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Rates and predictors of recurrent work disability due to common mental health disorders in the United States

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  • Fraser W Gaspar
  • Catherine S Zaidel
  • Carolyn S Dewa

Abstract

Context: Despite the high prevalence of work disability due to common mental disorders (CMD), no information exists on the rates and predictors of recurrence in a United States population. Objective: To estimate recurrent work disability statistics and evaluate factors associated with recurrence due to CMDs including adjustment, anxiety, bipolar, and depressive disorders. Methods: Recurrent work disability statistics were calculated using a nationwide database of disability claims. For the CMDs, univariate and multiple variable analyses were used to examine demographic factors and comorbidities associated with the time to recurrence. Results: Of the CMDs, cases with bipolar (n = 3,017) and depressive disorders (n = 20,058) had the highest recurrence densities, 98.7 and 70.9 per 1000 person-years, respectively. These rates were more than three times higher than recurrence rates for other chronic disorders (e.g., diabetes, asthma; n = 105,558) and non-chronic disorders (e.g., injury, acute illnesses; n = 153,786). Individuals with CMD were also more likely to have a subsequent disability distinct from their mental health condition. Risk factors for recurrent CMD disability included being younger, being an hourly employee, living in a geographic area with more college graduates, having more previous psychiatric visits, having a previous work leave, and the type of work industry. Conclusions: Results indicate that CMD patients may benefit from additional care and disability management both during and after their work absence to help prevent subsequent CMD and non-CMD related leaves.

Suggested Citation

  • Fraser W Gaspar & Catherine S Zaidel & Carolyn S Dewa, 2018. "Rates and predictors of recurrent work disability due to common mental health disorders in the United States," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-14, October.
    • Handle: RePEc:plo:pone00:0205170
    DOI: 10.1371/journal.pone.0205170
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    References listed on IDEAS

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    1. Austin P.C. & Tu J.V., 2004. "Bootstrap Methods for Developing Predictive Models," The American Statistician, American Statistical Association, vol. 58, pages 131-137, May.
    2. Giny Norder & Corné A M Roelen & Willem van Rhenen & Jan Buitenhuis & Ute Bültmann & Johannes R Anema, 2012. "Predictors of Recurrent Sickness Absence Due to Depressive Disorders – A Delphi Approach Involving Scientists and Physicians," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-7, December.
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    Cited by:

    1. Abasiama Etuknwa & Kevin Daniels & Rachel Nayani & Constanze Eib, 2023. "Sustainable Return to Work for Workers with Mental Health and Musculoskeletal Conditions," IJERPH, MDPI, vol. 20(2), pages 1-17, January.
    2. Mikko Laaksonen, 2021. "Work Resumption after a Fixed-Term Disability Pension: Changes over Time during a Period of Decreasing Incidence of Disability Retirement," IJERPH, MDPI, vol. 18(9), pages 1-13, April.

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