DHS COMPARATIVE

REPORTS 40

URBAN CHILD POVERTY, HEALTH, 

AND SURVIVAL IN LOW- AND 

MIDDLE-INCOME COUNTRIES

August 2016

This publication was produced for review by the United States Agency for International Development (USAID). The report was prepared by

Shea O. Rutstein, Sarah Staveteig, Rebecca Winter, and Jennifer Yourkavitch.

DHS Comparative Reports No. 40 

Urban Child Poverty, Health, and Survival in Low- and 

Middle-Income Countries 

Shea O. Rutstein 

Sarah Staveteig 

Rebecca Winter 

Jennifer Yourkavitch 

ICF International 

Rockville, Maryland, USA 

August 2016 

Corresponding author: Shea O. Rutstein, International Health and Development, ICF International, 530 

Gaither Road, Suite 500, Rockville, Maryland, USA; phone: 240-350-3680; fax: 301-407-6501; email: 

Shea.Rutstein@icfi.com 
Acknowledgments: The authors would like to thank Jennifer Winestock Luna for her thoughtful review, 

Thomas Pullum for his consultation and input, and Trinadh Dontamsetti and Clara Burgert-Brucker for 

their assistance with disaggregating urban areas in the datasets. 

Editor: Diane Stoy 

Document Production: Natalie La Roche 

This study was carried out with support provided by the United States Agency for International 

Development (USAID) through The DHS Program (#AID-OAA-C-13-00095). The views expressed are 

those of the authors and do not necessarily reflect the views of USAID or the United States Government. 

The DHS Program assists countries worldwide in the collection and use of data to monitor and evaluate 

population, health, and nutrition programs. For additional information about The DHS Program, contact 

The DHS Program, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; phone: 

301-407-6500; fax: 301-407-6501; email: reports@dhsprogram.com; Internet: www.dhsprogram.com. 

Recommended citation: 

Rutstein, Shea O., Sarah Staveteig, Rebecca Winter, and Jennifer Yourkavitch. 2016. Urban Child Poverty, 

Health, and Survival in Low- and Middle-Income Countries. DHS Comparative Reports No. 40. Rockville, 

Maryland, USA: ICF International. 
iii 

Contents 

Tables ................................................................................................................................................................... v

Figures ................................................................................................................................................................ vi

Preface ................................................................................................................................................................ ix

Abstract .............................................................................................................................................................. xi

1. Introduction .............................................................................................................................................. 1

1.1. Rationale for This Study ...................................................................................................................... 1

1.2. Background .......................................................................................................................................... 2

2. Data and Methods ..................................................................................................................................... 5

2.1. Data ...................................................................................................................................................... 5

2.2. Definition of Key Indicators ................................................................................................................ 6

2.3. Study Population ................................................................................................................................ 10

2.4. Analysis .............................................................................................................................................. 11

3. Results ...................................................................................................................................................... 13

3.1. Poverty Levels and Trends ................................................................................................................. 13

3.2. Health Status of Children under Age 5 .............................................................................................. 18

3.3. Nutritional Status of Children under Age 5 ........................................................................................ 28

3.4. Use of Children’s Health Services ..................................................................................................... 44

4. Discussion and Conclusions ................................................................................................................. 105

References ........................................................................................................................................................ 109

v 

Tables 

Table 2.1. Study countries, timing of included surveys, and cities with over 1 million persons 

as of 2014 .......................................................................................................................... 6 

Table 2.2. Indicators included in the study ........................................................................................ 8 

Table 2.3. Sample size of children under age 5 by level of urbanicity and poverty ........................ 10 

Table 3.1. Infant mortality rate by poverty according to level of urbanicity ................................... 19 

Table 3.2. Decadal change in infant mortality rate by poverty according to level of urbanicity ..... 21 

Table 3.3. Under-five mortality by poverty according to level of urbanicity .................................. 24 

Table 3.4. Decadal change in U5MR by poverty according to level of urbanicity .......................... 26 

Table 3.5. Stunting by poverty according to level of urbanicity ...................................................... 29 

Table 3.6. Decadal change in stunting by poverty according to level of urbanicity ........................ 31 

Table 3.7. Underweight by poverty according to level of urbanicity ............................................... 34 

Table 3.8. Decadal change in underweight by poverty according to level of urbanicity ................. 36 

Table 3.9. Prevalence of anemia (<11.0g/dl) among children age 6-59 months by poverty 

according to level of urbanicity ....................................................................................... 39 

Table 3.10. Decadal change in prevalence of anemia (<11.0g/dl) among children age 6-59 

months by poverty according to level of urbanicity ........................................................ 41 

Table 3.11. Four or more ANC visits by poverty according to level of urbanicity ............................ 46 

Table 3.12. Decadal change in four or more ANC visits by poverty according to level of 

urbanicity ........................................................................................................................ 48 

Table 3.13. Medical antenatal care by poverty according to level of urbanicity ............................... 51 

Table 3.14. Decadal change in medical antenatal care by poverty according to level of 

urbanicity ........................................................................................................................ 53 

Table 3.15. Home delivery by poverty according to level of urbanicity ............................................ 56 

Table 3.16. Decadal change in home delivery by poverty according to level of urbanicity .............. 58 

Table 3.17. Medical delivery attendance by poverty according to level of urbanicity ...................... 61 

Table 3.18. Decadal change in medical delivery attendance by poverty according to level of 

urbanicity ........................................................................................................................ 63 

Table 3.19. Short birth intervals (<36 months) by poverty according to level of urbanicity ............. 66 

Table 3.20. Decadal change in short birth intervals (<36 months) by poverty according to 

level of urbanicity ........................................................................................................... 68 

Table 3.21. Full basic immunization by poverty according to level of urbanicity ............................. 71 

Table 3.22. Decadal change in full basic immunization by poverty according to level of 

urbanicity ........................................................................................................................ 73 

Table 3.23. Coverage of care seeking from a medical source for children under age 5 with 

fever by poverty according to level of urbanicity ........................................................... 76 

Table 3.24. Decadal change in coverage of care seeking from a medical source for children 

under age 5 with fever by poverty according to level of urbanicity ................................ 78 

Table 3.25. Coverage of care seeking from a medical source for children under age 5 with 

symptoms of ARI by poverty according to level of urbanicity ....................................... 81 

Table 3.26. Decadal change in coverage of care seeking from a medical source for children 

under age 5 with symptoms of ARI by poverty according to level of urbanicity ........... 83 

Table 3.27. Coverage of care seeking from a medical source for children under age 5 with 

diarrhea by poverty according to level of urbanicity ...................................................... 85 

Table 3.28. Decadal change in coverage of care seeking from a medical source for children 

under age 5 with fever by poverty according to level of urbanicity ................................ 87 
vi 

Table 3.29. Coverage of treatment with ORT for children under age 5 with diarrhea by poverty 

according to level of urbanicity ....................................................................................... 90 

Table 3.30. Decadal change in coverage of treatment with ORT for children under age 5 with 

diarrhea by poverty according to level of urbanicity ...................................................... 92 

Table 3.31. Indicator by poverty according to level of urbanicity ..................................................... 95 

Table 3.32. Decadal change in indicator by poverty according to level of urbanicity ....................... 97 

Table 3.33. Indicator by poverty according to level of urbanicity ................................................... 100 

Table 3.34. Decadal change in indicator by poverty according to level of urbanicity ..................... 102 

Appendix Table A1. Imputation of number of sleeping rooms based on urban/rural area and individual 

household wealth score. ................................................................................................ 111 

Figures 

Figure 3.1. Pooled average composition of poverty by urbanicity, children under age 5 ................. 13 

Figure 3.2. Average difference in pooled composition of poverty between children under age 

5 and household residents of all ages, by urbanicity ....................................................... 14 

Figure 3.3. Poverty composition of children under age 5 nationwide ............................................... 15 

Figure 3.4. Pooled average decadal change in poverty classification, by area .................................. 16 

Figure 3.5. Percentage of children under age 5 in extreme poverty by level of urbanicity ............... 17 

Figure 3.6. Pooled average infant mortality rate among children born in the five years preceding 

the survey and pooled average decadal change in rate, by poverty according to level 

of urbanization ................................................................................................................ 18 

Figure 3.7. Pooled average under-five mortality rate among children born in the five years 

preceding the survey and pooled average decadal change in rate, by poverty 

according to level of urbanicity ....................................................................................... 23 

Figure 3.8. Pooled average prevalence of stunting among children under age 5 and pooled 

average decadal change in coverage, by poverty according to level of urbanicity ......... 28 

Figure 3.9. Pooled average prevalence of being underweight among children under age 5 

and pooled average decadal change in coverage, by poverty according to level of 

urbanicity ........................................................................................................................ 33 

Figure 3.10. Pooled average prevalence of anemia (<11.0g/dl) among children age 6-59 months 

and pooled average decadal change in coverage, by poverty according to level of 

urbanicity ........................................................................................................................ 38 

Figure 3.11. Pooled average prevalence of fever, diarrhea, and symptoms of ARI among children 

under age 5, by poverty according to level of urbanicity ................................................ 43 

Figure 3.12. Pooled average coverage of four or more ANC visits and pooled average decadal 

change in coverage, by poverty according to level of urbanicity .................................... 45 

Figure 3.13. Pooled average coverage of medical antenatal care and pooled average decadal 

change in coverage, by poverty according to level of urbanicity .................................... 50 

Figure 3.14. Pooled average prevalence of home delivery and pooled average decadal change in 

prevalence, by poverty according to level of urbanicity ................................................. 55 

Figure 3.15. Pooled average coverage of medical delivery attendance and pooled average decadal 

change in prevalence, by poverty according to level of urbanicity ................................. 60 

Figure 3.16. Pooled average prevalence of short birth Intervals (<36 months) and pooled average 

decadal change in prevalence, by poverty according to level of urbanicity .................... 65 

Figure 3.17. Pooled average coverage of full basic immunization and pooled average decadal 

change in coverage, by poverty according to level of urbanicity .................................... 70 
vii 

Figure 3.18. Pooled average coverage of care seeking from a medical source for children under 

age 5 with fever and pooled average decadal change in coverage, by poverty 

according to level of urbanicity ....................................................................................... 75 

Figure 3.19. Pooled average coverage of care seeking from a medical source for children under 

age 5 with symptoms of ARI and pooled average decadal change in coverage, 

by poverty according to level of urbanicity .................................................................... 80 

Figure 3.20. Pooled average coverage of care seeking from a medical source for children under 

age 5 with diarrhea and pooled average decadal change in coverage, by poverty 

according to level of urbanicity ....................................................................................... 80 

Figure 3.21. Pooled average coverage of treatment with ORT for children under age 5 with 

diarrhea and pooled average decadal change in coverage, by poverty according 

to level of urbanicity ....................................................................................................... 89 

Figure 3.22. Pooled average coverage of household mosquito bednet possession and pooled 

average decadal change in coverage, by poverty according to level of urbanicity ......... 94 

Figure 3.23. Pooled average coverage of bednet use by children under age 5 and pooled 

average decadal change in coverage, by poverty according to level of urbanicity ......... 99 

ix 

Preface 

The Demographic and Health Surveys (DHS) Program is one of the principal sources of international data 

on fertility, family planning, maternal and child health, nutrition, mortality, environmental health, 

HIV/AIDS, malaria, and provision of health services. 

One of the objectives of The DHS Program is to provide policymakers and program managers in low- and 

middle-income countries with easily accessible data on levels and trends for a wide range of health and 

demographic indicators. DHS Comparative Reports provide such information, usually for a large number 

of countries in each report. These reports are largely descriptive, without multivariate methods, but when 

possible they include confidence intervals and/or statistical tests. 

The topics in the DHS Comparative Reports series are selected by The DHS Program in consultation with 

the United States Agency for International Development. 

It is hoped that the DHS Comparative Reports will be useful to researchers, policymakers, and survey 

specialists, particularly those engaged in work in low- and middle-income countries. 

Sunita Kishor 

Director, The DHS Program 

xi 

Abstract 

This report examines levels and trends in poverty, health status, and use of health services among children 

under age 5 living in large cities in low- and middle-income countries, and compares their health status and 

use of services to those of their other urban, rural, and non-poor counterparts. Twenty-six countries were 

selected for inclusion; these are the countries with one or more large cities of more than one million 

inhabitants in 2014 and that had at least two DHS surveys, one between 1998 and 2004 and a second in or 

after 2010. Poverty was assessed using the method of unsatisfied basic needs (UBN) to provide comparable 

levels in three categories (extremely poor, moderately poor, and not poor). Differentials in levels and 

decadal trends in 17 health indicators were examined, and the results are shown for individual countries, as 

well as for the pooled weighted cross-country averages. 

On average, across the 26 low- and middle-income countries studied, we estimate that three out of four 

children under age 5 live in extreme poverty. Poverty is highest in rural areas. About half of children under 

age 5 who live in large cities are extremely poor, over half in other urban areas, and more than 4 of 5 in 

rural areas. While extreme poverty has decreased overall and in rural areas, extreme poverty has increased 

in large cities. 

The chances of survival of children under age 5 are greatest in urban areas compared to rural areas. Poor 

children in large cities and other urban areas have similar chances of survival to age 5. Nutritional status of 

poor children in large cities is better than in other urban areas, which in turn is better than in rural areas. 

Both infant and under-five mortality have decreased substantially, with the greatest decadal decline 

observed among the extremely poor. Small improvements were made in children’s nutritional status, 

notably for stunting and anemia. Nutritional status has improved more among the poor than non-poor 

children in all areas, including the large cities. The survival gap between the poor and non-poor has 

narrowed considerably. Similarly, the disadvantage of poor children in stunting and anemia has been 

reduced. 

Among the 12 indicators of health service use in this report, nine show moderate or large differences 

between the poor and the not poor. The gap between the poor and not poor has narrowed for eight of these 

indicators. In large cities, the gap decreased for 10 of the 12 indicators, although the narrowing was small 

for three indicators. 

Overall, there appear to be numerous health advantages to living in an urban area, but these advantages are 

not conferred to all children. In survival, we see stark disparities across levels of poverty. For all indicators, 

the urban extremely poor children fare better than their rural extremely poor counterparts, but not as well 

as non-poor rural children. Despite the narrowing of gaps in many health outcomes between poor and nonpoor and between urban and rural areas, the persistence of poverty and increases in extreme poverty in large 

cities in low- and middle-income countries remain cause for concern.

1 

1. Introduction 

1.1. Rationale for This Study 

The world’s population has been steadily urbanizing for several decades due to rapid population growth 

and a “transformed” global economy, both of which have been fueled by political and technological changes 

(Cohen 2006). The majority of the world’s people have lived in cities since 2007 (Harpham 2009). 

Developing countries have had a slower rate of urbanization than middle- and upper-income countries, 

although this trend is expected to reverse in the coming decades (United Nations Population Division 2015). 

There is mixed evidence about the effect of urbanization on child health. On one hand, urban residents 

generally have higher incomes than their rural counterparts and urban environments offer proximity to 

health resources that are lacking in rural environments. On the other hand, the rate of urban growth in 

developing countries can easily outpace expansion of the infrastructure such as transportation, water, and 

sanitation. High population density is often associated with poor sanitation and can facilitate disease 

transmission. Mortality has declined more in urban than rural areas of low- and middle-income countries 

(LMIC) over the past 60 years, although poor urban areas—slums—have recently had higher mortality 

(Garenne 2010). To further examine health conditions in urban and rural environments of LMICs, this 

report summarizes recent trends (2000-2015) in child health indicators in 26 countries and compares them 

by poverty level and place of residence. We hypothesize that large urban areas have different health 

dynamics than smaller urban areas, some of which may be settlements of a few thousand persons. We 

therefore distinguish large cities (those over 1 million in 2014) from other urban settlements and rural areas. 

Our analyses seek to show how the percent of children that are extremely poor has changed over time; 

health indicator differences between urban poor and their wealthier counterparts; and, how gaps in health 

by poverty level in urban areas compare to rural areas. In particular, the report seeks answers to the 

following questions about children under age 5: 

A. Children’s poverty: 

1. What is the level of poverty among children by urbanicity? Is poverty more or less concentrated 

among children under age 5 versus the overall household population? 

2. Is poverty among children increasing or decreasing? 

3. In which countries is the percentage of poor children greatest? In which countries is the percentage 

of poor children greatest in large cities? 

B. Children’s health status 

1. Has the health status of poor children improved? Has the health status of poor children in large 

cities improved? 

2. Are poor children in large cities more disadvantaged in health status than poor children in other 

urban and rural areas? 

3. Has the gap in health status narrowed between poor and non-poor children? In large urban areas? 
2 

C. Health services 

1. Is there a gap in health service utilization between poor and non-poor children? In large cities and 

other urban areas? 

2. Has the gap in health service utilization narrowed? 

D. Country comparison 

1. Which countries are doing the best and the worst in narrowing the gaps in health status and health 

service utilization? 

This section grounds those questions in extant literature, and provides an overview and description of trends 

in urbanization and different types of urban areas, a discussion of key literature about child health in urban 

areas, and a comparison of measures of urban poverty. 

1.2. Background 

Urbanization: overview and trends 

Over 50% of the world’s population lived in urban areas in 2014; this has increased from 30% in 1950 and 

is projected to be 66% in 2050 (United Nations Population Division 2015). There are regional differences: 

80% of the population of Latin America and the Caribbean, 37% of the population of sub-Saharan Africa, 

and 48% of the population of Asia lived in urban areas. According to the report, trends in rapid urbanization 

yield projections that more than half of the population of sub-Saharan Africa and nearly two-thirds of the 

population of Asia will be living in urban areas by 2040. 

Urbanization is characterized by population movement into cities and includes attributes such as relying on 

the public administration for services; depending on food and water that is delivered; changes in infant 

feeding and food consumption patterns; exposure to pollution; changes in the physical environment that 

increase the risk of disease, disability and death from poisonings and injuries; changes in social values and 

behavior; and exposure to tobacco, alcohol, and drugs (Gracey 2002). Rapid growth in urban populations 

over the past few decades has overwhelmed the administrative capacity to provide adequate services in 

many urban environments; challenges to sustainable urban development are anticipated to be greatest for 

small-to-medium urban areas, particularly in Africa (Cohen 2006). Migration to cities from poor rural areas 

and high fertility rates in urban areas have contributed to rapid urbanization in sub-Saharan Africa 

(Anyamele 2009). In addition, climate change and more specifically, less rainfall, along with increased 

mobility in response to fewer political restrictions over the past few decades, have increased urbanization 

in sub-Saharan Africa (Barrios, Bertinelli, and Strobl 2006). 

Types of urban areas 

Globally, there is no uniform definition of an urban area. National statistical offices have established 

varying thresholds based on population size of a settlement or a combination of population size and the 

proportion of residents employed in agriculture (United Nations Population Division 2015). Urban areas 

thus range from small settlements of a few thousand people to mega-cities with more than 10 million. Most 

urban residents of LMICs live in small cities and towns where health care shortages are similar to those in 

rural areas and poverty rates are higher than in larger cities (Montgomery 2009). Slums are overcrowded, 

poor, and informal urban settlements with poor sanitation that tend to be concentrated in rapidly urbanizing 

megacities (Fink, Günther, and Hill 2014). Slums foster distinct health inequalities in large urban areas such 

as differential access to safe water, electricity, and health services (Anyamele 2009). 
3 

Poor neighborhoods may not be uniformly poor, and may have some wealthy residents (Montgomery and 

Hewett 2005). This fact has implications for programs and research. Likewise, slums are not uniformly 

poor, and not all poor people live in slums. One study in India found that 80% of poor urban households 

were not located in slums (Montgomery 2009). The author concludes that more research is needed to 

determine whether poverty alleviation strategies should target poor neighborhoods (places) or poor 

individuals (living in many neighborhoods). 

Child health in urban areas 

Urbanization has profound effects on infant and child health around the world (Gracey 2002). In LMICs, 

overcrowding and environmental pollution increase the risk of undernutrition, respiratory infection, and 

diarrheal diseases (Gracey 2002). Although access to services is generally better in urban areas, and there 

is an inverse association between urbanization and child mortality in some African countries (Anyamele 

2009), those who live in urban areas often face challenges in obtaining health care. They may have to 

choose from inadequately supplied and trained public health services, expensive private health services, or 

self-medication through drug dispensaries (Harpham 2009).

The “urban advantage” for health is well documented, although averages obscure important sub-group 

differences (Montgomery 2009). Some urban poor have health indicators similar to people living in rural 

areas; in fact, there was higher infant mortality in Nairobi’s slums than in rural areas of Kenya (Montgomery 

2009). Other research found that where maternal health care is good in African countries, urban poor tend 

to be worse off than rural poor (Anyamele 2009). In sub-Saharan Africa, larger socioeconomic inequalities 

in stunting were found in urban than in rural areas; parental education, community socioeconomic status, 

and other maternal and child factors explained only a small part of the within-urban variance in child 

malnutrition (Fotso 2006). The author concludes that the so-called “urban advantage” in health hides large 

disparities between poor and non-poor in urban areas and that the urban poor need specific policies and 

programs. 

A simple urban/rural comparison in three African countries showed higher stunting and underweight 

prevalence among children born in rural areas compared with urban areas of Angola, the Central African 

Republic, and Senegal; however, when stratified by wealth, there was no difference according to place of 

residence (Kennedy et al. 2006). Wealthy and poor subgroups exist in both types of areas, and poverty 

seems to be a stronger predictor of chronic undernutrition than area of residence (Kennedy et al. 2006).

However, urban and rural lifestyles differ and this should be considered when designing programs 

(Kennedy et al. 2006). Care seeking is lower for the poor when compared to rich families in both areas, and 

richer people are more likely to obtain care, be seen by a doctor, and receive medicine when they are ill 

(Anyamele 2009; Schellenberg et al. 2003). 

There is mixed evidence of how well very poor children in urban areas do when compared with their rural 

counterparts. An analysis of DHS data from 73 LMICs indicated that children living in slums generally 

have better health indicators than their rural counterparts, but are worse off than the children living in 

wealthier neighborhoods within the same urban area (Fink, Günther, and Hill 2014). The study found that 

much of that observed difference was explained by access to health services, maternal education, and 

household wealth. Overall, children living in urban areas (slum or not) fared better than their rural 

counterparts in terms of mortality and stunting, but not in the incidence of recent illness. In contrast, Van 

de Poel et al. (2007) found that urban poor had higher rates of stunting and mortality than their rural 

counterparts, and that household wealth and sociodemographic factors explained most of the observed 

differences between urban and rural stunting and mortality rates.

Urbanization has been associated with improvements in some health indicators but not others, and may 

exacerbate a household’s vulnerability to poor health. Van de Poel et al. (2007) found that the rural-urban 

gap in stunting does not always mirror the mortality gap; their study of 47 countries found that the stunting 
4 

gap between urban and rural areas in the Latin America/Caribbean region was 1.5 times higher than the 

mortality gap. In addition, some urban poor experience a double burden of ill health, in which there is a 

disproportionate burden of both infectious and non-communicable disease, and one household may have 

both malnourished children and obese adults (Harpham 2009). 

Migrants to urban areas may face higher risks of poor health. A study in Bangladesh found that child 

survival was worse among migrants living in urban areas than among impoverished lifelong urban residents, 

with the worst indicators found among recent migrants (Islam and Azad 2008). This study also found that 

housing conditions and access to clean water and sanitation were critical determinants of survival for urban 

children. 

Measurement of poverty 

Wealth and health are correlated although the relationship may not be as simple as it seems. For example, 

non-poor households located in urban areas that lack clean water and sanitation services face threats to 

health that wealth alone cannot overcome (Montgomery 2009). Defining poverty only as a function of 

income focuses policy efforts on poverty reduction strategies like job creation that may not improve health 

without other interventions. In addition, investments in health can reduce poverty such as the provision (and 

use) of bednets that can avert loss of income due to illness (ibid).

As previously noted, focusing on averages hides inequalities among sub-groups; while disaggregation is 

important, sufficiently detailed data that permit such analyses are rare (Montgomery 2009). In addition, 

there are different types of urban poor. Mabogunje (2005) classifies the urban poor as new poor (recent 

poor); borderline poor (employed but unskilled and living below the poverty line); and chronic poor 

(poverty that lasts at least 5 years, and is often caused by the rural to urban transition rather than specific 

urban conditions). Health differences among these groups are difficult to measure due to the cross-sectional 

nature of most data collected in developing countries. 

The choice of wealth index affects the magnitude of the outcome (Anyamele 2009; Houweling, Kunst, and 

Mackenbach 2003). Following the work of Filmer and Pritchett (2001), typical measures of household 

wealth are derived from principal components analysis, which is also the method adopted by The DHS 

Program in its own wealth index (Rutstein and Johnson 2004). Kennedy et al. (2006) used principal 

components analysis of household assets to derive wealth index quintiles. Van de Poel et al. (2007) also 

used principal components analysis to create a household wealth index. They believe that the DHS wealth 

index underestimates the wealth of rural households because the DHS variables collected more information 

about assets typical of urban areas (television) and less for rural areas (grazing rights and living quarters 

for livestock). The DHS wealth index has subsequently been revised to incorporate separate approaches for 

rural and urban areas (Rutstein 2008). 

Montgomery and Hewett (2005) constructed a measure of relative affluence that is similar to a measure of 

consumption, which combines information about consumer durables and housing quality for each 

household. They averaged household measures across a survey cluster to produce neighborhood estimates. 

There has been a call for more neighborhood analysis, and an additional focus on the potential inequities in 

intra-household allocation of resources (Harpham 2009). 

This analysis uses a measure of unsatisfied basic needs (UBN), which is an absolute measure of certain 

living standards at the household level. This measure is described further in the next section. 
5 

2. Data and Methods 

2.1. Data 

The DHS surveys are nationally representative, population-based household surveys that monitor 

demographic trends, infant and child mortality, child and reproductive health, nutritional status, family 

planning use, and many other health-related issues, as well as sociodemographic characteristics of women 

and men of reproductive age. Each country survey is conducted by individual country survey organizations 

with technical assistance in design, sampling, training, fieldwork, data processing, tabulation, and report 

generation provided by ICF International. The data are collected with face-to-face household interviews by 

specially trained interviewers. Anthropometric measurements are taken by specially trained staff members 

who use internationally standardized height boards and UNICEF scales. Each survey includes a standard 

core questionnaire that enables comparisons across countries and over time. 

For this report, countries with DHS surveys were selected by the following criteria: 

1. Contained an urban area with one million or more inhabitants in 2014 as estimated by United Nations 

Population Division (2015). Thirty-six countries met this criterion. 

2. Had one DHS survey in 2010 or after and an earlier survey between 1998 and 2004, both with available 

recoded data. Eight countries did not meet this second criterion.1

 

3. Had sufficient information to identify clusters in cities over one million inhabitants. The 2012 DHS 

survey in Indonesia lacked this data. Haiti was excluded because of the number of households displaced 

or in earthquake refugee camps at the time of the survey.2

 

4. Therefore, a total of 26 countries were used for analysis: Armenia, Bangladesh, Burkina Faso, 

Cambodia, Cameroon, Colombia, Côte d’Ivoire, Dominican Republic, Egypt, Ethiopia, Ghana, Guinea, 

Jordan, Kenya, Mali, Mozambique, Nepal, Niger, Nigeria, Peru, Philippines, Rwanda, Senegal, 

Tanzania, Uganda, and Zambia. Table 2.1 identifies the large cities in these countries and shows the 

survey years included in the study. 

 

1

 Congo (Brazzaville), Democratic Republic of Congo, Honduras, Liberia, Pakistan, Sierra Leone, and Yemen. 2

 At the time of the survey, 5% of households were in earthquake refugee camps. Living standards for these 

households, such as access to water and sanitation, construction materials used in housing, and the number of sleeping 

rooms reflect the conditions of the camp itself and not the prior (or future) home. 
6 

Table 2.1. Study countries, timing of included surveys, and cities with over 1 million persons as of 

2014 

Country Survey 1 Survey 2 Cities over 1 million in 2014 

Armenia 2000 2010 Yerevan 

Bangladesh 1999-00 2014 Dhaka, Chittagong, Khulna 

Burkina Faso 2003 2010 Ouagadougou 

Cambodia 2000 2014 Phnum Pénh (Phnom Penh) 

Cameroon 2004 2011 Yaoundé, Douala 

Colombia 2000 2010 Bogotá, Medellín, Cali, Barranquilla, Bucaramanga, Cartagena 

Côte d’Ivoire 1998-99 2011-12 Abidjan 

Dominican Republic 2002 2013 Santo Domingo 

Egypt 2000 2014 Al-Qahirah (Cairo), Al-Iskandariyah (Alexandria) 

Ethiopia 2000 2011 Addis Ababa 

Ghana 2003 2014 Accra, Kumasi 

Guinea 1999 2012 Conakry 

Jordan 2002 2012 Amman 

Kenya 2003 2014 Nairobi, Mombasa 

Mali 2001 2012-13 Bamako 

Mozambique 2003 2011 Maputo 

Nepal 2001 2011 Kathmandu 

Niger 1998 2012 Niamey 

Nigeria 2003 2013 Lagos, Kano, Ibadan, Abuja, Port Harcourt, Benin City, 

Onitsha, Kaduna 

Peru 2000 2012 Lima 

Philippines 2003 2013 Manila, Davao City 

Rwanda 2000 2010 Kigali 

Tanzania 1999 2010 Dar es Salaam 

Uganda 2000-01 2011 Kampala 

Zambia 2001-02 2013-14 Lusaka 

Zimbabwe 1999 2010-11 Harare 

2.2. Definition of Key Indicators 

The study examines recent trends in maternal and child health among urban poor households relative to 

non-poor and rural households. The study uses the standard DHS urban-rural classifications, which rely on 

countries’ own census definitions. These definitions differ from country to country and could differ within 

countries over time. To distinguish large cities from other urban areas, DHS clusters located in cities with 

a population over 1 million persons in 2014 were identified. This identification used variables found in 

standard DHS recode files. For surveys in which major cities were not easily differentiated from other urban 

areas, GPS coordinates were cross-referenced with regional and district-level variables to identify the major 

city.3

 Children were then divided into three groups based on the classification of their household: those in 

large cities, other urban areas, and rural areas.

The DHS surveys do not capture monetary income, which can be transient, instead they include data on on 

assets and services owned by and available to a given household. The DHS wealth index is computed at the 

time of the survey and is not comparable across countries. While one procedure has been developed for 

making extant wealth index scores comparable relative to a standard baseline (Rutstein and Staveteig 2014) 

 

3

 Although the DHS Program routinely displaces clusters geographical coordinates by a random direction and distance, 

they all remain within metropolitan areas. 
7 

and another for harmonizing measures within countries over time (Staveteig and Mallick 2014), the 

comparable wealth scores produced by both methods are derived from a wide ranging combination of assets 

and services. Any given value or a range of values of a composite index reflects a wide array of possible 

combinations of assets and services; as such, establishing a universal poverty threshold with this type of 

combined score would be difficult. For these reasons, we define poverty as deprivation of basic standards 

of living using an index of household-level unsatisfied basic needs (UBN). 

The UBN method establishes a set number of possible deprivations (such as inadequate housing or 

inadequate source of drinking water) and a threshold cutpoint for each to assess deprivations. These 

deprivations are summed and in some cases weighted to produce a combined multidimensional poverty 

index. The UBN approach to poverty estimation was inspired by Amartya Sen’s seminal work on poverty 

(1976) and adapted with poverty mapping first done in Chile (Kast Rist and Silva 1975). The approach was 

expanded with applications to census data in the 1980s by the United Nations Economic Commission for 

Latin America and the Caribbean (ECLAC) and the Census Institute in Argentina (Feres and Mancero 2001; 

Instituto Nacional de Estadística y Censos (INDEC) 1984). In contemporary practice, there is no single 

definition of UBN and no single way to determine their scoring. The implementation of UBN is normally 

tailored to each country. Hicks (1998) enumerates the definition of poverty in 13 countries in Latin America, 

most of which use a slightly different set of UBN and a slightly different system for scoring poverty. We 

adopted the overall UBN approach as a way to compare gradients of poverty across surveys across countries 

and over time. Our specific criteria are the same as those described by Rutstein and Staveteig (2014). 

For the purpose of this report, we define UBN as follows: 

1. Poor housing construction: dirt or natural floor, or rustic wall materials. 

2. Inadequate sanitary facilities: household has either inadequate sanitary facilities or an inadequate 

drinking water supply. Inadequate sanitary facilities are anything except unshared improved facilities. 

Inadequate drinking water supply in urban areas is a non-private or non-piped water supply. In rural 

areas, it is a non-improved water supply. 

3. Economic dependency: more than three household members per worker, and the worker with the 

highest education has not completed primary education. 

4. Household crowding: more than three usual household members per room used for sleeping.4

 

Based on the above definitions, household members5

 are classified into one of three poverty groups: not 

poor (0 UBN), moderately poor (1 UBN) or extremely poor (2 or more UBN). This measure of poverty sets 

an absolute threshold that is more comparable over time in material terms than country-specific relative 

wealth indexes, and allows for distinguishing between overall change due to changes in the proportion of 

the population that is impoverished versus changes in living standards among those classified as poor or 

extremely poor. 

 

4 The question about the number of sleeping rooms was omitted in the model questionnaire for Phase IV DHS surveys 

but reinstated for Phase V and later model questionnaires. As a result, for some Phase IV surveys, crowding cannot 

be calculated directly. In other Phase IV surveys, the question was included as a country-specific item. Where the 

question was not included, we estimated the number of sleeping rooms for each household by using a regression with 

type of area (urban or rural) and the household’s wealth index score on data from the later survey. The values of the 

regression coefficients and the survey data used are shown in Appendix Table A1. 5

 As with the DHS wealth index, overnight guests who are not usual residents (de facto not de jure residents) are 

assumed to have the same wealth as the other members of the household in which they are temporarily staying. 
8 

To examine trends in the health of urban poor children, the study focuses on 20 key indicators of maternal 

and child health, listed and defined in Table 2 below. These include five indicators of antenatal, delivery, 

and post-delivery care; seven indicators related to child nutrition and illness prevention and treatment; and 

eight indicators of child health status and outcomes. These indicators conform to standard DHS tabulations. 

For more information on their calculation, see Rutstein and Rojas (2006). The web appendix shows results 

for 23 auxiliary indicators. 

Table 2.2. Indicators included in the study 

Indicator Definition Denominator 

Health and Nutritional Status of Children Under Age 5 

Infant mortality rate The probability of dying between birth and 

the first birthday, expressed in deaths per 

1,000 live births 

Births in the five years preceding the survey

Under-five mortality rate The probability of dying between birth and 

the fifth birthday, expressed in deaths per 

1,000 live births 

Births in the five years preceding the survey

Stunting Percentage of children under age 5 who 

are at least two standard deviations below 

the median for the reference population for 

height-for-age 

Children born in the five years preceding 

the survey 

Underweight Percentage of children under age 5 who 

are at least two standard deviations below 

the median for the reference population for 

weight-for-age 

Children born in the five years preceding 

the survey 

Any anemia Percentage of children age 6-59 months 

that have any anemia (<11.0g/dl) 

Children born 6-59 months preceding the 

survey 

Fever Percentage of children under age 5 with 

fever in the two weeks preceding the 

survey 

Children born in the five years preceding 

the survey 

Symptoms of ARI Percentage of children under age 5 with 

symptoms of ARI (cough and rapid 

breathing) in the two weeks preceding the 

survey 

Children born in the five years preceding 

the survey 

Diarrhea Percentage of children under age 5 with 

diarrhea in the two weeks preceding the 

survey 

Children born in the five years preceding 

the survey 

Continued 
9 

Table 2.2—Continued

Indicator Definition Denominator 

Use of Children’s Health Services 

Antenatal and delivery care 

4+ ANC visits Percentage of women with four or more 

antenatal care visits for their most recent 

pregnancy 

Women age 15-49 with a live birth in the 

five years preceding the survey 

Medical antenatal care Percentage of women who received 

antenatal care from a medical provider6 for 

their most recent pregnancy 

Women age 15-49 with a live birth in the 

five years preceding the survey 

Home delivery Percentage of births that were delivered at 

home 

Children born in the five years preceding 

the survey 

Medical delivery 

attendance 

Percentage of births that were assisted by 

a medical provider6

Children born in the five years preceding 

the survey 

Short preceding birth 

interval (<36 months) 

The percentage of births with a preceding 

birth interval of less than 36 months 

Children born in the five years preceding 

the survey 

Child illness prevention and treatment 

Full basic immunization Percentage of children age 12-23 months 

who received all recommended 

immunizations (Polio1-3, DPT 1-3, BCG, 

measles) from either a vaccination/health 

card or the mother’s report 

Children born 12-23 months preceding the 

survey 

Care seeking for 

children’s fever: Seen 

medically 

Among children under age 5 with recent 

fever, the percentage for whom care was 

sought from a health facility or medical 

provider7

Children under age 5 with fever in the two 

weeks preceding the survey 

Care seeking for 

children’s symptoms of 

ARI: Seen medically 

Among children under age 5 with recent 

symptoms of ARI, the percentage for whom 

care was sought from a health facility or 

medical provider7

Children under age 5 with symptoms of ARI 

in the two weeks preceding the survey 

Care seeking for 

children’s diarrhea: Seen 

medically 

Among children under age 5 with recent 

diarrhea, the percentage for whom care 

was sought from a health facility or medical 

provider7

Children under age 5 with diarrhea in the 

two weeks preceding the survey 

Treatment for diarrhea: 

ORT 

Among children under age 5 with recent 

diarrhea, the percentage that were treated 

with ORT 

Children under age 5 with diarrhea in the 

two weeks preceding the survey 

Household mosquito 

bednet possession 

Percentage of households that own at least 

one mosquito bednet of any type at the 

time of interview 

All households 

Mosquito bednet use by 

children 

Percentage of children under age 5 who 

used a bednet the night preceding the 

survey 

Children born in the five years preceding 

the survey 

 

6

 Medical providers include doctors, nurses, nurse midwives, auxiliary midwives, obstetrician/gynecologists, and 

country-specific health professionals. Not included are trained or untrained traditional birth attendants. 7

 Including hospitals, health centers, health posts, mobile clinics, community health workers, whether public or 

private, and excluding pharmacies, shops, and traditional practitioners/healers. 
10 

2.3. Study Population 

Poverty and UBN are defined by characteristics of the household. For computation of indicators, the 

corresponding maternal and child populations were identified and sample sizes are shown in Table 2.3 by 

degree of poverty and level of urbanicity. 

