Equity for Children and Adolescents
in the Middle East and North Africa:
An Opportunity for Growth
A Regional Overview
Prepared for UNICEF MENARO by Alberto Minujin with research assistance of
Asmaa Donahue and Carolyn McCaffrey
1
Table of Contents
List of Acronyms ...................................................................................................................................................................... ii
1. Executive Summary ........................................................................................................................................................... 1
2. Background ........................................................................................................................................................................... 2
Goal and objectives of the report ................................................................................................................................. 3
Overview of Methodology ............................................................................................................................................... 3
3. Context .................................................................................................................................................................................... 5
Demographics ...................................................................................................................................................................... 5
Socio-Economic Indicators ............................................................................................................................................. 7
Impact of Inequality on Human Development...................................................................................................... 10
Challenges to Monitoring Progress: The Data Gap in the MENA Region .................................................. 12
4. Findings ................................................................................................................................................................................ 13
Who Are the Most Vulnerable Children in the MENA Region? ...................................................................... 13
Marginalized Ethnic and Religious Groups ....................................................................................................... 13
Refugee, Internally Displaced and Stateless Children .................................................................................. 14
Children with Disabilities ......................................................................................................................................... 15
Adolescent Girls, Married Adolescents and Adolescent Mothers ............................................................ 16
Youth ................................................................................................................................................................................. 17
Inequity in Child Wellbeing: Going Beyond the Averages ............................................................................... 19
Shelter............................................................................................................................................................................... 22
Early Marriage (under age 15) ............................................................................................................................... 24
Access to Education .................................................................................................................................................... 26
Gender and Education................................................................................................................................................ 28
Determinants of Child Labor in 8 MENA Countries ....................................................................................... 31
5. Conclusion ........................................................................................................................................................................... 35
6. Key Recommendations ................................................................................................................................................... 37
Annex I: Methodological Note .......................................................................................................................................... 39
Annex II: Data Sources........................................................................................................................................................ 47
Annex III: Definitions .......................................................................................................................................................... 48
Annex IV: Institutional Definitions of MENA Region ............................................................................................. 52
Annex V: Statistics ................................................................................................................................................................ 53
Annex VI: Bibliography ...................................................................................................................................................... 55
i
List of Acronyms
CEDAW
CRC
DHS
EMRO
ESCWA
GCC
HDI
HIV and AIDS
IDP
IHDI
FGM/C
MDG
MENA
MENARO
MICS
MICS3
NGO
oPt
PPP
TFR
UAE
UNDESA
UNDP
UNESCO
UNFPA
UNHCR
UNICEF
WB
WEO
WHO
Convention on the Elimination of all Forms of Discrimination against Women
Convention of the Rights of the Child
Demographic Health Survey
Eastern Mediterranean Regional Office, WHO
United Nations Economic and Social Commission for Western Asia
Gulf Cooperation Council: Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, & UAE
Human Development Index
Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome
Internally Displaced Persons
Inequality-adjusted Human Development Index
Female genital mutilation/cutting
Millennium Development Goal
Middle East and North Africa
Middle East and North Africa Regional Office, UNICEF
Multiple Indicator Cluster Survey
3rd Round of the Multiple Indicator Cluster Survey
Non-governmental organization
occupied Palestinian territory
Purchasing power parity
Total Fertility Rate
United Arab Emirates
United Nations Department of Economic and Social Affairs
United Nations Development Programme
United Nations Educational, Scientific and Cultural Organization
United Nations Population Fund
United Nations High Commissioner for Refugees
United Nations Children’s Fund
The World Bank
World Economic Outlook database, published by the World Bank
World Health Organization
ii
1. Executive Summary
Many children are denied these rights not only because they are poor, but also because they are
discriminated against based on their gender, ethnicity, religion, disability, migration or noncitizen
status. Inequity occurs when social and cultural attitudes or laws and economic systems deprive
children of basic resources and limit their life opportunities because of who they are.
The Middle East and North Africa (MENA) is a demographically and socioeconomically diverse
region characterised by disparities both across and within countries. Throughout the MENA region
girls and boys experience material deprivation and discrimination, and, when the two types of
inequity overlap, children are even more vulnerable to lives of multidimensional, multigenerational
poverty and loss of rights.
Indicators of child wellbeing help chart country progress towards achieving development goals,
but mask inequities within countries when viewed only as national averages. Although
multidimensional child poverty measures provide a more nuanced understanding of the
deprivations children face, there is limited data available for the MENA region. By analysing
available quantitative and qualitative data on the sources of inequity among children living in
MENA countries, this report seeks to present an overview of the region’s most vulnerable
population groups, highlight patterns of inequity and propose overall policy responses.
Four main findings emerged through a comparison of disparities in material deprivation based on
children’s gender, wealth quintile, rural or urban residence, subregion and their household head’s
education level. First, subregion plays a pivotal role in inequity and is often the most important
determinant of negative outcomes for children. Second, disparities in children’s wellbeing tend to
result from multiple overlapping determinants, even if one determinant is more prevalent than the
others. Third, a number of vulnerable groups of children, which are not represented in official data,
are denied their rights and experience material deprivation because of discrimination on the basis
of gender, ethnicity, religion, disability, migration or noncitizen status. Finally, inequities are
greatest among the small percentage of children do not go to school, despite progress towards
universal education.
Based on these findings, this report makes the following five key recommendations:





Improve data collection and strengthen evidence on the deprivations experienced by
vulnerable groups of children in order to make them visible to policy makers and to
monitor inequity and discrimination.
Implement affirmative action policies such that all children – regardless of gender, ethnicity,
religion, disability or citizenship – have equal access to basic services, programmes and
protection.
Target investments in programmes focused on vulnerable children in such a way that
recognizes their potentially significant contributions to the economic and civic life of their
communities.
Develop child-led communication strategies that build on children’s capacity to convey
messages that raise awareness in their communities about discrimination, rights and
benefits.
Identify opportunities to advance the equity agenda in ways that support participation of
adolescents and youth.
By adopting policies that promote child equity, governments not only uphold the rights of all
children, but also invest in the future human capital that children represent.
1
2. Background
Under the Convention on the Rights of the Child, all children have the right to the care, resources,
and support needed for their survival and development; to be protected from violence, abuse and
exploitation; and to express themselves and be heard as participants in decision making about
matters concerning them. In reality, many girls and boys are not able to enjoy their rights not only
because they are poor but also because they face discrimination on the basis of their gender,
ethnicity, religion, disability, migration or other status. Inequity occurs when social and cultural
attitudes or laws and economic systems deprive children of basic resources and jeopardize their life
opportunities because of who they are.
Figure 2.1 illustrates how discrimination overlaps with material deprivation to place children at
greater disadvantage. Material deprivation, such as income poverty or lack of access to quality
basic social services, negatively impacts children’s wellbeing regardless of discrimination (the
lower left, pink box). This form of disadvantage is captured by traditional below-poverty line
measures and GINI coefficients. In addition, children may experience discrimination on the basis of
their gender or ethnicity, creating barriers to better schools and upward mobility, but not
necessarily leading to materially deprivation (the upper right pink box). Such would be the case of
young women in middle-income households who are able to complete their education through
university, but are prevented by gender discrimination from finding employment in their chosen
profession. The combination of discrimination and material deprivation, however, increases
children’s vulnerability and traps them in multidimensional, multigenerational poverty as
discrimination blocks their access to social programs and services targeting the poor and are
denied their rights (upper right red box).
Figure 2.1: Conceptual Framework for Child Equity
Sources of Inequity
Material Deprivations
(income and
basic social services)
Yes
Discrimination
Yes
(gender, ethnicity,
disability, noncitizen,
geography, etc.)
No
No
Vulnerable
groups
Multidimensional
child poverty
Children may experience overlapping forms of discrimination which are not taken into account
when programmes focus on only one form of deprivation. For example, rates of early school
leaving may be much higher than the national average in a remote, economically depressed
governorate where the country government has not adequately invested in infrastructure.
Attendance rates may be especially low among adolescent girls there and in neighboring districts
because of local households do not see an economic or socio-cultural benefit in girls’ secondary
education. On a national level, education budgets, teacher training and curriculum may disregard
2
the special needs of children with disabilities, resulting in structural barriers to their attending
school. Without education, disabled children in this example’s governorate are even less likely to
become economically independent as adults. These inequities have life-long impacts as children
who experience them enter adulthood without the same preparation and access to opportunity
needed to increase their earning potential and leave poverty.
The discussion of equity comes at a time of unprecedented social and political change in the Middle
East and North Africa (MENA) led by the region’s youth. On the one hand, vast improvements in
health, child survival and education have resulted in the largest and most educated population of
youth in the region’s history. On the other, youth are pushing back against a wave of
disappointment in and frustration with the pervasive lack of gainful employment and channels for
meaningful civic engagement. Youth-led movements in the region have called attention to the need
to ensure that equitable access to basic necessities like decent housing, education and healthcare
are coupled with equitable access to the means to build their futures. Until they do, MENA
countries will continue to miss a host of opportunities that their considerable wealth of youth
present: the economic contribution, energy, innovative ideas and aspirations that young women
and men bring.
Goal and objectives of the report
The findings reported in these pages are based on an initial equity analysis of social and economic
disparities in the MENA region that moves beyond national averages. They seek to present an
overview of the region’s most vulnerable population groups, highlight patterns of inequity, and
propose overall policy responses. A series of country-specific equity profiles have been developed
in tandem with this report as tools to support advocacy for children’s equity.
The analysis and findings presented here are by no means comprehensive, but rather are intended
to provide a springboard for further exploration of vulnerable groups in the MENA region and the
multidimensional disparities that lock them into long term disadvantage. It seeks to raise
awareness about the situation of child inequity and call for building more evidence to support
policies to address it. In order to do so, disaggregated data on children’s wellbeing and other
information must be made available to researchers. The lack of available data from many countries
on such basic indicators as child health, education or shelter greatly limited the scope of this report.
Overview of Methodology
Quantitative and qualitative data were used to identify sources of inequity in child well-being in the
MENA region. The information provided in “Who Are the Vulnerable Children of the MENA
Region?” of the Findings sections was the result of a literature review and processing available
statistical information. Sources included reports and data files produced by international
organizations, nongovernmental organizations and scholarly researchers, and media reports. The
quantitative portion of the study used MICS 3 data and other household survey micro data files to
compare the likely impact of five variables – gender, geographic location, subregion, wealth quintile
and household education – on different indicators of child well-being. For each variable, a ratio
between best and worst outcomes was calculated to show the relative gap, or disparity, between
disadvantaged and advantaged children. Disadvantage and advantage were assumed as follows:
Disadvantaged
Female
Rural
Worst subregion
Poorest quintile
Advantaged
Male
Urban
Best subregion
Richest quintile
3
Household head has no
education
Household head has at least
a secondary education
The results are produced in bar charts, such as in Figure 4.1. The vertical line at 1 indicates
complete equity; the more the ratio exceeds 1, the greater the gap. For example, Figure 4.1 shows
that 25% of Moroccan children lived in overcrowded or inadequate households, but children in
rural areas were 7.3 times more likely that children in urban areas from suffer from shelter
deprivation, and children whose head of the household had no education (the most disadvantaged)
are 6 times more likely than children that lived in a household which it head had at least a
secondary education (the most advantaged) to face severe shelter deprivation. A more detailed
explanation of the methodology is provided in Annex I of this report. Definitions for each of the
indicators are included in Annex III.
This report follows the definition for the MENA region used by UNICEF: Algeria, Bahrain, Djibouti,
Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, occupied Palestinian territory (oPt),
Oman, Qatar, Saudi Arabia, Syria, Sudan, Tunisia, UAE, and Yemen. One of the challenges of
comparing data for the MENA region from different sources is that not all institutions use the same
regional definitions or even refer to the region as “MENA”. Regional definitions followed by the
different data sources used in this report are listed in Annex IV.
4
3. Context
Demographics
With populations ranging from 1.2 million in Bahrain to over 81 million in Egypt, the Middle East
and North Africa is a demographically diverse region. Despite this variation in population size,
however, MENA countries share some common characteristics. Over the last 50 years,
improvements in health, sanitation and education have led to rapid increases in life expectancy and
child survival, and a much slower decline in fertility rates. As a result, the MENA region now has
the largest youth population in its history – more than half (51.8%) of the region’s population is
under the age of 25. Over 100 million people – 30% of the region’s population – are between the
ages of 15 and 29, a trend that will peak in the next 10 years in most of the MENA’s middle and high
income countries (Dhillon and Yousef 2007; Khalif 2009).
The populations in the least developed countries (LDC) are the youngest in the region, with nearly
half (46.5%) of the people in Yemen, Djibouti and Sudan under the age of 18. Figure 3.1
demonstrates this concentration of youth and suggests that Yemen may be in the early stages of
demographic transition – the gradual shift from high birth and mortality rates to lower birth rates
and longer life expectancy. Yemen, Djibouti and Sudan are all struggling to provide their
populations with adequate education, healthcare and other basic services. The challenge for these
pre-transition countries will be to invest the resources needed to quickly build up quality services
and programs for children and adolescents.
Figure 3.1: Classic population pyramid
Population pyramid Yemen
60-64
50-54
40-44
Age groups 30-34
Male
20-24
Female
10-14
0-4
20
10
0
10
20
Percentages
Source: World Bank World Development Indicators (2008)
In middle-income countries (MIC), where this demographic transition is already in progress,
populations are currently experiencing a youth bulge such that one fifth (20.4%) of people living in
middle-income MENA countries are between the ages of 15 and 24. This so-called “youth bulge”
presents a demographic dividend if, following the example of Asian economies, middle-income
countries like Egypt and Algeria – where the youth bulge is particularly pronounced (see Figures
3.2 and 3.3) – can harness the tremendous potential of a large working-age population with a low
dependency ratio. The opportunity implied here is therefore also a challenge: governments must
invest in expanding opportunities for young women and men and improving education to include
curriculum that is more relevant to the labor market’s needs.
5
Figure 3.2: Youth bulge
Population pyramid Egypt
60-64
50-54
40-44
Age groups 30-34
Male
20-24
Female
10-14
0-4
15
10
5
0
5
10
15
Percentages
Source: World Bank World Development Indicators (2008)
Figure 3.3: Youth bulge
Population pyramid Algeria
60-64
50-54
40-44
Age groups 30-34
Male
20-24
Female
10-14
0-4
15
10
5
0
5
10
15
Percentages
Source: World Bank World Development Indicators (2008)
Migration patterns in the MENA region have skewed this population bulge significantly in Gulf
countries, where foreign born workers in their 30s and 40s, and especially male migrants, make up
a large part of the labour force. Figures 3.4 and 3.5 reveal this migration effect in Saudi Arabia and
particularly in the United Arab Emirates.
6
Figure 3.4: Immigration effect
Figure 3.5: Immigration effect
Population pyramid UAE
60-64
50-54
40-44
Age groups 30-34
Male
20-24
Female
10-14
0-4
30
20
10
0
10
20
Percentages
Source: World Bank World Development Indicators (2008)
Socio-Economic Indicators
The Middle East and North Africa is a socioeconomically diverse region. GDP per capita at
purchasing power parity (PPP) ranges from an average of just over US$2,500 in the less developed
countries – Djibouti, Sudan and Yemen – to an average of more than US$30,000 in the higher
income Gulf countries (excluding Qatar, the richest country in the region, whose GDP per capita is
over US$88,000). Most of the MENA population – 85 % of the region’s 355 million people – lives in
middle-income countries, where GDP per capita ranges from US$1485 in the occupied Palestinian
territories to more than ten times that figure in Lebanon (World Bank 2011).
7
Disparities characterise the MENA region not only across countries, but also within them. GDP per
capita, however, only measures national averages, which mask inequities within each country.
Table 3.1: Socio-economic Indicators
GDP per Capita
(PPP current
internat'l $)
Category Country
Djibouti
LDCs
Sudan
Yemen
Algeria
Egypt
Iran
Iraq
Jordan
MICs
Lebanon
Libya
Morocco
OPT
Syria
Tunisia
Bahrain
Kuwait
Oman
HICs
Qatar
Saudi Arabia
UAE
Source
2,553
2,466
2,596
7,104
6,367
11,025
3,599
5,659
15,331
14,878
4,773
1,367
5,108
9,489
26,808
38,293
26,198
88,233
23,743
36,973
Poverty
Income Gini
Headcount Ratio Coefficient
at $1.25 a day
(PPP) (% of pop)
Human
Development
Index Rank
(169 countries)
Gender
Inequality Index
Rank
(169 countries)
Unemployment Multidimensional
Rate
Child Poverty
(% of total labor (severe) (%)
force)
19
N/A
18
7
2
2
N/A
2
N/A
N/A
6
N/A
N/A
3
N/A
N/A
N/A
N/A
N/A
N/A
0.40
N/A
0.38
0.35
0.32
0.38
N/A
0.38
N/A
N/A
0.41
N/A
N/A
0.41
N/A
N/A
N/A
0.41
N/A
N/A
147
154
133
84
101
70
N/A
82
N/A
53
114
N/A
111
81
39
47
N/A
38
55
32
N/A
106
138
70
108
98
123
76
N/A
52
104
N/A
103
56
55
43
N/A
94
128
45
N/A
14
N/A
10
9
11
N/A
13
N/A
N/A
10
0
11
13
N/A
2
N/A
4
10
4
65
N/A
64
N/A
26
N/A
N/A
N/A
N/A
N/A
41
7
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
HDI World Bank
UNDP HDR 2010 UNDP HDR 2010
IMF, WEO
Database
MICS 3
IMF, WEO
Database (for all
except OPT), UN
HDI World Bank
Statistical
Division (for
OPT)
Multidimensional child poverty measures that go beyond economic indicators like GDP, providing a
more nuanced understanding of the deprivations children experience, are available for a small
number of MENA countries.1 The rate of severe deprivation is very high among children in Djibouti
and Yemen at 65% and 64%, respectively, 41% in Morocco and 26% in Egypt (see the last column
in Table 3.1). By comparison, estimated percentages of the population living on less than US$1.25 a
day – 19% in Djibouti, 18% in Yemen, 6% in Morocco and 2% in Egypt – obscure the child-specific
impacts of poverty that multidimensional indicators reveal.
