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      Mothers' education but not fathers' education, household assets or land ownership is the best predictor of child health inequalities in rural Uganda

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          Abstract

          Background

          Health and nutrition inequality is a result of a complex web of factors that include socio-economic inequalities. Various socio-economic indicators exist however some do not accurately predict inequalities in children. Others are not intervention feasible.

          Objective

          To examine the association of four socio-economic indicators namely: mothers' education, fathers' education, household asset index, and land ownership with growth stunting, which is used as a proxy for health and nutrition inequalities among infants and young children.

          Methods

          This was a cross-sectional survey conducted in the rural district of Hoima, Uganda. Two-stage cluster sampling design was used to obtain 720 child/mother pairs. Information on indicators of household socio-economic status and child anthropometry was gathered by administering a structured questionnaire to mothers in their home settings. Regression modelling was used to determine the association of socio-economic indicators with stunting.

          Results

          One hundred seventy two (25%) of the studied children were stunted, of which 105 (61%) were boys (p < 0.001). Bivariate analysis indicated a higher prevalence of stunting among children of: non-educated mothers compared to mothers educated above primary school (odds ratio (OR) 2.5, 95% confidence interval (CI) 1.4–4.4); non-educated fathers compared to fathers educated above secondary school (OR 1.7, 95% CI 0.8–3.5); households belonging in the "poorest" quintile for the asset index compared to the "least poor" quintile (OR 2.1, 95% CI 1.2–3.7); Land ownership exhibited no differentials with stunting. Simultaneously adjusting all socio-economic indicators in conditional regression analysis left mothers' education as the only independent predictor of stunting with children of non-educated mothers significantly more likely to be stunted compared to those of mothers educated above primary school (OR 2.1, 95% CI 1.1–3.9). More boys than girls were significantly stunted in poorer than wealthier socio-economic strata.

          Conclusions

          Of four socio-economic indicators, mothers' education is the best predictor for health and nutrition inequalities among infants and young children in rural Uganda. This suggests a need for appropriate formal education of the girl child aimed at promoting child health and nutrition. The finding that boys are adversely affected by poverty more than their female counterparts corroborates evidence from previous studies.

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          Most cited references39

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          Estimating wealth effects without expenditure data--or tears: an application to educational enrollments in states of India.

          Using data from India, we estimate the relationship between household wealth and children's school enrollment. We proxy wealth by constructing a linear index from asset ownership indicators, using principal-components analysis to derive weights. In Indian data this index is robust to the assets included, and produces internally coherent results. State-level results correspond well to independent data on per capita output and poverty. To validate the method and to show that the asset index predicts enrollments as accurately as expenditures, or more so, we use data sets from Indonesia, Pakistan, and Nepal that contain information on both expenditures and assets. The results show large, variable wealth gaps in children's enrollment across Indian states. On average a "rich" child is 31 percentage points more likely to be enrolled than a "poor" child, but this gap varies from only 4.6 percentage points in Kerala to 38.2 in Uttar Pradesh and 42.6 in Bihar.
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            On the measurement of inequalities in health.

            This paper offers a critical appraisal of the various methods employed to date to measure inequalities in health. It suggests that only two of these--the slope index of inequality and the concentration index--are likely to present an accurate picture of socioeconomic inequalities in health. The paper also presents several empirical examples to illustrate of the dangers of using other measures such as the range, the Lorenz curve and the index of dissimilarity.
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              A simplified general method for cluster-sample surveys of health in developing countries.

              General guidelines are presented for the use of cluster-sample surveys for health surveys in developing countries. The emphasis is on methods which can be used by practitioners with little statistical expertise and no background in sampling. A simple self-weighting design is used, based on that used by the World Health Organization's Expanded Programme on Immunization (EPI). Topics covered include sample design, methods of random selection of areas and households, sample-size calculation and the estimation of proportions, ratios and means with standard errors appropriate to the design. Extensions are discussed, including stratification and multiple stages of selection. Particular attention is paid to allowing for the structure of the survey in estimating sample size, using the design effect and the rate of homogeneity. Guidance is given on possible values for these parameters. A spreadsheet is included for the calculation of standard errors.
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                Author and article information

                Journal
                Int J Equity Health
                International Journal for Equity in Health
                BioMed Central (London )
                1475-9276
                2004
                13 October 2004
                : 3
                : 9
                Affiliations
                [1 ]Centre for International Health, University of Bergen, Armauer Hansen Building, N-5021 Bergen, Norway
                [2 ]Ministry of Health, P.O Box 7272, Kampala, Uganda
                [3 ]Department of Paediatrics and Child Health, Makerere University Medical School, P.O Box 7072, Kampala, Uganda
                [4 ]Division of International Health (IHCAR), Karolinska Institute, Norrbacka, S-17176 Stockholm, Sweden
                Article
                1475-9276-3-9
                10.1186/1475-9276-3-9
                529301
                15482596
                7073ce78-ab7b-42b1-88e8-38f2f0861a47
                Copyright © 2004 Wamani et al; licensee BioMed Central Ltd.

                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.

                History
                : 6 April 2004
                : 13 October 2004
                Categories
                Research

                Health & Social care
                socio-economic,inequalities,mother education,uganda,stunting,targeting,child health
                Health & Social care
                socio-economic, inequalities, mother education, uganda, stunting, targeting, child health

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