Page 55 - IJPS-7-2

International Journal of
Population Studies Child mortality by residence in Ethiopia

child mortality at different levels. For example, in child mortality using the Demographic and Health Survey
South Asia, Zakaria et al. (2019) examined the effects (DHS) in 35 SSA countries. The data were analyzed using
of socioeconomic, demographic, and environmental Oaxaca-Blinder decomposition to depict urban-rural
variables on child mortality, and found that urbanization gap in the factors of under-five mortality. The results of
reduce child mortality. In South-Central Asia, Dendup the decomposition analysis revealed that the urban-rural
et al. (2020) investigated the factors associated with child differentials were due to demographic, socioeconomic,
mortality in rural and urban Bhutan and the roles of the and proximate factors. Yaya et al. (2019) also explored
factors in explaining child mortality disparities using the that very young age at first birth, children of higher birth
2012 National Health Survey. Logistic regression models order, and those with small size at birth had a higher risk
were applied to investigate the determinants and the of child mortality. Children from the richest households
analysis revealed that children of younger mothers born and births from educated women had a lower risk of
in households without safe sanitation and electricity had under-five mortality. Maternal age, maternal education,
increased odds of childhood mortality in the rural areas wealth index, total children ever born, and size of child
of the country. Larger number of births and smaller at birth had contributed toward explaining urban-rural
household sizes are associated with an increased odd of gap in child mortality (Yaya et al., 2019). In Nigeria, a
mortality irrespective of rural-urban residence (Dendup study conducted by Adeyinka et al. (2020) highlighted
et al., 2020). that children residing in different communities are likely
In Bangladesh, Rahman & Alam (2021) examined the to have different mortality risks. The study employed
role of socioeconomic indicators on child mortality and a multilevel multinomial logistic regression analysis
found that urbanization had a positive effect on child method to identify the social determinants of age-specific
mortality; whereas maternal education hurt child mortality childhood mortalities and to estimate the within- and
rate. Noor & Udddin (2021) also found out that mother’s between-community variations of mortality among under-
education, higher birth order, and size of child at birth five children. The multilevel analysis revealed that maternal
had a significant effect on child mortality in Bangladesh. education and household wealth index accounted for high
Jayathilaka et al. (2021) explored socioeconomic and variation in childhood mortalities across communities
demographic factors associated with child mortality in (Adeyinka et al., 2020).
Sri Lanka, and the improved source of drinking water had Despite the widely acknowledged rural-urban
a lower risk of child mortality. In Afghanistan, place of differential in child mortality, not all urban or all rural
residence, wealth index, age at first birth, and household populations are homogenous. Living in socioeconomically
size were found to be key determinants of child mortality disadvantaged urban areas might be associated with
(Shonazarova & Eshchanov, 2020). In Ghana, maternal increased child mortality risks, as living in resource-
age, mother’s education, household wealth index, place of rich and environmentally healthy rural areas might be
delivery, and birth order are found to be the most significant
socioeconomic determinants that influence child mortality associated with a lower risk of child mortality. In this
in rural-urban Ghana (Sarkodie, 2021). regard, a few studies documented intra-urban differentials
in child mortality in the developing countries (Antai &
In Ethiopia, Zewudie et al. (2020) examined determinants Moradi, 2010; Das, 2021; Touré et al., 2020). For example,
of child mortality and found that place of residence, a study in Nigeria found that urban-area disadvantage
mother’s educational level, religion, breastfeeding status, sex was independently associated with the risk of child death
of the child, birth order, and household size were found to even after controlling for individual child- and mother-
be significant predictors of child mortality. Likewise, Fenta level demographic and socioeconomic characteristics
and Fenta (2020) in their study examined that individual- (Antai & Moradi, 2010). A study in Ghana also examined
level factors, including maternal educational background intra-urban spatial variation in child mortality rates and
and age of the mother at first birth, are associated with the pointed out that non-traditional toilet types and water
small number of child death. On the other hand, higher supply sources are associated with high rates of under-five
birth order is associated with a higher number of child mortality rates (Touré et al., 2020). In India, Das (2021)
death (Fenta & Fenta, 2020). showed that poverty, low female literacy, and unsafe
More specifically, a few recent studies explored factors delivery in the community are associated with a higher
that determine child mortality including rural-urban risk of child mortality in urban areas. The economic
inequalities (Adeyinka et al., 2020; Dendup et al., 2020; inequalities in child mortality are higher in urban poor
Gebresilassie et al., 2021; Yaya et al., 2019). In Sub-Saharan than in rural but inequality is widened in urban poor in
Africa, Yaya et al. (2019) examined the rural-urban gap in India (Das, 2021).

Volume 7 Issue 2 (2021) 49 https://doi.org/10.36922/ijps.v7i2.392