While poorer children are generally more likely to be vulnerable to infant mortality in the MENA
region, under 5 mortality rates consistently vary across countries with similar GDP per capita (see
Figure 3.6). The less developed countries in the MENA region – Djibouti, Sudan and Yemen – share
comparable GDP per capita, but have different under 5 mortality rates of 94, 108 and 66 per 1000
births, respectively. There are also disparities between Lebanon and Libya, two middle-income
countries with nearly the same GDP per capita, but infant death rates of 12 and 19 per 1000 births,
respectively. These discrepancies are also visible among high-income countries with relatively
Multidimensional child poverty is defined as the percentage of children that suffer from 2 or more severe
deprivations. This measure was adopted by the UNICEF Global Study on Child Poverty and Disparity. See
Annex I for definitions of indicators and thresholds of severe deprivation.
1
8
similar GDP per capita – Saudi Arabia’s under 5 mortality rate, for example, nearly doubles that of
Oman.
Figure 3.6: Correlation of GDP per capita with U5MR2
110
100
90
80
70
60
U5MR
50
40
30
20
10
0
Sudan
Djibouti
Yemen
Iraq
MENA
Morocco
Algeria
OPT
Iran
Jordan
Tunisia
Egypt
Syria
0
5,000
10,000
Libya
Lebanon
15,000
20,000
Saudi Arabia
Oman
Bahrain
25,000
30,000
Kuwait
UAE
35,000
40,000
GDP per capita (PPP Current International $)
Sources: IMF, WEO Database (for GDP) UNICEF (for U5MR)
Although the Gulf States demonstrate some of the lowest infant death rates in the MENA region,
Figure 3.7 suggests that these countries need to develop more effective strategies to promote child
wellbeing. Despite having similar or even higher GDP per capita than countries like Canada, France,
the United Kingdom and the United States, Gulf countries have child mortality rates that almost
double or triple those of high-income countries outside of the MENA region.
2
See Annex IV for IMF definition of “MENA”.
9
Figure 3.7: Comparison of U5MRs of high income countries in MENA and other regions
25
Saudi Arabia
20
15
U5MR
Oman
Bahrain
UAE
UK
France
5
Qatar
Kuwait
10
USA
Canada
0
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
GDP per capita (PPP Current International $)
Sources: IMF, WEO Database (for GDP) UNICEF (for U5MR)
Impact of Inequality on Human Development
The Human Development Index (HDI) seeks to capture the development situation of countries
around the world by assessing their performance on an array of economic and social indicators. By
moving beyond economic measures to include health, education, material goods, political
participation and social cohesion, the HDI recognizes the multiple dimensions of development.
The HDI allows countries to be compared and ranked regionally based on their level of human
development, but is not well suited to capturing the disparities within those countries that
jeopardize development. In 2010, the Human Development Report (HDR) introduced a crucial
innovation, the Inequality-adjusted Human Development Index (IHDI) and the Inequality-adjusted
Education Index (for more information, please see footnote).3
As a region4, the Arab states suffer an overall loss of 27.6% in HDI value due to unequal distribution
of health, education and living standards – a loss surpassed only by the Sub-Saharan and South
Brief note on Inequality-adjusted Human Development and Education Indices (Extracted from UNDP, Human
Development Report 2010): The Human Development Index (HDI) is a pioneering measure that looks beyond income to
capture a country’s situation in terms of its human development. The Human Development Report 2010 includes a
relevant innovation on the estimation of the HDI. “To obtain a full picture of the evolution of human development, we
must go beyond the dimensions in the HDI. Significant aggregate progress in health, education and income is qualified by
high and persistent inequality, unsustainable production patterns and disempowerment of large groups of people around
the world” (HDR 2010).
3
The 2010 report presents, on top of the HDI, the Inequality-adjusted HDI (IHDI) that “captures the losses in human
development due to inequality in health, education and income.” The report presents the total loss due to
multidimensional inequalities and losses in each of the three dimensions: health, education and income.
In this study on child equity in MENA we present the IDHI, the total loss and the loss due to education, a dimension that
not only directly affects children, but also shows the highest impact in the region and in the countries included in the IDHI
estimation (for further explanation please see Chapter 5 and Technical notes in the HDR 2010).
4
See Annex IV for the UNDP’s definition of “Arab states”.
10
Asian regions (see Figure 3.8). Inequality in education alone represents a 16% loss in the Arab
region’s HDI value, figuring as the biggest loss due to education of all the regions.
Figure 3.8: Loss in HDI and its components due to inequality, by region5
35
30
25
Percentages
7
5
20
15
10
5
0
5
16
7
9
5
10
15
Health
7
5
4
5
15
11
5
7
14
Education
2
2
7
Living
standard
Source: UNDP HDR 2010
This education-related loss is also evident at the level of individual Arab countries (see Figures 3.9
and 3.10). For example, there is a 28.1% loss in Morocco’s HDI ranking due to inequity, lowering it
from 0.567 to 0.407. When educational outcomes are adjusted for inequity, the loss is even greater:
the Inequality-adjusted Education Index is only 0.246, with a loss of 42.7% in the value of the index
because of inequality in education. This trend holds true for each of the Arab countries.
Figure 3.9: HDI, inequality-adjusted HDI, inequality-adjusted education indices6
Arab States
HDI
Yemen, Rep.
Tunisia
Syrian Arab Republic
Inequalityadjusted Educ.
Index
Morocco
Jordan
Inequalityadjusted HDI
Egypt, Arab Rep.
Djibouti
0.0
5
6
0.2
0.4
0.6
Source: UNDP HDR 2010
See Annex IV for the UNDP’s definition of “Arab states”.
See Annex IV for the UNDP’s definition of “Arab states”.
11
0.8
Figure 3.10: Loss in HDI due to inequality and education inequality7
Arab States
Yemen, Rep.
Tunisia
Syrian Arab Republic
Loss due to
Edu. inequality
(%)
Loss due to
Inequality (%)
Morocco
Jordan
Egypt, Arab Rep.
Djibouti
60
40
20
0
Source: UNDP HDR 2010
Challenges to Monitoring Progress: The Data Gap in the MENA Region
The IHDI is a useful tool for measuring inequity, but its use in the MENA region is hampered by the
significant lack of statistical data needed to estimate index values. While there is IHDI-related
source data for over 75% of the countries in Sub-Saharan Africa, South Asia, and Latin America and
the Caribbean, there is comparable data for just over a third of MENA countries (see Figure 3.11).
The dearth of available statistical information poses a major challenge to tracking progress in the
MENA region. Not one of the high-income MENA countries, where the greater availability of
resources should result in better outcomes for children, had enough statistical information to
estimate an adjusted HDI. This point is reflected in Table 3.1, where data on income poverty,
unemployment and the Gini coefficient are missing in many countries.
Figure 3.11: Percentage of countries, by region, with inequality-adjusted HDI data
100
78
80
78
84
67
60
41
45
40
Percentage of countries
with Inequality-adjusted
HDI data
20
0
0
7
See Annex IV for the UNDP’s definition of “Arab states”.
12
4. Findings
Who Are the Most Vulnerable Children in the MENA Region?
The gap analysis provided in this report analyzes disparities between groups of children based on
gender, their rural or urban residence, the subregion in which they live, their household’s wealth
quintile, and the education of their household’s head. These household characteristics help provide
a baseline for identifying the inequity that children experience in accessing services or exercising
their rights. For example, in rural areas that lack sufficient infrastructure and resources, healthcare
facilities may not be able to provide the appropriate level of maternal and child healthcare.
In this section, we move beyond the data on household characteristics to explore some of the
groups that are vulnerable to inequity because of discrimination. What children in these groups
share in common is that, because of discrimination and not because of any fault or failure of ability,
they lack access to school and other basic services, and are at greater risk of violence and
exploitation. Thus, the combination of discrimination and material deprivation make it more
difficult for them to leave poverty. These are:
•
•
•
•
•
Children from marginalized ethnic or religious groups;
Refugee, stateless and internally displaced children (IDPs);
Children with disabilities;
Adolescent girls, especially married adolescents and adolescent mothers; and
Orphans
Recent civil society uprisings led by young people throughout the MENA region have also
highlighted the situation of youth. While they may have benefited from greater access to education
and services, youth lack opportunity to participate either in the economy or civil society.
Children in some of these groups literally do not count: either data collection is weak, as in the case
of tracking disabilities among children, or they remain statistically invisible, their numbers
subsumed under broader demographic categories, such in countries whose censuses do not
recognize some ethnic groups. Country governments need to work together to develop
standardized tools for data collection and coordinate efforts for monitoring progress among these
groups. One such effort to improve country level statistics on disability was launched through UN
ESCWA in 2002; sustained commitment is needed for such efforts to make progress.
It is important to note that these forms of vulnerability are often overlapping and mutually
reinforcing. As described below, a number of ethnic minorities in the region are unable to register
the births of their children, so that each new generation becomes stateless and legally invisible.
Girls who are refugees or IDPs are at greater risk of sexual violence and exploitation. Because most
disabled children are unlikely to attend or complete school, youth with disabilities often do not
have the means to become economically independent.
Marginalized Ethnic and Religious Groups
The MENA region is remarkably diverse in terms of ethnicity, language, culture and religious
identity. In addition to ethnic Arabs and Persians, there are also Kurds, Assyrians, Chaldeans,
Circassians, numerous Berber groups such as Kabyle and Tuareg, Baluchis and any number of
African ethnic groups such as the Nubians, Nuer and Dinka. In addition to various branches of
Sunni and Shiite Islam, some of the historically oldest Christian communities thrive in the region,
including Copts and Chaldean Christians, as well as small pockets of Judaism. Other minority
religious communities include the Druze, Baha’i, Yazidis, Mandaens, This diversity, potentially a
resource to the region, has instead presented challenges to national unity. In several countries,
13
ethnic and sectarian tensions have been exploited to fuel conflict, including in Iraq, Lebanon and
Sudan.
Human rights advocates continue to report political and economic discrimination and violence
against religious and ethnic minorities and some politically marginalized religious majorities in the
region, including Copts in Egypt; Chaldeans, Assyrians and other minorities in Iraq; Ismailis in
Saudia Arabia; Shi’ties in the Gulf; and Baha’i in Iran, Egypt and Jordan (Minority Rights Group
2010; Human Rights Watch 2007, 2008 and 2009). This section will highlight the situation of
several ethnic and religious groups whose marginalization raises serious concerns for child wellbeing.
In Bahrain, Shi’ites comprise 70 percent of the population but confront substantial barriers in
accessing better jobs, housing and government services (Johnson 21/2/11; Santana 30/5/09).
Birth certificates for Baha’i children are not easily obtained in Jordan because Baha’i marriages are
not recognized, and Baha’i students in Iran have reportedly been barred from higher education
(Minority Rights Group 2010).
In Yemen, an estimated 1 million people belonging to the so-called Akhdam, an ethnic group of
unknown origin, live in extreme poverty as the result of caste-like policies and practices.
Prohibited from owning property or sharecropping, the Akhdam live in informal slums and are
relegated to begging or working informally as street sweepers or itinerant agricultural laborers
(Seif 2006; Worth 28/2/08). Access to education is rare, and children who have lost their parents
are denied shelter or other services. Sexual exploitation and abuse of children, who often beg and
scavenge to support themselves, is common. Maternal mortality and early marriage, already high in
Yemen, are believed to be even worse for Akhdam women and girls (Seif, op cit.).
A number of ethnic minorities in the region are denied the right of citizenship, despite having lived
in the countries they call home for generations. As a result, in addition to being subjected to
harassment or violence, they and their children are denied access to education, public healthcare,
birth registration and other basic rights and services. These include the Tabu and Tuareg in Libya;
certain Kurdish minorities in Syria, Iran and Lebanon; stateless Palestinians throughout the region,
and the Bidun, a minority of Bedouin origin, in the Gulf states. Their situation is described in the
next section.
Refugee, Internally Displaced and Stateless Children
Forced displacement, whether as a refugee or internally displaced person (IDP), places children at
considerable physical and emotional risk. Depending on their situation, they struggle for basic
necessities such as food and shelter, they fall behind in school as their education is interrupted,
sometimes for years at a time, they may be exposed to sexual and physical violence, and lose many
of their rights in the process. Children from families who have been displaced for long periods may
in some cases face the same protection issues as those who are newly displaced. Trauma resulting
from these experiences can affect children and the adults upon whom they depend even once their
living conditions improve, compromising their ability to rebuild their lives.
According to UNHCR, the MENA region hosts 19 percent of the world’s refugees, including 2.3
million refugees and 72,900 people living in refugee-like situations (UNHCR 2010). The largest
numbers of the refugees living in the region are from Iraq, Sudan, OPt and Somalia. Several
countries, including Yemen and Lebanon, host refugees as well as internally displaced populations
related to internal armed conflicts. Of six countries reporting over a million IDPs, two are in MENA:
Sudan (4.9 million or 12 percent of its population) and Iraq (2.76 million or 9 percent of the
population). Between 2 and 9 percent of Lebanon’s population is internally displaced, most of them
14
during the war with Israel in 2006. Between 500,000 and 1.5 million people are believed to be
internally displaced in Algeria for the past 20 years and living in informal settlements (IDMC 2010).
Among IDPs, access to basic necessities and assistance is worst for those in Sudan, Yemen, oPt and
Iraq. In southern Sudan, where rates of malnutrition and poverty are quite high, communities with
a history of displacement struggle with many of the same challenges as newly returning IDPs.
Internally displaced children in Yemen, Sudan and Iraq are reported to have been recruited or
risked recruitment into armed forces; trauma related to forced displacement has been found among
children in those countries as well as in Lebanon. Sexual violence targeting children has been
reported among IDPs in Iraq and Sudan (IDMC 2010). Child workers among Iraqi refugees in Syria
already estimated at 18 percent of the refugee workforce in 2006, is believed to have risen in the
past few years as refugee families slide deeper into poverty (IRIN 14/12/09; UNHCR et al 2006).
Statelessness deprives thousands of minorities in the region of their most basic rights, including
access to education, healthcare, employment, and even legal recognition of their marriages.
Nationality in most MENA countries is based solely on descent from the father, so that a child of a
stateless father becomes so even if his or her mother is a citizen. Because of discriminatory laws
regulating nationality, marriage and birth registration, statelessness becomes an inherited state of
legal invisibility. (Refugee International 2009)
Denationalized Kurds, the Bidun, and Palestinians comprise the largest numbers of stateless
peoples in the region. Feili Kurds were among the half million Shiite Kurds expelled from Iraq
under former President Saddam Hussain. While most have since returned to Iraq to apply for
restoration of their nationality and property, several thousand remain in Iran and are unable to
obtain basic services or employment. A minority of ethnic Kurds in Syria were denationalized
during a 1962 census; together with their children and grandchildren, their numbers have more
than doubled to 300,000. The Bidun, so-called because they are “bidun jinsiya” or without
nationality, are the descendents of nomadic Bedouins who were never registered as citizens by new
governments in the 1940s. Thousands reside in Kuwait (80,000 – 140,000), Bahrain (9,000 –
15,000), Qatar (1,200 – 1,500) and United Arab Emirates; an unknown number living in Saudi
Arabia are among the most poor and marginalized. Several thousand Palestinians who were
expelled during the in Syria, Lebanon, Jordan, Iraq, Saudi Arabia and elsewhere fall outside the
administration of either UNRWA or UNHCR and are prohibited by local nationality laws from
seeking citizenship (Refugees International 2009).
Other stateless groups include Sahrawis refugees living in camps near Tindouf in Algeria, and
refugees of Iraqi, Somali and Sudanese origin in Libya (ibid). Bahrain and the United Arab Emirates
alone have made some preliminary efforts to register stateless individuals. Children of stateless
parents themselves become treated as foreigners in the country of their birth, unable to pursue
education, use the public healthcare system, legally work or marry a citizen in adulthood, or receive
benefits.
Children with Disabilities
While disability can occur regardless of wealth, in the MENA region it is strongly linked with
poverty. Malnutrition, unhealthy living conditions and the lack of quality healthcare, all stemming
from poverty, produce a significant proportion of preventable disabilities; and people with
disabilities face significant barriers to becoming economically independent (Axelsson 2009,
Ghuraibeh 2009, International Inclusion 2009 and 2006). A study published in 2006 found that
children with disabilities are more likely to live in housing that is overcrowded and lacks adequate
ventilation, lighting, toilet facilities or potable water (International Inclusion 2006).
15
Although people with disabilities frequently become locked in a cycle of poverty, it is not because
disability itself is limiting. In fact, when learning, mobility, independence and self sufficiency are
supported, even children living with significant disabilities can do very well and become
independent, productive members of their community (International Inclusion 2006). Too often,
however, this is not the case for children growing up with disabilities in MENA countries. Instead,
they face discrimination, denial of rights and barriers to education and other basic services, all of
which ensure that children with disabilities who grow up poor remain so in adulthood (Axelsson
2009).
Education, so critical to a child’s development and economic future, is one area where policies and
practices discriminate against the disabled. Education policies follow what advocates describe as a
“defective child” model, placing responsibility for lack of success in school on a child’s presumed
limitations rather than on teachers and schools that do not have the capacity to support learning
for children with disabilities (Inclusion International 2009). Schools and programmes in Jordan,
Lebanon and Syria will not accept students who have an impairment without a letter from their
doctor assessing the child’s condition and whether the child poses a risk to other students.
Meanwhile, most doctors do not provide the necessary recommendation as they believe that
schools have nothing to offer such children. Likewise, doctors tend not to recommend hearing
devices for deaf children because of the difficult training required (ibid). Parents rarely send
children to school if they have intellectual disabilities, seeking to protect them from rejection and
harm. Such exclusionary practices and policies ignore findings that even children with significant
disabilities are more likely to finish school, continue onto post-secondary education and training,
earn a decent living and become active members of their community if they have received a regular
education (International Inclusion 2006).
The major causes of disability in the region vary by country and are rooted in local economic, social
and political contexts. For children in poor and low income households, disabilities are often
preventable and result from under-nutrition and lack of access to quality healthcare. Pre- and
antenatal care, genetic counseling for parents, immunization and proper treatment for childhood
diseases and injuries can all prevent impairments. Marriage between first cousins, in decline in
many countries in the region, nevertheless continues to contribute high rates of genetic disorders
among children (Hakim and Jaganjac 2005). For example, two-thirds of blindness in children is
estimated to result from genetic disorders, ranging from 47 percent in Tunisia and 86 percent in
Kuwait (Gomaa cited in Ghuraibeh 2009).
In countries affected by armed conflict and war, such as Sudan, Iraq, Libya and the occupied
Palestinian territories, violence maims children and causes post traumatic stress disorder (PTSD).
