Policy Research Working Paper 10246
Reversing the Trend of Stunting in Sudan
Opportunities for Human Capital Development
through Multisectoral Approaches
Alvin Etang
Sering Touray
Poverty and Equity Global Practice
November 2022
Policy Research Working Paper 10246
Abstract
Stunting, measured using a height-for-age Z score [HAZ] drivers of nutrition also remains significantly low. Adequate
and an indicator of chronic malnutrition, among 0–5-year- access to nutrition drivers is strongly associated with a lower
old Sudanese children has been on the rise—from 34 percent likelihood of being stunted. Among the nutrition drivers
in 2010 to 38 percent in 2014. Although a multisectoral considered, adequate access to food security and care and
approach to tackling undernutrition may mask clarity and health care (both individually and jointly) significantly
undermine specificity of sectors to prioritize, it can be a lowers a child’s probability of being stunted. In rural areas
basis for designing evidenced-based and balanced multi- and poor households where stunting rates are highest, pri-
sectoral strategies to addressing stunting in Sudan. Overall, oritizing food security and access to adequate health care
stunting is more prevalent in the early years of Sudanese can contribute toward lowering stunting. Poverty remains
children and among children from the poorest households a central feature of stunting in Sudan and a main source of
and in rural areas where adequate access to the underlying inequalities in adequate access to nutrition drivers.
This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to
provide open access to its research and make a contribution to development policy discussions around the world. Policy
Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted
at aetangndip@worldbank.org; stouray@worldbank.org.
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Produced by the Research Support Team
Reversing the Trend of Stunting in Sudan: Opportunities for
Human Capital Development through Multisectoral
Approaches
Alvin Etang and Sering Touray1
Key words: Stunting, Human capital, Inequality, Welfare, Sudan
JEL Classification: I00, I10, I30, I32, O55
1 Alvin Etang is a Senior Economist in the Poverty and Equity Global Practice of the World Bank; Sering Touray is an
Economist in the Poverty and Equity Global Practice of the World Bank. The authors are grateful to Pierella Paci for
guidance and feedback on earlier drafts of this paper. Peer reviewer comments from Emmanuel Skoufias and Alaa
Mahmoud Hamed are also gratefully acknowledged. The findings, interpretations, and conclusions of this paper are
those of the authors and should not be attributed to the World Bank or its Executive Directors. The authors may be
contacted at aetangndip@worldbank.org and stouray@worldbank.org.
1. Introduction
The Sudanese economy has experienced several events in the recent past. Following the secession of
the South in 2011, the government experienced a significant decrease in total revenue, largely due to
loss of oil revenue, thereby constraining its fiscal space. As a result of this and other macroeconomic
shocks that emerged (notably rising prices and volatile exchange rates), the government faced immense
challenge of instituting reforms to restore macroeconomic stability, spur growth, and improve the
welfare of the Sudanese people. Recent poverty estimates obtained from the 2014/15 National
Household Budget and Poverty Survey (NHBPS) and released in November 2017 indicate that 36.1
percent of Sudanese had per capita expenditure levels below the national poverty line. Measured
against the World Bank’s international poverty line of US$1.90 per day (based on the 2011 purchasing
power parity [PPP]), 13.5 percent of Sudanese are deemed poor. These statistics are further marked
by significant geographic heterogeneity. For instance, in the Northern State, about 12 percent of the
population are estimated to be poor. In the state of Central Darfur and in Western Sudan, poverty is
estimated at 67 percent. Similarly, states in the Kordofan and Darfur regions as well as the Red Sea
and White Nile States have poverty rates higher than the national average.
Sudan’s low ranking in the World Bank’s 2018 Human Capital Index (HCI) may in part be driven by
a high prevalence of stunting, an indicator of long-term malnutrition, and widespread poverty. Recent
data from the World Bank’s HCI, which measures the amount of human capital that a child born
today is expected to attain by the time s/he reaches the age of 18 years, shows that the child will only
be 38 percent as productive when s/he grows up as s/he could be if s/he enjoyed complete education
and full health (World Bank Group 2018). At this level, Sudan ranks 139 out of 157 countries in the
World Bank’s 2018 HCI rankings—below its regional average (41 percent) and its income group
average (49 percent). Among lower-middle-income countries in Sub-Saharan Africa, Sudan’s level of
HCI is only higher than Zambia and Nigeria (see Figure 1a). The HCI is constructed by combining
measures of health (probability of survival to age 5, stunting among children ages 0–5 years, and
probability of survival to age 60) and education (expected years of schooling and test scores). Among
these indicators, stunting (an indicator of adverse undernutrition) among Sudanese children appears
to be the main driver of its low HCI. For instance, while 94 percent of children born in Sudan are
expected to live to age 5 and 78 percent of 15-year-olds are expected to live to age 60, 38 percent of
children ages 0–5 years are stunted and face the risk of cognitive and physical limitations that can last
2
a lifetime (World Bank Group 2018).2 Thus, Sudan’s low performance in the HCI rankings can in part
be explained by widespread stunting. Among its income group in Sub-Saharan Africa, Sudan has the
third-highest level of stunting among under-five-year-old children (see Figure 1a. Central to the link
between stunting and human capital accumulation is the extent of poverty. Inequalities in access to
determinants of undernutrition such as quality and adequate diets, sanitation, and health care are often
driven by poverty. Within Sudan, changes in poverty and stunting over time appear to mirror similar
patterns (see Figure 1b). Poverty (defined using the international poverty line of US$3.20 for lower-
middle-income countries) increased from 41 percent in 2009 to 46 percent in 2014/15. Similarly,
stunting among under-five-year-old children increased from 34 percent in 2010 to 38 percent in 2014.
This relationship is even more evident in rural areas where poverty is more widespread. Given that
human development remains a central pillar in the drive to achieving the Sustainable Development
Goals (SDGs) and the World Bank’s twin goals to eliminate extreme poverty and boost shared
prosperity by 2030, addressing the problem of stunting is crucial for a productive future labor force
and for sustained economic growth.
2 Another possible explanation for Sudan’s low HCI is slow progress toward improving learning outcomes. For instance,
while a Sudanese child who starts school at age 4 is expected to complete 7.3 years of school by age 18 and harmonized
test scores in Sudan average 380 (where 625 represents advanced attainment and 300 represents the minimum
attainment), learning-adjusted years of schooling is estimated at only 4.4 years—a learning gap of 2.9 years.
3
Figure 1: Human Capital, Stunting, and Poverty in Sudan
(a) HCI and Stunting in Lower-Middle-Income (b) Poverty and Stunting in Sudan
Countries
0.90 60%
0.80
50%
0.70
0.60 40%
0.50
0.40 30%
0.30
20%
0.20
0.10 10%
0.00
0%
National
National
Urban
Urban
Rural
Rural
Fraction of Kids Under 5 Not Stunted 2009/10 2014/15
Human Capital Index Poverty Stunting
Source: Authors’ calculation using the World Bank’s HCI data in panel (a). In panel (b), stunting data presented are obtained
from Sudan’s Multiple Indicator Cluster Survey (MICS) 2010 and 2014 household survey data. Poverty data are obtained
from Sudan’s 2009 National Baseline Household Survey (NBHS) and 2014/15 National Household Budget and Poverty
Survey (NHBPS) data.
Developing human resources through investments in human development to enhance population
capabilities and better health is needed to reap the double dividends of improving productivity for
growth and tacking inequality and hence forms a central pillar in Sudan’s medium-term national
development policy framework. Sudan’s Poverty Reduction Strategy Paper (PRSP) was aimed at
achieving sustainable development and poverty reduction in the medium term. Given the high
prevalence of stunting, a measure of long-term malnutrition with large negative effects, these efforts
can benefit from detailed insights into the underlying drivers of malnutrition. Furthermore, to reap
the double dividends of improving productivity to spur growth and lower inequality, investments in
human capital, particularly education and health care, among other things, are key.
This paper aims to inform these efforts by discussing the role of multisectoral approaches to tackling
undernutrition (focusing on stunting) in Sudan. It provides country-specific insights into the extent to
which inequalities in access to food security and care; health care; and water, sanitation, and hygiene
(WASH) individually and collectively drive the prevalence of stunting among 0–23-month-old
children. A multisectoral framework developed by the United Nations Children’s Fund (UNICEF)
for the identification of underlying determinants of undernutrition is adopted in this paper. These
4
determinants include indicators of food and care, WASH, and health care of children. We use two
rounds of the MICS collected in 2010 and 2014 to examine the extent to which limitations in access
to adequate levels of food security and care, WASH, and health care individually and jointly affect
nutrition outcomes of Sudanese children ages between 0 and 23 months.
Furthermore, we examine the extent to which inequalities in access to the underlying drivers of
nutrition exist as well as the varying degree to which adequate access to nutrition drivers influences
nutritional outcomes among children across space (rural versus urban) and wealth (rich versus poor)
in Sudan. Several studies on the determinants of undernutrition have highlighted the centrality of
poverty—both as an indicator and a source of undernutrition. Thus, by considering the heterogeneity
of stunting and the extent to which it is influenced by inadequate access to the underlying determinants
of undernutrition across the wealth distribution, gaps in access to main drivers (which are likely to
differ for rich and poor households) can be identified for reform. Similar insights can also be drawn
from the comparisons of stunting and access to adequate levels of nutrition drivers in rural and urban
areas.
The focus on 0–23-month-old children is motivated by empirical evidence that severe forms of
undernutrition such as stunting are both more prevalent and have larger adverse effects in the early
years of a child’s life (Victora et al. 2010).3 Recent data from Sub-Saharan Africa also show higher
prevalence of stunting among younger children (Skoufias, Vinha, and Sato 2019, p49). Results from
this paper will thus provide useful insights into recent trends in stunting across space (rural versus
urban) and households (particularly those in the bottom of the wealth distribution). These insights
will be useful for identifying the nutrition drivers that significantly influence stunting as well as gaps
in access to these drivers to inform the design of effective policies to address the problem of stunting
in Sudan.
Conceptually, the adopted framework is premised on the fact that at the heart of human development
for sustainable growth is the need to ensure that nutrition levels (particularly of children) and other
factors that influence it directly or indirectly are adequate. Achieving this objective requires a
multisectoral approach to ensure food security, adequate care (including a clean and healthy
environment), and access to health services. Deficiency in one or more of these factors, also referred
3In describing the nature of stunting in Sudan, we provide an overview of the prevalence of stunting across the age
distribution of children under five years of age. Similar patterns of prevalence described by early papers are also
observed- stunting rates among younger Sudanese children are higher. As a result, the analysis of the extent to which
access to adequate levels of nutrition drivers influences stunting focuses on children ages 0–23 months.
5
to as the ‘underlying determinants’ of nutrition in the literature, may significantly affect nutrition
outcomes and human capital formation. Although Sudan’s low level of human capital as indicated by
the World Bank’s HCI rankings can be explained by several factors, current nutrition levels,
particularly of children, highlight the centrality of nutrition quality in the human capital
formation/development and sustainable growth nexus. Typically, underweight (having low weight),
stunting (having low height-for-age), and wasting (having low weight-for-height) are considered
standard indicators of nutrition quality. Data from the MICS collected in 2010 and 2014 indicate that
stunting (measured as the percentage of children under age five who fall below −2 standard deviations
of the median height-for-age of the World Health Organization [WHO] standard) increased from 35
percent in 2010 to 38.2 percent in 2014. Severe stunting (percentage of children under age five who
fall below −2 standard deviations of the median height-for-age of the WHO standard) increased from
15 percent in 2010 to 18 percent in 2014. Other indicators such as underweight (which was 32.2
percent in 2010 and 33 percent in 2014) and wasting (which was 16.4 percent in 2010 and 16.3 percent
in 2014) indicate that progress toward lowering prevailing levels of undernutrition in Sudan is slow.
Similarly, across Sub-Saharan Africa, undernutrition remains a major challenge. A recent World Bank
report estimates that in Sub-Saharan Africa, 58 million children under the age of five are stunted and
14 million are wasted (Skoufias, Vinha, and Sato 2019).
