{"title":"Biological age and predicting future health care utilisation.","authors":"Apostolos Davillas, Andrew M Jones","doi":"10.1016/j.jhealeco.2024.102956","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":50186,"journal":{"name":"Journal of Health Economics","volume":"99 ","pages":"102956"},"PeriodicalIF":3.4000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Health Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1016/j.jhealeco.2024.102956","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/6 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
This journal seeks articles related to the economics of health and medical care. Its scope will include the following topics:
Production and supply of health services;
Demand and utilization of health services;
Financing of health services;
Determinants of health, including investments in health and risky health behaviors;
Economic consequences of ill-health;
Behavioral models of demanders, suppliers and other health care agencies;
Evaluation of policy interventions that yield economic insights;
Efficiency and distributional aspects of health policy;
and such other topics as the Editors may deem appropriate.