Social determinants of inequalities in child undernutrition in Bangladesh: A decomposition analysis

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Abstract

Socioeconomic inequalities in child undernutrition remain one of the main challenges in Bangladesh. The social determinants of health are mostly responsible for such inequalities across different population groups. However, no study has examined the relative contribution of different social determinants to the socioeconomic inequality in child undernutrition in Bangladesh. Our objective is to measure the extent of socioeconomic‐related inequalities in childhood stunting and identify the key social determinants that potentially explain these inequalities in Bangladesh. We used data for children younger than 5 years of age for this analysis from 2 rounds of Bangladesh Demographic and Health Surveys conducted in 2004 and 2014. We examined the socioeconomic inequality in stunting using the concentration curve and concentration index. We then decomposed the concentration index into the contributions of individual social determinants. We found significant inequality in stunting prevalence. The negative concentration index of stunting indicated that stunting was more concentrated among the poor than among the well‐off. Our results suggest that inequalities in stunting increased between 2004 and 2014. Household economic status, maternal and paternal education, health‐seeking behavior of the mothers, sanitation, fertility, and maternal stature were the major contributors to the disparity in stunting prevalence in Bangladesh. Equity is a critical component of sustainable development goals. Health policymakers should work together across sectors and develop strategies for effective intersectoral actions to adequately address the social determinants of equity and reduce inequalities in stunting and other health outcomes.

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Most cited references 31

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Maternal and child undernutrition and overweight in low-income and middle-income countries

Robert E Black, Cesar G Victora, Susan P. Walker … (2013)

The Lancet, 382(9890), 427-451

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Association of maternal stature with offspring mortality, underweight, and stunting in low- to middle-income countries.

Emre Özaltin (2010)

Although maternal stature has been associated with offspring mortality and health, the extent to which this association is universal across developing countries is unclear. To examine the association between maternal stature and offspring mortality, underweight, stunting, and wasting in infancy and early childhood in 54 low- to middle-income countries. Analysis of 109 Demographic and Health Surveys in 54 countries conducted between 1991 and 2008. Study population consisted of a nationally representative cross-sectional sample of children aged 0 to 59 months born to mothers aged 15 to 49 years. Sample sizes were 2,661,519 (mortality), 587,096 (underweight), 558,347 (stunting), and 568,609 (wasting) children. Likelihood of mortality, underweight, stunting, or wasting in children younger than 5 years. The mean response rate across surveys in the mortality data set was 92.8%. In adjusted models, a 1-cm increase in maternal height was associated with a decreased risk of child mortality (absolute risk difference [ARD], 0.0014; relative risk [RR], 0.988; 95% confidence interval [CI], 0.987-0.988), underweight (ARD, 0.0068; RR, 0.968; 95% CI, 0.968-0.969), stunting (ARD, 0.0126; RR, 0.968; 95% CI, 0.967-0.968), and wasting (ARD, 0.0005; RR, 0.994; 95% CI, 0.993-0.995). Absolute risk of dying among children born to the tallest mothers (> or = 160 cm) was 0.073 (95% CI, 0.072-0.074) and to those born to the shortest mothers (< 145 cm) was 0.128 (95% CI, 0.126-0.130). Country-specific decrease in the risk for child mortality associated with a 1-cm increase in maternal height varied between 0.978 and 1.011, with the decreased risk being statistically significant in 46 of 54 countries (85%) (alpha = .05). Among 54 low- to middle-income countries, maternal stature was inversely associated with offspring mortality, underweight, and stunting in infancy and childhood.

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

Laura Howe, James R M Hargreaves, Sharon Huttly (2008)

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.