Estimating MS-related work productivity loss and factors associated with work productivity loss in a representative Australian sample of people with multiple sclerosis

Mult Scler. 2019 Jun;25(7):994-1004. doi: 10.1177/1352458518781971. Epub 2018 Jun 18.

Abstract

Background: Little is known about the work productivity loss in multiple sclerosis (MS).

Objectives: To quantify the MS-related work productivity loss and to compare factors associated with labour force participation and work productivity loss.

Methods: Participants were from the Australian MS Longitudinal Study. MS-related work productivity loss included absenteeism (time missed from work) and presenteeism (reduced productivity while working). Data were analysed using log-binomial and Cragg hurdle regression.

Results: Among 740 MS employees, 56% experienced any work productivity loss due to MS in the past 4 weeks. The mean total work productivity loss was 2.5 days (14.2% lost productive time), absenteeism 0.6 days (3.4%) and presenteeism 1.9 days (10.8%)), leading to AU$6767 (US$4985, EURO€4578) loss per person annually. Multivariable analyses showed that work productivity was determined most strongly by symptoms, particularly 'fatigue and cognitive symptoms' and 'pain and sensory symptoms', while older age, and lower education level were also predictive of not being in the labour force.

Conclusion: MS-related presenteeism was three times higher than absenteeism, highlighting the importance of presenteeism being included in employment outcomes. The dominance of symptom severity as predictors of both work participation and productivity loss emphasises the need for improved management of symptoms.

Keywords: Multiple sclerosis; absenteeism; fatigue; pain; presenteeism; symptoms; work productivity loss.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Absenteeism*
  • Adult
  • Australia / epidemiology
  • Efficiency*
  • Employment / statistics & numerical data*
  • Female
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Multiple Sclerosis / epidemiology*
  • Multiple Sclerosis / physiopathology
  • Presenteeism / statistics & numerical data*
  • Severity of Illness Index