These statistics, particularly the high rates of stunting, highlight the urgency for action to avoid the
large negative effects of undernutrition on individuals and their societies. Stunting, in particular, results
in low cognitive development and human capital attainment, resulting in low future human capital
formation and hence economic growth (Hoddinott et al. 2013). Effects of undernutrition on health
outcomes are equally dire. In addition to increased vulnerability to diseases and likelihood of death
from diseases, undernutrition has been identified as a major source of risk of chronic diseases in later
life. Therefore, the analysis of the determinants of undernutrition serves as a tool to monitor progress
in achieving targets such as the SDGs and highlight the possible negative effects of undernutrition on
health and learning outcomes.
The paper is structured as follows: Section 2 provides an overview of the existing literature on
undernutrition and its determinants. Section 3 describes the methodology used in this paper—the
UNICEF conceptual framework and the MICS data collected in 2010 and 2014. The analysis section
(Section 4) begins by describing the nature of stunting among 0–5-year-old children in Sudan
highlighting differences in stunting rates across states, households, gender, and age groups. This
6
analysis is followed by an overview of the extent of inequalities in access to adequate levels of nutrition
drivers among 0–23-month-old children. The second part of Section 4 examines the extent to which
access to adequate levels of nutrition drivers influences stunting in Sudan. We estimate marginal effects
of access levels (including individual and joint access) on the probability of being stunted to identify
the main nutrition drivers that significantly affect stunting and the heterogeneity of their effects across
space, wealth, and gender. Finally, Section 5 concludes by discussing the implications of the results on
multisectoral responses to stunting in Sudan.
7
2. Stunting and Access to Nutrition Drivers
Undernutrition, particularly stunting among children, is widespread in developing countries and
identified as a major challenge to sustained economic growth. In 2018, joint estimates by the WHO,
UNICEF, and the World Bank Group indicated that globally 21.9 percent or 149 million children
under five years were stunted (that is, too short for their age); 7.3 percent or 49 million children under
five years were threatened by wasting (that is, too thin for their height); and 5.9 percent or 40 million
children under five years were overweight (that is, too heavy for their height). More than one-third of
stunted children (39 percent or 58.8 million children) live in Africa. Furthermore, between 2000 and
2018, Africa is the only region where the number of stunted children has risen—from 50.3 million to
58.8 million (UNICEF, WHO, and World Bank Group 2019). The widespread prevalence of
stunting—an indicator of long-term undernutrition (particularly in Africa)—is alarming and calls for
concerted efforts to confront it. There exists significant variability in the prevalence of undernutrition
across countries (based on income group, Sahel versus non-Sahel, fragility, and so on) and within
countries (rural versus urban, boys versus girls, the mother’s level of education, the child’s age group,
and so on) in the region. One striking result from recent studies is the high prevalence of stunting
among younger children (ages between 0 and 23 months) in Sub-Saharan Africa (Skoufias, Vinha, and
Sato 2019, p49).
High rates of undernutrition are likely to have large negative effects on affected children and their
societies in the immediate and long term. Undernourished children are less likely to develop cognitive
abilities needed for improved learning outcomes and are more likely to be vulnerable to diseases,
particularly chronic diseases in later life. As a result, children who are stunted in the early years of their
lives are more likely to have lower learning attainment and wages and are less likely to escape poverty
as adults (Fink et al. 2016; Hoddinott et al. 2008, 2011; and Martorell et al. 2010). Stunted women are
likely to face obstetric complications because of a smaller pelvis and also face the risk of delivering
low-birth-weight infants who in turn are more likely to be smaller adults, resulting in an
intergenerational cycle of malnutrition (WHO 2010). Similarly, societies with high rates of
undernutrition are less likely to be able to accumulate sufficient human capital for sustainable growth.
As a result, countries’ failure to address undernutrition (particularly in the early years of children) is
likely to significantly undermine economic growth. The negative effects of stunting in particular have
been identified to be particularly large. For instance, a recent World Bank report estimates the cost of
a country’s inability to eliminate stunting of today’s workers when they were children at 7 percent of
8
gross domestic product (GDP) per capita. In Sub-Saharan Africa and South Asia, these effects are
even larger—estimates are in the rage of 9 to 10 percent of GDP per capita (Galasso et al. 2017).
Given the extent of undernutrition in developing countries and its potential impact on their growth,
international organizations such as the World Bank, UNICEF, and so on are increasingly supporting
efforts to overcome the challenge of undernutrition through the financing of nutrition-specific
interventions and health sector reforms.
Identifying the drivers of malnutrition has been the subject of several studies—from sector-specific
studies to multisectoral studies identifying constraints to improving nutritional outcomes. Many of the
earlier contributions to the literature on determinants of child undernutrition focused on specific
variables that are likely to affect child nutritional outcomes such as socioeconomic conditions of the
household proxied by variables, including income, assets, and so on (Behrman and Deolalikar 1987)
and the education level of the mother (see Barrera 1990; Behrman and Wolfe 1984; Skoufias 1999;
and Webb and Block 2004; among others). In several of these types of studies, environment, health,
and child care practices and other unobservable factors likely to affect child nutrition are controlled
for using community and/or household fixed effects. Another strand of studies in the literature
examined drivers of malnutrition through a sector-specific lens, particularly in nutrition and health.
These studies examine the extent to which interventions in sectors such as nutrition (such as
promoting breastfeeding, providing micronutrient fortified and enhanced complementary food) and
health (such as increasing access to vitamins and minerals) improve nutrition outcomes (see Horton
et al. 2010, among others). Later studies have adopted a broader multisectoral framework—
incorporating various sectors considered by different strands of the literature on the determinants of
undernutrition (nutrition, health, and environmental factors). Indicators of dietary quality and
quantity, care and feeding practices, health care, and environmental factors such as water and
sanitation have typically been identified and used in these studies to examine the extent to which these
factors individually and interactively affect nutritional outcomes (Skoufias 2016).
UNICEF formalized these multisectoral determinants of undernutrition into a framework that
continues to provide operational and analytical guidance for combating undernutrition. The UNICEF
framework, which was first proposed in 1990, emphasized the interactions between food security,
environment, health, and child care practices in influencing child nutritional outcomes (UNICEF
1990). The framework identifies immediate causes of undernutrition such as disease and inadequate
dietary intake; underlying causes of undernutrition such as food insecurity, inadequate care,
9
unhealthy household environment, and inadequate access to health services; and basic causes of
undernutrition such as structural differences in social, cultural, economic, and political factors and
how they influence inequalities in the distribution of resources (financial, human, physical, and social
capital) in the society (Skoufias, Vinha, and Sato 2019; UNICEF 1990). On the basis of this conceptual
framework, basic causes of undernutrition trigger underlying causes by imposing constraints on
households’ ability to achieve food security and healthy environment, as well as access to care and
health services. Where these constraints are binding, immediate causes such as inadequate dietary
intake and diseases take effect. Although the framework captures the multisectoral nature of nutrition
to a great extent, it is important to highlight some of the limitations in its categorization. Evidently,
the central pillar of the determinants of undernutrition highlighted earlier is household poverty.
Competing needs of households (particularly the poor) impose budget constraints on their ability to
provide adequate and nutrient-rich food, proper care (including sanitation), and adequate access to
health services for their children in the early years of the lives. As a result, the quantity, quality, and
diversity of nutrition, as well as access to care and health services, are often low in these households,
exposing their children to undernutrition. The fact that household income is explicitly not included in
the UNICEF framework is one of its limitations. Other limitations, which have been cited in the
literature, include the absence of prices, knowledge, and education—all of which have direct and/or
indirect effects (through the categories identified by the framework) on nutrition (Skoufias 2016).
This framework (and modifications of it) has become the workhorse model used in the recent studies
on the determinants of undernutrition. Despite several modifications to the UNICEF framework, the
belief that poor diets, in terms of diversity, quality, and quantity resulting in micronutrient deficiencies
and increased vulnerability to illness, and inequalities in access to health care, clean water and
sanitation, proper care, and appropriate feeding practices play an individual and collective role in
influencing nutritional outcomes is still central to its foundation (Skoufias, Vinha, and Sato 2019).
Inadequate access to these determinants (particularly in the early years of a child’s life) exposes children
to various forms of malnutrition, including stunting. Typically, the framework is implemented by
identifying indicators of three underlying determinants of undernutrition—food security and care,
WASH, and health care. The indicators of food and care include the child’s access to minimum
acceptable diet (including exclusive breastfeeding for under-six-month-old children) and dietary
diversity and quantity. The WASH component captures indicators relating to access to safe drinking
water, handwashing facilities, and improved sanitation facilities (including the extent of open defection
10
in the community). The health component captures indicators relating to use of prenatal and postnatal
services, vaccination compliance, and access to health care professionals during childbirth (UNICEF
1990). Several studies—including those by institutions such as the Food and Agriculture Organization
(FAO) (2011), the U.S. Agency for International Development (USAID) (Riely et al. 1999), and the
World Food Programme (WFP) (2009)—have adopted this framework to generate a wealth of
knowledge on the extent and drivers of undernutrition and the identification of children and/or
geographical areas where it is most prevalent and hence better targeting of interventions in specific
countries. Similarly, other studies have adopted the framework to highlight cross-country differences
in the prevalence and drivers of undernutrition—see Smith and Haddad (2015) for a study of 116
countries. The World Bank also recently produced a report on the state of stunting in Sub-Saharan
Africa. The report, which also adopts the UNICEF framework, provides an important bridge of the
knowledge gap in the understanding the nature of stunting in the region. It uses child-level data from
the Demographic and Health Survey (DHS) collected in 2010 or later from 33 countries to provide a
detailed analysis of the underlying determinants of undernutrition in Sub-Saharan Africa. The report
also examined the extent of the heterogeneity in the prevalence of stunting across the subregion by
looking at attributes such as income (both income level and variability), landlocked countries, the Sahel
subregion, and fragility. Since DHS data from Sudan were not available for the period covered by the
report, Sudan was not included in the analysis. The report documents substantial inequalities in access
to the underlying determinants of stunting within countries—particularly between rural and urban and
poor and wealthy households. It also highlights the significance of access to health in lowering the
likelihood of a child being stunted—particularly when complemented with simultaneous access to
food security and care or WASH.
Understanding the underlying determinants of undernutrition is particularly important for designing
appropriate multisectoral interventions to meet nutritional targets needed to overcome stunting,
underweight, and wasting. With the increasing availability of rich data from DHSs and MICSs, the
literature on the determinants of undernutrition is rapidly growing. This is further fueled by growing
demand from policy makers as they seek to design appropriate interventions to address the rising
challenge of undernutrition. While the recent World Bank report covers substantial ground on the
state of stunting in Sub-Saharan Africa, it would be critical to have substantive country-specific
insights that can inform the policy makers of individual countries. The UNICEF framework lends
itself to this purpose by enabling researchers to capture the joint distribution of the underlying
11
determinants of undernutrition and thus identify the extent to which deficiencies in a single as well as
multiple determinants influence the prevalence of stunting. These insights are important for
identifying gaps in those determinant(s) that, if addressed through multisectoral interventions, can
improve nutrition outcomes. Empirical evidence so far illustrates that these insights are useful for the
design of nutrition-sensitive interventions that address issues of food insecurity, access to health
services, provision of caregiving resources in households and communities, and so on and can
strengthen other nutrition-related policies such as promoting adequate food and nutrient intake,
optimum breast feeding, caregiving, and so on (Black et al. 2013).
This paper aims to contribute to the existing literature by providing in-depth country-specific evidence
on the state of stunting in Sudan to inform policy. Drawing from the contributions in the literature,
particularly the recent World Bank report on stunting in Sub-Saharan Africa (Skoufias, Vinha, and
Sato 2019), this paper examines the prevalence of stunting in Sudan and the extent of the inequalities
in access to the underlying determinants of stunting that are influenced by poverty to inform policy.
