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Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries

BACKGROUND: Epidemiological studies often require measures of socio-economic position (SEP). The application of principal components analysis (PCA) to data on asset-ownership is one popular approach to household SEP measurement. Proponents suggest that the approach provides a rational method for wei...

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Autores principales: Howe, Laura D, Hargreaves, James R, Huttly, Sharon RA
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2248177/
https://www.ncbi.nlm.nih.gov/pubmed/18234082
http://dx.doi.org/10.1186/1742-7622-5-3
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author Howe, Laura D
Hargreaves, James R
Huttly, Sharon RA
author_facet Howe, Laura D
Hargreaves, James R
Huttly, Sharon RA
author_sort Howe, Laura D
collection PubMed
description BACKGROUND: Epidemiological studies often require measures of socio-economic position (SEP). The application of principal components analysis (PCA) to data on asset-ownership is one popular approach to household SEP measurement. Proponents suggest that the approach provides a rational method for weighting asset data in a single indicator, captures the most important aspect of SEP for health studies, and is based on data that are readily available and/or simple to collect. However, the use of PCA on asset data may not be the best approach to SEP measurement. There remains concern that this approach can obscure the meaning of the final index and is statistically inappropriate for use with discrete data. In addition, the choice of assets to include and the level of agreement between wealth indices and more conventional measures of SEP such as consumption expenditure remain unclear. We discuss these issues, illustrating our examples with data from the Malawi Integrated Household Survey 2004–5. METHODS: Wealth indices were constructed using the assets on which data are collected within Demographic and Health Surveys. Indices were constructed using five weighting methods: PCA, PCA using dichotomised versions of categorical variables, equal weights, weights equal to the inverse of the proportion of households owning the item, and Multiple Correspondence Analysis. Agreement between indices was assessed. Indices were compared with per capita consumption expenditure, and the difference in agreement assessed when different methods were used to adjust consumption expenditure for household size and composition. RESULTS: All indices demonstrated similarly modest agreement with consumption expenditure. The indices constructed using dichotomised data showed strong agreement with each other, as did the indices constructed using categorical data. Agreement was lower between indices using data coded in different ways. The level of agreement between wealth indices and consumption expenditure did not differ when different consumption equivalence scales were applied. CONCLUSION: This study questions the appropriateness of wealth indices as proxies for consumption expenditure. The choice of data included had a greater influence on the wealth index than the method used to weight the data. Despite the limitations of PCA, alternative methods also all had disadvantages.
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spelling pubmed-22481772008-02-20 Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries Howe, Laura D Hargreaves, James R Huttly, Sharon RA Emerg Themes Epidemiol Analytic Perspective BACKGROUND: Epidemiological studies often require measures of socio-economic position (SEP). The application of principal components analysis (PCA) to data on asset-ownership is one popular approach to household SEP measurement. Proponents suggest that the approach provides a rational method for weighting asset data in a single indicator, captures the most important aspect of SEP for health studies, and is based on data that are readily available and/or simple to collect. However, the use of PCA on asset data may not be the best approach to SEP measurement. There remains concern that this approach can obscure the meaning of the final index and is statistically inappropriate for use with discrete data. In addition, the choice of assets to include and the level of agreement between wealth indices and more conventional measures of SEP such as consumption expenditure remain unclear. We discuss these issues, illustrating our examples with data from the Malawi Integrated Household Survey 2004–5. METHODS: Wealth indices were constructed using the assets on which data are collected within Demographic and Health Surveys. Indices were constructed using five weighting methods: PCA, PCA using dichotomised versions of categorical variables, equal weights, weights equal to the inverse of the proportion of households owning the item, and Multiple Correspondence Analysis. Agreement between indices was assessed. Indices were compared with per capita consumption expenditure, and the difference in agreement assessed when different methods were used to adjust consumption expenditure for household size and composition. RESULTS: All indices demonstrated similarly modest agreement with consumption expenditure. The indices constructed using dichotomised data showed strong agreement with each other, as did the indices constructed using categorical data. Agreement was lower between indices using data coded in different ways. The level of agreement between wealth indices and consumption expenditure did not differ when different consumption equivalence scales were applied. CONCLUSION: This study questions the appropriateness of wealth indices as proxies for consumption expenditure. The choice of data included had a greater influence on the wealth index than the method used to weight the data. Despite the limitations of PCA, alternative methods also all had disadvantages. BioMed Central 2008-01-30 /pmc/articles/PMC2248177/ /pubmed/18234082 http://dx.doi.org/10.1186/1742-7622-5-3 Text en Copyright © 2008 Howe et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Analytic Perspective
Howe, Laura D
Hargreaves, James R
Huttly, Sharon RA
Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries
title Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries
title_full Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries
title_fullStr Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries
title_full_unstemmed Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries
title_short Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries
title_sort issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries
topic Analytic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2248177/
https://www.ncbi.nlm.nih.gov/pubmed/18234082
http://dx.doi.org/10.1186/1742-7622-5-3
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