Post conflict environments can be as hazardous for children as wartime, as children are injured by
landmines, cluster bombs, unexploded munitions and remnants of war. In 2009 alone, new
casualties from unexploded munitions and remnants of war were reported in Iran, Iraq, Jordan,
Lebanon, Libya, OPt, Sudan, Syria, Western Sahara, and Yemen. Globally, children make up a third
of all such casualties for whom the age is known (Landmine Monitor 2010). Finally, road accidents
in rapidly urbanizing settings are another major contributor to disability. In fact, the MENA region
has one of the highest traffic-related fatality rates in the world (Hakim and Jaganjac 2005).
Adolescent Girls, Married Adolescents and Adolescent Mothers
Adolescence, which spans ages of 10 to 19 years, is a gendered experience. For boys, the transition
to adulthood brings every widening opportunities to exercise their economic, social and political
rights and take on more public roles. By contrast, entrance into adulthood narrows the scope of
experience and choice for girls to the domestic sphere (Lloyd 2005). While both boys and girls in
poor households risk being pushed prematurely into adult roles such as work or soldiering,
16
adolescence introduces girls to new forms of gender discrimination and vulnerability. In the MENA
region, this includes early marriage and motherhood, domestic and sexual violence, and risk of HIV
infection.
While overall the age of first marriage is rising in the MENA region, early marriage persists in some
communities. The problem of child marriage in Yemen received international attention when 10year old Nujood Muhammed Ali filed for divorce from her 30 year-old husband, and again in 2010
when a 13-year old girl bled to death after forced intercourse with her 23 year-old husband. A
2009 study by Yemen’s Ministry for Social Affairs estimated that more than one-quarter of girls are
married before age 15 (McEvers 19/4/10). There is a strong argument to be made for
strengthening policies and programmes that support delayed marriage and address the needs of
adolescent girls who are already married and becoming mothers. (The trend of delayed marriage is
discussed in the section on youth, below.) Once married, adolescent girls fall even further out of
view, whether in statistics, policies or programmes. They leave school, become isolated from their
social networks and information sources as they join their husband’s household, have less mobility
and independence, and have less economic and household power. Adolescent brides are often
much younger than their husbands, leaving them at risk of unprotected, unwanted sex and
domestic violence. Reproductive health services tend to assume a client who is adult and at least
has enough decision making power to utilize their services, when in fact married adolescents tend
to be more dependent on their husbands and other adults for healthcare information and access
(Haberland 2004).
Another reason for focusing on adolescent girls in the region, however, is the enormous potential
that these emerging young women hold for building strong families and communities and
promoting positive social and economic change. A growing number of international organizations,
including the Population Council, CARE, Plan International and the UN Interagency Task Force on
Adolescent Girls have been calling for targeted investments in adolescent girls’ education, health,
leadership and skills as a way of protecting their rights and achieving the Millennium Development
Goals. In the MENA region, investments should empower girls to attend secondary school through
graduation, incorporate their needs into healthcare systems, build their life and leadership skills,
and expand economic and employment opportunities for them after they graduate.
Youth
The recent tide of youth-led civil society movements throughout the MENA region have highlighted
youth as a group that continues to face economic exclusion despite gains in education. As noted
earlier, over 100 million people in the MENA region are youth, a demographic dividend that
provides the region with an enormous opportunity for economic growth and development that has
yet to be seized (Dhillon and Yousef 2007). Instead, despite greater achievement in education,
youth unemployment rates in the MENA are the highest in the world. In 2010, it was estimated that
23.7 percent of youth were out of work, triple the unemployment rate for adults. Only 21.5 percent
of girls in the region, ages 15 to 24, participate in the labor force, the lowest rate for girls of any
region in the world (UNICEF 2010).
Without the income needed to start their own family, youth throughout the region are marrying
much later and some women are not marrying until their 20s or 30s (Rashad et al. 2005). In
Morocco, the average age of first marriage is 31 for men and 26 for women (Boudarbat and Ajbilou
2007). The median age at first marriage remains relatively low in the Gulf states; it is reportedly
17.5 years in Oman, 19.5 years in Saudi Arabia and 18.6 years in the United Arab Emirates (Shepard
2005).
17
While there are many benefits to delaying marriage, this trend has been driven by a poorly
performing labor market and chronic poverty rather than an expansion in life choices. Young
people as a result are delaying important key transitions into adulthood and remaining
economically dependent on their families at a time when they are seeking greater independence
(Dhillon and Yousef 2007; Singerman 2007). In addition, given social mores that prohibit sex
outside of marriage, unmarried youth do not have access to reproductive and sexual health
information and services and are at greater risk for unwanted pregnancy and sexually transmitted
diseases (Shepard 2005). The reality of a prolonged period of “waithood” has disappointed the
heightened expectations among a better educated, more urbanized youth about what their
prospects for work, family and marriage should be, leading to frustration and a desire for change.
The participation of youth in developing policies and programmes is critical; avenues for
meaningful civic engagement for young people must be provided beyond sports clubs, the military
and religious activities.
18
Inequity in Child Wellbeing: Going Beyond the Averages
This section moves beyond national averages to identify disparities in child wellbeing based on
whether children live in a rural or urban area, their subregion, their household wealth or the
educational level of their household head, and their gender. It explores inequity in 8 MENA
countries: Algeria, Djibouti, Egypt, Iraq, Morocco, oPt, Syria and Yemen. All are lower middle
income, medium human development countries except Djibouti and Yemen, which have low
country development and high child mortality. (Iraq is classified as “without rank” in the Human
Development Index.) No data was available for any of the high income countries from the Gulf.
Table 4.1 provides country averages for selected indicators of child well-being and the total
weighted average for all 8 countries.8 While numbers vary, a significant percentage of children
suffer from severe deprivation in most of the indicators9. One of the worst indicators is for shelter.
An average of 22.6 percent of children from the 8 countries studied is deprived of shelter, meaning
that they live in households that either have no flooring material or where five or more people
share a room. Nearly 9 percent of children had no access to clean water, and 5.8 percent of the
women aged 15 to 49 were married as adolescents under the age of 15. On average, 10.4 percent of
children between the ages of 5 and 14 support themselves or their households through child
labour. Outcomes are vary greatly, however, by country. For example, while the incidence of child
labour in Yemen is 27 percent, in Morocco and Algeria it was only 2.3 percent and 3.8 percent
respectively.
Table 4.2 illustrates how outcomes on different indicators vary by country: whether a country's
outcome is 25 percent above the weighted average for all countries, less or more than 25 percent
below it.10 In Algeria, Syria and oPt, deprivations for at least half of indicators are 25 percent below
the weighted average. By contrast, at least a third of the indicators of deprivation in Morocco, Iraq,
Djibouti and Yemen are 25 percent higher than average (see Table 4.2). At 22.6 percent, the
average incidence of shelter deprivation for all eight countries was quite high, but it is concentrated
in three countries (Djibouti, Iraq and Yemen) where the incidence is above the average. While only
7.2 percent of children in the eight countries has never received an education, the incidence of
deprivation much higher than the average in Djibouti, Iraq, Morocco and Yemen.
Weighted averages (last column of Table 4.1) for each indicator were estimated by using the corresponding
population groups for each variable and each country. For example, the weighted average in the case of
shelter was calculated by using the under age 18 population for each country; for early marriage, the
population of women aged 15 to 49 was used, and the weighted average for immunization uses the
population of children under the age of 5.
8
9
For the definition of indicators see Annex III.
Table 4.2 begins by assuming a weighted average for the eight countries to be 100 for each variable and
then calculating the ‘distance’ that each country is from 100. For example, when adjusted for total weighted
average, Algeria’s incidence for shelter deprivation is 66.0, or 34% lower than the total average for all eight
countries.
10
19
Algeria
Djibouti
Egypt
Iraq
Morocco
oPt
Syria
Yemen
Weigthed
Average
Table 4.1: Child and maternal wellbeing in 8 MENA countries: National averages in selected indicators for children and women
(percentage in all cases except child mortality, which is per 1,000 live births). See Annex III for definitions.
Shelter severe deprivation (U18)
14.9
55.7
14.8
30.8
25.0
4.1
19.3
42.9
22.6
Water severe deprivation (U18)
6.3
6.6
2.8
10.2
20.0
0.0
2.4
22.6
8.9
Sanitation severe deprivation (U18)
0.0
10.2
4.2
2.9
12.0
0.0
1.3
31.0
7.5
Married before 15 (w.15-49)
0.8
2.8
7.4
5.4
5.3
3.1
3.4
13.3
5.8
Married before 18 (w.15-49)*
6.5
8.1
27.8
21.0
15.0
20.0
15.4
26.5
20.1
Not antenatal care (w.15-49)
Infant mortality rate U5 -per 1000-
12.4
26.4
16.2
Dimension
Household
Women
Indicator
Nutrition less severe deprivation -Stunted
or Underweigth or Wasting- (U5)
Child
wellbeing
Child
protection
94.0
8.5
Health severe deprivation (U5)
Not measlesor or MMR immunized (12-23
months)
No education (7-17)
33.4
30.7
3.8
6.4
2.4
9.3
2.2
16.0
88.4
45.5
27.0
12.1
14.0
4.5
39.9
18.3
20.3
113.8
13.1
38.2
13.0
44.9
17.8
14.0
24.4
3.2
9.5
11.0
0.7
2.5
20.3
7.1
12.2
31.7
11.3
1.6
20.9
5.7
15.5
2.3
5.1
3.8
27.0
10.4
Not attending school (6-11)
Child labour (5-14)
16.5
3.8
6.0
11.9
10.3
Birth not registered (U5)
0.7
8.6
4.9
4.8
2.1
4.2
72.3
14.5
Orphans (U5)
4.0
11.3
4.7
6.2
2.9
3.3
5.1
4.8
*Woman 25-49 years.
Sources: MICS 3 – 2006; for Egypt, DHS 2008 for all indicators except “Not attending school” and “Child labour”, which use MICS 3 – 2006.
20
Household
Women
Child
wellbeing
Child
protection
Weigthed
Average
Yemen
Syria
oPt
Morocco
Iraq
Egypt
Indicator
Djibouti
Dimension
Algeria
Table 4.2: Comparing child and maternal outcomes to regional averages. Country outcomes that are 25% above or below the weighted
average for all 8 MENA countries studied (sum of weighted national averages of selected countries = 100).
Shelter severe deprivation (U18)
100.0
22.6%
Water severe deprivation (U18)
100.0
8.9%
Sanitation severe deprivation (U18)
100.0
7.5%
Married before 15 (w.15-49)
100.0
5.8%
Married before 18 (w.15-49)*
100.0
20.1%
Not antenatal care (w.15-49)
Infant mortality rate U5 -per 1000-
100.0
20.3%
100.0
38.2%
Nutrition less severe deprivation -Stunted
or Underweigth or Wasting- (U5)
100.0
13.0%
Health severe deprivation (U5)
100.0
14.0%
100.0
24.4%
100.0
7.1%
Not attending school (6-11)
Child labour (5-14)
100.0
15.5%
100.0
10.4%
Birth not registered (U5)
100.0
14.5%
Orphans (U5)
100.0
4.8%
Not measlesor or MMR immunized (12-23
months)
No education (7-17)
*Woman 25-49 years.
Sources: MICS 3 – 2006; for Egypt, DHS 2008 was used for all indicators except “Not attending school” and “Child labour” which use MICS 3 – 2006.
21
National averages provide an overall picture of the percentage of children facing deprivation, but
they mask disparities among vulnerable groups in each country, such as ethnic or religious
minorities, which are not typically identified in population-based surveys. The figures in this
section unpack the national averages in Tables 4.1 and 4.2 by comparing the relative gap in child
well-being between the following ‘inequity dimensions’: rural and urban households; households in
which the head has no education, compared to those with at least a secondary education;
households in the poorest wealth quintile (Q1) and households of the richest (Q5); and between
subregions. Relative gaps between disadvantaged and advantaged groups are expressed as a
multiple: for example, Figure 4.1 shows that while 55.7 percent of children in Djibouti are severely
deprived of shelter, children in some rural households are 1.7 times more likely to be severely
deprived than urban children. Designing data collection tools that can gather evidence on specific
vulnerable groups will improve the ability to track inequity.
The indicators presented in this section are: shelter, early marriage, mortality before age 5,11
education, and child labour. Information on all indicators, including the absolute values of
disaggregate incidence by inequity dimensions and relative gaps, are presented in the statistical
annex.
Shelter
One in five children in the eight countries studied are shelter deprived. Figure 4.1 demonstrates
how two pairs vulnerability –education of household head versus wealth quintile, rural/urban
residence versus subregion – affect the likelihood of children living in housing that is severely
overcrowded (five or more people to a room) or which has no flooring material. (Gender is not
represented as deprivation among boys and girls was equal.) National averages are shown in
parentheses next to each country’s name; the numbers at the tip of each bar on the graphs indicate
the gap or ration between disadvantaged and advantaged groups, such as rural versus poor. The
vertical line running through the graphs at 1 is the point of equality between disadvantaged and
advantaged groups; the more the ratio exceeds 1, the greater the gap. For example, children living
in Morocco’s rural areas were 7.1 times more likely to be shelter deprived than children in urban
areas, whereas the rural/urban gap in Iraq was only 1.43.
Comparing countries with similar national averages demonstrates how sources of inequity are
specific to local contexts. Both Algeria and Egypt have nearly identical national averages for shelter
deprivation – 14.9 percent and 14.8 percent respectively. Yet in Egypt, the household head’s
educational level and rural residence are the most important determinants, whereas in Algeria, all
four determinants are closely overlapping. In Morocco and Iraq, 25 percent and 30.9 percent of
children are shelter deprived. Rural children in Morocco are 7.1 times more likely to suffer shelter
deprivation than urban children. In Iraq, however, a rural/urban gap of 1.4 suggests that a high
percentage of urban children live in severely overcrowded housing as well.
If we compare the top and bottom graphs in Figure 4.1, we see that subregion is quite an important
determinant of shelter deprivation for most of the countries presented. In fact, it exerts the
greatest influence of any factor in all 8 countries except Syria, Algeria and Egypt. Overall, the
graphs demonstrate how different types of vulnerability often overlap to reinforce deprivation. For
example, both the educational level of the household head and rural residence are strongly
correlated with overcrowded housing in Egypt, whereas poverty and subregion overlap as sources
of inequity for children’s housing in Syria. The influence of subregion and the overlap of various
forms of vulnerability appeared throughout the study for most indicators of child wellbeing.
The estimation of mortality before age 5 was done using ‘indirect methods’ see Annex Definition of
Indicators
11
22
Figure 4.1: Shelter Deprivation in 8 MENA countries. Likelihood of children under 18 years living
in a dwelling with 5 or more people per room or if they live in a house with no flooring based on
rural/urban residence vs. subregion; and education of household head12 vs. wealth quintile.13
Gaps (ratio between disadvantaged and advantaged)
Djibouti (55.7%)
2.7
1.75
Yemen (42.9%)
10.0
2.1
Iraq (30.8%)
Subregion
Rural/Urban
2.7
1.43
7.2
7.1
Morocco (25%)
Syria (19.3%)
1.37
Algeria (14.9%)
2.3
2.5
Egypt (14.8%)
oPt (4.1%)
Ratio
6.7
2.2
5.7
5.4
1.30
0
1
2
3
4
56
86
7
10
8
15
Gaps (ratio between disadvantaged and advantaged)
7.9
Yemen (42.9%)
2.9
Iraq (30.8%)
NonEduc/Sec&more
1.19
2.8
Morocco (25%)
6.0
10.1
Syria (19.3%)
2.0
2.7
Algeria (14.9%)
2.1
3.4
Egypt (14.8%)
8.2
3.2
oPt (4.1%)
Ratio
Poorest/ Richest
1.78
0
1
2
3
4
56
68
7
10
8
15
Sources: MICS 3 – 2006, Egypt DHS 2008.
12For
Egypt, educational level of mother, not household head, was used. No data for education of household
head and wealth quintile were available for Djibouti; no data by wealth quintile was available for Iraq.
The jagged line followed by grey shading on the horizontal axis indicates that the scale changes after 4. The
bars that shaded dark blue in the top chart and gold in the bottom chart indicate that the most disadvantaged
group was compared to the national average instead of the most advantaged group.
13
23
Early Marriage (under age 15)
Overall, early marriage has been on the decline in the MENA region, partly as the result of progress
made in girls’ access to education but also as a result of economic barriers to marriage.
Nevertheless, a significant number of adolescent girls continue to marry, compromising their
reproductive, sexual and emotional health as well as curbing their opportunities for economic and
social participation (Rashad and Osman 2005; Singerman 2007). Figure 4.2 shows how four types
of vulnerability – education of household head, wealth quintile, rural/urban residence and
subregion – affect the likelihood of women aged 15 to 49 years having been married before the age
of 15 in the countries with information. Again, each bar represents the relative gap, or ratio,
between the most disadvantaged and most advantaged women in each of the four categories. The
vertical line at 1 indicates complete equity; the more the ratio exceeds 1, the greater the gap. For
example, 7.4% of Egyptian women aged 15-49 have married before the age of 15, but women
whose mother had no education (the most disadvantaged) are 9.8 times more likely than women
whose mothers had at least a secondary education (the most advantaged) to be married before
their 15th birthday.
When comparing the eight countries, no single universal determinant of early marriage emerges. In
Egypt, girls are most vulnerable to early marriage if they grow up in a home where the mother has
never been educated, but wealth is clearly also a factor. Unlike Egypt, the girls who are most at risk
of early marriage in Morocco are the poorest and live in the most disadvantaged subregion. In
Yemen, we see that early marriage is prevalent regardless of the educational level, wealth or
residence of the girls’ household. Rather, subregional location is the greatest determinant of early
marriage in Yemen (in this case, Al-Mahweet governorate). Subregion is also important in Iraq (AlMuthana), Syria (Daraa) and oPt (north Gaza).
Figure 4.3 tracks the incidence of early marriage among women aged 15 to 49 by wealth quintile.
Figure 4.2 showed that women were 7.4 times more likely to marry before their 15th birthday if
they were from the poorest quintile (the national average for under 15 marriage is also 7.4 percent
and not the same as the gap between poorest and richest quintiles). Figure 4.3 dramatically
illustrates the effect of poverty on early marriage in Egypt: the red line sloping downward
diagonally across quintiles shows a rapid decline, from nearly 15 percent to 2 percent, as
households acquire wealth. In Yemen, early marriage is quite high even among the richest quintiles
(11 percent compared to 16 percent in the poorest). Wealth has very little impact on early
marriage in Algeria, Djibouti, Morocco and oPt; it is actually slightly higher among women in the
richest quintile in Syria.
