Sequence analysis of sickness absence and disability pension days in 2012-2018 among privately employed white-collar workers in Sweden: a prospective cohort study.
prospective_cohort · Level II
Where this comes from
- Record sourced from PubMed, PMID 38097244.
- Also identified by DOI 10.1136/bmjopen-2023-078066 and PMC identifier 10729113.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
The aim of the study is to explore sequences of sickness absence (SA) and disability pension (DP) days from 2012 to 2018 among privately employed white-collar workers. A 7-year prospective cohort study using microdata from nationwide registers. Sweden. All 1 283 516 privately employed white-collar workers in Sweden in 2012 aged 18-67. Sequence analysis was used to describe clusters of individuals who followed similar development of SA and DP net days/year, and multinomial logistic regression to analyse associations between sociodemographic variables and belonging to each observed cluster of sequences. Odds ratios (ORs) and 95% confidence intervals (CIs) were adjusted for baseline sociodemographics. We identified five clusters of SA and DP sequences: (1) 'low or no SA or DP' (88.7% of the population), (2) 'SA due to other than mental diagnosis' (5.2%), (3) 'SA due to mental diagnosis' (3.4%), (4) 'not eligible for SA or DP' (1.4%) and (5) 'DP' (1.2%). Men, highly educated, born outside Sweden and high-income earners were more likely to belong to the first and the fourth cluster (ORs 1.13-4.49). The second, third and fifth clusters consisted mainly of women, low educated and low-income (ORs 1.22-8.90). There were only small differences between branches of industry in adjusted analyses, and many were not significant. In general, only a few privately employed white-collar workers had SA and even fewer had DP during the 7-year follow-up. The risk of belonging to a cluster characterised by SA or DP varied by sex, levels of education and income, and other sociodemographic factors.
Medical subject headings
- Persons with Disabilities