You are here

  • Home
  • Archive
  • Volume 8, Issue 5
  • Sickness absence as a predictor of disability retirement in different occupational classes: a register-based study of a working-age cohort in Finland in 2007–2014

Article Text

Article menu

Download PDFPDF

XML
Occupational and environmental medicine
Research
Sickness absence as a predictor of disability retirement in different occupational classes: a register-based study of a working-age cohort in Finland in 2007–2014
  1. Laura Salonen1,
  2. Jenni Blomgren2,
  3. Mikko Laaksonen3,
  4. Mikko Niemelä1,2
  1. 1 Department of Social Research, University of Turku, Turku, Finland
  2. 2 The Social Insurance Institution of Finland (KELA), Helsinki, Finland
  3. 3 The Finnish Centre for Pensions (ETK), Helsinki, Finland
  1. Correspondence to MSocSc Laura Salonen; lksalo{at}utu.fi

Abstract

Objectives The objective of the study was to examine diagnosis-specific sickness absences of different lengths as predictors of disability retirement in different occupational classes.

Design Register-based prospective cohort study up to 8 years of follow-up.

Participants A 70% random sample of the non-retired Finnish population aged 25–62 at the end of 2006 was included (n=1 727 644) and linked to data on sickness absences in 2005 and data on disability retirement in 2007–2014.

Main outcome measures Cox proportional hazards regression was utilised to analyse the association of sickness absence with the risk of all-cause disability retirement during an 8-year follow-up.

Results The risk of disability retirement increased with increasing lengths of sickness absence in all occupational classes. A long sickness absence was a particularly strong predictor of disability retirement in upper non-manual employees as among those with over 180 sickness absence days the HR was 9.19 (95% CI 7.40 to 11.40), but in manual employees the HR was 3.51 (95% CI 3.23 to 3.81) in men. Among women, the corresponding HRs were 7.26 (95% CI 6.16 to 8.57) and 3.94 (95% CI 3.60 to 4.30), respectively. Adjusting for the diagnosis of sickness absence partly attenuated the association between the length of sickness absence and the risk of disability retirement in all employed groups.

Conclusions A long sickness absence is a strong predictor of disability retirement in all occupational classes. Preventing the accumulation of sickness absence days and designing more efficient policies for different occupational classes may be crucial to reduce the number of transitions to early retirement due to disability.

  • social medicine
  • public health

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

https://doi.org/10.1136/bmjopen-2017-020491

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    View Full Text

    Footnotes

    • Contributors LS, JB, ML and MN: contributed to the planning, conducting and reporting of this study. LS: conducted the statistical analyses and wrote the first and successive drafts of the manuscript. JB, ML and MN: advised on the statistical approach and modelling and revised the drafts of manuscripts. LS, JB and ML: interpreted the results. All authors approved the final submitted version.

    • Funding This work is supported by the Strategic Research Council of the Academy of Finland (decision numbers: 293103 and 314250).

    • Competing interests None declared.

    • Patient consent Not required.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement No additional data available.