Table 2.3. Sample size of children under age 5 by level of urbanicity and poverty 

Large cities Other urban areas Rural areas 

Country Survey 

Not 

poor 

Modera

tely 

poor 

Extremely 

poor Total 

Not 

poor 

Moderat

ely poor

Extremely 

poor Total 

Not 

poor 

Moderat

ely poor 

Extremely 

poor Total 

Sub-Saharan Africa

Burkina Faso 2003 24 138 416 578 5 120 610 736 32 185 8,478 8,697 

Burkina Faso 2010 100 250 657 1,007 30 279 1,199 1,509 19 586 11,580 12,186 

Cameroon 2004 83 565 423 1,073 116 779 1,498 2,394 20 472 4,029 4,522 

Cameroon 2011 140 566 1,120 1,827 102 557 2,480 3,140 73 458 6,302 6,834 

Cote D’Ivoire 1998-99 30 97 185 313 15 59 226 302 9 142 1,166 1,318 

Cote D’Ivoire 2011-12 124 281 740 1,146 93 359 1,258 1,711 37 366 4,509 4,914 

Ethiopia 2000 12 36 121 170 10 94 859 964 3 35 10,090 10,129 

Ethiopia 2011 9 18 205 233 18 75 1,181 1,276 0 30 10,260 10,291 

Ghana 2003 3 132 461 597 2 135 490 628 1 221 2,212 2,435 

Ghana 2014 50 419 927 1,397 28 361 890 1,280 101 526 2,512 3,140 

Guinea 1999 16 143 507 668 2 115 551 669 1 202 3,881 4,085 

Guinea 2012 33 170 829 1,034 26 177 670 875 34 272 4,857 5,163 

Kenya 2003 75 144 274 494 32 145 369 547 66 454 4,312 4,833 

Kenya 2014 251 534 1,443 2,229 302 898 3,171 4,372 213 861 12,276 13,351 

Mali 2001 143 524 605 1,273 47 316 1,150 1,513 78 512 8,766 9,357 

Mali 2012-13 45 161 844 1,051 26 121 820 968 36 319 8,372 8,728 

Mozambique 2003 36 139 336 512 42 506 1,916 2,465 4 335 6,828 7,168 

Mozambique 2011 15 115 237 367 41 244 2,332 2,617 12 191 7,527 7,732 

Niger 1998 4 110 274 390 9 108 619 736 0 47 5,716 5,763 

Niger 2012 19 117 557 693 20 86 986 1,093 5 72 11,718 11,796 

Nigeria 2003 74 334 498 907 90 799 1,554 2,443 31 470 2,046 2,548 

Nigeria 2013 83 685 2,430 3,198 76 1,621 5,973 7,671 315 1,840 17,082 19,238 

Rwanda 2000 0 38 266 305 2 161 664 828 13 530 5,672 6,216 

Rwanda 2010 50 166 402 620 1 63 367 432 137 1,095 6,685 7,918 

Tanzania 1999 1 67 64 133 16 132 261 410 5 55 2,422 2,483 

Tanzania 2010 38 219 225 484 70 383 604 1,058 66 554 5,917 6,538 

Uganda 2000-01 0 2 346 350 0 2 427 430 0 23 6,598 6,622 

Uganda 2011 35 231 762 1,028 8 215 1,275 1,499 27 1,120 15,877 17,026 

Zambia 2001-02 3 81 519 605 12 435 951 1,398 1 113 4,308 4,423 

Zambia 2013-14 75 481 1,140 1,698 228 644 2,062 2,934 56 337 8,688 9,082 

Continued 
11 

Table 2.3–Continued 

Large cities Other urban areas Rural areas 

Country Survey 

Not 

poor 

Modera

tely 

poor 

Extremely 

poor Total 

Not 

poor 

Moderat

ely poor

Extremely 

poor Total 

Not 

poor 

Moderat

ely poor 

Extremely 

poor Total 

Sub-Saharan Africa

Zimbabwe 1999 22 185 187 395 11 349 323 684 20 248 2,230 2,498 

Zimbabwe 2010-11 58 303 397 759 153 315 370 840 234 673 3,404 4,312 

South and Southeast Asia

Bangladesh 2004 10 30 163 204 104 226 741 1,072 66 374 4,753 5,194 

Bangladesh 2014 72 198 377 649 36 308 1,006 1,351 295 867 4,634 5,797 

Cambodia 2000 0 106 100 207 1 46 728 775 4 404 6,020 6,429 

Cambodia 2014 109 219 142 470 97 169 327 595 384 1,117 5,237 6,739 

Nepal 2001 0 20 50 70 3 49 330 383 2 159 6,108 6,270 

Nepal 2011 26 56 52 135 18 84 258 362 212 607 3,951 4,771 

Philippines 2003 264 453 474 1,192 407 726 1,244 2,378 410 865 2,433 3,709 

Philippines 2013 225 338 640 1,204 352 574 1,211 2,138 507 797 2,742 4,047 

Europe

Armenia 2000 25 374 80 481 17 302 84 403 7 158 683 849 

Armenia 2010 281 173 16 471 258 102 30 391 217 314 84 616 

Latin America and Caribbean

Colombia 2000 735 453 250 1,439 864 527 447 1,839 313 435 816 1,565 

Colombia 2010 3,854 1,345 621 5,821 3,180 1,734 1,337 6,252 912 1,311 2,550 4,774 

Dominican 

Republic 2002 2,502 1,544 1,402 5,448 759 715 798 2,272 986 1,400 1,801 4,189 

Dominican 

Republic 2013 419 488 458 1,367 519 528 486 1,534 267 337 405 1,010 

Peru 2000 2,308 1,568 2,084 5,960 201 346 801 1,350 77 261 5,634 5,973 

Peru 2012 1,148 592 384 2,125 1,144 1,132 1,765 4,041 65 433 2,855 3,355 

North Africa and West Asia

Egypt 2000 1,274 381 204 1,860 1,402 457 310 2,170 2,018 1,849 2,711 6,579 

Egypt 2014 758 519 151 1,428 1,521 1,080 553 3,154 3,537 3,828 2,907 10,272 

Jordan 2002 309 541 325 1,176 845 1,128 1,026 3,000 276 453 563 1,293 

Jordan 2012 1,054 1,213 755 3,022 1,264 2,042 1,216 4,523 540 762 488 1,791 

2.4. Analysis 

To examine levels of the poverty, health status, and health service indicators, cross-tabulations are used 

with the appropriate sample weights to provide nationally representative results. The sampling weights are 

based on differences in sampling rates and response rates between areas. 

In tables, some results are too small to be shown because they are based on fewer than 25 unweighted cases 

or fewer than 250 births for mortality; these results are indicated by “*”. Results enclosed in parentheses 

should be considered with caution because they are based generally on 25 to 49 cases or 250 to 499 cases

for mortality rates. In the tables, NA indicates that an indicator was not asked or that a time trend cannot be 

calculated because one or both surveys had an insufficient sample size. 

We present trends between the two surveys, separately by urbanicity and poverty within urbanicity. Since 

there are varying numbers of years between baseline and endline surveys, the trends have been adjusted to 

decadal changes and standardized to a ten-year period. 
12 

Decadal changes to the indicators for each country are calculated by: 

ܫ

݀ = 10

(1ܫ − 2ܫ) × (1ܦ − 2ܦ)

where Id is the decadal change of indicator I, D is the calendar year of the survey, I is the specific indicator, 

the subscript 1 denotes the earlier survey of the pair and the subscript 2 the latter survey. For surveys 

spanning two calendar years, the 0.5 was added to the earlier calendar year for the calculation. 

Averages of the indicators and decadal changers were calculated using the inverse proportion of the 

variance as a weight as is customary in meta-analysis averaging. The formula is: 

ܫ= ݁ݒܽ

1 	× 	ܫ൬∑ 

൰2ݏ

∑ 1

2ݏ

where s2

 is the estimate of the variance for the indicator. For proportionate indicators, s2 is estimated as: 

(ܫ − 1) × ܫ = ଶݏ

݊

where I is the proportionate indicator and n is the denominator corresponding to the indicator, typically the 

number of living children under 5 at the time of the survey. For the estimated variance for questions based 

on prevalence, such as treatment for fever, diarrhea and acute respiratory tract infection (ARI), n is the 

prevalence rate times the number of living children. For the variance of birth-based indicators such as 

antenatal care and delivery assistance, n is an estimate of the number of births given as the number of living 

children divided by the proportion of children surviving to age 5 as given by the under-five mortality rate 

indicator. For the variance of infant and child mortality rates, the number of estimated births is doubled 

because these rates are based on the 10 years preceding the survey. Surveys with not asked indicators are 

not included in the pooled averages. Country cells with small numbers of cases are included but they 

contribute little to the average since their variance is high. 
13 

3. Results 

3.1. Poverty Levels and Trends 

The average poverty classification of children under age 58

 in all 52 surveys is shown in Figure 3.1. Across 

all areas, three-fourths of children under age 5 are extremely poor; this means that they reside in a household 

with two or more UBN. Fifteen percent of children are moderately poor, and 10% are not poor. Rural areas 

have the highest concentration of extreme poverty with 86% of children under age 5 in rural areas extremely 

poor, followed by 57% in other urban areas and 49% in large cities. The pattern is reversed for moderately 

poor and the non-poor. Large cities have the greatest concentration of moderately poor (28%), and nonpoor children (23%). In other urban areas, 17% of children under age 5 are not poor and in rural areas only 

4% are estimated not to be poor. 

Figure 3.1. Pooled average composition of poverty by urbanicity, children under age 5 

The average difference between the percentage of children within each poverty category, as shown above, 

and the percentage of the overall household population within the corresponding category are shown in 

Figure 3.2. Positive numbers indicate that the proportion among children under age 5 is larger than among 

all household residents. Extreme poverty is more concentrated among children than among household 

members of all ages, particularly in large cities: children under 5 living in large cities are 6 percentage 

points more likely to be extremely poor than all household members. The corresponding difference in other 

urban areas is 4 percentage points and in rural areas 3 percentage points. Conversely, children under age 5 

are less likely to be moderately poor or non-poor in any area of residence. 

 

8

 Sometimes indicated as “children”. 

49.2

57.4

85.6

74.8

27.9

25.2

10.0

15.4

22.7 17.4

4.3 9.8

Large cities Other urban

areas

Rural areas ALL AREAS

Extremely poor Moderately poor Not poor
14 

Figure 3.2. Average difference in pooled composition of poverty between children under age 5 and 

household residents of all ages, by urbanicity 

The pooled composition of child poverty, shown earlier, reflects important differences across global 

regions. Figure 3.3 shows the composition of poverty for children under age 5 nationwide in each country, 

grouped by world region. Extreme poverty ranges from 9% in Armenia 2010 to almost 100% in Uganda 

2000-01. Conversely, the percent of children who are not poor ranges from a low of almost 0% in Uganda 

2000-01 to a high of 51% in Armenia 2010. In sub-Saharan Africa, extreme poverty is above 70% in every 

country regardless of the year of survey; two countries in South and Southeast Asia (Cambodia and Nepal) 

have similar rates of extreme poverty. In other countries (notably Armenia, but also Colombia, Egypt, and 

Jordan) recent extreme poverty tends to be much lower. 

Comparing trends in countries over time, the majority of countries saw a decline in extreme child poverty, 

but this was by no means universal: 17 of 26 countries had a decline in extreme child poverty, and 19 

countries had an increase in the proportion of children who are not poor. The remaining 7 countries 

(Cameroon, Mali, Mozambique, Nigeria, Philippines, Dominican Republic, and Egypt) had an increase in 

aggregate child poverty. 

-3.9

-2.3

6.0

-1.9

-2.6

4.4

-0.8

-1.8

2.5

Not poor

Moderately Poor

Extremely poor

Not poor

Moderately Poor

Extremely poor

Not poor

Moderately Poor

Extremely poor

Large cities

Other urban

areas Rural areas

Percentage of children under 5 in poverty category indicated, 

minus the percentage of all housheold members in category
15 

Figure 3.3. Poverty composition of children under age 5 nationwide 

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Burkina Faso 2003

Burkina Faso 2010

Cameroon 2004

Cameroon 2011

Cote D'Ivoire 1998-99

Cote D'Ivoire 2011-12

Ethiopia 2000

Ethiopia 2011

Ghana 2003

Ghana 2014

Guinea 1999

Guinea 2012

Kenya 2003

Kenya 2014

Mali 2001

Mali 2012-13

Mozambique 2003

Mozambique 2011

Niger 1998

Niger 2012

Nigeria 2003

Nigeria 2013

Rwanda 2000

Rwanda 2010

Tanzania 1999

Tanzania 2010

Uganda 2000-01

Uganda 2011

Zambia 2001-02

Zambia 2013-14

Zimbabwe 1999

Zimbabwe 2010-11

Bangladesh 1999-00

Bangladesh 2014

Cambodia 2000

Cambodia 2014

Nepal 2001

Nepal 2011

Philippines 2003

Philippines 2013

Armenia 2000

Armenia 2010

Colombia 2000

Colombia 2010

Dominican Republic 2002

Dominican Republic 2013

Peru 2000

Peru 2012

Egypt 2000

Egypt 2014

Jordan 2002

Jordan 2012

Extremely poor Moderately poor Not poor
16 

Pooled decadal changes in poverty classification are shown in Figure 3.4. Increases are shown in blue and 

decreases are grey. On average, across all areas in all countries, there was a decadal decline in extreme 

poverty of 2.3 percentage points among children under age 5. This was counterbalanced by an overall 

increase in non-poor by 1.5 points and an increase in moderately poor of 0.8 points. Aggregate declines in 

extreme poverty occurred only in rural areas, which are the poorest overall. In urban areas, extreme poverty 

among children increased by 2.6 percentage points in large cities and 0.4 points in other urban areas. 

The increases in extreme poverty in urban areas were counterbalanced by decreases in moderate poverty. 

In large cities, this category saw a decadal decline of 4.5 percentage points overall and 1.5 percentage points 

in other urban areas. Accordingly, all three areas of residence saw an increase in the non-poor, by between 

1 and 2 percentage points. 

Figure 3.4. Pooled average decadal change in poverty classification, by area 

The proportion of children under age 5 living in extreme poverty by area of residence is shown in Figure 

3.5 for each survey, grouped by country. Grey diamonds indicate the proportion of children under age 5 in 

large cities that are in extreme poverty, brown boxes show the corresponding percentage for other urban 

areas, and green circles indicate the proportion of children under age 5 in rural areas who are extremely 

poor. 

As found in the pooled data, extreme poverty is highest among children in rural areas, and this is generally 

by a sizeable margin. The only survey where any other area has poverty at the level of rural areas is in 

Cambodia in 2000 where extreme poverty in rural areas was nearly at the same level as that of other urban 

areas. Conversely, extreme poverty tends to be lowest in large cities. Exceptions are the earliest surveys in 

Rwanda, Zambia, and Bangladesh, the latest surveys in Guinea and the Dominican Republic, and both 

surveys in Zimbabwe. 

In general, the differentials in extreme poverty between rural areas and large cities are around 30 percentage 

points. Notably, the first surveys in Cameroon and Armenia and both surveys in Peru show poverty 

differentials greater than 50 percentage points between large cities and rural areas. The earliest survey in 

Uganda and the latest survey in Jordan show near parity in extreme poverty between areas of residence. 
17 

Changes in extreme poverty within a given country tend to exhibit the same upward or downward trend 

within each area of residence, although not to the same degree. In nine countries—Guinea, Mozambique, 

Rwanda, Zambia, Zimbabwe, Bangladesh, Colombia, the Dominican Republic, and Egypt—trends in 

extreme poverty shifted in direction by area of residence. For example, extreme poverty among children in 

rural areas of Colombia increased slightly over the decade but declined in other urban areas and in large 

cities. 

Figure 3.5. Percentage of children under age 5 in extreme poverty by level of urbanicity 

 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Burkina Faso 2003Burkina Faso 2010

Cameroon 2004Cameroon 2011

Cote D'Ivoire 1998-99Cote D'Ivoire 2011-12

Ethiopia 2000Ethiopia 2011

Ghana 2003Ghana 2014

Guinea 1999Guinea 2012

Kenya 2003Kenya 2014

Mali 2001

Mali 2012-13

Mozambique 2003Mozambique 2011

Niger 1998Niger 2012

Nigeria 2003Nigeria 2013

Rwanda 2000Rwanda 2010

Tanzania 1999Tanzania 2010

Uganda 2011

Uganda 2000-01

Zambia 2001-02Zambia 2013-14

Zimbabwe 1999

Zimbabwe 2010-11

Bangladesh 1999-00

Bangladesh 2014

Cambodia 2000Cambodia 2014

Nepal 2001Nepal 2011

Philippines 2003Philippines 2013

Armenia 2000Armenia 2010

Colombia 2000Colombia 2010

Dominican Republic 2002Dominican Republic 2013

Peru 2000Peru 2012

Egypt 2000Egypt 2014

Jordan 2002Jordan 2012

Large cities Other urban areas Rural areas
18 

3.2. Health Status of Children Under Age 5 

In this section we examine differentials in two indicators of child survival—the infant and under-five 

mortality rates—across levels of poverty and urbanicity. 

Infant mortality rate 

Levels 

Figure 3.6 (left panel) shows the pooled average infant mortality rate, disaggregated by level of urbanicity 

and poverty level. As the figure shows, infant mortality is closely associated with household poverty within 

each area of residence. On average across all surveys, extremely poor children in large city areas are two 

times more likely to die before reaching their first birthday, compared with their non-poor urban 

counterparts (37 deaths per 1,000 live births compared with 19 deaths per 1,000 live births). This gap is 

slightly narrower in other urban areas, and is widest in rural areas, where 26 deaths per 1,000 live births 

occur among non-poor children, 41 among moderately poor children, and 65 among extremely poor 

children. 

An urban advantage is evident when comparing survival for extremely poor children across the three areas 

of residence. The infant mortality rate is lowest among extremely poor children in large cities, higher in 

other urban areas, and highest in rural areas. Table 3.1 shows the differentials in infant mortality by poverty 

according to level of urbanicity within the 26 study countries. 

Decadal change 

The decadal improvements in the infant mortality rate (IMR) closely mirror the levels, with the greatest 

improvements observed in the subgroups with the highest levels of infant mortality (see Figure 3.6, right 

panel). Within each level of urbanicity, the greatest improvements were among extremely poor children, 

which suggests a narrowing of the poverty differentials in infant survival over the decade. Table 3.2 shows 

these patterns within the 26 study countries. 

Figure 3.6. Pooled average infant mortality rate among children born in the five years preceding the 

survey (left panel) and pooled average decadal change in rate (right panel), by poverty according 

to level of urbanization 

18.8 24.3 25.9 31.9 29.0

41.1 37.3 42.5

64.6

Large cities Other urban areas Rural areas

Deaths per 1,000 live births

IMR

Not poor Moderately poor Extremely poor

-4.3 -4.9 -11.3 -6.4 -12.8

-26.2

-12.5

-20.4

-32.6

Large cities Other urban areas Rural areas

Deaths per 1,000 live births

Pooled average decadal change in IMR

Not poor Moderately poor Extremely poor
19

Table 3.1. Infant mortality rate by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey 

Not 

poor 

Moderately 

poor 

Extremely 

poor Total 

Not 

poor 

Moderately 

poor 

Extremely 

poor Total 

Not 

poor 

Moderately 

poor 

Extremely 

poor Total 

Not 

poor 

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * * (63.2) 69.2 * (76.0) 70.4 71.0 * (112.7) 95.0 95.3 * 94.3 92.2 92.1 Burkina Faso 2010 * (54.2) 62.0 59.9 * 75.3 58.9 61.5 * 77.4 81.0 80.9 * 70.6 78.2 77.6 

Cameroon 2004 * 54.8 56.5 55.4 * 63.1 80.9 73.1 * 88.4 91.6 91.2 (51.1) 67.4 86.7 81.2 Cameroon 2011 * 64.1 50.4 53.7 * 57.9 62.2 60.6 * 75.6 77.3 77.3 (43.9) 65.2 70.6 69.4 

Cote D’Ivoire 1998-99 * (89.4) 81.3 80.0 * * 80.1 89.8 * * 123.1 123.9 * 119.7 112.3 111.5 Cote D’Ivoire 2011-12 * (52.7) 71.3 69.0 * 70.9 61.7 63.3 * 89.2 81.3 81.6 (73.2) 72.3 76.3 75.8 

Ethiopia 2000 * * 80.2 81.0 * (107.1) 99.8 99.2 * * 114.7 114.7 * 111.1 113.1 112.9 Ethiopia 2011 * * 40.0 40.0 * * 64.1 62.7 * * 76.0 75.9 * (51.1) 74.1 73.8 

Ghana 2003 * * 45.3 56.8 * * 46.8 52.4 * (120.7) 64.5 69.7 * 100.0 59.0 64.7 Ghana 2014 * (65.9) 47.1 52.7 * 70.5 36.8 44.8 * 51.8 44.6 46.1 (58.6) 60.8 43.6 47.4 

Guinea 1999 * (100.4) 66.3 74.1 * (100.5) 81.0 84.2 * (112.0) 116.1 115.8 * 105.4 107.0 106.6 Guinea 2012 * * 51.5 50.6 * (58.1) 60.5 60.2 * 106.5 81.6 82.8 * 75.3 75.9 75.9 

Kenya 2003 (13.9) (90.1) 74.3 68.1 * (55.2) 54.2 54.1 * 56.1 82.4 78.7 (18.8) 63.1 79.9 75.5 Kenya 2014 * (69.1) 45.3 52.7 (19.8) 43.1 37.1 37.4 (41.6) 32.2 40.2 39.7 40.4 45.6 40.1 40.7 

Mali 2001 (71.9) 92.5 100.1 93.8 * (117.1) 115.7 115.8 * 166.7 130.6 131.9 (73.9) 126.3 127.3 126.2 Mali 2012-13 * (67.3) 38.7 42.0 * * 40.2 43.9 * (53.4) 68.4 68.0 * 62.4 63.6 63.3 

Mozambique 2003 * (61.2) 48.0 51.0 * 87.5 109.9 103.7 * 119.4 135.7 134.9 * 94.0 127.7 123.6 Mozambique 2011 * (74.5) 51.8 61.4 * 80.7 68.6 69.8 * (106.9) 70.9 71.9 * 88.2 69.9 71.0 

Niger 1998 * (68.1) 70.3 69.5 * (86.1) 86.2 85.0 * 146.9 146.7 * 81.3 138.1 135.8 

Niger 2012 * * 44.0 42.0 * (52.2) 40.7 41.5 * * 68.1 68.3 * 53.7 65.1 64.9 Nigeria 2003 * 68.3 73.8 71.2 * 92.6 102.5 98.3 * 141.0 129.7 131.3 (67.3) 103.6 112.9 109.3 Nigeria 2013 * 88.7 60.6 65.2 * 63.6 56.2 57.5 (73.0) 95.8 84.8 85.6 73.2 83.4 76.0 76.8 

Rwanda 2000 * * 77.1 79.0 * * 77.5 77.5 * 197.1 116.7 123.5 * 168.3 111.9 117.4 Rwanda 2010 * (36.7) 50.8 45.1 * * 70.3 68.1 * 77.4 60.4 62.0 (26.2) 70.6 60.4 61.2 

Tanzania 1999 * * * (70.8) * (98.5) 90.0 92.3 * * 114.0 113.0 * 87.8 110.4 107.8 Tanzania 2010 * * * (82.0) * 53.6 54.3 54.2 (56.1) 65.6 58.9 59.5 62.0 69.2 58.4 60.2 

Uganda 2000-01 * * 40.0 39.5 * * 67.9 67.4 * 93.2 93.7 * * 89.1 89.4 Uganda 2011 * (58.8) 41.1 47.4 * (81.8) 53.3 58.4 * (42.0) 67.1 66.3 * 56.9 65.3 64.7 

Zambia 2001-02 * * 59.1 69.0 * 67.4 85.2 79.8 * * 103.9 102.6 * 71.9 96.6 93.9 Zambia 2013-14 * (52.0) 41.3 44.4 (55.3) 53.0 45.7 47.7 * 69.1 48.6 49.3 (49.8) 56.2 47.4 48.3 

Zimbabwe 1999 * * * (43.5) * 59.5 (33.0) 49.3 * 88.0 62.6 65.3 * 67.9 57.3 59.7 Zimbabwe 2010-11 * (54.9) 54.8 57.1 * 48.9 47.6 48.6 (48.2) 47.5 56.8 55.0 55.7 49.7 55.7 54.3 

Bangladesh 2004 * * (64.5) 58.9 * 71.9 76.5 74.9 * 83.9 71.9 72.4 (59.1) 77.0 72.3 72.4 Bangladesh 2014 * (39.2) 32.7 33.1 * 47.8 43.8 43.9 (25.9) 37.3 46.8 45.0 (21.5) 39.9 45.4 43.9 

Cambodia 2000 * * * (34.9) * * 75.1 82.4 * 216.8 88.8 95.7 * 173.7 86.8 92.7 Cambodia 2014 * (7.8) * 3.9 (34.3) 15.3 21.6 21.3 (31.9) 35.7 44.0 42.5 25.3 28.5 41.5 38.5 

Nepal 2001 * * * * * * 54.4 52.9 * (75.1) 79.5 79.3 * 66.3 77.7 77.2 Nepal 2011 * * * (27.6) * (60.2) 39.7 42.9 * 41.3 57.5 55.0 * 43.4 55.4 53.3 

Philippines 2003 (13.0) 17.6 32.2 22.7 24.4 16.9 28.9 24.5 32.6 32.4 37.5 35.8 24.7 23.6 34.3 30.0 Philippines 2013 (10.2) 21.7 17.8 17.8 (16.3) 14.0 21.9 19.2 26.8 17.7 30.4 27.7 19.2 17.3 26.2 23.5 

Continued
20

Table 3.1—Continued

Large cities Other urban areas Rural areas National 

Country Survey 

Not 

poor 

Moderately 

poor 

Extremely 

poor Total 

Not 

poor 

Moderately 

poor 

Extremely 

poor Total 

Not 

poor 

Moderately 

poor 

Extremely 

poor Total 

Not 

poor 

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 31.0 * 34.2 * 36.6 * 37.9 * (43.5) 53.2 52.7 * 35.4 48.7 44.1 Armenia 2010 * (10.1) * (19.8) 6.7 7.4 * 11.3 * (21.7) (16.2) 21.7 21.3 14.0 24.9 18.4 

Colombia 2000 15.7 14.6 (24.7) 16.9 23.1 25.9 26.0 24.6 37.5 28.2 30.2 31.1 22.5 23.3 28.0 24.4 Colombia 2010 15.1 19.9 24.5 17.1 20.1 16.8 20.6 19.3 12.5 23.9 16.3 17.6 16.8 19.9 18.6 18.1 

Dominican 

Republic 

 2002 25.4 38.1 44.0 33.9 26.9 42.8 23.7 30.9 34.2 37.5 39.7 37.5 28.0 38.8 38.3 34.6 

Dominican 

Republic 

 2013 * (41.8) (37.8) 32.7 39.9 30.4 22.0 30.0 (15.0) 26.1 36.8 28.3 23.2 33.5 31.7 30.6 

Peru 2000 14.9 27.5 34.1 25.0 22.6 45.4 45.1 42.0 * 57.3 60.8 60.3 16.1 34.6 53.0 43.2 Peru 2012 8.9 (14.1) (17.2) 12.0 20.3 17.1 18.9 18.8 * 23.3 26.2 25.3 14.1 17.6 22.9 19.6 

Egypt 2000 32.3 52.5 (47.2) 38.6 40.8 58.4 53.2 47.0 42.1 58.6 75.7 61.8 38.9 57.7 71.7 54.7 Egypt 2014 25.2 11.7 (20.3) 17.5 28.9 16.4 18.4 20.8 34.2 24.1 31.2 28.9 31.5 20.7 28.6 25.9 

Jordan 2002 * 18.5 (12.1) 16.4 39.9 20.3 24.1 25.2 (36.6) 34.8 25.7 30.2 34.8 22.6 22.4 24.4 Jordan 2012 (24.0) 10.9 21.0 17.1 27.3 15.8 16.4 18.1 18.0 17.8 12.3 16.0 24.4 14.6 17.1 17.4 

Pooled Average 18.8 31.9 37.3 32.3 24.3 29.0 42.5 35.3 25.9 41.1 64.6 59.3 24.5 35.1 59.4 49.4 
21

Table 3.2. Decadal change in infant mortality rate by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA NA -1.7 -13.3 NA -1.0 -16.4 -13.6 NA -50.4 -20.0 -20.6 NA -33.9 -20.0 -20.7

Cameroon 2004 Cameroon 2011 NA 13.3 -8.7 -2.4 NA -7.4 -26.7 -17.9 NA -18.3 -20.4 -19.9 -10.3 -3.1 -23.0 -16.9

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA -28.2 -7.7 -8.5 NA NA -14.2 -20.4 NA NA -32.2 -32.5 NA -36.5 -27.7 -27.5

Ethiopia 2000 Ethiopia 2011 NA NA -36.5 -37.3 NA NA -32.5 -33.2 NA NA -35.2 -35.3 NA -54.5 -35.5 -35.5

Ghana 2003 Ghana 2014 NA NA 1.6 -3.7 NA NA -9.1 -6.9 NA -62.6 -18.1 -21.5 NA -35.6 -14.0 -15.7

Guinea 1999 Guinea 2012 NA NA -11.4 -18.1 NA -32.6 -15.8 -18.5 NA -4.2 -26.5 -25.4 NA -23.2 -23.9 -23.6

Kenya 2003 Kenya 2014 NA -19.1 -26.4 -14.0 NA -11.0 -15.5 -15.2 NA -21.7 -38.4 -35.5 19.6 -15.9 -36.2 -31.6

Mali 2001 Mali 2012.5 NA -21.9 -53.4 -45.0 NA NA -65.7 -62.5 NA -98.5 -54.1 -55.6 NA -55.6 -55.4 -54.7

Mozambique 2003 Mozambique 2011 NA 16.6 4.8 13.0 NA -8.5 -51.6 -42.4 NA -15.6 -81.0 -78.8 NA -7.3 -72.3 -65.8

Niger 1998 Niger 2012 NA NA -18.8 -19.6 NA -24.2 -32.5 -31.1 NA NA -56.3 -56.0 NA -19.7 -52.1 -50.6

Nigeria 2003 Nigeria 2013 NA 20.4 -13.2 -6.0 NA -29.0 -46.3 -40.8 NA -45.2 -44.9 -45.7 5.9 -20.2 -36.9 -32.5

Rwanda 2000 Rwanda 2010 NA NA -26.3 -33.9 NA NA -7.2 -9.4 NA -119.7 -56.3 -61.5 NA -97.7 -51.5 -56.2

Tanzania 1999 Tanzania 2010 NA NA NA 10.2 NA -40.8 -32.5 -34.6 NA NA -50.1 -48.6 NA -16.9 -47.3 -43.3

Uganda 2000.5 Uganda 2011 NA NA 1.0 7.5 NA NA -13.9 -8.6 NA NA -24.9 -26.1 NA NA -22.7 -23.5

Zambia 2001.5 Zambia 2013.5 NA NA -14.8 -20.5 NA -12.0 -32.9 -26.8 NA NA -46.1 -44.4 NA -13.1 -41.0 -38.0

Zimbabwe 1999 Zimbabwe 2010.5 NA NA NA 11.8 NA -9.2 12.7 -0.6 NA -35.2 -5.0 -9.0 NA -15.8 -1.4 -4.7

Bangladesh 2004 Bangladesh 2014 NA NA -31.8 -25.8 NA -24.1 -32.7 -31.0 NA -46.6 -25.1 -27.4 -37.6 -37.1 -26.9 -28.5

Cambodia 2000 Cambodia 2014 NA NA NA -22.1 NA NA -38.2 -43.6 NA -129.4 -32.0 -38.0 NA -103.7 -32.4 -38.7

Nepal 2001 Nepal 2011 NA NA NA NA NA NA -14.7 -10.0 NA -33.8 -22.0 -24.3 NA -22.9 -22.3 -23.9

Philippines 2003 Philippines 2013 -2.8 4.1 -14.4 -4.9 -8.1 -2.9 -7.0 -5.3 -5.8 -14.7 -7.1 -8.1 -5.5 -6.3 -8.1 -6.5

Continued
22

Table 3.2—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA -20.9 NA -14.4 NA -29.2 NA -26.6 NA -21.8 -37.0 -31.0 NA -21.4 -23.8 -25.7

Colombia 2000 Colombia 2010 -0.6 5.3 -0.2 0.2 -3.0 -9.1 -5.4 -5.3 -25.0 -4.3 -13.9 -13.5 -5.7 -3.4 -9.4 -6.3

Dominican 

Republic 

 2002 

Dominican 

Republic 

 2013 NA 3.4 -5.6 -1.1 11.8 -11.3 -1.5 -0.8 -17.5 -10.4 -2.6 -8.4 -4.4 -4.8 -6.0 -3.6

Peru 2000 Peru 2012 -5.0 -11.2 -14.1 -10.8 -1.9 -23.6 -21.8 -19.3 NA -28.3 -28.8 -29.2 -1.7 -14.2 -25.1 -19.7

Egypt 2000 Egypt 2014 -5.1 -29.1 -19.2 -15.1 -8.5 -30.0 -24.9 -18.7 -5.6 -24.6 -31.8 -23.5 -5.3 -26.4 -30.8 -20.6

Jordan 2002 Jordan 2012 NA -7.6 8.9 0.7 -12.6 -4.5 -7.7 -7.1 -18.6 -17.0 -13.4 -14.2 -10.4 -8.0 -5.3 -7.0

Pooled Average -4.3 -6.4 -12.5 -8.5 -4.9 -12.8 -20.4 -15.6 -11.3 -26.2 -32.6 -30.9 -4.8 -15.5 -29.0 -23.4Note: NA indicates too few cases to calculate decadal change.
23 

Under-five mortality 

Levels 

Stark disparities are evident in under-five child survival across levels of poverty (see Figure 3.7, left panel, 

and Table 3.3). In large city areas, children in extremely poor households are nearly three times more likely 

to die before reaching their fifth birthday, when compared with their non-poor counterparts. These 

differentials are greater than the differentials in child survival in other urban areas, where extremely poor 

children are two times more likely to die before reaching age 5 than non-poor children. In rural areas, the 

differentials are similar to those in large cities, with extremely poor children roughly 3 times more likely to 

die before reaching age 5 than their non-poor counterparts. 

In comparisons of survival for extremely poor children across the three levels of urbanicity, extremely poor 

children in urban areas (both groups) fare better than their extremely poor rural counterparts. The 

differentials across level of urbanicity are smaller for the non-poor (ranging from 22 deaths per 1,000 live 

births in large cities to 33 deaths per 1,000 live births in rural areas) and the moderately poor (ranging from 

42 deaths per 1,000 live births in large cities to 56 deaths per 1,000 live births in rural areas). 

Decadal change 

The decadal improvements in under-five mortality (U5M) closely mirror the mortality levels. Within each 

area of residence, the greatest improvements were observed among extremely poor children, thus 

suggesting a narrowing of the gap in the under-five mortality rate between the extreme poor and the notpoor over the decade (see Figure 3.7, right panel, and Table 3.4). 

Figure 3.7. Pooled average under-five mortality rate among children born in the five years preceding 

the survey (left panel) and pooled average decadal change in rate (right panel), by poverty according 

to level of urbanicity 

While both infant and U5M rates are highest for extremely poor children and lowest for non-poor children 

in all urbanicity areas, the rates have fallen more rapidly for the extremely poor and in rural areas. The 

overall fall over a ten-year period was 23 infant deaths and 39 under-five deaths per 1,000 live births. Thus, 

while the gap between poor and not-poor children narrowed, the poor children are still at a disadvantage. 

Extremely poor children in both large and smaller urban areas have about the same level of U5M while 

those in rural areas have much higher mortality rates. 

22.4 30.5 32.6

42.2 36.6

55.6 62.7 63.4

105.0

Large cities Other urban areas Rural areas

Deaths per 1,000 live births

U5M

Not poor Moderately poor Extremely poor

-7.7 -5.6 -12.2 -12.7 -19.6

-35.8 -29.2 -37.4

-57.5

Large cities Other urban areas Rural areas

Deaths per 1,000 live births

Pooled average decadal change in U5M

Not poor Moderately poor Extremely poor
24

Table 3.3. Under-five mortality by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * * (120.3) (118.7) * * 150.5 150.8 * * 201.1 201.5 * (177.9) 194.4 193.2 Burkina Faso 2010 * * 99.5 95.1 * (113.4) 110.2 110.3 * (160.8) 156.1 156.0 * 126.5 149.4 147.7

Cameroon 2004 * 96.0 (91.0) 93.3 * 111.1 145.4 130.5 * 150.9 171.0 168.8 (86.4) 117.1 159.6 147.6Cameroon 2011 * 83.5 75.1 75.8 * 89.0 105.2 102.0 * 141.9 153.8 153.4 * 102.2 132.8 128.4

Cote D’Ivoire 1998-99 * (118.5) (124.0) 118.2 * * 125.3 132.9 * * 197.1 196.8 * 171.0 178.7 174.3Cote D’Ivoire 2011-12 * * 97.8 96.5 * (110.6) 101.1 102.5 * 135.3 124.4 124.8 * 113.1 116.8 115.8

Ethiopia 2000 * * 113.6 113.5 * * 162.1 155.0 * * 192.5 192.5 * (131.2) 189.1 187.8Ethiopia 2011 * * 52.6 53.0 * * 90.1 88.3 * * 114.5 114.5 * (68.5) 110.8 110.3

Ghana 2003 * * 81.9 92.0 * * 89.5 93.4 * * 112.3 118.3 * 144.3 104.3 109.7Ghana 2014 * * 55.4 64.1 * (92.4) 56.1 64.4 * 81.6 72.5 74.6 * 87.0 65.3 70.1

Guinea 1999 * (199.6) 124.7 141.0 * * 158.6 156.4 * (230.1) 209.7 210.6 * 199.9 195.3 195.1Guinea 2012 * * 70.1 70.0 * (103.9) 105.6 104.4 * (182.6) 146.5 148.0 * 132.4 133.4 133.0

Kenya 2003 (35.7) (123.2) (109.5) 100.0 * (96.2) 84.8 87.0 * 70.5 123.0 116.9 (51.7) 86.7 119.5 112.7Kenya 2014 * (92.7) 58.2 67.5 * 52.3 52.1 51.4 * 39.9 56.6 55.5 (49.5) 57.6 55.9 56.0

Mali 2001 * 125.7 146.3 133.8 * (229.7) 224.8 224.6 * 316.4 251.3 253.2 (114.8) 220.5 242.9 238.2Mali 2012-13 * * 56.5 59.3 * * 64.7 69.0 * * 113.5 113.5 * 101.6 104.6 104.4

Mozambique 2003 * (112.2) 77.9 89.2 * 126.8 164.5 154.0 * (165.7) 193.3 192.0 * 137.6 183.9 178.2Mozambique 2011 * (104.7) 66.5 80.5 * (108.8) 101.7 103.3 * * 109.8 111.2 * 124.6 106.8 108.1

Niger 1998 * (142.8) 150.6 147.3 * * 196.6 193.6 * 327.5 327.4 * 181.2 307.5 302.6Niger 2012 * * 82.3 80.1 * * 83.4 84.5 * * 162.7 163.2 * (123.0) 153.5 153.0

Nigeria 2003 * (115.4) 140.8 128.4 * 207.8 217.1 211.4 * 214.9 257.3 249.7 * 192.4 228.8 217.1Nigeria 2013 * (121.7) 99.0 102.7 * 114.1 95.8 98.5 * 171.7 166.5 166.6 (110.5) 145.3 143.9 143.9

Rwanda 2000 * * 139.7 140.2 * * 140.6 141.7 * (371.6) 203.7 216.2 * 317.4 196.4 206.7Rwanda 2010 * (53.5) 71.3 64.7 * * 104.1 101.0 * 119.6 103.4 104.9 * 108.3 101.8 102.1

Tanzania 1999 * * * * * (139.4) 145.0 142.5 * * 166.9 165.9 * 134.9 164.4 161.1Tanzania 2010 * * * (115.7) * 74.3 95.6 85.0 (77.8) 93.5 92.0 91.9 73.0 97.6 92.0 92.4

Uganda 2000-01 * * 79.9 80.5 * * 118.5 117.7 * 162.7 163.4 * * 155.9 156.5Uganda 2011 * * (53.4) 65.1 * * 80.7 85.4 * * 112.1 110.6 * 79.7 108.0 106.3

Zambia 2001-02 * * 132.9 136.5 * 123.2 150.3 141.5 * * 185.4 182.3 * 119.7 174.3 167.9Zambia 2013-14 * (92.6) 62.8 71.2 * 76.1 72.1 72.9 * (99.0) 84.7 85.1 * 86.4 80.1 80.6

Zimbabwe 1999 * * * (70.2) * 82.6 (46.9) 68.3 * (115.8) 98.2 99.7 * 94.4 89.3 90.3Zimbabwe 2010-11 * (85.7) (71.2) 77.9 * 71.6 76.9 76.5 * 68.0 79.4 77.6 (84.3) 73.3 78.3 77.5

Bangladesh 2004 * * (89.2) 80.0 * 77.9 101.2 94.6 * 100.5 98.0 97.7 (64.9) 89.1 98.2 96.6Bangladesh 2014 * * 41.8 39.7 * (55.8) 49.0 49.4 * 52.9 57.7 56.5 (33.8) 51.9 55.2 54.0

Cambodia 2000 * * * (40.3) * * 100.3 106.9 * 263.4 118.4 126.0 * 207.5 115.5 121.6Cambodia 2014 * * (14.6) 10.1 * 17.3 24.9 24.3 * 41.4 54.4 52.4 35.8 33.0 51.5 47.7

Nepal 2001 * * * * * * 69.4 68.1 * (96.0) 112.4 111.9 * 85.1 109.5 108.4Nepal 2011 * * * (30.9) * (65.8) 48.5 50.9 * 48.4 67.2 64.4 * 50.6 64.9 62.4

