DEMOGRAPHIC

AND

HEALTH

SURVEYS

DHS WORKING PAPERS

2018 No. 135

Shireen Assaf

Thomas Pullum

February 2018

This document was produced for review by the United States Agency for

International Development.

Household and Community Risk Factors and Child 

Well-Being in Low- and Middle-Income Countries

DHS Working Paper No. 135 

Household and Community Risk Factors and Child 

Well-Being in Low- and Middle-Income Countries 

Shireen Assaf

Thomas Pullum

ICF

Rockville, Maryland, USA

February 2018

Corresponding author: Shireen Assaf, International Health and Development, ICF, 530 Gaither Road, 

Suite 500, Rockville, MD 20850, USA; telephone: +1 301–572–0950; fax: +1 301–572–0999; email: 

Shireen.Assaf@icf.com
Acknowledgments: This working paper was funded by the USAID’s Center for Children in Adversity 

(CECA), as part of a larger effort to use data from The Demographic and Health Surveys Program to 

describe how outcomes for children are associated with orphanhood, household structure, and household 

characteristics.

Editor: Bryant Robey

Document Production: Natalie Shattuck

The DHS Working Papers series is a prepublication series of papers reporting on research in progress that 

is based on Demographic and Health Surveys (DHS) data. This research is carried out with support provided 

by the United States Agency for International Development (USAID) through The DHS Program (#AIDOAA-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. Additional information about The DHS Program can be obtained 

from ICF, 530 Gaither Road, Suite 500, Rockville, MD 20850 USA; telephone: +1 301-572-0200, fax: 

+1 301-572-0999, email: info@DHSprogram.com, internet: www.DHSprogram.com.

Recommended citation:

Assaf, Shireen, and Thomas Pullum. 2018. Household and Community Risk Factors and Child Well-Being 

in Low- and Middle-Income Countries. DHS Working Paper No. 135. Rockville, Maryland, USA: ICF.
iii 

CONTENTS 

TABLES ........................................................................................................................................................ v

FIGURES .................................................................................................................................................... vii

ABSTRACT.................................................................................................................................................. xi

1 INTRODUCTION .............................................................................................................................. 1

2 DATA AND METHODS ................................................................................................................... 5

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

2.2 Outcome Variables.............................................................................................................. 6

2.3 Risk Factors ........................................................................................................................ 7

2.4 Methods .............................................................................................................................. 8

3 RESULTS ........................................................................................................................................ 9

3.1 Orphanhood and Household Living Arrangements ............................................................. 9

3.2 Household Risk Factors .................................................................................................... 11

3.3 Cluster-level Variables ...................................................................................................... 12

3.4 Outcomes .......................................................................................................................... 14

3.4.1 Children under age 5 ........................................................................................... 14

3.4.2 Children age 5-14 ................................................................................................ 17

3.4.3 Girls age 15-17..................................................................................................... 18

3.5 Regression Results ........................................................................................................... 19

3.5.1 Children under age 5 ........................................................................................... 19

3.5.2 Children age 5-14 ................................................................................................ 23

3.5.3 Girls age 15-17..................................................................................................... 24

4 DISCUSSION ................................................................................................................................. 27

REFERENCES ............................................................................................................................................ 33

APPENDICES ............................................................................................................................................. 37

v

TABLES 

Table 1 List of surveys used in the analysis by HDI rank and USAID priority status ......... 5

Table 2 Summary of meta-analysis of the outcomes for children under age 5 ................ 21

Table 3 Summary of meta-analysis of no schooling for children age 5-14....................... 24

Table 4 Summary of meta-analysis of the outcomes for girls age 15-17 ......................... 26

Appendix Table 1 Percentage of orphanhood type among households with children under 

age 18 .................................................................................................................. 37

Appendix Table 2 Percentage of household living arrangements among households with 

children under age 18 .......................................................................................... 38

Appendix Table 3 Household risk factors ......................................................................................... 39

Appendix Table 4 Cluster-level variables .......................................................................................... 40

Appendix Table 5 Childhood outcomes for children under age 5 ..................................................... 41

Appendix Table 6 Percentage of children age 5-14 not attending school ........................................ 42

Appendix Table 7 Childhood outcomes for girls age 15-17 .............................................................. 43

Appendix Table 8 Pooled odds ratios from the meta-analysis of the outcomes for children 

under age 5 .......................................................................................................... 44

Appendix Table 9 Pooled odds ratios from the meta-analysis of no schooling for children 

age 5-14 ............................................................................................................... 45

