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A latent class approach to inequity in health using biomarker data

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  • Vincenzo Carrieri
  • Apostolos Davillas
  • Andrew M. Jones

Abstract

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.

Suggested Citation

  • Vincenzo Carrieri & Apostolos Davillas & Andrew M. Jones, 2020. "A latent class approach to inequity in health using biomarker data," Health Economics, John Wiley & Sons, Ltd., vol. 29(7), pages 808-826, July.
  • Handle: RePEc:wly:hlthec:v:29:y:2020:i:7:p:808-826
    DOI: 10.1002/hec.4022
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Chris Sampson’s journal round-up for 15th June 2020
      by Chris Sampson in The Academic Health Economists' Blog on 2020-06-15 11:00:19

    Citations

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    Cited by:

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    2. Paolo Brunori & Alain Trannoy & Caterina Francesca Guidi, 2021. "Ranking populations in terms of inequality of health opportunity: A flexible latent type approach," Health Economics, John Wiley & Sons, Ltd., vol. 30(2), pages 358-383, February.
    3. Paolo Brunori & Apostolos Davillas & Andrew Jones & Giovanna Scarchilli, 2021. "Model-based Recursive Partitioning to Estimate Unfair Health Inequalities in the United Kingdom Household Longitudinal Study," Working Papers 596, ECINEQ, Society for the Study of Economic Inequality.
    4. Apostolos Davillas & Andrew M Jones, 2021. "The first wave of the COVID‐19 pandemic and its impact on socioeconomic inequality in psychological distress in the UK," Health Economics, John Wiley & Sons, Ltd., vol. 30(7), pages 1668-1683, July.
    5. Davillas, Apostolos & Jones, Andrew M., 2020. "The COVID-19 pandemic and its impact on inequality of opportunity in psychological distress in the UK," ISER Working Paper Series 2020-07, Institute for Social and Economic Research.
    6. Barry, L.E. & O'Neill, S. & Heaney, L.G. & O'Neill, C., 2021. "Stress-related health depreciation: Using allostatic load to predict self-rated health," Social Science & Medicine, Elsevier, vol. 283(C).
    7. Carrieri, Vincenzo & Davillas, Apostolos & Jones, Andrew M., 2021. "Equality of Opportunity and the Expansion of Higher Education in the UK," IZA Discussion Papers 14485, Institute of Labor Economics (IZA).
    8. Ding, Lanlin & Jones, Andrew M. & Nie, Peng, 2020. "Ex Ante Inequality of Opportunity in Health among the Elderly in China: A Distributional Decomposition Analysis of Biomarkers," IZA Discussion Papers 13292, Institute of Labor Economics (IZA).
    9. Salas-Ortiz, A.;, 2022. "Accumulation and transmission of inequality of opportunity in the double burden of malnutrition: the case of Mexico," Health, Econometrics and Data Group (HEDG) Working Papers 22/07, HEDG, c/o Department of Economics, University of York.
    10. Nie, P. & Ding, L. & Jones, A.M., 2020. "Inequality of opportunity in bodyweight among middle-aged and older Chinese: a distributional approach," Health, Econometrics and Data Group (HEDG) Working Papers 20/14, HEDG, c/o Department of Economics, University of York.
    11. Etilé, Fabrice & Frijters, Paul & Johnston, David W. & Shields, Michael A., 2021. "Measuring resilience to major life events," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 598-619.
    12. Cristina Elisa Orso & Matija Kovacic, 2022. "Trends in Inequality of Opportunity in health over the life cycle: the role of early-life conditions," Working Papers 598, ECINEQ, Society for the Study of Economic Inequality.

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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