24
Figure 4.2: Early Marriage in MENA. Likelihood of marriage before age 15 between among women
(15-49 years) based on education of household head, 14 wealth quintile, rural/urban residence and
subregion. 15
Gaps (ratio between disadvantaged and advantaged)
Yemen (13.3%)
5.4
1.09
Egypt (7.4%)
Iraq (5.4%)
3.4
1.18
Subregion
1.92
1.64
Morocco (5.3%)
Syria (3.4%)
0.68
oPt (3.1%)
0.75
4.6
2.0
1.22
Algeria (0.8%)
1.69
0
1
Rural/Urban
4.5
Djibouti (2.8%)
Ratio
4.6
2.4
2
2.7
3
4
65
68
7 15
8 20
9 25
10
10
Gaps (ratio between disadvantaged and advantaged)
1.49
1.14
Yemen (13.3%)
7.4
Egypt (7.4%)
23.8
Iraq (5.4%)
1.02
Morocco (5.3%)
2.0
NonEduc/Sec&more
0.83
0.84
Syria (3.4%)
1.21
1.13
oPt (3.1%)
2.1
Djibouti (2.8%)
4.6
Algeria (0.8%)
Ratio
Poorest/ Richest
3.1
3.4
1.70
0
1
2
3
4
65
68
7 15
8 20
9 10
10
25
14For
Egypt, educational level of mother, not household head, was used. No data data by wealth quintile was
available for Iraq.
The jagged line followed by grey shading on the horizontal axis indicates that the scale changes after 4. The
bar that is shaded gold in the bottom chart indicates that the most disadvantaged group was compared to the
national average instead of the most advantaged group.
15
25
Figure 4.3: The Impact of poverty on early marriage in 8 MENA countries. Percentage of women,
ages 15-49 years, who were married by their 15th birthday; by wealth quintile.
20
Yemen (13.3%, Q1/Q5: 1.49)
Syria (3.4%, Q1/Q5: 0.83)
oPt (3.1%, Q1/Q5: 1.21)
Morocco (5.3%, Q1/Q5: 3.1)
Egypt (7.4%, Q1/Q5: 7.4)
Djibouti (2.8%, Q1/Q5: 2.1)
Algeria (0.8%, Q1/Q5: 3.4)
18
16
14
12
10
8
6
4
2
0
Poorest
Second
Middle
Fourth
Richest
Sources: MICS 3 – 2006; Egypt uses DHS 2008.
Access to Education
Education is another area of child wellbeing where MENA countries have made a great deal of
progress, and yet lack of education continues to limit the futures of a significant number of children.
One in ten children in Iraq and Morocco and one in five in Djibouti and Yemen have never received
an education. Figure 4.4 shows how different forms of inequity combine to deprive children of
education. In the bottom graph, subregional location is more important than rural/urban residence
for 5 of 8 MENA countries in creating inequity in children’s access to education. It is not the key
determinant, however, except in Syria, where children living in the most disadvantaged region
(Raqqa, an economically depressed agricultural area in the northeast) are 18.3 times less likely
than children living in the most advantaged region to have had any education. Overall, poverty and
the household head’s lack of education combine to produce the greatest disparities in education.
Subregion is an influence, but has less impact. For example, while education deprivation affects
only 2.2 percent of children in Algeria, children are 14.2 times less likely to have an education if
they are in the poorest quintile, and 7.4 times less likely if their household head was never
educated. Egypt and Morocco follow similar patterns. Although household education level is not
the lead factor in any of the countries studied, Figure 4.4 highlights how it combines with other
forms of vulnerability to curtail children’s access to education.
26
Figure 4.4: Children deprived of education in 8 MENA countries. Likelihood of children (ages 717 years) never receiving education based on rural/urban residence vs. subregion; and education of
household head16 vs. wealth quintile. 17
Gaps (ratio between disadvantaged and advantaged)
6.0
Yemen (20.3%)
2.8
Rural/Urban
1.63
Morocco (11%)
5.5
6.1
Iraq (9.5%)
3.4
4.7
Egypt (3.2%)
2.4
18.3
Syria (2.5%)
1.85
1.27
Algeria (2.2%)
4.2
4.7
oPt (0.7%)
Ratio
Subregion
2.2
2.5
Djibouti (18.3%)
0.84
0
1
2
3
4
56
6
8
7
10
8
15
9
20
Gaps (ratio between disadvantaged and advantaged)
6.5
Yemen (20.3%)
4.8
11.2
Morocco (11%)
6.2
Iraq (9.5%)
5.4
11.3
10.0
Egypt (3.2%)
7.5
Syria (2.5%)
6.3
14.2
Algeria (2.2%)
7.4
Ratio
Poorest/ Richest
1.72
2.2
oPt (0.7%)
0
1
2
3
NonEduc/Sec&more
4
56
6
8
7
10
8
15
9
20
16For
Egypt, educational level of mother, not household head, was used. No data for education of household
head and wealth quintile were available for Djibouti; no data by wealth quintile was available for Iraq.
The jagged line followed by grey shading on the horizontal axis indicates that the scale changes after 4. The
bar that is shaded gold in the bottom chart indicates that the most disadvantaged group was compared to the
national average instead of the most advantaged group.
17
27
Sources: MICS 3 – 2006; Egypt uses DHS 2008.
Figure 4.5: The impact of poverty on access to education in MENA. Percentage of children (7-17
years) never educated, by wealth quintile.
50
Yemen (20.3%, Q1/Q5: 6.5)
Syria (2.5%, Q1/Q5: 7.5)
oPt (0.7%, Q1/Q5: 1.7)
Morocco (11%, Q1/Q5: 11.2)
Egypt (3.2%, Q1/Q5: 11.3)
Algeria (2.2%, Q1/Q5: 14.2)
45
40
35
30
25
20
15
10
5
0
Poorest
Second
Middle
Fourth
Richest
Sources: MICS 3 – 2006; Egypt uses DHS 2008.
Figure 4.5 offers another example of how inequity differs by country, but it also demonstrates how
national averages can mask disparities among vulnerable groups such as those in the poorest
wealth quintile.
Syria, Egypt and Algeria all have similar national averages when it comes to the percentage of
children who have never been educated. The greatest disparity for all three is among children in
the poorest quintile; the prevalence of children without any education is similar between the
second and richest quintiles.
In Morocco, there is a much bigger gap between children in the poorest two quintiles and children
in the wealthier quintiles, implying that poverty is a greater source of vulnerability for children
than in some of the other countries. Although 11 percent of Moroccan children nationwide have
never been educated, in the poorest quintile 25 percent of children have no schooling.
Yemen has a very high prevalence of children who have never been educated – it is 20 percent –
and as seen from the dark blue line in Figure 4.5, it remains high even in the richest quintiles. (6.7
percent of children among the richest quintile are not educated.) Although lack of education is a
problem across the board, we can see that in the poorest quintile it is especially high – affecting
nearly half of all children.
Gender and Education
Overall, MENA states have made substantial gains towards universal enrolment of children in
school and achieving gender parity. While adult literacy persists for generations that have come
before reforms in the region’s educational systems, more girls than ever are completing secondary
school and entering university – even outnumbering young male university students in some
countries. In Figure 4.6, female and male net enrolment patterns are represented by Yemen,
28
Tunisia and Morocco. Pre-primary rates are low everywhere except Morocco. Tunisia and
Morocco’s high primary school enrolments reflect those throughout the region; enrolments are
much lower in Yemen, especially for girls. However, secondary enrolments drop in all three
countries, most precipitously in Morocco and Yemen. Figure 4.7 shows the female to male ratio, or
gender gap, in enrolment. A ratio of 1.00 equals perfect gender parity, regardless of whether
enrolments are high or low. Girls fall farthest behind boys in secondary enrolment in Yemen,
followed by Morocco. However, in Tunisia girls actually outnumber boys in secondary education,
even though a lower percentage of girls – and boys – continue their education after primary school.
The trend continues for tertiary education. While the gender gap disadvantages young women in
Yemen and, to a lesser extent, Morocco, far more young women in Tunisia are entering tertiary
education than young men. Most high income and several middle income countries follow the
example of Tunisia, where near or perfect parity is reached in primary school, but girls begin to
outnumber boys in secondary and especially in tertiary education despite declining total
enrollments.
29
Figure 4.6: Girls’ and boys’ net enrollment in education: Percentage of girls and boys enrolled18 at
different levels of education appropriate for their age.
Yemen
Tertiary
Secondary
Primary
Pre-Primary
Tunisia
Tertiary
Secondary
Female
Male
Primary
Total
Pre-Primary
Morocco
Tertiary
Secondary
Primary
Pre-Primary
0
20
40
60
80
100
Source: UNESCO Institute of Statistics
18
Gross enrollment used for pre-primary and tertiary. Net enrollment used for primary and secondary.
30
Figure 4.7: Gender gap in education: Ratio between girls’ and boys’ net enrollment at different
levels of education. Perfect equality between genders is equal to 1.
Female/ Male ratio
Tertiary
Secondary
Yemen
Tunisia
Primary
Morocco
Pre-Primary
0.00
0.50
1.00
1.50
2.00
Source: UNESCO Institute of Statistics
Determinants of Child Labor in 8 MENA Countries
Advocates distinguish between “child work”, which encompasses the entire scope of work-related
tasks that children may perform, and “child labour”, usually a smaller subset which describes work
that is harmful to children and that should be targeted for elimination. While both boys and girls
work, child labour is divided by gender. Boys tend to have more paid, skilled work in small
industries such as car repair, manufacturing, or in rural areas, agriculture. While in some settings
girls may also be found in agriculture, unskilled manufacturing or traditional handicrafts, they are
largely found working as domestic servants or carrying out unpaid domestic chores at home (USW
2003; Ahmed 2010; Assaad 2010; Abu Ghazaleh 2004; Khalidi 2004). Of the eight countries
studied here, child labour is highest in Yemen, where it affects over a quarter of all children, and
Egypt and Iraq, where one in ten children work in harmful forms of labour.
The top graph in Figure 4.8 shows that in all 8 MENA countries, subregional location is far more
important than rural/urban residence, gender and even poverty or household education, in
determining inequity in child labor. This is less so for Iraq and Egypt, where rural residence and
subregion overlap. (The subregion in Iraq with the highest rate of child labour is Babil, an
agricultural area; in Egypt it is Rural Upper Egypt.) In the countries where child labour is quite low
– 6 percent or less – the effect of inequity is clear. Living in a particular subregion can increase the
risk of child labor by 9.1, 10.8 and even 15.5 times in oPt, Syria and Morocco respectively.
31
Figure 4.8: Determinants of child labour in 8 MENA Countries. Likelihood of child labour among
children (ages 5-14 years) based on their subregion, rural/urban residence or gender; and education
of household head19 or wealth quintile. 20
Gaps (ratio between disadvantaged and advantaged)
Yemen (27%)
5.7
1.79
1.76
1.57
Egypt (11.9%)
2.2
Subregion
2.08
6.3
3.7
Iraq (10.3%)
0.59
Rural/Urban
Female/Male
5.8
Djibouti (6%)
0.94
1.02
9.1
oPt (5.1%)
1.41
Algeria (3.8%)
1.51
3.49
4.1
0.62
Syria (3.8%)
0.49
15.5
2.0
Morocco (2.3%)
0.51
0
Ratio
10.8
2.2
1
2
3
4
65
86 10 7 15 820 9
Gaps (ratio between disadvantaged and advantaged)
Yemen (27%)
1.51
Egypt (11.9%)
2.4
1.89
Iraq (10.3%)
2.7
1.54
NonEduc/Sec&more
1.19
1.25
0.80
oPt (5.1%)
2.2
1.95
Algeria (3.8%)
Syria (3.8%)
Morocco (2.3%)
Ratio
Poorest/ Richest
2.4
Djibouti (6%)
2.5
0
1
2
3
3.1
3.2
4
4.6
65
68
7
10
8 20
9
15
19For
Egypt, educational level of mother, not household head, was used. No data by wealth quintile was
available for Iraq.
The jagged line followed by grey shading on the horizontal axis indicates that the scale changes after 4. The
bar that is shaded gold in the bottom chart indicates that the most disadvantaged group was compared to the
national average instead of the most advantaged group.
20
32
Source: MICS 3 – 2006.
MICS data incorporate both domestic chores and economic activity into its definition of child
labour, enabling it to more accurately capture girls’ unpaid labour. Gender has an interesting
relationship to child labour in the MENA region; whether boys or girls are more vulnerable depends
on the country. In Iraq, Algeria, Morocco and Syria, boys are somewhat more likely than girls to
work in harmful forms of labour. The ratios are low, however, ranging from .49 in Algeria to .62 in
Syria, and child labor is below 4 percent in all of them except Iraq (10.3 percent). In Djibouti, girls
and boys are equally vulnerable to child labour. Girls are more likely to engage in child labour than
boys in Yemen, Egypt and oPt. Girls’ labour is twice as common as boys’ in Egypt (16.2 percent
compared to 7.8 percent), and in oPt, girls are three and a half times more likely than boys to be
working in child labour (8 percent of girls compared to 2.3 percent of boys). Although the relative
gap between girls and boys in Yemen appear narrow – 1.76 – it is significant given the higher
overall incidence of child labour there: 34.6 percent of Yemeni girls compared to a fifth 19.7 percent
of boys. These findings raise questions about working children’s ability to attend and complete
school, which is beyond the scope of the present study. A handful of studies have begun to analyze
the trade-off between gender, child labour and education in Egypt and Lebanon (Ahmed 2010;
Assaad 2010; Abu Ghazaleh 2004; Khalidi 2004); however, far more quantitative study of the topic
in the region is needed.
The bottom graph shows that, while wealth may be more important than the educational level of
the household head in determining child labor, it is not by much, and the gaps are not as high as
they are by subregion (the yellow bars in the left hand chart). For example, in oPt, child labor is just
as likely in the poorest households compared to the richest, and exists regardless of whether the
household head has at least a secondary education or none at all.
Figure 4.9 follows rates of child labor across wealth quintiles. In the countries where the incidence
of child labor is highest – Yemen (27 percent) and Egypt (11.9 percent) child labor is even a
problem for children in the richest quintiles – affecting 16.2 percent of children in Yemen and 6.2
percent in Egypt. Yet in all of the countries shown here, children from the poorest quintile are 2 to
3 times more likely to engage in child labor than children from the richest. In Syria, the gap
between quintiles is higher (4.6). These disparities highlight the need for policies seeking to reduce
child labor must include measures to address greater vulnerability among children in the poorest
quintile.
33
Figure 4.9: The impact of poverty on child labor in 8 MENA countries. Percentage of child labour
among children aged 5-14 years, by wealth quintile.
45
Yemen (27%, Q1/Q5: 2.4)
Syria (3.8%, Q1/Q5: 4.6)
oPt (5.1%, Q1/Q5: 1.25)
Morocco (2.3%, Q1/Q5: 3.2)
Egypt (11.9%, Q1/Q5: 2.7)
Djibouti (6%, Q1/Q5: 2.4)
Algeria (3.8%, Q1/Q5: 2.2)
40
35
30
25
20
15
10
5
0
Poorest
Second
Middle
Fourth
Sources: MICS 3 – 2006; Egypt uses DHS 2008.
34
Richest
5. Conclusion
This report explored the impact of two types of inequity on children: material deprivation in access
to goods and services, such as education or immunization, and discrimination on the basis of a
child’s gender, ethnicity, religious identity, citizenship or migration status, or other basis. These
two forms of inequity overlap and interact to create new vulnerabilities including the lack of
opportunity and loss of rights. Such is the case of girls and boys who, perceived as not deserving of
their rights because of their ethnicity, must live with in a crowded slum without clean water or
sanitation; or who, deprived of the right to birth registration and citizenship, are unable to attend
school or legally work when they become adults. The cumulative result of discrimination when it
overlaps with material deprivation is multigenerational disadvantage as children grow into adults
who lack the skills, wellbeing and opportunities to support their families and actively engage in the
economic and civic life of their communities.
The methodology used in this report to calculate inequities between disadvantaged and advantaged
groups is new and more analysis is needed to fully interpret the significance of the gaps identified.
Thus far, however, several findings about inequity emerged when comparing disparities in material
deprivation based on children’s gender, wealth quintile, rural or urban residence, subregion and
their household head’s educational level.
1. Subregion exerts a strong influence on inequity and is often the most important
determinant of negative outcomes for children. Subregions where children are most
disadvantaged most likely have not received the same level of investment and
infrastructure as others, such as governorates in remote border areas, and may be
economically depressed. Services may be interrupted by armed conflict or political
instability, or may still await rebuilding post-conflict. In some areas, disadvantaged
subregions may correlate with the presence of ethnic or religious minorities or other
marginalized populations. If so, governments must work to identify and eliminate
discriminatory policies and ensure that all communities have equal access to resources and
services.
2. Disparities in children’s wellbeing is often the result of several overlapping
determinants, even if one determinant dominates. Shelter and lack of education
provide the two clearest examples where two or more variables combined to place children
at even greater risk of deprivation. Rural residence was an important factor for shelter,
water and sanitation, implying a lack of infrastructure outside most urban areas. Wealth, or
rather poverty as found in the lowest wealth quintile, overlapped with subregion for many
indicators and was especially important in Morocco and Algeria. Greater vulnerability was
often also associated with a household head who had no education, particularly in the case
of children not receiving an education and in the case of orphans.
3. A number of groups which are not officially represented in the data are denied their
rights and suffer from material deprivation because of discrimination. Whether
because of gender, ethnicity, religious identity, migration or noncitizen status, or disability,
they lack access to school and other basic services, are at greater risk of violence and
exploitation, and are less likely to leave poverty as a result. While disadvantaged
subregions, rural residence, poverty and households in which the head has no education all
serve as potential indicators of greater vulnerability and inequity, a commitment must be
made to tracking inequity among children who experience ethnic, religious and other forms
of discrimination.
35
4. Although the overall incidence of deprivation in education is low, disparities between
children who do or do not go to school are significant. Disparities between
disadvantaged and advantaged groups appear to be greatest where incidences are lowest,
underscoring the role of discrimination and inequity in blocking progress towards universal
education. Deeper analysis that explores more concretely the relationship between gender,
child labour and education could further shed light on barriers to school attendance and
guide country-level policy.
