Prospective cohort studies |
Tüchsen et al35 | 67% | Poisson regression model | Age, education, body mass index, smoking status, leisure time physical activity, general health, psychosocial and physical work environment factors Model 1: adjusted for variables excluding work environment factors Model 2: adjusted for all variables
| | Model 1: RR (95% CI): 1.03 (0.80 to 1.32) 1.31 (1.13 to 1.51) 0.97 (0.80 to 1.18) 1.17 (0.84 to 1.62) 1.26 (1.03 to 1.55) 0.91 (0.69 to 1.20)
| | Fixed evening workers had a significantly increased risk for taking a ≥2-week and a ≥8-week sick leave spell in model 1. When additionally adjusting for work environment factors (model 2), the increased risk was still evident for ≥2-week sick leave spells, but not for ≥8-week sick leave spells |
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Tüchsen et al36 | 67% | Cox proportional hazards model | Age, sex, children, education, work sector, establishment size, replacement policy, full-time work, overtime, 3 day sick leave without certificate rule. Model 1: age adjusted Model 2: fully adjusted
| ≥2 wks Men: Women: ≥8 wks Men: Women:
| | Model 2: HR (95% CI): 0.92 (0.71 to 1.18) 0.90 (0.71 to 1.14) 1.33 (0.91 to 1.94) 1.13 (0.81 to 1.59)
| After adjusting for age, only shift working men showed a significantly increased risk for taking a ≥8-week sick leave spell in a year. In model 2 this association was ameliorated |
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Case-control studies |
Kleiven et al38 | 76% | Logistic regression, stratification | Age, sex, seniority | OR (95% CI): Minor mental illness: 1.04 (0.64 to 1.70) Gastrointestinal diseases: 1.02 (0.64 to 1.63) Coronary heart disease: 0.75 (0.42 to 1.31) Musculoskeletal disease: 1.14 (0.92 to 1.40) Neoplasm: 0.75 (0.29 to 1.94)
| No significant difference was found between 3-shift workers and day workers for taking sick spells lasting >3 days |
Bourbonnais et al39 | 59% | χ2 Tests, multiple logistic regression | Duration of stay, nurse to patient ratio, job title, interaction between nurse to patient ratio and job title, job classification | Proportion ≥1 sick leave spells of ≥6–8 days: OR (95% CI) Night shifts: 1.96 (1.14 to 3.36) Evening shifts: 1.67 (1.02 to 2.75) Rotating shifts: 1.43 (0.88 to 2.31)
| Working night and evening shifts significantly increased the odds for sick leave, rotating shifts showed a meaningfully increased odds |
Cross-sectional studies |
Higashi et al40 | 67% | Mantel–Haenszel test | Age | | 3-Shift workers had a significantly lower percentage of sick leave spells than day workers, but not % lost work days |
Niedhammer et al41 | 62% | Logistic regression | Age, decision latitude, psychological demands, social support, bullying, aggression from public, occupation, work status, work hours, and physical-, ergonomic-, biological- and chemical exposure | Men: OR (95% CI) Fixed night: 1.11 (0.89 to 1.38) Shift excluding nights: 1.26 (1.09 to 1.45) Shift including nights: 1.24 (1.04 to 1.49) Women: OR (95% CI) Fixed night: 1.07 (0.79 to 1.45) Shift excluding nights: 1.03 (0.86 to 1.23) Shift including nights: 1.29 (0.91 to 1.83)
| Men working shifts including nights, as well as shifts excluding nights, showed a significantly increased odds for taking sick leave. No associations were found for women |
Böckerman and Laukkanen42 | 54% | Logistic regression | Sex, work sector, education, children at home, company size, replacement, work hours, match in work hours, sick leave policy | Marginal effect: 0.075 (p=0.045) | Participation in shift or period work significantly increases the prevalence of sickness absenteeism by 8% |
Ohayon et al43 | 54% | χ2, logistic regression | Age, sex, profession, children at home, daytime sleepiness, sleep duration, circadian rhythm disorders, obstructive sleep apnoea syndrome, insomnia disorder | | 2-Shift workers had a significantly increased OR for sick leave than day workers. No difference was found between night time/rotating shifts and day workers |
Eyal et al44 | 54% | RR | Age | RR to take ≧20 days sick leave: 1.3 (p<0.05) | | | Blue-collar shift workers had a significantly increased RR for sick leave |