Philippines 2003 (20.7) 19.9 41.9 29.2 24.4 22.3 38.3 31.1 35.9 41.1 58.5 52.2 27.8 29.7 50.7 41.6Philippines 2013 * 25.1 25.3 24.2 (28.3) 15.6 30.6 26.2 (33.6) 22.2 42.8 38.2 28.3 20.7 36.9 32.3

Continued
25

Table 3.3—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 34.3 * 36.5 * 37.0 (36.2) 38.1 * (47.4) 60.2 59.2 * 37.6 54.1 48.0 Armenia 2010 * (10.1) * (19.8) (11.2) 12.9 * 16.3 * (27.0) (19.7) 25.7 (22.8) 17.4 28.0 21.3

Colombia 2000 17.8 17.2 (24.7) 18.8 27.3 29.6 28.1 28.2 41.6 34.9 34.7 36.2 25.8 27.7 31.2 28.0Colombia 2010 16.1 23.1 29.9 19.0 22.4 19.9 24.6 22.2 19.2 30.2 23.7 24.5 19.0 24.1 24.8 21.7

Dominican 

Republic 

2002 30.6 52.0 52.5 42.4 30.5 49.2 34.9 37.8 38.3 43.3 55.5 46.9 32.6 48.2 50.6 43.2

Dominican 

Republic 

2013 * (42.3) (44.0) 35.2 43.5 30.8 24.0 31.6 * 31.4 42.2 35.8 28.6 35.1 36.2 34.0

Peru 2000 20.2 38.5 46.7 34.3 35.5 53.5 64.5 57.5 * 65.1 86.9 85.3 21.9 44.7 75.2 60.4Peru 2012 8.9 (21.6) * 13.8 23.5 20.3 28.6 24.9 * 32.1 33.8 32.9 15.7 23.2 30.6 25.2

Egypt 2000 36.0 62.8 (64.7) 45.6 48.2 71.6 78.9 58.9 53.7 74.0 97.4 79.2 46.9 71.9 93.4 69.2Egypt 2014 (25.2) 15.5 (20.3) 19.8 35.7 18.7 22.6 24.3 41.1 28.6 35.9 33.9 37.3 24.5 33.0 30.3

Jordan 2002 * 20.6 (16.8) 19.2 (46.5) 23.8 30.3 30.4 * 41.6 31.8 36.4 39.7 26.3 28.3 29.3Jordan 2012 * 12.3 28.3 20.3 31.6 18.2 20.4 21.2 (18.8) 20.3 16.1 18.8 26.5 16.7 22.2 20.5

Pooled Average 22.4 42.2 62.7 44.2 30.5 36.6 63.4 47.8 32.6 55.6 105.0 92.8 30.1 46.0 94.2 72.9
26

Table 3.4. Decadal change in U5MR by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA NA -29.7 -33.7 NA NA -57.6 -57.9 NA NA -64.3 -65.0 NA -73.4 -64.3 -65.0

Cameroon 2004 Cameroon 2011 NA -17.9 -22.7 -25.0 NA -31.6 -57.4 -40.7 NA -12.9 -24.6 -22.0 NA -21.3 -38.3 -27.4

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA NA -20.2 -16.7 NA NA -18.6 -23.4 NA NA -55.9 -55.4 NA -44.5 -47.6 -45.0

Ethiopia 2000 Ethiopia 2011 NA NA -55.5 -55.0 NA NA -65.5 -60.6 NA NA -70.9 -70.9 NA -57.0 -71.2 -70.5

Ghana 2003 Ghana 2014 NA NA -24.1 -25.4 NA NA -30.4 -26.4 NA NA -36.2 -39.7 NA -52.1 -35.5 -36.0

Guinea 1999 Guinea 2012 NA NA -42.0 -54.6 NA NA -40.8 -40.0 NA -36.5 -48.6 -48.2 NA -51.9 -47.6 -47.8

Kenya 2003 Kenya 2014 NA -27.7 -46.6 -29.5 NA -39.9 -29.7 -32.4 NA -27.8 -60.4 -55.8 -2.0 -26.5 -57.8 -51.5

Mali 2001 Mali 2012.5 NA NA -78.1 -64.8 NA NA -139.2 -135.3 NA NA -119.8 -121.5 NA -103.4 -120.3 -116.3

Mozambique 2003 Mozambique 2011 NA -9.4 -14.3 -10.9 NA -22.5 -78.5 -63.4 NA NA -104.4 -101.0 NA -16.3 -96.4 -87.6

Niger 1998 Niger 2012 NA NA -48.8 -48.0 NA NA -80.9 -77.9 NA NA -117.7 -117.3 NA -41.6 -110.0 -106.9

Nigeria 2003 Nigeria 2013 NA 6.3 -41.8 -25.7 NA -93.7 -121.3 -112.9 NA -43.2 -90.8 -83.1 NA -47.1 -84.9 -73.2

Rwanda 2000 Rwanda 2010 NA NA -68.4 -75.5 NA NA -36.5 -40.7 NA -252.0 -100.3 -111.3 NA -209.1 -94.6 -104.6

Tanzania 1999 Tanzania 2010 NA NA NA NA NA -59.2 -44.9 -52.3 NA NA -68.1 -67.3 NA -33.9 -65.8 -62.5

Uganda 2000.5 Uganda 2011 NA NA -25.2 -14.7 NA NA -36.0 -30.8 NA NA -48.2 -50.3 NA NA -45.6 -47.8

Zambia 2001.5 Zambia 2013.5 NA NA -58.4 -54.4 NA -39.3 -65.2 -57.2 NA NA -83.9 -81.0 NA -27.8 -78.5 -72.8

Zimbabwe 1999 Zimbabwe 2010.5 NA NA NA 6.7 NA -9.6 26.1 7.1 NA -41.6 -16.3 -19.2 NA -18.3 -9.6 -11.1

Bangladesh 2004 Bangladesh 2014 NA NA -47.4 -40.3 NA -22.1 -52.2 -45.2 NA -47.6 -40.3 -41.2 -31.1 -37.2 -43.0 -42.6

Cambodia 2000 Cambodia 2014 NA NA NA -21.6 NA NA -53.9 -59.0 NA -158.6 -45.7 -52.6 NA -124.6 -45.7 -52.8

Nepal 2001 Nepal 2011 NA NA NA NA NA NA -20.9 -17.2 NA -47.6 -45.2 -47.5 NA -34.5 -44.6 -46.0

Philippines 2003 Philippines 2013 NA 5.2 -16.6 -5.0 3.9 -6.7 -7.7 -4.9 -2.3 -18.9 -15.7 -14.0 0.5 -9.0 -13.8 -9.3

Continued
27

Table 3.4—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA -24.2 NA -16.7 NA -24.1 NA -21.8 NA -20.4 -40.5 -33.5 NA -20.2 -26.1 -26.7

Colombia 2000 Colombia 2010 -1.7 5.9 5.2 0.2 -4.9 -9.7 -3.5 -6.0 -22.4 -4.7 -11.0 -11.7 -6.8 -3.6 -6.4 -6.3

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 NA -8.8 -7.7 -6.5 11.8 -16.7 -9.9 -5.6 NA -10.8 -12.1 -10.1 -3.6 -11.9 -13.1 -8.4

Peru 2000 Peru 2012 -9.4 -14.1 NA -17.1 -10.0 -27.7 -29.9 -27.2 NA -27.5 -44.3 -43.7 -5.2 -17.9 -37.2 -29.3

Egypt 2000 Egypt 2014 -7.7 -33.8 -31.7 -18.4 -8.9 -37.8 -40.2 -24.7 -9.0 -32.4 -43.9 -32.4 -6.9 -33.9 -43.1 -27.8

Jordan 2002 Jordan 2012 NA -8.3 11.5 1.1 -14.9 -5.6 -9.9 -9.2 NA -21.3 -15.7 -17.6 -13.2 -9.6 -6.1 -8.8

Pooled Average -7.7 -12.2 -29.2 -16.9 -5.6 -19.6 -37.4 -25.9 -12.7 -35.8 -57.5 -51.9 -6.5 -22.8 -51.3 -38.8

Note: NA indicates too few cases to calculate decadal change.
28 

Nationally, three countries have experienced a decline of more than 100 deaths per 1,000 live births in 

under-five mortality in a 10-year period: Mali (116), Niger (107), and Rwanda (105) as shown in Table 3.4. 

The countries with the least decline, all under 10 deaths per 1,000 live births, were the Philippines (9), 

Jordan (9), the Dominican Republic (8), and Columbia (6). For the extremely poor in large cities, four 

countries have a more than 50 per 1000 decline: Mali (78), Rwanda (68), Zambia (58), and Ethiopia (55). 

Thus, the declines are the largest in the high mortality countries and the smallest in the low mortality 

countries. 

3.3. Nutritional Status of Children under Age 5 

Stunting 

Levels 

Within each area of residence, the pooled average prevalence of stunting is closely associated with 

household poverty (see Figure 3.8, left panel). In large cities, 17% of children in extremely poor households 

were stunted, compared with 12% in moderately poor households, and 7% in not poor households. In other 

urban areas, the disparity in stunting across poverty levels is even wider, with children in extremely poor 

households more than three times more likely to be stunted (25%) than children in non-poor households 

(9%). Among children in extreme poverty, stunting is lowest in large cities (17%) and other urban areas 

(25%), and is highest in rural areas (39%). 

In the latest surveys, stunting is over 40% of children in seven countries: Ethiopia and Rwanda (44%), 

Niger and Mozambique (43%), Tanzania (42%), and Nepal and Zambia (40%). For extremely poor children 

in large cities, severe stunting exceeds 10% in Bangladesh and Zambia (15%), Nigeria (14%), and Tanzania 

and Zimbabwe (13%) (see Table 3.5). 

Decadal change 

On average across all the surveys, stunting declined in all subgroups over the decade (see Figure 3.8, right 

panel). In large city areas, the decline was greatest among moderately poor children—a 7 percentage point 

decrease—compared with a 3 and 4 percentage point decrease for non-poor children and extremely poor 

children, respectively. In other urban areas, the decline was greatest among extremely poor children. Table 

3.6 shows country-specific differentials in the decadal change in stunting. 

Figure 3.8. Pooled average prevalence of stunting among children under age 5 (left panel) and 

pooled average decadal change in coverage (right panel), by poverty according to level of urbanicity 

7.3 9.4 16.2 11.7 13.5

21.0 17.4 24.6

38.6

Large cities Other urban areas Rural areas

Percentage

Stunting

Not poor Moderately poor Extremely poor

-2.8 -0.5 -6.8 -7.2 -2.9 -7.3 -3.9 -4.2 -4.5

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in stunting

Not poor Moderately poor Extremely poor
29

Table 3.5. Stunting by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * 14.5 22.2 19.5 * 22.0 27.7 26.5 * 32.8 46.2 45.9 (22.3) 23.9 43.9 42.8 Burkina Faso 2010 (15.3) 12.0 19.5 17.4 * 17.5 24.9 23.0 * 30.8 37.5 37.2 19.0 23.5 35.6 34.5

Cameroon 2004 15.2 17.6 26.3 20.8 19.5 30.0 37.7 34.4 * 35.5 44.3 43.3 17.7 27.5 41.3 37.5Cameroon 2011 (7.3) 8.0 15.1 12.3 (7.3) 18.0 29.3 26.5 (47.4) 30.8 40.7 40.1 18.1 18.0 34.8 32.0

Cote D’Ivoire 1998-99 (10.5) 7.5 14.9 12.3 * 32.3 34.9 33.8 * 27.7 36.2 35.0 11.3 21.9 33.3 31.0Cote D’Ivoire 2011-12 * 18.4 22.0 19.0 (12.3) 18.8 22.1 20.8 * 30.2 35.7 35.1 7.9 23.4 31.5 29.8

Ethiopia 2000 (17.5) 20.2 40.1 33.7 (7.7) 46.6 51.8 50.5 * (36.6) 58.3 58.2 16.5 39.2 57.6 57.1Ethiopia 2011 * (6.1) 24.7 22.2 * 16.5 34.0 32.9 * (41.1) 46.2 46.2 (24.1) 21.0 44.6 44.3

Ghana 2003 * 17.6 22.3 21.3 * 18.5 28.1 25.9 * 36.0 40.8 40.3 * 26.6 36.2 34.8Ghana 2014 * 7.6 13.2 11.3 * 11.8 17.2 15.5 (7.3) 20.2 22.8 21.8 7.8 13.7 19.6 17.9

Guinea 1999 * 16.4 20.1 19.3 * 24.0 25.1 24.9 * 35.7 34.1 34.2 * 26.6 31.0 30.5Guinea 2012 * 8.6 17.1 15.4 * 17.7 21.4 20.3 * 24.2 36.1 35.2 (5.4) 18.9 32.4 30.9

Kenya 2003 6.6 17.2 35.8 25.3 (10.2) 26.7 37.2 32.7 13.0 25.9 38.6 37.0 9.4 24.2 38.3 35.5Kenya 2014 8.2 16.3 21.1 18.6 7.2 15.0 23.2 20.3 18.9 17.8 30.0 29.0 10.5 16.3 27.9 25.8

Mali 2001 17.6 17.8 19.5 18.6 * 34.4 35.7 35.2 24.1 44.8 46.2 45.9 21.5 31.7 43.4 41.4Mali 2012-13 * 16.6 22.8 21.5 * 17.6 25.5 25.0 * 21.5 43.0 42.0 24.0 19.4 39.8 38.4

Mozambique 2003 (8.9) 19.9 28.0 24.5 (22.6) 26.0 39.7 36.4 * 37.5 52.4 51.6 19.3 29.1 48.8 46.5Mozambique 2011 (11.1) 19.3 25.1 22.6 (6.2) 24.5 39.1 37.2 * 36.3 45.8 45.5 11.2 27.4 43.8 42.8

Niger 1998 * 21.6 34.5 30.1 * 29.8 41.5 39.3 * (50.7) 48.6 48.6 * 30.6 47.3 46.5Niger 2012 * 6.2 24.3 21.6 * 22.6 37.4 35.6 * * 45.2 45.2 (8.6) 22.2 43.7 43.3

Nigeria 2003 27.8 24.1 34.7 30.0 17.4 33.1 43.4 39.0 (53.8) 42.7 52.7 50.7 27.9 34.1 46.8 42.5Nigeria 2013 8.6 18.7 26.9 24.6 33.8 21.9 27.6 26.4 24.6 29.1 44.9 43.0 22.9 24.5 39.0 36.7

Rwanda 2000 * 13.1 29.4 27.4 * 31.0 36.3 35.2 * 43.8 51.5 50.8 * 39.6 49.1 48.1Rwanda 2010 (8.5) 21.8 23.2 21.6 * (26.9) 38.5 36.2 18.6 35.6 48.6 46.2 16.0 33.5 46.8 44.0

Tanzania 1999 * 26.6 (30.0) 27.8 (25.5) 23.0 30.8 27.9 * 34.4 53.1 52.5 18.1 26.5 50.6 48.2Tanzania 2010 * 22.8 30.1 24.9 17.3 30.3 36.8 33.3 33.6 33.8 45.3 44.2 21.3 30.5 44.0 41.6

Uganda 2000-01 * * 31.5 31.4 * * 32.7 32.6 * * 45.6 45.7 * (61.7) 44.2 44.3Uganda 2011 * (12.0) 13.3 12.3 * (24.1) 24.0 23.5 * (19.4) 36.1 35.5 * 18.1 34.3 33.2

Zambia 2001-02 * 27.1 41.9 39.3 * 41.4 44.3 43.3 * 39.9 57.5 57.0 * 38.8 54.0 52.4Zambia 2013-14 (14.2) 35.0 38.8 36.8 22.8 30.2 38.3 35.4 (33.0) 41.6 42.0 42.0 22.5 34.4 41.1 40.0

Zimbabwe 1999 * 25.4 36.4 31.8 * 21.5 29.0 24.6 * 31.1 34.7 34.2 (26.9) 25.3 34.1 31.9Zimbabwe 2010-11 (21.0) 20.7 34.7 28.1 19.5 26.3 30.3 27.0 28.6 29.9 33.2 32.4 24.8 26.9 33.0 31.1

Bangladesh 2004 * (37.8) 46.9 43.6 22.4 26.8 53.5 44.6 25.3 36.2 53.4 51.8 23.0 32.7 53.3 50.4Bangladesh 2014 (14.7) 25.4 35.4 30.1 (12.0) 18.5 35.6 31.1 17.0 29.4 40.9 38.1 16.1 26.4 39.7 36.2

Cambodia 2000 * 12.3 26.7 19.3 * 40.7 47.9 47.5 * 51.0 51.6 51.5 * 42.6 50.8 50.2Cambodia 2014 (15.5) 12.8 33.3 19.1 13.8 20.9 33.2 26.4 19.3 29.2 35.1 33.4 17.4 25.5 34.9 31.9

Nepal 2001 * * (38.3) 38.0 * 23.9 46.3 43.1 * 38.7 58.6 58.0 * 35.7 57.8 57.0Nepal 2011 * * * 23.5 * 13.5 34.5 28.2 27.4 31.7 43.9 41.6 25.4 28.8 43.3 40.3

Philippines 2003 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Philippines 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Continued
30

Table 3.5—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 12.0 (8.2) 11.7 * 18.4 14.8 17.3 * 14.0 20.7 19.4 (15.7) 14.6 18.9 16.7 Armenia 2010 10.5 13.0 * 11.5 23.8 25.1 (29.1) 24.5 20.1 24.2 17.6 21.8 17.8 21.0 19.4 19.2

Colombia 2000 11.9 15.8 23.4 15.2 10.0 18.5 21.9 15.4 17.9 17.0 30.5 24.3 11.9 17.2 26.7 18.1Colombia 2010 8.8 17.4 15.7 11.6 8.5 10.4 19.5 11.4 11.4 14.2 20.5 17.0 9.0 13.7 19.5 13.1

Dominican 

Republic 

2002 5.5 10.9 13.1 9.2 10.0 11.2 15.0 12.1 8.2 11.5 19.1 13.8 7.0 11.2 16.1 11.4

Dominican 

Republic 

2013 8.0 3.3 7.0 6.0 5.5 6.3 12.1 7.8 7.0 4.2 8.3 6.5 6.7 4.7 9.2 6.8

Peru 2000 7.1 15.9 25.6 16.1 12.2 17.2 31.5 25.1 18.9 24.9 48.4 47.1 7.8 17.2 41.2 31.0Peru 2012 3.2 3.9 7.4 4.2 6.7 10.1 20.3 13.7 12.8 20.4 34.2 31.9 5.1 10.4 27.0 17.8

Egypt 2000 13.6 14.2 17.4 14.1 20.0 22.9 28.7 21.9 23.9 24.4 30.8 26.8 19.9 22.6 29.7 23.5Egypt 2014 19.7 19.2 17.8 19.3 25.6 24.9 22.0 24.7 19.0 19.9 24.1 20.8 20.8 20.8 23.5 21.5

Jordan 2002 5.8 10.1 8.6 8.6 9.9 9.9 11.7 10.5 10.4 13.8 20.9 16.1 9.1 10.8 13.7 11.4Jordan 2012 1.6 6.2 16.9 7.2 5.9 7.6 8.6 7.5 7.7 7.8 12.2 9.0 4.6 7.2 11.7 7.6

Pooled Average 7.3 11.7 17.4 12.9 9.4 13.5 24.6 17.8 16.2 21.0 38.6 34.6 10.3 16.7 34.5 26.8
31

Table 3.6. Decadal change in stunting by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA -3.6 -3.9 -3.0 NA -6.4 -4.0 -5.0 NA -2.9 -12.4 -12.4 -4.7 -0.6 -11.9 -11.9

Cameroon 2004 Cameroon 2011 -11.3 -13.7 -16.0 -12.1 -17.4 -17.1 -12.0 -11.3 NA -6.7 -5.1 -4.6 0.6 -13.6 -9.3 -7.9

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA 8.4 5.5 5.2 NA -10.4 -9.8 -10.0 NA 1.9 -0.4 0.1 -2.6 1.2 -1.4 -0.9

Ethiopia 2000 Ethiopia 2011 NA -12.8 -14.0 -10.5 NA -27.4 -16.2 -16.0 NA 4.1 -11.0 -10.9 6.9 -16.5 -11.8 -11.6

Ghana 2003 Ghana 2014 NA -9.1 -8.3 -9.1 NA -6.1 -9.9 -9.5 NA -14.4 -16.4 -16.8 NA -11.7 -15.1 -15.4

Guinea 1999 Guinea 2012 NA -6.0 -2.3 -3.0 NA -4.8 -2.8 -3.5 NA -8.8 1.5 0.8 NA -5.9 1.1 0.3

Kenya 2003 Kenya 2014 1.5 -0.8 -13.4 -6.1 -2.7 -10.6 -12.7 -11.3 5.4 -7.4 -7.8 -7.3 1.0 -7.2 -9.5 -8.8

Mali 2001 Mali 2012.5 NA -1.0 2.9 2.5 NA -14.6 -8.9 -8.9 NA -20.3 -2.8 -3.4 2.2 -10.7 -3.1 -2.6

Mozambique 2003 Mozambique 2011 2.8 -0.7 -3.6 -2.4 -20.5 -1.9 -0.8 1.0 NA -1.5 -8.3 -7.6 -10.1 -2.1 -6.3 -4.6

Niger 1998 Niger 2012 NA -11.0 -7.3 -6.1 NA -5.1 -2.9 -2.6 NA NA -2.4 -2.4 NA -6.0 -2.6 -2.3

Nigeria 2003 Nigeria 2013 -19.2 -5.4 -7.8 -5.4 16.4 -11.2 -15.8 -12.6 -29.2 -13.6 -7.8 -7.7 -5.0 -9.6 -7.8 -5.8

Rwanda 2000 Rwanda 2010 NA 8.7 -6.2 -5.8 NA -4.1 2.2 1.0 NA -8.2 -2.9 -4.6 NA -6.1 -2.3 -4.1

Tanzania 1999 Tanzania 2010 NA -3.5 0.1 -2.6 -7.5 6.6 5.5 4.9 NA -0.5 -7.1 -7.5 2.9 3.6 -6.0 -6.0

Uganda 2000.5 Uganda 2011 NA NA -17.3 -18.2 NA NA -8.3 -8.7 NA NA -9.0 -9.7 NA -41.5 -9.4 -10.6

Zambia 2001.5 Zambia 2013.5 NA 6.6 -2.6 -2.1 NA -9.3 -5.0 -6.6 NA 1.4 -12.9 -12.5 NA -3.7 -10.8 -10.3

Zimbabwe 1999 Zimbabwe 2010.5 NA -4.1 -1.5 -3.2 NA 4.2 1.1 2.1 NA -1.0 -1.3 -1.6 -1.8 1.4 -1.0 -0.7

Bangladesh 2004 Bangladesh 2014 NA -12.4 -11.5 -13.5 -10.4 -8.3 -17.9 -13.5 -8.3 -6.8 -12.5 -13.7 -6.9 -6.3 -13.6 -14.2

Cambodia 2000 Cambodia 2014 11.1 0.4 4.7 -0.1 NA -14.1 -10.5 -15.1 NA -15.6 -11.8 -12.9 NA -12.2 -11.4 -13.1

Nepal 2001 Nepal 2011 NA NA NA -14.5 NA -10.4 -11.8 -14.9 NA -7.0 -14.7 -16.4 NA -6.9 -14.5 -16.7

Philippines 2003 Philippines 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Continued
32

Table 3.6—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA 1.0 NA -0.2 NA 6.7 14.3 7.2 NA 10.2 -3.1 2.4 2.1 6.4 0.5 2.5

Colombia 2000 Colombia 2010 -3.1 1.6 -7.7 -3.6 -1.5 -8.1 -2.4 -4.0 -6.5 -2.8 -10.0 -7.3 -2.9 -3.5 -7.2 -5.0

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 2.3 -6.9 -5.5 -2.9 -4.1 -4.5 -2.6 -3.9 -1.1 -6.6 -9.8 -6.6 -0.3 -5.9 -6.3 -4.2

Peru 2000 Peru 2012 -3.3 -10.0 -15.2 -9.9 -4.6 -5.9 -9.3 -9.5 -5.1 -3.8 -11.8 -12.7 -2.3 -5.7 -11.8 -11.0

Egypt 2000 Egypt 2014 4.4 3.6 0.3 3.7 4.0 1.4 -4.8 2.0 -3.5 -3.2 -4.8 -4.3 0.6 -1.3 -4.4 -1.4

Jordan 2002 Jordan 2012 -4.2 -3.9 8.3 -1.4 -4.0 -2.3 -3.1 -3.0 -2.7 -6.0 -8.7 -7.1 -4.5 -3.6 -2.0 -3.8

Pooled Average -2.8 -6.8 -3.9 -4.5 -0.5 -2.9 -4.2 -2.9 -7.2 -7.3 -4.5 -5.4 -2.8 -5.7 -4.4 -4.7Note: NA indicates too few cases to calculate decadal change.
33 

Underweight 

Levels 

On average across the surveys, being underweight is less prevalent than stunting (see Figure 3.9, left panel). 

Urban children in large cities who are extremely poor are roughly seven times more likely to be underweight 

than their non-poor counterparts; urban children in other urban areas are roughly five times more likely to 

be underweight than their non-poor counterparts; and in rural areas, they are roughly four times more likely. 

Among children in extreme poverty, being underweight is least prevalent in large cities (7%) and other 

urban areas (10%), and is highest in rural areas (15%). 

Three countries have 20% or more underweight children under age 5 in large cities: Nigeria (29%), 

Bangladesh (26%) and Burkina Faso (23%). In all three countries, the percent underweight among the 

extremely poor large city children is more than triple the cross-country average for that group of children 

(Table 3.7). These three countries also have the highest percentage of severely underweight for that group 

of children (Table 3.7). 

Decadal change 

On average across the surveys, there was little decadal change in the prevalence of being underweight 

among children under age 5 (see Figure 3.9, right panel). In fourteen countries, the percent underweight fell 

among the extremely poor children in large cities. However, in the remaining nine countries, the percent 

underweight rose, with the greatest increase occurring in Nigeria (+14% per decade) (see Table 3.8). It is 

interesting to note that in this country, the percent underweight decreased by about 10 percentage points for 

non-poor children of the large cities. 

Figure 3.9. Pooled average prevalence of being underweight among children under age 5 (left panel) 

and pooled average decadal change in coverage (right panel), by poverty according to level of 

urbanicity 

1.2 2.0 3.8 0.9 6.5 4.5 5.4 9.9 15.4

Large cities Other urban areas Rural areas

Percentage

Underweight

Not poor Moderately poor Extremely poor

-1.0 -0.1 -1.7 -0.2 -1.4 -1.4 -0.8 -1.7 -1.4

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in underweight

Not poor Moderately poor Extremely poor
34

Table 3.7. Underweight by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * 15.6 16.7 15.9 * 18.4 18.8 18.6 * 31.7 35.7 35.6 (20.5) 22.8 33.7 33.1 Burkina Faso 2010 (18.3) 12.7 22.7 20.0 * 15.4 18.2 17.4 * 26.3 27.2 27.1 12.6 20.6 26.2 25.7

Cameroon 2004 1.7 3.1 6.6 4.3 7.4 8.2 17.1 13.7 * 8.5 19.8 18.5 4.5 6.7 18.1 15.1Cameroon 2011 (3.8) 3.4 1.9 2.5 (1.9) 3.7 11.0 9.3 (8.3) 10.4 21.4 20.5 4.4 5.4 16.5 14.6

Cote D’Ivoire 1998-99 (5.5) 9.7 6.8 7.5 * 14.3 14.4 14.1 * 16.9 22.1 21.4 5.3 14.0 19.0 17.9Cote D’Ivoire 2011-12 * 12.2 8.1 9.8 (15.8) 5.8 13.4 12.0 * 21.4 16.3 16.6 14.2 13.6 14.9 14.7

Ethiopia 2000 (5.4) 11.1 12.8 11.8 0.0 27.7 31.8 30.9 * (31.5) 42.3 42.2 2.4 25.4 41.1 40.7Ethiopia 2011 * (2.7) 7.6 6.8 * 8.9 19.0 18.3 * (7.2) 30.6 30.5 (11.9) 7.5 29.1 28.8

Ghana 2003 * 6.2 8.5 8.2 * 12.9 16.8 15.9 * 16.4 21.1 20.6 * 12.9 18.6 17.8Ghana 2014 * 6.3 10.3 8.9 * 7.5 8.7 8.2 (3.8) 13.6 12.9 12.7 4.6 9.5 11.5 10.8

Guinea 1999 * 13.8 15.0 14.9 * 11.9 14.0 13.6 * 14.2 21.6 21.1 * 13.6 19.7 19.1Guinea 2012 * 8.7 9.9 9.5 * 6.7 12.2 10.6 * 12.1 21.2 20.6 (2.4) 9.7 19.0 18.0

Kenya 2003 3.3 3.1 8.8 6.2 0.0 10.1 15.0 12.8 6.8 9.9 17.8 16.9 4.0 8.5 17.1 15.5Kenya 2014 2.2 2.6 5.5 4.5 1.2 4.8 9.6 7.9 3.4 6.1 13.3 12.7 2.1 4.7 11.9 10.6

Mali 2001 11.9 11.5 11.4 11.5 * 13.0 24.1 21.6 21.7 32.4 33.0 32.9 16.7 19.8 30.7 29.0Mali 2012-13 * 19.5 18.0 17.8 * 12.3 15.9 15.7 * 18.3 28.0 27.5 11.1 17.2 26.1 25.4

Mozambique 2003 0.0 7.0 6.3 6.2 (8.1) 5.9 15.3 13.1 * 16.1 23.4 23.0 4.2 9.6 21.0 19.7Mozambique 2011 (7.7) 6.3 5.5 5.8 (4.4) 6.8 10.9 10.4 * 8.5 17.0 16.8 5.9 7.3 15.4 14.9

Niger 1998 * 22.5 26.4 24.8 * 25.5 30.3 29.2 * (22.7) 47.7 47.4 * 23.7 45.2 44.2Niger 2012 * 8.3 15.4 14.2 * 17.5 30.6 29.1 * * 38.1 38.1 (5.4) 16.0 36.6 36.2

Nigeria 2003 14.3 14.7 18.4 16.7 7.4 19.4 23.9 21.8 (29.6) 24.5 31.4 29.9 14.0 19.9 26.9 24.4Nigeria 2013 4.4 21.3 31.9 28.8 35.4 18.2 20.7 20.3 18.5 21.2 33.7 32.3 18.5 20.0 30.5 28.8

Rwanda 2000 * 6.1 10.6 10.1 * 17.2 12.1 13.3 * 20.1 21.1 21.0 * 18.8 19.8 19.7Rwanda 2010 (9.5) 4.2 4.5 4.8 * (3.0) 10.1 8.8 1.5 7.3 13.1 12.0 3.4 6.7 12.5 11.4

Tanzania 1999 * 15.6 (19.8) 17.2 (19.8) 6.9 18.8 14.6 * 21.8 26.6 26.4 13.6 12.3 25.7 24.4Tanzania 2010 * 13.1 12.8 11.9 3.7 7.8 14.5 11.5 8.7 9.7 17.4 16.6 4.8 9.7 16.9 15.6

Uganda 2000-01 * * 8.8 8.8 * * 9.7 9.6 * * 19.1 19.1 * (13.1) 18.1 18.1Uganda 2011 * (11.1) 4.3 6.0 * (12.7) 5.6 7.1 * (6.6) 15.0 14.8 * 9.5 14.0 13.7

Zambia 2001-02 * 10.0 18.9 17.3 * 14.6 22.3 20.1 * 16.7 24.3 24.1 * 14.3 23.5 22.6Zambia 2013-14 0.0 10.4 11.5 10.7 6.1 12.3 15.0 13.8 (3.0) 15.2 15.8 15.7 4.3 12.4 15.2 14.7

Zimbabwe 1999 * 2.8 7.8 5.1 * 5.6 5.0 5.4 * 7.8 12.1 11.5 (2.5) 5.7 10.9 9.5Zimbabwe 2010-11 0.0 7.6 10.0 8.4 6.4 7.3 9.2 8.0 5.8 7.7 10.5 9.8 5.3 7.6 10.4 9.4

Bangladesh 2004 * (36.3) 37.3 37.1 18.6 22.2 44.9 37.3 31.5 29.7 44.8 43.6 24.6 27.2 44.7 42.4Bangladesh 2014 (16.8) 19.3 30.5 25.7 (18.4) 16.9 29.7 26.5 23.1 25.5 37.2 34.8 21.5 22.7 35.5 32.6

Cambodia 2000 * 10.8 23.3 16.9 * 24.5 36.0 35.2 * 33.2 40.8 40.3 * 28.0 40.1 39.1Cambodia 2014 (14.7) 4.7 22.7 12.1 7.6 17.3 19.8 17.1 17.8 23.9 26.5 25.7 15.2 20.0 26.0 24.1

Nepal 2001 * * (21.3) 19.7 * 16.7 31.1 29.1 * 19.8 44.7 44.0 * 18.9 43.8 42.9Nepal 2011 * * * 5.9 * 12.0 23.2 20.1 9.7 15.9 33.1 29.8 9.9 14.6 32.2 28.5

Philippines 2003 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Philippines 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Continued
35

Table 3.7—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 0.4 (4.1) 1.0 * 3.3 5.7 3.6 * 4.1 2.2 2.5 0.0 2.1 2.7 2.3 Armenia 2010 1.0 4.3 * 2.2 3.1 3.5 (7.3) 3.5 6.2 7.5 10.5 7.5 3.2 5.8 8.6 4.7

Colombia 2000 2.9 3.2 6.0 3.5 2.1 5.3 7.3 4.3 3.8 4.2 8.0 6.1 2.7 4.3 7.4 4.6Colombia 2010 1.6 3.6 5.4 2.5 1.9 3.1 6.3 3.2 2.0 3.5 6.2 4.7 1.8 3.4 6.1 3.4

Dominican 

Republic 

2002 1.9 3.3 4.2 2.9 2.0 3.9 5.7 3.9 3.1 3.3 8.0 5.2 2.2 3.4 6.2 3.9

Dominican 

Republic 

2013 0.0 3.3 5.2 3.0 1.9 3.2 6.0 3.6 3.3 2.0 3.9 3.1 1.6 2.9 5.1 3.3

Peru 2000 1.2 1.7 2.9 2.0 0.2 1.5 4.7 3.3 0.2 3.9 8.4 8.1 1.1 2.0 6.7 4.9Peru 2012 0.6 2.8 1.5 1.4 1.1 2.2 3.7 2.6 2.4 1.8 6.5 5.8 0.9 2.3 5.1 3.4

Egypt 2000 2.5 2.4 3.4 2.6 3.2 3.2 3.1 3.2 2.9 4.1 5.4 4.2 2.9 3.7 5.0 3.7Egypt 2014 4.2 4.4 4.4 4.3 6.0 6.0 8.4 6.4 5.5 4.7 6.3 5.4 5.4 4.9 6.5 5.5

Jordan 2002 1.6 2.7 4.4 2.9 2.8 2.5 3.3 2.9 3.9 3.3 7.9 5.4 2.8 2.7 4.8 3.5Jordan 2012 3.7 2.3 6.1 3.7 2.2 2.5 4.3 2.9 2.3 1.2 3.1 2.0 2.8 2.2 4.6 3.0

Pooled Average 1.2 0.9 6.5 1.8 2.0 4.5 9.9 6.4 3.8 5.4 15.4 12.9 2.4 4.8 13.4 8.9
36

Table 3.8. Decadal change in underweight by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA -4.1 8.6 5.9 NA -4.3 -0.9 -1.7 NA -7.7 -12.1 -12.1 -11.3 -3.1 -10.7 -10.6

Cameroon 2004 Cameroon 2011 3.0 0.4 -6.7 -2.6 -7.9 -6.4 -8.7 -6.3 NA 2.7 2.3 2.9 -0.1 -1.9 -2.3 -0.7

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA 1.9 1.0 1.8 NA -6.5 -0.8 -1.6 NA 3.5 -4.5 -3.7 6.8 -0.3 -3.2 -2.5

Ethiopia 2000 Ethiopia 2011 NA -7.6 -4.7 -4.5 NA -17.1 -11.6 -11.5 NA -22.1 -10.6 -10.6 8.6 -16.3 -10.9 -10.8

Ghana 2003 Ghana 2014 NA 0.1 1.6 0.6 NA -4.9 -7.4 -7.0 NA -2.5 -7.5 -7.2 NA -3.1 -6.5 -6.4

Guinea 1999 Guinea 2012 NA -3.9 -3.9 -4.2 NA -4.0 -1.4 -2.3 NA -1.6 -0.3 -0.4 NA -3.0 -0.5 -0.8

Kenya 2003 Kenya 2014 -1.0 -0.5 -3.0 -1.5 1.1 -4.8 -4.9 -4.5 -3.1 -3.5 -4.1 -3.8 -1.7 -3.5 -4.7 -4.5

Mali 2001 Mali 2012.5 NA 7.0 5.7 5.5 NA -0.6 -7.1 -5.1 NA -12.3 -4.3 -4.7 -4.9 -2.3 -4.0 -3.1

Mozambique 2003 Mozambique 2011 9.6 -0.9 -1.0 -0.5 -4.6 1.1 -5.5 -3.4 NA -9.5 -8.0 -7.8 2.1 -2.9 -7.0 -6.0

Niger 1998 Niger 2012 NA -10.1 -7.9 -7.6 NA -5.7 0.2 -0.1 NA NA -6.9 -6.6 NA -5.5 -6.1 -5.7

Nigeria 2003 Nigeria 2013 -9.9 6.6 13.5 12.1 28.0 -1.2 -3.2 -1.5 -11.1 -3.3 2.3 2.4 4.5 0.1 3.6 4.4

Rwanda 2000 Rwanda 2010 NA -1.9 -6.1 -5.3 NA -14.2 -2.0 -4.5 NA -12.8 -8.0 -9.0 NA -12.1 -7.3 -8.3

Tanzania 1999 Tanzania 2010 NA -2.3 -6.4 -4.8 -14.6 0.8 -3.9 -2.8 NA -11.0 -8.4 -8.9 -8.0 -2.4 -8.0 -8.0

Uganda 2000.5 Uganda 2011 NA NA -4.3 -2.7 NA NA -3.9 -2.4 NA NA -3.9 -4.1 NA -3.4 -3.9 -4.2

Zambia 2001.5 Zambia 2013.5 NA 0.3 -6.2 -5.5 NA -1.9 -6.1 -5.3 NA -1.3 -7.1 -7.0 NA -1.6 -6.9 -6.6

Zimbabwe 1999 Zimbabwe 2010.5 NA 4.2 1.9 2.9 NA 1.5 3.7 2.3 NA -0.1 -1.4 -1.5 2.4 1.7 -0.4 -0.1

Bangladesh 2004 Bangladesh 2014 NA -17.0 -6.8 -11.4 -0.2 -5.3 -15.2 -10.8 -8.4 -4.2 -7.6 -8.8 -3.1 -4.5 -9.2 -9.8

Cambodia 2000 Cambodia 2014 10.5 -4.4 -0.4 -3.4 NA -5.1 -11.6 -12.9 NA -6.6 -10.2 -10.4 NA -5.7 -10.1 -10.7

Nepal 2001 Nepal 2011 NA NA NA -13.8 NA -4.7 -7.9 -9.0 NA -3.9 -11.6 -14.2 NA -4.3 -11.6 -14.4

Philippines 2003 Philippines 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Continued
37

Table 3.8—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA 3.9 NA 1.2 NA 0.2 1.6 -0.1 NA 3.4 8.3 5.0 3.2 3.7 5.9 2.4

Colombia 2000 Colombia 2010 -1.3 0.4 -0.6 -1.0 -0.2 -2.2 -1.0 -1.1 -1.8 -0.7 -1.8 -1.4 -0.9 -0.9 -1.3 -1.2

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 -1.7 0.0 0.9 0.1 -0.1 -0.6 0.3 -0.3 0.2 -1.2 -3.7 -1.9 -0.5 -0.5 -1.0 -0.5

Peru 2000 Peru 2012 -0.5 0.9 -1.2 -0.5 0.8 0.6 -0.8 -0.6 1.8 -1.8 -1.6 -1.9 -0.2 0.3 -1.3 -1.3

Egypt 2000 Egypt 2014 1.2 1.4 0.7 1.2 2.0 2.0 3.8 2.3 1.9 0.4 0.6 0.9 1.8 0.9 1.1 1.3

Jordan 2002 Jordan 2012 2.1 -0.4 1.7 0.8 -0.6 0.0 1.0 0.0 -1.6 -2.1 -4.8 -3.4 0.0 -0.5 -0.2 -0.5

Pooled Average -1.0 -0.1 -1.7 -0.8 -0.2 -1.4 -1.4 -1.5 -0.8 -1.7 -1.4 -1.5 0.0 -0.9 -1.3 -0.8Note: NA indicates too few cases to calculate decadal change.
38 

Any anemia among children age 6-59 months (<11.0g/dl) 

Levels 

Within each area of residence, the pooled average anemia (<11.0g/dl) prevalence is closely associated with 

household poverty (see Figure 3.10, left panel). In large cities, more than half (52%) of children in 

extremely poor households were anemic, compared with 38% in moderately poor households and 31% in 

not poor households. The anemia levels and differentials by poverty are similar in other urban areas, and 

are slightly wider in rural areas, where 62% of extremely poor children are anemic. 