Using two rounds of the MICS data collected in 2010 and 2014, this paper highlights geographic and
socioeconomic (particularly wealth) heterogeneity in the prevalence of stunting among 0–23-month-
old children in Sudan in both years. We use the UNICEF framework described earlier to identify
indicators of food security and child care, WASH, and health care from the MICS data. We examine
the extent to which these underlying determinants individually and collectively influence stunting
among children in Sudan. The paper also highlights inequalities in access to these determinants and
the extent to which such inequalities are driven by poverty. By providing detailed insights into the
adequacy of these underlying determinants across states and households over time, gaps in access to
drivers that significantly influence stunting can be identified to inform policy. Given recent
macroeconomic and political changes in Sudan and ongoing efforts to formulate a national policy for
sustained growth and poverty reduction such as the PRSP, results from these analyses will serve as
inputs in the design and implementation of such policies by highlighting gaps in the underlying
determinants that need to be addressed to improve nutrition outcomes.
12
3. Methodology
In this section, we describe the data used, the identification of stunted children, and the various
indicators of the underlying determinants of stunting (food security and care, WASH, and health care)
discussed in the previous section.
Data
This paper uses data from the MICSs collected in 2010 and 2014 by the Central Bureau of Statistics
(CBS) of the Republic of Sudan in collaboration with UNICEF and the Ministry of Health.4 The
sample size was 14,778 households in 2010 and 16,801 households in 2014. The survey employed a
two-stage stratified cluster design in which the enumeration areas (EAs) were selected in the first stage
based on the 2008 population census, and individual households were randomly selected in the second
stage following household listing exercise in the selected EAs. A total of 25 households were selected
per EA. The sample was designed to be representative both nationally and at the level of all Sudan’s
states (15 states in 2010 and 18 states in 2014). Similar to the DHS, the MICS collects data at
household, child, and women levels. In addition to information about households typically collected
in household surveys such as demographics, socioeconomic status, livelihoods, and so on, the MICS
collects comprehensive data on child-level health and nutrition (anthropometric indicators), maternal
health, and WASH indicators. For this reason, it is easy to construct indicators of undernutrition such
as stunting, underweight, and wasting using variables such as height-for-age, weight-for-age, and so
on. Furthermore, the comprehensiveness of the data on child nutrition and care, access to health care,
and WASH facilities makes it easy to examine the underlying determinants of undernutrition using the
UNICEF framework.
Definitions
Stunting. A child who is too short for his/her age is referred to as being stunted. The WHO defines
stunting as having a height-for-age Z score (HAZ) more than 2 standard deviations below the WHO
Child Growth Standards median (WHO 2010). For this paper, it is expressed as a percentage of
children ages 0–5 years whose HAZ falls below the WHO threshold. In discussing the general trend
of stunting in Sudan (changes between 2010 and 2014, differences across space and households), we
4 The 2010 MICS was labelled as the second wave of the Sudan Household Health Survey (SHHS); thus, we maintain
the same nomenclature in the rest of the paper.
13
consider all children under five years of age. However, in analyzing the underlying determinants of
stunting, we focus more on children ages 0–23 months.
Underlying determinants of stunting. In Table 1, we describe the underlying determinants of
stunting based on the UNICEF conceptual framework. For each determinant, we discuss the
indicators considered and the condition for a child to be considered to have an adequate level in the
determinant. The adequacy definitions are constructed using thresholds based on accepted
international standards (Skoufias, Vinha, and Sato 2019; UNICEF 1990). These determinants are
constructed for children ages 0–23 months.
Table 1: Underlying Determinants of Stunting
Determinant Component Adequate When:
Food security 1. Minimum acceptable diet. This is an indicator of A child is considered to have an
and care the child’s level of food security. Under this adequate level of food security and
component, children under 6 months old must be child care if the condition for
exclusively breastfed, children ages 6–8 months minimum acceptable diet is met with
should be still breastfed and consume at least four one of the two indicators of child care:
food groups5 at least twice a day, children ages 9–23 early initiation of breastfeeding or age-
months and are still breastfed must consume at least appropriate breastfeeding.
four food groups at least three times a day, and
children ages 6–23 months who are not being
breastfed must consume at least four food groups at
least four times a day.
2. Early initiation of breastfeeding. This component
captures child care and is met when a child was
breastfed within hours after birth.
3. Age-appropriate feeding. This is another indicator
of child care. Under this component, children under 6
months old must be exclusively breastfed and those
ages 6 and 24 months in addition to consuming other
food, must also be still breastfed.
WASH 1. Access to safe drinking water. The child lives in a A child is considered to have adequate
household with access to pipe-borne water or water WASH if s/he meets at least three of
obtained from tube well or bore well, protected well the five components.
or spring, or rainwater.
2. Access to improved sanitation facilities. The child
lives in a household with a flush toilet, ventilated or
slabbed pit latrine, or a composting toilet.
3. Community-level sanitation. This indicator
captures the extent of open defecation in a child’s
community/primary sampling unit (PSU), that is,
households who do not have access to any toilet
facility and thus resort to open defecation. Typically,
appropriate community-level sanitation is reached
when less than 25 percent of a households in the
community use open defecation.
5The food groups are defined to capture the extent of dietary diversity; these include grains, roots, and tubers; legumes
and nuts; dairy products; flesh foods including organ meats; eggs; vitamin A-rich fruits and vegetables including orange
and yellow vegetables; and other fruits.
14
Determinant Component Adequate When:
4. Access to hand washing facilities.6 A child lives in
a household with handwashing facilities along with
water and soap or detergent, as observed by the
interviewer.
5. Feces disposal. A child’s stools are disposed into
improved sanitation facilities.
Health care 1. Antenatal visits. This indicator is adequate when a A child is considered to have adequate
child’s mother had at least four antenatal visits during health care if s/he meets all three
pregnancy. indicators. In other studies, an
2. Birth assisted by health care professional. The indicator of access to mosquito net is
childbirth was assisted by health care professionals included in the health care component.
such as a doctor, nurse, birth attendant, midwife, and However, since this was not available
so on. in the MICS data set, we restrict the
3. Immunization compliance. This indicator captures health care component to the three
a child’s compliance with his/her vaccines as and indicators.
when they are due based on the WHO vaccination
schedule:7 tuberculosis- BCG (at birth); diphtheria,
pertussis, and tetanus DPT/PENTA (at 2, 3, and 4
months), polio (at birth, 2, 3, and 4 months), and
measles (at 9 months). Typically, a leeway of 2
months is added to the vaccination schedule after
which a child is considered to be noncompliant with
the vaccination requirement.
6 This indicator was not available in the 2010 data.
7 See https://tinyurl.com/y3gykpr9 for Sudan’s vaccination schedule.
15
4. Analysis
This section aims to provide a description of the state of stunting in Sudan by highlighting differences
in stunting levels across space and over time (between 2010 and 2014). We complement this
description with a basic analysis of the relationship between stunting and the drivers discussed earlier.
These analyses focus on highlighting the correlation between inequalities in individual and/or joint
determinants of stunting and observed levels of stunting.
In the second part of the analysis,
• We estimate the effect of access to adequate levels of nutrition drivers on stunting of 0–23-
month-old children;
• We consider the effect of individual and joint access to adequate levels of nutrition drivers on
stunting;
• For each component of nutrition driver, we also examine the effect of the individual indicators
that form these components on stunting to identify the main drivers of nutritional outcomes
among Sudanese children; and
• We also consider differences in the effect of the drivers of stunting across space (rural versus
urban), households (rich versus poor), and gender.
Overview Stunting in Sudan
Overall, the number of stunted children who are five years old or younger increased in Sudan between
2010 and 2014, driven largely by an increase in rural areas. In 2010, 34 percent of children under five
years were stunted, 15 percent of whom were severely stunted. In 2014, it is estimated that 38 percent
of under-five-year-olds were stunted with 18 percent being severely stunted. In rural Sudan, stunting
is more prevalent and continues to rise—from 38 percent in 2010 to 43 percent in 2014 compared to
25 percent in 2010 and 27 percent in 2014 in urban areas. Across states, there appears to be significant
spatial heterogeneity in the prevalence of stunting. In some states, the number of stunted children
decreased between 2010 and 2014, but in most states, it increased. For instance, the largest decreases
in the prevalence of stunting were observed in Sinnar, Red Sea, and North Kordofan where the
percentage of stunted children decreased by 8 percent, 6 percent, and 5 percent, respectively. On the
16
other hand, in Gezira, North Darfu, and Blue Nile, the percentage of stunted children increased by
13 percent, 12 percent, and 10 percent, respectively, between 2010 and 2014.
Figure 2: Prevalence of Stunting among Under-Five-Year-Old Children in Sudan: National, Rural, and Urban
as well as Changes across States
(a) National, Rural, and Urban (b) Changes across States
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
National Rural Urban National Rural Urban
2014 2010
Stunted Severely Stunted
Source: Authors’ calculation using MICS 2010 and 2014 data.
Stunting is more prevalent among children from poorer households. Using a composite indicator of
household wealth, it can be observed that stunting is more prevalent among households in the bottom
of the wealth distribution and remained high in 2014. More than 40 percent of children in the poorest,
poor, and middle wealth quintiles were stunted in 2014—more than 20 percent of these children were
severely stunted. Although the prevalence of stunting increased across the wealth distribution between
2010 and 2014, children from households at the bottom of the distribution remain disproportionately
affected. These statistics highlight the centrality of household poverty in the prevalence of stunting.
Understanding the extent to which poverty influences undernutrition, particularly its role in driving
inequalities in access to the underlying determinants of nutrition, is a crucial first step in designing and
implementing needed reforms. This paper aims to make a contribution in this regard- by highlighting
the role of multisectoral approaches. There also appears to be significant heterogeneity in the
prevalence of stunting across households based on the education level of mothers. In both 2010 and
2014, moderate and severe stunting were more prevalent among children whose mothers had no
formal education compared to those whose mothers had some primary, secondary, or higher
education. For instance, in 2014, the percentage of moderately and severely stunted children whose
17
mothers had no formal education was 47 percent and 24 percent, respectively—more than double the
prevalence of stunting among children whose mothers had higher education.
Gender patterns in the prevalence of stunting in Sudan have changed between 2010 and 2014, with
more boys being stunted in 2014 than girls. Although stunting (both moderate and severe) was more
prevalent among female children in 2010, the reverse was observed in 2014. In 2010, 37 percent of
female children were stunted compared to 32 percent of male children. Similarly, 16 percent of female
children were severely stunted compared to 13 percent of male children. However, in 2014, 40 percent
of boys were stunted compared to 36 percent of girls, and 20 percent of boys were severely stunted
compared to 16 percent of girls. Although the prevalence of stunting fell among girls between 2010
and 2014, the rate of progress was slow. High prevalence of stunting among girls has significant long-
term implications. Small female adults are more likely to give birth to low-birth infants who in turn
face significant risk of being smaller adults tomorrow, resulting in an intergenerational cycle of
malnutrition. Thus, addressing the problem of stunting through a gender lens is crucial for tackling
the intergenerational cycle of undernutrition.
Within the 0–5 age group, the prevalence of stunting continues to be high among the youngest
children, including those under 24 months. High prevalence of stunting in the early years of Sudanese
children continues to be a major concern. In both 2010 and 2014, the highest rates of stunting were
observed among children ages 24–35 month, 35–47 months, and 12–23 months. Furthermore, the
recent data show an increase in the prevalence of stunting in these age groups. Stunting among
children ages 24–35 months increased from 43 percent in 2010 to 50 percent in 2014, from 40 percent
in 2010 to 47 percent in 2014 for children ages 35–47 months, and from 38 percent to 40 percent for
children ages 12–23 months. The rates of severe stunting also mirror similar patterns. Another
indicator of the high prevalence of stunting in the early years of Sudanese children is the prevalence
rate among children under 24 months since this period falls within the traditional first 1,000-day
threshold. Moderate stunting rates did not significantly change for this age category in Sudan between
2010 and 2014. In both periods, an estimated 27 percent of children under 24 months were stunted,
more than 10 percent of whom were severely stunted; modest reductions in stunting among children
ages 0–5 and 6–11 months have been overshadowed by an increase in stunting among children ages
12–23 months. Nutritional deprivation in the early years of a child’s life (particularly the first 1 ,000
days) resulting in stunted growth exposes the children to the risk of delayed cognitive and physical
development, illness, and death. If not addressed, stunting in the early years of a child’s life implies
18
that such children are less likely to live to be adults or more likely to grow into less productive adults,
leaving societies with lower or less productive human capital and slower growth.
