Medical Predictors of Disability Pension in Long-term Sickness Absence. Results from a population-based prospective study in the Norwegian county of Hordaland 1994–1999
Year: 2002
Type: report
Study design: Observational Study
Abstract: Background: While several socio-demographic predictors of disability pension have been identified, less is known about the importance of the medical aspects. The aim of this study was to explore the importance of diagnoses, prognoses, level of care and previous sickness absence as predictors for future disability pension status among long-term sickness absentees. Methods: A representative sample of Norwegian long-term sickness absentees, 2043 women and 1585 men, with detailed diagnostic information (based on International Classification of Primary Care), was followed up for 5 years. The date of granting of disability pension was obtained from the Norwegian disability register and was used as the dependent variable in Cox multivariate regression. Results: Kaplan-Meier estimates of the 5-year risk of disability pension (1- survival) were 22.9% for the full sample, 22.5% for men and 23.3% for the women. Men on sick leave for mental health disorders had an increased disability risk. For women a diagnosis of a cardiovascular disorder implied a slightly increased risk, while a pregnancy-related sickness absence carried almost no risk for disability pension during follow-up. Among cases with musculoskeletal disorders (54.5% of the sample), subgroups with significantly different disability risks were identified, with a gender-specific pattern. The prognoses formulated by the certifying doctor significantly predicted the outcome. Previous sickness absence days increased the disability risk, but were significant only for total absence above 20 weeks in the 4 years preceding inclusion. The level of care at the eight-week sickness certification did not affect the disability risk. Conclusion: Medical factors were important in identifying cases with an increased risk of disability pension.
Language: English
Subfield: Demography
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2216128089