36
6. Key Recommendations
1. Utilize affirmative action policies to ensure that all children, regardless of gender,
ethnicity, religion, citizenship or disability have equal access to basic services, programs
and protection of their rights. Policies should follow children into young adulthood,
guaranteeing equity in access to employment, workforce development, land and other
economic opportunity for youth. Public campaigns, using local languages and other
strategies to reach vulnerable groups, should raise awareness about the availability of social
programs and entitlements, the right of all children to access them, and where to report
complaints when access has been denied. At the same time, public media campaigns and
school curricula should work to promote respect for diversity and change public
perceptions that fuel discrimination.
2. Target investments in programs focused on vulnerable children who are discriminated
against, in a way that recognizes the potentially significant contribution they can make to
the economic and civic life of their communities. These can range from social protection
programs such as cash transfers, to funding teacher training and curricula development that
allows children with disabilities to attend mainstream schools, to investing in public works
projects to build much needed infrastructure in remote areas and provide jobs to
marginalized communities. Given the strong presence of subregional inequity in this study
as a key source of child deprivation, investment in rural infrastructure is critical. Leakages
in investment can be prevented by using automatic cash transfer points, timing public work
projects to coincide with low-labor seasons, and radio campaigns that inform communities
of their rights (Kabeer 2007).
3. Improve data collection and strengthen evidence to make vulnerable children visible to
policy makers and monitor inequity and discrimination. MICS and DHS already have the
capacity to disaggregate data by gender and age; they should also gather information on
children’s ethnicity, religious identity, migration and noncitizen status, and disability.
Moreover, countries must work with partners to collect household level micro data on child
wellbeing. Over half of the countries in the MENA region are classified as high or mediumhigh development according to their GDP per capita and rank high on the Human
Development Index. Yet paradoxically, there is a near absence of information on basic
indicators of child wellbeing such as nutrition and child mortality. As shown in Figure 3.11,
the lack of available information compared to other ‘less developed’ regions is striking.
4. Develop child-led communication strategies. UNICEF is already part of Children in a
Changing Climate, a coalition of international agencies and NGOs that work with children as
agents of change and disaster-risk communicators. The groundbreaking work of the
coalition recognizes that children are strategic players in communicating the risk of disaster
to peers and relatives, identifying vulnerable children in their neighborhoods who might
otherwise be invisible to local authorities, and proposing creative solutions for disaster
recovery (Tanner 2010; Seballos 2009). Similarly, child-led communication strategies can
help convey messaging that challenges discrimination, disseminate information into hard-to
reach communities about rights and entitlements, identify vulnerable children, and spark
innovate ideas about other strategies for advancing equity for children.
5. Identify opportunities to advance the equity agenda in a way that supports
participation by adolescents and youth. Throughout the region, young people have been
leading social movements that call for political and economic change. Many of the youth
involved have benefited from improved education, but have been frustrated by the high
37
unemployment that awaits them after graduation and the limited avenues available for
meaningful civic participation. As a consequence, MENA countries have missed not only the
economic contribution of its considerable wealth of youth, but the energy, innovative ideas
and aspirations that young women and men bring. As UNICEF seeks to promote equity for
children in the MENA region, it should develop communications and advocacy strategies
that allow the participation and leadership of adolescents and youth, particularly those
representing groups that have traditionally faced discrimination.
38
Annex I: Methodological Note
This note explains the methodology used in preparing the regional report “Equity for Children and
Adolescents in the Middle East and North Africa: An Opportunity for Growth.” The report seeks to
identify sources and locations of child inequities within countries in the Middle East and North
Africa region to better inform programme design and implementation. Public programmes in the
fields of survival, early development, education and protection are essential to a child’s
development and full membership in society. The fulfilment of these rights not only depends on
family income, but also involves other factors that range from availability and quality of services to
issues related to discrimination and neglect (UNICEF, 2000; United Nations Development
Programme, 2000). By examining the differing levels of access to services and opportunities among
groups of children, a more nuanced and specific assessment of needs can be conducted in order to
achieve more effective programming and implementation.
This study’s selection of indicators and thresholds for analysing geographic and wealth disparities
follows UNICEF’s methodology for measuring child poverty and disparity based on the concept of
child deprivation. This methodology was first applied worldwide in the early 2000s and published
in 2003 (Gordon, SWOC 2005, Minujin 2003). This landmark study estimated child deprivation and
child poverty in the developing world using, for the first time, a multidimensional approach and
child-specific indicators. In 2006, UNICEF launched the Global Study on Child Poverty and Disparity
based on the same methodology. The Global Study covered more than 40 countries, five of them in
MENA.21
The seven selected child deprivation dimensions used in the Global Study and adopted by the
present report are based on a definition of poverty agreed upon by the governments of 117
countries at the World Social Summit in Copenhagen: absolute poverty was defined, for policy
purposes, as "a condition characterised by severe deprivation of basic human needs, including food,
safe drinking water, sanitation facilities, health, shelter, education and information. It depends not
only on income but also on access to social services" (UN, 1995, p57).
Indicators and thresholds for those seven dimensions – food/nutrition, water, sanitation, health,
shelter, education and information – were adopted according to the theory of ‘relative deprivation’
that conceptualises a continuum (see Box 1 below) ranging from no deprivation to extreme
deprivation (Gordon, 2002).
In order to gather, analyse and present information on child inequities, and better inform policy
design and implementation affecting child rights, inequities can be related to each other and
observed through two combined dimensions. As explained in the report’s conceptual framework,
these dimensions can be characterised as: 1) material deprivation related to economic and
geographic barriers; and 2) inequities related to vulnerabilities, discrimination and persistent or
‘durable inequality.’22
1) Material deprivation related to economic and geographic barriers, including income,
subregional, rural/urban and intra-urban inequalities. Children living in poverty face,
The five MENA countries covered in the Global Study were: Djibouti, Egypt, Morocco, oPt and Yemen.
‘Durable inequality’ describes persistent social inequality, in which groups are excluded and face barriers
to accessing rights and entitlements based on their belonging to socially defined categories, such as race,
ethnicity, citizen, or gender. Charles Tilly, Durable Inequality (University of California Press: 1999). Social
exclusion and durable inequality is one of the key issues to be explored to understand the root causes of
inequity. Paradoxically, information, especially quantitative, on groups experiencing discrimination is scarce.
This report provides a starting point for assessing such disparities.
21
22
39
during their life cycle, a series of difficulties accessing adequate goods and services for the
full development of their capabilities. These fundamental life obstacles start before birth,
beginning with a lack of prenatal care and inadequate maternal nutrition, and continue
during the child’s life, aggregating into more conditions of inequity for the child population.
Many children do not survive and for those that do, inequities of access create a difficult
situation in which to develop a productive and creative life. This lack of access perpetuates
the poverty cycle for the generation to come. These inequities of access to quality goods and
services are deemed ‘material deprivations.’ From a policy perspective these material
deprivations can be organized into two broad areas: a) economic or monetary deprivations
related to employment, salaries and family income, and b) basic social services disparities
related to policies of supply and access to quality public services for girls and boys alike.
2) Inequities related to vulnerabilities,23 discrimination and persistent or ‘durable
inequality.’ Vulnerable groups include ethnic and religious minorities, refugees and
displaced persons. Certain groups of children and adolescents are vulnerable or socially
excluded due to discrimination or durable inequalities linked to class, gender, race, ethnicity
or religious discrimination. Examples of these socially excluded groups are orphans,
children living in female-headed households, refugees and internally displaced children,
married adolescents and adolescent mothers, the disabled, sexually exploited and trafficked
children, and children belonging to ethnic or religious groups subject to societal
discrimination. These forms of inequities create distinct vulnerabilities resulting in lack of
opportunity, loss of rights and various forms of social exclusion. They are often
accompanied by material deprivations. When discrimination and material deprivations
combine, they often create the most vulnerable groups of children and adolescents. Children
and adolescents subject to such inequities should be considered, for the purposes of policy
and programme development, as distinct and vulnerable groups. These inequities are
mainly related to cultural discrimination and legal injustice.
Both forms of inequities are often interdependent and create a negative synergy in opportunities
for and capabilities of children and adolescents. For example, gender may determine different levels
of access to nutrition and education. Ethnicity may result in deprivations of certain opportunities in
education and employment. An adolescent girl living in poverty and belonging to a socially excluded
minority might have less opportunities in her life than a boy who is similarly poor but who does not
belong to a minority that is discriminated against. In this scenario, the girl accumulates several
inequity factors – gender, poverty and discrimination based on minority status – which implies that
disadvantages can combine in a negative, exponential way to limit the opportunities available to
her throughout her life. These inequities have life-long impacts as, for example, children from
socially excluded groups enter adulthood without the same preparation and access to opportunity
needed to increase their earning potential and leave poverty. The study of this kind of multicausality relations is not the object of the present report. Such a study requires specific qualitative
and quantitative information that goes beyond the scope of this report and the data available for
the region.
However, the quantitative information provided by household surveys such as MICS or DHS capture
valuable information related to child material deprivation that may be disaggregated, for example,
Vulnerability is related to risk and the capacity or readiness to cope with that risk. For example, while
soaring food prices may place children throughout an area at greater risk of food insecurity, girls in the
poorest households might be more vulnerable to negative coping strategies such as early marriage, school
drop out or child labour to reduce non-food expenses and lower the number of dependents in the household.
There are different vulnerabilities and different levels of vulnerability according to those dimensions.
23
40
by geographic location, gender, and wealth quintile. Administrative health and education records
seldom provide information that allows for analysis of the situation of children’s lives beyond broad
averages, effectively masking significant inequities.
Information relating to vulnerable groups of children and adolescents, such as adolescent mothers,
orphans or children belonging to marginalized ethnic groups, requires special surveys and
qualitative information that is not captured in household surveys. With more nuanced and
qualitative data, better informed policies and programmes can be developed.
Box 1: A Multidimensional Deprivation Approach
i) Bristol Deprivation Approach: The Bristol Deprivation Model was adopted by the
Global Study on Child Poverty and Disparity as a method to measure child poverty that not
only captures the multidimensional nature of child poverty, but also the depth of poverty.
The deprivation measures of child poverty are based on internationally agreed upon
dimensions of child wellbeing and the child rights enshrined in the CRC, namely: adequate
nutrition, safe drinking water, decent sanitation facilities, health, shelter, education and
information. The dimensions shown below were agreed upon at the 1995 World Social
Summit.
ii) The Seven Dimensions of Child Poverty
Food
Water
Shelter
Sanitation
Health
Education
Information
ii) The Continuum of Deprivation along Each Dimension
iii) Thresholds for Severe and Less Severe Deprivation in Each Dimension
Deprivation Severe
Food
Water
Less Severe
Age
Children whose height and
weight are more than 3 SDs
below the median of the
international reference
population.
Children who are more than 2
SDs below the median of the
international reference
population for stunting or
wasting, or are underweight.
Under
5yrs
Children who only have
access to surface water (e.g.
rivers) for drinking or who
live in households where the
nearest source of water is
more than 30 minutes round
trip away.
Children using water from an
unimproved source such as
open wells, open springs or
surface water or for whom it
takes 30 minutes or longer to
collect water.
Under
18yrs
41
Shelter
Children living in dwellings
with 5 or more people per
room or with no flooring
material.
Children living in dwellings
with 1 or more people per
room or in a house with no
flooring or inadequate
roofing.
Under
18yrs
Sanitation
Children without access to a
toilet of any kind in the
vicinity of their dwelling e.g.
no private or communal
toilets or latrines.
Children using unimproved
sanitation facilities e.g. poor
flush latrines, covered pit
latrines, open pit latrines, and
buckets.
Under
18yrs
Children who have not been
immunized against any
diseases or young children
who have had a recent illness
and have not received any
medical advice or treatment.
Children who have not been
immunized by 2yrs of age.
Children are defined as
deprived if they have not
received eight specific
vaccinations or if they have
not received treatment for a
recent illness involving an
acute respiratory infection or
diarrhoea.
Under
5yrs
Children who have never
been to school and are not
currently attending school.
Children of schooling age not
currently attending school or
who have not completed their
primary education.
717yrs
Health
Education
Information
Children without access to
Children with no access to
newspapers, radio, television, broadcast media (television
phones, or computers at
and radio).
home.
317yrs
iv) Incidence of Child Poverty Using Deprivation
Severe Deprivation: The condition of
being severely deprived in at least one
dimension.
Multiple Severe Deprivation: The
condition of being severely deprived in two
or more dimensions.
Source: UNICEF EAPRO Child Poverty in East Asia and the Pacific: Shared Vision, Different Strategies
(forthcoming) based on UNICEF Global Study on Child poverty and Disparity.
Strategy for gathering and presenting information on MENA Child Equity
Following the methodological conceptual framework presented above, the researchers pursued the
following strategies, depending on the availability of household survey micro data files:
I.
For the study of inequities of material deprivations in those countries with available
household survey micro data files, mainly MICS3, researchers employ the following steps:
42
Step 1: Complete, as much is possible, the attached spreadsheet with information on: a)
deprivation within the household; b) women/mothers, including social protection; c) child
wellbeing; and d) child protection. These statistics, where possible, are disaggregated by:
gender, urban/rural, wealth quintile, education of the household head or mother, and subnational regions24 (ethnic group information is not available for MENA).25 Please see Box 1 for
the definition of deprivation indicators and thresholds and the annex on definition of indicators.
(Access to information was not included as an indicator this study.)
Step 2: Selection of additional indicators, on top of the deprivation indicators included in Box 1,
that show relevant incidence and disparity. These include early marriage, prenatal care when
available, child labour, birth registration and orphanhood.
Step 3: Calculate the relative gaps using the extreme – the disadvantaged and advantaged –
categories of each selected indicator. For example, in the case of wealth quintiles the relative
gap is calculated as the ratio between the poorest quintile, Q1, and the richest quintile, Q5.
Disadvantage and advantage are assumed as follows:
Disadvantaged
Female
Rural
Worst subregion
Poorest quintile
Household Head has no
education
Advantaged
Male
Urban
Best subregion
Richest quintile
Household head has at least
a secondary education
Gaps between the advantaged and disadvantaged value for each indicator are determined by
dividing the percentage corresponding to the disadvantaged category in the numerator by the
advantaged category in the denominator. This ratio is called the relative gap. For instance, the
indicator “Total Child labour (5-14)” for Djibouti in the table below shows that the percentage of
working children in the poorest quintile, Q1, is 7.3% while the incidence of child labour in the
richest quintile, Q5, is 3%. The relative gap between the disadvantaged, Q1, and the advantaged, Q5,
is calculated by dividing the percentage of child labour in Q1, 7.3, by the incidence of child labour in
Q5, 3 The result is equal to 2.4, which is the relative or inequality gap presented in the figure
included in the report. It reveals that children in the poorest quintile are 2.4 times more likely to be
working than children in the richest quintile.
Table 1 presents the information related to the incidence of child labour in Djibouti by different
dimensions of inequality (see statistical annex). Figure 4.8 below shows the results of these
calculations for the 8 countries with available information included in the report.
The present report provides the relative gaps between the worst and best outcomes by subregion,
highlighting geographic location as a main factor in inequity. The statistical annex includes specific
information on outcomes by subregion. An in-depth analysis of subregional disparities, which would provide
greater insight into factors producing inequity in child wellbeing, was beyond the scope of this report.
25 Where ethnic or religious groups predominate in a governorate or district, subnational regions may be
useful in capturing inequities based on such identities.
24
43
Table 1:26 Disparities in child labour (ages 5-14 years) by gender, residence, education of
household head and wealth quintile. Djibouti.
Subregion
Residence
Education of head of household
Worst
Urban
None
Total
Child
labour
(5-14)
6.0
Secondary
13.3
Best
2.3
6.9
Rural
6.5
6.7
Wealth quintile
Poorest
Primary
4.4
Richest
Q2
or +
Q1
5.6
7.3
Q3
Q4
Q5
6.7
5.7
6.2
3.0
These gaps are represented in the graphs below by showing the disparity between groups. The
vertical line, at 1, indicates complete equity. The degree to which the bar exceeds 1 indicates the
severity of inequity in that category. In the case of Djibouti, for example, children whose household
head has no education are almost equally likely to be at risk for child labour as children whose
household head has at least a secondary education – the relative gap is only 1.19. The inequity is
more severe when considering wealth, however, as the poorest children in Djibouti are 2.4 times
more likely to engage in child labour than the richest children.
The information presented in this table is included in the statistical annex. The statistical annex presents
raw information on the incidence of deprivation for all of the indicators and equity dimensions.
26
44
Figure 4.8: Determinants of child labour in 8 MENA Countries. Likelihood of child labour among
children (ages 5-14 years) based on their rural/urban residence, subregion or gender; and education
of household head27 or wealth quintile. 28
Gaps (ratio between disadvantaged and advantaged)
Yemen (27%)
5.7
1.79
1.76
1.57
Egypt (11.9%)
2.2
Subregion
2.08
6.3
3.7
Iraq (10.3%)
0.59
Rural/Urban
Female/Male
5.8
Djibouti (6%)
0.94
1.02
9.1
oPt (5.1%)
1.41
Algeria (3.8%)
1.51
3.49
4.1
0.62
Syria (3.8%)
0.49
15.5
2.0
Morocco (2.3%)
0.51
0
Ratio
10.8
2.2
1
2
3
4
65
86 10 7 15 820 9
Gaps (ratio between disadvantaged and advantaged)
Yemen (27%)
1.51
Egypt (11.9%)
2.4
1.89
Iraq (10.3%)
2.7
1.54
NonEduc/Sec&more
1.19
1.25
0.80
oPt (5.1%)
2.2
1.95
Algeria (3.8%)
Syria (3.8%)
Morocco (2.3%)
Ratio
Poorest/ Richest
2.4
Djibouti (6%)
2.5
0
1
2
3
3.1
3.2
4
4.6
65
68
7
10
8 20
9
15
Source: MICS 3 – 2006.
27For
Egypt, educational level of mother, not household head, was used. No data by wealth quintile was
available for Iraq.
28
The jagged line followed by grey shading on the horizontal axis indicates that the scale changes after 4.
45
II.
The study of inequity related to material deprivations in countries with limited information:
In the absence of household micro data, it is necessary to rely on available information
provided by Population Census and administrative records. This information is problematic
in that the data refer to national averages, without disaggregation. This inhibits analysis of
equity dimensions to some extent. Occasionally, information is provided by geographical
location.
For data-limited countries, researchers employ an extensive search for indicators that can
provide information on disparities. For example, in the case of education, the only available
information might be gross or net enrolment. In this case, the gap between gross or net
enrolment in primary and in secondary school may provide an indication of dropout levels
as indicators of disparity.
III.
