Severe Acute Malnutrition Among Under-Five Children in Low- and Middle-Income Countries: A Hierarchical Analysis of Associated Risk Factors

2019 ◽  
Author(s):  
Adeniyi Fagbamigbe ◽  
Ngianga-Bakwin Kandala ◽  
Olalekan Uthman
Keyword(s):  
Risk Factors ◽  
Severe Acute Malnutrition ◽  
Acute Malnutrition ◽  
Hierarchical Analysis ◽  
Middle Income ◽  
Under Five ◽  
Under Five Children ◽  
Middle Income Countries ◽  
Associated Risk Factors ◽  
Low And Middle Income

scholarly journals Decomposing the educational inequalities in the risk factors of severe acute malnutrition among under-five children in low and middle-income countries

2019 ◽  
Author(s):  
Adeniyi Francis Fagbamigbe ◽  
Ngianga- Bakwin Kandala ◽  
Olalekan Uthman
Keyword(s):  
Severe Acute Malnutrition ◽  
Acute Malnutrition ◽  
Educational Inequalities ◽  
Middle Income ◽  
Under Five ◽  
Under Five Children ◽  
Middle Income Countries ◽  
Individual Household ◽  
The Individual ◽  
Low And Middle Income

Abstract Background Low- and Middle-income countries (LMIC) are still plagued with the burden of severe acute malnutrition (SAM). While studies have identified factors that influence SAM, efforts have not been made to decompose the educational inequalities across the individual, neighbourhood and national levels in LMIC. This study aims to decompose educational-related inequalities in the prevalence of SAM across LMIC.Methods We pooled successive secondary data from the Demographic and Health Survey (DHS) 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 (literate vs illiterate) was the main exposure variable. The explanatory variables cut across the individual-, household and neighbourhood-level factors of the mothers-children pair. Oaxaca-Blinder decomposition method was used to analyse the educational gap in the factors associated with SAM.Results Mothers with no formal education ranged from 0.1% in Armenia and Kyrgyz 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. Thirteen countries had statistically significant pro-illiterate inequality (i.e. SAM concentrated among uneducated mothers) while none of the countries showed statistically significant pro-literate inequality. There were variations in the important factors responsible for the educational inequalities across the countries. On average, neighbourhood socioeconomic status disadvantage, location of residence were the most important factors in most countries. Other contributors to the explanation of educational inequalities are birth weight, maternal age and toilet type.Conclusions We identified that SAM is prevalent in most LMIC with wide educational inequalities. The occurrence of SAM was explained by the individual, household and community-level factor. A potential strategy to reduce the burden of SAM to reduce educational inequalities among mothers in the low- and middle-income countries through the promotion of women education.

scholarly journals Decomposing the educational inequalities in the factors associated with severe acute malnutrition among under-five children in Low- and Middle-Income Countries

2020 ◽  
Author(s):  
Adeniyi Francis Fagbamigbe ◽  
Ngianga- Bakwin Kandala ◽  
Olalekan Uthman
Keyword(s):  
Severe Acute Malnutrition ◽  
Acute Malnutrition ◽  
Educational Inequalities ◽  
Middle Income ◽  
Under Five ◽  
Factors Associated ◽  
Under Five Children ◽  
Middle Income Countries ◽  
The Individual ◽  
Low And Middle Income

Abstract Background: Low- and Middle-Income Countries (LMIC) have remained plagued with the burden of severe acute malnutrition (SAM). While studies have identified factors that influence SAM, efforts have not been made to decompose the educational inequalities across individual, neighbourhood and national level characteristics in LMIC. 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 (DHS) 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 (literate vs illiterate) was the main exposure variable. The explanatory variables cut across the individual-, household and neighbourhood-level factors of the mothers-children pair. Oaxaca-Blinder decomposition method was used to analyse the educational gap in the factors associated with SAM. Results: Mothers with no formal education ranged from 0.1 % in Armenia and Kyrgyz 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. Thirteen countries had statistically significant pro-illiterate inequality ( p<0.05) while none of the countries showed statistically significant pro-literate inequality. There were variations in the significant factors associated with the educational inequalities across the countries studied. On the average, neighbourhood socioeconomic status disadvantage, location of residence were the most important factors in most countries. Other contributors to the explanation of educational inequalities are birth weight, maternal age and toilet type. Conclusions: We identified that SAM is prevalent in most LMIC with wide educational inequalities. The occurrence of SAM was explained by the individual, household and community-level factor. A potential strategy to reduce the burden of SAM is to reduce educational inequalities among mothers in the low- and middle- income countries through the promotion of women education as better education among all women will close the gaps and reduce the burden of SAM generally.

