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. 2012 Oct;69(10):701–712. doi: 10.1136/oemed-2011-100488

Table 5.

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

  • 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

  • ≥2 wks

  • Fixed night:

  • Fixed evening:

  • Rotating shifts:

  • ≥8 wks

  • Fixed night:

  • Fixed evening: Rotating shifts:

  • 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)

  • Model 2:

  • RR (95% CI):

  • 0.97 (0.73 to 1.29) 1.29 (1.10 to 1.52)

  • 0.93 (0.76 to 1.15)

  • 0.93 (0.62 to 1.38)

  • 1.24 (0.99 to 1.56)

  • 0.85 (0.63 to 1.16)

 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

  • 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 1

  • HR (95% CI):

  • 0.94 (0.74 to 1.19)

  • 1.20 (0.96 to 1.50)

  • 1.43 (1.01 to 2.04) 1.35 (0.98 to 1.84)

  • 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
Case-control studies
 Kleiven et al 38 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 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

  • 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 al 40 67% Mantel–Haenszel test Age

  • Shift versus day:

  • 1) %Spells/man/year: 25.1 vs 33.1 (p<0.01),

  • 2) % Lost days/ working days: 0.83 vs 1.04 (NS)

 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: 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 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

  • Proportion of workers at least 1 sick day:

  • 2-shift: OR: 2.6 (p<0.05) (95% CI not reported) Fixed/rotating night: no numerical results given

 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