in Europe.
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Concepts
Study heterogeneity, Epidemiology, North America, Evidence-based medicine, Systematic review, Meta-analysis
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