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- Kivimäki, M, et al.
(författare)
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Sickness absence as a prognostic marker for common chronic conditions : analysis of mortality in the GAZEL study.
- 2008
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Ingår i: Occup Environ Med. - : BMJ. - 1470-7926 .- 1351-0711. ; 65:12, s. 820-6
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 3. |
- Ropponen, A, et al.
(författare)
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Predicting the duration of sickness absence spells due to back pain: a population-based study from Sweden
- 2020
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Ingår i: Occupational and environmental medicine. - : BMJ. - 1470-7926 .- 1351-0711. ; 77:2, s. 115-121
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Tidskriftsartikel (refereegranskat)abstract
- We aimed to develop and validate a prediction model for the duration of sickness absence (SA) spells due to back pain (International Statistical Classification of Diseases and Related Health Problems 10th Revision: M54), using Swedish nationwide register microdata.MethodsInformation on all new SA spells >14 days from 1 January 2010 to 30 June 2012 and on possible predictors were obtained. The duration of SA was predicted by using piecewise constant hazard models. Nine predictors were selected for the final model based on a priori decision and log-likelihood loss. The final model was estimated in a random sample of 70% of the SA spells and later validated in the remaining 30%.ResultsOverall, 64 048 SA spells due to back pain were identified during the 2.5 years; 74% lasted ≤90 days, and 9% >365 days. The predictors included in the final model were age, sex, geographical region, employment status, multimorbidity, SA extent at the start of the spell, initiation of SA spell in primary healthcare and number of SA days and specialised outpatient healthcare visits from the preceding year. The overall c-statistic (0.547, 95% CI 0.542 to 0.552) suggested a low discriminatory capacity at the individual level. The c-statistic was 0.643 (95% CI 0.634 to 0.652) to predict >90 days spells, 0.686 (95% CI 0.676 to 0.697) to predict >180 spells and 0.753 (95% CI 0.740 to 0.766) to predict >365 days spells.ConclusionsThe model discriminates SA spells >365 days from shorter SA spells with good discriminatory accuracy.
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