Modeling Deficiency of Hemoglobin Severity Among Children in Ethiopia

Background: Anemia is a public health problem that affects populations worldwide. Anemia in children is a recognized public health problem that impacts adversely on child morbidity, mortality and impairs cognitive development. This study aimed to determine the prevalence of mild, moderate and severe anaemia, and the associated factors among children under-five years in EthiopiaMethod: The data was obtained from 2016 Ethiopia Demographic and Health Survey which is the fourth survey. The sample was selected using a stratified; two-stage cluster sampling design and the data was analyzed using Partial Proportional Odds model. Results: From 4684 sample of children half of the children (54%) have moderate anemic status while 39.4% and 6.6% of them have mild and severe anemic status respectively. The highest prevalence of anemia among children observed in Somali (17.8%) and the lowest percentage that was recorded in Addis Ababa (3.1%). Conclusion: The female children, rural children, children from poor family, and having low weight are related to the severity of anemia.


Source of Data and Study Design
The data was obtained from 2016 EDHS, which was taken from Central Statistical Agency (CSA). It is the fourth survey conducted in Ethiopia as part of the worldwide project. The 2016 EDHS sample was stratified and selected in two stages. Each region was stratified into urban and rural areas, yielding 21 sampling strata. Samples of Enumeration Areas (EAs) were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage of sampling. In this study a total of 4,684 underfive children affected by anaemia were considered from nine regional states and two city administratives [12].

Outcome variable
The outcome variable in this study was the level of anemia among children which is classified based on hemoglobin concentration and categorized as follows.

Method of Data Analysis
Based on the valid data obtained, we have performed a descriptive analysis using frequency distribution, percentage and chi-square test of association. To identify risk factors of anaemia amongst Ethiopian children Partial Proportional Odds model (PPOM) was used. PPOM can be used when parallel lines assumption holds or not. The maximum likelihood estimation technique was applied to estimate parameters of the model [13]. Data cleaning, management and analysis were carried out using STATA, Version 12. Variables were re-coded to meet the desired classification. All hypotheses testing to determine differences, associations and relationships were judged significant at p <0.05

Result
In this study a total of 4,684 under-five children affected by anemia were considered from nine regional states and two city administrative. The result in table 1 revealed that more than half of the children (54%) are at moderate while 39.4% and 6.6% of them are at mild and severe anemic status respectively. The size of each level of anaemia by different socio-demographic factors with their corresponding chi-square test of association had been presented in table 1. More than half of the children (51.9%) were female and the remaining 48.1% are male. The result also showed that about 55.1% of female children are moderately anaemic while 36.6% and 6.7% of them are at mild and severe anaemic status respectively. Among male children about 40.6%, 52.8% and 6.6% of them are mild, moderate and severe anaemic status respectively. Majority of the anaemia prevalence (84.6%) was from rural part of Ethiopia of which 54.4% and 7.1% were moderate and severe anaemic status respectively. According to age of the child, the highest percentage (27%) and the smallest percentage (15.2%) were 12-23 months and 6-11 months respectively. About 9% of 24-35 months of age children are at severe anaemic status while 61.3% of 12-23 months old child were at moderate level. About 52% of mild anaemia is observed among 48-59 months old children.
More than half of anaemic children (60.2%) were from poor families while 13% and 26.8% of anaemic children were from middle and rich families. About 35.4%, 56% and 8.6% of anaemic children from poor families were at mild, moderate and severe anaemic status respectively. According to regional states of the country, the highest severe anaemia is found in Somalia region which is estimated to be 14.5% followed by Dire Dawa and Harari with 14.2% and 7.3% respectively. In addition, 5.9%, 5.1% and 4.8% of anaemic children from Afar, Oromia and Amhara are at severe anaemic level respectively.
The association between predictor variables and anemia status of children was identified by conducting chisquare test of association from table 1 we conclude that there is association between wealth index, region, breast mother education and residence with prevalence anemia among children in Ethiopia.

Linear Trend Alternative to Independence for Some Selected Variables
By using equal space score method, from table 2 the result implied that there is a linear dependence between mother education and status of anemia at 5% significance level since p-value (0.038<0.05) similarly, there is a linear dependence between residence, weight and status of anemia since p-value (0.001<0.05).