In the 18 latest surveys with anemia measurement, over 25% of children in all countries are anemic (Table 

3.9). In four countries, more than 75% of children are anemic: Burkina Faso (88%), Mali (82%), Guinea 

(78%), and Cote d’Ivoire (76%). The extremely poor children of large cities fare little better. For those four 

countries, the percent anemic for that group of children ranges between 68% and 74%. 

Decadal change 

On average across the pooled surveys, anemia levels declined in all subgroups (see Figure 3.10, right panel). 

The decadal declines were lowest for non-poor children in other urban and rural areas (1 and 3 percentage 

point declines, respectively), and highest for extremely poor children in each area of residence (8 percentage 

point decline in the three areas). Table 3.10 shows these patterns in the 26 study countries. 

Figure 3.10. Pooled average prevalence of anemia (<11.0g/dl) among children age 6-59 months (left 

panel) and pooled average decadal change in coverage (right panel), by poverty according to level 

of urbanicity 

30.7 27.2 32.1 38.1 36.4 41.8

51.7 51.4

61.6

Large cities Other urban areas Rural areas

Percentage

Children's anemia

Not poor Moderately poor Extremely poor

-6.4 -4.1 -1.1 -2.5 -7.9 -4.6 -8.0 -8.1 -8.1

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in children's 

anemia

Not poor Moderately poor Extremely poor
39

Table 3.9. Prevalence of anemia (<11.0g/dl) among children age 6-59 months by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * * (75.3) 71.2 * (76.8) 81.5 80.2 * (98.7) 93.6 93.7 * 80.2 92.2 91.6 Burkina Faso 2010 * 70.3 74.4 72.7 * 76.4 81.2 80.3 * 87.2 90.1 90.0 75.9 81.0 88.6 87.9

Cameroon 2004 * 60.1 62.7 61.4 (41.3) 61.0 68.0 64.6 * 72.3 73.9 73.6 48.1 63.7 71.7 69.4Cameroon 2011 (58.1) 53.1 59.0 57.1 (25.5) 53.5 59.1 57.2 (56.2) 68.1 64.3 64.4 48.2 57.4 62.3 61.3

Cote D’Ivoire 1998-99 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NACote D’Ivoire 2011-12 * (67.4) 68.0 66.4 (58.6) 62.8 71.9 69.2 * 76.5 80.3 80.0 60.9 69.3 77.3 75.7

Ethiopia 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Ethiopia 2011 * * 33.6 33.1 * 18.9 37.2 36.0 * (13.6) 46.0 45.9 * 19.4 44.9 44.7Ghana 2003 * 61.3 66.6 65.3 * 64.1 73.5 71.6 * 78.4 80.6 80.4 * 70.2 77.5 76.5Ghana 2014 * 48.0 56.9 54.2 * 63.7 66.6 65.7 (52.2) 70.0 74.5 73.0 55.4 60.5 69.1 66.8

Guinea 1999 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Guinea 2012 * (63.2) 72.8 71.2 * 63.6 72.4 70.7 * 77.6 79.9 79.7 (72.2) 70.1 78.4 77.6Kenya 2003 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAKenya 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAMali 2001 * 66.1 76.5 71.6 * (67.1) 84.2 79.4 * 81.3 85.0 84.7 (59.2) 73.7 84.4 82.7Mali 2012-13 * 61.6 70.6 68.8 * 35.9 70.3 66.1 * 74.9 85.5 85.1 (77.0) 63.3 83.1 81.9Mozambique 2003 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAMozambique 2011 * 57.0 50.5 52.8 * 55.3 62.5 61.5 * 78.4 72.2 72.4 (50.9) 63.9 69.6 69.2

Niger 1998 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Niger 2012 * (66.6) 79.7 78.3 * 49.6 65.7 64.0 * * 74.4 74.3 (58.8) 56.8 74.0 73.7Nigeria 2003 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NANigeria 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NARwanda 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NARwanda 2010 (41.9) 33.4 42.5 40.0 * (38.7) 32.7 33.5 27.1 32.8 40.1 38.8 30.1 33.2 39.9 38.6Tanzania 1999 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NATanzania 2010 * 68.9 70.0 69.0 64.4 56.4 59.4 58.6 52.7 50.6 60.1 59.3 59.6 56.0 60.4 59.8

Uganda 2000-01 * * 55.9 56.1 * * 62.7 62.7 * * 73.1 73.0 * * 71.9 71.8Uganda 2011 * (27.1) 42.1 39.1 * (40.4) 38.5 38.4 * (40.8) 52.3 52.0 * 36.6 51.0 50.3

Zambia 2001-02 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAZambia 2013-14 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAZimbabwe 1999 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAZimbabwe 2010-11 * 58.3 59.4 58.1 62.1 60.8 61.3 61.2 60.5 53.8 58.2 57.6 59.4 56.4 58.5 58.2Bangladesh 2004 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NABangladesh 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NACambodia 2000 * * * (37.0) * * 63.4 62.5 * 61.5 64.7 64.5 * 55.4 64.1 63.5Cambodia 2014 (45.6) 38.3 38.3 40.0 39.3 43.2 49.9 46.1 41.6 57.4 59.9 58.7 42.0 52.9 58.8 56.6Nepal 2001 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NANepal 2011 * * * (27.9) * 32.7 54.0 47.5 43.0 39.0 48.2 46.8 37.8 38.3 48.3 46.4

Philippines 2003 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Philippines 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Continued
40

Table 3.9—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 13.0 (11.4) 12.9 * 18.3 22.4 19.0 * 33.8 32.5 32.8 (18.1) 18.5 29.7 23.9 Armenia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAColombia 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAColombia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NADominican 

Republic 

2002 

NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

Dominican 

Republic 

2013 

NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

Peru 2000 44.0 42.5 51.1 46.1 (26.5) 54.5 50.9 49.1 * 41.9 54.3 53.4 42.7 44.1 53.1 49.6Peru 2012 19.5 29.1 25.8 23.5 23.1 31.8 36.6 31.6 38.3 41.1 40.5 40.6 21.8 32.9 37.9 32.8

Egypt 2000 19.3 23.3 21.1 20.3 25.1 33.8 30.9 27.9 31.5 33.0 37.8 34.5 26.1 31.6 35.9 30.5Egypt 2014 24.3 20.3 (12.5) 21.6 24.0 23.2 24.6 23.9 28.1 28.8 32.0 29.5 26.5 26.8 29.9 27.4

Jordan 2002 (32.0) 27.7 (31.5) 29.7 31.1 36.6 31.0 33.3 37.7 42.2 38.7 39.7 32.7 35.5 33.7 34.2Jordan 2012 31.9 31.1 34.2 32.1 29.4 30.6 35.9 31.9 29.4 33.1 37.1 33.2 30.2 31.3 35.6 32.2

Pooled Average 30.7 38.1 51.7 42.3 27.2 36.4 51.4 41.7 32.1 41.8 61.6 57.0 30.0 39.4 59.5 51.8
41

Table 3.10. Decadal change in prevalence of anemia (<11.0g/dl) among children age 6-59 months by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA NA -1.3 2.1 NA -0.6 -0.4 0.1 NA -16.4 -5.0 -5.3 NA 1.1 -5.1 -5.3

Cameroon 2004 Cameroon 2011 NA -10.0 -5.3 -6.1 -22.6 -10.7 -12.7 -10.6 NA -6.0 -13.7 -13.1 0.1 -9.0 -13.4 -11.6

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA 51.8 52.3 51.1 45.1 48.3 55.3 53.2 NA 58.8 61.8 61.5 46.8 53.3 59.5 58.2

Ethiopia 2000 Ethiopia 2011 NA NA 30.5 30.1 NA 17.2 33.8 32.7 NA 12.4 41.8 41.7 NA 17.6 40.8 40.6

Ghana 2003 Ghana 2014 NA -12.1 -8.8 -10.1 NA -0.4 -6.3 -5.4 NA -7.6 -5.5 -6.7 NA -8.8 -7.6 -8.8

Guinea 1999 Guinea 2012 NA 48.6 56.0 54.8 NA 48.9 55.7 54.4 NA 59.7 61.5 61.3 55.5 53.9 60.3 59.7

Kenya 2003 Kenya 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAMali 2001 Mali 2012.5 NA -3.9 -5.1 -2.4 NA -27.1 -12.1 -11.6 NA -5.6 0.4 0.3 15.5 -9.0 -1.1 -0.7Mozambique 2003 Mozambique 2011 NA 71.3 63.1 66.0 NA 69.1 78.1 76.9 NA 98.0 90.3 90.5 63.6 79.9 87.0 86.5

Niger 1998 Niger 2012 NA 47.6 56.9 55.9 NA 35.4 46.9 45.7 NA NA 53.1 53.1 42.0 40.6 52.9 52.6

Nigeria 2003 Nigeria 2013 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

Rwanda 2000 Rwanda 2010 41.9 33.4 42.5 40.0 NA 38.7 32.7 33.5 27.1 32.8 40.1 38.8 30.1 33.2 39.9 38.6

Tanzania 1999 Tanzania 2010 NA 62.6 63.6 62.7 58.5 51.3 54.0 53.3 47.9 46.0 54.6 53.9 54.2 50.9 54.9 54.4

Uganda 2000.5 Uganda 2011 NA NA -13.1 -16.2 NA NA -23.0 -23.1 NA NA -19.8 -20.0 NA NA -19.9 -20.5

Zambia 2001.5 Zambia 2013.5 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAZimbabwe 1999 Zimbabwe 2010.5 NA 50.7 51.7 50.5 54.0 52.9 53.3 53.2 52.6 46.8 50.6 50.1 51.7 49.0 50.9 50.6Bangladesh 2004 Bangladesh 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NACambodia 2000 Cambodia 2014 32.6 NA NA 2.1 28.1 NA -9.6 -11.7 NA -2.9 -3.4 -4.1 NA -1.8 -3.8 -4.9Nepal 2001 Nepal 2011 NA NA NA 27.9 NA 32.7 54.0 47.5 43.0 39.0 48.2 46.8 37.8 38.3 48.3 46.4

Philippines 2003 Philippines 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Continued
42

Table 3.10—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA -13.0 -11.4 -12.9 NA -18.3 -22.4 -19.0 NA -33.8 -32.5 -32.8 -18.1 -18.5 -29.7 -23.9

Colombia 2000 Colombia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 

NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 

Peru 2000 Peru 2012 -20.4 -11.2 -21.1 -18.8 -2.8 -18.9 -11.9 -14.6 NA -0.7 -11.5 -10.7 -17.4 -9.3 -12.7 -14.0

Egypt 2000 Egypt 2014 3.6 -2.1 -6.1 0.9 -0.8 -7.6 -4.5 -2.9 -2.4 -3.0 -4.1 -3.6 0.3 -3.4 -4.3 -2.2

Jordan 2002 Jordan 2012 -0.1 3.4 2.7 2.4 -1.7 -6.0 4.9 -1.4 -8.3 -9.1 -1.6 -6.5 -2.5 -4.2 1.9 -2.0

Pooled Average -6.4 -4.1 -8.0 -6.1 -1.1 -7.9 -8.1 -6.5 -2.5 -4.6 -8.1 -7.4 -3.3 -5.4 -8.4 -7.3Note: NA indicates too few cases to calculate decadal change.
43 

Prevalence of illness in the two weeks preceding the survey 

Illness prevalence can fluctuate seasonally and annually. This fluctuation makes comparisons across 

countries problematic. Differences by levels of urbanicity and poverty are less subject to this fluctuation 

than the estimation of trends, especially for individual countries. 

Fever: The prevalence of fever in the latest surveys varies little across levels of poverty and level of 

urbanicity (Figure 3.11). Within the large cities, the average for all levels of poverty is 18%. The highest 

average prevalence is only 4 percentage points greater among the extremely poor of rural areas. 

Diarrhea: The average prevalence of diarrhea in children under age 5 increases with the level of poverty 

by 3 to 5 percentage points (Figure 3.11). There is very little variation when comparing within poverty 

levels across the areas. 

Acute Respiratory Illness (ARI): Similar to fever, the average prevalence of ARI varies little across levels 

of poverty and level of urbanicity (Figure 3.11), with the lowest among the moderately poor in large cities 

(6%) and the highest among the extremely poor in rural areas (9%). 

Figure 3.11. Pooled average prevalence of fever, diarrhea, and symptoms of ARI among children 

under age 5, by poverty according to level of urbanicity 

18.2 18.4 18.3 18.8 18.9 21.1 19.0 19.9 22.2

Large cities Other urban areas Rural areas

Percentage

Fever prevalence

Not poor Moderately poor Extremely poor

18.2 18.4 18.3 18.8 18.9 21.1 19.0 19.9 22.2

Large cities Other urban areas Rural areas

Percentage

Diarrhea prevalence

Not poor Moderately poor Extremely poor

18.2 18.4 18.3 18.8 18.9 21.1 19.0 19.9 22.2

Large cities Other urban areas Rural areas

Percentage

Symptoms of ARI prevalence

Not poor Moderately poor Extremely poor
44 

3.4. Use of Children’s Health Services 

The following section describes levels and trends in the use of children’s health services in the order of 

approximate use by the age of the child. Also included in this section are the results of examining levels 

and trends in birth spacing, which are critical to the survival and nutritional status of children under age 5. 

Antenatal and delivery care 

Four or more ANC visits 

Levels 

Figure 3.12 (left panel) shows the pooled average percentage of women with four or more antenatal care 

(ANC) visits for their most recent birth, disaggregated by level of urbanicity and poverty level. Across the 

surveys, the coverage of four or more ANC visits within large cities decreases incrementally with increasing 

poverty. On average, extremely poor women in large cities have lower coverage (58%) than their less poor 

(77%) and not poor (88%) urban counterparts. The poverty differentials are similar in other urban areas, 

but are substantially wider in rural areas, where the non-poor have 71% coverage, compared with 23% 

coverage among the extremely poor. 

Comparing ANC coverage across places of residence within the extremely poor, coverage among urban 

women—regardless of whether they live in a large city or other urban area—is more than two times higher 

than coverage among extremely poor rural women. 

Only in four countries—Rwanda, Niger, Bangladesh, and Burkina Faso—do less than 50% of extremely 

poor women in large cities have less than 4 or more ANC visits (Table 3.11). In ten countries, the percentage 

exceeds 80%. 

Decadal change 

Overall, pooled decadal improvements in ANC coverage were concentrated in rural areas, with the smallest 

improvements in large cities (see Figure 3.12, right panel). Within large cities and other urban areas, the 

decadal increases in coverage were roughly similar across poverty levels, so that the underlying disparities 

by poverty remain. In six countries, the rates of ANC coverage among extremely poor women in large cities 

have declined, with the largest declines occurring in Zambia and Tanzania (-27 and -21%, respectively). In 

ten countries, the decadal increase in coverage for this group was more than 10 percentage points (see Table 

3.12). 

In rural areas, the pooled average decadal increases in ANC coverage were concentrated in the non-poor 

and moderately poor groups; this would increase the gaps in coverage by poverty level in rural areas. 
45 

Figure 3.12. Pooled average coverage of four or more ANC visits (left panel) and pooled average 

decadal change in coverage (right panel), by poverty according to level of urbanicity 

88.7 86.5

70.7 77.2 73.5

48.7

58.2 52.1

23.4

Large cities Other urban areas Rural areas

Percentage

4+ ANC visits

Not poor Moderately poor Extremely poor

5.6 9.8

21.9

5.3 10.0

22.0

7.2 8.9 13.3

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in 4+ ANC visits

Not poor Moderately poor Extremely poor
46

Table 3.11. Four or more ANC visits by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * 52.0 31.6 39.2 * 31.4 27.7 28.6 * 25.0 14.7 15.0 (41.0) 34.9 16.4 17.6 Burkina Faso 2010 73.6 62.6 47.8 54.4 (67.4) 40.6 36.8 38.2 * 45.0 30.2 31.0 69.0 48.2 31.8 33.7

Cameroon 2004 96.5 88.2 82.0 86.7 79.2 77.5 61.7 68.3 * 65.2 45.9 48.4 86.0 77.9 52.7 60.4Cameroon 2011 92.8 86.2 86.0 86.6 84.6 80.9 66.5 70.0 77.1 66.6 48.5 50.2 86.9 79.2 57.8 62.2

Cote D’Ivoire 1998-99 84.1 66.3 47.1 58.4 (63.2) 68.8 39.0 47.4 * 46.1 27.1 30.0 80.8 57.2 31.2 37.8Cote D’Ivoire 2011-12 87.4 74.1 67.9 71.7 85.8 60.1 48.7 53.7 * 50.3 31.0 32.9 84.4 60.6 39.2 44.2

Ethiopia 2000 (81.7) 71.6 71.0 72.0 (86.1) 54.5 34.9 38.2 * (22.9) 6.1 6.1 77.4 51.0 9.3 10.4Ethiopia 2011 * (86.7) 86.4 86.4 * 73.7 34.9 37.6 * (44.0) 14.3 14.4 (69.6) 68.3 18.2 19.1

Ghana 2003 * 85.0 89.4 88.2 * 85.9 78.2 80.3 * 69.0 59.8 61.0 * 77.8 67.5 69.4Ghana 2014 * 98.6 91.7 94.3 (100.0) 92.8 88.2 89.9 88.3 88.9 81.1 82.9 92.3 93.1 84.9 87.3

Guinea 1999 * 73.6 74.5 74.7 * 67.3 62.5 63.5 * 58.9 40.7 41.9 * 65.7 47.0 49.1Guinea 2012 * 88.6 80.8 82.8 (80.4) 76.6 68.3 70.5 * 71.6 47.0 48.5 80.0 77.8 53.8 56.6

Kenya 2003 80.5 75.0 64.1 71.0 (87.6) 70.3 55.6 62.3 (71.2) 63.2 46.2 48.6 78.4 67.4 48.0 52.3Kenya 2014 86.2 71.9 68.5 71.5 83.6 74.9 59.4 65.4 68.4 65.4 49.6 51.3 80.9 70.9 53.6 57.6

Mali 2001 76.6 74.1 61.6 68.8 * 60.4 40.9 46.8 (56.2) 33.4 19.8 21.0 72.4 55.5 24.7 29.9Mali 2012-13 (80.3) 80.6 68.8 71.4 (88.3) 81.2 56.9 61.3 * 57.3 33.5 34.6 79.1 69.0 38.8 41.2

Mozambique 2003 (83.6) 80.0 71.4 75.2 (82.3) 81.2 65.4 69.7 * 57.2 44.4 45.2 84.3 73.2 50.0 53.1Mozambique 2011 (65.4) 76.5 65.5 69.3 (80.7) 62.7 56.7 57.8 * 58.9 46.5 46.9 73.6 64.7 49.5 50.6

Niger 1998 * 50.9 30.7 37.2 * 40.4 31.9 34.0 * (16.2) 6.9 7.0 * 40.3 10.2 11.5Niger 2012 (78.4) 62.5 44.2 48.4 (69.6) 57.8 42.9 44.8 * 48.2 30.3 30.5 78.1 56.9 32.0 32.8

Nigeria 2003 88.0 83.9 77.5 80.9 (61.9) 61.1 45.1 51.4 (48.3) 48.8 27.7 32.4 68.2 61.9 40.0 47.4Nigeria 2013 84.3 83.0 69.4 73.1 81.1 83.0 72.4 75.0 66.9 57.8 35.3 38.2 72.3 71.9 46.8 51.1

Rwanda 2000 * 34.5 18.8 21.2 * 21.2 17.7 18.2 * 10.0 8.7 8.9 * 12.9 10.0 10.4Rwanda 2010 66.0 49.0 34.2 41.2 * 56.7 36.2 39.1 48.6 38.4 33.7 34.7 52.9 40.8 33.9 35.4

Tanzania 1999 * 96.1 (83.5) 89.5 (95.9) 83.2 84.4 84.3 * 89.4 64.6 65.3 (95.7) 87.5 67.5 69.9Tanzania 2010 * 60.3 60.2 62.1 61.7 56.0 46.2 51.2 41.6 49.4 38.0 39.2 59.8 54.1 39.7 42.8

Uganda 2000-01 * * 68.5 68.8 * * 63.7 63.9 * * 38.5 38.4 * (38.5) 41.9 41.9Uganda 2011 (61.5) 73.2 59.2 65.3 * 54.5 49.1 50.4 * 54.7 45.5 45.8 50.4 61.0 46.3 47.6

Zambia 2001-02 * 88.8 81.7 83.3 * 84.7 75.1 77.9 * 84.2 66.9 67.5 * 85.4 69.8 71.6Zambia 2013-14 (87.3) 56.1 49.7 53.2 65.6 59.4 55.9 57.5 (63.3) 57.9 55.1 55.2 69.7 58.0 54.6 55.5

Zimbabwe 1999 * 51.0 49.4 50.8 * 66.9 59.5 64.2 (67.0) 71.7 66.3 67.0 65.2 64.5 64.2 64.3Zimbabwe 2010-11 (76.6) 65.5 56.7 62.1 68.6 73.3 66.8 69.8 78.1 66.8 62.6 64.3 74.6 68.1 62.3 64.8

Bangladesh 2004 * (49.5) 21.9 27.7 77.6 53.4 22.1 34.9 40.5 23.7 9.7 11.3 62.2 35.9 11.8 15.9Bangladesh 2014 (66.5) 51.8 47.0 50.7 (74.0) 58.0 36.6 43.2 54.3 33.1 22.7 26.1 58.0 41.9 26.5 31.2

Cambodia 2000 * 69.5 38.8 54.8 * 11.1 14.0 13.8 * 9.5 6.3 6.6 * 19.1 7.7 8.9Cambodia 2014 92.4 94.3 75.9 88.4 90.3 85.8 78.4 82.6 90.1 82.4 70.7 73.9 90.7 84.6 71.3 75.6

Nepal 2001 * * (60.0) 67.2 * 60.5 41.5 44.9 * 45.2 10.7 11.8 * 51.7 12.7 14.3Nepal 2011 * (87.8) (73.3) 83.3 (95.2) 78.8 59.5 66.5 81.0 76.4 40.7 47.7 83.6 77.7 42.4 50.1

Philippines 2003 88.2 87.3 66.6 80.0 91.4 80.6 69.5 77.2 80.6 71.0 54.9 62.3 86.6 78.0 60.8 70.4Philippines 2013 94.6 93.0 87.7 90.8 89.3 92.5 80.4 85.5 90.2 86.4 77.8 81.3 91.0 89.9 80.1 84.3

Continued
47

Table 3.11—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 91.3 (87.0) 90.1 * 71.4 72.3 71.0 * 60.7 41.2 45.4 (77.4) 78.8 49.1 64.7 Armenia 2010 98.4 95.5 * 96.9 94.6 92.4 (93.6) 93.9 89.5 89.6 84.8 88.8 94.6 91.9 86.8 92.8

Colombia 2000 93.4 84.3 76.9 88.1 88.9 79.9 73.2 83.0 86.9 71.8 56.3 67.7 90.4 79.1 65.1 80.2Colombia 2010 94.5 88.7 84.6 92.2 93.2 88.5 83.7 90.2 88.5 86.7 75.2 81.4 93.3 88.1 79.1 88.6

Dominican 

Republic 

2002 95.8 92.4 91.6 93.9 97.0 93.5 93.8 94.9 95.3 93.3 88.4 92.1 95.9 92.9 90.7 93.5

Dominican 

Republic 

2013 93.8 94.1 96.0 94.6 97.0 95.4 95.2 95.9 98.0 96.2 93.1 95.6 96.1 95.2 94.9 95.4

Peru 2000 91.2 83.8 71.5 82.7 88.2 78.0 67.9 73.8 71.6 76.1 49.3 50.9 90.4 81.9 56.9 68.5Peru 2012 99.2 96.5 94.2 97.5 97.6 94.9 93.4 95.1 97.3 94.7 90.4 91.2 98.3 95.3 91.8 94.4

Egypt 2000 68.4 45.5 22.5 58.8 59.0 44.9 23.1 51.3 43.1 26.5 17.5 28.3 55.1 32.6 18.4 39.0Egypt 2014 95.2 85.9 85.6 90.7 91.7 84.7 75.8 86.4 88.8 80.7 70.6 80.5 90.5 82.0 72.1 82.8

Jordan 2002 96.2 92.9 94.0 94.1 95.3 90.8 88.9 91.3 96.4 86.7 81.0 86.4 95.7 90.6 87.7 90.9Jordan 2012 97.0 94.9 88.8 94.1 97.7 95.3 92.3 95.1 96.8 95.4 86.5 93.5 97.3 95.2 90.1 94.5

Pooled Average 88.7 77.2 58.2 69.7 86.5 73.5 52.1 62.0 70.7 48.7 23.4 25.9 82.9 63.9 29.8 36.4
48

Table 3.12. Decadal change in four or more ANC visits by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA 15.1 23.1 21.7 NA 13.1 13.0 13.7 NA 28.6 22.1 22.9 40.0 19.0 22.0 23.0

Cameroon 2004 Cameroon 2011 -5.3 -2.9 5.7 -0.1 7.7 4.9 6.9 2.4 NA 2.0 3.7 2.6 1.3 1.9 7.3 2.6

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 2.5 6.0 16.0 10.2 17.4 -6.7 7.5 4.8 NA 3.2 3.0 2.2 2.8 2.6 6.2 4.9

Ethiopia 2000 Ethiopia 2011 NA 13.7 14.0 13.1 NA 17.5 0.0 -0.5 NA 19.2 7.5 7.5 -7.1 15.7 8.1 7.9

Ghana 2003 Ghana 2014 NA 12.4 2.1 5.5 NA 6.3 9.1 8.7 NA 18.1 19.4 19.9 NA 13.9 15.8 16.3

Guinea 1999 Guinea 2012 NA 11.5 4.8 6.2 NA 7.2 4.5 5.4 NA 9.8 4.8 5.1 NA 9.3 5.2 5.8

Kenya 2003 Kenya 2014 5.2 -2.8 4.0 0.5 -3.6 4.2 3.5 2.8 -2.5 2.0 3.1 2.5 2.3 3.2 5.1 4.8

Mali 2001 Mali 2012.5 3.2 5.7 6.3 2.3 NA 18.1 13.9 12.6 NA 20.8 11.9 11.8 5.8 11.7 12.3 9.8

Mozambique 2003 Mozambique 2011 -22.8 -4.4 -7.4 -7.4 -2.0 -23.1 -10.9 -14.9 NA 2.1 2.6 2.1 -13.4 -10.6 -0.6 -3.1

Niger 1998 Niger 2012 NA 8.3 9.6 8.0 NA 12.4 7.9 7.7 NA 22.9 16.7 16.8 NA 11.9 15.6 15.2

Nigeria 2003 Nigeria 2013 -3.7 -0.9 -8.1 -7.8 19.2 21.9 27.3 23.6 18.6 9.0 7.6 5.8 4.1 10.0 6.8 3.7

Rwanda 2000 Rwanda 2010 NA 14.5 15.4 20.0 NA 35.5 18.5 20.9 NA 28.4 25.0 25.8 NA 27.9 23.9 25.0

Tanzania 1999 Tanzania 2010 NA -32.5 -21.2 -24.9 -31.1 -24.7 -34.7 -30.1 NA -36.4 -24.2 -23.7 -32.6 -30.4 -25.3 -24.6

Uganda 2000.5 Uganda 2011 NA NA -8.9 -3.3 NA NA -13.9 -12.9 NA NA 6.7 7.0 NA 21.4 4.2 5.4

Zambia 2001.5 Zambia 2013.5 NA -27.3 -26.7 -25.1 NA -21.1 -16.0 -17.0 NA -21.9 -9.8 -10.3 NA -22.8 -12.7 -13.4

Zimbabwe 1999 Zimbabwe 2010.5 NA 12.6 6.3 9.8 NA 5.6 6.3 4.9 9.7 -4.3 -3.2 -2.3 8.2 3.1 -1.7 0.4

Bangladesh 2004 Bangladesh 2014 NA 2.3 25.1 23.0 -3.6 4.6 14.5 8.3 13.8 9.4 13.0 14.8 -4.2 6.0 14.7 15.3

Cambodia 2000 Cambodia 2014 66.0 17.7 26.5 24.0 NA 53.4 46.0 49.1 NA 52.1 46.0 48.1 NA 46.8 45.4 47.6

Nepal 2001 Nepal 2011 NA NA 13.3 16.1 NA 18.3 18.0 21.6 NA 31.2 30.0 35.9 NA 26.0 29.7 35.8

Philippines 2003 Philippines 2013 6.4 5.7 21.1 10.8 -2.1 11.9 10.9 8.3 9.6 15.4 22.9 19.0 4.4 11.9 19.3 13.9

Continued
49

Table 3.12—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA 4.2 NA 6.8 NA 21.0 21.3 22.9 NA 28.9 43.6 43.4 17.2 13.1 37.7 28.1

Colombia 2000 Colombia 2010 1.1 4.4 7.7 4.1 4.3 8.6 10.5 7.2 1.6 14.9 18.9 13.7 2.9 9.0 14.0 8.4

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 -1.8 1.5 4.0 0.6 0.0 1.7 1.3 0.9 2.5 2.6 4.3 3.2 0.2 2.1 3.8 1.7

Peru 2000 Peru 2012 6.7 10.6 18.9 12.3 7.8 14.1 21.3 17.8 21.4 15.5 34.3 33.6 6.6 11.2 29.1 21.6

Egypt 2000 Egypt 2014 19.1 28.9 45.1 22.8 23.4 28.4 37.6 25.1 32.6 38.7 37.9 37.3 25.3 35.3 38.4 31.3

Jordan 2002 Jordan 2012 0.8 2.0 -5.2 0.0 2.4 4.5 3.4 3.8 0.4 8.7 5.5 7.1 1.6 4.6 2.4 3.6

Pooled Average 5.6 5.3 7.2 6.2 9.8 10.0 8.9 8.5 21.9 22.0 13.3 14.3 11.5 14.2 13.1 13.1Note: NA indicates too few cases to calculate decadal change.
50 

Medical antenatal care 

Levels 

On average across all the surveys, coverage of medical ANC is quite high among urban women, with similar 

levels in large cities and other urban areas (see Figure 3.13, left panel). In large cities and other urban areas, 

medical ANC coverage is lowest for extremely poor women; however, the differentials are small. For 

example, in large cities, there is 85% coverage among extremely poor, compared with 90% among the 

moderately poor, and 91% among the non-poor. Only in three countries is this percent less than 90% (see 

Table 3.13). The widest differentials by poverty are found in rural areas, where coverage among extremely 

poor women is more than 25 percentage points lower than coverage among non-poor women. 

Decadal change 

On average, medical ANC coverage increased by 15 percentage points over a 10-year period. As Figure 

3.13 (right panel) shows, the decadal change was greater in other urban and rural areas than in large cities. 

Within large cities, the change was smallest among the extremely poor, at a 3 percentage point increase, 

compared with a 5 percentage point increase for the moderately poor and a 7 percentage point increase for 

the not poor. Table 3.14 shows the country-specific decadal changes in medical ANC coverage, by poverty 

level and level of urbanicity. 

Figure 3.13. Pooled average coverage of medical antenatal care (left panel) and pooled average 

decadal change in coverage (right panel), by poverty according to level of urbanicity 

91.2 94.5

87.2 89.8 92.8

82.2 85.8 86.3

61.1

Large cities Other urban areas Rural areas

Percentage

Medical antenatal care

Not poor Moderately poor Extremely poor

6.7 8.5

15.7

4.7 8.9

15.9

3.4

12.4 17.8

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in medical 

antenatal care

Not poor Moderately poor Extremely poor
51

Table 3.13. Medical antenatal care by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * 100.0 97.0 97.9 * 97.1 94.6 95.2 * 89.1 68.2 68.9 (98.9) 94.7 71.3 72.8 Burkina Faso 2010 98.0 99.2 98.3 98.5 (100.0) 98.7 98.0 98.2 * 97.4 93.9 94.1 98.6 98.2 94.6 94.9

Cameroon 2004 100.0 96.2 98.0 97.1 97.7 97.6 88.2 92.1 * 93.3 71.6 74.4 98.8 96.0 77.9 83.4Cameroon 2011 98.2 98.3 98.4 98.4 95.8 97.7 92.7 93.8 97.4 93.6 73.8 75.6 97.3 96.9 81.8 84.7

Cote D’Ivoire 1998-99 100.0 95.5 97.3 97.1 (93.0) 95.2 94.5 94.6 * 90.8 78.4 80.1 98.4 93.2 83.0 85.5Cote D’Ivoire 2011-12 100.0 97.3 96.7 97.3 97.2 97.4 95.9 96.4 * 92.6 85.9 86.5 97.9 95.8 89.3 90.6

Ethiopia 2000 (87.2) 84.0 82.2 83.1 (92.3) 81.7 60.1 63.4 * (37.2) 21.5 21.6 89.7 72.2 25.5 26.7Ethiopia 2011 * (94.7) 94.6 94.3 * 85.2 72.3 73.5 * (65.8) 36.4 36.5 (94.6) 81.9 41.9 42.6

Ghana 2003 * 93.2 98.6 97.2 * 98.9 98.5 98.6 * 94.1 87.8 88.6 * 95.2 91.2 91.9Ghana 2014 * 100.0 98.3 98.9 (100.0) 98.9 97.8 98.2 99.6 97.0 95.8 96.2 99.7 98.5 96.8 97.3

Guinea 1999 * 95.3 96.8 96.5 * 98.1 91.8 93.1 * 80.6 64.9 65.8 * 89.6 71.5 73.5Guinea 2012 * 98.4 95.3 96.1 (100.0) 98.7 95.9 96.6 * 93.7 79.9 80.8 95.8 96.4 83.8 85.2

Kenya 2003 95.3 97.0 92.6 94.7 (93.6) 97.7 88.5 91.7 (96.5) 95.1 85.5 86.8 95.5 96.1 86.2 88.1Kenya 2014 98.8 98.8 97.9 98.3 99.0 99.2 97.2 97.9 100.0 99.3 94.0 94.5 99.2 99.1 95.1 95.9

Mali 2001 91.1 95.6 91.2 93.1 * 93.5 76.6 81.2 (76.6) 67.5 45.4 47.1 88.6 84.4 51.7 56.8Mali 2012-13 (95.3) 96.6 93.9 94.5 (94.1) 94.3 91.3 91.8 * 88.5 68.3 69.3 96.3 92.0 72.7 74.2

Mozambique 2003 (100.0) 99.4 99.4 99.5 (98.5) 98.5 95.8 96.5 * 93.8 78.0 78.9 99.3 97.1 82.7 84.6Mozambique 2011 (100.0) 98.8 96.4 97.4 (100.0) 98.6 95.8 96.2 * 92.8 88.0 88.2 100.0 96.8 90.1 90.6

Niger 1998 * 97.4 95.4 95.8 * 96.4 85.2 87.1 * (64.5) 30.1 30.4 * 90.9 37.7 40.0Niger 2012 (97.5) 98.6 97.5 97.7 (100.0) 98.0 96.0 96.3 * 97.8 80.3 80.4 98.8 98.2 82.4 82.8

Nigeria 2003 93.4 92.3 88.9 90.6 (86.9) 76.4 58.2 65.7 (61.3) 63.0 39.4 44.6 84.3 75.5 52.1 60.1Nigeria 2013 97.0 93.2 85.7 87.9 97.6 92.9 84.5 86.7 80.0 71.6 48.2 51.2 85.8 83.5 59.9 64.0

Rwanda 2000 * 94.3 91.4 91.9 * 100.0 94.9 95.9 * 95.4 91.5 91.9 * 96.0 91.8 92.3Rwanda 2010 100.0 100.0 97.9 98.7 * 100.0 97.5 97.9 100.0 98.8 97.8 98.0 100.0 99.0 97.8 98.0

Tanzania 1999 * 100.0 (97.2) 98.5 (100.0) 99.5 97.2 98.2 * 100.0 90.5 90.7 (100.0) 99.7 91.5 92.5Tanzania 2010 * 98.7 98.6 98.7 89.7 93.1 95.2 93.9 94.5 90.2 84.7 85.4 93.8 93.1 86.3 87.7

Uganda 2000-01 * * 97.2 97.2 * * 96.4 96.5 * * 91.7 91.8 * (94.6) 92.4 92.4Uganda 2011 (96.6) 98.4 97.8 98.0 * 97.7 96.7 97.0 * 94.5 94.4 94.4 93.0 96.6 94.7 94.9

Zambia 2001-02 * 97.5 97.9 97.8 * 99.0 96.9 97.6 * 97.9 90.9 91.1 * 98.5 92.6 93.4Zambia 2013-14 (100.0) 100.0 99.0 99.3 99.1 98.4 98.0 98.2 (100.0) 98.6 93.8 94.0 99.4 99.0 95.1 95.7

Zimbabwe 1999 * 97.9 93.5 95.7 * 95.6 91.4 94.0 (100.0) 95.2 91.8 92.3 97.1 96.0 91.9 93.1Zimbabwe 2010-11 (95.1) 89.1 83.8 87.0 94.2 93.6 91.1 92.7 94.6 91.6 89.0 89.8 94.6 91.4 88.6 89.8

Bangladesh 2004 * (86.8) 73.2 76.0 94.1 87.3 60.5 70.0 84.9 65.1 40.3 42.9 90.3 74.3 44.0 48.7Bangladesh 2014 (97.3) 86.8 75.7 81.8 (79.5) 84.8 74.8 77.5 85.5 73.5 53.6 58.6 86.6 78.2 58.5 63.9

Cambodia 2000 * 98.3 90.8 94.7 * 67.3 51.5 53.0 * 41.6 32.9 33.8 * 53.0 35.9 37.7Cambodia 2014 96.6 100.0 99.2 98.9 98.8 99.3 97.5 98.3 99.7 98.0 93.7 94.8 98.9 98.4 94.0 95.3

Nepal 2001 * * (87.5) 91.8 * 84.5 77.7 78.9 * 77.7 45.2 46.1 * 81.2 47.2 48.6Nepal 2011 * (98.0) (91.1) 95.6 (100.0) 96.5 90.0 92.2 98.5 93.9 80.0 82.9 98.7 94.6 80.8 83.9

Philippines 2003 97.3 95.0 85.4 92.1 97.3 92.6 87.0 90.8 97.9 90.2 78.3 83.9 97.5 92.1 81.8 87.6Philippines 2013 99.4 99.5 97.5 98.5 98.0 98.0 93.4 95.6 98.3 96.8 92.5 94.2 98.5 97.8 93.5 95.4

Continued
52

Table 3.13—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 98.6 (95.7) 97.4 * 93.6 91.4 93.2 * 91.8 88.0 88.9 (92.2) 95.6 89.2 92.4 Armenia 2010 100.0 97.1 * 98.5 99.0 95.9 (97.5) 98.0 100.0 100.0 98.8 99.8 99.7 98.3 96.9 98.9

Colombia 2000 98.1 93.2 88.6 95.2 95.7 91.1 85.0 92.1 94.4 87.8 77.5 84.3 96.4 90.9 81.8 90.8Colombia 2010 99.1 96.5 97.6 98.4 98.8 97.6 94.2 97.7 98.4 96.8 90.5 94.0 98.9 97.0 92.7 97.0

