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Measuring socioeconomic status in multicountry studies: results from the eight-country MAL-ED study

BACKGROUND: There is no standardized approach to comparing socioeconomic status (SES) across multiple sites in epidemiological studies. This is particularly problematic when cross-country comparisons are of interest. We sought to develop a simple measure of SES that would perform well across diverse...

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Autores principales: Psaki, Stephanie R, Seidman, Jessica C, Miller, Mark, Gottlieb, Michael, Bhutta, Zulfiqar A, Ahmed, Tahmeed, Ahmed, AM Shamsir, Bessong, Pascal, John, Sushil M, Kang, Gagandeep, Kosek, Margaret, Lima, Aldo, Shrestha, Prakash, Svensen, Erling, Checkley, William
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4234146/
https://www.ncbi.nlm.nih.gov/pubmed/24656134
http://dx.doi.org/10.1186/1478-7954-12-8
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author Psaki, Stephanie R
Seidman, Jessica C
Miller, Mark
Gottlieb, Michael
Bhutta, Zulfiqar A
Ahmed, Tahmeed
Ahmed, AM Shamsir
Bessong, Pascal
John, Sushil M
Kang, Gagandeep
Kosek, Margaret
Lima, Aldo
Shrestha, Prakash
Svensen, Erling
Checkley, William
author_facet Psaki, Stephanie R
Seidman, Jessica C
Miller, Mark
Gottlieb, Michael
Bhutta, Zulfiqar A
Ahmed, Tahmeed
Ahmed, AM Shamsir
Bessong, Pascal
John, Sushil M
Kang, Gagandeep
Kosek, Margaret
Lima, Aldo
Shrestha, Prakash
Svensen, Erling
Checkley, William
author_sort Psaki, Stephanie R
collection PubMed
description BACKGROUND: There is no standardized approach to comparing socioeconomic status (SES) across multiple sites in epidemiological studies. This is particularly problematic when cross-country comparisons are of interest. We sought to develop a simple measure of SES that would perform well across diverse, resource-limited settings. METHODS: A cross-sectional study was conducted with 800 children aged 24 to 60 months across eight resource-limited settings. Parents were asked to respond to a household SES questionnaire, and the height of each child was measured. A statistical analysis was done in two phases. First, the best approach for selecting and weighting household assets as a proxy for wealth was identified. We compared four approaches to measuring wealth: maternal education, principal components analysis, Multidimensional Poverty Index, and a novel variable selection approach based on the use of random forests. Second, the selected wealth measure was combined with other relevant variables to form a more complete measure of household SES. We used child height-for-age Z-score (HAZ) as the outcome of interest. RESULTS: Mean age of study children was 41 months, 52% were boys, and 42% were stunted. Using cross-validation, we found that random forests yielded the lowest prediction error when selecting assets as a measure of household wealth. The final SES index included access to improved water and sanitation, eight selected assets, maternal education, and household income (the WAMI index). A 25% difference in the WAMI index was positively associated with a difference of 0.38 standard deviations in HAZ (95% CI 0.22 to 0.55). CONCLUSIONS: Statistical learning methods such as random forests provide an alternative to principal components analysis in the development of SES scores. Results from this multicountry study demonstrate the validity of a simplified SES index. With further validation, this simplified index may provide a standard approach for SES adjustment across resource-limited settings.
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spelling pubmed-42341462014-11-18 Measuring socioeconomic status in multicountry studies: results from the eight-country MAL-ED study Psaki, Stephanie R Seidman, Jessica C Miller, Mark Gottlieb, Michael Bhutta, Zulfiqar A Ahmed, Tahmeed Ahmed, AM Shamsir Bessong, Pascal John, Sushil M Kang, Gagandeep Kosek, Margaret Lima, Aldo Shrestha, Prakash Svensen, Erling Checkley, William Popul Health Metr Research BACKGROUND: There is no standardized approach to comparing socioeconomic status (SES) across multiple sites in epidemiological studies. This is particularly problematic when cross-country comparisons are of interest. We sought to develop a simple measure of SES that would perform well across diverse, resource-limited settings. METHODS: A cross-sectional study was conducted with 800 children aged 24 to 60 months across eight resource-limited settings. Parents were asked to respond to a household SES questionnaire, and the height of each child was measured. A statistical analysis was done in two phases. First, the best approach for selecting and weighting household assets as a proxy for wealth was identified. We compared four approaches to measuring wealth: maternal education, principal components analysis, Multidimensional Poverty Index, and a novel variable selection approach based on the use of random forests. Second, the selected wealth measure was combined with other relevant variables to form a more complete measure of household SES. We used child height-for-age Z-score (HAZ) as the outcome of interest. RESULTS: Mean age of study children was 41 months, 52% were boys, and 42% were stunted. Using cross-validation, we found that random forests yielded the lowest prediction error when selecting assets as a measure of household wealth. The final SES index included access to improved water and sanitation, eight selected assets, maternal education, and household income (the WAMI index). A 25% difference in the WAMI index was positively associated with a difference of 0.38 standard deviations in HAZ (95% CI 0.22 to 0.55). CONCLUSIONS: Statistical learning methods such as random forests provide an alternative to principal components analysis in the development of SES scores. Results from this multicountry study demonstrate the validity of a simplified SES index. With further validation, this simplified index may provide a standard approach for SES adjustment across resource-limited settings. BioMed Central 2014-03-21 /pmc/articles/PMC4234146/ /pubmed/24656134 http://dx.doi.org/10.1186/1478-7954-12-8 Text en Copyright © 2014 Psaki 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 credited.
spellingShingle Research
Psaki, Stephanie R
Seidman, Jessica C
Miller, Mark
Gottlieb, Michael
Bhutta, Zulfiqar A
Ahmed, Tahmeed
Ahmed, AM Shamsir
Bessong, Pascal
John, Sushil M
Kang, Gagandeep
Kosek, Margaret
Lima, Aldo
Shrestha, Prakash
Svensen, Erling
Checkley, William
Measuring socioeconomic status in multicountry studies: results from the eight-country MAL-ED study
title Measuring socioeconomic status in multicountry studies: results from the eight-country MAL-ED study
title_full Measuring socioeconomic status in multicountry studies: results from the eight-country MAL-ED study
title_fullStr Measuring socioeconomic status in multicountry studies: results from the eight-country MAL-ED study
title_full_unstemmed Measuring socioeconomic status in multicountry studies: results from the eight-country MAL-ED study
title_short Measuring socioeconomic status in multicountry studies: results from the eight-country MAL-ED study
title_sort measuring socioeconomic status in multicountry studies: results from the eight-country mal-ed study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4234146/
https://www.ncbi.nlm.nih.gov/pubmed/24656134
http://dx.doi.org/10.1186/1478-7954-12-8
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