Results of PPOM
Parallel-lines assumption for each variable was tested using a series of Wald tests to see whether its coefficients differ across equations. Since the parallel-lines assumption has been violated by some of explanatory variable ordinal logistic regression cannot be used. Therefore, PPOM was used and the result was showed in table 3 below. The coefficients for wealth index are consistently negative but decline across cut-points. This means that children were their wealth index was poor more affected by anemia than the children's whose their wealth index were middle and rich, with the greatest differences being the children poor were less likely to put themselves in moderate and severe categories. Conversely, the age group effect is negative but gets larger across cut points. Hence, higher age group tend to be less anemic than lower age group with the greatest differences being that higher age group are less likely to place in put themselves moderate and severe categories.
Sex, the odds of having higher chance of moderate and severe anemia for male children is 14% less likely than female children when it is compared with Mild anemia. Likewise, the odds of having higher chance of severe anemia for male children 14% less likely than female children when it is compared with Mild and moderate anemia.
Residence, we would say that for residence going from urban to rural the odds of severe anemia versus the combined moderate and mild anemia categories are 1.473 greater, given that all of the other variables in the model are held constant. Likewise, the odds of the combined moderate and severe anemia versus mild anemia are 1.473 times greater, given that all of the other variables in the model are held constant, indicate that severity of anemia is in rural than in urban area.
Regions, when the region of children are Afar, Oromia, Somali, Harari and Addis Ababa, the odds of mild anemia versus the combined moderate and severe anemia categories are 1.37, 1.39, 3.963, 2.11 and 2.011 greater respectively, given that all of the other variables in the model are held constant respectively, indicate that in those region the prevalence of anemia is high, but for Benishangul-Gumuz odds of mild anemia versus the combined moderate and severe anemia is 0.638 less likely Tigray region, given that all of the other variables in the model are held constant, indicate that the prevalence of anemia is low. However, for Dire Dawa, the odd of moderate and severe anemia versus mild anemia is twice of the odds of mild anemia versus the combined moderate and severe anemia given that all of the other variables in the model are held constant.

Discussion
In this study, we were attempts to investigate the prevalence of anemia in Ethiopia and identify the associated factors of children aged under-five. The prevalence of anemia in Ethiopia was found to be (54%) are at moderate while 39.4% and 6.6% of them are at mild and severe anemic status respectively. The prevalence of anemia in Ethiopia is high when we compared with finding conducted in Togo of which 42.7% had moderate, 25.6% had mild anemia, anemia and 2.6% had severe anemia [14].
Higher age group tends to be less anemic than Lower age group in line with the findings done in Kenya and West Africa [15][16][17]. On the other hand, our findings show that children with lower age groups had a higher chance of severing anemic and the result is consistent with the previous study conducted in some countries like Nepal, rural India and Brazil [18][19][20][21]. This is might be due to the Hemoglobin concentration had undeviating and a progressive association with age. The reason behind this could be the fact that as age get increased; an insistent dietary nutrient for growth relatively becomes lower than an early age.
Regarding Weight of children, the PPOM shows that as Weight of children is increased the odds of Mild anemia vs moderate and severe anemia, as well as the odds Mild and moderate anemia vs severe anemia is 1% less likely times. This finding was agreed with studies conducted in Punjab India, Tanzania, Kenya and Nigeria [22][23][24][25][26]. In case this may be due to Undernourishment and insufficient dietary maybe leads to iron deficiency which is one of the major associated factors of anemia [27][28][29]. The study revealed that children whose theirs residence is rural are more likely affected by anemia compared to the children whose theirs residence is urban by the prevalence of anemia that consistent with other studies [6,30]. They indicated that better access to food and quality diet in urban, better access to medical care.
Our study also revealed that the chance of having severe anemia status was found to decrease with the increase of household wealth index, or under-five children from poor households are at a higher risk of prevalence of anemia than children from rich households. This finding is consistent with other studies [30].They indicated that better access to food and higher cash incomes than poor households, allowing them quality diet, better access to medical care and more money to spend on essential nonfood items such as schooling, clothing and hygiene products.

Conclusion
From 4684 sample of children half of the children (54%) have moderate anemic status while 39.4% and 6.6% of them have mild and severe anemic status respectively. The highest prevalence of anemia among children observed in Somali (17.8%) and the lowest percentage that was recorded in Addis Ababa (3.1%). Emphasis should be given for female children, rural children, children from poor family, and children having low weight.

List of abbreviations CSA:
Central Statistical Agency EAs: Enumeration Areas EDHS: Ethiopian Demographic and Health Survey OR: Odds Ratio PPOM: Partial Proportional Odds Model WHO: World Health Organization

Declarations Ethics approval and consent to participate
Ethics approval and participant consent were not necessary as this study involved the use of a previously-published database by CSA of Ethiopia.

Availability of data and material
The dataset was demanded and retrieved from CSA website after formal online registration and submission of the project title and detail project description