Dominican 

Republic 

2002 98.4 97.9 98.3 98.2 98.8 99.4 98.5 98.9 99.2 98.1 96.8 98.0 98.6 98.3 97.7 98.3

Dominican 

Republic 

2013 100.0 100.0 98.8 99.6 100.0 99.1 99.2 99.5 96.9 99.5 98.8 98.5 99.3 99.5 98.9 99.3

Peru 2000 69.3 56.1 45.5 57.9 55.2 42.0 34.6 39.7 52.0 40.5 42.8 42.8 67.7 52.0 42.7 49.7Peru 2012 100.0 100.0 99.0 99.8 99.6 98.9 98.1 98.8 100.0 98.7 96.5 96.9 99.8 99.2 97.3 98.4

Egypt 2000 84.7 67.6 40.9 76.6 75.4 59.4 44.3 67.9 58.7 44.0 33.6 44.7 71.1 50.4 35.2 55.7Egypt 2014 96.5 91.0 90.6 93.9 95.8 90.7 86.0 92.2 94.5 89.9 82.1 89.2 95.1 90.1 83.1 90.3

Jordan 2002 100.0 99.6 99.3 99.6 98.9 98.9 98.4 98.7 99.4 97.2 96.0 97.2 99.2 98.7 98.0 98.6Jordan 2012 99.4 99.0 97.3 98.7 99.7 99.4 98.9 99.4 100.0 99.6 97.7 99.2 99.6 99.3 98.2 99.1

Pooled Average 91.2 89.8 85.8 89.2 94.5 92.8 86.3 89.6 87.2 82.2 61.1 64.0 91.9 88.3 67.6 72.9
53

Table 3.14. Decadal change in medical antenatal care by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA -1.1 1.9 0.9 NA 2.3 4.9 4.3 NA 11.9 36.7 36.0 -0.4 5.0 33.3 31.6

Cameroon 2004 Cameroon 2011 -2.6 3.0 0.6 1.9 -2.7 0.1 6.4 2.4 NA 0.4 3.1 1.7 -2.1 1.3 5.6 1.9

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 0.0 1.4 -0.5 0.2 3.2 1.7 1.1 1.4 NA 1.4 5.8 4.9 -0.4 2.0 4.8 3.9

Ethiopia 2000 Ethiopia 2011 NA 9.7 11.3 10.2 NA 3.2 11.1 9.2 NA 26.0 13.5 13.5 4.5 8.8 14.9 14.5

Ghana 2003 Ghana 2014 NA 6.2 -0.3 1.5 NA 0.0 -0.6 -0.4 NA 2.6 7.3 6.9 NA 3.0 5.1 4.9

Guinea 1999 Guinea 2012 NA 2.4 -1.2 -0.3 NA 0.5 3.2 2.7 NA 10.1 11.5 11.5 NA 5.2 9.5 9.0

Kenya 2003 Kenya 2014 3.2 1.6 4.8 3.3 4.9 1.4 7.9 5.6 3.2 3.8 7.7 7.0 3.4 2.7 8.1 7.1

Mali 2001 Mali 2012.5 3.7 0.9 2.3 1.2 NA 0.7 12.8 9.2 NA 18.3 19.9 19.3 6.7 6.6 18.3 15.1

Mozambique 2003 Mozambique 2011 0.0 -0.8 -3.8 -2.6 1.9 0.1 0.0 -0.4 NA -1.3 12.5 11.6 0.9 -0.4 9.2 7.5

Niger 1998 Niger 2012 NA 0.9 1.5 1.4 NA 1.1 7.7 6.6 NA 23.8 35.9 35.7 NA 5.2 31.9 30.6

Nigeria 2003 Nigeria 2013 3.6 0.9 -3.2 -2.7 10.7 16.5 26.3 21.0 18.7 8.6 8.8 6.6 1.5 8.0 7.8 3.9

Rwanda 2000 Rwanda 2010 NA 5.7 6.5 6.8 NA 0.0 2.6 2.0 NA 3.4 6.3 6.1 NA 3.0 6.0 5.7

Tanzania 1999 Tanzania 2010 NA -1.2 1.3 0.2 -9.4 -5.8 -1.8 -3.9 NA -8.9 -5.3 -4.8 -5.6 -6.0 -4.7 -4.4

Uganda 2000.5 Uganda 2011 NA NA 0.6 0.8 NA NA 0.3 0.5 NA NA 2.6 2.5 NA 1.9 2.2 2.4

Zambia 2001.5 Zambia 2013.5 NA 2.1 0.9 1.3 NA -0.5 0.9 0.5 NA 0.6 2.4 2.4 NA 0.4 2.1 1.9

Zimbabwe 1999 Zimbabwe 2010.5 NA -7.7 -8.4 -7.6 NA -1.7 -0.3 -1.1 -4.7 -3.1 -2.4 -2.2 -2.2 -4.0 -2.9 -2.9

Bangladesh 2004 Bangladesh 2014 NA 0.0 2.5 5.8 -14.6 -2.5 14.3 7.5 0.6 8.4 13.3 15.7 -3.7 3.9 14.5 15.2

Cambodia 2000 Cambodia 2014 69.0 1.2 6.0 3.0 NA 22.9 32.9 32.4 NA 40.3 43.4 43.6 NA 32.4 41.5 41.1

Nepal 2001 Nepal 2011 NA NA 3.6 3.8 NA 12.0 12.3 13.3 NA 16.2 34.8 36.8 NA 13.4 33.6 35.3

Philippines 2003 Philippines 2013 2.1 4.5 12.1 6.4 0.7 5.4 6.4 4.8 0.4 6.6 14.2 10.3 1.0 5.7 11.7 7.8

Continued
54

Table 3.14—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA -1.5 NA 1.1 NA 2.3 6.1 4.8 NA 8.2 10.8 10.9 7.5 2.7 7.7 6.5

Colombia 2000 Colombia 2010 1.0 3.3 9.0 3.2 3.1 6.5 9.2 5.6 4.0 9.0 13.0 9.7 2.5 6.1 10.9 6.2

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 1.5 1.9 0.5 1.3 1.1 -0.3 0.6 0.5 -2.1 1.3 1.8 0.5 0.6 1.1 1.1 0.9

Peru 2000 Peru 2012 25.6 36.6 44.6 34.9 37.0 47.4 52.9 49.3 40.0 48.5 44.8 45.1 26.8 39.3 45.5 40.6

Egypt 2000 Egypt 2014 8.4 16.7 35.5 12.4 14.6 22.4 29.8 17.4 25.6 32.8 34.6 31.8 17.1 28.4 34.2 24.7

Jordan 2002 Jordan 2012 -0.6 -0.6 -2.0 -0.9 0.8 0.5 0.5 0.7 0.6 2.4 1.7 2.0 0.4 0.6 0.2 0.5

Pooled average 6.7 4.7 3.4 4.2 8.5 8.9 12.4 10.5 15.7 15.9 17.8 17.7 9.7 10.8 16.6 15.0Note: NA indicates too few cases to calculate decadal change.
55 

Home delivery 

Levels 

Across the pooled surveys, delivering babies at home is rare, and takes place almost exclusively among 

extremely poor women (see Figure 3.14, left panel). Six percent of extremely poor women in large cities, 

11% of extremely poor women in other urban areas, and 46% of women in rural areas deliver their babies 

at home. Compared with their non- and less-poor counterparts, extremely poor women are more likely to 

deliver at home in all three localities; the poverty-gaps in coverage are wider in other urban areas than in 

large cities, and are widest in rural areas. In contrast to the general rarity of delivering at home, many 

extremely poor women in large cities did so in the most recent survey in Bangladesh (43%) and in Nigeria 

(53%), as seen in Table 3.15. 

Decadal change 

Decreases in the percentage of births delivered at home were concentrated in the group where the overall 

prevalence of birthing at home was greatest: rural extremely poor women (see Figure 3.14, right panel). In 

three countries—Tanzania, Nigeria, and Zimbabwe—there was a decadal increase in home delivery for 

extremely poor large city women (see Table 3.16). 

Figure 3.14. Pooled average prevalence of home delivery (left panel) and pooled average decadal 

change in prevalence (right panel), by poverty according to level of urbanicity 

0.5 2.4 0.6 2.2 0.9 5.9 6.6 10.8

45.5

Large cities Other urban areas Rural areas

Percentage

Home delivery

Not poor Moderately poor Extremely poor

-1.7 -1.7 -0.9 -1.0 -2.8 -6.8 -3.9 -6.1

-17.5

Large cities Other urban areas Rural areas

Percentage point change

Not poor Moderately poor Extremely poor

Pooled average decadal change in home delivery
56

Table 3.15. Home delivery by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * 2.9 5.6 4.7 * 10.5 20.8 18.6 (12.6) 39.0 69.4 68.5 6.6 20.2 63.8 61.3 Burkina Faso 2010 4.0 2.0 1.7 2.0 0.0 3.9 9.6 8.3 * 18.3 39.8 38.7 5.0 11.0 35.3 33.2

Cameroon 2004 1.4 5.3 6.8 5.5 9.6 10.9 30.6 23.0 * 24.3 61.9 57.5 5.7 12.6 50.1 40.0Cameroon 2011 0.7 5.4 3.7 4.1 4.9 6.4 23.9 20.0 31.0 26.6 56.8 54.4 9.4 11.8 42.7 37.3

Cote D’Ivoire 1998-99 13.0 16.0 18.8 17.2 (13.9) 22.6 26.3 24.9 * 55.0 69.6 67.5 11.7 36.6 57.5 52.7Cote D’Ivoire 2011-12 1.6 7.4 10.0 8.4 2.5 18.5 23.7 21.3 (36.7) 30.3 57.6 55.3 6.5 19.8 45.5 40.7

Ethiopia 2000 (16.8) 22.7 38.1 32.8 (61.2) 59.5 76.2 74.2 * 86.5 98.0 97.9 35.2 58.9 95.6 94.8Ethiopia 2011 * (4.9) 18.9 17.2 (0.1) 30.2 58.0 55.4 * (60.1) 95.5 95.4 3.8 33.5 90.4 89.5

Ghana 2003 * 8.9 10.5 10.1 * 24.2 33.2 31.0 * 56.4 71.4 69.7 * 35.7 56.6 53.4Ghana 2014 0.0 1.4 6.3 4.5 0.0 5.8 19.6 15.1 22.8 31.8 43.4 40.6 14.4 15.0 30.8 26.6

Guinea 1999 * 33.2 31.7 31.7 * 42.6 46.4 45.5 * 66.2 80.5 79.7 * 50.2 71.7 69.5Guinea 2012 * 12.3 20.5 18.7 (11.3) 27.4 43.7 39.4 (46.5) 48.4 71.1 69.6 21.6 33.0 61.8 58.8

Kenya 2003 6.9 18.1 38.9 27.3 (5.6) 17.0 38.9 31.2 18.7 35.7 69.4 65.5 10.7 28.2 65.3 58.7Kenya 2014 0.8 6.6 15.6 11.5 2.7 9.6 24.9 19.7 8.0 15.4 52.1 48.9 3.2 10.8 43.3 37.4

Mali 2001 8.5 7.7 7.4 7.7 (10.5) 12.6 35.0 29.4 22.2 61.2 74.5 73.2 12.8 30.2 66.3 60.8Mali 2012-13 4.5 3.6 4.9 4.7 (4.8) 7.0 13.5 12.4 (22.9) 24.6 52.7 51.6 9.7 15.1 45.5 43.4

Mozambique 2003 (6.8) 7.4 9.2 8.4 4.8 11.3 21.4 18.9 * 43.9 65.4 64.3 5.4 21.9 54.4 50.6Mozambique 2011 (2.2) 4.4 6.4 5.5 3.6 4.2 19.3 17.6 * 22.0 54.5 53.5 4.9 10.4 45.3 43.1

Niger 1998 * 16.5 29.7 25.3 * 18.8 34.1 31.5 * (55.4) 91.4 91.1 * 24.9 83.8 81.3Niger 2012 0.0 6.3 14.8 13.0 0.0 4.0 20.7 18.9 * 57.1 77.7 77.6 0.0 20.2 70.9 69.5

Nigeria 2003 36.2 27.5 41.9 36.0 47.7 51.0 69.7 62.9 62.3 62.7 83.9 79.4 46.5 50.2 73.8 66.4Nigeria 2013 5.4 22.3 52.7 44.6 26.1 23.1 37.7 34.4 40.0 53.6 80.2 76.9 31.5 36.9 68.1 63.1

Rwanda 2000 * 9.5 31.2 28.2 * 19.6 40.7 36.6 * 68.1 80.5 79.3 (68.0) 56.3 74.7 72.6Rwanda 2010 0.0 5.7 15.4 11.4 * 4.9 26.8 23.4 5.7 16.6 33.7 30.8 4.1 14.6 32.4 29.0

Tanzania 1999 * 8.0 (7.5) 7.6 8.6 11.2 26.6 20.0 * 30.3 66.2 65.3 5.8 14.2 61.2 56.3Tanzania 2010 0.0 12.4 14.4 12.2 6.2 6.5 28.7 19.1 13.1 33.0 58.8 56.1 7.3 19.8 54.5 48.1

Uganda 2000-01 * * 10.3 10.1 * * 27.7 27.6 * (57.7) 67.1 67.0 * (49.2) 62.0 61.9Uganda 2011 (7.3) 4.1 8.4 6.7 * 6.6 13.8 12.2 * 18.3 48.1 46.8 8.8 11.0 44.3 41.6

Zambia 2001-02 * 14.4 19.2 18.3 * 7.6 28.1 21.7 * 27.8 72.5 71.3 * 12.4 60.7 55.7Zambia 2013-14 0.0 5.2 9.6 7.9 3.0 7.1 14.8 12.2 11.8 19.4 43.1 42.0 3.7 9.2 34.8 31.3

Zimbabwe 1999 * 6.4 4.1 5.8 * 8.2 11.0 9.7 (11.3) 21.1 32.0 30.5 14.1 11.8 27.5 23.3Zimbabwe 2010-11 (4.0) 18.7 17.3 16.9 7.1 10.5 14.5 11.6 20.7 33.4 44.9 41.6 13.6 23.9 39.0 33.5

Bangladesh 2004 * (51.0) 85.6 78.1 37.9 59.0 86.9 76.2 76.0 84.2 94.2 93.3 52.0 73.5 93.0 89.9Bangladesh 2014 (10.9) 33.6 43.1 36.7 (4.8) 32.8 50.7 44.8 31.2 53.4 74.7 69.1 25.7 45.5 68.8 62.2

Cambodia 2000 * 2.9 20.0 11.5 * 56.6 81.3 79.4 * 89.7 92.8 92.5 * 73.2 90.5 89.0Cambodia 2014 4.5 0.2 4.1 2.4 1.0 2.7 8.2 5.3 3.0 9.6 21.8 18.7 3.0 7.3 20.6 16.6

Nepal 2001 * (4.0) 36.5 26.0 * 35.7 61.9 58.5 * 60.7 92.2 91.3 * 51.0 90.3 88.9Nepal 2011 * 11.5 26.0 15.1 (3.5) 21.2 39.0 33.0 29.1 42.0 72.5 66.7 24.3 37.3 69.9 63.1

Philippines 2003 12.5 28.2 44.7 31.4 26.3 45.1 65.5 52.9 39.7 67.1 86.5 77.0 27.5 50.5 75.1 61.4Philippines 2013 10.9 16.6 23.5 18.9 14.7 19.0 43.3 32.0 22.7 32.3 56.3 47.6 17.3 24.3 48.1 38.0

Continued
57

Table 3.15—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 0.4 7.1 1.5 * 0.9 1.3 1.0 * 6.5 18.3 15.9 0.0 1.7 15.6 8.5 Armenia 2010 0.0 0.0 * 0.0 0.1 0.0 0.0 0.0 0.5 0.4 0.0 0.4 0.2 0.2 0.0 0.2

Colombia 2000 1.0 2.5 5.2 2.2 2.5 7.5 11.3 6.1 11.7 18.8 25.5 20.9 3.3 9.2 17.8 9.6Colombia 2010 0.4 0.8 3.6 0.9 0.8 1.8 3.6 1.7 4.0 6.4 13.1 9.5 1.0 2.8 8.9 3.6

Dominican 

Republic 

2002 0.1 0.8 0.8 0.5 0.1 0.3 1.0 0.5 1.0 1.4 6.5 3.4 0.3 0.9 3.3 1.5

Dominican 

Republic 

2013 0.0 0.7 0.5 0.4 0.4 0.9 1.5 0.9 0.4 1.2 3.6 1.9 0.2 0.9 1.8 1.0

Peru 2000 3.8 9.9 17.8 10.3 11.4 26.3 34.3 29.0 23.4 35.9 54.8 53.6 5.0 15.7 44.1 32.0Peru 2012 0.6 0.0 0.6 0.4 1.2 3.6 11.7 6.5 4.5 14.4 37.7 33.8 1.0 4.7 25.3 14.5

Egypt 2000 16.2 32.6 52.1 23.4 28.3 43.1 58.1 35.8 50.0 63.2 78.2 65.3 34.2 55.1 74.6 51.7Egypt 2014 2.4 8.3 7.5 5.1 3.7 9.3 10.7 6.8 9.9 14.1 26.9 16.3 7.3 12.6 23.5 13.2

Jordan 2002 1.3 2.1 1.8 1.8 2.4 3.7 3.5 3.3 0.2 2.9 6.5 3.9 1.8 3.1 4.0 3.1Jordan 2012 1.5 2.1 1.7 1.8 0.8 0.6 2.0 1.0 0.1 0.9 1.2 0.7 0.9 1.2 1.7 1.2

Pooled Average 0.5 2.4 5.9 2.6 0.6 2.2 10.8 2.8 0.9 6.6 45.5 23.7 1.2 4.2 31.9 11.2
58

Table 3.16. Decadal change in home delivery by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA -1.3 -5.6 -3.9 NA -9.4 -16.0 -14.7 NA -29.6 -42.3 -42.6 -2.3 -13.1 -40.7 -40.1

Cameroon 2004 Cameroon 2011 -1.0 0.1 -4.4 -2.0 -6.7 -6.4 -9.6 -4.3 NA 3.3 -7.3 -4.4 5.3 -1.1 -10.6 -3.9

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 -8.8 -6.6 -6.8 -6.8 -8.8 -3.2 -2.0 -2.8 NA -19.0 -9.2 -9.4 -4.0 -12.9 -9.2 -9.2

Ethiopia 2000 Ethiopia 2011 NA -16.2 -17.5 -14.2 -55.5 -26.6 -16.5 -17.1 NA -24.0 -2.3 -2.3 -28.5 -23.1 -4.7 -4.8

Ghana 2003 Ghana 2014 NA -6.8 -3.8 -5.1 NA -16.7 -12.4 -14.5 NA -22.4 -25.5 -26.5 NA -18.8 -23.5 -24.4

Guinea 1999 Guinea 2012 NA -16.1 -8.6 -10.0 NA -11.7 -2.1 -4.7 NA -13.7 -7.2 -7.8 NA -13.2 -7.6 -8.2

Kenya 2003 Kenya 2014 -5.5 -10.5 -21.2 -14.4 -2.6 -6.7 -12.7 -10.5 -9.7 -18.5 -15.7 -15.1 -6.8 -15.8 -20.0 -19.4

Mali 2001 Mali 2012.5 -3.5 -3.6 -2.2 -2.6 -5.0 -4.9 -18.7 -14.8 0.6 -31.8 -19.0 -18.8 -2.7 -13.1 -18.1 -15.1

Mozambique 2003 Mozambique 2011 -5.8 -3.8 -3.5 -3.6 -1.5 -8.9 -2.6 -1.6 NA -27.4 -13.6 -13.5 -0.6 -14.4 -11.4 -9.4

Niger 1998 Niger 2012 NA -7.3 -10.6 -8.8 NA -10.6 -9.6 -9.0 NA 1.2 -9.8 -9.6 NA -3.4 -9.2 -8.4

Nigeria 2003 Nigeria 2013 -30.8 -5.2 10.8 8.6 -21.6 -27.9 -32.0 -28.5 -22.3 -9.1 -3.7 -2.5 -15.0 -13.3 -5.7 -3.3

Rwanda 2000 Rwanda 2010 NA -3.8 -15.8 -16.8 NA -14.7 -13.9 -13.2 NA -51.5 -46.8 -48.5 -63.9 -41.7 -42.3 -43.6

Tanzania 1999 Tanzania 2010 NA 4.0 6.3 4.2 -2.2 -4.3 1.9 -0.8 NA 2.5 -6.7 -8.4 1.4 5.1 -6.1 -7.5

Uganda 2000.5 Uganda 2011 NA NA -1.8 -3.2 NA NA -13.2 -14.7 NA -37.5 -18.1 -19.2 NA -36.4 -16.9 -19.3

Zambia 2001.5 Zambia 2013.5 NA -7.7 -8.0 -8.7 NA -0.4 -11.1 -7.9 NA -7.0 -24.5 -24.4 NA -2.7 -21.6 -20.3

Zimbabwe 1999 Zimbabwe 2010.5 NA 10.7 11.5 9.7 NA 2.0 3.0 1.7 8.2 10.7 11.2 9.7 -0.4 10.5 10.0 8.9

Bangladesh 2004 Bangladesh 2014 NA -17.4 -42.5 -41.4 -33.1 -26.2 -36.2 -31.4 -44.8 -30.8 -19.5 -24.2 -26.3 -28.0 -24.2 -27.7

Cambodia 2000 Cambodia 2014 3.2 -1.9 -11.4 -6.5 NA -38.5 -52.2 -52.9 NA -57.2 -50.7 -52.7 NA -47.1 -49.9 -51.7

Nepal 2001 Nepal 2011 NA 7.5 -10.5 -10.9 NA -14.5 -22.9 -25.5 NA -18.7 -19.7 -24.6 NA -13.7 -20.4 -25.8

Philippines 2003 Philippines 2013 -1.6 -11.6 -21.2 -12.5 -11.6 -26.1 -22.2 -20.9 -17.0 -34.8 -30.2 -29.4 -10.2 -26.2 -27.0 -23.4

Continued
59

Table 3.16—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA -0.4 NA -1.5 NA -0.9 -1.3 -1.0 NA -6.1 -18.3 -15.5 0.2 -1.5 -15.6 -8.3

Colombia 2000 Colombia 2010 -0.6 -1.7 -1.6 -1.3 -1.7 -5.7 -7.7 -4.4 -7.7 -12.4 -12.4 -11.4 -2.3 -6.4 -8.9 -6.0

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 -0.1 -0.1 -0.3 -0.1 0.3 0.5 0.5 0.4 -0.5 -0.2 -2.6 -1.4 -0.1 0.0 -1.4 -0.5

Peru 2000 Peru 2012 -2.7 -8.3 -14.3 -8.3 -8.5 -18.9 -18.8 -18.8 -15.8 -17.9 -14.3 -16.5 -3.3 -9.2 -15.7 -14.6

Egypt 2000 Egypt 2014 -9.9 -17.4 -31.9 -13.1 -17.6 -24.1 -33.9 -20.7 -28.6 -35.1 -36.6 -35.0 -19.2 -30.4 -36.5 -27.5

Jordan 2002 Jordan 2012 0.2 0.0 -0.1 0.0 -1.6 -3.1 -1.5 -2.3 -0.1 -2.0 -5.3 -3.2 -0.9 -1.9 -2.3 -1.9

Pooled Average -1.7 -1.7 -3.9 -2.5 -0.9 -2.8 -6.1 -3.0 -1.0 -6.8 -17.5 -13.7 -1.2 -3.4 -12.7 -7.1Note: NA indicates too few cases to calculate decadal change.
60 

Medical delivery attendance 

Levels 

Within each area of residence, differentials in medical delivery attendance coverage are evident across 

poverty levels (see Figure 3.15, left panel). In large cities, 76% of extremely poor women gave birth with 

medical delivery attendance, compared with 90% of moderately poor women and 95% of non-poor women. 

These gaps are slightly wider in other urban areas (67% among extremely poor and 88% among moderately 

poor) and are by far the widest in rural areas (18% among extremely poor and 84% among moderately 

poor). According to the latest surveys, more than 20% of extremely poor women living in large cities in 

only three countries—Bangladesh, Nigeria and Nepal—lacked medical attendance at their last delivery (see 

Table 3.17). 

In terms of medical delivery attendance coverage, extremely poor women in urban areas fare better than 

their rural extremely poor counterparts. However, they fair worse than non-poor rural women. 

Decadal change 

Within large cities, as well as other urban areas, the decadal increases in coverage were greatest among the 

extremely poor (see Figure 3.15, right panel). In Peru, Egypt, and Bangladesh, the increases were 29 

percentage points or greater. However, there were small decadal decreases in Tanzania, Zimbabwe, and 

Nigeria. In rural areas—where the overall coverage of medical delivery attendance is lowest among the 

extremely poor—decadal improvements were concentrated in the moderately poor group. Table 3.18 shows 

the country-specific decadal changes in medical delivery attendance, by poverty level and level of 

urbanicity. 

Figure 3.15. Pooled average coverage of medical delivery attendance (left panel) and pooled 

average decadal change in prevalence (right panel), by poverty according to level of urbanicity 

94.7 95.6

84.2 89.6 87.6

64.5

76.4

66.9

18.3

Large cities Other urban areas Rural areas

Percentage

Medical delivery attendance

Not poor Moderately poor Extremely poor

4.7 5.7

14.4

4.7

11.5

22.4

8.2

16.9 11.6

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in medical 

delivery attendance

Not poor Moderately poor Extremely poor
61

Table 3.17. Medical delivery attendance by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * 99.2 93.7 95.4 * 88.8 79.5 81.5 (87.4) 57.9 29.6 30.5 93.4 79.0 35.4 37.8 Burkina Faso 2010 96.0 96.6 97.9 97.4 (100.0) 96.1 90.3 91.6 * 81.2 60.7 61.8 95.0 88.4 65.1 67.1

Cameroon 2004 100.0 95.9 94.7 95.7 95.6 90.9 71.3 79.1 * 76.9 39.9 44.2 97.7 88.8 51.7 61.8Cameroon 2011 98.4 95.2 95.8 95.8 95.8 93.6 77.7 81.3 71.5 73.4 44.3 46.7 91.1 88.4 58.4 63.6

Cote D’Ivoire 1998-99 87.0 84.0 80.6 82.4 (86.1) 76.5 74.7 75.6 * 44.0 30.1 32.1 88.3 62.8 42.4 47.1Cote D’Ivoire 2011-12 98.4 94.2 90.0 92.0 97.0 83.7 76.7 79.4 (63.3) 69.2 42.2 44.5 93.3 81.2 54.4 59.4

Ethiopia 2000 (82.8) 77.3 64.8 69.1 (53.9) 47.4 26.0 28.7 * 13.7 2.2 2.3 71.1 45.0 4.8 5.6Ethiopia 2011 * (92.9) 82.8 83.9 (99.9) 71.7 43.6 46.1 * (42.7) 4.7 4.8 95.2 68.0 10.0 10.8

Ghana 2003 * 90.6 88.3 88.9 * 75.6 68.3 70.1 * 43.8 29.3 30.9 * 64.2 44.0 47.1Ghana 2014 (100.0) 98.9 92.8 95.0 (100.0) 94.3 79.8 84.5 78.2 69.2 57.4 60.2 86.3 85.6 69.3 73.7

Guinea 1999 * 82.6 85.3 84.9 * 74.2 64.2 66.3 * 36.9 20.4 21.4 * 60.2 31.9 34.8Guinea 2012 * 95.4 89.9 91.1 (91.2) 81.7 73.1 75.4 (56.2) 55.3 30.0 31.6 81.2 73.2 42.0 45.3

Kenya 2003 93.1 82.4 63.3 74.1 (94.4) 83.5 62.5 69.9 81.2 66.0 30.5 34.5 89.2 73.0 34.9 41.6Kenya 2014 97.9 94.3 83.4 87.9 96.1 89.5 74.0 79.2 89.2 84.4 47.2 50.4 95.1 89.0 55.9 61.8

Mali 2001 93.0 94.1 93.4 93.7 (92.5) 88.8 70.3 75.0 80.4 41.3 26.4 27.7 89.4 71.8 35.0 40.6Mali 2012-13 95.5 98.6 95.4 95.9 (95.2) 93.3 87.3 88.4 (77.1) 77.6 49.6 50.7 90.3 86.6 56.6 58.6

Mozambique 2003 (96.4) 92.0 87.0 89.2 96.8 86.1 76.6 79.0 * 55.8 33.0 34.2 96.8 76.5 43.9 47.7Mozambique 2011 (97.8) 90.6 90.3 90.8 85.6 91.7 77.2 78.8 * 74.3 43.4 44.3 89.4 85.4 52.2 54.3

Niger 1998 * 84.2 69.6 74.5 * 76.8 63.1 65.5 * (46.0) 7.7 8.1 * 74.0 15.1 17.6Niger 2012 (96.3) 92.2 85.3 86.8 100.0 96.0 78.6 80.5 * 42.9 21.0 21.2 98.2 79.2 27.9 29.3

Nigeria 2003 69.6 77.2 59.7 67.1 57.7 54.7 34.3 41.8 44.1 38.0 16.6 21.3 59.2 53.7 28.2 36.2Nigeria 2013 97.2 82.9 55.4 62.7 77.7 81.6 67.3 70.5 62.1 49.9 22.2 25.6 70.9 67.3 35.4 40.5

Rwanda 2000 * 90.5 69.1 72.0 * 81.0 59.0 63.3 * 31.1 18.7 20.0 (32.0) 43.2 24.6 26.7Rwanda 2010 100.0 94.6 83.0 87.7 * 93.5 71.0 74.5 93.7 81.8 64.1 67.2 95.4 84.0 65.5 69.0

Tanzania 1999 * 94.2 (92.9) 93.7 97.3 88.1 74.0 80.3 * 77.2 33.6 34.8 97.9 87.3 38.7 43.8Tanzania 2010 (96.7) 88.7 83.7 87.2 95.0 92.9 70.1 80.1 80.8 64.9 37.5 40.4 90.0 79.3 42.2 48.9

Uganda 2000-01 * * 89.4 89.6 * * 72.4 72.5 * (49.2) 33.0 33.1 * (56.5) 38.1 38.2Uganda 2011 (92.7) 95.2 93.0 93.8 * 93.1 86.2 87.7 * 84.1 52.8 54.1 91.2 89.7 56.5 59.3

Zambia 2001-02 * 85.6 80.3 81.3 * 91.7 71.5 77.9 * 72.2 26.3 27.6 * 87.2 38.3 43.4Zambia 2013-14 (100.0) 94.7 89.5 91.4 95.9 91.6 84.2 86.7 87.0 76.3 50.4 51.6 95.4 89.3 60.2 64.2

Zimbabwe 1999 * 91.7 88.8 90.1 * 90.4 87.8 89.0 (84.9) 76.1 62.4 64.2 84.5 86.2 67.4 72.4Zimbabwe 2010-11 (96.0) 82.9 82.1 83.5 92.4 89.7 85.6 88.4 78.1 66.2 54.6 57.9 85.6 76.4 60.6 66.2

Bangladesh 2004 * (49.0) 17.2 24.2 67.5 52.0 18.7 30.5 31.5 20.1 7.9 9.1 53.9 33.1 9.6 13.2Bangladesh 2014 (91.9) 69.6 52.9 62.4 (93.4) 73.5 53.4 59.7 72.6 51.9 29.9 35.6 77.5 59.7 35.2 42.1

Cambodia 2000 * 98.6 88.7 93.6 * 71.9 46.2 48.2 * 36.5 27.3 28.0 * 49.3 30.2 31.8Cambodia 2014 95.5 99.5 97.2 97.9 99.0 99.0 96.6 97.7 97.7 93.6 85.5 87.6 97.5 95.1 86.4 89.0

Nepal 2001 * (96.0) 65.4 75.3 * 67.7 44.0 47.1 * 45.6 9.2 10.2 * 54.2 11.3 12.9Nepal 2011 * 88.5 74.0 84.9 (96.5) 81.3 64.7 70.2 78.8 65.5 32.3 38.6 82.2 69.1 34.8 41.9

Philippines 2003 97.2 88.4 75.4 85.1 91.6 81.4 67.7 75.8 83.0 58.2 27.9 40.8 89.9 73.3 45.7 59.8Philippines 2013 92.1 90.7 85.1 88.1 93.0 91.7 70.8 80.1 89.0 79.6 54.6 63.6 91.0 86.1 63.3 72.8

Continued
62

Table 3.17—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 99.6 94.6 98.8 * 99.2 100.0 99.4 * 98.8 93.4 94.5 (100.0) 99.3 94.1 96.8 Armenia 2010 99.4 100.0 * 99.7 99.9 100.0 100.0 100.0 99.5 98.4 100.0 99.0 99.6 99.1 100.0 99.5

Colombia 2000 97.9 97.5 90.0 96.4 97.3 90.8 83.5 92.1 87.8 74.8 60.5 69.8 96.1 88.2 72.3 86.4Colombia 2010 99.5 98.4 94.5 98.7 98.8 97.3 95.1 97.6 96.0 92.6 79.4 86.2 98.8 96.3 86.2 94.8

Dominican 

Republic 

2002 99.7 98.8 97.8 99.0 99.0 99.5 98.5 99.0 99.1 97.0 92.5 95.7 99.4 98.3 95.6 97.8

Dominican 

Republic 

2013 100.0 100.0 99.5 99.8 99.3 97.9 98.3 98.5 95.3 98.4 97.3 97.1 98.6 98.8 98.4 98.6

Peru 2000 84.0 72.8 63.6 73.9 69.3 55.4 41.8 49.2 56.1 51.1 18.2 20.1 82.0 67.3 31.2 46.9Peru 2012 99.0 100.0 98.2 99.1 99.4 96.9 89.5 94.3 96.7 91.3 69.3 72.8 99.1 96.7 78.9 88.0

Egypt 2000 90.9 78.3 54.3 84.5 86.8 72.1 52.4 78.7 66.5 50.6 32.4 48.0 79.3 58.4 35.7 60.9Egypt 2014 98.9 95.7 95.2 97.4 98.0 95.1 92.4 96.0 94.6 91.3 80.4 89.3 96.1 92.4 82.9 91.5

Jordan 2002 98.7 99.3 99.4 99.2 98.8 98.2 98.9 98.6 100.0 98.3 94.0 96.8 99.0 98.5 97.6 98.3Jordan 2012 99.3 99.0 100.0 99.4 99.9 99.8 99.6 99.8 100.0 99.9 99.2 99.7 99.7 99.6 99.6 99.6

Pooled Average 94.7 89.6 76.4 84.4 95.6 87.6 66.9 76.7 84.2 64.5 18.3 21.0 92.2 78.8 30.1 38.1
63

Table 3.18. Decadal change in medical delivery attendance by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA -3.7 6.0 2.9 NA 10.4 15.4 14.4 NA 33.3 44.4 44.7 2.3 13.4 42.4 41.9

Cameroon 2004 Cameroon 2011 -2.3 -1.0 1.6 0.1 0.3 3.9 9.1 3.1 NA -5.0 6.3 3.6 -9.4 -0.6 9.6 2.6

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 8.8 7.8 7.2 7.4 8.4 5.5 1.5 2.9 NA 19.4 9.3 9.5 3.8 14.2 9.2 9.5

Ethiopia 2000 Ethiopia 2011 NA 14.2 16.4 13.5 41.8 22.1 16.0 15.8 NA 26.4 2.3 2.3 21.9 20.9 4.7 4.7

Ghana 2003 Ghana 2014 NA 7.5 4.1 5.5 NA 17.0 10.5 13.1 NA 23.1 25.5 26.6 NA 19.5 23.0 24.2

Guinea 1999 Guinea 2012 NA 9.8 3.5 4.8 NA 5.8 6.8 7.0 NA 14.2 7.4 7.8 NA 10.0 7.8 8.1

Kenya 2003 Kenya 2014 4.4 10.8 18.3 12.5 1.5 5.5 10.5 8.5 7.3 16.7 15.2 14.5 5.4 14.5 19.1 18.4

Mali 2001 Mali 2012.5 2.2 3.9 1.7 1.9 2.3 3.9 14.8 11.7 -2.9 31.6 20.2 20.0 0.8 12.9 18.8 15.7

Mozambique 2003 Mozambique 2011 1.7 -1.8 4.1 2.0 -14.0 7.0 0.8 -0.3 NA 23.1 13.0 12.6 -9.2 11.1 10.4 8.2

Niger 1998 Niger 2012 NA 5.7 11.2 8.8 NA 13.7 11.1 10.7 NA -2.2 9.5 9.4 NA 3.7 9.1 8.4

Nigeria 2003 Nigeria 2013 27.6 5.7 -4.3 -4.4 20.0 26.9 33.0 28.7 18.0 11.9 5.6 4.3 11.7 13.6 7.2 4.3

Rwanda 2000 Rwanda 2010 NA 4.1 13.9 15.7 NA 12.5 12.0 11.2 NA 50.7 45.4 47.2 63.4 40.8 40.9 42.3

Tanzania 1999 Tanzania 2010 NA -5.0 -8.4 -5.9 -2.1 4.4 -3.5 -0.2 NA -11.2 3.5 5.1 -7.2 -7.3 3.2 4.6

Uganda 2000.5 Uganda 2011 NA NA 3.4 4.0 NA NA 13.1 14.5 NA 33.2 18.9 20.0 NA 31.6 17.5 20.1

Zambia 2001.5 Zambia 2013.5 NA 7.6 7.7 8.4 NA -0.1 10.6 7.3 NA 3.4 20.1 20.0 NA 1.8 18.3 17.3

Zimbabwe 1999 Zimbabwe 2010.5 NA -7.7 -5.8 -5.7 NA -0.6 -1.9 -0.5 -5.9 -8.6 -6.8 -5.5 1.0 -8.5 -5.9 -5.4

Bangladesh 2004 Bangladesh 2014 NA 20.6 35.7 38.2 25.9 21.5 34.7 29.2 41.1 31.8 22.0 26.5 23.6 26.6 25.6 28.9

Cambodia 2000 Cambodia 2014 68.2 0.6 6.1 3.1 NA 19.4 36.0 35.4 NA 40.8 41.6 42.6 NA 32.7 40.1 40.9

Nepal 2001 Nepal 2011 NA -7.5 8.6 9.6 NA 13.6 20.7 23.1 NA 19.9 23.1 28.4 NA 14.9 23.5 29.0

Philippines 2003 Philippines 2013 -5.1 2.3 9.7 3.0 1.4 10.3 3.1 4.3 6.0 21.4 26.7 22.8 1.1 12.8 17.6 13.0

Continued
64

Table 3.18—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA 0.4 NA 0.9 NA 0.8 0.0 0.6 NA -0.4 6.6 4.5 -0.4 -0.2 5.9 2.7

Colombia 2000 Colombia 2010 1.6 0.9 4.5 2.3 1.5 6.5 11.6 5.5 8.2 17.8 18.9 16.4 2.7 8.1 13.9 8.4

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 0.3 1.1 1.5 0.7 0.3 -1.5 -0.2 -0.5 -3.5 1.3 4.4 1.3 -0.7 0.5 2.5 0.7

Peru 2000 Peru 2012 12.5 22.7 28.8 21.0 25.1 34.6 39.8 37.6 33.8 33.5 42.6 43.9 14.3 24.5 39.8 34.3

Egypt 2000 Egypt 2014 5.7 12.4 29.2 9.2 8.0 16.4 28.6 12.4 20.1 29.1 34.3 29.5 12.0 24.3 33.7 21.9

Jordan 2002 Jordan 2012 0.6 -0.3 0.6 0.2 1.1 1.6 0.7 1.2 0.0 1.6 5.2 2.9 0.7 1.1 2.0 1.3

Pooled Average 4.7 4.7 8.2 6.3 5.7 11.5 16.9 13.6 14.4 22.4 11.6 12.4 7.2 14.2 14.9 14.8Note: NA indicates too few cases to calculate decadal change.
65 

Short preceding birth intervals (<36 months) 

Preceding birth intervals shorter than 36 months adversely affect child mortality and nutritional status. The 

mechanisms for these adverse effects are not fully understood. The principal way to lengthen birth intervals 

among married and cohabitating women is through contraception. While use of contraception is not 

included in this report, the prevalence of short birth intervals is a good indicator of low use of contraceptive 

health services. 

