The determinant of National Vitamin A supplementation in Ethiopia: A Multilevel Logistic Regression Analysis

Background: Vitamin A deficiency is a public health problem in many low-income countries including Ethiopia. Globally, the prevalence of vitamin A deficiency is estimated to be 190 million among children under-five age causing one up to two million deaths annually.Its periodic supply is a major intervention program to reduce the morbidity, mortality, and blindness among the children in Ethiopia. Objective: The aim of this study was to determine associated factors of national vitamin A supplementationamong children aged 6-59 monthsusing the 2016 Ethiopian Demographic and Health Survey Data. Methods: A population based cross-sectional study design wasperformed to determine factors associated with the vitamin A supplyamong children aged between 6 and 59 monthswithin the last six months before the start of the survey. A univariateanalysis, bivariate analysis, binary logistic regression, and generalized linear mixed effect model were appliedto analyze the data. Results: After adjusting for covariates; the odds of taking vitamin A supply were 1.3 times, 1.7 times, and 1.8 times higher among the women who had two, three, and four and above antenatal care visits, respectively. The mothers’ employment status, health cheek up after their delivery,and theirhealth facility delivery were positively influence the uptake of the vitamin A capsule. In addition,women residing in the communities with high proportion of the media exposure[AOR (Adjusted Odds Ratio) = 1.17 (95%CI: 1.00, 1.37)]were positively associated with the receipt of vitamin A capsule.Random effects indicated that the variation on the uptake of vitamin A supplementation between the communities was statistically significant in all stage of the models. Conclusions: The individual and community level characteristics had a significant influence on the uptake of vitamin A supplementation. Therefore, these factors should be considered in policy formulation and programming in order to improve the coverage of vitamin A supplementation in Ethiopia.

universal vitamin A supplementation programs targeted to children age from six to fifty-nine months through semi-annual national campaigns [17]. Vitamin A supplementation programs began in the 1990's in response to evidence demonstrating the association between Vitamin A deficiency and increased childhood mortality [18,19]. After that, many related studies have concluded that Vitamin A supplementation can considerably reduce the mortality and the morbidity of the children in 6-59 months of age [20].
In Ethiopia, there has been a rise in nutrition interventions for children due to the investment in the health system [21]. In 2004, the enhanced outreach strategy started in four drought prone regions.
The mobile teams went from local to local in order to provide vitamin A capsule, deworming, and nutrition screening in twice-yearly campaigns. Malnourished children and lactating mothers were sent into the supplementary feeding programs [21]. Consequently, the whole country was considered for the vitamin A capsule during 2006. In this year, almost ten million children had been received vitamin A capsule. Then after, an important improvement had observed due to support of the UNICEF in all related matters [21,22]. In 2008, the pilot districts in the original four regions began to transit the package of nutrition interventions from the enhanced outreach strategy to community health days, with the aim of gradually integrating the activities into the routine health services [21,23]. The communities were mobilized to attend the campaign sites that arranged by each health post on specific days every three months to receive a package of the services, and every six months to receive vitamin A supplementation. The services were provided by outreach sites during the campaigns and through the house to-house visit in the urban areas [21,23]. In 2013, the community health day's program and the enhanced outreach strategy were fully transitioned into the routine services program.
Ethiopia has maintained the good coverage of supplementation throughout these changes. The Demographic and Health Survey (EDHS), the overall coverage of vitamin A supplementation in unser-5 children within the last six months was 46.8 % [2]. There was variation in coverage of Vitamin A uptake in subsequent years; in addition, there were a hidden variation at regional levels. For instance, the Tigray region has the highest coverage (65 %), whereas the Benishangul Gumuz region had around 25 %, the lowest coverage [2]. These disparities in the coverage of vitamin A supplementation indicated that there is a factor that determines the coverage of vitamin A supplementation beyond the individual level factors. The regional or community level factors have also an essential role in determining the coverage of vitamin A supplementation [1,25,26].
As evidence from previously published studies has shown, the uptake of vitamin A supplementation is influenced by the socio-economic, demographic, and geographical factors [1,2,21,[26][27][28][29]. Some of these principal factors include the maternal educational status, or the educational status of their husbands, the employment status of the mother, the place of the delivery of the child, the number of antenatal care visits, community poverty level, community media exposure, and community level maternal education [1,2,21,28,29].
This study has tried to address not only the effects of the individual and socio-economic factors on the uptake of vitamin A supplementation, but also the factors that operate at the community levels. The communities provide a localized context for the social, economic, and political structures relevant to the interplay between macro and individual level determinants of health and health outcomes [27].
The people with similar characteristics who live in different neighborhood may have different health status because the presence of economic, cultural, political or geographical variations. In other words, different people may have almost similar health status because they share a common environment [1,28]. According to the studies [29], the community level factors have a great influence in the child health and identifying these factors will allow the policy makers and the concerned bodies to prepare the community-level strategies and interventions.
Therefore, the aim of this study was to determine associated factors of national vitamin A supplementation in Ethiopia for the last six months before the 2016 EDHS. children aged from six up to fifty-nine months was included in the analysis.

