Modeling non-Gaussian data analysis on determinants of underweight among under five children in rural Ethiopia: Ethiopian demographic and health survey 2016 evidences

Abstract

Background Childhood under-nutrition is a major global health problem. Although the rate of under-nutrition in Ethiopia has declined in the last decade, but it still remains being the major causes of morbidity and mortality of children under-five years. The problem is even worse in rural areas. The prevalence of underweight among rural children was 25% compared with 13% among urban children. To alleviate this problem, it is necessary to determine the magnitude and determinants of underweight. The study models non-Gaussian data analysis to identify risk factors associated with underweight among under-five children in rural Ethiopia. Methodology The data source for this study was secondary data, which was retrieved from EDHS 2016 database. It was analyzed using two model families; one with marginal models (GEE and ALR) in which responses are modeled and marginalized overall other responses, and the other is random effects model (GLMM) which is useful when the interest of the analyst lies in the individual’s response profiles as well as to evaluate within and between regional variations of underweight. Result From fitting non-Gaussian data analysis to identify risk factors associated with underweight among under five children in rural Ethiopia, the independent variable which have significant effect on underweight were:—Age of child, birth interval, mothers education, fathers education, wealth index, diarrhea in last two weeks, fever in last two weeks are significant and also father’s work status shows that difference in significance among the category. Conclusion Child age, preceding birth interval, mother’s education, household’s wealth index, fever, diarrhea, father’s education and father’s work status were associated with child underweight. Furthermore, there is both within and between regional heterogeneity of underweight among children in rural Ethiopia. Therefore, rigorous community-based interventions (such as uplifting mother’s education by providing formal education and preventing infectious diseases that cause diarrhea and fever) should be developed and executed throughout the country to improve this grave situation of underweight prevalence in rural areas of Ethiopia.

The Socio-economic, Demographic, and Contextual Predictors of Malnutrition among Children aged 6-59 months in Nigeria

“…The same ndings were reported in previous studies on malnutrition [17][18][19][20][21][22][23][24][25][26][27][28][29][30], The risks of children aged 24-35 months cohabiting malnutrition were 2.22 times higher than those of children aged 6-11 months. Similar conclusions were reached in previous studies that an increase in the age of the children has a harmful effect on poor nourishment for the children [31][32][33][34][35][36][37][38][39][40][41][42][43]. The possible explanation for this difference is that as the child grows older, less attention is paid to their welfare compared with the youngest child.…”

“…Also, children who had diarrhoea two weeks before the survey, were more likely to be poorly nourished than children who did not have the illnesses. This nding is supported by previous studies [32,33,[43][44][45][46]. Similarly, children of workingclass mothers are more likely to be poorly nourished than children whose mothers do not work.…”

“…Other studies substantiated the result on maternal education [31-34, 36, 38-40, 42, 44-46, 48-52], and for paternal educational attainment was supported in [33,39,51]. The results also show that the richer the household, the less likely the children from such a home will be poorly nourished compared with their counterparts from the poorest household.…”

Socio-economic, demographic, and contextual predictors of malnutrition among children aged 6–59 months in Nigeria

“…The odds of being poorly nourished are inversely proportional to the educational status that mothers and fathers have obtained. Other studies substantiated the result on maternal education [ 31 – 34 , 36 , 38 – 40 , 42 , 44 – 46 , 48 – 52 ], and for paternal educational attainment was supported in [ 33 , 39 , 51 ]. The results also show that the richer the household, the less likely the children from such a home will be poorly nourished compared with their counterparts from the poorest household.…”

Determinants of undernutrition among young children in Ethiopia

“…Similarly, different studies have elicited the predictors of wasting in children, such as sex of the child 27 , 35 , birth size 36 , cough 27 , fever 37 , maternal BMI 36 , maternal education 27 , 38 , diarrheal morbidity 35 , 38 , 39 , complementary food starting before 6 months 38 , and unimproved drinking water 40 . Furthermore, sex of the child 41 , 42 , child age 42 , 43 , diarrheal morbidity in the last two weeks 41 – 43 , paternal education 41 , 43 , preceding birth interval 43 , birth order 42 , type of birth 42 , maternal body mass index 42 , birth size of child 42 , duration of breastfeeding 42 , and wealth index 42 , 43 had a significant effect on underweight.…”