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IZA Discussion Paper No. 17159
July 2024
Biological Age and Predicting Future Health Care Utilisation

revised version published in: Journal of Health Economics, 2025, 99, 102956

We explore the role of epigenetic biological age in predicting subsequent health care utilisation. We use longitudinal data from the UK Understanding Society panel, capitalizing 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 predicts future GP consultations and IP care, while chronological rather than biological age matters 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.

Communications
Mark Fallak
mark.fallak@liser.lu
+352 585-855-526
World of Labour
Olga Nottmeyer
olga.nottmeyer@liser.lu
+352 585-855-501
Network Coordination
Christina Gathmann
christina.gathmann@liser.lu

The IZA@LISER Network is a global community of scholars dedicated to excellence in labor economics and related fields, now coordinated at the Luxembourg Institute of Socio-Economic Research (LISER) following its transition from Bonn.

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