Appendix Table 10 Pooled odds ratios from the meta-analysis of the outcomes for girls 

age 15-17 ............................................................................................................. 46

vii 

FIGURES 

Figure 1 Percentages of orphanhood type among households with children less than 

age 18. ................................................................................................................... 9

Figure 2 Percentages of household living arrangements among households with 

children less than age 18. .................................................................................... 10

Figure 3 Household risk factors ......................................................................................... 11

Figure 4 Cluster-level variables .......................................................................................... 12

Figure 5 Mean percentage of educated adults and educated women within clusters ....... 13

Figure 6 Nutrition indicators for children under age 5 ........................................................ 14

Figure 7 No treatment for symptoms of ARI for children under age 5 ............................... 15

Figure 8 No birth registration or birth certificate for children under age 5 .......................... 16

Figure 9 No school attendance for children age 5-14 ........................................................ 17

Figure 10 Nutrition indicators for girls age 15-17 ................................................................. 18

Figure 11 Adolescent fertility and sex before age 15 ........................................................... 19

Figure 12 I

2

 values and test of heterogeneity for the pooled odds ratio of proportion 

of educated women in a cluster ........................................................................... 29

Figure 13 I

2

 values and test of heterogeneity for the pooled odds ratio of crowding ........... 29

Figure 14 I

2

 values and test of heterogeneity for the pooled odds ratio of children 

living with relative compared with children living with both parents ..................... 30

Figure 15 I

2

 values and test of heterogeneity for the pooled odds ratio of children not 

living with relative compared with children living with both parents ..................... 31

Appendix Figure 1 Adjusted odds of being stunted, among children under age 5, for males vs. 

females (reference) .............................................................................................. 47

Appendix Figure 2 Adjusted odds of being stunted, among children under age 5, for three 

types of orphans vs. non-orphans (reference) ..................................................... 48

Appendix Figure 3 Adjusted odds of being stunted, among children under age 5, for four 

types of living arrangements vs. living with both parents (reference) .................. 49

Appendix Figure 4 Adjusted odds of being stunted, among children under age 5, for the 

number of educated women in the household vs. no educated women 

(reference) ............................................................................................................ 50

Appendix Figure 5 Adjusted odds of being stunted, among children under age 5, for the 

household crowding index and the youth dependency ratio ................................ 51

Appendix Figure 6 Adjusted odds of being stunted, among children under age 5, for the 

percentage of educated women in a cluster, nighttime lights, and travel 

time to a major city ............................................................................................... 52

Appendix Figure 7 Adjusted odds of being wasted, among children under age 5, for males vs. 

females (reference) .............................................................................................. 53

Appendix Figure 8 Adjusted odds of being wasted, among children under age 5, for three 

types of orphans vs. non-orphans (reference) ..................................................... 54

Appendix Figure 9 Adjusted odds of being wasted, among children under age 5, for four 

types of living arrangements vs. living with both parents (reference) .................. 55

Appendix Figure 10 Adjusted odds of being wasted, among children under age 5, for the 

number of educated women in the household vs. no educated women 

(reference) ............................................................................................................ 56
viii 

Appendix Figure 11 Adjusted odds of being wasted, among children under age 5, for the 

household crowding index and the youth dependency ratio ................................ 57

Appendix Figure 12 Adjusted odds of being wasted, among children under age 5, for the 

percentage of educated women in a cluster, nighttime lights, and travel 

time to a major city ............................................................................................... 58

Appendix Figure 13 Adjusted odds of anemia, among children under age 5, for males vs. 

females (reference) .............................................................................................. 59

Appendix Figure 14 Adjusted odds of anemia, among children under age 5, for three types of 

orphans vs. non-orphans (reference) .................................................................. 60

Appendix Figure 15 Adjusted odds of anemia, among children under age 5, for four types of 

living arrangements vs. living with both parents .................................................. 61

Appendix Figure 16 Adjusted odds of anemia, among children under age 5, for the number of 

educated women in the household vs. no educated women (reference) ............ 62

Appendix Figure 17 Adjusted odds of anemia, among children under age 5, for the household 

crowding index and the youth dependency ratio ................................................. 63

Appendix Figure 18 Adjusted odds of anemia, among children under age 5, for the percentage 

of educated women in a cluster, nighttime lights, and travel time to a 

major city .............................................................................................................. 64

Appendix Figure 19 Adjusted odds of receiving no treatment for ARI, among children under 

age 5 with ARI symptoms, for males vs. females (reference) ............................. 65

Appendix Figure 20 Adjusted odds of receiving no treatment for ARI, among children under 

age 5 with ARI symptoms, for only mother alive vs. non-orphans (reference). ... 65