scholarly journals Hierarchical disentanglement of contextual from compositional risk factors of diarrhoea among under-five children in low- and middle-income countries

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Adeniyi Francis Fagbamigbe ◽  
A. Olalekan Uthman ◽  
Latifat Ibisomi
Keyword(s):  
Risk Factors ◽  
National Level ◽  
Cross Sectional ◽  
Middle Income ◽  
Contextual Risk ◽  
Under Five ◽  
Factors Associated ◽  
Under Five Children ◽  
Middle Income Countries ◽  
Low And Middle Income

AbstractSeveral studies have documented the burden and risk factors associated with diarrhoea in low and middle-income countries (LMIC). To the best of our knowledge, the contextual and compositional factors associated with diarrhoea across LMIC were poorly operationalized, explored and understood in these studies. We investigated multilevel risk factors associated with diarrhoea among under-five children in LMIC. We analysed diarrhoea-related information of 796,150 under-five children (Level 1) nested within 63,378 neighbourhoods (Level 2) from 57 LMIC (Level 3) using the latest data from cross-sectional and nationally representative Demographic Health Survey conducted between 2010 and 2018. We used multivariable hierarchical Bayesian logistic regression models for data analysis. The overall prevalence of diarrhoea was 14.4% (95% confidence interval 14.2–14.7) ranging from 3.8% in Armenia to 31.4% in Yemen. The odds of diarrhoea was highest among male children, infants, having small birth weights, households in poorer wealth quintiles, children whose mothers had only primary education, and children who had no access to media. Children from neighbourhoods with high illiteracy [adjusted odds ratio (aOR) = 1.07, 95% credible interval (CrI) 1.04–1.10] rates were more likely to have diarrhoea. At the country-level, the odds of diarrhoea nearly doubled (aOR = 1.88, 95% CrI 1.23–2.83) and tripled (aOR = 2.66, 95% CrI 1.65–3.89) among children from countries with middle and lowest human development index respectively. Diarrhoea remains a major health challenge among under-five children in most LMIC. We identified diverse individual-level, community-level and national-level factors associated with the development of diarrhoea among under-five children in these countries and disentangled the associated contextual risk factors from the compositional risk factors. Our findings underscore the need to revitalize existing policies on child and maternal health and implement interventions to prevent diarrhoea at the individual-, community- and societal-levels. The current study showed how the drive to the attainment of SDGs 1, 2, 4, 6 and 10 will enhance the attainment of SDG 3.

scholarly journals Exploring the socio-economic determinants of educational inequalities in diarrhoea among under-five children in low- and middle-income countries: a Fairlie decomposition analysis

2021 ◽  
Vol 79 (1) ◽  
Author(s):  
Adeniyi Francis Fagbamigbe ◽  
Olukemi Grace Adebola ◽  
Natisha Dukhi ◽  
Omon Stellamaris Fagbamigbe ◽  
Olalekan A. Uthman
Keyword(s):  
Risk Factors ◽  
Household Wealth ◽  
Risk Difference ◽  
Demographic And Health Surveys ◽  
Educational Inequalities ◽  
Middle Income ◽  
Under Five ◽  
Under Five Children ◽  
Middle Income Countries ◽  
Low And Middle Income

