Sickness absence as a prognostic marker for common chronic conditions : analysis of mortality in the GAZEL study.

• Sickness absence as a prognostic marker for common chronic conditions: analysis of mortality in the GAZEL study.Kivimäki M, Head J, Ferrie JE, Singh-Manoux A, Westerlund H, Vahtera J, Leclerc A, Melchior M, Chevalier A, Alexanderson K, Zins M, Goldberg M.Department of Epidemiology and Public Health, University College London, London, UK. m.kivimaki@ucl.ac.ukOBJECTIVES: To determine whether sickness absence is a prognostic marker in terms of mortality among people with common chronic conditions. METHODS: Prospective occupational cohort study of 13,077 men and 4871 women aged 37-51 from the National Gas and Electricity Company, France. Records of physician-certified sickness absences over a 3-year period were obtained from employers' registers. Chronic conditions were assessed in annual surveys over the same period. The main outcome measure was all-cause mortality (803 deaths, mean follow-up after assessment of sickness absence: 13.9 years). RESULTS: In Cox proportional hazard models adjusted for age, sex, socioeconomic position and co-morbidity, >28 annual sickness-absence days versus no absence days was associated with an excess mortality risk among those with cancer (hazard ratio 5.4, 95% CI 2.2 to 13.1), depression (1.7, 1.1 to 2.8), chronic bronchitis or asthma (2.7, 1.6 to 4.6) and hypertension (1.6, 1.0 to 2.6). The corresponding hazard ratios for more than five long (>14 days) sickness-absence episodes per 10 person-years versus no such episodes were 5.4 (2.2 to 13.1), 1.8 (1.3 to 2.7), 2.0 (1.3 to 3.2) and 1.8 (1.2 to 2.7), respectively. Areas under receiver operating characteristics curves for these absence measures varied between 0.56 and 0.73, indicating the potential of these measures to distinguish groups at high risk of mortality. The findings were consistent across sex, age and socioeconomic groups and in those with and without co-morbid conditions. CONCLUSION: Data on sickness absence may provide useful prognostic information for common chronic conditions at the population level.

Nyckelord

Absenteeism

Adult

Chronic Disease/*mortality

Comorbidity

Female

France/epidemiology

Humans

Male

Middle Aged

Occupational Health/*statistics & numerical data

Prognosis

Prospective Studies

Sick Leave/*statistics & numerical data

MEDICINE

MEDICIN

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