The study of vulnerable and socially excluded children and adolescent groups:
Currently, household micro-level data allows us to compare outcomes by gender, wealth
quintiles and between rural and urban areas. It does not yet disaggregate by ethnicity,
religion or other social identity that would permit, for example, a study comparing
outcomes for citizens compared to noncitizens, or indigenous children compared to
children belonging to the predominant ethnic group. Recent literature on social exclusion
and chronic poverty note that aggregate measures of poverty assume that populations are
homogenous, masking inequalities even within income poor communities.29 Capturing such
information is crucial for MENA studies as it provides relevant information on the complex
social situation in which children in the region live. Mostly qualitative and some
quantitative information related to vulnerable and socially excluded groups is provided
through grey literature, academic or institutional studies or specialized websites. Where
quantitative studies are available, they tend to be limited to one group in a specific locale –
such as a study on educational barriers for disabled children in the Levant or “zabbalaeen”
children in Cairo – or are too small in scale to be statistically significant. Nevertheless, such
studies can help raise awareness of the presence of vulnerable groups and call attention to
the need for documenting and monitoring their situation.
In this case the researchers are doing the following:
Step 1: Extended bibliographic and literature search and review to identify vulnerable
groups specific to the MENA region as well as gather qualitative and any quantitative data
on such groups.
Step 2: Selection and classification of the information by themes, MENA vulnerable groups
and countries.
Step 3: Descriptive analysis and synthesis of information, including, where possible, a small
box or figure highlighting specific findings for one or more groups.
See, for example, Naila Kabeer, 2006, “Social Exclusion and the MDGs: The Challenge of ‘Durable
Inequalities in the Asian Context” and Frances Stewart, 2008, “Horizontal Inequalities: A Neglected
Dimension of Development.” WIDER Annual Lectures 5.
29
46
Annex II: Data Sources
IMF (International Monetary Fund). 2010. World Economic Outlook Database.
[http://www.imf.org/external/pubs/ft/weo/2010/02/weodata/weoselco.aspx?g=2406&sg=All+c
ountries+%2f+Emerging+and+developing+economies+%2f+Middle+East+and+North+Africa]
Accessed February 2011.
UIS (UNESCO Institute for Statistics). 2010. Data Centre online database, Profiles.
[http://stats.uis.unesco.org/unesco/TableViewer/document.aspx?ReportId=198&IF_Language=en
g] Accessed February 2011.
UNDP (United Nations Development Programme). 2010. Human Development Report 2010. Online
database. [http://hdr.undp.org/en/statistics/ihdi/] Accessed February 2011.
UNHCR. 2010. Statistical Annexes from 2009 Global Trends. Refugees, Asylum-seekers, Returnees,
Internally Displaced and Stateless Persons. [http://www.unhcr.org/pages/49c3646c4d6.html]
Accessed March 2011.
UNICEF. Multiple Indicators Cluster Survey 3. Extracted from UNICEF Global Study on Child Poverty
and Disparity, Statistical Tables. Accessed February 2011.
UNPP (Population Division of the Department of Economic and Social Affairs of the United Nations
Secretariat). 2008. World Population Prospects: The 2008 Revision. Online database.
[http://esa.un.org/unpp] Accessed February 2011.
World Bank. 2010. World Development Indicators. Online database. [http://data.worldbank.org/]
Accessed February 2011.
47
Annex III: Definitions
1. Definition of indicators
The definitions for the indicators used in Section 3 “Socio-Economic Indicators” of this report follow
IMF, World Bank and UNDP definitions as indicated.
The definitions for the indicators used in Section 4 “Inequity in Child Wellbeing: Going Beyond
Averages” of this report are adapted from the UNICEF Global Study on Child Poverty and Disparity,
Section IV. Statistical Template. The Global Study adopted the Bristol Deprivation Model as a
method to measure the multidimensional nature and depth of child poverty (UNICEF, 2007).
1.1 Socio-Economic Indicators
GDP per capita is derived by first converting GDP in national currency to U.S. dollars and then
dividing it by the total population (IMF, 2011).
Poverty gap is the mean shortfall from the poverty line (counting the non-poor as having zero
shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty
as well as its incidence (World Bank, 2010B).
Poverty headcount ratio at $1.25 a day (PPP) (% of population) is the percentage of the
population living on less than $1.25 a day at 2005 international prices (World Bank, 2010C).
Gini Index measures the extent to which the distribution of income (or, in some cases,
consumption expenditure) among individuals or households within an economy deviates from a
perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income
received against the cumulative number of recipients, starting with the poorest individual or
household. The Gini index measures the area between the Lorenz curve and a hypothetical line of
absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index
of 0 represents perfect equality, while an index of 100 implies perfect inequality (World Bank,
2010A).
Human Development Index (HDI) is a composite index measureing average achievement in three
basic dimensions of human development— a long and healthy life, knowledge and a decent
standard of living (UNDP, 2010).
Inequality-adjusted HDI is the human development index value adjusted for inequalities in the
three basic dimensions of human development including health, education and income (UNDP,
2010).
Gender Inequality Index is a composite index measuring loss in achievements in three dimensions
of human development—reproductive health, empowerment and labour market, due to inequality
between genders (UNDP, 2010).
Unemployment rate can be defined by either the national definition, the ILO harmonized
definition, or the OECD harmonized definition. The OECD harmonized unemployment rate gives the
number of unemployed persons as a percentage of the labor force (the total number of people
48
employed plus unemployed). As defined by the International Labour Organization, unemployed
workers are those who are currently not working but are willing and able to work for pay, currently
available to work, and have actively searched for work (IMF, 2011).
1.2 Household indicators
Shelter (severe deprivation), under age 18: Percentage of children under 18 years living in a
dwelling with 5 or more people per room OR if they live in a house with no flooring.
Water (severe deprivation), under age 18: Children using surface water (for example rivers,
ponds) OR if water source is more than 30 minutes away (round trip).
Sanitation (severe deprivation), under age 18: Percentage of children under 18 years with no
access to a toilet facility of any kind.
Education of head of household (primary or less): Percentage of children under 18 years living
in households where the maximum education level of head of household is primary or less.
1.3 Women’s health indicators
No comprehensive knowledge of HIV prevention: Percentage of women ages 15 to 24 years that
no had comprehensive knowledge of HIV prevention. Comprehensive knowledge means knowing
that use of condom and having just one uninfected faithful partner can reduce the chance of getting
the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the
two most common local misconception (AIDS virus can be transmitted by mosquito bites and by
sharing food with an infected person).
Married before age 15: Percentage of women aged 15 to 49 years who married before age 15.
Married before age 18: Percentage of women aged 15 to 49 years who married before age 18.
No health insurance: Percentage of women aged 15 to 49 years who have no health insurance.
No antenatal care: Percent of women aged 15 to 49 years who gave birth in the two years
preceding the survey who did not receive at least one antenatal care consultation from a medically
trained person, defined as a doctor, nurse or trained-midwife.
Female circumcision (U18): Percentage of prevalence of female circumcision among female
children less than 18 years.
1.4 Child wellbeing indicators
1.4.1 Child mortality, nutrition and health
Under 5 mortality rate: Percentage of children born alive who died before age 5.
Note: Indirect methodology for MICS3 (child mortality rate U5). Assumptions of the child mortality
estimation method for MICS3 data:
1) The risk of a child dying is only a function of the age of the child and not other factors such as their mother's age,
the birth order of the child, etc.
2) The age of the mother can be used to reliably predict the age distribution of her children in all countries.
49
3) Fertility patterns and the age distribution of the population are assumed to have remained constant in the recent
past.
4) Child mortality patterns are assumed to have remained constant in the recent past.
5) The fertility patterns and child mortality patterns of mother's in the survey are similar to those of mother's who
have died and who are therefore not in the survey.
6) The Coale and Demeny North Model is frequently used (1966. Regional Model Life Tables and Stable
Populations. Princeton. New Jersey. Princeton University Press.) - The observed life tables underlying the North
model come from Iceland (1941-1950). Norway (1856-1880 and 1946-1955) and Sweden (1851-1890). Nine
tables were used to derive this pattern of mortality, characterized by comparatively low infant mortality coupled
with relatively high child mortality and by mortality rates above age 50 that fall increasingly below those of the
standard. The populations displaying this mortality pattern were very probably subject to endemic tuberculosis
(positive deviations from the standard pattern in the middle age range, from age 10 to 40, suggest this
fact). Therefore, this model is recommended as an adequate representation of mortality in populations where the
incidence of this disease is high. Life expectancy in these tables ranges from 44.4 years (Sweden. 1851 - 1860) to
74.7 years (Norway. 1951 - 1955). With regard to infant and child mortality, the North Model is often
recommended in populations where breastfeeding is a common practice and where weaning occurs at a relatively
late age (i.e. 12 months or over). It is assumed that, in such populations, infant mortality will be relatively low due
to the protection afforded by breastfeeding against malnutrition and infectious diseases. Once a child is weaned it
is less protected and more likely to die (UN DESA, 1983 Manual X: Indirect Techniques for Demographic Estimation.
New York, UN). However, in countries with high infant mortality rates (e.g. due to neonatal tetanus, malnutrition,
low breastfeeding rates, parasitic disease, etc.) other model life tables are likely to be more appropriate (e.g. 'East'
or 'South' or one of the UN life tables such as 'Latin American', 'Chilean' or 'South Asian' - UN DESA, 1982, Model
Life Tables for Developing Countries. . New York, UN).
7) Only the data from women aged 24-29 and 30-34 are used (i.e. number of children ever born and surviving
classified by age of mother).
8) The final child mortality rates (infant and under five mortality) are the arithmetic mean of the 24-29 and 30-34
women's rates (i.e. IMR(24-29)+IMR(30-34)/2). The final child mortality rates are therefore not population
weighted i.e. adjusted for the different numbers of children ever born to women in these two age groups (i.e. 25-29
and 30-34).
9) The final child mortality rates are not calculated for boys and girls separately (even though this information is
available in the survey data) - therefore it is assumed that the sex ratio of boys to girls is the same as in the
frequently used North Model life tables.
Nutrition (severe deprivation), under age 5: Percentage of children under 5 years who are more
than 3 standard deviations below the international reference population for stunting (height for
age) OR wasting (height for weight) OR underweight (weight for age).
Nutrition (less severe deprivation), under age 5: Percentage of children under 5 years who are
more than 2 standard deviations below the international reference population for stunting (height
for age) OR wasting (height for weight) OR underweight (weight for age).
Health (severe deprivation), under age 5: Percentage of children under 5 years has not received
any immunization OR if child had a recent illness AND were not treated (for diarrhoea or acute
respiratory infection).
Health (less severe deprivation), under age 5: Percentage of children under 5 years who have
not been immunized against all vaccines by two years of age OR did not receive treatment for a
recent illness (for diarrhoea or acute respiratory infection).
50
Not measles or MMR immunized: Percent of children among 12-23 months who not have
received dose of measles or MMR vaccine.
1.4.2 Education
No education (ages 7-17): Percentage of children among 7 to17 years with who are not currently
in school AND who have never been to school.
Not attending school (ages 6-11): Percentage of children ages 6 to11 years who are not currently
attending school.
1.5 Child Protection indicators
Child labour (ages 5-14): Percentage of children among 5 to 14 years of age involved in child
labour activities, including economic activity and domestic chores.
Birth not registered (under age 5): Percentage of children under 5 years whose birth was not
registered.
Orphans (under age 18): Percentage of children under 18 years who are orphaned (one or both
parents dead).
51
Annex IV: Institutional Definitions of MENA Region
Below is a listing of regional definitions followed by the data sources used in this report. It was
compiled from the definitions provided by the institutions’ online databases. Countries in bolded
italics differ from UNICEF’s regional definition.
HDI/UNDP
Arab States (Developing Countries): Algeria, Djibouti, Egypt, Iraq, Jordan, Kuwait, Lebanon,
Libyan Arab Jumahiriya, Morocco, Occupied Palestinian Territories, Oman, Saudi Arabia, Somalia,
Sudan, Syrian Arab Republic, Tunisia, Yemen (does not include Iran; Bahrain, Qatar and United
Arab Emirates are grouped separately with “Developed non-OECD countries”).
UIS/UNESCO
Arab States: Algeria, Bahrain, Djibouti, Egypt, Iraq, Jordan, Kuwait, Lebanon, Libyan Arab
Jamahiriya, Mauritania, Morocco, Oman, Occupied Palestinian Territories, Qatar, Saudi Arabia,
Sudan, Syrian Arab Republic, Tunisia, United Arab Emirates, Yemen (does not include Iran).
UNICEF
Middle East and North Africa: Algeria, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait,
Lebanon, Libya, Morocco, Oman, oPt, Qatar, Saudi Arabia, Sudan, Syria, Tunisia, United Arab
Emirates, Yemen.
UNHCR
Middle East and North Africa Region: Algeria, Bahrain, Egypt, Iraq, Israel, Jordan, Kuwait,
Lebanon, Libya, Mauritania, Morocco, Oman, oPt, Qatar Saudi Arabia, Syria, Tunisia, United Arab
Emirates, Western Sahara Territory, Yemen (does not include Djibouti, Iran, or Sudan).
WDI/World Bank
Middle East and North Africa : Algeria, Bahrain, Djibouti, Egypt, Iran, Iraq, Israel, Jordan, Kuwait,
Lebanon, Libya, Malta, Morocco, Oman, Qatar, Saudi Arabia, Syria, Tunisia, United Arab Emirates,
West Bank and Gaza (instead of oPt), Yemen (does not include Sudan).
52
Annex V: Statistics
Table V.1: Per capita GDP and U5MR in MENA and selected high income developed countries.
Country
Algeria
Bahrain
Djibouti
Egypt
Iran
Iraq
Jordan
Kuwait
Lebanon
Libya
Morocco
Oman
OPT
Qatar
Saudi Arabia
Sudan
Syria
Tunisia
UAE
Yemen
MENA
Canada
UK
France
USA
GDP per capita
(PPP current
international $)
(in 000’s)
7,104
26,808
2,553
6,367
11,025
3,599
5,659
38,293
15,331
14,878
4,773
26,198
1,485
88,233
23,743
2,466
5,108
9,489
36,973
2,596
8,806
38,477
34,881
34,249
47,701
Under 5
Mortality
Rate
(per 1,000
live births)
32
12
94
21
31
44
25
10
12
19
38
12
30
11
21
108
16
21
7
66
41
6
6
4
8
Sources: IMF, WEO Database (for GDP); UNICEF (for U5MR).
53
Table V.2: Loss in HDI and its components due to inequality, by region.30
Overall Loss
Living
Region
(%)
standard
Education
Arab States
27.6
19
57
East Asia and the Pacific
21.5
43
33
Europe and Central Asia
13.6
39
27
Latin America and the Caribbean
25.1
54
28
South Asia
30.2
15
50
Sub-Saharan Africa
32.8
22
32
Developed Countries
10.2
67
17
Source: UNDP HDR 2010.
Table V.3: Impact of inequality on HDI and education.
Country
Djibouti
Egypt
Jordan
Morocco
Syrian Arab Republic
Tunisia
Yemen
Arab States
Inequalityadjusted HDI
0.252
0.449
0.550
0.407
0.467
0.511
0.289
0.426
Inequalityadjusted
Education Index
0.144
0.304
0.508
0.246
0.312
0.378
0.149
0.289
Source: UNDP HDR 2010.
Table V.4: HDI loss due to inequality and education inequality.
HDI Loss Due to
HDI Loss Due to
Education
Country
Inequality (%)
Inequality (%)
Djibouti
37.3
47.0
Egypt
27.5
43.6
Jordan
19.2
25.1
Morocco
28.1
42.7
Syrian Arab Republic
20.8
31.5
Tunisia
25.2
38.7
Yemen
34.2
49.8
Arab States
27.6
43.4
Source: UNDP HDR 2010.
30
See Annex IV for HDI/UNDP definition of Arab states.
54
HDI
0.402
0.620
0.681
0.567
0.589
0.683
0.439
0.588
Health
24
24
34
18
34
45
15
Table V.5: Availability of HDI data by region.
Total
countries
17
3
11
3
9
32
45
Region
MENA Region
MENA LDCs
MENA MICs
MENA HICs
South Asia
LACs
Sub-Saharan Africa
Number of
countries lacking
Inequality-adjusted
HDI data
10
1
6
3
2
7
7
Number of
countries with
Inequality-adjusted
HDI data
7
2
5
0
7
25
38
Percentage of
countries with
Inequality-adjusted
HDI data
41
67
45
0
78
78
84
Women
Child
wellbeing
Egypt
Iraq
Morocco
oPt
Syria
Yemen
Shelter severe deprivation (U18)
Household Water severe deprivation (U18)
Sanitation severe deprivation (U18)
Djibouti
Indicator
Algeria
Dimension
Weigthed Average
Table V.6: MENA countries relative position in relation to the weighted average (weighted
average = 100).
66.0
246.9
65.6
136.5
110.8
18.2
85.5
190.2
100.0
22.6%
70.5
73.8
31.3
114.1
223.7
26.8
252.8
100.0
8.9%
135.6
55.8
38.6
159.5
17.3
412.1
100.0
7.5%
Married before 15 (w.15-49)
13.7
48.0
126.9
92.6
90.9
53.1
58.3
228.0
100.0
5.8%
Married before 18 (w.15-49)*
32.4
40.4
138.6
104.7
74.8
99.7
76.8
132.1
100.0
20.1%
Not antenatal care (w.15-49)
61.2
130.4
80.0
100.0
20.3%
231.6
119.2
100.0
38.2%
207.9
93.2
100.0
13.0%
100.2
32.2
100.0
14.0%
100.0
24.4%
Infant mortality rate U5 -per 1000Nutrition less severe deprivation -Stunted
or Underweigth or Wasting- (U5)
Health severe deprivation (U5)
Not measlesor or MMR immunized (12-23
months)
No education (7-17)
Not attending school (6-11)
Child labour (5-14)
Child
Birth not registered (U5)
protection
Orphans (U5)
246.3
65.5
87.5
236.4
27.2
49.3
17.2
38.2
30.8
79.0
163.8
256.5
106.6
298.2
100.9
321.2
73.1
44.9
133.2
154.2
9.8
35.0
284.5
100.0
7.1%
78.8
204.8
73.0
10.3
135.0
36.8
100.0
15.5%
22.1
36.5
57.7
114.3
99.0
49.0
36.5
259.4
100.0
10.4%
4.9
59.3
33.8
33.0
14.5
29.0
498.1
100.0
14.5%
84.1
237.6
98.8
130.4
61.0
69.4
107.2
100.0
4.8%
*Egypt: woman 25-49 years
More tha n 25% bel ow the wei ghted a vera ge.