Appendix Figure 21 Adjusted odds of receiving no treatment for ARI, among children under 

age 5 with ARI symptoms, for living with mother only vs. living with both 

parents (reference). ............................................................................................. 66

Appendix Figure 22 Adjusted odds of receiving no treatment for ARI, among children under 

age 5 with ARI symptoms, for the number of educated women in the 

household vs. no educated women (reference) ................................................... 67

Appendix Figure 23 Adjusted odds of receiving no treatment for ARI, among children under 

age 5 with ARI symptoms, for the household crowding index and the youth 

dependency ratio.................................................................................................. 68

Appendix Figure 24 Adjusted odds of receiving no treatment for ARI, among children under 

age 5 with ARI symptoms, for the percentage of educated women in a 

cluster, nighttime lights, and travel time to a major city ....................................... 69

Appendix Figure 25 Adjusted odds of not having a birth certificate or birth registration, among 

children under age 5, for males vs. females (reference) ..................................... 70

Appendix Figure 26 Adjusted odds of not having a birth certificate or birth registration, among 

children under age 5, for three types of orphans vs. non-orphans (reference) ... 71

Appendix Figure 27 Adjusted odds of not having a birth certificate or birth registration, among 

children under age 5, for four types of living arrangements vs. living with 

both parents (reference) ...................................................................................... 72

Appendix Figure 28 Adjusted odds of not having a birth certificate or birth registration, among 

children under age 5, for the number of educated women in the household 

vs. no educated women (reference) .................................................................... 73

Appendix Figure 29 Adjusted odds of not having a birth certificate or birth registration, among 

children under age 5, for the household crowding index and the youth 

dependency ratio.................................................................................................. 74
ix

Appendix Figure 30 Adjusted odds of not having a birth certificate or birth registration, among 

children under age 5, for the percentage of educated women in a cluster, 

nighttime lights, and travel time to a major city .................................................... 75

Appendix Figure 31 Adjusted odds of not attending school, among children age 5-14, for males 

vs. females (reference) ........................................................................................ 76

Appendix Figure 32 Adjusted odds of not attending school, among children age 5-14, for three 

types of orphans vs. non-orphans (reference) ..................................................... 77

Appendix Figure 33 Adjusted odds of not attending school, among children age 5-14, for four 

types of living arrangements vs. living with both parents (reference) .................. 78

Appendix Figure 34 Adjusted odds of not attending school, among children age 5-14, for the 

number of educated women in the household vs. no educated women 

(reference) ............................................................................................................ 79

Appendix Figure 35 Adjusted odds of not attending school, among children age 5-14, for the 

household crowding index and the youth dependency ratio ................................ 80

Appendix Figure 36 Adjusted odds of not attending school, among children age 5-14, for the 

percentage of educated women in a cluster, nighttime lights, and travel 

time to a major city ............................................................................................... 81

Appendix Figure 37 Adjusted odds of adolescent fertility, among girls age 15-17, for three 

types of orphans vs. non-orphans (reference) ..................................................... 82

Appendix Figure 38 Adjusted odds of adolescent fertility, among girls age 15-17, for four 

types of living arrangements vs. living with both parents (reference) .................. 83

Appendix Figure 39 Adjusted odds of adolescent fertility, among girls age 15-17, for the 

number of educated women in the household vs. no educated women 

(reference) ............................................................................................................ 84

Appendix Figure 40 Adjusted odds of adolescent fertility, among girls age 15-17, for the 

household crowding index and the youth dependency ratio ................................ 85

Appendix Figure 41 Adjusted odds of adolescent fertility, among girls age 15-17, for the 

percentage of educated women in a cluster, nighttime lights, and travel 

time to a major city ............................................................................................... 86

Appendix Figure 42 Adjusted odds of sex before age 15, among girls age 15-17, for three 

types of orphans vs. non-orphans (reference) ..................................................... 87

Appendix Figure 43 Adjusted odds of sex before age 15, among girls age 15-17, for four 

types of living arrangements vs. living with both parents (reference) .................. 88

Appendix Figure 44 Adjusted odds of sex before age 15, among girls age 15-17, for the 

number of educated women in the household vs. no educated women 

(reference) ............................................................................................................ 89

Appendix Figure 45 Adjusted odds of sex before age 15, among girls age 15-17, for the 

household crowding index and the youth dependency ratio ................................ 90

Appendix Figure 46 Adjusted odds of sex before age 15, among girls age 15-17, for the 

percentage of educated women in a cluster, nighttime lights, and travel 

time to a major city ............................................................................................... 91

