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Decomposing the educational inequalities in the factors associated with severe acute malnutrition among under-five children in low- and middle-income countries.

ABSTRACT: BACKGROUND:Low- and Middle-Income Countries (LMIC) have remained plagued with the burden of severe acute malnutrition (SAM). The decomposition of the educational inequalities in SAM across individual, household and neighbourhood characteristics in LMIC has not been explored. This study aims to decompose educational-related inequalities in the development of SAM among under-five children in LMIC and identify the risk factors that contribute to the inequalities. METHODS:We pooled successive secondary data from the Demographic and Health Survey conducted between 2010 and 2018 in 51 LMIC. We analysed data of 532,680 under-five children nested within 55,823 neighbourhoods. Severe acute malnutrition was the outcome variable while the literacy status of mothers was the main exposure variable. The explanatory variables cut across the individual-, household- and neighbourhood-level factors of the mother-child pair. Oaxaca-Blinder decomposition method was used at p?=?0.05. RESULTS:The proportion of children whose mothers were not educated ranged from 0.1% in Armenia and Kyrgyz Republic to as much as 86.1% in Niger. The overall prevalence of SAM in the group of children whose mothers had no education was 5.8% compared with 4.2% among those whose mothers were educated, this varied within each country. Fourteen countries (Cameroon(p

SUBMITTER: Fagbamigbe AF

PROVIDER: S-EPMC7183681 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Decomposing the educational inequalities in the factors associated with severe acute malnutrition among under-five children in low- and middle-income countries.

Fagbamigbe A F AF Kandala N B NB Uthman O A OA

BMC public health 20200425 1

<h4>Background</h4>Low- and Middle-Income Countries (LMIC) have remained plagued with the burden of severe acute malnutrition (SAM). The decomposition of the educational inequalities in SAM across individual, household and neighbourhood characteristics in LMIC has not been explored. This study aims to decompose educational-related inequalities in the development of SAM among under-five children in LMIC and identify the risk factors that contribute to the inequalities.<h4>Methods</h4>We pooled su ...[more]

PMID: 32334558

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Project description:A good understanding of the poor-non-poor gap in childhood development of severe wasting (SW) is a must in tackling the age-long critical challenge to health outcomes of vulnerable children in low- and middle-income countries (LMICs). There is a dearth of information about the factors explaining differentials in wealth inequalities in the distribution of SW in LMICs. This study is aimed at quantifying the contributions of demographic, contextual and proximate factors in explaining the poor-non-poor gap in SW in LMICs. We pooled successive secondary data from the Demographic and Health Survey conducted between 2010 and 2018 in LMICs. The final data consist of 532,680 under-five children nested within 55,823 neighbourhoods from 51 LMICs. Our outcome variable is having SW or not among under-five children. Oaxaca-Blinder decomposition was used to decipher poor-non-poor gap in the determinants of SW. Children from poor households ranged from 37.5% in Egypt to 52.1% in Myanmar. The overall prevalence of SW among children from poor households was 5.3% compared with 4.2% among those from non-poor households. Twenty-one countries had statistically significant pro-poor inequality (i.e. SW concentrated among children from poor households) while only three countries showed statistically significant pro-non-poor inequality. There were variations in the important factors responsible for the wealth inequalities across the countries. The major contributors to wealth inequalities in SW include neighbourhood socioeconomic status, media access, as well as maternal age and education. Socio-economic factors created the widest gaps in the inequalities between the children from poor and non-poor households in developing SW. A potential strategy to alleviate the burden of SW is to reduce wealth inequalities among mothers in the low- and middle-income countries through multi-sectoral and country-specific interventions with considerations for the factors identified in this study.

Project description:BackgroundThe heavy and ever rising burden of non-communicable diseases (NCDs) in low- and middle-income countries (LMICs) warrants interventions to reduce their underlying risk factors, which are often linked to lifestyles. To effectively supplement nationwide policies with targeted interventions, it is important to know how these risk factors are distributed across socioeconomic segments of populations in LMICs. This study quantifies the prevalence and socioeconomic inequalities in lifestyle risk factors in LMICs, to identify policy priorities conducive to the Sustainable Development Goal of a one third reduction in deaths from NCDs by 2030.MethodsData from 1,278,624 adult respondents to Demographic & Health Surveys across 22 LMICs between 2013 and 2018 are used to estimate crude prevalence rates and socioeconomic inequalities in tobacco use, overweight, harmful alcohol use and the clustering of these three in a household. Inequalities are measured by a concentration index and correlated with the percentage of GDP spent on health. We estimate a multilevel model to examine associations of individual characteristics with the different lifestyle risk factors.ResultsThe prevalence of tobacco use among men ranges from 59.6% (Armenia) to 6.6% (Nigeria). The highest level of overweight among women is 83.7% (Egypt) while this is less than 12% in Burundi, Chad and Timor-Leste. 82.5% of women in Burundi report that their partner is "often or sometimes drunk" compared to 1.3% in Gambia. Tobacco use is concentrated among the poor, except for the low share of men smoking in Nigeria. Overweight, however, is concentrated among the better off, especially in Tanzania and Zimbabwe (Erreygers Index (EI) 0.227 and 0.232). Harmful alcohol use is more concentrated among the better off in Nigeria (EI 0.127), while Chad, Rwanda and Togo show an unequal pro-poor distribution (EI respectively - 0.147, - 0.210, - 0.266). Cambodia exhibits the largest socioeconomic inequality in unhealthy household behaviour (EI - 0.253). The multilevel analyses confirm that in LMICs, tobacco and alcohol use are largely concentrated among the poor, while overweight is concentrated among the better-off. The associations between the share of GDP spent on health and the socioeconomical distribution of lifestyle factors are multidirectional.ConclusionsThis study emphasizes the importance of lifestyle risk factors in LMICs and the socioeconomic variation therein. Given the different socioeconomic patterns in lifestyle risk factors - overweight patters in LMICs differ considerably from those in high income countries- tailored interventions towards specific high-risk populations are warranted to supplement nationwide policies.

Dataset Information

Decomposing the educational inequalities in the factors associated with severe acute malnutrition among under-five children in low- and middle-income countries.

Publications

Decomposing the educational inequalities in the factors associated with severe acute malnutrition among under-five children in low- and middle-income countries.

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