Les s tha n 25% bel ow or a bove the wei gthed a vera ge.
More tha n 25% a bove the wei gthed a vera ge.
* Weighted by population group corresponding to each indicator.
Sources: MICS 3, 2006; Egypt DHS 2008 (except “not attending school” and “child labour,” which use MICS 3,
2006).
55
Household
Table V.7: Child household deprivation indicators by gender, rural/urban residence,
subregion, education of household head and wealth quintile. All indicators are percentages;
gaps are shown as ratios.31
Primary
Secondary
&more
Poorest
Second
Middle
Fourth
Richest
Female/
Male
Rural/Urban
Subregion
(worst/best)
NonEduc/
Sec&more
Poorest/
Richest
Sa ni tation
s evere
depri va tion
(U18)
30.4
None
Wa ter s evere
Al geri a
depri va tion
Dji bouti
(U18)
Ira q
Morocco
Yemen
0.0
2.4
2.8
6.3
6.6
10.2
20.0
22.6
14.8
18.9
Worst
Syri a
Egypt
14.7
Gaps (ratio between disadvantaged
and advantaged
Wea l th i ndex qui ntil es
Best
Al geri a
Shel ter s evere
Syri a
depri va tion
Morocco
(U18)
Ira q
Yemen
Dji bouti
oPt
4.1
14.8
14.9
19.3
25.0
30.8
42.9
55.7
Educa tion of
hous ehol d hea d /
mother
Rural
oPt
Egypt
Total
(%)
Subregi on
Urban
Country
Male
Indi ca tor
Urba n_Rura l
Female
Gender
14.9
4.0
3.8
5.1
21.6
1.8
1.0
9.6
36.9
6.2
28.9
5.2
13.8
3.5
3.5
13.1
50.1
4.1
14.3
1.9
2.5
1.0
0.5
0.1
0.0
n/d
1.02
1.30
5.68
5.42
2.50
1.78
8.22
3.19
3.39
15.1
19.8
9.4
12.3
6.4
21.3
26.4
45.6
12.2
8.4
6.4
16.6
56.1
46.1
19.3
29.5
33.1
16.5
20.9
17.9
9.3
14.8
5.5
40.4
42.0
69.3
14.1
23.0
28.1
8.6
13.8
10.7
3.9
9.4
3.3
1.0
4.2
0.4
2.28
2.16
7.08
1.37
6.71
7.18
2.08
2.00
6.01
2.71
10.08
2.77
31.1
26.3
23.8
51.7
37.5
50.5
90.4
17.1
8.0
26.4
46.6
81.4
71.9
32.2
90.6
35.4
42.5
27.0
31.0
88.3
52.0
32.9
23.0
11.1
0.0
0.4
0.5
0.0
4.3
4.3
0.0
0.0
0.1
0.0
8.2
18.2
0.0
4.3
4.5
0.0
3.2
3.1
0.0
1.1
1.2
0.0
9.4
7.2
0.0
1.1
3.5
0.0
0.2
2.0
0.0
0.0
0.5
0.0
0.1
0.2
1.02
1.05
n/d
1.02
n/d
n/d
*
1.43
2.12
1.75
*
2.72
10.11
2.72
*
1.19
2.93
n/d
*
n/d
7.95
n/d
*
1.01
1.02
11.43
8.68
3.47
6.50
4.04
3.66
3.90
2.58
2.7
4.0
0.3
1.5
0.5
10.4
40.6
25.2
40.8
31.3
2.2
0.0
0.1
0.0
0.0
8.5
19.5
35.6
42.3
65.7
9.8
5.2
3.7
17.0
5.7
2.8
2.3
1.3
0.98
n/d
3.82
10.15
3.81
2.95
2.65
n/d
13.48
n/d
16.4
27.4
56.1
10.6
14.0
20.9
7.3
2.5
11.2
67.3
74.8
19.4
27.3
1.6
3.9
0.0
0.8
0.0
0.0
0.97
n/d
n/d
2.47
27.72
1.39
3.50
2.12
2.91
2.25
10.99
5.02
n/d
3.36
3.31
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
*
*
*
*
*
*
*
*
*
*
5.6
0.2
0.0
0.0
0.0
0.95
24.76
5.39
7.08
4.34
1.02
1.10
2.48
8.45
4.39
1.54
7.43
2.75
n/d
26.23
n/d
8.46
3.18
n/d
n/d
n/d
n/d
23.63
2.89
6.76
2.63
14.55
2.20
3.99
24.05
2.3
2.8
2.4
2.9
6.4
6.3
10.3
10.0
Al geri a
oPt
0.0
Syri a
1.3
1.3
1.2
0.1
2.5
0.0
6.8
3.3
1.4
0.5
Ira q
Egypt
2.9
2.9
4.0
2.9
4.4
0.0
0.7
7.2
6.3
0.0
0.1
12.7
6.5
7.2
6.5
3.0
3.9
1.0
2.4
8.3
4.5
4.3
2.3
0.3
Dji bouti
10.2
Morocco
12.0
31.0
6.7
1.0
56.7
23.7
0.4
0.0
32.4
34.7
15.3
9.2
2.3
31.6
16.5
3.4
0.4
0.5
2.9
42.1
0.0
68.1
76.9
26.1
19.3
72.4
46.4
19.6
7.2
3.0
Yemen
0.0
0.0
0.0
4.2
Sources: MICS 3, 2006; DHS 2008.
Grey cells indicate that the most disadvantaged group was compared to the national average instead of the
most advantaged group. Empty cells indicate that no data was available. Asterisk (*) indicates that there is
no gap because the national incidence is 0%.
31
56
Shelter
Figure V.1: Shelter deprivation (severe) in 8 MENA countries. Likelihood of children under age
18 living in a dwelling with 5 of more people per room OR living in a house with no flooring, based on
gender,32 rural/urban residence, subregion, education of household head33 and wealth quintile. 3435
Gaps (ratio between disadvantaged and advantaged)
8
15
7
10
68
56
4
3
A
A
A
A
2
A
1
0
oPt
(4.1%)
Egypt
(14.8%)
Female/Male
Algeria
(14.9%)
Syria
(19.3%)
NonEduc/Sec&more
Morocco
(25%)
Poorest/ Richest
Iraq
(30.8%)
Yemen
(42.9%)
Rural/Urban
Djibouti
(55.7%)
Subregion
Sources: MICS 3, 2006; DHS 2008.
No gender data was available for oPt, Morocco, Yemen or Djibouti.
In Egypt, educational level of mother, not household head, was used. No household head education data
was available for Djibouti.
34 No wealth quintile data was available for Iraq or Djibouti.
35 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4.
“A” indicates that the most disadvantaged group was compared to the national average instead of the most
advantaged group.
32
33
57
Water
Figure V.2: Water deprivation (severe) in 7 MENA countries. Likelihood of children under age
18 using surface water (such as rivers or ponds) OR a water source that is more than 30 minutes away
(round trip) based on gender, 36 rural/urban residence, subregion, education of household head37 and
wealth quintile. 3839
10
25
9
20
8
15
7
10
86
A
65
4
A
A
3
A
A
A
A
A
A
A
A
2
A
1
Gaps (ratio between disadvantaged and advantaged)
11
30
0
Syria
(2.4%)
Female/Male
Egypt
(2.8%)
Algeria
(6.3%)
NonEduc/Sec&more
Djibouti
(6.6%)
Iraq
(10.2%)
Poorest/ Richest
Morocco
(20%)
Rural/Urban
Yemen
(22.6%)
Subregion
Sources: MICS 3, 2006; DHS 2008.
No gender data was available for Djibouti, Morocco or Yemen.
In Egypt, educational level of mother, not household head, was used. No household head education data
was available for Djibouti.
38 No wealth quintile data was available for Iraq or Djibouti.
39 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4.
“A” indicates that the most disadvantaged group was compared to the national average instead of the most
advantaged group.
36
37
58
Sanitation
Figure V.3: Sanitation deprivation (severe) in 6 MENA countries. Likelihood of children under
age 18 not having access to a toilet facility of any kind based on gender, 40 rural/urban residence,
subregion, education of household head41 and wealth quintile. 4243
10
25
9
20
8
15
7
10
86
65
4
A
A
A
A
3
A
A
A
A
2
A
1
Gaps (ratio between disadvantaged and advantaged)
11
30
0
Syria (1.3%)
Female/Male
Iraq (2.9%)
Egypt (4.2%)
NonEduc/Sec&more
Djibouti
(10.2%)
Poorest/ Richest
Morocco
(12%)
Yemen (31%)
Rural/Urban
Subregion
Sources: MICS 3, 2006; DHS 2008.
No gender data was available for Djibouti, Morocco or Yemen.
In Egypt, educational level of mother, not household head, was used. No household head education data
was available for Djibouti.
42 No wealth quintile data was available for Iraq or Djibouti.
43 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4.
“A” indicates that the most disadvantaged group was compared to the national average instead of the most
advantaged group.
40
41
59
Women
Table V.8: Women’s deprivation indicators by rural/urban residence, subregion, education
of household head and wealth quintile. All indicators are percentages; gaps are shown as
ratios.44
Yemen
Ma rri ed
before 18
(w.15-49)
Al geri a
Dji bouti
Morocco
Syri a
oPt
Ira q
Yemen
Egypt
Al geri a
Not a ntena tal
ca re (w.15-49) Syri a
Ira q
Not hea l th Morocco
i ns ura nce
Egypt
(w.15-49)
Rural/Urban
Subregion
(worst/best)
NonEduc/
Sec&more
Poorest/
Richest
0.83
3.10
2.0
1.18
2.40
3.41
4.65
1.02
23.81
n/d
7.37
Richest
0.84
2.01
Fourth
4.54
1.92
Middle
0.68
1.64
Second
3.37
2.05
1.2
Poorest
1.70
4.63
1.1
Secondary
&more
7.4
13.3
2.70
1.95
4.6
Primary
Ira q
Egypt
1.69
1.22
0.7
None
Syri a
Morocco
0.8
2.8
3.1
3.4
5.3
5.4
Worst
Al geri a
Dji bouti
oPt
Total
(%)
Gaps (ratio between
disadvantaged and
advantaged
Wea l th i ndex qui ntil es
Best
Ma rri ed
before 15
(w.15-49)
Country
Educa tion of
hous ehol d hea d /
woma n
Rural
Indi ca tor
Subregi on
Urban
Urba n_Rura l
0.6
2.9
3.4
4.0
4.2
1.1
3.5
2.5
2.7
6.9
0.5
2.1
1.3
1.1
0.0
1.3
4.1
5.7
5.2
10.2
1.0
3.9
3.0
2.7
5.9
0.9
2.4
3.8
4.2
5.5
0.6
0.9
2.7
3.2
2.9
1.3
4.4
2.8
2.8
7.6
0.8
3.4
3.7
3.1
6.5
0.8
2.7
3.2
3.9
6.1
0.8
2.0
3.4
4.0
4.3
0.4
2.1
2.3
3.4
2.5
5.1
4.1
6.0
9.8
2.8
3.2
9.5
14.7
5.0
15.7
6.6
9.2
4.8
0.7
14.8
10.1
7.2
4.0
12.6
13.7
4.6
25.4
13.7
13.6
12.1
16.6
15.1
12.4
12.3
11.1
1.09
5.47
1.14
1.49
6.5
8.1
15.0
15.4
20.0
21.0
26.5
27.8
5.6
9.8
12.2
16.5
21.2
7.6
13.6
19.2
14.2
18.5
4.2
5.9
8.2
8.0
12.5
10.5
11.3
21.4
23.0
28.0
6.4
11.6
15.7
9.2
11.8
7.0
10.4
17.1
18.0
22.0
6.1
3.9
10.5
16.4
19.7
8.3
14.8
19.2
12.2
18.5
6.6
10.8
19.7
15.9
21.1
7.0
9.0
16.2
17.2
22.6
6.5
7.1
12.0
17.9
21.4
4.0
8.2
9.5
14.1
16.8
1.36
1.39
1.57
2.49
1.94
2.60
1.06
2.98
1.49
2.08
1.81
2.02
0.86
0.9
2.88
2.2
0.56
0.6
0.86
1.1
20.1
22.2
19.4
22.8
28.8
22.2
15.1
17.4
18.2
29.2
52.2
51.5
18.7
25.3
53.2
24.3
29.5
43.6
20.0
26.2
10.7
30.3
52.3
28.2
42.2
28.3
32.6
26.2
22.6
21.2
11.9
1.13
1.29
1.93
1.93
3.00
4.98
0.93
0.96
4.39
n/d
1.43
2.82
12.4
16.0
16.2
8.0
10.0
10.5
17.6
22.1
25.4
9.7
0.6
7.1
14.0
32.9
23.9
21.0
23.0
22.9
12.6
19.5
18.9
6.7
11.8
11.2
26.6
32.0
13.5
17.6
9.0
11.1
7.2
10.4
3.0
5.8
2.21
2.20
2.42
1.44
25.90
3.36
3.12
1.95
2.06
8.77
5.56
n/d
47.7
20.3
89.4
0.0
71.3
77.2
49.3
0.0
95.3
89.9
66.8
28.7
0.0
4.41
1.49
1.62
2.00
82.0
80.5
92.7
76.3
96.6
98.3
96.2
71.0
98.7
96.5
92.2
84.2
69.0
1.15
1.38
1.43
1.27
Sources: MICS 3, 2006; DHS 2008.
Grey cells indicate that the most disadvantaged group was compared to the national average instead of the
most advantaged group. Empty cells indicate that no data was available.
44
60
Figure V.4: Early marriage (under 15) in 8 MENA countries. Likelihood of marriage before the
age of 15 among women (15-49 years) based on rural/urban residence, subregion, education of
household head45 and wealth quintile. 4647
10
25
Gaps (ratio between disadvantaged and advantaged)
9
20
15
8
10
7
86
65
4
3
2
A
1
0
Algeria
(0.8%)
Djibouti
(2.8%)
oPt
(3.1%)
NonEduc/Sec&more
Syria
(3.4%)
Morocco
(5.3%)
Poorest/ Richest
Iraq
(5.4%)
Rural/Urban
Egypt
(7.4%)
Yemen
(13.3%)
Subregion
Sources: MICS 3, 2006; DHS 2008.
In Egypt, educational level of mother, not household head, was used.
No wealth quintile data was available for Iraq.
47 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4. “A”
indicates that the most disadvantaged group was compared to the national average instead of the most
advantaged group.
45
46
61
Figure V.5: Early marriage (under 18) in 8 MENA countries. Likelihood of marriage before the
age of 18 among women (15-49 years) based on rural/urban residence, subregion, education of
household head48 and wealth quintile. 49 50
Gaps (ratio between disadvantaged and advantaged)
65
4
3
2
1
0
Algeria
(6.5%)
Djibouti
(8.1%)
Morocco
(15%)
NonEduc/Sec&more
Syria
(15.4%)
oPt
(20%)
Poorest/ Richest
Iraq
(21%)
Rural/Urban
Yemen
(26.5%)
Egypt
(27.8%)
Subregion
Sources: MICS 3, 2006; DHS 2008.
In Egypt, educational level of mother, not household head, was used.
No wealth quintile data was available for Iraq.
50 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4.
48
49
62
Figure V.6: No antenatal care in 3 MENA countries. Likelihood of women (15-49 years) not
receiving at least one antenatal care consultation from a medically trained person (defined as a
doctor, nurse or trained-midwife) based on rural/urban residence, subregion, education of household
head and wealth quintile.
Gaps (ratio between disadvantaged and advantaged)
4
3
2
1
0
Algeria (6.5%)
NonEduc/Sec&more
Djibouti (8.1%)
Poorest/ Richest
Morocco (15%)
Rural/Urban
Source: MICS 3, 2006.
63
Subregion
Child Wellbeing
Table V.9: Child health deprivation indicators by gender, rural/urban residence, subregion,
education of household head and wealth quintile. All indicators are percentages; gaps are
shown as ratios.51
Gaps (ratio between disadvantaged
and advantaged
Rural/Urba
n
Subregion
(worst/best
NonEduc/
Sec&more
Poorest/
Richest
1.33
2.28
1.16
2.05
2.59
1.03
1.19
13.28
1.11
n/d
0.91
0.98
0.71
0.83
1.43
5.65
1.14
1.12
0.77
1.65
0.99
0.90
n/d
0.96
n/d
0.89
1.66
1.15
1.21
0.93
1.23
1.73
12.46
3.29
1.99
3.91
4.00
6.85
1.65
1.47
1.71
n/d
1.46
n/d
0.87
1.72
1.23
2.51
n/d
2.04
n/d
1.59
2.55
0.75
2.64
1.55
1.98
1.58
1.35
1.91
4.31
0.96
1.50
17.38
1.98
3.54
1.06
1.49
3.17
1.43
n/d
45.4
107.2
30.7
47.3
61.2 71.0
113.8 101.8
56.2
59.5
36.6
31.6
52.8
113.7
46.6
109.5
46.9
85.0
41.5
68.8
28
95.0
91.2
28.7
73.0
123.6
36.2
50.8
18.0
96.1
179.7 125.2
45.7 44.0
80.3
82.2
35.5
93.8
46.6
24.7
127.3
157.6
49
85.6 91.6
128.4 108.5
36.1 32.2
66.6
93.1
27.2
110.0
76.9
18.9
6.5
6.0
7.1
1.0
13.7
7.2
6.0
6.4
8.8
12.4
8.1
12.1
9.8
12.8
6.9
10.6
6.8
5.6
9.7
31.7
9.4
13.1
7.7
13.0
8.3
11.7
8.3
15.7
6.6
12.0
8.5
10.5
8.4
12.6
10.8
9.5
13.1
28.7
13.0
25.7
13.8
20.3
32.2
12.3
33.6
36.9
1.7
13.4
17.8
20.8
44.0
35.4
16.8
30.3
14.2
27.0
11.4
17.7
16.3
40.4
11.5
27.6
12.7
24.6
11.6
19.9
13.2
16.1
2.4
3.8
4.5
14.0
44.9
2.4
2.3
2.1
2.9
4.2
10.1
67.2
2.5
2.7
5.2
17.6
50.6
1.0
2.2
1.3
0.0
27.3
3.9
8.8
8.6
23.1
72.2
2.8
2.9
1.9
3.6
2.5
2.0
1.9
1.8
3.8
16.0
96.6
5.0
12.4
56.7
4.3
9.3
62.2
5.1
20.2
56.9
5.0
15.1
50.2
4.9
14.8
44.4
4.2
7.6
38.6
3.2
7.9
28.8
n/d
n/d
n/d
9.3
8.4
10.3
7.3
11.6
7.7
10.4
13.5
9.1
7.1
15.8
11.4
6.1
7.7
3.7
1.23
17.8
18.1
17.4
14.3
21.4
2.6
45.2
28.1
19.8
14.2
31.7
18.4
13.1
14.6
9.0
39.9
38.7
41.1
33.3
49.7
21.3
67.4
47.4
43.8
33.1
103.4
38.4
6.4
6.3
8.5
12.1
13.1
27.0
30.7
80.8
None
45.0
71.2
45.5
88.4
94.0
113.8
33.4
Worst
Fourth
1.94
3.22
1.02
2.69
1.78
Middle
1.99
2.40
n/d
3.54
2.54
Second
1.01
1.51
0.77
1.36
1.26
Poorest
n/d
n/d
0.78
n/d
0.73
Secondary
&more
39.7
49.9
Primary
Richest
Wea l th i ndex qui ntil es
Best
Not
Al geri a
mea s l es or or
Syri a
MMR
i mmuni zed Ira q
(12-23
Educa tion of
hous ehol d hea d /
mother
Rural
oPt
Morocco
Infa nt
mortal i ty ra te Dji bouti
U5 -per 1000- Yemen
Egypt
Nutri tion l es s Ira q
s evere
Al geri a
depri va tion - oPt
Stunted or
Syri a
Underwei gth
Morocco
or Wa s tingDji bouti
(U5)
Egypt
Not
i mmnui zed- Dji bouti
Hea l th s evere oPt
depri va tion- Morocco
(U5)
Yemen
Subregi on
Urban
Total
(%)
Female
Country
Male
Indi ca tor
Urba n_Rura l
Female/
Male
Gender
Sources: MICS 3, 2006; DHS 2008.
