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Measuring total health inequality: adding individual variation to group-level differences
BACKGROUND: Studies have revealed large variations in average health status across social, economic, and other groups. No study exists on the distribution of the risk of ill-health across individuals, either within groups or across all people in a society, and as such a crucial piece of total health...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2002
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC140140/ https://www.ncbi.nlm.nih.gov/pubmed/12379153 http://dx.doi.org/10.1186/1475-9276-1-3 |
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author | Gakidou, Emmanuela King, Gary |
author_facet | Gakidou, Emmanuela King, Gary |
author_sort | Gakidou, Emmanuela |
collection | PubMed |
description | BACKGROUND: Studies have revealed large variations in average health status across social, economic, and other groups. No study exists on the distribution of the risk of ill-health across individuals, either within groups or across all people in a society, and as such a crucial piece of total health inequality has been overlooked. Some of the reason for this neglect has been that the risk of death, which forms the basis for most measures, is impossible to observe directly and difficult to estimate. METHODS: We develop a measure of total health inequality – encompassing all inequalities among people in a society, including variation between and within groups – by adapting a beta-binomial regression model. We apply it to children under age two in 50 low- and middle-income countries. Our method has been adopted by the World Health Organization and is being implemented in surveys around the world; preliminary estimates have appeared in the World Health Report (2000). RESULTS: Countries with similar average child mortality differ considerably in total health inequality. Liberia and Mozambique have the largest inequalities in child survival, while Colombia, the Philippines and Kazakhstan have the lowest levels among the countries measured. CONCLUSIONS: Total health inequality estimates should be routinely reported alongside average levels of health in populations and groups, as they reveal important policy-related information not otherwise knowable. This approach enables meaningful comparisons of inequality across countries and future analyses of the determinants of inequality. |
format | Text |
id | pubmed-140140 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2002 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-1401402003-01-21 Measuring total health inequality: adding individual variation to group-level differences Gakidou, Emmanuela King, Gary Int J Equity Health Research BACKGROUND: Studies have revealed large variations in average health status across social, economic, and other groups. No study exists on the distribution of the risk of ill-health across individuals, either within groups or across all people in a society, and as such a crucial piece of total health inequality has been overlooked. Some of the reason for this neglect has been that the risk of death, which forms the basis for most measures, is impossible to observe directly and difficult to estimate. METHODS: We develop a measure of total health inequality – encompassing all inequalities among people in a society, including variation between and within groups – by adapting a beta-binomial regression model. We apply it to children under age two in 50 low- and middle-income countries. Our method has been adopted by the World Health Organization and is being implemented in surveys around the world; preliminary estimates have appeared in the World Health Report (2000). RESULTS: Countries with similar average child mortality differ considerably in total health inequality. Liberia and Mozambique have the largest inequalities in child survival, while Colombia, the Philippines and Kazakhstan have the lowest levels among the countries measured. CONCLUSIONS: Total health inequality estimates should be routinely reported alongside average levels of health in populations and groups, as they reveal important policy-related information not otherwise knowable. This approach enables meaningful comparisons of inequality across countries and future analyses of the determinants of inequality. BioMed Central 2002-08-12 /pmc/articles/PMC140140/ /pubmed/12379153 http://dx.doi.org/10.1186/1475-9276-1-3 Text en Copyright © 2002 Gakidou and King; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL. |
spellingShingle | Research Gakidou, Emmanuela King, Gary Measuring total health inequality: adding individual variation to group-level differences |
title | Measuring total health inequality: adding individual variation to group-level differences |
title_full | Measuring total health inequality: adding individual variation to group-level differences |
title_fullStr | Measuring total health inequality: adding individual variation to group-level differences |
title_full_unstemmed | Measuring total health inequality: adding individual variation to group-level differences |
title_short | Measuring total health inequality: adding individual variation to group-level differences |
title_sort | measuring total health inequality: adding individual variation to group-level differences |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC140140/ https://www.ncbi.nlm.nih.gov/pubmed/12379153 http://dx.doi.org/10.1186/1475-9276-1-3 |
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