Appendix Figure 47 Adjusted odds of being underweight, among girls age 15-17, for three 

types of orphans vs. non-orphans (reference) ..................................................... 92

Appendix Figure 48 Adjusted odds of being underweight, among girls age 15-17, for four 

types of living arrangements vs. living with both parents (reference) .................. 93

Appendix Figure 49 Adjusted odds of being underweight, among girls age 15-17, for the 

number of educated women in the household vs. no educated women 

(reference) ............................................................................................................ 94
x

Appendix Figure 50 Adjusted odds of being underweight, among girls age 15-17, for the 

household crowding index and the youth dependency ratio ................................ 95

Appendix Figure 51 Adjusted odds of being underweight, among girls age 15-17, for the 

percentage of educated women in a cluster, nighttime lights, and travel 

time to a major city ............................................................................................... 96

Appendix Figure 52 Adjusted odds of anemia, among girls age 15-17, for three types of 

orphans vs. non-orphans (reference) .................................................................. 97

Appendix Figure 53 Adjusted odds of anemia, among girls age 15-17, for four types of living 

arrangements vs. living with both parents (reference) ......................................... 98

Appendix Figure 54 Adjusted odds of anemia, among girls age 15-17, for the number of 

educated women in the household vs. no educated women (reference) ............ 99

Appendix Figure 55 Adjusted odds of anemia, among girls age 15-17, for the household 

crowding index and the youth dependency ratio ............................................... 100

Appendix Figure 56 Adjusted odds of anemia, among girls age 15-17, for the percentage of 

educated women in a cluster, nighttime lights, and travel time to a 

major city ............................................................................................................ 101
xi 

ABSTRACT 

This report focuses on the well-being of children age 0-17 using 10 outcomes in four domains: nutrition, 

health care, schooling, and child protection. The data used in the analysis were obtained from recent surveys 

conducted by The Demographic and Health Surveys Program, one survey in each of 30 countries selected 

on the basis of USAID priorities or low levels of the Human Development Index. The analysis describes 

the relationship between each outcome and risk factors at the levels of the child, household, and sample 

cluster. The working hypothesis, based on empirical generalizations found in the literature, was that risk 

factors would correspond with negative outcomes for all indicators in all countries. However, to the 

contrary, it is found that the effect of most risk factors cannot be generalized across all outcomes or all 

countries. For example, the effect of household structure, represented by the presence of biological parents 

and the relationship of the child to the household head, tends to be stronger for the child protection and 

schooling outcomes than for other outcomes, but this relationship is not consistent across all countries. The 

index of household crowding—the number of household members per room—has a strong association with 

most outcomes across all the surveys, but this generalization does not hold for schooling and birth 

registration. The analysis implies that the impact on child outcomes of household structure and other 

household-level or community-level variables can vary, sometimes substantially, across countries.

KEY WORDS: Child well-being, household structure, orphanhood status, household risk factors, 

community level risk factors, nutrition, schooling, child protection, vulnerable children

1

1 INTRODUCTION 

Surveys conducted by The Demographic and Health Surveys (DHS) Program include a great deal of 

information about children—persons age 17 and younger—in the household population. This report 

analyzes the relationship between outcomes that relate to child well-being, on the one hand, and background 

characteristics that potentially measure a child’s risk or vulnerability, on the other hand. The scope of the 

report is as broad as possible, including virtually all indicators of child well-being and child vulnerability 

that can be extracted from DHS surveys.

The literature on child well-being generally employs five domains: physical, psychological, cognitive, 

social, and economic (Pollard and Lee 2003). Several studies have used a combination of indicators in 

different domains to examine child well-being. A study by Kanamori and Pullum (2013) focused on 

deprivation of children’s basic human needs for health, water, sanitation, education, food, information, and 

shelter, using DHS data from 30 countries in sub-Saharan Africa. These data included child-specific health 

indicators, such as stunting and vaccination, and household-level indicators, such as source of drinking 

water and type of shelter. The Child Poverty and Deprivations Study, developed by UNICEF and conducted 

in 40 countries, uses individual-level data from DHS surveys or Multiple Indicator Cluster Surveys (MICS) 

to summarize indicators in seven domains: shelter, sanitation facilities, safe drinking water, information, 

food, education, and health (UNICEF 2007). UNICEF examines these domains through child-level and 

household-level indicators and publishes country-specific reports aimed at policymakers to highlight 

children’s vulnerability and deprivation in each country, as in Jamaica (UNICEF 2009a), Tanzania 

(UNICEF 2009b), and Nigeria (UNICEF 2009c).