Data source
A stratified, two-stage cluster sampling technique was used to identify representative samples. The sampling frame of the 2016 EDHS consists of a complete list of 84,915 enumeration areas. An enumeration area is a geographic area covering on average of 181 households. In the first stage, 645 enumeration areas (202 in urban areas and 443 in rural areas) were selected using probability proportional to each size of enumeration area and with independent selection in each sampling stratum. In the second stage, twenty-eight households per cluster were selected using systematic selection. The mothers either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed [30].

Study variables
The dependent variable is vitamin A supplementation. This outcome data were collect from mothers' direct verbal report, whether their children had taken vitamin A capsule [30].
Independent variables include individual level factors: The age of the mother, religion, ethnicity, marital status, the educational status of the mother, the educational status of the husband, the employment status of the mother and their husbands, the working status of the mother, place of the delivery, sex of the child, pregnancy wanted, the mothers health cheek after delivery, current age of the child, birth order, number of children live, and the number of antenatal care visits. And, the community level factors: the region, the place of residence, type of region of residence, community level poverty, community level education, and community media exposure. These variables were selected for the analysis in this study because they have been considered by the previous similar studies in the developing countries [1,2,31]. Some of the covariates were re-coded for suitable analysis. The aggregate community level covariates were found by aggregating individual level covariates at cluster level and its categorization was done as high or low based on proportion distribution values [31]. Histogram was used to check the distribution of the proportion values. If the aggregate variable was normally distributed, the mean value was considered, and if not normally distributed, median value was used as cut off point for categorization [31]. Therefore, the community poverty was categorized as high if the proportion of mothers from the two lowest wealth quintiles in a given community was 35-100 % and low if the proportion was 0-34 %. Community media exposure was classified as low if the proportion of the media exposure in the community was from 0-68 %, and as high if the proportion was from 69-100 %. Community education was classified as low if the proportion in the community with primary, secondary and above education was 0 %, and classified as high if the proportion was from 1-100 % [31]. These aggregations were performed because the variables are not directly available in the EDHS data set. This study adopted the classification method because the previous studies have analyzed the community-level variables in this way [1,31].

Data collection tools, techniques, and procedures
The data were collected through face-to-face interviews using a structured questionnaire. The questionnaire was first prepared in English, translated in to three different local languages. The trained interviewers collected the data under close supervision throughout the data collection process in order to ensure its quality [30].
Data processing and analysis 8 The data were checked for its completeness. The covariate that needed coding was coded and missing values were dealt before the actual analysis. The data were analyzed by the investigators using Version 14.0 Stata Statistical Software. The dependent variable vitamin A supply was coded as No = 0 and Yes =1. Univariate analysis was done to explain the frequency and percentage of the dependent and independent variables. In a bivariate analysis, cross tabulation was carried out to show the percentage of the vitamin A supply as changes in the categories of the explanatory variables and to describe the relationship between the variables using the crude odd ratio.
Multi-level logistic regression analysis technique was applied in order to consider the hierarchal nature of the data (two-stage cluster-sampling procedure) and the binary response of the dependent variable. Binary multilevel logistic regression analysis was applied to calculate the crude odds ratios at 95 % confidence interval and those covariates that were statistically significant were considered for individual and community level multivariate analysis. Multivariable multilevel logistic regression analysis (multivariate) was applied for individual and community level variables and those variables, which were statistically significant, were considered for the final model of multivariate analysis.
Multivariable multilevel logistic regression analysis was done to calculate the adjusted odds ratios and to estimate the extent of the random variations between the communities [31 -34]. In multivariate analysis, Variance Inflation Factor (VIF) was calculated to identify the extent of multi-collinearity of explanatory covariates using the average value of VIF, help to identify suitable covariates for multivariate analysis. As a rule of thumb, average VIF value is less than five can be tolerated [35][36][37][38].

