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All-cause and diagnosis-specific sickness absence as a predictor of sustained suboptimal health: a 14-year follow-up in the GAZEL cohort

Abstract

Background Previous studies show that sickness absence predicts health, but it is unclear whether this association is persistent over time and whether specific diseases underlie long-term associations. The aim of this study was to investigate overall and diagnosis-specific sickness absences as predictors of sustained suboptimal health.

Methods Prospective occupational cohort study of 15 320 employees (73% men) aged 37–51. Sickness absence records in 1990–1992, including 13 diagnostic categories, were examined in relation to self-rated health measured annually for the years 1993–2006.

Results 3385 employees (22%) had >30 days of sickness absence and 5564 (36%) 1–30 days during the 3-year exposure window. Repeated-measures logistic regression analysis adjusted for age, sex, occupational status and chronic diseases show that employees with >30 absence days, compared with those with no absences, had 2.14 (95% CI 2.00 to 2.29) times higher odds for suboptimal health over the 14 years of follow-up. Retirement did not dilute this association. Nine sickness absence diagnostic categories, such as diseases of the nervous, circulatory, metabolic, musculoskeletal, sensory and gastrointestinal systems, cancer, mental disorders and external causes, independently predicted increased risk of sustained suboptimal health.

Conclusions There is a remarkably persistent association between sickness absence and future long-term self-rated health status for the majority of diagnostic categories for sickness absence. This suggests that the association between sickness absence and health is ubiquitous and not driven by a limited number of rare and severe diseases.

  • Sickness absence
  • self-rated health
  • longitudinal
  • multilevel
  • occupational
  • longitudinal studies
  • multilevel modelling
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