Abstract Background What explains the underlying causes of educational inequalities in diarrhoea among under-five children in low- and middle-income countries (LMIC) is poorly exploited, operationalized, studied and understood. This paper aims to assess the magnitude of educational-related inequalities in the development of diarrhoea and decompose risk factors that contribute to these inequalities among under-five children (U5C) in LMIC. Methods Secondary data of 796,150 U5C from 63,378 neighbourhoods in 57 LMIC was pooled from the Demographic and Health Surveys (DHS) conducted between 2010 and 2019. The main determinate variable in this decomposition study was mothers’ literacy levels. Descriptive and inferential statistics comprising of bivariable analysis and binary logistic multivariable Fairlie decomposition techniques were employed at p = 0.05. Results Of the 57 countries, we found a statistically significant pro-illiterate odds ratio in 6 countries, 14 showed pro-literate inequality while the remaining 37 countries had no statistically significant educational-related inequality. The countries with pro-illiterate inequalities are Burundi (OR = 1.11; 95% CI: 1.01–1.21), Cameroon (OR = 1.84; 95% CI: 1.66–2.05), Egypt (OR = 1.26; 95% CI: 1.12–1.43), Ghana (OR = 1.24; 95% CI: 1.06–1.47), Nigeria (OR = 1.80; 95% CI: 1.68–1.93), and Togo (OR = 1.21; 95% CI: 1.06–1.38). Although there are variations in factors that contribute to pro-illiterate inequality across the 6 countries, the overall largest contributors to the inequality are household wealth status, maternal age, neighbourhood SES, birth order, toilet type, birth interval and place of residence. The widest pro-illiterate risk difference (RD) was in Cameroon (118.44/1000) while the pro-literate risk difference was widest in Albania (− 61.90/1000). Conclusions The study identified educational inequalities in the prevalence of diarrhoea in children with wide variations in magnitude and contributions of the risk factors to pro-illiterate inequalities. This suggests that diarrhoea prevention strategies is a must in the pro-illiterate inequality countries and should be extended to educated mothers as well, especially in the pro-educated countries. There is a need for further studies to examine the contributions of structural and compositional factors associated with pro-educated inequalities in the prevalence of diarrhoea among U5C in LMIC.

scholarly journals Decomposing the educational inequalities in the factors associated with severe acute malnutrition among under-five children in Low- and Middle-Income Countries

2020 ◽  
Author(s):  
Adeniyi Francis Fagbamigbe ◽  
Ngianga-Bakwin Kandala ◽  
Olalekan A. Uthman
Keyword(s):  
Socioeconomic Status ◽  
Maternal Age ◽  
Severe Acute Malnutrition ◽  
Acute Malnutrition ◽  
Educational Inequalities ◽  
Middle Income ◽  
Under Five ◽  
Under Five Children ◽  
Middle Income Countries ◽  
Individual Household

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, neighbourhood and national level 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 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<0.001), Chad(p<0.001), Comoro(p=0.047), Burkina Faso(p<0.001), Ethiopia(p<0.001), India(p<0.001), Kenya(p<0.001), Mozambique(p=0.012), Namibia(p=0.001), Nigeria(p<0.001), Pakistan(p<0.001), Senegal(p=0.003), Togo(p=0.013), and Timor Leste(p<0.001) had statistically significant pro-illiterate inequality while no country showed statistically significant pro-literate inequality. We found significant differences in SAM prevalence across child’s age (p<0.001), child’s sex(p<0.001), maternal age(p=0.001), household wealth quintile(p=0.001), mother’s access to media(p=0.001), birth weight(p<0.001) and neighbourhood socioeconomic status disadvantage(p<0.001). On the average, neighbourhood socioeconomic status disadvantage, location of residence were the most important factors in most countries. Other contributors to the explanation of educational inequalities are birth weight, maternal age and toilet type. Conclusions: SAM is prevalent in most LMIC with wide educational inequalities explained by individual, household and community-level factors. Promotion of women education should be strengthened as better education among women will close the gaps and reduce the burden of SAM generally. We recommend further studies of other determinate causes of inequalities in severe acute malnutrition in LMIC.

