TY - JOUR
T1 - Measuring socioeconomic status in multicountry studies
T2 - Results from the eight-country MAL-ED study
AU - Psaki, Stephanie R.
AU - Seidman, Jessica C.
AU - Miller, Mark
AU - Gottlieb, Michael
AU - Bhutta, Zulfiqar A.
AU - Ahmed, Tahmeed
AU - Ahmed, AM M.S.
AU - Bessong, Pascal
AU - John, Sushil M.
AU - Kang, Gagandeep
AU - Kosek, Margaret
AU - Lima, Aldo
AU - Shrestha, Prakash
AU - Svensen, Erling
AU - Checkley, William
N1 - Funding Information:
The Interactions of Malnutrition & Enteric Infections: Consequences for Child Health and Development (MAL-ED) study is carried out as a collaborative project and supported by the Bill & Melinda Gates Foundation, the Foundation for the NIH, and the National Institutes of Health/Fogarty International Center. The authors thank the staff and participants of the MAL-ED Network Project for their important contributions. William Checkley was further supported by a Pathway to Independence Award (R00HL096955) from the National Heart, Lung and Blood Institute, National Institutes of Health.
PY - 2014/3/21
Y1 - 2014/3/21
N2 - 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.
AB - 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.
KW - Child growth
KW - Classification
KW - Measurement
KW - Socioeconomic status
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U2 - 10.1186/1478-7954-12-8
DO - 10.1186/1478-7954-12-8
M3 - Article
C2 - 24656134
AN - SCOPUS:84897986964
SN - 1478-7954
VL - 12
JO - Population Health Metrics
JF - Population Health Metrics
IS - 1
M1 - 8
ER -