首页|Biological age and predicting future health care utilisation

Biological age and predicting future health care utilisation

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  • NETL
  • NSTL
  • Elsevier
© 2024 The Author(s)We explore the role of epigenetic biological age in predicting subsequent health care utilisation. We use longitudinal data from the UK Understanding Society panel, capitalising on the availability of baseline epigenetic biological age measures along with data on general practitioner (GP) consultations, outpatient (OP) visits, and hospital inpatient (IP) care collected 5–12 years from baseline. Using least absolute shrinkage and selection operator (LASSO) regression analyses and accounting for participants’ pre-existing health conditions, baseline biological underlying health, and socio-economic predictors we find that biological age is selected as a predictor of future GP consultations and IP care, while chronological rather than biological age is selected for future OP visits. Post-selection prediction analysis and Shapley-Shorrocks decompositions, comparing our preferred prediction models to models that replace biological age with chronological age, suggest that biological ageing has a stronger role in the models predicting future IP care as opposed to “gatekeeping” GP consultations.

Biological ageEpigeneticsHealth care utilisationLASSORed herring hypothesisSupervised machine learning

Davillas A.、Jones A.M.

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Department of Economics University of Macedonia||IZA Bonn

Department of Economics and Related Studies University of York

2025

10.1016/j.jhealeco.2024.102956

Journal of health economics

Journal of health economics

ISSN：0167-6296
年,卷(期)：2025.99(Jan.)
  • 52