Using repeated measures of sleep disturbances to predict future diagnosis-specific work disability: A cohort study

Abstract

Context: It is unknown whether or not measuring sleep disturbances repeatedly, rather than at only one point in time, improves prediction of work disability. Study Objective: To examine sleep disturbance patterns over time as a risk marker for diagnosis-specific work disability. Design: Prospective cohort study linking repeatedly measured self-reported sleep disturbances with records of physician-certified work disability (sickness absence) from a national register. Participants responded to surveys in 2000-2002, and 2004, and were followed up for 12 mo. Setting: Public sector employees in Finland. Participants: 25,639 participants (mean age 45.6 yr, 82% female). Main Outcome Measure: Incident diagnosis-specific sickness absence of > 9 days. Results: During a mean follow-up of 323 days, 4,975 employees (19%) had a new episode of sickness absence. In multivariable-adjusted models corrected for multiple testing, stable severe sleep disturbances, in comparison with no sleep disturbances, were associated with an increased risk of sickness absence due to diseases of the musculoskeletal system (hazard ratio (HR) 1.68, 95% confidence interval (CI) 1.45-1.95), and injuries and poisonings (HR 1.64, 95% CI 1.23-2.18). Increases in sleep disturbances predicted subsequent sickness absence due to mental disorders (HR 1.59, 95% CI 1.32-1.91), and diseases of the musculoskeletal system (HR 1.44, 95% CI 1.27-1.64) According to net reclassification improvement analyses, measurement of sleep disturbance patterns rather than the level of sleep disturbances at one point in time improved prediction of all-cause sickness absence by 14%, and diagnosis-specific sickness absences up to 17% (P for improvement < 0.001). Conclusions: Increasing and severe chronic sleep disturbances mark an increased risk of diagnosis-specific work disability.