Figure 3: Prevalence of Stunting in Sudan: Wealth Quintile, Mothers’ Education Level, Age Group, and
Children Gender
(a) Wealth Quintile (b) Mothers’ Education Level
50% 50%
45% 45%
40% 40%
35% 35%
30% 30%
25%
25%
20%
20%
15%
15%
10%
10%
5%
5%
0%
Higher
Primary
Secondary
Primary
Secondary
None
None
0%
Rich
Rich
Richest
Poorest
Poor
Richest
Poorest
Poor
Middle
Middle
2014 2010 2014 2010
Stunted Severely Stunted Stunted Severely Stunted
(c) Age Groups (in Months) (d) Gender of Child
60% 45%
40%
50%
35%
40% 30%
25%
30%
20%
20%
15%
10% 10%
5%
0%
0-5
12-23
6-11
0-5
6-11
12-23
24-35
36-47
48-59
24-35
36-47
48-59
0%
Girls Boys Girls Boys
2014 2010 2014 2010
Stunted Severely Stunted Stunted Severely Stunted
Source: Authors’ calculation using MICS 2010 and 2014 data.
19
Overview of the Underlying Determinants of Nutrition (0–23-month-old Children)
Adequate access to the underlying determinants of stunting remains low in Sudan. In 2014, only 5
percent of children ages 0–23 months had adequate levels in all three determinants of stunting
considered in this paper: food security and care, WASH, and health care.8 Although the percentage of
0–23-month-old children with adequate levels of these determinants has increased from 4 percent in
2010, this is largely driven by increases in access for children from rich and urban households. Figure
4a and Figure 4b illustrate the extent of the deficiencies in the access to the underlying determinants
of nutrition in Sudan in 2014 and 2010, respectively. Low access to these underlying determinants of
nutrition among children in Sudan highlights the urgency for holistic and multisectoral approaches in
nutrition and care, WASH, and health to address the widespread prevalence of stunting in Sudan. In
the following sections, we identify and discuss the indicators driving these deficiencies in each
component to inform the needed responses.
Inequalities in access to adequate levels of the underlying determinants of stunting, particularly
between rich and poor as well as rural and urban households, are widespread in Sudan. Most 0–23-
month-old children without access to any of the underlying determinants of stunting are from poor
or rural households. In both 2010 and 2014, more than 50 percent of children from households in the
bottom 20 percent of the wealth distribution and more than 30 percent of those in rural areas did not
have adequate levels in any of the three determinants of stunting. On the other hand, the percentage
of children from the richest households with inadequate access to all three determinants of nutrition
decreased from 5 percent in 2010 to 1 percent in 2014. Similarly, in urban areas, children without
adequate access to all three determinants decreased from 20 percent in 2010 to 7 percent in 2014. At
face value, these figures illustrate that the increase in the prevalence of stunting in Sudan between
2010 and 2014 was likely driven by inadequate access to adequate levels of the underlying determinants
of nutrition for children from poor and rural households. Inequalities in access between these children
and those from rich and urban households widened between 2010 and 2014, driving the increase in
the prevalence of stunting in poor and rural households.
Although occurring at varying degrees, some states registered significant progress in improving access
to the underlying determinants of nutrition between 2010 and 2014. Figure 4a and Figure 4b show the
changes between 2010 and 2014 in the percentage of children ages 0–23 months without access and
8 See Table 1 for the description of the different indicators considered in each component and the definition of adequacy
levels.
20
with access to all three underlying determinants of nutrition across states in Sudan. Most states
experienced a decrease (increase) in the percentage of children without (with) access to all three
determinants of nutrition between 2010 and 2014. For instance, in the Red Sea and Blue Nile States,
the percentage of children without access to any of the three determinants decreased by more than 20
percent between 2010 and 2014. However, in other states such as Gadarif and North Kordofan, the
reverse is observed—the percentage of children without access to any of the three determinants
increased by 11 percent and 4 percent, respectively. Changes in the percentage of children with
adequate access to all three determinants were moderate across Sudan. The largest improvements were
registered in the Northern, River Nile, and Red Sea States, where the percentage of children ages 0–
23 months with access to all three determinants increased by 10 percent, 7 percent, and 5 percent,
respectively.
21
Figure 4: Access to the Underlying Determinants of Nutrition of 0–23-month-old Children
(a) Underlying Determinants of Nutrition: 2014 (b) Underlying Determinants of Nutrition: 2010
60% 60%
50% 50%
40% 40%
30% 30%
20% 20%
10% 10%
0% 0%
National Rural Urban Bottom Top 20 National Rural Urban Bottom Top 20
20 percent 20 percent
percent percent
Adequate in ZERO determinants Adequate in ZERO determinants
Adequate in ALL THREE determinants Adequate in ALL THREE determinants
(c) Adequate Access to ZERO determinants (d) Adequate Access to ALL THREE determinants
Source: Authors’ calculation using MICS 2010 and 2014 data.
Access to Individual Indicators of Nutrition Drivers
Low adequate access to the underlying determinants of undernutrition appears to be largely
driven by low access to adequate health care. Less than 15 percent of children ages 0–23 months
had adequate access to health care in both 2010 and 2014. Children in the poorest households continue
to have the lowest access to health care in both 2010 and 2014. Compared to the other determinants,
22
adequate access to health care remains a major challenge to improving nutrition outcomes of Sudanese
children. Despite the inequalities in access to food security and care as well as WASH between poor
and rich and rural and urban households, access to these determinants is much higher than access to
health care—55 percent of 0–23-month-old children had access to adequate levels of WASH in 2014
(an increase from 35 percent in 2010). Although access to food security and care decreased by 6
percent between 2010 and 2014, 36 percent of children had adequate access to food security and care
in 2014.
Access to adequate levels of food security and care decreased between 2010 and 2014, driven largely
by increased food insecurity. Across Sudan, 36 percent of 0–23-month-old children had adequate
levels of food security and care in 2014, a slight decrease from 42 percent in 2010 (see Error! Not a
valid bookmark self-reference.a and Error! Not a valid bookmark self-reference.b). Inequalities
in access to adequate food security and care between rural and urban as well as poor and rich
households widened between 2010 and 2014. The gap in the percentage of 0–23-month-old children
with adequate access to food security and care between poor and rich households was 4 percentage
points in 2010 and 12 percentage points in 2014. Similarly, between rural and urban households, this
gap increased from 1 percentage point in 2010 to 3 percentage points in 2014. A closer look at the
individual components of food security and care shows a decrease in food security and significant
improvements in indicators of care such as early initiation of breastfeeding—59 percent of children
were breastfed within hours after birth in 2014 compared to 37 percent in 2010. Similarly, more than
80 percent of children met the age-appropriate breastfeeding thresholds in both 2010 and 2014. Food
security (an important determinant of nutrition outcomes and measured through the lens of minimum
acceptable diets) remains low and unequal between households. The percentage of children with
adequate minimum acceptable diets decreased from 43 percent in 2010 to 36 percent in 2014. The gap
between rich and poor households also widened from 4 percentage points in 2010 to 12 percentage
points in 2014. Increased food insecurity, particularly among the poorest households, is likely to be a
major driver of the increased prevalence of stunting in Sudan.
Access to adequate WASH albeit high is masked by large inequalities, particularly between rich and
poor households. The percentage of 0–23-month-old children with adequate WASH increased from
35 percent in 2010 to 55 percent in 2014 but was largely driven by increase in access for children from
rich and urban households (see Error! Not a valid bookmark self-reference.c and Error! Not a
valid bookmark self-reference.d). The gap in the percentage of children with adequate WASH
23
between rich and poor households remains disproportionately high—more than 70 percentage points
in both 2010 and 2014. Nearly all children under 24 months old from households in the top 20 percent
of the wealth distribution have adequate access to WASH whereas slightly above 20 percent of similar
children from the bottom 20 percent of the wealth distribution have adequate access to WASH. Access
to the individual components of WASH is equally marked by significant inequalities between rich and
poor households. Access to safe drinking water and improved sanitation (both at household and
community level) improved between 2010 and 2014. However, children from households at the
bottom of the wealth distribution continue to have low access levels to these components of WASH.
Availability of handwashing facilities is relatively low in Sudan, particularly in poor households.
Access to adequate health care remains low and unequal in Sudan despite improvements in
immunization compliance. Less than 15 percent of under-24-month-old children in Sudan had access
to adequate health care in 2010 and 2014 (see Figure 6a and Figure 6b). Among poor and rural
households, access to health care was much lower in both 2010 and 2014; less than 5 percent of
children in poor households and less than 10 percent of those in rural areas had adequate access to
health care. In rich and urban households, moderate improvements in access to health care were
observed between 2010 and 2014. Nationally, immunization compliance rates increased from 49
percent in 2010 to 60 percent in 2014 and are less unequal between rich and poor as well as urban and
rural households. Inequalities in the use of prenatal services and health professional assisted delivery
remain wide between poor and rich as well as rural and urban households. It is thus surprising that
while immunization compliance has improved, which illustrates increased use of postnatal services,
the use of health centers for prenatal visits and/or delivery remains low in Sudan. Therefore,
addressing the inadequate access to health care requires interventions to improve access to and use of
health centers, particularly in poor and rural households.
24
Figure 5: Components of Food Security and Care and WASH for Children Ages 0–23 Months
(a) Components of Food Security and Care: 2014 (b) Components of Food Security and Care: 2010
Adequate Food Security Adequate Food Security
and Care and Care
Age Appropriate Age Appropriate
Breastfeeding Breastfeeding
Early Initiation of Early Initiation of
breastfeeding breastfeeding
Minimum Acceptable
Minimum Acceptable Diet Diet
0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100%
Top 20 percent Bottom 20 percent Top 20 percent Bottom 20 percent
Urban Rural Urban Rural
National National
(c) Components of WASH: 2014 (d) Components of WASH: 2010
Adequate level of WASH Adequate level of WASH
indicators indicators
Appropriate Feces disposal Appropriate Feces
Availability of Handwashing disposal
facilitiy Community level
Community level sanitation sanitation
Access to Improved
Access to Improved
Sanitation
Sanitation
Access to Safe Drinking Access to Safe Drinking
Water Water
0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100%
Top 20 percent Bottom 20 percent Top 20 percent Bottom 20 percent
Urban Rural Urban Rural
National National
Source: Authors’ calculation using MICS 2010 and 2014 data.
25
Figure 6: Components of Health Care for Children Ages 0–23 Months
(a) Components of Health Care: 2014 (b) Components of Health Care: 2010
Adequate Level of Health Adequate Level of Health
Indicators Indicators
Immunization compliance Immunization compliance
Health Professional Health Professional
Assisted Birth Assisted Birth
Use of Prenatal Services Use of Prenatal Services
0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80%
Top 20 percent Bottom 20 percent Top 20 percent Bottom 20 percent
Urban Rural Urban Rural
National National
Source: Authors’ calculation using MICS 2010 and 2014 data.
Joint Access to the Underlying Determinants of Nutrition
Of the three nutrition drivers considered in this report, access to adequate health care continues to be
low for Sudanese children (particularly those in rural areas and from households in the bottom 40
percent of the wealth distribution). Figure 7 shows that in both 2010 and 2014, more children ages
between 0 and 23 months had joint access to adequate levels of food security and WASH indicators
only than food security and health care only or WASH and health care only. For instance, across
Sudan, in 2010, 15 percent of 0–23-month-old children had adequate access to food security and care
and WASH only (and inadequate access to health care). On the other hand, only 1 percent and 5
percent of children had adequate access to food security and care and health care only as well as
WASH and health care only, respectively. In 2014, 11 percent of children ages 0–23 months in Sudan
had adequate access to both food security and care and WASH only, but only 2 percent of 0–23-
month-old children had joint access to adequate levels of food security and care and health care or
WASH and health care. In rural areas and among households in the bottom 20 percent of the wealth
distribution, joint access to adequate levels of the underlying determinants of nutrition are lower,
particularly when access to health care is considered. In both 2010 and 2014, less than 5 percent of
children from rural areas or households in the bottom 40 percent of the wealth distribution had
adequate joint access to food security and care and health care or WASH and health care. Access to
adequate food security and care and WASH for these children remains below the national average and
26
decreased between 2010 and 2014. These results highlight the extent to which low access to adequate
health care remains a main driver of inadequate access to the underlying determinants of
undernutrition.
