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Occupational Branch and Labor Market Marginalization among Young Employees with Adult Onset of Attention Deficit Hyperactivity Disorder—A Population-Based Matched Cohort Study

Author

Listed:
  • Katalin Gémes

    (Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, 17177 Stockholm, Sweden)

  • Emma Björkenstam

    (Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, 17177 Stockholm, Sweden
    Department of Medical Sciences, Uppsala University, 75185 Uppsala, Sweden)

  • Syed Rahman

    (Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, 17177 Stockholm, Sweden)

  • Klas Gustafsson

    (Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, 17177 Stockholm, Sweden)

  • Heidi Taipale

    (Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, 17177 Stockholm, Sweden
    Niuvanniemi Hospital, FI-70240 Kuopio, Finland
    School of Pharmacy, University of Eastern Finland, FI-70211 Kuopio, Finland)

  • Antti Tanskanen

    (Niuvanniemi Hospital, FI-70240 Kuopio, Finland)

  • Lisa Ekselius

    (Department Women’s and Children’s Health, Uppsala University, 75237 Uppsala, Sweden)

  • Ellenor Mittendorfer-Rutz

    (Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, 17177 Stockholm, Sweden)

  • Magnus Helgesson

    (Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, 17177 Stockholm, Sweden)

Abstract

We compared labor market marginalization (LMM), conceptualized as days of unemployment, sickness absence and disability pension, across occupational branches (manufacturing, construction, trade, finance, health and social care, and education), among young employees with or without attention deficit hyperactivity disorder (ADHD) and examined whether sociodemographic and health-related factors explain these associations. All Swedish residents aged 19–29 years and employed between 1 January 2005 and 31 December 2011 were eligible. Individuals with a first ADHD diagnosis ( n = 6030) were matched with ten controls and followed for five years. Zero-inflated negative binomial regression was used to model days of LMM with adjustments for sociodemographic and health-related factors. In total, 20% of those with ADHD and 59% of those without had no days of LMM during the follow-up. The median of those with LMM days with and without ADHD was 312 and 98 days. Having an ADHD diagnosis was associated with a higher incidence of LMM days (incident rate ratios (IRRs) 2.7–3.1) with no differences across occupational branches. Adjustments for sociodemographic and health-related factors explained most of the differences (IRRs: 1.4–1.7). In conclusion, young, employed adults with ADHD had a higher incidence of LMM days than those without, but there were no substantial differences between branches, even after adjusting for sociodemographic and health-related factors.

Suggested Citation

  • Katalin Gémes & Emma Björkenstam & Syed Rahman & Klas Gustafsson & Heidi Taipale & Antti Tanskanen & Lisa Ekselius & Ellenor Mittendorfer-Rutz & Magnus Helgesson, 2022. "Occupational Branch and Labor Market Marginalization among Young Employees with Adult Onset of Attention Deficit Hyperactivity Disorder—A Population-Based Matched Cohort Study," IJERPH, MDPI, vol. 19(12), pages 1-12, June.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:12:p:7254-:d:838100
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    References listed on IDEAS

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    1. Andreas Jangmo & Ralf Kuja-Halkola & Ana Pérez-Vigil & Catarina Almqvist & Cynthia M Bulik & Brian D’Onofrio & Paul Lichtenstein & Ewa Ahnemark & Tamara Werner-Kiechle & Henrik Larsson, 2021. "Attention-deficit/hyperactivity disorder and occupational outcomes: The role of educational attainment, comorbid developmental disorders, and intellectual disability," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-16, March.
    2. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
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