Levels 

Within large cities, the prevalence of short birth intervals is highest among extremely poor women (45%), 

followed by poor women (40%), and is lowest among non-poor women (35%). The pooled average 

prevalence is also highest among extremely poor women in other urban areas (48%) and in rural areas 

(56%) (see Figure 3.16, left panel). Across the 26 countries’ latest surveys, the prevalence of birth intervals 

less than 36 months varies from 29% of births in Bangladesh to 66% of births in Niger. For extremely poor 

women in large cities, the prevalence ranges from 23% in Bangladesh to 60% in Nigeria, as shown in Table 

3.19. The table also shows that four other countries have more than half of their births arriving in less than 

36 months after the preceding birth. 

Decadal change 

Most sub-groups experienced a decadal decrease in the prevalence of short birth intervals (see Figure 3.16, 

right panel). In both large and other urban areas, the decreases were slightly larger for extremely poor 

women, when compared with the two less poor groups. In rural areas, the decadal decrease was largest for 

moderately poor women. 

Figure 3.16. Pooled average prevalence of short birth Intervals (<36 months) (left panel) and pooled 

average decadal change in prevalence (right panel), by poverty according to level of urbanicity 

35.0 39.4

52.9

39.9 41.3 47.9 45.1 48.4

56.0

Large cities Other urban areas Rural areas

Percentage

Birth interval <36 months

Not poor Moderately poor Extremely poor

-5.6

0.2 3.6

-5.6 -5.6 -7.1 -8.4 -7.5 -4.9

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in birth interval 

<36 months

Not poor Moderately poor Extremely poor
66

Table 3.19. Short birth intervals (<36 months) by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * (23.8) 47.3 43.0 * 34.6 41.8 40.9 * 59.0 51.7 51.8 (63.6) 40.3 50.9 50.7 Burkina Faso 2010 (44.6) 30.2 34.1 34.1 * 39.6 37.1 37.3 * 54.8 52.7 52.8 39.0 46.0 50.6 50.3

Cameroon 2004 35.3 51.7 49.4 49.3 53.3 55.1 61.1 58.9 * 57.8 65.0 64.1 44.1 55.0 63.1 60.9Cameroon 2011 44.8 47.1 48.3 47.8 53.6 51.6 57.7 56.6 68.4 60.3 61.9 61.9 54.2 52.9 59.5 58.7

Cote D’Ivoire 1998-99 (23.7) 33.2 44.8 40.0 * 47.3 43.8 44.5 * 50.7 55.6 55.2 35.8 45.5 52.7 51.3Cote D’Ivoire 2011-12 (30.4) 35.8 39.5 37.9 56.4 37.8 46.4 45.3 * 51.5 50.5 50.5 41.3 42.7 48.5 47.7

Ethiopia 2000 (40.4) 42.5 43.5 43.1 * 54.2 55.4 55.0 * * 57.6 57.7 (43.2) 59.8 57.3 57.3Ethiopia 2011 * * 24.4 25.3 * 47.1 42.3 42.9 * * 57.8 57.8 * 47.2 56.0 56.0

Ghana 2003 * 28.9 38.7 36.9 * 34.3 38.6 38.0 * 42.4 47.5 47.1 * 36.5 45.0 44.1Ghana 2014 * 46.4 41.8 42.7 * 39.6 38.7 38.8 48.5 39.9 45.8 45.1 43.8 41.7 43.6 43.3

Guinea 1999 * 44.8 45.9 45.6 * 51.8 49.9 50.5 * 53.9 54.3 54.3 * 50.8 53.0 52.8Guinea 2012 * 37.1 45.0 43.7 * 42.8 40.8 41.1 * 48.4 49.2 49.2 (44.4) 44.5 47.9 47.6

Kenya 2003 40.6 44.9 56.0 51.2 * 38.1 53.6 48.8 (42.6) 48.9 62.5 61.2 37.6 46.3 61.5 59.4Kenya 2014 (37.9) 38.7 37.8 38.0 46.8 36.1 44.9 43.7 28.4 37.1 53.9 52.9 38.8 37.1 50.8 49.4

Mali 2001 47.0 54.0 55.8 54.2 (71.8) 49.6 60.4 58.7 43.3 67.3 62.1 62.3 51.5 58.3 61.6 61.0Mali 2012-13 (53.0) 39.5 48.4 47.6 * 46.0 47.7 47.4 * 48.3 58.7 58.5 57.8 45.6 57.0 56.5

Mozambique 2003 * 32.7 41.3 38.1 (18.0) 36.7 54.9 50.7 * 46.9 57.9 57.4 20.6 39.8 56.9 55.1Mozambique 2011 (38.6) 31.0 33.3 32.8 (15.9) 38.7 51.2 49.8 * 52.7 55.2 55.2 29.8 42.2 53.9 53.3

Niger 1998 * 45.4 60.0 56.1 * 61.6 65.7 65.2 * (59.8) 68.9 68.9 * 54.5 68.3 67.9Niger 2012 * 49.0 54.0 53.8 * 53.3 55.2 55.2 * (72.2) 67.4 67.4 (59.5) 57.3 66.0 65.9

Nigeria 2003 65.1 54.2 61.6 59.5 (75.4) 60.6 66.6 65.1 (61.8) 66.3 63.1 63.6 68.7 61.3 64.3 63.7Nigeria 2013 85.7 67.3 60.0 61.6 (71.5) 62.1 59.2 59.7 70.4 65.5 63.2 63.4 73.0 64.6 62.0 62.4

Rwanda 2000 * 71.4 64.3 65.3 * 76.8 66.5 68.3 * 63.9 58.7 59.0 * 67.2 59.5 60.1Rwanda 2010 (62.7) 56.5 56.9 57.2 * (57.3) 53.1 53.4 63.6 63.1 59.1 59.6 62.6 62.1 58.7 59.1

Tanzania 1999 * 27.5 (12.5) 20.9 (34.3) 41.3 36.1 38.1 * 44.7 62.1 61.7 39.5 39.4 59.3 57.5Tanzania 2010 * 21.9 35.0 29.6 26.1 37.4 46.5 42.3 42.9 37.9 61.0 59.0 35.2 34.9 58.9 55.4

Uganda 2000-01 * * 58.5 58.5 * * 63.7 63.5 * * 70.9 70.8 * * 70.1 70.0Uganda 2011 * 38.2 51.3 47.4 * 38.6 58.1 54.9 * 51.6 68.3 67.7 (47.5) 44.8 67.1 65.8

Zambia 2001-02 * (35.9) 54.5 52.4 * 50.8 52.3 51.7 * 62.3 61.4 61.4 * 51.2 59.4 58.7Zambia 2013-14 * 43.3 41.7 42.3 39.1 36.9 42.3 41.1 * 48.7 58.5 58.2 43.5 41.6 54.2 53.0

Zimbabwe 1999 * (35.7) 25.0 30.1 * 33.2 34.1 33.7 * 36.4 43.5 42.8 (45.5) 34.7 41.1 39.9Zimbabwe 2010-11 * 17.3 24.9 21.7 40.1 25.1 25.3 27.0 33.1 34.2 31.1 31.6 32.7 28.0 29.9 29.6

Bangladesh 2004 * * 34.2 34.0 25.9 31.4 41.7 38.7 (32.2) 38.1 43.3 42.9 29.2 35.3 42.8 41.9Bangladesh 2014 * 20.4 22.8 24.0 * 30.6 23.4 24.8 36.6 27.2 31.2 30.9 40.2 27.0 29.4 29.4

Cambodia 2000 * (39.8) 42.9 41.5 * (40.4) 58.4 57.6 * 53.5 54.7 54.7 * 49.4 54.9 54.7Cambodia 2014 (43.8) 31.2 25.9 31.7 45.1 28.9 38.5 36.8 49.6 39.4 36.6 37.3 47.4 36.5 36.4 36.9

Nepal 2001 * * (41.2) (47.6) * (51.1) 60.4 59.8 * 55.4 60.4 60.3 * 55.6 60.3 60.2Nepal 2011 * * (24.3) 27.4 * 46.7 46.7 46.0 (52.9) 44.1 50.7 50.2 50.5 43.2 50.1 49.5

Philippines 2003 50.5 62.7 65.0 61.7 45.0 53.1 60.6 56.6 46.6 57.0 64.3 61.4 47.0 57.0 63.3 60.0Philippines 2013 47.6 46.0 45.8 46.1 41.4 49.9 51.7 50.3 55.7 47.4 54.6 53.6 49.5 48.0 52.6 51.4

Continued
67

Table 3.19—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 45.3 (40.0) 44.0 * 54.0 52.2 53.4 * 65.7 62.1 62.7 * 52.2 59.3 56.1 Armenia 2010 (52.2) 37.5 * 42.3 62.9 24.0 (39.0) 44.9 63.3 60.6 29.6 54.8 59.0 44.9 29.0 48.1

Colombia 2000 38.5 45.7 50.5 43.2 39.2 48.0 55.9 46.8 43.4 49.7 61.3 55.5 39.6 48.0 57.9 48.9Colombia 2010 23.0 35.9 41.9 28.6 26.6 39.9 51.7 36.9 34.2 36.7 52.2 45.3 25.9 37.7 50.7 37.0

Dominican 

Republic 

2002 38.5 52.8 57.1 48.4 45.9 50.4 66.3 55.4 45.1 55.5 67.8 58.9 41.5 53.4 63.6 53.5

Dominican 

Republic 

2013 23.8 38.6 41.2 36.9 43.5 33.0 42.5 39.1 38.8 44.6 45.9 44.1 35.7 37.9 43.0 39.6

Peru 2000 32.8 34.0 40.0 35.9 37.2 31.6 51.8 45.1 (34.7) 42.1 59.1 58.3 33.3 34.6 54.3 48.2Peru 2012 24.5 22.2 29.1 24.9 22.3 26.1 34.2 29.1 (24.6) 26.6 41.2 39.2 23.4 25.1 37.8 32.2

Egypt 2000 45.4 41.2 50.0 44.9 44.8 47.2 57.7 47.6 55.5 55.4 60.7 57.8 49.6 51.8 59.8 53.6Egypt 2014 62.8 30.8 35.0 43.5 66.8 31.4 36.6 44.9 71.1 44.8 41.6 49.9 68.8 40.4 40.5 48.2

Jordan 2002 76.1 52.4 50.8 56.1 81.9 54.9 58.2 61.6 86.1 65.4 69.8 70.7 81.5 56.3 60.1 62.5Jordan 2012 79.5 48.3 55.0 57.7 80.9 52.6 54.8 58.9 81.0 47.2 58.4 57.9 80.4 50.2 55.6 58.3

Pooled Average 35.0 39.9 45.1 41.9 39.4 41.3 48.4 45.8 52.9 47.9 56.0 55.3 41.6 44.3 54.3 51.9
68

Table 3.20. Decadal change in short birth intervals (<36 months) by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA 9.1 -18.9 -12.7 NA 7.1 -6.7 -5.1 NA -6.0 1.4 1.4 -35.1 8.1 -0.4 -0.6

Cameroon 2004 Cameroon 2011 13.6 -6.6 -1.6 -2.1 0.4 -5.0 -4.9 -3.3 NA 3.6 -4.4 -3.1 14.4 -3.0 -5.1 -3.1

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 5.2 2.0 -4.1 -1.6 NA -7.3 2.0 0.6 NA 0.6 -3.9 -3.6 4.2 -2.2 -3.2 -2.8

Ethiopia 2000 Ethiopia 2011 NA NA -17.4 -16.2 NA -6.5 -11.9 -11.0 NA NA 0.2 0.1 NA -11.5 -1.2 -1.2

Ghana 2003 Ghana 2014 NA 15.9 2.8 5.3 NA 4.8 0.1 0.7 NA -2.3 -1.5 -1.8 NA 4.7 -1.3 -0.7

Guinea 1999 Guinea 2012 NA -5.9 -0.7 -1.5 NA -6.9 -7.0 -7.2 NA -4.2 -3.9 -3.9 NA -4.8 -3.9 -4.0

Kenya 2003 Kenya 2014 -2.5 -5.6 -16.5 -12.0 NA -1.8 -7.9 -4.6 -12.9 -10.7 -7.8 -7.5 1.1 -8.4 -9.7 -9.1

Mali 2001 Mali 2012.5 5.2 -12.6 -6.4 -5.7 NA -3.1 -11.0 -9.8 NA -16.5 -3.0 -3.3 5.5 -11.0 -4.0 -3.9

Mozambique 2003 Mozambique 2011 NA -2.1 -10.0 -6.6 -2.6 2.5 -4.6 -1.1 NA 7.3 -3.4 -2.7 11.5 3.0 -3.8 -2.3

Niger 1998 Niger 2012 NA 2.6 -4.3 -1.6 NA -5.9 -7.5 -7.1 NA 8.9 -1.1 -1.1 NA 2.0 -1.6 -1.4

Nigeria 2003 Nigeria 2013 20.6 13.1 -1.6 2.1 -3.9 1.5 -7.4 -5.4 8.6 -0.8 0.1 -0.2 4.3 3.3 -2.3 -1.3

Rwanda 2000 Rwanda 2010 NA -14.9 -7.4 -8.1 NA -19.5 -13.4 -14.9 NA -0.8 0.4 0.6 NA -5.1 -0.8 -1.0

Tanzania 1999 Tanzania 2010 NA -5.1 20.5 7.9 -7.5 -3.5 9.5 3.8 NA -6.2 -1.0 -2.5 -3.9 -4.1 -0.4 -1.9

Uganda 2000.5 Uganda 2011 NA 36.4 -6.9 -10.6 NA NA -5.3 -8.2 NA NA -2.5 -3.0 45.2 NA -2.9 -4.0

Zambia 2001.5 Zambia 2013.5 NA 6.2 -10.7 -8.4 NA -11.6 -8.3 -8.8 NA -11.3 -2.4 -2.7 NA -8.0 -4.3 -4.8

Zimbabwe 1999 Zimbabwe 2010.5 NA -16.0 -0.1 -7.3 NA -7.0 -7.7 -5.8 NA -1.9 -10.8 -9.7 -11.1 -5.8 -9.7 -9.0

Bangladesh 2004 Bangladesh 2014 NA NA -11.4 -10.0 NA -0.8 -18.3 -13.9 4.4 -10.9 -12.1 -12.0 11.0 -8.3 -13.4 -12.5

Cambodia 2000 Cambodia 2014 31.3 -6.1 -12.1 -7.0 32.2 -8.2 -14.2 -14.9 NA -10.1 -12.9 -12.4 NA -9.2 -13.2 -12.7

Nepal 2001 Nepal 2011 NA NA -16.9 -20.2 NA -4.4 -13.7 -13.8 NA -11.3 -9.7 -10.1 NA -12.4 -10.2 -10.7

Philippines 2003 Philippines 2013 -2.9 -16.7 -19.2 -15.6 -3.6 -3.2 -8.9 -6.3 9.1 -9.6 -9.7 -7.8 2.5 -9.0 -10.7 -8.6

Continued
69

Table 3.20—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA -7.8 NA -1.7 NA -30.0 -13.2 -8.5 NA -5.1 -32.5 -7.9 NA -7.3 -30.3 -8.0

Colombia 2000 Colombia 2010 -15.5 -9.8 -8.6 -14.6 -12.6 -8.1 -4.2 -9.9 -9.2 -13.0 -9.1 -10.2 -13.7 -10.3 -7.2 -11.9

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 -13.4 -12.9 -14.5 -10.5 -2.2 -15.8 -21.6 -14.8 -5.7 -9.9 -19.9 -13.5 -5.3 -14.1 -18.7 -12.6

Peru 2000 Peru 2012 -6.9 -9.8 -9.1 -9.2 -12.4 -4.6 -14.7 -13.3 -8.4 -12.9 -14.9 -15.9 -8.3 -7.9 -13.8 -13.3

Egypt 2000 Egypt 2014 12.4 -7.4 -10.7 -1.0 15.7 -11.3 -15.1 -1.9 11.1 -7.6 -13.6 -5.6 13.7 -8.1 -13.8 -3.9

Jordan 2002 Jordan 2012 3.4 -4.1 4.2 1.6 -1.0 -2.3 -3.4 -2.7 -5.1 -18.2 -11.4 -12.8 -1.1 -6.1 -4.5 -4.2

Pooled Average -5.6 -5.6 -7.1 -6.7 0.2 -5.6 -8.4 -7.0 3.6 -7.5 -4.9 -5.0 -0.6 -6.0 -5.8 -5.8Note: NA indicates too few cases to calculate decadal change.
70 

Child illness prevention and treatment 

Full basic immunization 

The DHS Program considers full basic vaccination to be a dose of bacille Calmette-Guerin (BCG), three 

doses of diphtheria, tetanus, and pertussis (DPT) vaccine, three doses of polio vaccine, and a dose of 

measles vaccine. This full basic vaccination is measured for children age 12 to 23 months, except in Latin 

America and the Caribbean where the age range for measurement is 18 to 29 months due to the PAHO 

recommendation to give the measles vaccine at 12-14 months. 

In large cities, the average pooled decadal improvement in coverage is closely associated with poverty 

level, with the greatest gains made among the non-poor (34 percentage points), the next greatest gains made 

among the moderately poor (17 percentage points), and the least gains made among the extremely poor (6 

percentage points). However, vaccination coverage fell in five countries for the extremely poor children in 

large cities: Mali, Mozambique, Peru, Guinea, and Zambia (see Table 3.22). The average pooled gains were 

also inequitable in other urban areas and rural areas (see Figure 3.17, right panel) with an 11 percentage 

point gap between the non-poor and the extremely poor in the other urban areas, and 14 percentage point 

gap in rural areas. 

Levels 

In contrast to the patterns observed for ANC and delivery care, coverage of full basic vaccination does not 

vary substantially across poverty levels in urban areas, either in large cities or other areas (see Figure 3.17, 

left panel). For all poverty groups in all urban areas, the average pooled coverage is around 50%. In rural 

areas, coverage is lowest for extremely poor children at 33%. 

By country in the latest surveys, there is great variation in coverage of full basic vaccination (see Table 

3.21). The level of vaccination is 80% or greater in only seven countries: Burkina Faso, Armenia, 

Bangladesh, Nepal, Egypt, Rwanda, and Jordan. At the other end of the range, five countries have less than 

50% of their children with full basic vaccination: Ethiopia, Nigeria, Guinea, Mali, and the Dominican 

Republic. For extremely poor urban children, 15 countries do not reach the 80% level. 

Decadal change 

In large cities, the average pooled decadal improvement in coverage is closely associated with poverty 

level, with the greatest gains made among the non-poor (34 percentage points), the next greatest gains made 

among the moderately poor (17 percentage points), and the least gains made among the extremely poor (6 

percentage points). However, vaccination coverage fell in five countries for the extremely poor children in 

large cities: Mali, Mozambique, Peru, Guinea, and Zambia (see Table 3.22). The average pooled gains were 

also inequitable in other urban areas and rural areas (see Figure 3.17, right panel) with an 11 percentage 

point gap between the non-poor and the extremely poor in the other urban areas, and 14 percentage point 

gap in rural areas. 

Figure 3.17. Pooled average coverage of full basic immunization (left panel) and pooled average 

decadal change in coverage (right panel), by poverty according to level of urbanicity 

49.4

60.1 54.7 54.4 60.2

49.5 51.8 51.0

33.1

Large cities Other urban areas Rural areas

Percentage

Full basic vaccination

Not poor Moderately poor Extremely poor

34.4 30.2 28.6

17.4

24.9 25.2

6.4

19.1 14.6

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in full basic 

vaccination

Not poor Moderately poor Extremely poor
71

Table 3.21. Full basic immunization by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * * (61.8) (68.4) * (71.1) 54.3 58.0 * (61.2) 40.5 41.2 * 69.8 42.2 43.9 Burkina Faso 2010 * (94.4) 80.6 80.2 * 80.7 83.2 82.7 * 90.4 80.8 81.3 (63.0) 88.6 81.1 81.3 

Cameroon 2004 * 57.8 55.7 58.5 * 60.0 50.8 53.4 * 51.8 41.2 42.4 (58.1) 57.4 44.8 48.2 

Cameroon 2011 (68.3) 68.1 60.0 63.1 (84.3) 74.2 58.5 62.9 * 56.5 44.8 46.1 75.8 66.9 49.8 53.2 

Cote D’Ivoire 1998-99 * (78.5) 70.4 73.3 * (66.2) 63.3 65.7 * * 39.6 41.8 * 64.9 46.4 50.7 Cote D’Ivoire 2011-12 * (65.0) 78.4 73.9 * 62.0 52.1 55.2 * 66.0 39.8 42.2 (71.1) 64.3 47.0 50.5 

Ethiopia 2000 * * 74.8 73.8 * (53.2) 34.4 36.6 * * 11.0 11.0 * 46.2 13.6 14.3 

Ethiopia 2011 * * 78.0 78.7 * (76.7) 39.9 42.5 * * 20.3 20.4 * (71.6) 23.6 24.3 

Ghana 2003 * (58.6) 76.4 71.1 * (69.7) 82.8 79.5 * 75.1 64.8 66.0 * 68.6 69.4 69.4 Ghana 2014 * (68.4) 81.5 77.0 * 75.7 74.7 75.1 * 75.5 79.3 78.4 (76.6) 73.5 78.7 77.3 

Guinea 1999 * (48.4) 51.9 51.1 * * 41.6 43.3 * (37.6) 25.9 26.7 * 43.8 30.8 32.2 

Guinea 2012 * (52.0) 39.1 43.5 * (66.2) 41.8 46.8 * 38.0 33.1 33.5 * 48.1 34.8 36.5 

Kenya 2003 * (59.7) 56.2 56.9 * (61.5) 40.3 49.7 * 62.4 50.0 51.5 (65.1) 61.7 49.6 51.8 Kenya 2014 * 70.2 65.1 66.8 78.7 78.6 70.9 73.6 (90.6) 81.1 70.2 71.2 76.7 77.0 69.8 71.1 

Mali 2001 (43.2) 60.7 64.4 60.8 * (54.3) 36.3 40.3 * 24.0 20.9 21.5 (51.6) 46.2 25.5 28.7 

Mali 2012-13 * 53.1 43.3 45.7 * (56.6) 48.9 50.1 * 43.2 36.2 36.6 * 48.9 38.0 38.9 

Mozambique 2003 * (88.0) 91.7 91.3 * 89.2 74.6 78.1 * 66.4 55.2 56.0 * 80.6 60.8 63.3 Mozambique 2011 * 72.7 77.8 76.7 * 68.0 75.8 74.8 * (69.9) 59.7 60.0 (74.7) 69.7 63.7 64.1 

Niger 1998 * (81.3) 68.4 71.3 * (59.2) 42.6 46.5 * * 10.0 10.5 * 65.3 15.9 18.4 Niger 2012 * (69.0) 73.0 72.5 * (77.3) 63.4 65.7 * * 48.7 49.1 * 75.5 51.1 52.0 

Nigeria 2003 * 28.8 26.2 28.9 * 22.7 10.3 14.6 * 12.2 4.1 5.4 (25.2) 21.4 8.8 12.9 Nigeria 2013 * 67.9 36.2 45.8 * 51.4 37.8 41.1 49.3 30.0 13.3 15.8 50.1 44.9 20.9 25.3 

Rwanda 2000 * (80.0) 63.0 64.8 * * 82.9 82.4 * 84.4 74.6 75.8 * 83.2 74.9 76.0 

Rwanda 2010 * (98.7) 92.1 94.9 * * 91.0 91.3 * 93.2 88.9 89.7 (100.0) 93.9 89.1 90.1 

Tanzania 1999 * * * (69.6) * (77.3) 89.5 85.0 * * 65.3 65.5 * 77.7 67.5 68.3 Tanzania 2010 * (92.9) (83.8) 88.7 * 84.2 82.1 83.4 (68.9) 80.0 72.0 72.7 80.2 84.5 73.3 75.2 

Uganda 2000-01 * * 43.8 42.7 * * 41.6 41.6 * * 36.0 50.2 * * 36.7 36.7 Uganda 2011 * (71.8) 52.7 63.4 * (67.3) 55.8 58.9 * (46.7) 50.3 36.0 * 58.2 50.7 51.6 

Zambia 2001-02 * * 78.3 75.0 * 86.7 72.8 77.6 * (87.2) 66.5 67.2 * 83.3 68.3 70.0 Zambia 2013-14 * 65.8 74.4 71.0 84.9 78.1 78.4 78.9 * 66.5 64.5 64.5 79.6 70.8 67.6 68.3 

Zimbabwe 1999 * * * (50.0) * 70.3 76.0 72.0 * (48.4) 64.7 63.6 * 61.7 64.8 64.0 

Zimbabwe 2010-11 * (66.5) (67.5) 67.7 (65.4) 69.5 78.4 72.0 69.8 68.3 60.3 62.3 69.0 68.2 62.5 64.5 

Bangladesh 2004 * * (84.7) (84.4) (97.9) 95.8 72.0 80.3 * 82.2 69.9 71.1 (93.9) 88.4 70.6 73.1 Bangladesh 2014 * (79.9) 89.5 87.0 * 90.3 86.5 87.8 93.6 90.3 80.1 82.5 94.3 89.1 81.8 83.8 

Continued
72

Table 3.21—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Cambodia 2000 * * * * * * 40.5 39.5 * 41.6 38.6 39.0 * 44.7 39.3 39.9 

Cambodia 2014 * (93.7) * 93.3 77.1 84.7 77.7 79.6 83.5 76.4 69.1 71.2 86.9 79.9 70.0 73.4Nepal 2001 * * * * * * 71.4 72.3 * (89.8) 64.2 65.0 * (87.6) 64.7 65.6Nepal 2011 * * * (90.6) * (89.6) 88.6 89.6 (100.0) 95.5 84.8 86.6 (100.0) 94.5 84.9 87.0

Philippines 2003 86.6 78.7 72.0 77.8 87.7 69.9 69.7 72.6 81.7 73.5 58.2 65.1 85.0 73.3 63.7 69.8Philippines 2013 (76.8) 88.4 79.5 81.5 84.0 81.7 73.1 77.1 77.4 84.2 70.0 74.4 79.3 84.3 72.4 76.5

Armenia 2000 * (75.6) * 73.3 * 72.7 * 73.1 * (75.9) 68.0 69.1 * 74.3 69.1 71.4Armenia 2010 (81.8) * * 80.6 84.9 (86.4) * 83.9 (68.4) 88.1 * 80.9 78.9 86.6 (78.9) 81.6

Colombia 2000 10.7 17.4 (18.1) 13.8 15.0 23.2 10.1 16.3 17.7 10.5 12.2 25.3 13.5 17.4 12.6 14.4Colombia 2010 71.3 69.7 54.7 68.9 70.0 69.7 60.4 68.0 62.0 71.2 63.9 65.8 69.7 70.2 61.3 67.7

Dominican 

Republic 

2002 45.9 28.9 19.0 34.9 46.2 35.3 37.9 39.6 41.1 34.2 26.1 36.5 44.9 32.1 26.1 34.9

Dominican 

Republic 

2013 (51.2) (32.0) (33.1) 37.9 44.7 42.7 44.1 43.8 58.5 54.8 41.3 63.6 50.5 41.6 39.2 43.6

Peru 2000 63.6 59.0 56.8 60.0 (57.5) 74.2 57.9 62.6 * 60.6 50.4 59.6 63.6 61.6 52.7 56.4Peru 2012 69.0 (61.1) (41.1) 61.3 61.6 68.3 64.4 64.8 * 70.3 60.7 71.5 65.1 66.5 60.0 62.7

Egypt 2000 93.4 91.8 (87.9) 92.5 93.4 93.8 89.7 93.0 93.5 90.5 91.5 91.7 93.4 91.3 91.1 92.2Egypt 2014 92.3 87.3 * 91.6 88.8 88.1 87.6 88.4 90.0 89.6 88.1 89.3 90 89.1 88.5 89.3

Jordan 2002 (43.2) (33.1) (41.9) 38.2 39.0 26.2 32.5 32.4 6.9 9.0 4.7 6.8 33.3 24.3 27.1 27.9Jordan 2012 90.0 92.7 (93.4) 91.7 95.2 94.2 92.5 94.0 96.6 94.0 86.6 92.8 93.3 93.7 91.5 93.0

Pooled Average 49.4 54.7 51.8 54.1 60.1 60.2 51.0 57.6 54.4 49.5 33.1 36.1 59.0 57.2 40.2 45.0
73

Table 3.22. Decadal change in full basic immunization by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA NA 26.9 16.9 NA 13.7 41.3 35.3 NA 41.7 57.6 57.2 NA 26.9 55.6 53.4

Cameroon 2004 Cameroon 2011 NA 14.7 6.1 6.6 NA 20.3 11.0 13.6 NA 6.7 5.1 5.3 25.3 13.6 7.1 7.1

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA -10.4 6.2 0.5 NA -3.2 -8.6 -8.1 NA NA 0.2 0.3 NA -0.5 0.5 -0.2

Ethiopia 2000 Ethiopia 2011 NA NA 2.9 4.5 NA 21.4 5.0 5.4 NA NA 8.5 8.5 NA 23.1 9.1 9.1

Ghana 2003 Ghana 2014 NA 8.9 4.6 5.4 NA 5.5 -7.4 -4.0 NA 0.4 13.2 11.2 NA 4.5 8.5 7.2

Guinea 1999 Guinea 2012 NA 2.8 -9.8 -5.8 NA NA 0.2 2.7 NA 0.3 5.5 5.2 NA 3.3 3.1 3.3

Kenya 2003 Kenya 2014 NA 9.5 8.1 9.0 NA 15.5 27.8 21.7 NA 17.0 18.4 17.9 10.5 13.9 18.4 17.5

Mali 2001 Mali 2012.5 NA -6.6 -18.3 -13.1 NA 2.0 11.0 8.5 NA 16.7 13.3 13.1 NA 2.3 10.9 8.9

Mozambique 2003 Mozambique 2011 NA -19.1 -17.4 -18.3 NA -26.5 1.5 -4.1 NA 4.4 5.6 5.0 NA -13.6 3.6 1.0

Niger 1998 Niger 2012 NA -8.8 3.3 0.9 NA 12.9 14.9 13.7 0.0 NA 27.6 27.6 NA 7.3 25.1 24.0

Nigeria 2003 Nigeria 2013 NA 39.1 10.0 16.9 NA 28.7 27.5 26.5 NA 17.8 9.2 10.3 24.9 23.5 12.1 12.4

Rwanda 2000 Rwanda 2010 NA 18.7 29.1 30.1 NA NA 8.1 8.9 NA 8.8 14.3 13.9 NA 10.7 14.2 14.1

Tanzania 1999 Tanzania 2010 NA NA NA 17.4 NA 6.3 -6.7 -1.5 NA NA 6.1 6.5 NA 6.2 5.3 6.3

Uganda 2000.5 Uganda 2011 NA NA 8.5 19.7 NA NA 13.5 16.5 NA NA 13.6 -13.5 NA NA 13.3 14.2

Zambia 2001.5 Zambia 2013.5 NA NA -3.2 -3.3 NA -7.2 4.7 1.1 NA -17.3 -1.7 -2.3 NA -10.4 -0.6 -1.4

Zimbabwe 1999 Zimbabwe 2010.5 NA NA NA 15.4 NA -0.7 2.1 0.0 NA 17.3 -3.8 -1.1 NA 5.7 -2.0 0.4

Bangladesh 2004 Bangladesh 2014 NA NA 4.8 2.6 NA -5.5 14.5 7.5 NA 8.1 10.2 11.4 0.4 0.7 11.2 10.7

Cambodia 2000 Cambodia 2014 NA NA NA NA 55.1 NA 26.6 28.6 NA 24.9 21.8 23.0 NA 25.1 21.9 23.9

Nepal 2001 Nepal 2011 NA NA NA NA NA NA 17.2 17.3 100.0 5.7 20.6 21.7 NA 6.9 20.2 21.4

Philippines 2003 Philippines 2013 -9.8 9.7 7.5 3.7 -3.7 11.8 3.4 4.5 -4.3 10.7 11.8 9.2 -5.7 11.0 8.7 6.7

Continued
74

Table 3.22—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA NA NA 7.3 NA 13.7 NA 10.8 NA 12.2 NA 11.8 NA 12.3 9.8 10.2

Colombia 2000 Colombia 2010 60.6 52.3 36.6 55.1 55.0 46.5 50.3 51.7 44.3 60.7 51.7 40.5 56.2 52.8 48.7 53.3

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 4.8 2.8 12.8 2.7 -1.4 6.7 5.6 3.8 15.8 18.7 13.8 24.6 5.1 8.6 11.9 7.9

Peru 2000 Peru 2012 4.5 1.8 -13.1 1.1 3.4 -4.9 5.4 1.8 NA 8.1 8.6 9.9 1.2 4.1 6.1 5.3

Egypt 2000 Egypt 2014 -0.8 -3.2 NA -0.6 -3.3 -4.1 -1.5 -3.3 -2.5 -0.6 -2.4 -1.7 -2.4 -1.6 -1.9 -2.1

Jordan 2002 Jordan 2012 46.8 59.6 51.5 53.5 56.2 68.0 60.0 61.6 89.7 85.0 81.9 86.0 60.0 69.4 64.4 65.1

Pooled Average 34.4 17.4 6.4 14.8 30.2 24.9 19.1 18.3 28.6 25.2 14.6 14.2 28.1 22.1 14.9 16.4Note: NA indicates too few cases to calculate decadal change.
75 

Fever seen medically 

Levels 

In large cities, the pooled average level of coverage of medical care for fever is closely associated with 

household poverty. Children in extremely poor households are the least likely to receive medical treatment 

for fever (47%) when compared with their moderately poor (52%) and not poor (58%) counterparts. The 

pattern in other urban areas is similar (see Figure 3.18, left panel). Among the extremely poor children in 

large cities who were sick with fever, less than 50% were seen medically in Cameroon and Cote d’Ivoire 

(Table 3.23). 

Urban children (in large cities or other urban areas) who are moderately or extremely poor are more likely 

to receive medical care for fever than their rural poor counterparts. In almost half of the countries, the rural 

extremely poor children are less likely than not to receive medical attention for their fever. 

Decadal change 

In large cities, the decadal change in medical fever care seeking coverage was concentrated in extremely 

poor households (13 percentage point increase, as compared with 4% in moderately poor households, and 

1% in non-poor households). In all but three countries with available data, the decadal change is positive; 

in four countries, there is a more than a 20 percentage point increase (see Table 3.24). A similar pattern is 

evident in other urban areas, while the opposite pattern was found in rural areas, where the greatest decadal 

increases were observed for children in non-poor households (see Figure 3.18, right panel). 

