Economic Inequality and Child Stunting in Bangladesh and Kenya: An Investigation of Six Hypotheses

Reinbold, Gary W.

doi:10.1111/j.1728-4457.2011.00453.x

Cited by 13 publications

(12 citation statements)

References 39 publications

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“…Using data from repeated national surveys in 25 low- and middle-income countries, Restrepo-Méndez et al [37] have documented a general decline in the prevalence of stunting, accompanied in many cases by worsening equity at the national level. Another strand of literature has employed micro-data for a number of countries, including Bangladesh, to explore associations between under-five stunting and a wide variety of socio-economic and biological factors [15, 16, 26, 36]. Relatively under-researched is the question that links these two literatures: What factors are driving socioeconomic inequities in stunting and their trends?…”

Section: Introductionmentioning

confidence: 99%

Trends and determinants of inequities in childhood stunting in Bangladesh from 1996/7 to 2014

Rabbani

Khan

Yusuf

et al. 2016

Int J Equity Health

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BackgroundWe explore long-term trends and determinants of socioeconomic inequities in chronic childhood undernutrition measured by stunting among under-five children in Bangladesh. Given that one in three children remain stunted in Bangladesh, the socioeconomic mapping of stunting prevalence may be critical in designing public policies and interventions to eradicate childhood undernutrition.MethodsSix rounds of Bangladesh Demographic and Health Survey data are utilized, spanning the period 1996/97 to 2014. Using recognized measures of absolute and relative inequality (namely, absolute and relative difference, concentration curve and index), we quantify trends, and decompose changes in the concentration index to identify factors that best explain observed dynamics.ResultsDespite remarkable improvements in average nutritional status over the last two decades, socio-economic inequalities have persisted, and according to some measures, even worsened. For example, expressed as rate-ratios, the relative inequality in under-five stunting increased by 56% and the concentration index more than doubled between 1996/97 and 2014. Decomposition analyses find that wealth and maternal factors such as mothers’ schooling and short stature are major contributors to observed socio-economic inequalities in child undernutrition and their changes over time.ConclusionsReflecting on recent success around socioeconomic and gender equity in child mortality, and the weak legacy of nutrition policy in Bangladesh, we suggest that nutrition programming energies be focused specifically on the most disadvantaged and applied at scale to close socioeconomic gaps in stunting prevalence.

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Section: Introductionmentioning

confidence: 99%

Trends and determinants of inequities in childhood stunting in Bangladesh from 1996/7 to 2014

Rabbani

Khan

Yusuf

et al. 2016

Int J Equity Health

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“…In another work, we had also shown that there was a significant socioeconomic inequality in childhood stunting in Ethiopia [16]. Studies done in Iran [17], Bangladesh [14, 18], and Kenya [18] also reported pro-poor socioeconomic inequalities in various forms of malnutrition among under-5 children. We found maternal education to be contributing the greatest proportion of the inequality in anemia between the rich and the poor.…”

Section: Discussionmentioning

confidence: 73%

The contribution of dietary and non-dietary factors to socioeconomic inequality in childhood anemia in Ethiopia: a regression-based decomposition analysis

2019

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Objective There is a scarcity of evidence on socioeconomic inequalities of childhood anemia in Ethiopia. We determined the magnitude of socioeconomic inequality in anemia and the contribution of dietary and non-dietary factors to the observed inequality, using a nationally representative data of 2902 children included in the 2016 Ethiopian demographic and health survey. The data were collected following a multistage, stratified cluster sampling strategy. We followed the Blinder–Oaxaca regression-based approach to decompose the inequality and determine the relative contribution (%) of the dietary and non-dietary factors to the observed inequality. Result We found a significant pro-poor socioeconomic inequality in childhood anemia in Ethiopia. A third (~ 33%) of the inequality was attributable to compositional differences in the dietary determinants of anemia (dietary diversity, meal frequency, and breastfeeding factors). Non-dietary factors like residence place, maternal education, and birth weight) jointly explained ~ 36% of the inequality. Maternal education was the single most important factor, accounting alone for ~ 28% the inequality, followed by rural residence (~ 17%) and dietary diversity (~ 16%). Efforts to narrow socioeconomic gaps and/or designing equity sensitive interventions by prioritizing the poor in health/nutrition interventions stands worth of consideration to reduce the burden of childhood anemia in Ethiopia and beyond.

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“…[23] Another study utilizing the Gini coefficient as a measure of inequality in Ecuador found inequality to have a significant, adverse effect on stunting, but only at the provincial scale. [11] In contrast, Gary Reinbold [24] found the Gini coefficient as a measure of economic inequality to be a non-significant predictor of individual health, instead finding the difference between individual household wealth and mean community household wealth to be the most important predictor of stunting, with the odds of stunting.…”

Section: Discussionmentioning

confidence: 94%

The impact of health care spending and income inequality on stunting prevalence

Bowser

Zeng

Akobirshoev

et al. 2016

IJH

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Design: Stunting prevalence data were collected for 86 countries over the period 1995-2010 and combined with panel data that included health care spending and income inequality variables as well as other underlying and socioeconomic variables. Country fixed-effects regression models were utilized to examine the impact of these variables on overall stunting prevalence, controlling for time trends. Setting: While a number of crosscountry analyses have examined the drivers of stunting prevalence reduction, few have examined the impact from health care spending or income inequality. The objective of this analysis was to determine the impact of health care spending and income inequality on overall stunting prevalence. Subjects: The analysis was conducted at the country level using aggregate data, so no individual subjects were included in the analysis. Results: The results show that investments in social health insurance, as a percent of government health care spending, are one of the main drivers of lowered stunting prevalence. In addition, we show that reducing income inequality, by increasing the share of income held by three lowest income groups, reduces stunting levels. Conclusions: The results of the analysis highlight the important role of targeted health care spending and reductions in income inequality on stunting prevalence.

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Economic Inequality and Child Stunting in Bangladesh and Kenya: An Investigation of Six Hypotheses

Cited by 13 publications

References 39 publications

Trends and determinants of inequities in childhood stunting in Bangladesh from 1996/7 to 2014

Trends and determinants of inequities in childhood stunting in Bangladesh from 1996/7 to 2014

The contribution of dietary and non-dietary factors to socioeconomic inequality in childhood anemia in Ethiopia: a regression-based decomposition analysis

The impact of health care spending and income inequality on stunting prevalence

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