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Stress-related health depreciation: Using allostatic load to predict self-rated health

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  • Barry, L.E.
  • O'Neill, S.
  • Heaney, L.G.
  • O'Neill, C.

Abstract

Approximately one quarter of UK adults are currently diagnosed with two or more chronic conditions, often referred to as multimorbidity. Chronic stress has been implicated in the development of many diseases common to multimorbidity. Policymakers and clinicians have acknowledged the need for more preventative approaches to deal with the rise of multimorbidity and “early ageing”. However divergence may occur between an individual's self-rated health and objectively measured health that may preclude preventative action. The use of biomarkers which look ‘under the skin’ provide crucial information on an individual's underlying health to facilitate lifestyle change or healthcare utilisation. The UK's Understanding Society dataset, was used to examine whether baseline variation in biomarkers measuring stress-related “wear and tear” – Allostatic Load (AL) – predict changes in future self-rated health (SRH) while adjusting for baseline SRH, socioeconomic and lifestyle factors, and healthcare inputs. An interaction between baseline AL and baseline SRH was included to test for differential rates of SRH change. We examined SRH using the SF6D instrument, measuring health-related-quality of life (HRQoL), as well as its physical and mental health components separately. We found that HRQoL and physical health decline faster for those with higher baseline AL (indicating greater “wear and tear”) however the same pattern was not observed for mental health. These findings provide novel insights for clinicians and policymakers on the usefulness of AL in capturing health trajectories of which individual's may not be aware and its importance in targeting resilience enhancing measures earlier in the lifecourse to delay physical health decline.

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  • Barry, L.E. & O'Neill, S. & Heaney, L.G. & O'Neill, C., 2021. "Stress-related health depreciation: Using allostatic load to predict self-rated health," Social Science & Medicine, Elsevier, vol. 283(C).
  • Handle: RePEc:eee:socmed:v:283:y:2021:i:c:s0277953621005025
    DOI: 10.1016/j.socscimed.2021.114170
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    1. Davillas, Apostolos & Pudney, Stephen, 2020. "Biomarkers as precursors of disability," Economics & Human Biology, Elsevier, vol. 36(C).
    2. Davillas, Apostolos & Pudney, Stephen, 2017. "Concordance of health states in couples: Analysis of self-reported, nurse administered and blood-based biomarker data in the UK Understanding Society panel," Journal of Health Economics, Elsevier, vol. 56(C), pages 87-102.
    3. Davillas, Apostolos & Pudney, Stephen, 2020. "Biomarkers, disability and health care demand," Economics & Human Biology, Elsevier, vol. 39(C).
    4. Vincenzo Carrieri & Apostolos Davillas & Andrew M. Jones, 2020. "A latent class approach to inequity in health using biomarker data," Health Economics, John Wiley & Sons, Ltd., vol. 29(7), pages 808-826, July.
    5. Benzeval, Michaela & Davillas, Apostolos & Kumari, Meena & Lynn, Peter, 2014. "Understanding Society: The UK Household Longitudinal Study Biomarker User Guide and Glossary," MPRA Paper 114713, University Library of Munich, Germany.

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    Keywords

    Stress; Ageing; Allostatic load; Health depreciation; Biomarkers; SF6D;
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