Figure 7: Joint Access to Nutrition Drivers
(a) 2014 (b) 2010
25% 25%
20% 20%
15% 15%
10%
10%
5%
5%
0%
0% National Rural Urban Bottom Top 20
National Rural Urban Bottom 20 Top 20 20 percent
percent percent percent
Food Security/Care & WASH Only Food Security/Care & WASH Only
Food Security/Care & Health Care Only Food Security/Care & Health Care Only
WASH & Health Care Only WASH & Health Care Only
Source: Authors’ calculation using MICS 2010 and 2014 data.
The description of the nature of stunting in Sudan above provides an overview and several insights to
inform responses. The heterogeneity in the prevalence of stunting of across states and between rural
and urban shows the degree to which rural children remain most vulnerable to stunting. Similarly,
across households, poor households (particularly those in the bottom 20 percent of the wealth
distribution) and children whose mothers have no formal education remain disproportionately
stunted. Large inequalities in access to adequate levels of the underlying determinants of
undernutrition exist between rural and urban and rich and poor households. More rural and poor
households have inadequate access to all the three determinants, food security and care, WASH, and
health care, than their urban and rich counterparts. Access to adequate health care remains significantly
low for most households in Sudan, particularly rural and poor households. A closer look at joint access
to these determinants shows that inadequate access to health care remains a main barrier for poor and
rural households’ access to the adequate levels of these underlying determinants of undernutrition.
These features of the nature of stunting in Sudan are fairly consistent with observed trends from recent
data from Sub-Saharan African countries (Skoufias, Vinha, and Sato 2019).
27
Stunting and Children’s Access to the Underlying Determinants of Undernutrition
This section examines the relationship between stunting and the number of determinants of
undernutrition accessed at the same time. By means of probability density functions (PDFs) and
cumulative density functions (CDFs) of children’s HAZ and access to different numbers of the
underlying determinants of undernutrition, we examine the relationship between having access to one,
two, or all three drivers of nutrition and stunting. Figure 8 presents the CDFs and PDFs for 2010 and
2014 and for various access levels to the underlying determinants of undernutrition: zero, one, two,
and three. The black vertical line in each graph at −2 shows the WHO threshold of HAZ used to
define stunting. The intersection of this line with each CDF, denoted by the dotted/dashed lines,
represents the prevalence of stunting among children with that access level. Similarly, in the PDFs,
the area under the curve and left of the −2 threshold represents stunting.
The prevalence of stunting is higher among children with access to zero underlying determinants and
lower among children with access to all three underlying determinants of undernutrition. The CDFs
of HAZ for children with access to zero, one, two, and three determinants of undernutrition presented
in Figure 8a and Figure 8b illustrate correlations between stunting and access to the drivers of
nutrition. In both 2010 and 2014, the prevalence of stunting was significantly lower among children
with access to more drivers of nutrition. For instance, 37 percent children under 24 months of age
without access to any of the underlying determinants of undernutrition were stunted in 2010,
compared to only 6 percent of children in the same age group with access to all three determinants of
undernutrition. Similarly, in 2014, 38 percent of children without access to any of the underlying
determinants were stunted compared to 14 of children with access to all three. It can also be observed
from the CDFs that the largest reductions in stunting are associated with increases in access from
none (0) to any one nutrition driver and from any one driver to simultaneous access to any two drivers
of nutrition. For instance, in both 2010 and 2014, stunting rates were lowest among children with
access to all three nutrition drivers (6 percent and 14 percent, respectively), followed by children with
simultaneous access to any two nutrition drivers (17 percent and 19 percent, respectively) and children
with access to any one nutrition driver (25 percent and 27 percent, respectively). Stunting rates were
highest among children without access to any nutrition driver (37 percent and 38 percent, respectively).
The PDFs (in Figure 8c and Figure 8d) summarize the same information in a different way. Children
with better access to the underlying determinants of undernutrition have a higher mean HAZ (the
PDF shifts right) and most of the differences in the PDFs for different access levels are in the lower
28
left tail of the bell-shaped curve, which represents stunting. It is easy to observe that in both 2010 and
2014, stunting was higher among children without access to any nutrition driver and lowest among
children with access to all three drivers; in Figure 8c and Figure 8d, the area under the blue PDF and
to the left of the −2 threshold is larger than the area under the orange PDFs and to the left of the −2
threshold. Similarly, stunting is lower among children with simultaneous access to any two drivers
than children with access to only one nutrition driver.
In both the PDFs and CDFs, it can be observed that differences in the prevalence of stunting due to
inequalities in access to the underlying determinants of undernutrition were larger in 2010 than in
2014. Fewer children with adequate levels in all three determinants were stunted in 2010 than in 2014.
Furthermore, the difference in the prevalence of stunting between children with adequate levels in all
three determinants and children with adequate levels in only two determinants was larger in 2010 than
in 2014. In 2010, only 6 percent of children with adequate levels in all three drivers of nutrition were
stunted compared to 14 percent in 2014. The difference in the prevalence of stunting between children
with adequate levels in all three drivers and those with adequate levels in only two was 9 percentage
points in 2010 and 5 percentage points in 2014. The PDFs also illustrate a similar story—the area
under the curve and left to the −2 threshold for children with adequate level in all three determinants
is smaller in 2010 than in 2014 and much smaller than for children with adequate access to only two
determinants in 2010 than in 2014.
29
Figure 8: Cumulative and Probability Density Functions of HAZ and Nutrition Drivers
(a) CDF 2010 (b) CDF 2014
(c) PDF 2010 (d) PDF 2014
Source: Authors’ calculation using MICS 2010 and 2014 data. Estimates are based on children under 24 months of age.
30
Estimating the Impact of the Underlying Determinants of Undernutrition on Stunting
The preceding sections describe the nature of stunting and access to drivers of nutrition in Sudan by
highlighting differences in the prevalence of stunting across states and households in Sudan as well as
the relationship between stunting and access to nutrition drivers. The figures presented summarize
patterns of stunting and changes between 2010 and 2014. In particular, the CDFs and PDFs (Figure
8) illustrate the correlation between stunting and access to nutrition drivers. However, these analyses
ignore the potential influence that individual child, parental, and regional characteristics may have on
the relationship between stunting and access to one or more determinants of nutrition. In this section,
we complement the description of the nature of stunting by estimating the extent to which the
underlying determinants of undernutrition individually and jointly affect stunting among 0–23-month-
old children in Sudan while controlling for these attributes. It is important to highlight that the
estimated parameters from the following models capture correlations between stunting and having
adequate levels of access to one or more of the underlying drivers of nutrition identified by the
UNICEF framework. The additional controls included are aimed at minimizing the influence of
confounding factors on the relationship between having adequate access to the underlying
determinants of undernutrition and stunting.9 Thus, we interpret the results with these caveats in mind.
The methodology adopted closely follows the work of Skoufias, Vinha, and Sato (2019).
In the first specification, we examine the effect of varying access to nutrition drivers on stunting by
fitting the following logit model:
������������������������������������������������������ = ������0 + ������1 ������������������1������������ + ������2 ������������������2������������ + ������3 ������������������3������������ + ������������������ + ������������ + ������������������ , (1)
where the dependent variable ������������������������������������������������������ is a binary variable taking the value of 1 if child ������ in state ������
age between 0 and 23 months is stunted (that is, has a HAZ less than −2 standard deviation for the
reference WHO population) and 0 otherwise. The variables, ������������������1������������ , ������������������2������������ , and ������������������3������������ , are binary
variables that take the value of 1 if the child has adequate level in any one, any two, or all three nutrition
drivers, respectively; ������������������ captures a set of control variables relating to child characteristics (gender,
birth month, birth order, and so on); parental characteristics (mother’s age, education level, marital
status, and so on); and household characteristics (number of household members, number of children
9 Some studies estimate reduced form models that capture budget constraints and so on (see Barrera 1990).
31
under five years of age, location of household [rural or urban], and wealth of household). ������������ is state-
level fixed effects, and ������������������ is the error term.
In the specification described earlier, the constant term ������0 provides an estimate of the probability of
being stunted for children in the reference group, that is, children without access to adequate levels in
any of the three nutrition drivers. The other parameters, ������1, ������2, and ������3, provide estimates of the
marginal decline in the probability of being stunted for children with access to any one, any two, or
all three nutrition drivers, respectively, relative to children in the reference group. It is important to
state that the parameter estimates from this specification do not imply causal inference on the impact
of access to nutrition drivers on stunting. The possibility of omitted variable bias cannot be entirely
ruled out. It is for this reason that additional control variables and state fixed effects are included to
minimize such biases.
In a second specification, we examine the effect of joint access to nutrition drivers on stunting. Figure
7 shows that simultaneous access to nutrition drivers is associated with a decline in the prevalence of
stunting. It is thus important to identity which of these drivers is associated with a more significant
decline in stunting rates. Insights from such analysis are particularly important for policy targeting,
especially for governments such as Sudan facing constrained fiscal space. We examine this using the
following logit model:
������������������������������������������������������ = ������0 + ������������������ ������������������������ + ������������ ������������������ + ������������ ������������������ + ������������������������ ������������_������������������ + ������������������������ ������������_������������������ (2)
+ ������������������ ������_������������������ + ������������������������������ ������������������3������������ + ������������������ + ������������ + ������������������
The dependent variable ������������������������������������������������������ , the set of control variables ������������������ , state fixed effects ������������ , and error
term ������������������ are as defined in equation (1). The effect of having adequate access to one nutrition driver or
a combination of two or all three nutrition drivers on the probability of being stunted (assuming child,
parental and household characteristics are constant) is captured by the ������ parameter estimates (except
������0 which captures the probability of being stunted of children in the reference category, that is, those
who have inadequate access to all three nutrition drivers). For instance, the estimated value of ������������������
represents the estimated decline in the probability of being stunted among children who have adequate
access to food security and care only (FC = 1) but inadequate access to WASH and health care, relative
to the probability of a child in the reference group being stunted. The estimated values of ������������ and ������������
have similar interpretations for adequate access to WASH only and health care only, respectively.
32
Similarly, the effect of having simultaneous access to any two and all three nutrition drivers on the
probability of being stunted is obtained from parameter estimates of ������������������������ , ������������������������ , ������������������ , and ������������������������������ .
We estimate these specifications for each round of data, 2010 and 2014, separately using a logit model.
It is important to highlight that fixed effects estimators on pseudo panel data constructed using the
two rounds of cross-sectional data10. Such techniques will allow us estimate the effects of the
underlying determinants on nutrition with better precision. However, the recent changes in Sudan’s
geopolitical landscape between 2010 and 2014, particularly the secession of the South in 2011, makes
the assumptions underpinning a pseudo panel hard to justify in this case.
Empirical Results
Having access to adequate levels of nutrition drivers is associated with lower probability of stunting.
In both 2010 and 2014, children under 24 months old with access to all three underlying determinants
of nutrition were, respectively, 23.4 percent and 17.4 percent less likely to be stunted than children
without adequate access to any of the three determinants. Furthermore, having adequate access to
some nutrition drivers is better than having adequate access to none; children who have access to
adequate levels to some (one or two of the three) of the nutrition drivers are significantly less likely to
be stunted than those without adequate access to any of the three drivers. For instance, in 2014,
children with adequate access to at least one determinant were 7.5 percent less likely to be stunted
than those without adequate access to any of the three determinants. Similarly, children with adequate
access to any two determinants were 13.4 percent less likely to be stunted than those without adequate
access to any. Similar effects are observed from the 2010 data. These estimates are robust to state
fixed effects as well as child, mother, and household covariates.
