Pierre Martel1, Francisco Mbofana2, Simon Cousens3. 1. Multiple Indicator Cluster Survey, Mokhotlong, Lesotho. 2. Ministry of Health, Maputo, Mozambique. 3. London School of Hygiene and Tropical Medicine, London, UK.
Abstract
BACKGROUND: The DHS wealth index - based on a statistical technique known as principal component analysis - is used extensively in mainstream surveys and epidemiological studies to assign individuals to wealth categories from information collected on common assets and household characteristics. Since its development in the late nineties, the index has established itself as a standard and, due to its ease of use, has led to a large and welcome increase in the analysis of inequalities. The index is, however, known to present some serious limitations, one being a bias towards patterns of urban wealth: the so-called "urban bias". METHODS: We use 10 data sets - 5 MICS (Multiple Indicator Cluster Survey), 4 DHS (Demographic and Health Survey) and one HBS (Household Budget Survey) - to demonstrate that urban bias continues to be a prominent and worrying feature of the wealth index, even after several methodological changes implemented in recent years to try to reduce it. We then propose and investigate an approach to improve the performance of the index and reduce the urban bias. This approach involves the use of ordinal rather than dummy variables, of a polychoric instead of a product-moment correlation matrix, and the use of two principal components rather than one. These approaches are used jointly to produce the polychoric dual-component wealth index (P2C). RESULTS: The P2C index enables a larger proportion of the variance of the asset variables to be accounted for, results in all assets contributing positively to the wealth score, exploits added analytical power from ordinal variables, and incorporates the extra dimension of wealth expressed by the second principal component. It results in a better representation of typically rural characteristics of wealth and leads to the identification of more plausible distributions of both the urban and rural populations across wealth quintiles, which are closer to expenditure quintiles than the standard DHS index. CONCLUSIONS: The P2C wealth index can be easily applied to mainstream surveys, such as the MICS and DHS, and to epidemiological studies; it yields more credible distributions of rural and urban subpopulations across wealth quintiles. It is proposed as an alternative to the DHS wealth index.
BACKGROUND: The DHS wealth index - based on a statistical technique known as principal component analysis - is used extensively in mainstream surveys and epidemiological studies to assign individuals to wealth categories from information collected on common assets and household characteristics. Since its development in the late nineties, the index has established itself as a standard and, due to its ease of use, has led to a large and welcome increase in the analysis of inequalities. The index is, however, known to present some serious limitations, one being a bias towards patterns of urban wealth: the so-called "urban bias". METHODS: We use 10 data sets - 5 MICS (Multiple Indicator Cluster Survey), 4 DHS (Demographic and Health Survey) and one HBS (Household Budget Survey) - to demonstrate that urban bias continues to be a prominent and worrying feature of the wealth index, even after several methodological changes implemented in recent years to try to reduce it. We then propose and investigate an approach to improve the performance of the index and reduce the urban bias. This approach involves the use of ordinal rather than dummy variables, of a polychoric instead of a product-moment correlation matrix, and the use of two principal components rather than one. These approaches are used jointly to produce the polychoric dual-component wealth index (P2C). RESULTS: The P2C index enables a larger proportion of the variance of the asset variables to be accounted for, results in all assets contributing positively to the wealth score, exploits added analytical power from ordinal variables, and incorporates the extra dimension of wealth expressed by the second principal component. It results in a better representation of typically rural characteristics of wealth and leads to the identification of more plausible distributions of both the urban and rural populations across wealth quintiles, which are closer to expenditure quintiles than the standard DHS index. CONCLUSIONS: The P2C wealth index can be easily applied to mainstream surveys, such as the MICS and DHS, and to epidemiological studies; it yields more credible distributions of rural and urban subpopulations across wealth quintiles. It is proposed as an alternative to the DHS wealth index.
Authors: Aluísio J D Barros; Carine Ronsmans; Henrik Axelson; Edilberto Loaiza; Andréa D Bertoldi; Giovanny V A França; Jennifer Bryce; J Ties Boerma; Cesar G Victora Journal: Lancet Date: 2012-03-31 Impact factor: 79.321
Authors: Laura D Howe; Bruna Galobardes; Alicia Matijasevich; David Gordon; Deborah Johnston; Obinna Onwujekwe; Rita Patel; Elizabeth A Webb; Debbie A Lawlor; James R Hargreaves Journal: Int J Epidemiol Date: 2012-03-21 Impact factor: 7.196