Outcomes and conclusions for the high quality studies
Study | Quality Score | Analysis | Confounder used in analysis | Adjusted outcomes | Conclusions | ||
Prospective cohort studies | |||||||
Tüchsen et al 35 | 67% | Poisson regression model |
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| 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 |
Tüchsen et al 36 | 67% | Cox proportional hazards model |
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| 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 |
Case-control studies | |||||||
Kleiven et al 38 | 76% | Logistic regression, stratification | Age, sex, seniority |
| No significant difference was found between 3-shift workers and day workers for taking sick spells lasting >3 days | ||
Bourbonnais et al 39 | 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 |
| Working night and evening shifts significantly increased the odds for sick leave, rotating shifts showed a meaningfully increased odds | ||
Cross-sectional studies | |||||||
Higashi et al 40 | 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 al 41 | 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 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 al 43 | 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 al 44 | 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 |