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Biomarkers, disability and health care demand

Apostolos Davillas and Stephen Pudney

Economics & Human Biology, 2020, vol. 39, issue C

Abstract: Using longitudinal data from a representative UK panel, we focus on a group of apparently healthy individuals with no history of disability or major chronic health condition at baseline. A latent variable structural equation model is used to analyse the predictive role of latent baseline biological health, indicated by a rich set of biomarkers, and other personal characteristics, in determining the individual’s disability state and health service utilisation five years later. We find that baseline biological health affects future health service utilisation very strongly, via progression to functional disability channel. We also find systematic income gradients in future disability risks, with those of higher income experiencing a lower progress to disability. Our model reveals that observed pro-rich inequity in health care utilisation, is driven by the fact that higher-income people tend to make greater use of health care treatment, for any given biological health and disability status; this is despite the lower average need for treatment shown by the negative association of income with both baseline ill biological health and disability progression risk. Factor loadings for latent baseline health show that a broader set of blood-based biomarkers, rather than the current focus mainly on blood pressure, cholesterol and adiposity, may need to be considered for public health screening programs.

Keywords: Health services; Health care demand; Biomarkers; Disability (search for similar items in EconPapers)
JEL-codes: C3 C8 I10 I18 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Working Paper: Biomarkers, disability and health care demand (2020) Downloads
Working Paper: Biomarkers, disability and health care demand (2020) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ehbiol:v:39:y:2020:i:c:s1570677x20301994

DOI: 10.1016/j.ehb.2020.100929

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