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Does Self-Assessed Health Reflect the True Health State?

Self-assessed health (SAH) is a widely used tool to estimate population health. However, the debate continues as to what exactly this ubiquitous measure of social science research means for policy conclusions. This study is aimed at understanding the tenability of the construct of SAH by simultaneou...

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Detalles Bibliográficos
Autores principales: Paul, Pavitra, Nguemdjo, Ulrich, Kovtun, Natalia, Ventelou, Bruno
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8582715/
https://www.ncbi.nlm.nih.gov/pubmed/34769671
http://dx.doi.org/10.3390/ijerph182111153
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author Paul, Pavitra
Nguemdjo, Ulrich
Kovtun, Natalia
Ventelou, Bruno
author_facet Paul, Pavitra
Nguemdjo, Ulrich
Kovtun, Natalia
Ventelou, Bruno
author_sort Paul, Pavitra
collection PubMed
description Self-assessed health (SAH) is a widely used tool to estimate population health. However, the debate continues as to what exactly this ubiquitous measure of social science research means for policy conclusions. This study is aimed at understanding the tenability of the construct of SAH by simultaneously modelling SAH and clinical morbidity. Using data from 17 waves (2001–2017) of the Russian Longitudinal Monitoring Survey, which captures repeated response for SAH and frequently updates information on clinical morbidity, we operationalise a recursive semi-ordered probit model. Our approach allows for the estimation of the distributional effect of clinical morbidity on perceived health. This study establishes the superiority of inferences from the recursive model. We illustrated the model use for examining the endogeneity problem of perceived health for SAH, contributing to population health research and public policy development, in particular, towards the organisation of health systems.
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spelling pubmed-85827152021-11-12 Does Self-Assessed Health Reflect the True Health State? Paul, Pavitra Nguemdjo, Ulrich Kovtun, Natalia Ventelou, Bruno Int J Environ Res Public Health Article Self-assessed health (SAH) is a widely used tool to estimate population health. However, the debate continues as to what exactly this ubiquitous measure of social science research means for policy conclusions. This study is aimed at understanding the tenability of the construct of SAH by simultaneously modelling SAH and clinical morbidity. Using data from 17 waves (2001–2017) of the Russian Longitudinal Monitoring Survey, which captures repeated response for SAH and frequently updates information on clinical morbidity, we operationalise a recursive semi-ordered probit model. Our approach allows for the estimation of the distributional effect of clinical morbidity on perceived health. This study establishes the superiority of inferences from the recursive model. We illustrated the model use for examining the endogeneity problem of perceived health for SAH, contributing to population health research and public policy development, in particular, towards the organisation of health systems. MDPI 2021-10-23 /pmc/articles/PMC8582715/ /pubmed/34769671 http://dx.doi.org/10.3390/ijerph182111153 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Paul, Pavitra
Nguemdjo, Ulrich
Kovtun, Natalia
Ventelou, Bruno
Does Self-Assessed Health Reflect the True Health State?
title Does Self-Assessed Health Reflect the True Health State?
title_full Does Self-Assessed Health Reflect the True Health State?
title_fullStr Does Self-Assessed Health Reflect the True Health State?
title_full_unstemmed Does Self-Assessed Health Reflect the True Health State?
title_short Does Self-Assessed Health Reflect the True Health State?
title_sort does self-assessed health reflect the true health state?
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8582715/
https://www.ncbi.nlm.nih.gov/pubmed/34769671
http://dx.doi.org/10.3390/ijerph182111153
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