Model building
Four models were fitted using the xtmelogit command. Model I, empty model, was fitted without independent covariates in order to test random variability of the intercept and to estimate the intraclass correlation coefficient (ICC). Model II fitted in order to see the effects of individual level covariates. Model III fitted to see the effect of community level covariates. Model IV examined the effects of both the individual and community level variables simultaneously. The individuals (the mother and child) were nested within the community was expressed elsewhere [31,32]. The chi square likelihood-ratio test was used to assess the difference between the models because the models were nested, the P-values were estimated using the wald statistics, tells about the model adequacy.

Parameter estimation methods
In the multilevel models, the fixed effects (measures of association) estimates the association between the likelihood of taking vitamin A capsule and the individual and community level factors.
These estimates were expressed as odds ratio with their 95 % confidence intervals. The random effects are the measures of variation in use of vitamin A supply across the communities. It was expressed as ICC and proportional change in variance (PCV). The ICC was calculated to evaluate whether the variation in vitamin A supplementation is primarily within or between communities [39, 40]. The ICC ranges from 0 to 1, with ICC of 1 indicating that mothers in the community have identical use of vitamin A supply for their children, and with ICC of 0 indicating that mothers in the community do not have identical use of vitamin A supply. A multilevel random intercept logistic regression models was used in the analysis. In addition, the mixed-effect logistic regression was used to determine extent of the variation in use of the vitamin A supply attributable to the individual and community-level characteristics. The mixed-effects logistic regression model consists of two parts, namely, the fixed effect and the random effect [37,38].
The model was specified as: logit (πij) = log (πij/1-πij) = β 0 + β 1 xij + β 2 x 2 ij + … + β 8 x 8 ij + β 9 z 1 j + β 10 z 2 j +…β 14 z 6 j + μ 0 j Where: πij is the log of the odds of using vitamin A supply for the mothers i in the cluster j; (1-πij) is the log of no-receiving; x and z are the explanatory variables for the likelihood of taking vitamin A; x 1 to x 8 are the individual-level variables; z 1 to z 6 are the community-level variables; β 0 is the overall intercept; β1-β14 are the regression coefficients for the explanatory variables x1 to x8, and z1 to z6; and u 0 j is the community-level random effect (assumed to be normally distributed with mean equal to 0 and variance equal to σ 2 μ 0 ). The ZjXij is added as a cross-level interaction term.

Ethical consideration
The researchers had received the survey data and an authorized approval letter from the Measure DHS site (Supplementary file 1).

Results
Socio-demographic characteristics of the respondents A total of 8,361 (after weighting of the data) children aged between 6 and 59 months were involved in the study analysis, based on the report of their mothers. Among the total mothers whose data were analyzed, 49 % were aged above 30 years, 41 % were Oromo in their ethnicity, and 40 % were Muslim in their religion. Further characteristics analyzed showed that 66.5 % of the respondents were no education, most of the women were married (99 %), and 55 % were unemployed. Among respondent's husband, 92 % were employees in their occupation and 48 % had no education in respect to their educational qualification (Table 1).
Based on the community level factors, more than three-fourths of the respondents were rural residents and about two-thirds of the respondents had low-level community education (Table 2).