Figure 3.18. Pooled average coverage of care seeking from a medical source for children under age 

5 with fever (left panel) and pooled average decadal change in coverage (right panel), by poverty 

according to level of urbanicity 

57.9 59.1

51.7 51.5 55.5

45.0 46.8 46.5

25.9

Large cities Other urban areas Rural areas

Percentage

Fever seen medically

Not poor Moderately poor Extremely poor

0.8 6.6

20.6

3.8 9.2

17.1 13.3 11.4 16.0

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in fever seen 

medically

Not poor Moderately poor Extremely poor
76

Table 3.23. Coverage of care seeking from a medical source for children under age 5 with fever by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * * (59.8) 59.2 * 54.6 52.7 53.0 * 52.2 29.8 30.5 * 53.1 31.8 33.0 Burkina Faso 2010 * (67.3) 50.8 54.3 * 72.9 64.7 66.2 * 66.5 50.5 51.5 (48.6) 68.4 52.0 53.4

Cameroon 2004 * 55.1 42.4 51.2 * 43.0 42.4 43.1 * 45.8 35.5 36.8 (61.1) 47.2 37.8 40.9Cameroon 2011 (30.4) 39.6 36.1 36.7 * 40.6 30.8 33.5 * 39.9 20.3 21.7 42.6 40.1 24.5 26.9

Cote D’Ivoire 1998-99 * (19.1) 29.3 26.0 * (22.3) 22.5 23.2 * (30.0) 14.3 16.3 (35.2) 25.3 16.9 18.7Cote D’Ivoire 2011-12 * (55.6) 36.3 41.1 (39.6) 46.9 38.3 40.5 * 51.0 27.5 29.3 (37.2) 50.6 30.8 33.8

Ethiopia 2000 * * 56.5 57.5 * (67.3) 46.9 48.1 * * 14.7 14.8 * 50.4 17.5 18.0Ethiopia 2011 * * (67.8) (67.3) * (79.8) 29.9 33.9 * * 22.3 22.4 * 66.4 23.6 24.2

Ghana 2003 * * 59.9 58.4 * (56.7) 52.9 53.7 * 47.6 40.9 41.8 * 50.7 46.0 46.8Ghana 2014 * (68.9) 58.9 62.6 * (83.0) 82.8 82.9 * 79.0 73.1 74.3 * 77.0 72.7 73.8

Guinea 1999 * 35.2 32.9 33.8 * (30.0) 34.6 33.7 * 26.0 15.4 16.1 * 29.2 19.4 20.4Guinea 2012 * (64.6) 54.5 56.1 * (65.4) 44.1 49.0 * 39.5 27.3 28.2 * 52.0 31.3 33.4

Kenya 2003 (61.9) 55.0 59.0 58.1 * 42.3 48.4 48.9 * 54.6 43.4 44.7 68.1 52.4 44.8 46.3Kenya 2014 * (72.6) 62.9 66.1 81.4 59.1 58.4 60.5 (67.4) 72.0 61.9 62.6 77.9 66.8 61.4 62.5

Mali 2001 (52.1) 50.8 41.4 47.0 * 28.1 25.9 28.0 * 18.2 9.0 9.3 44.1 35.8 12.2 15.3Mali 2012-13 * * 51.8 55.2 * * 38.1 41.7 * * 23.3 23.6 * (52.5) 26.7 28.3

Mozambique 2003 * 67.4 61.9 64.0 * 72.9 63.2 65.1 * 58.6 44.6 45.9 * 65.1 49.3 51.4Mozambique 2011 * * (72.0) 67.3 * (69.9) 72.5 72.1 * * 50.1 49.9 * 59.6 55.6 55.7

Niger 1998 * 40.7 27.7 32.2 * (28.1) 21.2 22.0 * * 6.7 6.8 * 29.9 8.6 9.4Niger 2012 * (52.7) 61.0 59.3 * * 61.8 64.1 * * 49.1 49.3 * 64.3 50.7 51.0

Nigeria 2003 * 52.9 38.9 47.4 * 44.9 29.4 35.0 * 34.0 23.3 25.9 50.8 42.6 26.9 32.1Nigeria 2013 * 60.7 70.7 68.6 * 73.8 65.0 66.7 (76.9) 75.1 61.2 62.8 80.0 72.2 62.8 64.3

Rwanda 2000 * * 18.4 18.8 * * 9.3 9.5 * 10.2 6.4 6.7 * 10.6 7.0 7.3Rwanda 2010 * (61.1) 54.6 56.8 * * (55.6) 54.1 * 55.6 38.4 40.8 * 56.1 40.2 42.7

Tanzania 1999 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NATanzania 2010 * (43.5) (58.4) 50.2 * 61.4 46.6 52.6 (31.8) 25.4 13.9 15.0 58.3 42.1 20.4 24.5

Uganda 2000-01 * * 84.2 84.2 * * 77.5 77.5 * * 65.8 79.3 * * 67.1 67.1Uganda 2011 * (91.3) 86.2 88.2 * (89.4) 86.1 86.7 * 83.9 79.1 65.8 * 86.3 79.7 80.1

Zambia 2001-02 * * 62.5 64.3 * 79.5 67.0 69.9 * (87.5) 63.2 63.8 * 80.7 63.7 64.8Zambia 2013-14 * (82.3) 70.1 74.4 (77.4) 77.5 77.0 77.1 * 82.1 69.5 70.0 (82.8) 80.0 70.8 71.9

Zimbabwe 1999 * (60.0) * 51.0 * 52.0 37.1 44.0 * (49.9) 45.4 46.0 * 53.7 44.2 46.2Zimbabwe 2010-11 * * * (29.3) * (31.6) (23.9) 27.9 * 27.3 37.8 35.6 (37.9) 25.7 36.0 33.7

Bangladesh 2004 * * 27.1 28.9 (68.2) 47.0 24.4 32.6 (26.4) 22.4 13.7 14.4 46.6 33.8 15.5 18.0Bangladesh 2014 * 68.3 58.9 62.9 * 52.3 57.8 57.2 48.3 48.9 55.4 54.2 53.3 52.7 56.0 55.4

Cambodia 2000 * (42.6) (28.0) 34.5 * * 42.9 44.7 * 39.7 32.4 32.9 * 42.7 33.3 34.1Cambodia 2014 (74.5) 52.2 (52.1) 56.9 57.5 57.3 60.9 59.2 50.8 61.4 61.9 61.1 56.6 59.1 61.5 60.6

Nepal 2001 * * * * * * 29.0 31.8 * 27.6 24.4 24.4 * 32.0 24.7 25.0Nepal 2011 * * * * * (60.6) 51.4 55.1 * 49.1 38.3 40.5 (63.5) 49.9 39.3 41.9

Philippines 2003 (64.3) 44.5 47.5 50.7 51.3 54.3 46.5 49.7 45.2 49.8 40.8 43.3 52.5 50.8 43.1 46.3Philippines 2013 (54.0) (57.4) 58.9 57.7 44.1 51.0 49.9 49.5 57.1 47.4 48.1 48.8 52.2 50.1 49.8 50.1

Continued
77

Table 3.23—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * 33.3 * 32.8 * (24.1) * 27.3 * * 17.0 19.0 * 30.1 22.0 25.7 Armenia 2010 (64.6) * * (63.3) (40.3) (52.4) * 48.2 * * * 42.9 57.9 47.6 * 54.1

Colombia 2000 53.8 49.8 36.8 50.0 52.5 55.9 44.3 51.0 43.9 33.6 24.9 31.0 52.0 47.6 34.3 45.4Colombia 2010 56.0 52.3 50.6 54.4 58.8 61.6 53.8 58.5 50.0 47.8 41.3 44.7 56.5 55.3 46.9 53.5

Dominican 

Republic 

2002 60.4 61.0 65.2 61.9 74.7 66.6 62.0 67.4 74.5 59.8 57.7 62.1 66.5 61.7 61.1 63.1

Dominican 

Republic 

2013 (57.8) (54.7) (71.3) 61.8 64.8 66.4 59.5 63.6 76.9 65.8 75.1 73.3 65.7 61.2 68.1 65.1

Peru 2000 71.5 57.9 55.6 61.7 (66.8) 60.1 49.4 54.0 * 69.1 47.8 48.5 70.1 59.7 49.6 54.0Peru 2012 61.3 (58.3) (62.2) 60.7 68.6 54.2 48.3 54.8 * 67.2 52.4 53.7 63.8 57.7 52.0 55.8

Egypt 2000 41.4 * * 39.6 42.5 36.1 30.2 39.6 31.7 36.9 30.7 32.7 37.2 37.6 30.0 35.1Egypt 2014 68.5 68.0 (62.0) 67.5 64.0 68.6 66.3 66.2 73.9 67.0 63.2 68.2 71.0 67.4 63.7 67.7

Jordan 2002 * * * (73.6) 63.3 62.7 73.6 67.4 (66.9) (68.1) 71.4 69.4 69.0 65.3 72.4 69.1Jordan 2012 (71.5) 58.2 (75.8) 66.9 68.8 67.5 61.7 66.1 76.6 82.3 87.7 81.7 71.1 66.5 70.1 68.8

Pooled Average 57.9 51.7 46.8 50.9 59.1 55.5 46.5 50.8 51.5 45.0 25.9 27.7 57.4 50.4 30.4 34.4
78

Table 3.24. Decadal change in coverage of care seeking from a medical source for children under age 5 with fever by poverty according to level of 

urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA NA -12.9 -7.0 NA 26.1 17.1 18.9 NA 20.4 29.6 30.0 NA 21.9 28.9 29.1

Cameroon 2004 Cameroon 2011 NA -22.1 -9.0 -20.7 NA -3.4 -16.6 -13.7 NA -8.4 -21.7 -21.6 -26.4 -10.1 -19.0 -20.0

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA 28.1 5.4 11.6 NA 18.9 12.2 13.3 NA 16.2 10.2 10.0 1.5 19.5 10.7 11.6

Ethiopia 2000 Ethiopia 2011 NA NA 10.3 8.9 NA 11.4 -15.5 -12.9 NA NA 6.9 7.0 NA 14.5 5.5 5.6

Ghana 2003 Ghana 2014 NA NA -0.9 3.8 NA 23.9 27.2 26.5 NA 28.5 29.3 29.6 NA 23.9 24.3 24.5

Guinea 1999 Guinea 2012 NA 22.6 16.6 17.2 NA 27.2 7.3 11.8 NA 10.4 9.2 9.3 NA 17.5 9.2 10.0

Kenya 2003 Kenya 2014 NA 16.0 3.5 7.3 NA 15.3 9.1 10.5 NA 15.8 16.8 16.3 8.9 13.1 15.1 14.7

Mali 2001 Mali 2012.5 NA NA 9.0 7.1 NA NA 10.6 11.9 NA NA 12.4 12.4 NA 14.5 12.6 11.3

Mozambique 2003 Mozambique 2011 NA NA 12.6 4.1 NA -3.8 11.6 8.8 NA NA 6.9 5.1 NA -6.9 7.9 5.4

Niger 1998 Niger 2012 NA 8.6 23.8 19.4 NA NA 29.0 30.1 0.0 NA 30.3 30.4 NA 24.6 30.1 29.7

Nigeria 2003 Nigeria 2013 NA 7.8 31.8 21.2 NA 28.9 35.6 31.7 NA 41.1 37.9 36.9 29.2 29.6 35.9 32.2

Rwanda 2000 Rwanda 2010 NA NA 36.2 38.0 0.0 NA 46.3 44.6 NA 45.4 32.0 34.1 NA 45.5 33.2 35.4

Tanzania 1999 Tanzania 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAUganda 2000.5 Uganda 2011 NA 87.0 1.9 3.8 NA NA 8.2 8.8 NA NA 12.7 -12.8 NA NA 12.0 12.4Zambia 2001.5 Zambia 2013.5 NA NA 6.3 8.4 NA -1.7 8.3 6.0 NA -4.5 5.3 5.2 NA -0.6 5.9 5.9

Zimbabwe 1999 Zimbabwe 2010.5 NA NA NA -18.9 NA -17.7 -11.5 -14.0 NA -19.7 -6.6 -9.0 NA -24.3 -7.1 -10.9

Bangladesh 2004 Bangladesh 2014 NA NA 31.8 34.0 NA 5.3 33.4 24.6 21.9 26.5 41.7 39.8 6.7 18.9 40.5 37.4

Cambodia 2000 Cambodia 2014 53.2 6.9 17.2 16.0 41.1 NA 12.9 10.4 36.3 15.5 21.1 20.1 40.4 11.7 20.1 18.9

Nepal 2001 Nepal 2011 NA NA NA NA NA NA 22.4 23.3 NA 21.5 13.9 16.0 NA 17.9 14.6 16.9

Philippines 2003 Philippines 2013 -10.3 12.9 11.4 7.0 -7.2 -3.3 3.4 -0.2 11.9 -2.4 7.3 5.5 -0.3 -0.7 6.7 3.8

Continued
79

Table 3.24—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA NA NA 30.5 NA 28.3 NA 20.9 NA NA NA 23.9 NA 17.5 NA 28.4

Colombia 2000 Colombia 2010 2.2 2.5 13.8 4.4 6.3 5.7 9.5 7.5 6.1 14.2 16.4 13.7 4.5 7.7 12.6 8.1

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 -2.4 -5.7 5.5 -0.1 -9.0 -0.2 -2.3 -3.5 2.2 5.5 15.8 10.2 -0.7 -0.5 6.4 1.8

Peru 2000 Peru 2012 -8.5 0.3 5.5 -0.8 1.5 -4.9 -0.9 0.7 NA -1.6 3.8 4.4 -5.3 -1.7 2.0 1.5

Egypt 2000 Egypt 2014 19.4 NA NA 19.9 15.4 23.2 25.8 19.0 30.1 21.5 23.2 25.3 24.1 21.3 24.1 23.3

Jordan 2002 Jordan 2012 NA NA NA -6.7 5.5 4.8 -11.9 -1.3 9.7 14.2 16.3 12.3 2.1 1.2 -2.3 -0.3

Poooled Average 0.8 3.8 13.3 9.1 6.6 9.2 11.4 9.3 20.6 17.1 16.0 15.0 9.4 11.6 15.4 14.7Note: NA indicates too few cases to calculate decadal change.
80 

Seen medically for symptoms of ARI and diarrhea 

Levels 

The patterns in coverage of medical care seeking for children’s symptoms of ARI and diarrhea closely 

follow those described for fever (see Figures 3.19 and 3.20, left panels). Tables 3.25 and 3.27 show 

differentials in care seeking coverage by poverty and level of urbanicity within the study countries. 

Decadal change 

For both symptoms of ARI and diarrhea, increases in care seeking were greatest for children in extremely 

poor households, and were concentrated in rural areas (see Figures 3.19 and 3.20, right panels). Overall, 

there was less decadal improvement in medical care seeking for children’s symptoms of ARI than for fever 

or diarrhea. Tables 3.26 and 3.28 show country-specific differentials in the decadal changes in care seeking 

coverage by poverty and level of urbanicity. 

Figure 3.19. Pooled average coverage of care seeking from a medical source for children under age 

5 with symptoms of ARI (left panel) and pooled average decadal change in coverage (right panel), 

by poverty according to level of urbanicity 

Figure 3.20. Pooled average coverage of care seeking from a medical source for children under age 

5 with diarrhea (left panel) and pooled average decadal change in coverage (right panel), by poverty 

according to level of urbanicity 

24.8

35.3 33.4

21.0 21.2 18.5 23.2 27.8

16.1

Large cities Other urban areas Rural areas

Percentage

Symptoms of ARI seen medically

Not poor Moderately poor Extremely poor

12.8 12.4

24.0

14.9 19.4 26.0

17.2

25.0 30.5

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in symptoms of 

ARI seen medically

Not poor Moderately poor Extremely poor

41.8 47.2 44.8 39.5 43.1

32.4 35.5 40.5

21.0

Large cities Other urban areas Rural areas

Percentage

Diarrhea seen medically

Not poor Moderately poor Extremely poor

5.9 11.3 8.2 9.1 12.4 15.3 11.0 14.4 20.3

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in diarrhea seen 

medically

Not poor Moderately poor Extremely poor
81

Table 3.25. Coverage of care seeking from a medical source for children under age 5 with symptoms of ARI by poverty according to level of 

urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * * * * * * 57.8 59.2 * * 30.4 31.7 * (68.1) 33.7 35.9 Burkina Faso 2010 * * (41.9) (46.8) * (74.1) 58.6 62.1 * (50.8) 47.0 47.4 * 59.4 47.7 49.2

Cameroon 2004 * 62.0 (45.9) 56.7 * 42.0 45.2 43.4 * 44.6 33.4 34.5 * 49.3 37.6 40.6Cameroon 2011 * 25.0 34.7 30.2 * 38.2 26.0 28.6 * 28.9 18.6 19.9 (40.8) 29.8 22.5 24.0

Cote D’Ivoire 1998-99 * * (52.0) 53.2 * * 48.5 48.7 * * 27.2 28.1 * 39.3 33.0 34.9Cote D’Ivoire 2011-12 * * (44.2) 42.6 * (49.7) 37.9 41.2 * (48.4) 23.0 25.2 * 47.2 28.9 31.9

Ethiopia 2000 * * (56.3) (58.4) * * 40.1 39.0 * * 13.8 13.9 * (24.6) 15.6 15.8Ethiopia 2011 * * * * * * 29.6 34.8 * * 23.2 23.3 * * 24.2 24.9

Ghana 2003 * * (61.3) (63.6) * * 42.1 46.7 * (50.8) 38.8 40.2 * (58.4) 41.8 44.0Ghana 2014 * * (77.8) (72.6) * (70.4) 84.2 80.0 * (68.4) 64.9 66.6 * 67.2 70.4 70.3

Guinea 1999 * * 60.0 60.4 * * 60.6 61.2 * (58.2) 31.2 32.8 * 58.2 37.5 39.4Guinea 2012 * * 60.4 61.9 * * 50.0 53.1 * (33.5) 24.7 25.3 * 49.3 31.1 32.8

Kenya 2003 * (62.4) 75.5 70.5 * (62.1) 53.0 56.3 * 58.1 45.4 46.2 * 60.2 47.4 49.1Kenya 2014 * (66.6) 70.5 67.7 (80.4) 60.4 54.1 57.5 * 68.4 56.3 57.3 72.5 64.9 56.9 58.2

Mali 2001 * 49.8 52.8 54.7 * * 33.8 37.6 * 32.4 11.8 13.0 (52.9) 43.8 16.4 20.7Mali 2012-13 * * 54.2 58.2 * * * * * * 20.6 21.2 * (51.9) 26.5 28.5

Mozambique 2003 * 58.4 50.0 54.6 * 69.8 60.7 63.0 * (65.9) 51.7 52.8 * 65.0 53.4 55.4Mozambique 2011 * * (56.9) 58.5 * (41.7) 68.6 63.2 * * 48.5 48.1 * 44.2 54.6 53.6

Niger 1998 * (62.5) (55.0) 59.5 * * 59.7 64.4 * * 17.9 18.2 * (70.7) 22.9 25.5Niger 2012 * * 58.3 58.8 * * 67.4 73.5 * * 45.7 45.9 * (76.3) 47.8 48.8

Nigeria 2003 * (28.8) (46.9) 40.1 * 50.3 30.0 35.9 * 44.3 22.0 28.7 * 44.1 27.1 32.8Nigeria 2013 * * (68.9) (75.0) * (87.9) 76.4 77.9 * 73.9 59.5 60.8 * 80.8 64.0 65.8

Rwanda 2000 * * 31.5 33.7 * * 16.5 19.0 * 21.6 13.6 14.4 * 24.2 14.5 15.5Rwanda 2010 * (67.9) (64.1) 63.2 * * (50.6) (49.4) * 47.4 34.8 36.3 * 51.5 37.1 39.1

Tanzania 1999 

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

Tanzania 2010 * * * (43.9) * (51.7) (46.7) 49.6 * 25.9 13.7 15.2 (56.1) 38.4 18.3 22.9

Uganda 2000-01 * * 88.7 88.7 * * 70.9 71.1 * * 65.1 75.7 * * 66.5 66.5Uganda 2011 * (70.2) 75.8 72.4 * (63.0) 74.3 72.0 * (80.2) 75.5 65.1 * 72.2 75.4 75.2

Zambia 2001-02 * * 77.4 78.9 * (73.1) 69.2 70.0 * * 66.7 67.4 * 80.7 68.2 69.1Zambia 2013-14 * * * (66.8) * 79.0 73.5 75.3 * (81.0) 62.9 63.8 * 77.8 64.7 66.8

Zimbabwe 1999 * * * * * (51.6) * 47.3 * (51.9) 47.7 48.4 * 56.1 47.6 49.8Zimbabwe 2010-11 * * * (50.5) * (42.3) (29.6) 38.1 * 43.0 39.5 40.1 (46.3) 45.1 39.1 40.9

Bangladesh 2004 * * (31.2) (35.9) * 60.9 28.1 34.0 * 32.7 15.5 16.7 * 42.5 17.6 19.9Bangladesh 2014 * * 63.2 64.6 * (48.3) 63.8 61.8 (55.4) 61.3 61.0 60.8 (62.9) 58.4 61.6 61.2

Cambodia 2000 * * * (39.5) * * 47.9 49.6 * 42.0 34.4 34.9 * 45.2 35.8 36.6Cambodia 2014 * * * (65.7) * (72.5) (68.9) 68.5 * 75.2 66.6 67.2 (57.5) 71.5 66.8 67.1

Nepal 2001 * * * * * * 36.0 38.4 * (29.9) 24.8 24.9 * 35.4 25.7 26.1Nepal 2011 * * * * * (62.1) 51.5 56.5 * (43.2) 39.6 40.7 * 48.2 41.2 43.2

Philippines 2003 * * (58.5) 59.8 * 69.5 59.8 64.1 (59.3) 49.7 47.9 49.0 62.9 59.6 51.8 54.8Philippines 2013 * * (70.7) 71.5 (55.2) 67.2 59.9 61.1 (65.3) 63.0 55.5 58.0 62.9 65.5 58.2 60.4

Continued
82

Table 3.25—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * (37.9) * (33.3) * (19.0) * (20.7) * * 24.0 24.5 * 29.4 24.1 26.2 Armenia 2010 * * * (67.0) (51.8) * * 48.6 * * * 49.6 66.4 (46.3) * 58.6

Colombia 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Colombia 2010 64.6 (74.4) * 67.9 73.6 67.5 55.4 67.1 (59.6) 58.2 56.5 57.5 67.7 67.2 57.8 64.8Dominican 

Republic 

2002 58.9 63.2 57.1 59.6 76.7 71.5 69.0 72.2 67.7 56.6 65.6 63.3 64.9 62.3 63.1 63.5

Dominican 

Republic 

2013 * (48.6) (72.4) 61.1 55.2 60.1 65.3 60.2 (83.1) 71.3 69.6 74.4 63.4 58.7 69.5 64.1

Peru 2000 73.6 68.4 51.9 63.6 * 74.7 57.3 63.6 * (83.8) 49.9 51.2 73.2 70.9 51.1 57.9Peru 2012 (62.5) (56.2) * 61.7 63.2 50.9 55.3 56.1 * 67.5 60.9 61.7 62.5 56.8 59.5 59.5

Egypt 2000 73.4 * * 74.7 81.1 76.5 (75.6) 79.1 64.8 65.4 55.2 60.6 71.8 68.4 57.9 66.0Egypt 2014 75.5 65.7 * 70.9 67.5 64.7 63.5 65.7 70.1 65.7 62.1 66.3 70.1 65.5 62.5 66.5

Jordan 2002 * * * (70.9) 88.9 67.7 82.1 78.7 (86.1) (81.2) 68.7 76.3 88.1 67.7 76.6 76.4Jordan 2012 * (73.8) * 80.6 68.5 69.9 68.5 69.1 71.9 76.8 70.9 74.0 75.1 72.6 75.0 74.0

Pooled Average 63.0 55.2 53.5 56.8 67.4 59.2 49.9 55.0 61.9 51.7 31.0 33.2 66.3 55.7 35.5 39.7
83

Table 3.26. Decadal change in coverage of care seeking from a medical source for children under age 5 with symptoms of ARI by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA NA NA NA NA NA 1.1 NA NA NA 23.7 4.1 NA -12.4 20.0 19.0

Cameroon 2004 Cameroon 2011 NA -52.9 -16.0 -37.9 NA -5.4 -27.4 -37.9 NA -22.4 -21.1 -21.1 NA -27.9 -21.6 -23.7

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA NA -6.0 -8.2 NA NA -8.2 -8.2 NA NA -3.2 -5.8 NA 6.1 -3.2 -2.3

Ethiopia 2000 Ethiopia 2011 NA NA NA NA NA NA -9.5 NA NA NA 8.5 -3.8 NA NA 7.8 8.3

Ghana 2003 Ghana 2014 NA NA 15.0 8.2 NA NA 38.3 8.2 NA 16.0 23.7 30.3 NA 8.0 26.0 23.9

Guinea 1999 Guinea 2012 NA NA 0.3 1.2 NA NA -8.2 1.2 NA -19.0 -5.0 -6.2 NA -6.8 -4.9 -5.1

Kenya 2003 Kenya 2014 NA 3.8 -4.5 -2.5 NA -1.5 1.0 -2.5 NA 9.4 9.9 1.1 NA 4.3 8.6 8.3

Mali 2001 Mali 2012.5 NA NA 1.2 3.0 NA NA NA 3.0 NA NA 7.7 NA NA 7.0 8.8 6.8

Mozambique 2003 Mozambique 2011 NA NA 8.6 4.9 NA -35.1 9.9 4.9 0.0 NA -4.0 0.3 NA -26.0 1.5 -2.3

Niger 1998 Niger 2012 NA NA 2.4 -0.5 NA NA 5.5 -0.5 0.0 NA 19.9 6.5 NA 4.0 17.8 16.6

Nigeria 2003 Nigeria 2013 NA NA 22.0 34.9 NA 37.6 46.4 34.9 NA 29.6 37.5 42.0 NA 36.7 36.9 33.0

Rwanda 2000 Rwanda 2010 NA NA 32.6 29.5 NA NA 34.1 29.5 NA 25.8 21.2 30.4 NA 27.3 22.6 23.6

Tanzania 1999 Tanzania 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAUganda 2000.5 Uganda 2011 NA 66.9 -12.3 -15.5 NA NA 3.2 -15.5 NA NA 9.9 0.9 NA NA 8.5 8.3Zambia 2001.5 Zambia 2013.5 NA NA NA -10.1 NA 4.9 3.6 -10.1 NA NA -3.2 4.4 NA -2.4 -2.9 -1.9

Zimbabwe 1999 Zimbabwe 2010.5 NA NA NA NA NA -8.1 NA NA NA -7.7 -7.1 -8.0 NA -9.6 -7.4 -7.7

Bangladesh 2004 Bangladesh 2014 NA NA 32.0 28.7 NA -12.6 35.7 28.7 NA 28.6 45.5 27.8 NA 15.9 44.0 41.3

Cambodia 2000 Cambodia 2014 NA NA NA 18.7 NA NA 15.0 18.7 NA 23.7 23.0 13.5 41.1 18.8 22.1 21.8

Nepal 2001 Nepal 2011 NA NA NA NA NA NA 15.5 NA NA 13.3 14.8 18.1 NA 12.8 15.5 17.1

Philippines 2003 Philippines 2013 NA NA 12.2 11.7 NA -2.3 0.1 11.7 6.0 13.3 7.6 -3.0 0.0 5.9 6.4 5.6

Continued
84

Table 3.26—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA NA NA 33.7 NA NA NA 33.7 NA NA NA 27.9 NA 16.9 NA 32.4

Colombia 2000 Colombia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 NA -13.3 13.9 1.4 -19.5 -10.4 -3.4 1.4 14.0 13.4 3.6 -10.9 -1.4 -3.3 5.8 0.5

Peru 2000 Peru 2012 -9.3 -10.2 NA -1.6 NA -19.8 -1.7 -1.6 NA -13.6 9.2 -6.3 -8.9 -11.8 7.0 1.3

Egypt 2000 Egypt 2014 1.5 NA NA -2.7 -9.7 -8.4 -8.6 -2.7 3.8 0.2 4.9 -9.6 -1.2 -2.1 3.3 0.4

Jordan 2002 Jordan 2012 NA NA NA 9.7 -20.4 2.2 -13.6 9.7 -14.2 -4.4 2.2 -9.6 -13.0 4.9 -1.6 -2.4

Pooled Average -9.2 -8.3 4.4 0.4 -12.0 -1.8 5.1 1.7 6.1 7.3 10.5 9.1 -2.4 1.2 10.0 8.7Note: NA indicates too few cases to calculate decadal change.
85

Table 3.27. Coverage of care seeking from a medical source for children under age 5 with diarrhea by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * * (30.2) 35.4 * (38.9) 25.3 28.1 * 19.0 14.5 14.9 * 34.4 15.9 17.2 Burkina Faso 2010 * (58.1) 44.1 49.5 * 62.2 54.4 56.2 * 51.2 45.2 45.7 * 55.9 46.0 47.1

Cameroon 2004 * (29.0) (20.4) 25.3 * 27.3 30.7 30.1 * 23.3 16.5 17.0 * 26.4 20.2 21.4Cameroon 2011 * 32.3 31.0 30.5 * 38.0 26.7 27.9 * 28.1 19.0 19.3 (17.5) 32.4 21.8 22.8

Cote D’Ivoire 1998-99 * * 39.3 39.5 * * 36.5 40.2 * * 25.8 26.5 * (38.7) 28.6 30.0Cote D’Ivoire 2011-12 * (28.8) 16.8 21.5 * 28.6 35.4 34.3 * 38.9 24.8 26.2 (50.2) 32.3 25.7 27.2

Ethiopia 2000 * * (28.1) 31.1 * * 45.3 44.9 * * 10.8 10.9 * (22.3) 13.1 13.3Ethiopia 2011 * * (42.7) (47.2) * * 55.5 54.4 * * 29.2 29.2 * * 31.7 31.8

Ghana 2003 * * (29.2) 29.7 * * 47.3 40.1 * (19.6) 21.4 21.3 * 20.7 26.1 25.5Ghana 2014 * * (58.0) 55.8 * 65.6 63.0 63.9 * 69.6 65.4 66.5 * 64.4 63.7 64.1

Guinea 1999 * (44.0) 51.0 50.0 * * 59.5 53.8 * 45.3 30.5 31.6 * 41.5 35.3 36.0Guinea 2012 * (59.0) 47.6 50.3 * (63.0) 38.6 46.2 * (50.3) 32.3 33.5 * 56.4 35.2 37.7

Kenya 2003 * (46.7) 30.9 35.9 * * 21.7 25.9 * (51.8) 28.1 29.5 * 48.1 27.7 29.7Kenya 2014 * (60.8) 58.8 58.0 * 54.3 55.6 56.0 * 54.3 58.2 58.1 59.1 56.1 57.8 57.6

Mali 2001 * 30.8 23.1 28.5 * * 16.2 18.9 * 5.0 3.4 3.6 (44.8) 18.4 5.4 7.0Mali 2012-13 * (23.8) 34.1 31.5 * * (43.0) 46.6 * (21.8) 26.1 26.2 * 27.9 28.1 28.3

Mozambique 2003 * (25.2) 46.8 41.7 * 63.1 54.9 56.6 * (49.3) 46.7 46.9 * 51.3 48.5 48.9Mozambique 2011 * * (62.6) 64.4 * (58.0) 66.6 66.3 * * 51.2 51.6 * 64.1 55.4 56.0

Niger 1998 * (40.0) 30.0 32.3 * (54.4) 40.3 42.2 * * 13.9 14.0 * 41.8 16.6 17.5Niger 2012 * (46.0) 49.4 48.5 * * 49.8 52.1 * * 51.0 51.1 * 55.8 50.8 50.9

Nigeria 2003 * 39.6 23.1 30.8 * 28.0 23.0 25.1 * 32.7 13.5 15.8 (26.3) 31.2 18.1 21.5Nigeria 2013 * (64.7) 55.7 57.9 * 75.3 63.6 65.5 * 66.7 56.7 57.6 (60.0) 69.9 58.3 59.7

Rwanda 2000 * * 23.7 23.6 * * 8.8 8.5 * 28.2 12.3 13.9 * 25.9 12.4 13.8Rwanda 2010 * * 32.2 34.8 * * 29.9 31.4 * 48.8 36.1 37.8 * 47.3 35.4 37.2

Tanzania 1999 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NATanzania 2010 * * (30.0) (30.0) * 37.1 31.7 35.1 * 15.5 13.8 14.0 (42.6) 26.0 16.9 18.9

Uganda 2000-01 * * (71.4) (69.8) * * 60.3 60.3 * * 42.9 72.7 * * 44.8 44.9Uganda 2011 * (73.5) 65.8 68.7 * (67.4) 72.5 71.6 * (77.6) 72.6 43.0 * 74.1 72.3 72.4

Zambia 2001-02 * * 28.1 28.4 * (40.4) 49.4 46.9 * (55.3) 43.4 43.7 * 42.8 42.9 42.8Zambia 2013-14 * (70.2) 61.8 65.0 (58.4) 63.5 64.2 63.6 * 68.4 66.4 66.5 (62.0) 67.2 65.4 65.6

Zimbabwe 1999 * * * * * (41.5) (22.7) 31.5 * (30.2) 33.8 33.2 * 33.4 32.3 32.1Zimbabwe 2010-11 * (36.6) (30.2) 32.9 (49.1) 48.0 31.7 41.7 * 26.8 31.4 30.8 (41.1) 36.0 31.3 32.9

Bangladesh 2004 * * * * * * 21.8 31.5 * * 11.8 12.3 * (24.3) 13.3 15.7Bangladesh 2014 * * (65.8) (70.1) * * 47.8 51.1 * (41.7) 49.8 48.8 * 52.7 50.9 51.4

Cambodia 2000 * * * (30.1) * * 32.1 32.5 * 25.8 20.0 20.3 * 30.4 20.9 21.6Cambodia 2014 * (40.7) * 50.7 * 42.2 39.6 42.2 (52.2) 49.6 58.6 56.9 58.5 47.2 57.4 55.5

Nepal 2001 * * * * * * 17.4 20.6 * * 21.2 21.1 * (23.9) 21.0 21.2Nepal 2011 * * * * * * 43.4 47.9 * (43.3) 36.5 37.5 (46.3) 44.4 36.7 38.0

Philippines 2003 (39.7) (30.0) (40.2) 36.1 (32.4) 35.9 37.4 36.2 (33.5) 29.0 27.8 28.6 34.8 31.8 32.1 32.4Philippines 2013 * * (39.9) 54.2 (40.2) (28.3) 42.2 38.6 (43.3) 43.2 39.7 40.9 48.7 42.5 40.5 42.1

Continued
86

Table 3.27—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * * * * * (22.6) * (25.0) * * 24.2 27.0 * 25.3 25.1 26.5 Armenia 2010 * * * (47.9) (24.4) * * 30.8 * * * 45.7 41.3 (43.4) * 42.2

Colombia 2000 37.8 (36.7) (30.2) 35.7 30.8 28.9 29.8 29.8 (29.0) 25.4 18.6 22.2 33.4 29.7 24.0 28.8Colombia 2010 43.5 51.5 (41.7) 45.5 50.8 45.4 42.6 47.1 43.6 41.2 32.5 36.9 46.8 45.7 36.8 43.2

Dominican 

Republic 

2002 33.5 34.3 26.7 31.4 39.3 39.3 40.5 39.8 42.7 35.7 39.1 38.7 37.1 35.9 35.0 35.9

Dominican 

Republic 

2013 (40.5) (40.8) (55.7) 45.5 67.8 41.9 53.2 53.5 (49.3) 70.7 61.8 61.1 52.4 47.9 56.4 52.0

Peru 2000 47.9 37.4 32.7 38.2 * 57.7 41.4 44.7 * 48.2 37.0 37.6 46.5 42.8 36.3 38.5Peru 2012 (42.5) * * 33.0 35.3 28.5 30.9 31.1 * 38.6 36.6 36.4 37.9 31.7 32.7 33.4

Egypt 2000 44.1 * * 47.3 53.3 59.7 (56.7) 55.3 39.5 50.5 40.8 43.4 45.3 52.9 42.4 46.3Egypt 2014 83.0 (41.2) * 65.0 53.1 55.6 59.6 55.3 59.5 52.4 49.3 53.9 60.5 52.1 50.8 55.0

Jordan 2002 * (55.6) * 51.0 47.3 48.8 60.3 52.1 67.4 53.8 48.7 54.9 50.9 51.7 54.8 52.5Jordan 2012 (52.8) (53.2) (56.0) 54.0 55.6 57.9 55.8 56.6 58.5 55.2 57.6 57.0 54.9 56.1 56.2 55.7

Pooled Average 41.8 39.5 35.5 38.6 47.2 43.1 40.5 42.6 44.8 32.4 21.0 22.0 46.7 41.3 25.9 29.2
87

Table 3.28. Decadal change in coverage of care seeking from a medical source for children under age 5 with fever by poverty according to level of 

urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA NA 19.9 20.1 NA 33.3 41.6 40.1 NA 46.0 43.9 44.0 NA 30.7 43.0 42.7

Cameroon 2004 Cameroon 2011 NA 4.7 15.1 7.4 NA 15.3 -5.7 -3.1 NA 6.9 3.6 3.3 NA 8.6 2.3 2.0

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA NA -17.3 -13.8 NA NA -0.8 -4.5 NA NA -0.8 -0.2 NA -4.9 -2.2 -2.2

Ethiopia 2000 Ethiopia 2011 NA NA 13.3 14.6 NA NA 9.3 8.6 NA NA 16.7 16.7 NA NA 16.9 16.8

Ghana 2003 Ghana 2014 NA NA 26.2 23.7 NA NA 14.3 21.6 NA 45.5 40.0 41.1 NA 39.7 34.2 35.1

Guinea 1999 Guinea 2012 NA 11.5 -2.6 0.2 NA NA -16.1 -5.8 NA 3.8 1.4 1.5 NA 11.5 -0.1 1.3

Kenya 2003 Kenya 2014 NA 12.8 25.4 20.1 NA NA 30.8 27.4 NA 2.3 27.4 26.0 NA 7.3 27.4 25.4

Mali 2001 Mali 2012.5 NA -6.1 9.6 2.6 NA NA 23.3 24.1 NA 14.6 19.7 19.7 NA 8.3 19.7 18.5

Mozambique 2003 Mozambique 2011 NA NA 19.8 28.4 NA -6.4 14.6 12.1 NA NA 5.6 5.9 NA 16.0 8.6 8.9

Niger 1998 Niger 2012 NA 4.3 13.9 11.6 NA NA 6.8 7.1 0.0 NA 26.5 26.5 NA 10.0 24.4 23.9

Nigeria 2003 Nigeria 2013 NA 25.1 32.6 27.1 NA 47.3 40.6 40.4 NA 34.0 43.2 41.7 33.7 38.7 40.2 38.2

Rwanda 2000 Rwanda 2010 NA NA 8.5 11.2 NA NA 21.1 22.9 NA 20.6 23.8 23.9 NA 21.4 23.0 23.4

Tanzania 1999 Tanzania 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAUganda 2000.5 Uganda 2011 NA NA -5.3 -1.0 NA 64.2 11.6 10.8 NA NA 28.3 -28.2 NA NA 26.2 26.2Zambia 2001.5 Zambia 2013.5 NA NA 28.1 30.5 NA 19.3 12.3 13.9 NA 10.9 19.2 18.9 NA 20.3 18.8 19.0

Zimbabwe 1999 Zimbabwe 2010.5 NA NA NA NA 42.7 5.7 7.8 8.9 NA -3.0 -2.1 -2.1 NA 2.3 -0.9 0.7

Bangladesh 2004 Bangladesh 2014 NA NA NA NA NA NA 26.0 19.6 NA NA 38.0 36.5 NA 28.4 37.6 35.7

Cambodia 2000 Cambodia 2014 NA NA NA 14.7 NA NA 5.4 6.9 37.3 17.0 27.6 26.1 41.8 12.0 26.1 24.2

Nepal 2001 Nepal 2011 NA NA NA NA NA NA 26.0 27.3 NA NA 15.3 16.4 NA 20.5 15.7 16.8

Philippines 2003 Philippines 2013 NA NA -0.3 18.1 7.8 -7.6 4.8 2.4 9.8 14.2 11.9 12.3 13.9 10.7 8.4 9.7

Continued
88

Table 3.28—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA NA NA NA NA NA NA 5.8 NA NA NA 18.7 NA 18.1 NA 15.7

Colombia 2000 Colombia 2010 5.7 14.8 11.5 9.8 20.0 16.5 12.8 17.3 14.6 15.8 13.9 14.7 13.4 16.0 12.8 14.4

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 6.4 5.9 26.4 12.8 25.9 2.4 11.5 12.5 6.0 31.8 20.6 20.4 13.9 10.9 19.5 14.6

Peru 2000 Peru 2012 -4.5 NA NA -4.3 NA -24.3 -8.8 -11.3 NA -8.0 -0.3 -1.0 -7.2 -9.3 -3.0 -4.3

Egypt 2000 Egypt 2014 27.8 NA NA 12.6 -0.1 -2.9 2.1 0.0 14.3 1.4 6.1 7.5 10.9 -0.6 6.0 6.2

Jordan 2002 Jordan 2012 NA -2.4 NA 3.0 8.3 9.1 -4.5 4.5 -8.9 1.4 8.9 2.1 4.0 4.4 1.4 3.2

Pooled Average 5.9 8.2 11.0 10.1 11.3 12.4 14.4 12.5 9.1 15.3 20.3 17.2 8.4 12.3 19.0 17.8Note: NA indicates too few cases to calculate decadal change.
89 

ORT use for children’s diarrhea 

Levels 

Unlike many of the other child health indicators, provision of oral rehydration therapy (ORT) for children 

with diarrhea is equitable across poverty groups (see Figure 3.21, left panel). Urban extremely poor children 

fare similarly to their less poor and non-poor urban counterparts, and fare slightly better than their rural 

extremely poor counterparts. National provision of ORT varies very substantially, from 40% to 90% of 

children with diarrhea in the latest surveys (see Table 3.29). 

Decadal change 

On average, there was minimal change observed between baseline and endline surveys (see Figure 3.21, 

right panel). Among extremely poor urban children—both in large cities and other urban areas—there was 

a decrease in coverage over the decade of 2 percentage points. Improvements in coverage were greatest 

among the non-poor in other urban areas (8 percentage point increase), non-poor large cities (4 percentage 

point increase), and the non-poor in rural areas (1 percentage point increase). Unfortunately, ORT use 

declined in nine of the sixteen countries for the extremely poor in large cities (see Table 3.30). 