Table 2: Marginal Effects: Adequate Access to Underlying Determinants of Nutrition
2010 2014
Variables
(1) (2) (3) (1) (2) (3)
Adequate in 1 −0.123*** −0.114*** −0.0733*** −0.109*** −0.0964*** −0.0750***
determinants (0.0167) (0.0162) (0.0170) (0.0216) (0.0213) (0.0220)
Adequate in 2 −0.201*** −0.187*** −0.125*** −0.187*** −0.163*** −0.134***
determinants (0.0227) (0.0235) (0.0257) (0.0256) (0.0279) (0.0304)
All three determinants -0.310*** -0.294*** −0.234*** −0.243*** −0.213*** −0.174***
(0.0294) (0.0343) (0.0437) (0.0440) (0.0493) (0.0587)
State Fixed Effects — Yes Yes — Yes Yes
Additional Controls Yes Yes
Observations 4,846 4,846 4,769 4,580 4,580 4,273
Note: (1) All specifications are estimated for children under 24 months old.
10
See (Christiaensen & Subbarao, 2005) for an application of such techniques.
33
(2) Marginal effects are based on coefficient estimates obtained from the logit model in equation (1).
(3) Base category in each specification is children with inadequate access to all three determinants.
(4) Additional controls include child-level characteristics (such as birth month, gender of child, birth order except in
2010); mother-level characteristics (such as age, education level, marital status, and so on); and household characteristics
(such as household size, number of children under five, wealth quintile, gender of head, and so on).
(5) Household weights applied.
Robust standard errors clustered in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.
The effects of access to adequate levels of nutrition drivers on stunting described earlier are masked
by significant heterogeneity across space (rural/urban), income (bottom 40 and top 20 of the wealth
distribution), and gender (male and female children). Using both 2010 and 2014 rounds of data, we
draw some insights on the extent of the heterogeneity in the effect of access to adequate levels of
nutrition drivers on stunting across households and over time as shown in Table 3. Estimates from
both rounds of data show that patterns between rural and urban children, bottom 40 and top 20
percent of wealth distribution, as well as boys and girls have changed overtime. For instance, the effect
of adequate access to all three determinants on the likelihood of stunting was higher among rural
children than urban children in 2010 (30.7 percent compared to 26.2 percent), while the reverse was
observed in 2014. Among urban children, adequate access to all three determinants is associated with
a 18.5 percent decrease in the probability of stunting relative to those without adequate access to any
of the three determinants in 2014. In rural areas, adequate access to one or two nutrition drivers yields
significantly more reduction in the probability of stunting—these children are on average 8.5 percent
and 13.4 percent, respectively, less likely to be stunted than children without adequate access to any
nutrition driver. Access to some nutrition drivers has a larger effect on stunting outcomes for rural
children than urban children.
Overall, adequate access to the underlying determinants of nutrition yields larger effects on the
stunting outcomes of children from the poorest households than those of children from the richest
households. For children from households in the bottom 40 percent of the wealth distribution, access
to nutrition drivers significantly lowers their probability of stunting. This is true for children with
access to all as well as those with access to some of the nutrition drivers. In 2014, children from these
households with adequate access to one nutrition driver decrease their probability of stunting by 9.6
percent, access to two is associated with a 17.7 percent decrease in their probability of stunting, and
children with access to all three nutrition drivers were 28.8 percent less likely to be stunted compared
to children without adequate levels of access to any of the nutrition drivers. Compared to their
counterparts from households in the richest 20 percent of the wealth distribution, differences in access
34
to the underlying determinants of nutrition do not appear to have a statistically significant effect on
stunting outcomes.
Among both boys and girls, better access to adequate levels of nutrition drivers lowers their probability
of being stunted with the gains from improved access being larger for girls in 2014. In 2010, gains
from adequate access to nutrition drivers were larger for boys than girls —boys with adequate access
in one, two, and all three nutrition drivers were 8.8 percent, 16.1 percent, and 25.8 percent,
respectively, less likely to be stunted than boys without adequate access to any of the nutrition drivers.
For girls, on the other hand, adequate access to one, two, and three nutrition drivers was only
associated with 6.2 percent, 9.1 percent, and 21 percent reductions, respectively, in the likelihood of
stunting, compared to girls without adequate access to any nutrition driver. However, estimates from
the latest round of data show that girls are gaining more from having access to nutrition drivers. Girls
with adequate access to all three nutrition drivers are on average 23.4 percent less likely to be stunted
than girls without adequate access to any nutrition driver. The effect on the comparable category of
boys is statistically insignificant. Similarly, girls with access to any one or any two nutrition drivers are
also 7.2 percent and 13.6 percent, respectively, less likely to be stunted. For boys with similar access
levels, the effect on their probability of stunting is 7.5 percent and 12.9 percent, respectively. Gains
from improvements in access to adequate levels of nutrition drivers appear to be larger for girls than
boys, particularly in 2014. Girls with adequate access to all three nutrition drivers gained an additional
9 percentage point reduction in their probability of being stunted compared to girls with adequate
access to only two nutrition drivers.
35
Table 3: Marginal Effects: The Heterogeneity of the Effects of Adequate Access to Underlying Determinants of Nutrition
2010 2014
Variables
Rural Urban Bottom 40 Top 20 Boys Girls Rural Urban Bottom 40 Top 20 Boys Girls
Adequate in 1 −0.0662*** −0.0768*** −0.0813*** −0.0353 −0.0881*** −0.0623*** −0.0848*** -0.0534 −0.0961*** 0.0623 −0.0754** −0.0721**
determinant (0.0186) (0.0285) (0.0253) (0.0739) (0.0247) (0.0238) (0.0249) (0.0657) (0.0315) (0.0665) (0.0313) (0.0308)
Adequate in 2 −0.131*** −0.113*** −0.141** −0.0328 −0.161*** −0.0905*** −0.134*** −0.131** −0.177*** 0.0444 −0.129*** −0.136***
determinants (0.0388) (0.0368) (0.0593) (0.0763) (0.0359) (0.0345) (0.0384) (0.0651) (0.0536) (0.0542) (0.0431) (0.0395)
All 3 −0.307** −0.262*** −0.113 −0.258*** −0.210*** −0.133 −0.185** −0.288*** −0.105 −0.234***
determinants (0.148) (0.100) (0.0947) (0.0723) (0.0457) (0.0918) (0.0803) (0.0871) (0.0932) (0.0533)
State fixed Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
effects
Additional Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
controls
Observations 3,446 1,323 2,059 601 2,407 2,362 3,082 1,191 1,942 543 2,177 2,096
Note: Robust standard errors clustered in parentheses. ***p < 0.01, **p < 0.05, *p < 0.
36
Although adequate access to food security and care significantly lowers the probability of stunting, the
effect is larger when combined with access to health care. Holding, child, parental, household, and
state-specific factors constant, having adequate access to food security and care only yields large
reductions in a child’s probability of being stunted (see Table 4). Children with access to adequate
levels of food security and care only were 9.7 percent and 20.4 percent less likely to be stunted in 2010
and 2014, respectively, than those without adequate access to any of the nutrition drivers. Compared
to the effects of having adequate access to WASH only or health care only, the effect of having
adequate access to food security and care only is larger and statistically significant on the probability
of being stunted. The effect of food security and care on stunting is larger when combined with access
to adequate health care, although the magnitude decreased between 2010 and 2014. The probability
of being stunted associated with having simultaneous access to adequate food security and care and
health care was 22.6 percent and 21.2 percent in 2010 and 2014, respectively. This implies that the
marginal decline in the probability of being stunted associated with adding access to adequate health
care for children with adequate access to food security and care was 12.9 percentage points in 2010
[(−0.226) − (−0.0965) = −0.129] and about 1 percentage point in 2014 [(−0.21) − (−0.20) = −0.01].
The gains from adding adequate access to WASH for children with adequate access to food security
and care are not as large. Similarly, children with joint access to adequate WASH and health care were
16.6 percent less likely to be stunted in 2010 than those without adequate access to any of the
underlying nutrition drivers. The effect in 2014 was statistically insignificant once child, mother,
household, and state-specific fixed effects are accounted for.
The large nutritional gains from having adequate food security and care offer one possible explanation
for the increase in the rate of stunting in Sudan between 2010 and 2014. Adequate access to food
security and care decreased significantly in rural areas (from 42 percent in 2010 to 35 percent in 2014)
and among the poorest households (from 39 percent in 2010 to 33 percent in 2014), thereby resulting
in large increases in stunting. One possible policy implication of these results, particularly in a country
such as Sudan where the government faces constrained fiscal space, is that in identifying priority
sectors for responses to tackle stunting, ensuring access to adequate food security and care for
deprived children should be a primary one. For children who already have adequate access to food
security and care only, resources can be directed toward ensuring that they have simultaneous access
to health care to further improve their nutritional outcomes.
37
Table 4: Marginal Effects: Joint Access to Underlying Determinants of Nutrition
2010 2014
Variables
(1) (2) (3) (1) (2) (3)
Adequate food security/care −0.120*** −0.122*** −0.0965*** −0.208*** −0.209*** −0.204***
only (0.0177) (0.0173) (0.0177) (0.0267) (0.0268) (0.0315)
Adequate WASH only −0.0984*** −0.0798*** −0.0220 −0.0706*** −0.0510** −0.0236
(0.0220) (0.0227) (0.0256) (0.0227) (0.0231) (0.0246)
Adequate health care only −0.148* −0.133 −0.102 0.0844 0.0891* 0.136**
(0.0815) (0.0829) (0.0824) (0.0542) (0.0531) (0.0595)
Adequate food security/care −0.173*** −0.160*** −0.0933*** −0.181*** −0.160*** −0.133***
and WASH only (0.0285) (0.0290) (0.0301) (0.0319) (0.0331) (0.0356)
Adequate food security/care −0.293*** −0.289*** −0.226*** −0.215** −0.214** −0.212**
and health care only (0.0803) (0.0787) (0.0809) (0.0863) (0.0861) (0.0944)
Adequate WASH and health −0.309*** −0.268*** −0.166** −0.176*** −0.113** −0.0558
care only (0.0801) (0.0767) (0.0773) (0.0483) (0.0536) (0.0551)
Adequate all 3 determinants −0.427*** −0.389*** −0.281*** −0.261*** −0.215*** −0.166**
(0.0867) (0.0894) (0.0896) (0.0654) (0.0665) (0.0721)
State fixed effects — Yes Yes — Yes Yes
Additional controls Yes Yes
Observations 4,846 4,846 4,769 4,580 4,580 4,273
Note: (1) All specifications are estimated for children under 24 months old.
(2) Marginal effects are based on coefficient estimates obtained from the logit model in equation (2).
(3) Base category in each specification is children with inadequate access to all three determinants.
(4) Additional controls include child-level characteristics (such as birth month, gender of child, birth order except in
2010); mother-level characteristics (such as age, education level, marital status, and so on); and household characteristics
(such as household size, number of children under five, wealth quintile, gender of head, and so on).
(5) Household weights applied.
Robust standard errors clustered in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.
Gains from adequate access to food security and care have improved and were larger for girls, children
in rural areas, and those from poorer households in 2014. While adequate access to food security and
care significantly lowers the probability of stunting, the magnitude of this effect differs across children
based on their location, wealth, and gender (see Table 5). For instance, the 2010 data show that the
effect was slightly larger for children from urban areas and boys, while the reverse is observed in the
2014 data. Rural children with adequate access to food security and care were 22.1 percent less likely
to be stunted than children without adequate access to any nutrition driver—an improvement from
9.5 percent in 2010. Similarly, the probability of being stunted associated with having adequate access
to food security and care was 26.4 percent for children from households in the bottom 40 percent of
the wealth distribution in 2014 (from 11.9 percent in 2010) and 22.2 percent for girls in 2014 (from
7.7 percent in 2010). Given that between 2010 and 2014, stunting rates increased in rural areas (see
Figure 2) and among the poorest households (see Figure 3), these results provide useful insights for
policy response. Improving access to adequate food security and care for children in rural areas and
those from the poorest households will significantly contribute to lowering stunting rates in Sudan.