Reproductive, maternal, and child health characteristics
Among the total mothers, whose data were analyzed, 37 % were no antenatal care visits, 90 % were their pregnancy wanted, 94 % were no postnatal health cheek ups or postnatal care visits, and 75 % were delivered at their home. About 29 % of children were found from 45-59 age groups (Table 1).

Binary multilevel logistic regression analysis
Bivariate multilevel logistic regression analysis was performed for individual and community level factors to select statistically significant variables for multivariate multi-level logistic regression analysis. Antenatal care visits, employment status of the mothers and their husbands, educational status of the mothers and their husbands, age of the mothers, ethnicity, the current working status of the mothers, place of delivery, and mother's health cheek after delivery were significant at 0.05 of individual level factors. In addition, place of residence, type of region of residence, community media exposure, community level poverty, and community level education were significant at community level variables (Table 3).

Multivariable multilevel logistic regression analysis
The fixed effects (measure of association) and the random intercepts for receiving vitamin A supplementation are presented in Table 4 and 5. The results of the model I depicted that there was a statistically significant variability in the odds of the receipt of vitamin A supplementation between communities (τ = 1.208, P-value <0.0001). Similarly, the ICC in the empty model implied that 26.9 % of the total variance in the receipt of vitamin A supplementation was attributed to differences between communities, or intra cluster or community factors are responsible for 26.9 % of variation in the uptake of vitamin A supplementation.
In model II, only significant individual level variables were added. The results showed that the age of the mothers, employment status of the mothers and their husbands, number of antenatal care visits, mother's health cheek after delivery, and place of delivery were significantly associated with the uptake of vitamin A supplementation. The ICC in Model II indicated that, 16.7 % of the variation in child's vitamin A supplementation uptake was attributable to the differences across the communities.
As shown by the PCV, 45.6 % of the variance in the uptake of vitamin A supplementation across communities was explained by the individual level characteristics.
In model III, only significant community level variables were added. The result revealed that those women residing in the communities with low poverty level, residing in the communities with high media exposure, and those women residing in the communities with high education level were significantly associated with the uptake of vitamin A supplementation. The ICC in Model III implied that differences between communities account for about 25.0 % of the variation in the uptake of vitamin A supplementation. In addition, the PCV indicated that 9.2 % of the variation in the uptake of vitamin A supplementation between communities was explained by community level characteristics.  In multivariate analysis, the fitness of the goodness of test was computed and it showed that the model is good fitted (Pearson χ 2 = 833.6; P value = 0.17). To cheek the presence of multi collinearity between variables, the VIF was computed and it revealed that the mean VIF value was 1.26. It showed that the explanatory variables were not multi-collinear as well as the variables were sufficient for adequate estimation of the regression coefficients. The Wald chi-square (χ 2 ) confirmed that all the fitted models were statistically significant at P value of less than 0.0001.