Figure 3.21. Pooled average coverage of treatment with ORT for children under age 5 with diarrhea 

(left panel) and pooled average decadal change in coverage (right panel), by poverty according to 

level of urbanicity 

60.3 61.0

52.9

64.1 61.1 57.9 63.8 63.6

53.0

Large cities Other urban areas Rural areas

Percentage

Diarrhea ORT use

Not poor Moderately poor Extremely poor

4.2 7.6 0.7 1.3

0.0

0.2

-2.2 -1.9 -2.3

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in Diarrhea ORT 

use

Not poor Moderately poor Extremely poor
90

Table 3.29. Coverage of treatment with ORT for children under age 5 with diarrhea by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * * (64.8) 71.9 * (72.9) 68.7 69.9 * 67.5 61.5 61.5 * 75.2 62.1 62.8 Burkina Faso 2010 * (66.4) 72.1 69.1 * 50.8 47.8 48.7 * 45.7 37.9 38.4 * 53.5 40.6 42.1

Cameroon 2004 * (73.7) (70.5) 73.6 * 69.4 59.3 62.0 * 60.8 51.3 52.0 * 67.7 54.3 56.7Cameroon 2011 * 76.8 73.1 75.0 * 73.5 66.0 66.7 * 62.6 57.7 57.9 (71.6) 71.4 61.0 62.2

Cote D’Ivoire 1998-99 * * 78.8 81.5 * * 64.1 67.8 * * 62.3 62.7 * (73.4) 64.5 66.1Cote D’Ivoire 2011-12 * (41.8) 48.7 46.8 * 36.1 60.0 53.5 * 58.2 46.8 48.0 (49.5) 45.4 49.6 49.0

Ethiopia 2000 * * (64.8) 67.3 * * 68.4 68.7 * * 42.8 43.0 * (74.5) 44.5 44.9Ethiopia 2011 * * (65.9) (65.1) * * 53.1 54.0 * * 37.8 37.8 * * 39.5 39.7

Ghana 2003 * * (65.3) 65.8 * * 69.4 69.4 * (66.0) 61.0 61.4 * 67.7 62.8 63.3Ghana 2014 * * (59.1) 62.7 * 75.2 58.7 63.5 * 70.6 59.9 61.0 * 72.1 59.5 61.8

Guinea 1999 * (76.0) 77.5 77.3 * * 71.9 74.7 * 88.5 66.0 67.5 * 85.1 67.7 69.3Guinea 2012 * (82.1) 58.2 62.3 * (54.3) 56.8 56.4 * (74.4) 47.5 49.2 * 72.2 49.9 52.2

Kenya 2003 * (61.5) 61.6 65.0 * * 41.5 40.6 * (60.3) 49.4 50.1 * 56.8 49.6 50.6Kenya 2014 * (82.0) 81.8 80.7 * 75.8 69.1 69.9 * 66.8 69.1 68.9 62.7 74.2 70.3 70.6

Mali 2001 * 86.1 74.0 80.1 * * 75.2 75.9 * 63.3 63.2 63.3 (88.7) 74.1 64.6 65.7Mali 2012-13 * (62.3) 54.9 56.0 * * (62.2) 62.1 * (60.4) 48.2 48.7 * 61.6 49.8 50.6

Mozambique 2003 * (77.8) 88.5 86.0 * 86.7 88.1 87.8 * (67.1) 61.8 62.1 * 78.7 69.3 70.5Mozambique 2011 * * (86.0) 85.5 * (68.3) 73.3 73.1 * * 58.2 58.7 * 74.2 62.7 63.5

Niger 1998 * (80.0) 72.2 74.8 * (83.6) 79.3 79.9 * * 65.0 65.2 * 80.8 66.5 67.0Niger 2012 * (68.7) 61.1 62.2 * * 59.1 58.9 * * 58.8 59.0 * 68.0 59.0 59.3

Nigeria 2003 * 60.9 41.7 53.0 * 37.2 45.5 42.8 * 54.8 31.5 34.9 (48.3) 45.7 38.0 40.2Nigeria 2013 * (68.4) 51.6 55.8 * 62.0 50.3 52.6 * 42.0 39.9 40.1 (50.5) 53.4 43.0 44.3

Rwanda 2000 * * 50.9 52.8 * * 40.0 36.4 * 37.0 27.8 28.8 * 36.1 29.6 30.2Rwanda 2010 * * 46.3 43.5 * * 47.7 48.2 * 53.7 47.7 48.4 * 51.5 47.7 48.1

Tanzania 1999 * * * * * * (66.0) 66.6 * * 67.8 68.3 * (73.2) 67.4 67.8Tanzania 2010 * * (47.9) (55.2) * 79.2 76.9 76.5 * 64.5 60.1 60.6 (71.1) 68.5 61.6 62.8

Uganda 2000-01 * * (76.2) (74.4) * * 61.8 61.8 * * 51.9 53.9 * * 53.2 53.1Uganda 2011 * (64.9) 61.9 62.4 * (51.0) 68.2 65.3 * (66.7) 53.5 51.8 * 62.9 54.8 55.3

Zambia 2001-02 * * 73.0 72.5 * (72.2) 71.4 71.5 * (71.0) 64.4 64.6 * 71.3 66.5 66.9Zambia 2013-14 * (87.3) 83.3 84.4 (92.0) 77.3 73.6 75.6 * 80.7 72.3 72.7 (87.1) 81.9 73.7 74.9

Zimbabwe 1999 * * * * (64.1) (89.4) 77.6 * (92.3) 77.8 78.5 * 79.2 80.2 79.7Zimbabwe 2010-11 * (80.8) (83.3) 82.3 (63.3) 82.3 76.5 76.7 * 64.9 71.7 70.8 (66.8) 74.9 73.8 73.7

Bangladesh 2004 * * * * * * 85.1 87.7 * * 81.6 82.6 * (93.2) 82.1 83.4Bangladesh 2014 * * (79.3) (83.3) * * 93.8 93.9 * (80.6) 86.1 85.3 * 85.2 86.6 86.4

Cambodia 2000 * * * (76.8) * * 61.6 61.0 * 55.9 62.9 62.4 * 58.2 63.2 62.8Cambodia 2014 * (59.8) * 69.6 * 41.7 49.0 45.5 (58.5) 61.0 55.7 56.7 59.4 58.6 56.4 57.0

Nepal 2001 * * * * * * 63.6 64.1 * * 45.1 45.6 * (71.1) 45.9 46.5Nepal 2011 * * * * * * 49.8 54.1 * (49.2) 48.5 49.5 (65.0) 52.2 48.6 50.0

Philippines 2003 (76.4) (81.2) (81.6) 80.1 (87.3) 81.6 85.9 84.9 (79.5) 72.0 75.4 75.1 81.5 77.7 79.5 79.3Philippines 2013 * * (80.4) 75.6 (63.8) (81.0) 69.6 71.2 (60.1) 57.6 63.5 61.8 63.2 66.6 67.5 66.7

Continued
91

Table 3.29—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 * * * * * (70.5) * (65.7) * * 48.2 53.9 * 68.6 49.8 59.7Armenia 2010 * * * (92.7) (89.8) * * 82.9 * * * 94.8 93.5 (84.5) * 90.4

Colombia 2000 60.1 (60.0) (48.5) 57.3 59.5 58.7 52.6 57.2 (44.7) 38.8 49.6 45.7 57.3 52.5 50.3 53.2Colombia 2010 81.0 74.5 (72.5) 77.9 79.2 72.4 73.3 75.7 70.4 74.2 64.6 68.3 78.6 73.6 68.3 73.8

Dominican 

Republic 

2002 56.3 45.3 50.7 50.9 57.4 55.5 64.6 59.6 59.6 56.6 56.4 57.1 57.4 51.7 56.0 55.0

Dominican 

Republic 

2013 (64.3) (77.4) (66.1) 70.2 71.1 55.5 60.4 61.8 (54.5) 82.7 51.4 63.1 64.2 71.5 60.3 65.7

Peru 2000 64.2 71.6 73.6 70.5 * 80.5 65.6 68.6 * 70.7 65.7 66.1 64.5 72.9 67.7 68.0Peru 2012 (79.8) * * 71.9 67.6 77.5 70.3 71.8 * 57.3 61.2 60.6 73.2 70.8 65.1 67.8

Egypt 2000 34.4 * * 29.3 39.1 56.8 (43.4) 43.8 43.8 61.4 49.5 51.8 40.0 56.9 47.7 47.3Egypt 2014 34.6 (47.2) * 39.2 47.4 49.9 67.9 52.5 46.2 45.9 38.9 43.9 45.2 46.6 43.2 45.2

Jordan 2002 * (61.2) * 61.9 59.0 71.1 66.9 66.1 54.9 57.9 67.8 61.2 59.6 65.4 65.8 63.9Jordan 2012 (52.1) (37.7) (45.7) 45.6 62.2 52.3 55.2 56.3 52.8 50.7 57.9 53.5 57.0 47.8 51.8 52.1

Pooled Average 60.3 64.1 63.8 63.9 61.0 61.1 63.6 63.0 52.9 57.9 53.0 53.4 58.5 60.9 55.3 56.3
92

Table 3.30. Decadal change in coverage of treatment with ORT for children under age 5 with diarrhea by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA NA 10.4 -4.0 NA -31.6 -29.9 -30.3 NA -31.1 -33.7 -33.1 NA -31.0 -30.7 -29.6

Cameroon 2004 Cameroon 2011 NA 4.4 3.7 2.0 NA 5.9 9.6 6.7 NA 2.6 9.1 8.5 NA 5.3 9.6 7.9

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA NA -23.2 -26.7 NA NA -3.2 -11.0 NA NA -11.9 -11.2 NA -21.5 -11.5 -13.2

Ethiopia 2000 Ethiopia 2011 NA NA 1.0 -2.0 NA NA -13.9 -13.4 NA NA -4.5 -4.7 NA NA -4.5 -4.7

Ghana 2003 Ghana 2014 NA NA -5.6 -2.8 NA NA -9.7 -5.4 NA 4.2 -1.0 -0.4 NA 4.0 -3.0 -1.4

Guinea 1999 Guinea 2012 NA 4.7 -14.8 -11.5 NA NA -11.6 -14.1 NA -10.8 -14.2 -14.1 NA -9.9 -13.7 -13.2

Kenya 2003 Kenya 2014 NA 18.6 18.4 14.3 NA NA 25.1 26.6 NA 5.9 17.9 17.0 NA 15.8 18.8 18.2

Mali 2001 Mali 2012.5 NA -20.7 -16.6 -21.0 NA NA -11.3 -12.0 NA -2.5 -13.0 -12.6 NA -10.9 -12.9 -13.1

Mozambique 2003 Mozambique 2011 NA NA -3.1 -0.6 NA -23.0 -18.5 -18.4 NA NA -4.5 -4.2 NA -5.6 -8.2 -8.8

Niger 1998 Niger 2012 NA -8.1 -7.9 -9.0 NA NA -14.4 -15.0 0.0 NA -4.4 -4.4 NA -9.1 -5.4 -5.5

Nigeria 2003 Nigeria 2013 NA 7.5 9.9 2.8 NA 24.8 4.8 9.8 NA -12.8 8.4 5.2 2.2 7.7 5.0 4.1

Rwanda 2000 Rwanda 2010 NA NA -4.6 -9.3 NA NA 7.7 11.8 NA 16.7 19.9 19.6 NA 15.4 18.1 17.9

Tanzania 1999 Tanzania 2010 NA NA NA NA NA NA 9.9 9.0 NA NA -7.0 -7.0 NA -4.3 -5.3 -4.5

Uganda 2000.5 Uganda 2011 NA NA -13.6 -11.4 NA 48.6 6.1 3.3 NA NA 1.5 -2.0 NA NA 1.5 2.1

Zambia 2001.5 Zambia 2013.5 NA NA 8.6 9.9 NA 4.3 1.8 3.4 NA 8.1 6.6 6.7 NA 8.8 6.0 6.7

Zimbabwe 1999 Zimbabwe 2010.5 NA NA NA NA 55.0 15.8 -11.2 -0.8 NA -23.8 -5.3 -6.7 NA -3.7 -5.6 -5.2

Bangladesh 2004 Bangladesh 2014 NA NA NA NA NA NA 8.7 6.2 NA NA 4.5 2.7 NA -8.0 4.5 3.0

Cambodia 2000 Cambodia 2014 NA NA NA -5.1 NA NA -9.0 -11.1 41.8 3.6 -5.1 -4.1 42.4 0.3 -4.9 -4.1

Nepal 2001 Nepal 2011 NA NA NA NA NA NA -13.8 -10.0 NA NA 3.4 3.9 NA -18.9 2.7 3.5

Philippines 2003 Philippines 2013 NA NA -1.2 -4.5 -23.5 -0.6 -16.3 -13.7 -19.4 -14.4 -11.9 -13.3 -18.3 -11.1 -12.0 -12.6

Continued
93

Table 3.30—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA NA NA NA NA NA NA 17.2 NA NA NA 40.9 NA 15.9 NA 30.7

Colombia 2000 Colombia 2010 20.9 14.5 24.0 20.6 19.7 13.7 20.7 18.5 25.7 35.4 15.0 22.6 21.3 21.1 18.0 20.6

Dominican 

Republic 

2002 

Dominican 

Republic 

2013 7.3 29.2 14.0 17.5 12.5 0.0 -3.8 2.0 -4.6 23.7 -4.5 5.5 6.2 18.0 3.9 9.7

Peru 2000 Peru 2012 13.0 NA NA 1.2 NA -2.5 3.9 2.7 NA -11.2 -3.8 -4.6 7.3 -1.8 -2.2 -0.2

Egypt 2000 Egypt 2014 0.1 NA NA 7.1 5.9 -4.9 17.5 6.2 1.7 -11.1 -7.6 -5.6 3.7 -7.4 -3.2 -1.5

Jordan 2002 Jordan 2012 NA -23.5 NA -16.3 3.2 -18.8 -11.7 -9.8 -2.1 -7.2 -9.9 -7.7 -2.6 -17.6 -14.0 -11.8

Pooled Average 4.2 0.7 -2.2 -1.0 7.6 0.0 -1.9 -0.7 1.3 0.2 -2.3 -2.3 4.1 0.5 -2.0 -1.2
94 

Household mosquito bednet possession 

Levels 

Household possession of one or more mosquito bednets was included in 28 surveys. Only 10 countries 

included information about bednets in both the baseline and endline surveys. 

On average across the 28 surveys with data, the level of household mosquito bednet possession in large 

cities is similar across levels of poverty, ranging from 15-17% (see Figure 3.22, left panel). The differentials 

are larger in other urban areas, ranging from 43% in non-poor households to 29% in moderately poor 

households. The differentials are widest in rural areas, where 51% of non-poor households possess at least 

one mosquito bednet, as compared with just 10% of extremely poor households. In the 16 endline surveys 

with data, possession of bednets by extremely poor large city households ranges from 33% in Cameroon to 

89% in Rwanda (see Table 3.31). Two other countries are below 50% in possession for extremely poor 

large city households: Zimbabwe (41%) and Guinea (43%). 

Decadal change 

In all three areas of residence, the decadal improvement in coverage was closely associated with poverty 

level, with the greatest gains made among the non-poor. The next greatest gains were made among the 

moderately poor, and the least gains made among the extremely poor (see Figure 3.22, right panel). This 

pattern, which is stronger in the two urban areas, suggests that gaps in bednet ownership by poverty level 

narrowed more in these areas over the decade. For the extremely poor large city households, possession 

increased in all countries with data except Cameroon (see Table 3.32). 

Figure 3.22. Pooled average coverage of household mosquito bednet possession (left panel) and 

pooled average decadal change in coverage (right panel), by poverty according to level of urbanicity 

17.4

42.8

50.8

17.1

29.2 27.5

15.2

36.1

10.1

Large cities Other urban areas Rural areas

Percentage

Household mosquito bednet possession

Not poor Moderately poor Extremely poor

17.8

10.3

32.6

23.2 26.4

36.2 36.1 33.1

43.3

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in household 

mosquito bednet possession

Not poor Moderately poor Extremely poor
95

Table 3.31. Household mosquito bednet possession by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 (51.3) 44.3 37.3 41.6 (59.9) 54.3 48.8 51.1 (66.1) 33.6 39.0 38.8 56.5 43.2 39.6 40.4 Burkina Faso 2010 72.4 65.6 66.1 66.7 77.8 70.7 67.1 68.6 81.6 65.6 64.6 64.8 75.1 67.2 65.0 65.5

Cameroon 2004 18.9 26.8 48.1 30.5 18.9 16.0 23.1 19.3 (15.1) 20.4 16.0 16.7 18.7 20.7 20.1 20.3Cameroon 2011 21.3 23.5 32.6 26.8 15.0 20.0 27.6 24.2 26.8 22.0 27.5 26.9 20.0 21.8 28.2 26.1

Cote D’Ivoire 1998-99 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NACote D’Ivoire 2011-12 41.6 57.7 66.5 58.7 58.4 63.7 67.8 65.5 75.7 72.8 78.2 77.3 50.8 65.0 74.4 70.4

Ethiopia 2000 1.0 0.9 0.6 0.7 20.2 5.7 3.1 3.8 * 1.6 0.7 0.7 8.1 3.5 0.9 1.1Ethiopia 2011 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Ghana 2003 12.3 5.7 11.3 8.5 (17.9) 9.0 13.6 11.3 * 20.0 26.6 24.4 15.5 12.7 21.4 17.7Ghana 2014 56.7 50.7 65.9 57.3 56.4 62.0 72.2 66.3 75.5 75.6 82.5 79.7 66.9 62.3 76.2 69.6

Guinea 1999 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Guinea 2012 45.2 40.3 42.9 42.3 47.6 50.7 56.3 54.4 50.5 52.8 55.0 54.8 47.2 47.4 53.5 52.4Kenya 2003 63.5 37.2 28.9 40.3 73.8 37.6 22.6 33.9 48.3 29.4 12.8 16.6 59.3 33.6 14.5 22.0Kenya 2014 63.9 69.5 62.3 65.3 72.6 67.2 65.9 67.0 63.8 64.3 64.0 64.1 67.1 66.8 64.2 65.1

Mali 2001 56.2 59.4 51.3 55.7 (75.5) 56.4 59.8 59.4 69.5 58.9 52.8 53.3 62.2 58.5 53.5 54.4Mali 2012-13 80.2 81.1 83.1 82.4 90.4 92.9 88.9 89.6 (84.0) 89.9 88.7 88.7 83.7 87.6 88.2 88.1

Mozambique 2003 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAMozambique 2011 71.2 53.1 58.4 57.1 76.6 66.6 65.9 66.3 (48.9) 55.6 53.5 53.6 69.7 60.2 56.5 57.0

Niger 1998 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Niger 2012 67.9 78.9 82.1 80.4 84.1 80.7 78.2 78.6 * 87.5 70.5 70.7 76.2 81.4 71.8 72.2Nigeria 2003 6.6 3.7 5.0 4.4 9.5 6.4 13.8 10.0 13.7 14.5 18.4 17.2 9.0 7.9 15.2 11.9Nigeria 2013 41.3 40.1 55.4 48.1 40.7 41.2 54.2 48.5 59.8 56.8 61.8 60.7 53.5 46.9 59.2 55.4

Rwanda 2000 (57.7) 40.9 35.3 37.2 (15.4) 33.8 25.5 26.9 14.8 3.1 2.7 2.9 18.2 8.7 6.0 6.7Rwanda 2010 90.7 82.3 88.6 86.5 * 86.3 83.2 84.0 89.6 81.4 82.2 82.2 90.3 81.8 82.6 82.7

Tanzania 1999 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NATanzania 2010 (80.9) 87.4 83.6 85.9 94.4 85.7 77.8 82.8 73.1 77.8 70.8 71.7 82.7 83.0 71.9 74.9

Uganda 2000-01 * (55.2) 37.1 38.1 * 42.3 27.7 28.1 * 5.3 9.2 9.2 * 19.6 12.7 12.9Uganda 2011 82.9 57.3 75.6 66.1 90.7 51.4 76.4 66.5 (100.0) 27.1 68.1 62.3 89.8 39.1 69.1 63.1

Zambia 2001-02 * 22.2 26.9 25.7 (34.3) 47.2 34.7 39.3 (54.1) 51.7 21.8 23.3 40.0 42.1 24.4 27.2Zambia 2013-14 50.8 48.1 55.8 52.2 84.3 78.5 76.6 78.1 80.9 80.8 75.8 76.2 75.2 68.0 73.9 72.9

Zimbabwe 1999 19.0 11.8 10.5 12.5 26.0 19.0 16.4 19.2 13.7 9.8 5.0 6.3 20.5 13.7 6.7 10.3Zimbabwe 2010-11 45.7 40.7 41.0 41.4 56.0 50.7 50.9 52.0 41.6 34.7 38.8 38.1 47.2 40.5 40.2 41.2

Bangladesh 2004 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NABangladesh 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NACambodia 2000 (88.5) 88.0 92.0 89.5 * 90.4 92.8 92.4 (100.0) 78.1 80.8 80.4 94.4 80.6 82.2 82.0Cambodia 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NANepal 2001 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NANepal 2011 60.2 62.7 69.9 64.4 91.0 87.0 83.1 85.3 91.4 77.9 60.5 66.2 86.8 77.6 62.4 67.9

Philippines 2003 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Philippines 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Continued
96

Table 3.31—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Armenia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAColombia 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAColombia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NADominican 

Republic 

2002 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Dominican 

Republic 

2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Peru 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAPeru 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAEgypt 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAEgypt 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAJordan 2002 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAJordan 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAPooled Average 17.4 17.1 15.2 16.7 42.8 29.2 36.1 35.1 50.8 27.5 10.1 10.9 40.5 30.2 15.0 17.3NA=not asked. 
97

Table 3.32. Decadal change in household mosquito bednet possession by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 30.1 30.4 41.1 35.9 25.6 23.4 26.1 25.0 22.1 45.7 36.6 37.1 26.6 34.3 36.3 35.9

Cameroon 2004 Cameroon 2011 3.4 -4.7 -22.1 -5.3 -5.6 5.7 6.4 7.0 16.7 2.3 16.4 14.6 1.9 1.6 11.6 8.3

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAEthiopia 2000 Ethiopia 2011 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAGhana 2003 Ghana 2014 40.4 40.9 49.6 44.4 35.0 48.2 53.3 50.0 NA 50.5 50.8 50.3 46.7 45.1 49.8 47.2

Guinea 1999 Guinea 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Kenya 2003 Kenya 2014 0.4 29.4 30.4 22.7 -1.1 26.9 39.4 30.1 14.1 31.7 46.5 43.2 7.1 30.2 45.2 39.2

Mali 2001 Mali 2012.5 20.9 18.9 27.7 23.2 13.0 31.7 25.3 26.3 12.6 27.0 31.2 30.8 18.7 25.3 30.2 29.3

Mozambique 2003 Mozambique 2011 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NANiger 1998 Niger 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NANigeria 2003 Nigeria 2013 34.7 36.4 50.4 43.7 31.2 34.8 40.4 38.5 46.1 42.3 43.4 43.5 44.5 39.0 44.0 43.5

Rwanda 2000 Rwanda 2010 33.0 41.4 53.3 49.3 NA 52.5 57.7 57.1 74.8 78.3 79.5 79.3 72.1 73.1 76.6 76.0

Tanzania 1999 Tanzania 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAUganda 2000.5 Uganda 2011 NA 2.0 36.7 26.7 NA 8.7 46.4 36.6 95.2 20.8 56.1 50.6 NA 18.6 53.7 47.8Zambia 2001.5 Zambia 2013.5 NA 21.6 24.1 22.1 41.7 26.1 34.9 32.3 22.3 24.3 45.0 44.1 29.3 21.6 41.3 38.1

Zimbabwe 1999 Zimbabwe 2010.5 23.2 25.1 26.5 25.1 26.1 27.6 30.0 28.5 24.3 21.7 29.4 27.7 23.2 23.3 29.1 26.9

Bangladesh 2004 Bangladesh 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NACambodia 2000 Cambodia 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NANepal 2001 Nepal 2011 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAPhilippines 2003 Philippines 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Continued
98

Table 3.32—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAColombia 2000 Colombia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NADominican 

Republic 

2002 

Dominican 

Republic 

2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Peru 2000 Peru 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAEgypt 2000 Egypt 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAJordan 2002 Jordan 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAPooled Average 17.8 23.2 36.2 29.7 10.3 26.4 33.1 29.7 32.6 36.1 43.3 41.5 23.6 30.0 40.9 37.8NA=not asked. 
99 

Bednet use by children under age 5 

Levels 

Across the 27 surveys with data, in large cities the average use of bednets by children under age 5 is similar 

across levels of poverty, ranging from 21-25% (see Figure 3.23, left panel). The differentials are greater in 

other urban areas, ranging from 35% in non-poor households to 21% in moderately poor households. The 

differentials are widest in rural areas, where 33% of non-poor children slept under a bednet the night 

preceding the survey, compared with 16% of extremely poor children. Fifteen of the endline surveys include 

data on children sleeping under bednets. For these surveys, use by large city extremely poor children ranged 

from 13% in Zimbabwe to 88% in Tanzania (see Table 3.33). Ten of the 16 countries had less than half of 

this group of children sleeping under a bednet. 

Decadal change 

Decadal change can be calculated for 11 countries where children’s bednet use was ascertained in both 

baseline and endline surveys. In all three areas of residence, the decadal improvement in coverage was 

closely associated with poverty level, with the greatest gains made among the non-poor (see Figure 3.23, 

right panel). Use increased for the large city extremely poor children in 10 of the surveys and up to 44 

decadal percentage points in Rwanda. Cameroon was the only country where bednet use decreased (see 

Table 3.34). 

Figure 3.23. Pooled average coverage of bednet use by children under age 5 (left panel) and pooled 

average decadal change in coverage (right panel), by poverty according to level of urbanicity 

24.8

35.3 33.4

21.0 21.2 18.5 23.2 27.8

16.1

Large cities Other urban areas Rural areas

Percentage

Bednet use by children under age 5

Not poor Moderately poor Extremely poor

12.8 12.4

24.0

14.9 19.4 26.0

17.2

25.0 30.5

Large cities Other urban areas Rural areas

Percentage point change

Pooled average decadal change in bednet use by 

children under age 5

Not poor Moderately poor Extremely poor
100

Table 3.33. Bednet use by children under age 5 by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 * 25.8 16.4 20.6 * 52.0 29.4 34.3 (33.2) 22.3 22.8 22.8 (38.9) 31.3 22.9 23.6 Burkina Faso 2010 48.4 46.4 40.9 43.2 (69.3) 70.8 61.1 63.3 * 66.5 58.5 59.0 55.8 62.5 57.7 58.1

Cameroon 2004 20.0 28.7 36.2 30.6 16.5 17.1 14.0 15.3 * 12.6 8.2 8.7 17.5 20.2 12.1 14.4Cameroon 2011 19.4 24.7 26.6 25.4 14.9 18.0 19.0 18.6 24.4 18.9 15.6 16.0 19.1 20.8 17.9 18.4

Cote D’Ivoire 1998-99 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NACote D’Ivoire 2011-12 23.0 27.0 29.6 28.0 44.3 41.7 42.3 42.3 (32.9) 52.6 52.9 52.7 31.1 40.6 47.4 45.6

Ethiopia 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Ethiopia 2011 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAGhana 2003 * 6.8 8.9 8.8 * 8.6 9.7 9.7 * 21.5 19.1 19.4 * 13.8 15.9 15.6Ghana 2014 * 33.1 32.7 33.0 (36.6) 44.4 44.6 44.3 61.0 62.9 59.6 60.3 51.4 48.3 50.2 49.8

Guinea 1999 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Guinea 2012 (45.0) 33.3 18.9 22.7 (36.8) 44.3 41.9 42.2 (29.7) 29.7 35.8 35.4 38.0 35.0 34.0 34.2Kenya 2003 73.2 53.3 29.8 45.1 (74.9) 41.5 22.5 31.9 59.3 30.6 9.8 12.9 68.3 38.0 12.0 18.0Kenya 2014 72.2 81.9 68.5 72.6 78.9 76.0 67.3 70.2 68.0 69.8 56.8 58.0 73.7 75.3 60.0 62.7

Mali 2001 58.8 57.6 43.1 51.1 * 50.8 51.7 52.6 (73.0) 46.6 39.8 40.5 67.8 51.9 41.3 43.2Mali 2012-13 (77.9) 78.1 74.0 74.9 * 83.1 82.9 82.8 * 83.9 79.7 80.0 80.9 82.0 79.5 79.7

Mozambique 2003 35.1 30.8 14.9 21.6 41.9 27.3 13.2 17.2 * 10.9 7.7 7.8 37.3 22.5 9.1 10.9Mozambique 2011 (63.1) 56.3 42.9 48.2 (71.6) 59.3 56.2 56.8 * 44.0 39.5 39.6 61.1 53.3 43.4 44.2

Niger 1998 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Niger 2012 (49.0) 50.4 55.2 54.1 (59.2) 49.0 43.1 44.0 * (33.6) 23.4 23.4 49.0 45.6 26.5 27.1Nigeria 2003 4.0 3.4 4.7 4.1 (8.6) 3.1 6.8 5.6 (15.4) 10.2 8.4 8.9 7.9 5.3 7.4 6.8Nigeria 2013 27.4 22.9 17.6 19.2 37.2 24.8 22.0 22.9 29.8 25.0 19.1 19.9 30.6 24.6 19.7 20.6

Rwanda 2000 * 60.3 35.2 38.6 * 37.3 24.5 26.7 * 2.8 2.3 2.4 * 10.8 5.6 6.2Rwanda 2010 88.5 88.3 79.5 82.8 * (84.8) 75.6 76.9 84.1 83.4 72.6 74.4 85.4 84.1 73.1 75.1

Tanzania 1999 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NATanzania 2010 * 88.2 87.5 87.4 87.3 86.1 77.8 81.7 80.6 78.1 73.6 74.2 83.6 82.9 74.5 76.2

Uganda 2000-01 * * 33.3 33.7 * * 23.8 23.8 * * 7.6 7.6 * (15.6) 10.1 10.1Uganda 2011 (77.8) 86.5 73.7 78.7 * 80.1 67.2 70.5 * 69.5 56.9 57.7 89.4 76.7 58.3 60.1

Zambia 2001-02 * 16.1 16.5 16.9 * 35.4 26.7 29.9 * 53.5 15.2 16.2 * 35.3 17.2 19.4Zambia 2013-14 (44.9) 29.4 22.9 25.9 68.2 59.3 53.0 55.7 (63.5) 58.1 51.3 51.7 62.7 48.8 48.7 49.1

Zimbabwe 1999 * 8.2 4.0 5.8 * 11.5 7.0 9.3 * 1.8 1.3 1.3 1.1 7.5 2.2 3.5Zimbabwe 2010-11 (24.5) 17.1 12.8 15.5 27.3 27.1 22.9 25.4 14.9 15.2 13.1 13.5 20.8 18.8 14.0 15.7

Bangladesh 2004 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NABangladesh 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NACambodia 2000 * 90.7 97.8 93.9 * 92.6 88.8 89.1 * 79.8 75.6 76.0 * 82.6 77.3 77.8Cambodia 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NANepal 2001 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NANepal 2011 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAPhilippines 2003 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAPhilippines 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Continued
101

Table 3.33—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Armenia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAColombia 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAColombia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NADominican 

Republic 

2002 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Dominican 

Republic 

2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Peru 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAPeru 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAEgypt 2000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAEgypt 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAJordan 2002 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAJordan 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAPooled Average 24.8 21.0 23.2 23.3 35.3 21.2 27.8 27.5 33.4 18.5 16.1 16.6 26.9 25.0 21.1 23.0NA=not asked. 
102

Table 3.34. Decadal change in bednet use by children under age 5 by poverty according to level of urbanicity 

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Burkina Faso 2003 Burkina Faso 2010 NA 29.4 35.0 32.3 NA 26.9 45.3 41.4 NA 63.1 51.0 51.7 24.1 44.6 49.7 49.3

Cameroon 2004 Cameroon 2011 -0.9 -5.7 -13.7 -7.4 -2.3 1.3 7.1 4.7 NA 9.0 10.6 10.4 2.3 0.9 8.3 5.7

Cote D’Ivoire 1998.5 Cote D’Ivoire 2011.5 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAEthiopia 2000 Ethiopia 2011 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAGhana 2003 Ghana 2014 NA 23.9 21.6 22.0 NA 32.5 31.7 31.5 NA 37.6 36.8 37.2 NA 31.4 31.2 31.1

Guinea 1999 Guinea 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Kenya 2003 Kenya 2014 -0.9 26.0 35.2 25.0 3.6 31.4 40.7 34.8 7.9 35.6 42.7 41.0 4.9 33.9 43.6 40.6

Mali 2001 Mali 2012.5 16.6 17.8 26.9 20.7 NA 28.1 27.1 26.3 NA 32.4 34.7 34.3 11.4 26.2 33.2 31.7

Mozambique 2003 Mozambique 2011 35.0 31.9 35.0 33.3 37.1 40.0 53.8 49.5 NA 41.4 39.8 39.8 29.8 38.5 42.9 41.6

Niger 1998 Niger 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Nigeria 2003 Nigeria 2013 23.4 19.5 12.9 15.1 28.6 21.7 15.2 17.3 14.4 14.8 10.7 11.0 22.7 19.3 12.3 13.8

Rwanda 2000 Rwanda 2010 NA 28.0 44.3 44.2 NA 47.5 51.1 50.2 NA 80.6 70.3 72.0 NA 73.3 67.5 68.9

Tanzania 1999 Tanzania 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAUganda 2000.5 Uganda 2011 NA NA 38.5 42.9 NA NA 41.3 44.5 NA NA 47.0 47.7 NA 58.2 45.9 47.6Zambia 2001.5 Zambia 2013.5 NA 11.1 5.3 7.5 NA 19.9 21.9 21.5 NA 3.8 30.1 29.6 NA 11.3 26.3 24.8

Zimbabwe 1999 Zimbabwe 2010.5 NA 7.7 7.7 8.4 NA 13.6 13.8 14.0 NA 11.7 10.3 10.6 17.1 9.8 10.3 10.6

Bangladesh 2004 Bangladesh 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NACambodia 2000 Cambodia 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NANepal 2001 Nepal 2011 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAPhilippines 2003 Philippines 2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Continued
103

Table 3.34—Continued

Large cities Other urban areas Rural areas National 

Country Survey Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total Not poor 

Moderately 

poor 

Extremely 

poor Total Not poor

Moderately 

poor 

Extremely 

poor Total 

Armenia 2000 Armenia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAColombia 2000 Colombia 2010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NADominican 

Republic 

2002 

Dominican 

Republic 

2013 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Peru 2000 Peru 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAEgypt 2000 Egypt 2014 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAJordan 2002 Jordan 2012 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NAPooled Average 14.9 17.2 16.4 12.4 19.4 25.0 22.6 24.0 26.0 30.5 30.0 17.0 20.9 28.8 27.4 12.8NA=not asked. 

105 

4. Discussion and Conclusions 

In this study, we examined health outcomes and poverty status of children under age 5 by area of residence 

in 26 low- and middle-income countries surveyed by DHS. We selected all countries where DHS surveys 

were conducted between 1998 and 2004 and in 2010 or after if they had at least one city with estimated 

population one million or over in 2014, and this city was distinguishable from other urban areas in the 

dataset. In these countries, we examined the relationship between poverty, area of residence, and health 

indicators among children under age 5. Poverty was measured using the unsatisfied basic needs 

methodology, which is comparable across countries over time. We counted households as poor if they met 

one of the following four conditions: the house was poorly constructed, had inadequate sanitary facilities, 

was crowded, or the household exhibited economic dependency. Households that met one of these criteria 

were considered moderately poor, while those that met two or more criteria were considered extremely 

poor. Households that met no criteria were considered non-poor. It is important to note that non-poor is not 

synonymous with “wealth.” 

Across the 26 countries studied, we find that the vast majority of children under age 5 are extremely or 

moderately poor. Poverty among children is more concentrated than it is among adults. While the 

concentration of children in poverty is highest in rural areas, it is still great in urban areas. The focus of the 

study is poverty within large cities; results for other urban areas and rural areas are included in the report 

for comparison. The report is descriptive and does not include confidence intervals or significance testing. 

It was guided by several important questions: 

What is the level of poverty among children under age 5 by area of residence? 

Three out of four children under age 5 live in extreme poverty. About half of children under age 5 living in 

large cities are extremely poor; over half in other urban areas are extremely poor; and more than 4 out of 5 

are extremely poor in rural areas. Overall, only one in 10 children and fewer than one in 20 in rural areas 

are not poor. Given that the threshold for poverty used in this report was fairly low, the findings indicate a 

quite dire situation for the health and well-being of young children. 

Is the percentage of poor children greater than the percentage of the poor in general? 

Children under age 5 are more concentrated in the extremely poor category than the general household 

population. This over-concentration occurs more frequently in large cities than in other urban or rural areas. 

It is likely that this over-concentration is caused primarily by two factors. Fertility is generally higher among 

the extremely poor, and adults in extremely poor households are likely to be younger and more concentrated 

in the higher part of the fertility-by-age curve. 

Is poverty among children increasing or decreasing? 

Trends in poverty among children under age 5 vary with the size of residential area. While extreme poverty 

as a whole and extreme poverty in rural areas have decreased, extreme poverty has increased in large cities. 

In those large cities, the not poor have also increased. It is likely that economic progress has not been 

uniform and that economic improvement has provided an incentive for the extremely poor to migrate from 

rural areas to urban areas with sub-standard housing conditions. 

In which countries is the percentage of poor children greatest? In which countries is the percentage 

of poor children greatest in large cities? 
106 

The latest surveys show that six countries have more than 90% of children under age 5 in extreme poverty, 

with Ethiopia (99%) and Niger (98%) having the most children living in extreme poverty. Four countries 

have less than 30% of their children in extreme poverty, with Armenia having the least (9%). 

The pattern by country holds true for children in the large cities. Ethiopia and Niger lead the list with 90% 

or more in extreme poverty, with Armenia having the least. 

Are large city poor children more disadvantaged in health status than poor children from other 

urban and rural areas? 

The chances of survival for children under age 5 are greatest in urban areas when compared to rural areas. 

However, poor children in large cities and other urban areas have similar chances of survival to age 5. 

Nutritional status of poor children in large cities is better than in other urban areas, which in turn is better 

than that of poor children in rural areas. The better nutritional status of children who live in large cities 

may be due to the advantage they enjoy from the variety of foods available to them. The prevalence of 

major illness among the poor shows no difference for fever, and a small advantage of living in large cities. 

Has the health status of poor children improved? Has the health status of large city poor children 

improved? 

The health status of poor children under age 5 has substantially improved in both infant and child mortality, 

with the greatest decline of decadal rates among the extremely poor. Small improvements in nutritional 

status associated with stunting and anemia have also occurred. Nutritional status has improved more among 

the poor than non-poor children in all areas, including large cities. In those large cities, stunting has declined 

more for moderately poor than extremely poor children although the opposite is true for anemia. 

Has the gap in health status narrowed between poor and non-poor children? In large-urban areas? 

The survival gap between the poor and not poor has narrowed considerably. Similarly, the disadvantage of 

poor children in stunting and anemia has been reduced. For anemia, the narrowing of the gap with the not 

poor has been greatest among the extremely poor. The narrowing of the gaps has occurred in large cities 

but has not been greater than in the other areas. 

Is there a gap in health service utilization between poor and non-poor children? In large cities and 

other urban areas? 

Almost by definition, larger cities tend to have a greater number of health facilities than smaller urban areas. 

Whether facilities in larger cities are actually more accessible to all residents is an open question. Poor 

households are often concentrated in specific sections of cities, and their access to health services may thus 

be more geographically restricted than the non-poor. By their very size, and by transportation difficulties, 

spatial segregation of the poor may pose even greater challenges to health care access in large cities than in 

smaller urban areas. However, this depends on country- and city-specific factors such as the spatial 

concentration of poverty, the location of facilities, and other barriers to health care such as cost, insurance, 

opening hours, and so forth. 

A gap in health-service utilization between poor and non-poor children is substantiated by the evidence 

shown here, both overall and within large cities. Among the 12 indicators of health service use presented 

in this report, nine show moderate or large differences between the poor and the not poor. With medical 

ANC, vaccinations, and use of ORT for diarrhea, there were small or no differences between the poor and 

not poor. For children in large cities, there are fewer indicators with a moderate or large gap between the 

poor and not poor. Those with moderate or large differences in large cities are four or more ANC visits, 
107 

medical attendance of live births, the proportion of women with birth spacing less than 36 months, and 

medical assistance for children with fever or diarrhea. 

Has the gap in health service utilization narrowed? 

There have been improvements in most indicators of health service use between the baseline and endline 

surveys. The gap between the poor and not poor has narrowed for eight indicators of health service use. 

However, there was no narrowing or an increase for three indicators. In large cities, the gap decreased for 

10 indicators although the narrowing was small for three. The gap in full basic vaccination increased in 

large cities and there was no change for ORT. 

It is clear that the advantages of living in an urban area (amenities, infrastructure, roads, and health facility 

access) are not conferred to all women and children. In survival, we see stark disparities across levels of 

poverty. For all indicators, the extremely poor in urban areas fair better than their rural extremely poor 

counterparts, but not as well as non-poor rural children. 

Limitations of this study 

• World geographic regions are not fully represented in the study because DHS surveys are primarily 

concentrated in sub-Saharan Africa. 

• There have been changes in questionnaires over time and survey-specific customizations that 

limited the selection of indicators. 

• Urban areas are country-defined and urban boundaries may have changed over time in accordance 

with changes in census definitions. 

• Small sample sizes of some poverty-urbanicity groups affect the accuracy of estimates for these 

groups. A number of country-specific results had to be suppressed due to these limitations.

• As this is a comparative report, tests of statistical significance of differences were not conducted. 

Conclusion 

This study is the first to focus on the health conditions for children under age 5 by level of urbanicity and 

a comparable measure of absolute poverty. However, the study results raise additional questions: Are 

differences in health status more related to urbanicity, poverty level, availability of health services, differing 

levels of parent’s education, culture of child care, migration status, or other background variables? Why do 

some countries have large differences in health service use for comparable levels of poverty? Why are some 

countries improving health status and narrowing the gaps between the poor and not poor and other countries 

are not? These questions require in-depth investigation in order to bring the health status of the poor up to 

the non-poor in the best performing countries and to indicate the way forward for achieving Sustainable 

Development Goal 3 – ensuring healthy lives and promoting wellbeing for all at all ages. 

109 

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Appendix Table A1. Imputation of number of sleeping rooms based on urban/rural 

area and individual household wealth score. 

 Imputation coefficients 

Country Survey Year Survey used constant 

Urban/rural 

area (hv025) 

Household 

wealth score 

(hv271) 

Burkina Faso 2003 1998 0.847 1.109 0.035 

Ghana 2003 1998 1.119 0.341 0.071 

Rwanda 2000 2010 1.368 0.424 0.357 

Uganda 2000-01 2006 0.090 0.919 0.396 

Zambia 2001-02 2007 1.367 0.336 0.445 

Zimbabwe 1999 2005 0.091 0.657 0.364 

Cambodia 2000 2005 1.261 -0.012 0.287 

Nepal 2001 2006 1.472 0.293 0.278 

Philippines 2003 2013 1.676 0.250 0.445 

Armenia* 2000 2005 1.214 0.572 0.256 

* hv025 not available, used sh40.