Page 56 - IJPS-7-2

International Journal of
Population Studies Child mortality by residence in Ethiopia

In Ethiopia, Gebresilassie et al. (2021) examined the of 10,641 under-five children born during the past 5 years
factors behind the rural-urban differentials in under- preceding the survey date were included in the children’s
five mortality using Fairlie’s decomposition technique to database. Of these, 8162 children (12 – 59 months of age)
analyze data from the three-round of the Ethiopian DHSs. data were extracted from the children’s dataset for this
The child size at birth, mother’s education, and household study.
size contributed to narrowing the disparity in child
mortality rate (Gebresilassie et al., 2021). 2.2. Study variables
To sum up, although the previous studies (Dendup The outcome variable of the present study was the risk of
et al., 2020; Ekholuenetale et al., 2020; Yaya et al., 2019), child mortality. The outcome variable was measured in
including the study conducted in Ethiopia (Gebresilassie EDHS as the probability of dying between the exact age
th
et al., 2021), have examined the rural-urban inequalities of 1 and the 5 birthday, and assigned a value of 1 if the
in child mortality risks, the determinants contributing to child died between 12 and 59 months, and 0 if the child
intra-rural and intra-urban inequalities in child mortality was alive at least until the age of 59 months. To explore
were not covered. On the other hand, a few studies the effects of individual, household, and community level
(Antai & Moradi, 2010; Das, 2021; Touré et al., 2020) characteristics on child mortality and to examine their
assessed only intra-urban differentials in child mortality influences and relationships between rural-urban effects,
in the developing countries. However, the determinants the explanatory variables were grouped into individual,
contributing to intra-rural and intra-urban inequalities in household, and community-level factors.
child mortality have not been previously well documented The individual-level factors included in this paper
in Ethiopia. Therefore, this paper seeks to contribute are as follows: Sex of child; child size at birth as reported
evidence on the major factors explaining the rural-urban subjectively by mother; breastfeeding initiation; birth
inequalities in child mortality, including the intra-rural order; place of delivery; maternal education; maternal age
and intra-urban gap in Ethiopia. at first birth; number of children ever born; and mother’s

2. Data and methods religion. Please refer to the detailed categories in Table 1.
The household-level factors comprise of sex of household
This section highlights the data sources, study variables, head; household size; source of drinking water; type of toilet
and statistical methods used for the present study. Study facility; type of cooking fuel; and combined wealth status.
context and design and data sources are presented under In 2016 EDHS dataset, the urban/rural asset scores are
data source subsection. Description of study variables is standardized in relation to a standard normal distribution
explained under study variable subsection while the overall with a mean of zero and a standard deviation of one.
data diagnosis and analysis techniques are discussed in Finally, the standardized urban/rural wealth index scores
statistical methods subsection.
of the poorest, poorer, middle, richer, and richest levels
2.1. Data sources are further regrouped into poor and non-poor for the
analysis of intra-urban and intra-rural inequalities in child
We used data from the 2016 Ethiopia DHS (EDHS) which mortality.
was collected from January 18, 2016, to June 27, 2016
(Central Statistical Agency [CSA] [Ethiopia] and ICF, The community-level factors consist of administrative
2016). The 2016 EDHS is a large-scale and cross-sectional regions and place of residence (urban vs. rural). For the
survey conducted in a nationally representative sample of sake of simplicity, the 11 administrative regions of Ethiopia
households from all regions of Ethiopia. Ethiopia is the are categorized into three regional categories: Emerging
second most populous country in Africa, after Nigeria regions (Afar, Somali, Benishangul-Gumuz, and Gambella),
and characterized by enormous diversity (FMOH-FDRE, developed regions (Amhara, Oromia, Harari, Southern
2016). The EDHS 2016 data were collected based on a Nations Nationalities, and People’s Region [SNNPR], and
two-stage stratified cluster sampling technique. In the first Tigray) and fully urban (Addis Ababa and Dire Dawa
stage, 645 clusters (202 urban and 443 rural) were selected. City Administrations). Here, it is good to note that the
In the second stage, a fixed number of 28 households emerging regions are drought-affected areas, pastoralists,
per cluster were selected to gather the socioeconomic and marginalized in terms of basic infrastructure as well
and health status of children below the age of 5 and their as least developed as compared to developed and urban
mothers of reproductive ages (15 – 49 years). The 2016 regional categories (Bareke et al., 2022). Moreover, to
EDHS used standardized questionnaires to collect detailed analyze the child mortality inequality gaps between and
information on birth histories, health, nutrition, and related within rural-urban, the place of residence was assigned as
information on mothers and children. Accordingly, a total a dummy variable.

Volume 7 Issue 2 (2021) 50 https://doi.org/10.36922/ijps.v7i2.392