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Sustainable Working Life Patterns in a Swedish Twin Cohort: Age-Related Sequences of Sickness Absence, Disability Pension, Unemployment, and Premature Death during Working Life

Author

Listed:
  • Annina Ropponen

    (Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
    Finnish Institute of Occupational Health, 00032 Työterveyslaitos, Finland)

  • Pontus Josefsson

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

  • Petri Böckerman

    (IZA Institute of Labor Economics, 53113 Bonn, Germany
    School of Business and Economics, University of Jyväskylä, 40014 Jyväskylä, Finland
    Labour Institute for Economic Research LABORE, 00100 Helsinki, Finland)

  • Karri Silventoinen

    (Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
    Population Research Unit, Faculty of Social Sciences, University of Helsinki, 00014 Helsinki, Finland)

  • Jurgita Narusyte

    (Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
    Center of Epidemiology and Community Medicine, Stockholm County Council, 104 31 Stockholm, Sweden)

  • Mo Wang

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

  • Pia Svedberg

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

Abstract

We aimed to investigate sustainable working life via age-related sequences of sickness absence (SA), disability pension (DP), unemployment (UE), premature death, and the influence of individual characteristics, accounting for familial confounding. The sample included monozygotic (MZ) and dizygotic (DZ) same-sexed twin pairs with register data ( n = 47,450) that were followed for 10 years in four age cohorts: 26–35 ( n = 9892), 36–45 ( n = 10,620), 46–55 ( n = 12,964) and 56–65 ( n = 13,974). A sequence analysis was done in a 7-element state space: 1. “Sustainable working life”: SA/DP 0–30 days and UE 0–90 days; 2. “Unemployment >90 days”: SA/DP 0–30 days and UE > 90 days; 3. “Moderate SA/DP”: SA/DP 30–180 days; 4. “Almost full year of SA/DP”: SA/DP 180–365 days; 5. “Full year of SA/DP”: SA/DP ≥ 365 days; 6. Death; 7. Old-age pension. The largest cluster had a sustainable working life and never experienced states 2–6 (34–59%). Higher education and being married predicted a lower likelihood of experiencing states 2–6. The MZ twin pairs (vs. DZ) were more often in the same cluster suggesting the role of genetic factors. To conclude, the sustainable working life was the largest cluster group. Few individuals had prolonged periods of interruptions of sustainable working life meriting actions, especially in early adulthood for interventions to support workability.

Suggested Citation

  • Annina Ropponen & Pontus Josefsson & Petri Böckerman & Karri Silventoinen & Jurgita Narusyte & Mo Wang & Pia Svedberg, 2022. "Sustainable Working Life Patterns in a Swedish Twin Cohort: Age-Related Sequences of Sickness Absence, Disability Pension, Unemployment, and Premature Death during Working Life," IJERPH, MDPI, vol. 19(17), pages 1-14, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:17:p:10549-:d:896405
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    References listed on IDEAS

    as
    1. Brendan Halpin, 2017. "SADI: Sequence analysis tools for Stata," Stata Journal, StataCorp LP, vol. 17(3), pages 546-572, September.
    2. Annina Ropponen & Mo Wang & Jurgita Narusyte & Karri Silventoinen & Petri Böckerman & Pia Svedberg, 2021. "Sustainable Working Life in a Swedish Twin Cohort—A Definition Paper with Sample Overview," IJERPH, MDPI, vol. 18(11), pages 1-16, May.
    3. Christian Brzinsky-Fay & Ulrich Kohler & Magdalena Luniak, 2006. "Sequence analysis with Stata," Stata Journal, StataCorp LP, vol. 6(4), pages 435-460, December.
    4. Laura Serra & Kristin Farrants & Kristina Alexanderson & Mónica Ubalde & Tea Lallukka, 2022. "Trajectory analyses in insurance medicine studies: Examples and key methodological aspects and pitfalls," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-12, February.
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