Grey cells indicate that the most disadvantaged group was compared to the national average instead of the
most advantaged group. Empty cells indicate that no data was available.
51
64
Figure V.7: Under 5 mortality rate in 5 MENA countries. Likelihood of children born alive dying
before the age of 5 based on gender, 52 rural/urban residence, subregion,53 education of mother54 and
wealth quintile.
Gaps (ratio between disadvantaged and advantaged)
4
3
2
1
0
Egypt (33‰)
Female/Male
oPt (46‰)
Morocco (88‰) Djibouti (94‰)
NonEduc/Sec&more
Poorest/ Richest
Rural/Urban
Sources: MICS 3, 2006; DHS 2008.
No gender data was available for oPt, Morocco or Yemen.
No subregional data was available for Djibouti.
54 In Djibouti, educational level of household head, not mother, was used.
52
53
65
Yemen (114‰)
Subregion
Figure V.8: Nutrition deprivation (less severe) in 6 MENA countries. Likelihood of children
under age 5 being more than 2 standard deviations below the international reference population for
stunting or wasting or underweight based on gender,55 rural/urban residence, subregion, education of
household head56 and wealth quintile. 57 58
Gaps (ratio between disadvantaged and advantaged)
8
15
7
10
68
56
4
3
2
1
0
Iraq
(6.4%)
Female/Male
Algeria
(8.5%)
oPt
(12.1%)
NonEduc/ Sec&more
Syria
(13.1%)
Poorest/ Richest
Morocco
(27%)
Djibouti
(30.7%)
Rural/Urban
Subregion
Source: MICS 3, 2006.
No gender data was available for Djibouti.
No household head education data was available for Djibouti.
57 No wealth quintile data was available for Iraq or Djibouti.
58 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4.
55
56
66
Figure V.9: Health deprivation (less severe) in 5 MENA countries/ Not measles or MMR
immunized in 3 MENA countries. Likelihood of children under age 5 to have not been immunized
against all vaccines by two years of age OR to have not received treatment for a recent illness
(diarrhea or acute respiratory infection)/ Likelihood of children age 12-23 months to have not
received a dose of measles or MMR based on gender,59 rural/urban residence, subregion, education of
household head60 and wealth quintile.61 62
15
8
10
7
68
56
4
3
2
A
1
0
Egypt
(2.4%)
Djibouti
(3.8%)
oPt
(4.5%)
Morocco
(14%)
Yemen
(44.9%)
Health severe deprivation
Female/Male
NonEduc/ Sec&more
Algeria
(9.3%)
Syria
(17.8%)
Iraq
(39.9%)
Gaps (ratio between disadvantaged and advantaged)
9
20
Not measlesor or MMR
Poorest/ Richest
Rural/Urban
Subregion
Sources: MICS 3, 2006; DHS 2008.
No gender data was available for Djibouti, oPt, Morocco and Yemen.
In Egypt, educational level of mother, not household head, was used. No household head education data
was available for Djibouti.
61 No wealth quintile data was available for Iraq or Djibouti.
62 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4.
“A” indicates that the most disadvantaged group was compared to the national average instead of the most
advantaged group.
59
60
67
Education
Table V.10: Child deprivation education indicators by gender, rural/urban residence,
subregion, education of household head and wealth quintile. All indicators are percentages;
gaps are shown as ratios.63
NonEduc/
Sec&more
Poorest/
Richest
n/d
4.81
2.15
n/d
6.47
1.56
1.27
1.44
2.96
4.90
2.73
1.70
3.32
7.23
5.46
13.83
1.21
1.04
1.02
1.25
1.50
1.43
1.22
1.50
2.08
1.19
3.34
2.11
2.01
1.44
1.55
1.72
3.32
2.23
2.03
n/d
Female/
Male
2.23
6.01
6.46
Richest
2.54
2.79
0.76
Fourth
9.95
5.36
6.23
11.26
6.10
1.63
Middle
4.71
Second
2.44
3.36
5.46
Poorest
1.72
14.24
7.53
Secondary
&more
2.16
Primary
Subregion
(worst/best)
Not a ttendi ng
s chool (6-11) Egypt
Al geri a
Syri a
Ira q
Rural/Urban
Yemen
Morocco
4.73
1.27
18.26
None
Dji bouti
Yemen
oPt
3.2
9.5
11.0
0.84
Worst
Morocco
0.7
2.2
2.5
Best
Al geri a
Syri a
No educa tion Egypt
(7-17)
Ira q
Gaps (ratio between disadvantaged
and advantaged
Wea l th i ndex qui ntil es
Rural
oPt
Total
(%)
Educa tion of
hous ehol d hea d /
mother
Subregi on
Urban
Country
3.1
2.9
0.7
0.9
1.7
0.6
3.7
3.2
0.2
1.9
0.4
1.1
2.4
7.8
1.4
4.2
6.8
0.7
1.3
2.0
0.6
0.6
1.1
0.9
6.6
6.0
0.8
1.5
2.3
0.8
1.0
1.6
0.4
0.6
1.3
0.5
0.5
0.8
n/d
2.19
1.42
1.7
4.9
3.4
4.2
16.6
18.8
1.4
3.7
0.0
6.7
22.4
17.9
6.5
21.0
14.4
1.3
10.3
5.3
0.7
3.9
2.3
9.1
3.0
1.1
0.6
0.8
1.72
2.33
25.3
14.4
4.9
1.6
2.3
16.4
9.0
41.7
25.0
10.1
7.0
22.5
41.8
45.0
17.3
9.4
43.6
23.4
15.8
10.8
6.7
Male
Indi ca tor
Urba n_Rura l
Female
Gender
1.4
2.1
2.4
5.7
4.1
13.4
18.3
20.3
1.6
5.7
11.3
1.9
5.1
9.3
1.3
6.5
13.4
1.7
2.5
3.9
1.3
7.3
19.1
0.7
0.0
0.0
4.4
15.5
19.2
3.1
8.1
15.1
1.7
4.7
7.9
1.5
2.4
2.1
1.9
11.5
25.9
1.6
7.6
15.1
1.9
6.6
5.4
1.4
3.1
2.6
1.2
2.1
1.9
12.2
16.5
20.9
31.7
11.1
16.2
20.7
28.3
13.4
16.8
21.2
35.2
9.3
13.8
18.8
26.2
14.0
19.7
23.0
39.4
8.0
15.5
8.5
22.5
16.6
18.4
28.3
47.5
17.6
19.9
27.7
42.9
12.7
15.9
22.3
35.4
8.7
13.8
17.9
25.0
20.0
24.1
28.2
13.1
17.6
22.3
10.0
14.6
20.3
9.7
13.3
18.0
6.0
10.8
13.9
n/d
n/d
n/d
0.65
4.19
1.85
7.39
6.26
Sources: MICS 3, 2006, DHS 2008.
Grey cells indicate that the most disadvantaged group was compared to the national average instead of the
most advantaged group. Empty cells indicate that no data was available.
63
68
n/d
11.16
Figure V.10: Children with no education in 8 MENA countries. Likelihood of children ages 7-17
never receiving an education based on gender,64 rural/urban residence, subregion, education of
household head65 and wealth quintile. 6667
Gaps (ratio between disadvantaged and advantaged)
9
20
8
15
7
10
6
8
5
4
3
2
A
1
0
oPt
(0.7%)
Algeria
(2.2%)
Female/Male
Syria
(2.5%)
Egypt
(3.2%)
NonEduc/Sec&more
Iraq
(9.5%)
Morocco
(11%)
Poorest/ Richest
Djibouti
(18.3%)
Rural/Urban
Yemen
(20.3%)
Subregion
Sources: MICS 3, 2006; DHS 2008.
.
No gender data was available for oPt, Morocco, Djibouti and Yemen.
In Egypt, educational level of mother, not household head, was used. No household head education data
was available for Djibouti.
66 No wealth quintile data was available for Iraq or Djibouti.
67 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4.
“A” indicates that the most disadvantaged group was compared to the national average instead of the most
advantaged group.
64
65
69
Figure V.11: Children not attending school in 7 MENA countries. Likelihood of children ages 611 not attending school based on gender, rural/urban residence, subregion, education of household
head68 and wealth quintile.6970
Gaps (ratio between disadvantaged and advantaged)
9
20
8
15
10
7
86
65
4
3
A
2
A
1
0
oPt
(1.6%)
Female/Male
Yemen
(5.7%)
Morocco
(11.3%)
NonEduc/Sec&more
Egypt
(12.2%)
Algeria
(16.5%)
Poorest/ Richest
Syria
(20.9%)
Rural/Urban
Iraq
(31.7%)
Subregion
Sources: MICS 3, 2006; DHS 2008.
In Egypt, educational level of mother, not household head, was used.
No wealth quintile data was available for Iraq.
70 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4.
“A” indicates that the most disadvantaged group was compared to the national average instead of the most
advantaged group.
68
69
70
Child Protection
Table V.11: Child protection indicators by gender, rural/urban residence, subregion,
education of household head and wealth quintile. All indicators are percentages; gaps are
shown as ratios.71
Poorest/
Richest
1.2
2.4
2.8
4.8
5.6
8.7
8.4
20.7
0.4
2.3
3.0
3.9
3.4
1.5
61.2
2.3
1.8
2.5
3.6
5.2
4.2
6.9
NonEduc/
Sec&more
1.3
4.1
3.1
5.7
4.4
11.1
13.4
23.6
0.5
1.7
4.0
5.5
5.4
5.5
72.0
3.5
2.8
3.2
4.5
4.5
6.1
8.3
Subregion
(worst/best)
3.0
7.5
5.4
3.8
6.7
13.4
15.9
31.2
1.4
1.4
9.7
5.6
6.6
11.5
78.6
7.6
9.0
6.0
7.7
5.5
11.7
14.7
Rural/Urban
7.1
13.0
6.8
7.6
13.3
24.5
15.8
50.0
1.3
6.0
12.4
7.5
6.3
15.9
95.8
4.6
4.8
4.3
5.3
8.2
9.6
14.7
Richest
0.5
1.2
1.7
0.8
2.3
3.9
7.2
9.5
0.5
0.1
0.7
1.1
3.6
7.5
15.6
1.6
0.4
3.5
2.5
1.9
3.7
6.2
Female/
Male
Secondary
&more
10.0
72.2
2.9
3.5
3.9
4.5
5.3
6.5
11.9
3.1
5.3
4.7
6.5
6.5
18.9
13.7
30.9
0.9
3.6
4.8
4.3
5.0
13.8
78.6
2.8
3.3
3.5
4.8
5.1
5.7
12.4
1.5
1.4
2.7
4.3
3.0
0.51
0.49
0.62
3.49
1.02
0.59
2.08
1.76
1.09
1.09
1.08
1.05
n/a
1.35
1.00
1.03
1.09
0.98
0.93
1.07
1.08
1.12
2.02
2.24
1.51
1.41
0.94
3.73
1.57
1.79
1.64
2.05
1.34
0.83
1.06
1.15
1.42
1.05
1.01
0.81
1.07
1.01
0.86
1.27
15.55
10.82
4.09
9.10
5.78
6.31
2.20
5.28
3.80
2.84
2.96
1.42
1.94
2.13
6.13
3.37
13.22
1.21
2.14
4.32
2.59
2.38
2.45
3.11
1.95
0.80
1.19
1.54
1.89
1.51
4.79
0.61
6.42
n/a
2.72
7.67
1.28
1.21
4.88
2.38
2.14
1.06
2.79
2.13
3.19
4.63
2.22
1.25
2.43
n/d
2.71
2.37
2.76
1.18
18.23
7.12
1.75
18.62
2.12
2.90
1.70
0.94
1.87
1.62
n/d
1.80
Fourth
Primary
7.4
72.3
2.8
3.2
4.0
4.8
5.0
6.0
10.6
1.5
2.4
3.1
4.6
6.9
5.1
8.8
17.3
0.6
1.8
3.6
5.1
4.7
12.0
55.2
2.7
3.3
4.4
4.5
5.1
6.6
9.7
Middle
None
1.6
2.5
2.9
8.0
6.0
7.6
16.2
34.6
0.7
2.2
4.4
4.9
Second
Worst
3.1
5.1
4.7
2.3
5.9
13.0
7.8
19.7
0.7
2.0
4.0
4.7
Gaps (ratio between disadvantaged
and advantaged
Wea l th i ndex qui ntil es
Poorest
Best
2.3
3.8
3.8
5.1
6.0
10.3
11.9
27.0
0.7
2.1
4.2
4.8
4.9
8.6
72.3
2.9
3.3
4.0
4.7
5.1
6.2
11.3
Rural
Morocco
Syri a
Al geri a
Chi l d l a bour oPt
(5-14)
Dji bouti
Ira q
Egypt
Yemen
Al geri a
oPt
Bi rth not
Syri a
regi s tered Ira q
(U5)
Egypt
Dji bouti
Yemen
oPt
Syri a
Al geri a
Orpha ns (U5) Egypt
Yemen
Ira q
Dji bouti
Total
(%)
Educa tion of
hous ehol d hea d /
mother
Urban
Country
Subregi on
Female
Indi ca tor
Urba n_Rura l
Male
Gender
4.7
6.6
6.1
5.4
7.3
2.2
4.7
3.6
5.9
6.7
1.7
3.1
3.5
4.5
5.7
0.8
2.7
2.7
5.1
6.2
16.8
38.3
1.7
2.1
7.4
13.4
31.5
0.5
2.9
5.1
12.1
27.5
0.5
2.0
3.3
9.1
19.9
0.3
1.8
3.1
6.2
16.2
0.4
1.8
1.2
6.8
18.8
90.4
2.8
3.6
3.7
5.9
7.2
5.2
10.5
84.0
2.6
3.7
3.8
5.8
4.4
4.1
6.4
75.2
3.0
3.9
4.8
3.9
5.2
5.4
2.7
58.8
3.5
3.0
3.8
4.3
4.3
2.5
1.0
42.7
2.3
2.1
3.9
3.1
4.4
12.0
12.0
10.3
12.3
6.7
Sources: MICS 3, 2006; DHS 2008.
Grey cells indicate that the most disadvantaged group was compared to the national average instead of the
most advantaged group. Empty cells indicate that no data was available.
71
71
Child Labour
Figure V.12: Child labour in 8 MENA countries. Likelihood of children (ages 5-14) engaging in
child labour based on gender, rural/urban residence, subregion, education of household head72 and
wealth quintile. 7374
Gaps (ratio between disadvantaged and advantaged)
9
20
15
8
10
7
86
65
4
3
2
1
0
Morocco
(2.3%)
Syria
(3.8%)
Female/Male
Algeria
(3.8%)
oPt
(5.1%)
NonEduc/Sec&more
Djibouti
(6%)
Poorest/ Richest
Iraq
(10.3%)
Egypt
(11.9%)
Rural/Urban
Yemen
(27%)
Subregion
Sources: MICS 3, 2006; DHS 2008.
In Egypt, educational level of mother, not household head, was used.
No wealth quintile data was available for Iraq.
74 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4.
72
73
72
Birth registration
Figure V.13: Birth not registered in 7 MENA countries. Likelihood of children under age 5 not
having their birth registered based on gender, rural/urban residence, subregion, education of
household head75 and wealth quintile. 7677
Gaps (ratio between disadvantaged and advantaged)
9
20
15
8
10
7
86
65
4
3
A
A
2
1
0
Algeria
(0.7%)
Female/Male
oPt
(2.1%)
Syria
(4.2%)
NonEduc/ Sec&more
Iraq
(4.8%)
Egypt
(4.9%)
Poorest/ Richest
Djibouti
(8.6%)
Rural/Urban
Yemen
(72.3%)
Subregion
Sources: MICS 3, 2006; DHS 2008.
In Egypt, educational level of mother, not household head, was used.
No wealth quintile data was available for Iraq.
77 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4. “A”
indicates that the most disadvantaged group was compared to the national average instead of the most
advantaged group.
75
76
73
Orphans
Figure V.14: Orphans (in 7 MENA countries. Likelihood of children under age 18 being orphaned
(with one or both parents dead) based on gender, rural/urban residence, subregion, education of
household head78 and wealth quintile. 7980
Gaps (ratio between disadvantaged and advantaged)
8
15
10
7
86
65
4
3
2
1
0
Syria
(3.3%)
Female/Male
Algeria
(4%)
Egypt
(4.7%)
NonEduc/Sec&more
Yemen
(5.1%)
Poorest/ Richest
Iraq
(6.2%)
Djibouti
(11.3%)
Rural/Urban
Subregion
Sources: MICS 3, 2006; DHS 2008.
In Egypt, educational level of mother, not household head, was used.
No wealth quintile data was available for Iraq.
80 The jagged line followed by the grey shading on the vertical axis indicates that the scale changes after 4.
78
79
74
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