Page 54 - IJPS-7-2

International Journal of
Population Studies Child mortality by residence in Ethiopia

Department of International Economic and Social inequality in child mortality can be explained by the
Affairs, 1985). The 1994 International Conference on individual, household, and community-level factors. The
Population and Development also urged governments to different approaches employed by various governments
reduce child mortality inequalities between and within may make community-level factors influence under-five
developed and developing countries by promoting child mortality differently. Therefore, this study attempts to
health and survival, and eliminating preventable mortality answer the research question “What are the key factors that
among children (United Nations, 1995). Moreover, the explain the rural-urban, intra-rural, and intra-urban gaps
United Nations had set a Millennium Development Goal in child mortality in Ethiopia?” Answering this question is
(MDG4) to reduce the child mortality rate by two-thirds instrumental to explain the inequalities in child mortality
between 1990 and 2015 (UNICEF, 2015). Although MDG4 between and within urban-rural areas. Thus, the objective
was targeted to reduce the under-five mortality rate of this paper was to examine the key factors that explain
(U5MR) by 67%, the target was not achieved and reduced both between and within rural-urban inequalities in child
by 53% reduction reached globally (United Nations mortality in Ethiopia.
Inter-agency Group for Child Mortality Estimation [UN
IGME], 2020), from 91 deaths/1000 live births in 1990 to 1.2. Theoretical framework
43 deaths/1000 live births in 2015 (UNDP, 2016). Apart This study is based on the two theoretical frameworks
from the low reduction, there are inequalities across formulated to identify determinant factors and their
regions and countries. relationships on child survival (Mosley & Chen, 1984;
Due to different efforts exerted by governments and Schultz, 1984). Schultz (1984) is one of the pioneering
development partners, the number of under-five deaths researchers who developed the theoretical framework on
dropped from 12.5 million in 1990 to 5.2 million in child survival. Schultz’s theoretical framework focused on
2019 globally. As a result, 14,000 children died before the structural relationship between child survival and the
age 5 every day in 2019 compared to 34,000 in 1990 and individual’s behavioral variables along with both observed
27,000 in 2000 (United Nations Inter-agency Group for socioeconomic (such as social, economic, community,
Child Mortality Estimation [UN IGME], 2020). Despite and religious) and biomedical (breastfeeding patterns and
the progress in child mortality, the 2019 figure is still hygiene), and unobserved biological factors. In Schultz’s
large and alarming to the Sustainable Development Goal framework, biomedical factors are modeled as having
(SDG) targets and efforts to eliminate preventable child direct effect on child mortality, while socioeconomic factors
deaths between birth and age 5. In this regard, the SDG affect child survival indirectly as they work through the
aims to reduce the under-five mortality rate to at least as biomedical factors (Schultz, 1984). Likewise, Mosley and
low as 25 deaths/1000 live births by 2030 (WHO, 2015). Chen (1984) classified the determinants of child survival as
However, Sub-Saharan Africa (SSA) remains the region socioeconomic (such as social, economic, community, and
with the highest under-five mortality rate in the world regional determinants) and biomedical factors (such as
(United Nations Inter-agency Group for Child Mortality maternal, environmental, nutrition, injuries, and personal
Estimation [UN IGME], 2020). In 2019, the region had an illness). In Mosley and Chen’s framework, socioeconomic
average under-five mortality rate of 76 deaths/1000 live factors are proposed to indirectly affect child survival as
births, which was 20 times higher than that of the region of they pass through the proximate factors while proximate
Australia and New Zealand (United Nations Inter-agency determinants affect child mortality directly (Mosley & Chen,
Group for Child Mortality Estimation [UN IGME], 2020). 1984). Mosley and Chen categorized a set of proximate
Moreover, the SSA countries had high child mortality rates determinants into maternal factors (age, birth order, and
with significant urban-rural differences (Yaya et al., 2019). birth intervals); environmental hygiene factors (source of
water and type of sanitations); nutrient deficiency (calories,
Ethiopia is one of the Sub-Saharan Africa countries
with high burden of child mortality, ranking third in protein, and micronutrient deficiency); injury (related to
physical, burn, and poisoning injury); and personal illness
Africa (Dheresa et al., 2022). Ethiopia was among the five control (immunization, bed net, etc.). In addition, Mosley
countries which account for half of the global under-five and Chen also classified the socioeconomic determinants
deaths in 2019 (UN IGME, 2020). The child mortality of child survival into individual-, household-, and
was declined by 76% from 96 deaths/1000 live children community-level variables (Mosley & Chen, 1984).
in 1990 to 23/1000 live children in 2015 (Yohannes
et al., 2017). Ethiopia had significant inequalities in child Several studies have applied hierarchical models
mortality between rural and urban areas where the risk of that are rooted in Mosely and Chen (1984) to analyze
child mortality is largely higher in rural than urban areas how micro (i.e., individual and household level) and
(Gebresilassie et al., 2021). The overwhelming urban-rural macro/contextual (community level) factors influence

Volume 7 Issue 2 (2021) 48 https://doi.org/10.36922/ijps.v7i2.392