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Journal Article

A latent class approach to inequity in health using biomarker data

Authors

Publication date

Jul 2020

Summary

We adopt an empirical approach to analyse, measure and decompose inequality of opportunity (IOp) in health, based on a latent class model. This addresses some of the limitations that affect earlier work in this literature concerning the definition of types, such as partial observability, the ad hoc selection of circumstances, the curse of dimensionality and unobserved type‐specific heterogeneity that may lead to biased estimates of IOp. We apply our latent class approach to measure IOp in allostatic load, a composite measure of biomarker data. Using data from Understanding Society: The UK Household Longitudinal Study (UKHLS), we find that a latent class model with three latent types best fits the data, with the corresponding types characterised in terms of differences in their observed circumstances. Decomposition analysis shows that about two thirds of the total inequalities in allostatic load can be attributed to the direct and indirect contribution of circumstances and that the direct contribution of effort is small. Further analysis conditional on age–sex groups reveals that the relative (percentage) contribution of circumstances to the total inequalities remains mostly unaffected and the direct contribution of effort remains small.

Published in

Health Economics

Volume and page numbers

29 , 808 -826

DOI

https://doi.org/10.1002/hec.4022

ISSN

16

Subjects

Economics, Health, and Biology

Links

University of Essex, Albert Sloman Library Periodicals *restricted to University of Essex registered users* - https://lib.essex.ac.uk/iii/encore/record/C__Rb2328367


Related publications

  1. A latent class approach to inequity in health using biomarker data

    Vincenzo Carrieri, Apostolos Davillas, and Andrew M. Jones

    1. Economics
    2. Health
    3. Biology

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