38
Box 1: Comparing Sudan with Other Countries in Sub-Saharan Africa
In the graphs below, we compare results from the 2010 and 2014 MICS data from Sudan and results from
2010 or later DHS data from 33 other countries in Sub-Saharan presented in the All Hands on Deck report
(Skoufias, Vinha, and Sato 2019). Although as documented in the report, there exist significant heterogeneity
across the 33 Sub-Saharan African countries which is likely to mask the effects of access to nutrition drivers
on stunting, the results provide useful insights on the state of stunting in the sub-region and hence an
important benchmark for comparison. A striking difference in the comparison is the larger effect of
adequate access to food security and care on stunting in Sudan relative to other countries in Sub-Saharan
Africa. In both 2010 and 2014, the marginal effect of adequate access to food security and care on the
probability of being stunted was significantly larger in Sudan. For instance, under budgetary constraints, it
appears the greatest “bang for the buck” in reducing stunting in other Sub-Saharan African countries is
through expanded access to health care (see Panel b) below). In Sudan, using the latest round of the MICS
data collected in 2014, ensuring adequate access to food security and care appears to yield the largest gains
for reducing stunting (see Panel a) below). The increased prominence of food security and care in reducing
stunting in Sudan may be sensitive to recent macroeconomic events- particularly rising prices; which have
characterized the country following the independence of the South.
However, in the case of simultaneous access to the underlying drives of nutrition, data from both Sudan
and other countries in sub-region illustrate large gains from joint access to food security and care; and health
care. Synergies of interventions by nutrition and health sectors may contribute to significantly lowering
stunting among 0-23 month old children in Sudan as well as in other countries in the Sub-region. While the
implementation of multisectoral strategies to tackle stunting is likely to vary across countries due to
budgetary constraints, effectiveness of coordination systems and incentive mechanisms among other
factors, certain similarities exist. By combining insights from country-specific studies on stunting and
drawing lessons from other countries which are effectively implementing multisectoral approaches to tackle
stunting, significant gains can be registered.
(a) Sudan (b) Sub-Saharan Africa
Source: Panel a)Authors’ calculation using MICS 2010 and 2014 data., Panel b) Skoufias, Vinha, and Sato 2019, p13.
39
On joint access to nutrition drivers, significant heterogeneity exists across space, wealth, and gender:
for boys, children from poor households, and those from urban areas, joint access to food security
and care and WASH has larger effects in lowering the probability of stunting; for girls, joint access to
food security and care and health care has a larger effect; and for children in rural areas, joint access
to WASH and health care yields larger gains toward lowering stunting. As highlighted earlier, gains
from joint access to food security and care and health care are particularly large in Sudan. In 2010, the
effect of simultaneous access to food security and care and health care on stunting was particularly
large for children in rural areas—boys and girls. However, data from 2014 show that the effect is still
large and statistically significant—but for girls. In 2014, girls with adequate access to both food security
and care and health care were 22.8 percent less likely to be stunted than girls with inadequate access
to any of the three nutrition drivers.
On the other hand, the effect of joint access to food security and care and WASH on the probability
of being stunted is larger for boys (than girls), children in urban areas (than those in rural areas) and
children from the poorest households (than those from the richest households). The probability of
being stunted associated with having simultaneous access to food security and care and WASH was
13.1 percent and 13.7 percent less for boys in 2010 and 2014, respectively; 10.1 percent and 14.7
percent less for children in urban areas in 2010 and 2014, respectively; and 12.3 percent and 22.7
percent less for children from households in the bottom 40 percent of the wealth distribution in 2010
and 2014, respectively. In each of these cases, the reference group is children without adequate access
to any of the three nutrition drivers. In rural areas, although joint access to food security and care and
health care has a large effect in lowering stunting, the effect of having joint access to WASH and
health care is larger. Rural children with joint access to WASH and health care were 28.7 percent and
15.3 percent less likely to be stunted in 2010 and 2014, respectively. These results provide further and
more specific insights to inform responses to tackle stunting. These results also highlight the
importance of access to adequate food security and care in improving nutrition outcomes of Sudanese
children. Additional insights for complementing access to food security and care for children across
space, wealth, and gender are also provided. These additional insights are particularly useful for
effectively identifying priorities and targeting most affected children
40
Table 5: Marginal Effects: The Heterogeneity of Joint Access to Underlying Determinants of Nutrition
2010 2014
Variables Bottom
Rural Urban Bottom 40 Top 20 Boys Girls Rural Urban Top 20 Boys Girls
40
Adequate −0.0949*** −0.114*** −0.119*** 0.0283 −0.122*** −0.0773*** −0.221*** −0.150** −0.264*** 1.543*** −0.184*** −0.222***
food (0.0206) (0.0370) (0.0266) (0.113) (0.0250) (0.0261) (0.0370) (0.0766) (0.0387) (0.241) (0.0467) (0.0425)
security/care
only
Adequate −0.00521 −0.0512 0.0171 −0.0480 −0.0211 −0.0231 −0.0327 −0.00957 −0.0127 1.654*** −0.0196 −0.0243
WASH only (0.0322) (0.0415) (0.0428) (0.0713) (0.0365) (0.0327) (0.0302) (0.0532) (0.0376) (0.229) (0.0330) (0.0335)
Adequate −0.120 −0.0901 −0.122 −0.0028 −0.0816 −0.155 0.162** 0.129 0.0330 0.166**
health care (0.0947) (0.130) (0.148) (0.143) (0.111) (0.109) (0.0677) (0.0828) (0.102) (0.0741)
only
Adequate −0.0934** −0.101** −0.123* −0.0218 −0.131*** −0.0529 −0.123** −0.147*** −0.227*** 1.618*** −0.137*** −0.124***
food/care (0.0412) (0.0414) (0.0693) (0.0784) (0.0413) (0.0400) (0.0481) (0.0517) (0.0742) (0.212) (0.0437) (0.0430)
and WASH
only
Adequate −0.251** −0.154 −0.272 0.155 −0.232* −0.221** −0.165 — −0.116 — −0.206 −0.228**
food/care (0.100) (0.121) (0.168) (0.109) (0.121) (0.0890) (0.101) (0.142) (0.132) (0.115)
and health
only
Adequate −0.287* −0.111 — −0.178* −0.219** −0.129 −0.153* 0.00716 −0.184 1.658*** −0.00291 −0.101
WASH and (0.164) (0.0834) (0.0947) (0.106) (0.110) (0.0810) (0.0713) (0.153) (0.226) (0.0891) (0.0672)
health care
only
Adequate all 3 −0.296** −0.255** — −0.122 −0.286** −0.274*** −0.134 −0.173* −0.370** 1.586*** −0.0795 −0.278***
determinants (0.149) (0.102) (0.0912) (0.133) (0.104) (0.101) (0.0885) (0.178) (0.242) (0.0950) (0.0968)
State fixed Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
effects
Additional Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
controls
Observations 3,446 1,323 2,057 601 2,407 2,362 3,082 1,191 1,942 548 2,177 2,096
Note: Robust standard errors clustered in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.
41
Among food security and care indicators, food security yields the largest gains on children’s nutritional
outcomes. Controlling for child, mother, and household characteristics as well as state fixed effects,
children who are food secured (that is, have adequate access to quality diets) were 10.6 percent less
likely to be stunted than those without adequate access to any of the nutrition drivers in 2014. The
effect using the 2010 data was significant but only when geographic location fixed effects are
accounted for (see Table 6). Among the care indicators, age-appropriate breastfeeding has a large
effect on children’s probability of being stunted. Controlling for state fixed effects, children who are
age-appropriately breastfed were 4 percent less likely to be stunted than those without adequate access
to any of the nutrition drivers. However, the effect is statistically insignificant when child, mother, and
household characteristics are controlled for in the 2010 and 2014 data. In both years, the probability
of being stunted associated with early initiation of breastfeeding is statistically insignificant.
Among the WASH indicators, access to improved sanitation facilities has the largest effect on
children’s probability of being stunted. Children with access to improved sanitation (such as flush
toilet, ventilated or slabbed pit latrine, or a composting toilet) are on average less likely to be stunted.
In 2010, the effect of having access to improved sanitation on stunting is larger than the effect of
access to the other WASH indicators. Children with improved sanitation were 4 percent less likely to
be stunted in 2010 than those without adequate access to any of the nutrition drivers. A similar effect
is observed in 2014, but only when state fixed effects and child, mother, and household characteristics
are not controlled for.
Among the health care access indicators, immunization yields the largest reductions in the probability
of being stunted. Controlling for child, mother, and household characteristics and state fixed effects,
children who are in compliance with their immunization requirements were 13.7 percent and 11.1
percent less likely to be stunted in 2010 and 2014, respectively. Nutritional gains from immunization
compliance among Sudanese children are larger than gains from access to any of the individual
indicators of the three nutrition drivers considered in this report. Other indicators of access to health
care which also reduce the probability of being stunted include health facility-assisted delivery. The
probability of being stunted for children who were delivered by health professionals decreased by 4.8
percent in 2010 when state fixed effects were included. However, when child, mother, and household
characteristics are added, the effect (although still negative) turns statistically insignificant.
42
Table 6: Marginal Effects: Components of Underlying Determinants of Nutrition
2010 2014
Variables
(1) (2) (3) (1) (2) (3)
Food security and care indicators
Minimum acceptable diet −0.0330* −0.0365* −0.0291 −0.110*** −0.116*** −0.106***
(0.0191) (0.0190) (0.0191) (0.0233) (0.0233) (0.0280)
Early initiation of breastfeeding 0.0364 0.0330 0.0278 −0.00497 −0.00736 −0.0261
(0.0244) (0.0236) (0.0235) (0.0249) (0.0244) (0.0257)
Age appropriate breastfeeding −0.0384* −0.0401** −0.0312 −0.0225 −0.0185 −0.0273
(0.0202) (0.0198) (0.0200) (0.0236) (0.0238) (0.0253)
WASH indicators
Safe water −0.0263 −0.00710 0.00131 −0.0275 −0.0297 −0.0151
(0.0176) (0.0176) (0.0176) (0.0214) (0.0217) (0.0228)
Improved sanitation −0.0824*** −0.0750*** −0.0426* −0.0488** −0.0264 0.00626
(0.0194) (0.0207) (0.0223) (0.0224) (0.0241) (0.0233)
Community sanitation −0.0264 −0.0353* −0.0196 0.0243 0.0418* 0.0577**
(0.0210) (0.0208) (0.0220) (0.0242) (0.0240) (0.0239)
Handwashing facilities — — — −0.0246 −0.0163 −0.0167
(0.0234) (0.0244) (0.0243)
Feces disposal 0.00305 0.00908 0.0222 −0.0245 −0.0319 −0.0348
(0.0186) (0.0194) (0.0192) (0.0232) (0.0241) (0.0218)
Health care indicators
Use of prenatal services −0.0214 −0.0258* −0.0137 −0.0235 −0.0181 −0.00332
(0.0161) (0.0156) (0.0151) (0.0181) (0.0193) (0.0208)
Health facility assisted delivery −0.0586*** −0.0484** −0.0358 −0.0306 −0.0112 0.00757
(0.0212) (0.0237) (0.0245) (0.0235) (0.0251) (0.0256)
Immunization compliance −0.151*** −0.147*** −0.137** −0.0990*** −0.0967*** −0.111***
(0.0178) (0.0178) * (0.0202) (0.0205) (0.0238)
(0.0192)
State fixed effects — Yes Yes — Yes Yes
Additional controls — — Yes — — Yes
Observations 4,846 4,846 4,769 4,580 4,580 4,273
Note: Robust standard errors clustered in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.
Nutritional gains from food security are larger for children from urban areas, poorest households, and
girls. Although food security has the largest effect on the probability of being stunted among the other
indicators of food security and care, the effect is quite heterogenous across space, wealth, and gender,
as shown in Table 7. Between rural and urban areas, nutritional gains from food security are larger for
children from urban areas. In 2014, the probability of being stunted associated with having food
security for children in urban areas was 12.3 percent in 2014 compared to 9.97 percent for children in
rural areas. However, children from rural areas gained more from early initiation of breastfeeding.
Across the wealth distribution, children from the poorest households gain more from food security;
access to quality diets for these children lowers their probability of being stunted by 21.1 percent based
on data from 2014. Children from the richest households gained more from early initiation of
breastfeeding; the probability of being stunted associated with early breastfeeding for these children
decreased by 10.1 percent in 2014. Between girls and boys, although the effects of food security on
43
stunting were larger for boys in 2010, the reverse was observed in 2014. The probability of being
stunted associated with having food security decreased by 12.5 percent in 2014 for girls compared to
9.1 percent for boys. These differences in the effect of food security on stunting highlight the
heterogeneity which masks the large gains from access to quality diets and provide insights for policy
response.