Discussion
This population-based study was employed to determine the factors associated with vitamin A supply in children aged 6-59 months based on Ethiopian Demographic and Health Survey data. Accordingly, the number of antenatal care visits, the employment status of the mother and their husbands, mother's health cheek after delivery, health facility delivery, and the community level media exposure were independently and significantly associated with the receipt of vitamin A supply in all stages of the model.
In this study, the mothers who had more than one antenatal care attendance were more likely to receive vitamin A capsule for their child as compared to the mothers who had no-antenatal care attendance. This finding is supported by similar study conducted in the Nigeria [1]. As the previous studies reported, attending antenatal care follow up during the pregnancy increases the chance of receiving vitamin A capsule, even mothers those who had at least one antenatal care visit for their recent birth had higher likelihood of receiving the vitamin A capsule compared to those mothers who had no antenatal care visits [1,31]. This can be explained with the idea that mothers with antenatal care follow up have a better chance of being familiar with maternal and child health services. As reported by the DHS based studies, the characteristics that predispose the mothers to seek pregnancy care also make them more likely to seek care during and after the delivery [1,41,42,43].
Attending antenatal care visits will make mothers to get information about post-delivery maternal and child health services, informed about pregnancy complications, and to be familiar with healthy maternal and child health practices during and after the delivery (exclusive breastfeeding, immunization, regular growth monitoring, birth preparedness plan which includes identification of health facility for delivery etc., for example). These will increase the likelihood of receiving maternal and child health services, particularly vitamin A supplementation [1,31,43,44]. In addition, attending antenatal care visits create an opportunity for health care workers to provide the relevant health information. This may be due to the health information given to the pregnant women during antenatal care visits is a vital to promote post-delivery health services like vitamin A supplementation. In similar manner, mother's health cheek after the delivery, and health facility delivery were significant predictors of the receipt of vitamin A supplementation. It is a platform where mothers and their children are given necessary health information in order to prevent ill health and adopts healthy practices. Thus, antenatal care attendance, health facility delivery, and postnatal health cheek up increase the likelihood of receiving the vitamin A capsule [1,43]. The employment status of the mothers and their husbands were independently and positively associated with the receipt of vitamin A supplementation. The working status of the mothers increases the chance of receiving vitamin A capsule for their child [1,2]. The possible explanation could be due to the information needed to access health care services were easily obtained from their colleagues; the employed parents were mostly educated, and it improves the use health services like vitamin A capsule uptake.
In this study, the mothers residing in the communities with high proportion of the media exposure were more likely to receive vitamin A capsule for their child compared to the women residing in the will influence and make them to utilize it more.
The findings of this study indicated that the community level random intercept, the community level variation, were large and statistically significant that indicating considerable differences between the communities in the odds of taking vitamin A capsule among the children of the mothers. This notion supports the use of multilevel modeling technique for the analysis of this study [31][32][33][34]39]. This study also indicated that the presence of significant unobserved variations between the communities beyond the influence of the measured individual and community level factors on vitamin A supply. This finding is in agreement with the previous African studies [31,41]. The unobserved effects might represent the differences among communities in terms of social norms and attitude, cultural beliefs, and quality of health services that influences the mothers to use these services.

Strength And Limitations Of The Study
This is a population-based study and based on the most recent Ethiopian Demographic and Health Survey with a nationally representative large sample size. This study has applied a multilevel modeling technique to accommodate the hierarchical nature of the EDHS data.
Despite the above strong sides, the study has the following limitations. The cross-sectional nature of the study does not allow making assumptions surrounding causal effects between the relationships.
Due to the presence of a few articles related with vitamin A supplementation that uses a multilevel modeling technique, we were restricted in some extent to compare and contrast deeply in discussion section.

Conclusions
In this study, both the individual and community level factors had significant influence on the uptake of the vitamin A capsule.
The factors like the number of antenatal care visits, employment status of the mother and their husbands, mother's health cheek after delivery, and health facility delivery were independently and significantly associated with on the uptake of vitamin A capsule at the individual level.
This study also showed that the communities in which the mothers reside play a significant role in shaping a mothers decision to receive vitamin A capsule for their children. Of this, the community level media exposure was positively and significantly associated with the uptake of vitamin A capsule at the community level. Therefore, the authors recommend that, special awareness creation about maternal and child health services through the means of the media should be given to the population. The government should strive also to expand access to media to remote areas of the country to promote health services. This will help them to develop appropriate knowledge towards vitamin A supplementation.
Further, it is also very important to give special emphasis for those communities who had home delivery, low health cheek up after delivery, and very low antenatal care visit attendance.

Declarations
Ethics approval and consent to participate "Not applicable".

Consent for publication
"Not applicable".

Availability of data and materials
The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests
The authors declare that they have no competing interests.

Funding
Funding for data collection and entry were provided by the authors. Any costs for the article covered by the authors.

Authors contributions
MO, SY, ZM, MM, and AM participated in conceptualization, formal analysis, investigation, methodology, supervision, visualization, writing-original draft, writing-review and editing, and approving the final draft. All authors read and approved the manuscript.
Science, Institute of Public Health, Department of Epidemiology and Biostatistics for their kind support during the entire process of the study.
for preventing morbidity and mortality in children from 6 months to 5 years of age.      Key: * statistically significant at P-value ≤ 0.05 in multi-level multivariable logistic regression analysis. AOR = Adjusted Odds Ratio.