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Background: Despite progress made to improve access to child health services, mothers’ consistent utilization of these services has been constrained by several factors. This study is aimed at assessing the inequalities in key child health service utilization and assess the role of antenatal care (ANC) on subsequent service use. Method: The analysis of the present study was based on the Ethiopian Demographic and Health Surveys, a nationally representative sample of 10,641 children. A health service utilization score was constructed from the affirmative responses of six key child health interventions associated with the most recent birth: ANC service, delivery of the last child at health facilities, postnatal care services, vitamin A intake, iron supplementation and intake of deworming pills by the index child. A mixed effect Poisson regression model was used to examine the predictors of health service utilization and three separate mixed effect logistic regression models for assessing the role of ANC for continued use of delivery and postnatal care services. Results: The results of mixed effect Poisson regression indicate that the expected mean score of health service utilization was lower among non-first birth order children, older and high parity women, those living in polygamous families and women living in households with no access to radio. The score was higher for respondents with better education, women who had previous experience of terminated pregnancy, residing in more affluent households, and women with experiences of mild to high intimate partner violence. Further analysis of the three key health services (ANC, delivery, and postnatal care), using three models of mixed effect logistic regression, indicates consistent positive impacts of ANC on the continuum of utilizing delivery and postnatal care services. ANC had the strongest effects on both institutional delivery and postnatal care service utilization. Conclusion: The findings implicated that maternal and child health services appear as continuum actions/behavior where utilization of one affects the likelihood of the next service types. The study indicated that promoting proper ANC services is very beneficial in increasing the likelihood of mothers utilizing subsequent services such as delivery and postnatal care services.
Ethiopia is the second-most populous nation in Africa with an estimated population of 109 million people [18]. Children (0–14 years) account for about 40% of the total population of the country [19]. Administratively, the country is divided into nine regions and two autonomous cities. The country has an agrarian economy, where agriculture accounts for more than 60% of the GDP and employs nearly 85% of the population[16]. According to World Bank estimates, Ethiopian economy was the third-fastest growing among those having 10 million or more population in the world (for the period 2000 to 2018), as measured by GDP per capita [20]. However, nearly a third of its population still lives below the poverty line and two-thirds have no education and limited access to health care services [21]. Despite remarkable improvements in child survival rates, both infant and child mortality rates are one of the highest in Sub-Saharan African countries [15]. Ethiopian national health policy emphasizes health care decentralization and prioritization of health promotion, disease prevention and basic curative services[22]. At the micro-level, the Essential Health Service Package (EHSP) has been used to guide service provision with a clear stratification of service delivery and financial arrangements [22]. The Ethiopian health system is a four-tier health care system, which is organized into Primary Health Care Units (PHCUs), District Hospitals, General Hospitals and Specialized Hospitals [23, 24]. Under each PHCU, there are five satellite Health Posts, each post serving approximately 5000 people. The PHC provides essential health care usually free for people living in rural areas [23, 24]. Health Extension Workers (HEW), deployed to each health post, are mandated to provide antenatal care, administer vaccines, conduct normal and safe deliveries, conduct monitoring of growth, provide nutrition counseling, offer family planning services, and organize referrals for services, hygiene and environmental sanitation, and health education and Communication [23, 24]. The EDHS of 2016 collected health-related information from women of reproductive ages 15–49 [15]. It is a cross-sectional household survey which employed a stratified two-stage cluster sample design. For the present analysis, the recoded data file of the EDHS, which contains entries for 10,641 respondents who had children under five years of age, was used. The EDHS data were collected from 645 enumeration areas (EA’s). The data file contains household and women’s characteristics, as well as child health information for the most recent birth. For the present analysis, only those who had the most recent birth (within three years prior to the survey date) were considered. Permission to use the data for the purposes of the present study was granted by ICF international (U.S.) and Central Statistics Authority (Ethiopia) (http://dhsprogram.com/data/Access‐Instructions’). Ethical approval was also received by the University of Saskatchewan Behavioral Research Ethics Board. For the regression analysis, four outcome variables were used. The first outcome was the child health service utilization score, which was constructed from the affirmative responses of six key child health interventions associated with the most recent birth: (1) ANC service (> 4 visits), (2) delivery of the last child at health facilities, (3) postnatal care services, (4) vitamin A intake, (5) iron supplementation and (6) intake of deworming by the index child. This outcome variable thus took a count form ranging from 0 to 6; taking a value of ‘0’ if the mothers’ response to the six indicators is “no,” and 6 if mothers respond ‘yes’ to all the six indicators. The three key health services (ANC, delivery, and postnatal care) were also used as separate outcome variables of their own to assess the likelihood of institutional delivery and postnatal care. Health service utilization behavior is thought to depend on a set of individual, parental, household, and community-level characteristics. Thus, the exposure variables in the current analysis were categorized into three major groups: maternal and child factors (which includes, birth order, mothers’ education, age, work status, mother’s level of exposure to intimate partners violence, ever experienced pregnancy termination, parity, access to information/radio), household factors (which include non-monetary wealth index, religion, and type of family structure) and community variables (residence and type of region). The type of region was constructed based on clustering/grouping of the 11 regions based on their urbanization level and categorized as highly urbanized (Addis Ababa, Dire Dawa andHarari), medium-level urbanization (Tigray, Amhara, Oromia, SNNP, Gambella) and least urbanized (Afar, Benishangul Gumuz and Somali). Most of the background variables (child’s sex, age, parental education, type of family structure, parity) were used the way they were coded in the original data. DHS constructed wealth index from selected key household assets and other characteristics that relate to economic status [25]. Intimate partner violence (IPV) was constructed from a set of dichotomous responses on a mother’s exposure to violence during a reference period of 12 months. The EDHS data are clustered (i.e., individuals are nested within households, and households are nested within the 645 enumeration areas/EAs) [25]. It is thus expected that mothers within the same cluster may have similarity. This violates the assumption of independence of observations across the clusters and, hence, limits the use of conventional regression as an outcome may be measured more than once on the same person [26]. Thus, a mixed effects regression was used. For the present analysis, the enumeration areas/EAs were used as clustering women respondents. mixed effects models are useful with data that have more than one source of random variability [26]. In this analysis, level one represents the individual (children characteristics), whereas level two is the cluster (community characteristics). Data were analyzed using STATA version 12 [27]. Two sets of analyses were conducted. In the primary analysis, a mixed effect Poisson regression model was used to assess the determinants of service utilization score, which takes a form of count/rate, and skewed to the right (Fig. 1). In the secondary analysis, mixed effect logistic regression was used to assess the role of ANC in subsequent service utilization. The analysis began with checking if there was any multicollinearity between the explanatory variables using tolerance test/variance inflation factors (VIF). Using the routine Collin in Stata, a VIF > 10 or mean VIF > 6 represents severe multicollinearity [28]. Then, the bivariate association between child health service utilization and each potential predictor was examined. All predictors statistically associated with a p value of < 0.2 at bivariate level were subsequently included in the multivariable regression models. The model selection criterion was the Akaike Information Criterion (AIC), and the level of statistical error was set to be 5%. In the final model, we used a p value of < 0.05 to define statistical significance. The ratio of Deviance and Degree of Freedom (Deviance/DF) was used to test the model fitness [29]. The fitness of the model was also compared with a negative binomial regression model using AIC values and dispersion scores. Distribution of the outcome variable: health service utilization scores, Ethiopia Further analysis of the continuum adherence to the health care service utilization was carried out using a mixed effect logistic regression model. The model hierarchically builds three separate models; model 1 contained predictors of ANC, model 2 adds ANC as a factor of the place of delivery, and model 3 included ANC and delivery place as key factors of postnatal care service utilization. All the analyses were weighted using the weight variable given by EDHS.
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