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Utility and limitations of measures of health inequities: a theoretical perspective
SUMMARY BOX: This paper examines common approaches for quantifying health inequities and assesses the extent to which they incorporate key theories necessary for explicating the definition of health inequity. The first theoretical analysis examined the distinction between inter-individual and inter-...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Co-Action Publishing
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4565845/ https://www.ncbi.nlm.nih.gov/pubmed/26361347 http://dx.doi.org/10.3402/gha.v8.27591 |
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author | Alonge, Olakunle Peters, David H. |
author_facet | Alonge, Olakunle Peters, David H. |
author_sort | Alonge, Olakunle |
collection | PubMed |
description | SUMMARY BOX: This paper examines common approaches for quantifying health inequities and assesses the extent to which they incorporate key theories necessary for explicating the definition of health inequity. The first theoretical analysis examined the distinction between inter-individual and inter-group health inequalities as measures of health inequities. The second analysis considered the notion of fairness in health inequalities from different philosophical perspectives. To understand the extent to which different measures of health inequities incorporate these theoretical explanations, four criteria were used to assess each measure: 1) Does the indicator demonstrate inter-group or inter-individual health inequalities or both; 2) Does it reflect health inequalities in relation to socioeconomic position; 3) Is it sensitive to the absolute transfer of health (outcomes, services, or both) or income/wealth between groups; 4) Could it be used to capture inequalities in relation to other population groupings (other than socioeconomic status)? The measures assessed include: before and after measures within only the disadvantaged population, range, Gini coefficient, Pseudo-Gini coefficient, index of dissimilarity, concentration index, slope and relative indices of inequality, and regression techniques. None of these measures satisfied all the four criteria, except the range. Whereas each measure quantifies a different perspective in health inequities, using a measure within only the disadvantaged population does not measure health inequities in a meaningful way, even using before and after changes. For a more complete assessment of how programs affect health inequities, it may be useful to use more than one measure. |
format | Online Article Text |
id | pubmed-4565845 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Co-Action Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-45658452015-09-23 Utility and limitations of measures of health inequities: a theoretical perspective Alonge, Olakunle Peters, David H. Glob Health Action Current Debate SUMMARY BOX: This paper examines common approaches for quantifying health inequities and assesses the extent to which they incorporate key theories necessary for explicating the definition of health inequity. The first theoretical analysis examined the distinction between inter-individual and inter-group health inequalities as measures of health inequities. The second analysis considered the notion of fairness in health inequalities from different philosophical perspectives. To understand the extent to which different measures of health inequities incorporate these theoretical explanations, four criteria were used to assess each measure: 1) Does the indicator demonstrate inter-group or inter-individual health inequalities or both; 2) Does it reflect health inequalities in relation to socioeconomic position; 3) Is it sensitive to the absolute transfer of health (outcomes, services, or both) or income/wealth between groups; 4) Could it be used to capture inequalities in relation to other population groupings (other than socioeconomic status)? The measures assessed include: before and after measures within only the disadvantaged population, range, Gini coefficient, Pseudo-Gini coefficient, index of dissimilarity, concentration index, slope and relative indices of inequality, and regression techniques. None of these measures satisfied all the four criteria, except the range. Whereas each measure quantifies a different perspective in health inequities, using a measure within only the disadvantaged population does not measure health inequities in a meaningful way, even using before and after changes. For a more complete assessment of how programs affect health inequities, it may be useful to use more than one measure. Co-Action Publishing 2015-09-09 /pmc/articles/PMC4565845/ /pubmed/26361347 http://dx.doi.org/10.3402/gha.v8.27591 Text en © 2015 Olakunle Alonge and David H. Peters http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license. |
spellingShingle | Current Debate Alonge, Olakunle Peters, David H. Utility and limitations of measures of health inequities: a theoretical perspective |
title | Utility and limitations of measures of health inequities: a theoretical perspective |
title_full | Utility and limitations of measures of health inequities: a theoretical perspective |
title_fullStr | Utility and limitations of measures of health inequities: a theoretical perspective |
title_full_unstemmed | Utility and limitations of measures of health inequities: a theoretical perspective |
title_short | Utility and limitations of measures of health inequities: a theoretical perspective |
title_sort | utility and limitations of measures of health inequities: a theoretical perspective |
topic | Current Debate |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4565845/ https://www.ncbi.nlm.nih.gov/pubmed/26361347 http://dx.doi.org/10.3402/gha.v8.27591 |
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