In terms of access to health care, gains from immunization compliance are particularly large for
children from rural areas, the poorest households, and girls. Similar to food security, gains from
immunization compliance are heterogenous across Sudanese children. Across space, immunization
compliance yields larger gains in lowering stunting than other indicators of health care. These gains
are larger for children from rural areas than for those from urban areas. The probability of being
stunted associated with immunization compliance decreased by 15.3 and 12.5 percent for children
from rural areas in 2010 and 2014, respectively, compared to 8.4 and 7.7 percent for children from
urban areas in 2010 and 2014, respectively. Across the wealth distribution, gains from immunization
compliance are larger and statistically significant for children from the poorest households but not for
children from the richest households. Children from households in the bottom 40 percent of the
wealth distribution were 16.4 and 7.3 percent less likely to be stunted in 2010 and 2014, respectively.
Similarly, although immunization compliance lowers the probability of being stunted for both boys
and girls, the magnitude of the gains for boys is larger. Boys who complied with their immunization
schedule were 14.9 and 12.5 percent less likely to be stunted in 2010 and 2014, respectively, compared
to 12.5 and 8.9 percent for girls in 2010 and 2014, respectively. These results reinforce the fact that
while gains from immunization compliance are statistically significant and larger than the effects of
other health care indicators, and highlight the extent of the heterogeneity across children, ensuring
that rural children and children from poor households are immunized can significantly contribute
toward lowering stunting rates in Sudan.
44
Table 7: Marginal Effects: The Heterogeneity of the Effects of Components of Underlying Determinants of Nutrition
2010 2014
Variables Bottom
Rural Urban Top 20 Boys Girls Rural Urban Bottom 40 Top 20 Boys Girls
40
Food security and care indicators
Minimum −0.0164 −0.0599* −0.0418 0.0441 −0.0465* −0.0119 −0.0997*** −0.123*** −0.211*** −0.0183 −0.0907*** −0.125***
acceptable (0.0226) (0.0346) (0.0308) (0.0401) (0.0266) (0.0266) (0.0376) (0.0278) (0.0398) (0.0347) (0.0336) (0.0370)
diet
Early 0.00631 0.0949** −0.0109 −0.0774 0.0174 0.0255 −0.0516* 0.0227 −0.0552 −0.101* −0.0318 −0.0166
initiation of (0.0278) (0.0421) (0.0372) (0.0694) (0.0332) (0.0331) (0.0304) (0.0450) (0.0409) (0.0590) (0.0359) (0.0338)
breastfeeding
Age −0.0392 −0.0235 −0.0104 0.0421 −0.0340 −0.0277 −0.0317 −0.0359 0.00943 −0.0639 −0.0197 −0.0228
appropriate (0.0240) (0.0341) (0.0304) (0.0470) (0.0306) (0.0264) (0.0315) (0.0397) (0.0382) (0.0497) (0.0332) (0.0340)
breastfeeding
WASH indicators
Safe water 0.0152 −0.0326 0.00198 −0.0795 0.00594 −0.00157 −0.0132 0.0643 0.00601 0.0866 −0.0198 −0.00667
(0.0193) (0.0398) (0.0244) (0.0777) (0.0240) (0.0226) (0.0258) (0.0619) (0.0318) (0.0976) (0.0313) (0.0298)
Improved −0.0272 −0.0535 0.00609 −0.0146 −0.0650** −0.0248 0.0162 −0.0225 −0.0167 0.0505 −0.00329 0.0156
sanitation (0.0268) (0.0354) (0.0410) (0.0441) (0.0317) (0.0279) (0.0290) (0.0359) (0.0497) (0.0595) (0.0323) (0.0280)
Community −0.0184 −0.0600 −0.0227 −0.0138 0.00371 −0.0486* 0.0535** 0.102* 0.0297 0.0649 0.0911*** 0.0263
sanitation (0.0228) (0.0639) (0.0357) (0.0646) (0.0294) (0.0282) (0.0272) (0.0537) (0.0360) (0.0973) (0.0314) (0.0306)
Handwashing −0.0129 −0.0261 0.000727 0.0196 −0.0565* 0.0215
facilities (0.0314) (0.0353) (0.0466) (0.0377) (0.0315) (0.0314)
Feces disposal 0.0195 0.0301 0.0325 −0.0591 0.0146 0.0315 −0.0419 −0.0138 −0.0432 0.0418 −0.0480* −0.0270
(0.0203) (0.0409) (0.0307) (0.0449) (0.0274) (0.0252) (0.0272) (0.0413) (0.0314) (0.0597) (0.0283) (0.0312)
Health care indicators
Use of −0.0183 −0.0143 0.00656 0.00277 −0.0227 −0.00294 −0.00853 0.0138 0.00129 0.101** 0.00918 −0.0153
Prenatal (0.0180) (0.0279) (0.0248) (0.0393) (0.0219) (0.0204) (0.0267) (0.0271) (0.0299) (0.0415) (0.0262) (0.0247)
services
Health facility −0.0487 −0.0134 −0.0106 −0.0181 −0.0242 −0.0646* −0.00608 0.0327 0.0169 0.0431 0.00843 0.000267
assisted (0.0317) (0.0371) (0.0432) (0.0398) (0.0318) (0.0344) (0.0334) (0.0349) (0.0439) (0.0391) (0.0358) (0.0291)
delivery
Immunization −0.153*** −0.0835*** −0.164*** −0.0709 −0.149*** −0.125*** −0.125*** −0.0774** −0.0730*** −0.0498 −0.125*** −0.0890***
compliance (0.0231) (0.0316) (0.0317) (0.0474) (0.0260) (0.0272) (0.0290) (0.0329) (0.0281) (0.0382) (0.0333) (0.0254)
45
2010 2014
Variables Bottom
Rural Urban Top 20 Boys Girls Rural Urban Bottom 40 Top 20 Boys Girls
40
State fixed Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
effects
Additional Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
controls
Observations 3,446 1,323 2,057 601 2,407 2,362 3,082 1,191 1,942 548 2,177 2,096
Note: Robust standard errors clustered in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.
46
While the results above provide insights for multisectoral approaches to reducing stunting in Sudan,
the implementation of such approaches is often quite complex. For instance, Sudan’s current
economic and sociopolitical conditions impose large constraints on its limited resources. As a result,
implementing multisectoral approaches to reduce stunting maybe costly. Furthermore, the empirical
evidence on the effectiveness of multisectoral approaches to reducing stunting is generally
inconclusive. In particular, the lack of clarity and specificity of the roles of each sector under
multisectoral approaches- particularly in environments where the coordination of resources,
governance structures and other institutions is limited; is often cited as a major challenge to
implementing such approaches (IEG 2009). These concerns and constraints may significantly affect
the implementation of multisectoral approaches to reduce stunting in Sudan.
However, certain countries such as Senegal have registered some success in reducing undernutrition
through multisectoral approaches (Skoufias, Vinha, and Sato 2019). Sudan can draw from these
lessons- particularly the role of incentive structures and effective coordination of sectors; together
with insights from the results presented in this paper to inform its design of multisectoral approaches
to reduce stunting. Results from this report- particularly the differences in prevalence of stunting and
gaps in access to nutrition drivers across states; as well as the large individual and joint effect of access
to nutrition drivers such as food security and health on stunting; can inform certain aspects of
multisectoral approaches such as the sequencing of interventions, geographic targeting and
identification of missing sectors in Sudan.
In addition to this report, a recent study by the Health, Nutrition and Population (HNP) Group of
the World Bank provide detail and sector-specific insights for health and nutrition approaches to
reduce stunting in Sudan. In their report, the HNP team highlight five cost-effective and high impact
nutrition-specific interventions (such as breastfeeding, complementary feeding, iron-folic acid and
vitamin-A supplementation; and two additional nutrition-sensitive interventions which can be
integrated within the health sector- such as family planning and hand-washing).
47
5. Conclusion
This paper adopts a multisectoral approach to examine the effect of access to underlying determinants
of nutrition on stunting among 0–23-month-old children in Sudan using data collected in 2010 and
2014. Using a framework developed by UNICEF, three categories of nutrition drivers are identified:
food security and care, WASH, and health care. Components of food security and care include access
to quality diets, early initiation of breastfeeding, and age-appropriate breastfeeding; components of
WASH include access to safe drinking water, household and community sanitation, and access to
handwashing facilities; and components of health care include access to prenatal services, health
professional-assisted delivery, and immunization compliance. Adequate access to these components
is determined based on international standards. We examine the extent to which adequate access to
these components of nutrition drivers influences stunting among 0–23-month-old children in Sudan.
We also examine the extent to which inequalities in access to nutrition drivers, particularly due to
wealth, influence the prevalence of stunting across children. Results from these analyses contribute to
existing literature by providing country-specific insights to inform policy response. With the increase
in the prevalence of stunting in Sudan between 2010 and 2014, results from these analyses will be vital
inputs for the ongoing interventions to improve nutritional outcomes of children, build human capital,
and spur growth.
One of the key findings from this study is that the probability of a 0–23-month-old child being stunted
decreases with improvements in adequate access to the underlying drivers of nutrition: food security
and care, WASH, and health care. Children with adequate access to all three nutrition drivers are
significantly less likely to be stunted than those without adequate access to any of the three nutrition
drivers. However, although at a lesser magnitude, having adequate access to some nutrition drivers
(one or two of the three) still influences nutritional outcomes by lowering the probability of being
stunted. Estimates from the latest round of data used in this report show that holding child, household,
and mother characteristics as well as state fixed effects constant, 0–23-month-old children with
adequate access to all three nutrition drivers are 17.4 percent less likely to be stunted than those
without adequate access to all three nutrition drivers. However, children with adequate access to two
nutrition drivers and those with adequate access to one nutrition driver were, respectively, 13.4 percent
and 7.5 percent less likely to be stunted than children without adequate access to any of the three
nutrition drivers.
48
Although a multisectoral approach to tackling undernutrition may mask clarity and undermine
specificity of sectors to prioritize, it can be a basis for designing evidenced-based and balanced
multisectoral strategies to addressing stunting in Sudan. Results from this report together with lessons
from countries which have successfully implemented such approaches can provide insights for
sequencing of interventions and geographic targeting by highlighting both differences in prevalence
of stunting and gaps in access to nutrition drivers. Given Sudan’s current macroeconomic
environment and the resulting constraints on its limited fiscal resources, such insights are useful for
formulating appropriate interventions to tackle stunting. Our analysis indicates that ensuring food
security (particularly in rural areas and among the poorest households) may contribute to significantly
lowering stunting among 0–23-month-old Sudanese children. For children who already have adequate
food security and care, ensuring adequate access to health care (particularly immunization compliance)
may further improve their nutritional outcomes. The large nutritional gains from having adequate food
security and care offer one possible explanation for the increase in the rate of stunting in Sudan
between 2010 and 2014. Adequate access to food security and care decreased significantly in rural
areas and among the poorest households, thereby resulting in large increases in stunting.
Implementing such multisectoral approaches in a country such as Sudan which already faces
significant constraints and competing demands for its limited resources, requires geographic targeting
of areas where stunting is most prevalent, identification of population groups most deprived of
nutrition drivers and incentives for an effective coordination of all actors. Once these areas are
identified, knowledge of available and missing sectors as well as gaps in access to nutrition drivers can
inform the sequencing of interventions to tackle undernutrition in Sudan. Therefore states such as
Blue Nile, North Darfur and Gezira which have experienced an increase in the prevalence of stunting
between 2010 and 2014 (see Figure 2 – panel b)) by nearly 10 percent, require urgent attention.
Identifying population groups within these states who are deprived from access to nutrition drivers is
an essential first step. Similarly, in states such as Gadarif and North Kordufan where the percentage
of children without access to any of the three nutrition drivers increased by 11 percent and 4 percent
between 2010 and 2014 respectively (see Figure 4 – panel c)), prioritizing access to food security and
care can contribute to lowering stunting. The effectiveness of these multisectoral approaches can be
greatly enhanced by programs which aim to increase income levels and lower income variability. For
households in the bottom 40 percent of the income distribution, interventions targeting income
growth can significantly contribute towards lowering stunting.
49
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