alexa Association of socio-demographic factors, sick-leave and health care patterns with the risk of being granted a disability pension among psychiatric outpatients with depression.
Infectious Diseases

Infectious Diseases

Epidemiology: Open Access

Author(s): MittendorferRutz E, Hrknen T, Tiihonen J, Haukka J

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Abstract BACKGROUND: Depression ranges among the leading causes of early exit from the labor market worldwide. We aimed to investigate the associations of socio-demographic factors, sickness absence, health care and prescription patterns with the risk of being granted a disability pension in psychiatric outpatients with depression. METHODS: All non-retired patients aged 18-60 years and living in Sweden 31.12.2005 with at least one psychiatric outpatient care visit due to a depressive episode during 2006 (N = 18,034): were followed from 01.01.2007 to 31.12.2010 with regard to granting of all-cause and diagnosis-specific disability pension. Uni- and multivariate Rate Ratios (RR) and 95\% Confidence Intervals (CI) were estimated for the various risk markers by Poisson Regression. RESULTS: During the four years of follow-up, 3044 patients (16.8\%) were granted a disability pension, the majority due to mental disorders (2558, 84\%). In the multivariate analyses, being female, below 25 or above 45 years of age, with low educational level, living alone, residing outside big cities and being born outside Europe were predictive of a granted disability pension. Frequent in- and outpatient care due to mental disorders, prescription of antidepressants and long sickness absence spells were also associated with an increased risk of disability pension (range of RRs 1.10 to 5.26). Somatic health care was only predictive of disability pension due to somatic disorders. The risk of being granted a disability pension remained at the same level as at the start of follow-up for about 1.5 years, when it started to decrease and to level off at about 20\% of the risk at the end of follow-up. CONCLUSIONS: Identified risk markers should be considered when monitoring individuals with depression and when designing intervention programs.
This article was published in PLoS One and referenced in Epidemiology: Open Access

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