scholarly journals Decomposing the educational inequalities in the factors associated with severe acute malnutrition among under-five children in Low- and Middle-Income Countries

2020 ◽  
Author(s):  
Adeniyi Francis Fagbamigbe ◽  
Ngianga- Bakwin Kandala ◽  
Olalekan Uthman
Keyword(s):  
Socioeconomic Status ◽  
Maternal Age ◽  
Severe Acute Malnutrition ◽  
Acute Malnutrition ◽  
Educational Inequalities ◽  
Middle Income ◽  
Under Five ◽  
Under Five Children ◽  
Middle Income Countries ◽  
Individual Household

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, neighbourhood and national level characteristics in LMIC have 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 (DHS) 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: Mothers with no formal education ranged from 0.1 % in Armenia and Kyrgyz 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<0.001), Chad(p<0.001), Comoro(p=0.047), Burkina Faso(p<0.001), Ethiopia(p<0.001), India(p<0.001), Kenya(p<0.001), Mozambique(p=0.012), Namibia(p=0.001), Nigeria(p<0.001), Pakistan(p<0.001), Senegal(p=0.003), Togo(p=0.013), and Timor Leste(p<0.001) had statistically significant pro-illiterate inequality while no country showed statistically significant pro-literate inequality. We found significant differences in SAM prevalence across child’s age(p<0.001), child’s sex(p<0.001), maternal age(p=0.001), household wealth quintile(p=0.001), mother’s access to media(p=0.001), birth weight(p<0.001) and neighbourhood socioeconomic status disadvantage(p<0.001). On the average, neighbourhood socioeconomic status disadvantage, location of residence were the most important factors in most countries. Other contributors to the explanation of educational inequalities are birth weight, maternal age and toilet type. Conclusions: SAM is prevalent in most LMIC with wide educational inequalities explained by individual, household and community-level factors. Promotion of women education should be strengthened as better education among women will close the gaps and reduce the burden of SAM generally. We recommend further studies of other determinate causes of inequalities in severe acute malnutrition in LMIC.

scholarly journals Decomposing the educational inequalities in the factors associated with severe acute malnutrition among under-five children in Low- and Middle-Income Countries

2020 ◽  
Author(s):  
Adeniyi Francis Fagbamigbe ◽  
Ngianga-Bakwin Kandala ◽  
Olalekan A. Uthman
Keyword(s):  
Socioeconomic Status ◽  
Maternal Age ◽  
Severe Acute Malnutrition ◽  
Acute Malnutrition ◽  
Educational Inequalities ◽  
Middle Income ◽  
Under Five ◽  
Under Five Children ◽  
Middle Income Countries ◽  
Individual Household

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, neighbourhood and national level characteristics in LMIC have 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: Mothers with no formal education ranged from 0.1 % in Armenia and Kyrgyz 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<0.001), Chad(p<0.001), Comoro(p=0.047), Burkina Faso(p<0.001), Ethiopia(p<0.001), India(p<0.001), Kenya(p<0.001), Mozambique(p=0.012), Namibia(p=0.001), Nigeria(p<0.001), Pakistan(p<0.001), Senegal(p=0.003), Togo(p=0.013), and Timor Leste(p<0.001) had statistically significant pro-illiterate inequality while no country showed statistically significant pro-literate inequality. We found significant differences in SAM prevalence across child’s age(p<0.001), child’s sex(p<0.001), maternal age(p=0.001), household wealth quintile(p=0.001), mother’s access to media(p=0.001), birth weight(p<0.001) and neighbourhood socioeconomic status disadvantage(p<0.001). On the average, neighbourhood socioeconomic status disadvantage, location of residence were the most important factors in most countries. Other contributors to the explanation of educational inequalities are birth weight, maternal age and toilet type. Conclusions: SAM is prevalent in most LMIC with wide educational inequalities explained by individual, household and community-level factors. Promotion of women education should be strengthened as better education among women will close the gaps and reduce the burden of SAM generally. We recommend further studies of other determinate causes of inequalities in severe acute malnutrition in LMIC.

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