Other studies have combined multiple indicators from several domains into a child well-being index. The 

Child and Youth Well-Being Index was developed to track trends over time in the well-being of children 

and youth in the United States (Land, Lamb, and Zheng 2011; Land et al. 2007). This index uses aggregatelevel indicators in seven domains: family economic well-being, health, safety/behavioral concerns, 

educational attainment, community connectedness, social relationships, and emotional/spiritual well-being. 

The index combines 28 national indicators, including poverty rates, mortality rates, and mathematics test 

scores (Land, Lamb, and Zheng 2011; Land et al. 2007). The Child Status Index was developed by 

O’Donnell et al. (2013) to monitor the situation of children made vulnerable by the HIV/AIDS pandemic, 

through orphanhood or otherwise. The index covers many of the same domains as in the study by Kanamori 

and Pullum and in the Child and Youth Well-Being Index. The Child Status Index is constructed by scoring 

households during home visits in the domains of food/nutrition, shelter and care, protection, health care, 

psychosocial concerns, and education (O’Donnell et al. 2013).

From our perspective, these studies have examined children’s well-being in terms of outcomes and risk 

factors. The distinction between an outcome and a risk factor is not always clear, as some outcomes are 

themselves risk factors for other outcomes. For instance, stunting can be viewed as an outcome of 

household-level risk factors, but it can also be a risk factor for not attending school (Grantham-McGregor 

et al. 2007). Outcomes and risk factors can be differentiated such that, from a policy and program 

intervention perspective, outcomes are the end products to be improved and risk factors can be mitigated to 

help achieve these improvements. Risk factors can cut across several levels related to the child, parents or 

caregivers, the household, and the community or country where the child lives. Each level has its own risk 
2

factors or vulnerabilities. For instance, orphanhood, an uneducated caregiver, a crowded household, a poor 

community, and a developing country can all reduce the chance that a child will receive a formal education. 

In addition, vulnerability at each level may contribute to vulnerability at another level. Household risk 

factors such as overcrowding, a high dependency ratio, and poverty can be closely tied to the characteristics 

of the community where the household is located.

An analysis by UNICEF covering nine child outcomes, ranging from vaccination to early marriage, 

identified a vulnerable child as one whose household is in the bottom two wealth quintiles, who is not living 

with either parent, who has lost one or both parents, and whose household has no educated adults (UNICEF 

2014). Akwara et al. (2010) analyzed 60 nationally representative surveys from 36 countries on three 

outcomes (wasting, school attendance, and early sex) and several child-level and household-level risk 

factors. The authors highlighted several household-level variables, such as wealth, education of household 

head or eldest female, and sanitation, as better measures of child vulnerability than orphanhood status or 

living with a chronically ill adult.

Previous research has shown that children tend to experience worse outcomes if they are an orphan of any 

kind (Akwara et al. 2010; Case, Paxson, and Ableidinger 2004; Mishra and Bignami-Van Assche 2008; 

UNICEF n.d. 2014), if they do not live with both parents (UNICEF 2014), or if they live in a household 

with few educated adults or low level of literacy (Assaf, Kothari, and Pullum 2015; Hobcraft 1993; Pezzulo 

et al. 2016; UNICEF 2014), a high level of crowding (Evans 2006; Gove, Hughes, and Galle 1983; Solari 

and Mare 2012), or a high dependency ratio (Hadley et al. 2011; UNICEF 2014). Boys tend to have worse 

nutrition outcomes than girls (Assaf, Kothari, and Pullum 2015; Kanamori and Pullum 2013) but better 

health care (Kanamori and Pullum 2013; Pandey et al. 2002) and schooling (Kanamori and Pullum 2013; 

Shahidul and Karim 2015; UNESCO 2012; UNICEF 2014). While the education of both the father and 

mother in the household is important for the child’s well-being, the mother’s education appears to be more 

important than the father’s for the child’s health (Cochrane, Leslie, and O’Hara 1982; Hobcraft 1993; 

Wamani et al. 2004).

There is evidence that children tend to experience worse outcomes if they live in a community with a low 

level of development, usually represented in the literature by urban-rural residence or the household wealth 

index (Assaf, Kothari, and Pullum 2015; Grantham-McGregor et al. 2007; Hadley et al. 2011; Kanamori 

and Pullum 2013; UNICEF 2014; Victora et al. 2003). Another characterization of development can be 

produced using spatial data involving the level of nighttime lights or nearness to a major city (Nelson 2008; 

National Centers for Environmental Information 2015; Uchida and Nelson 2010). These variables are 

highly correlated with urban-rural residence as well as household wealth quintile or poverty, and are seen 

as a more accurate measure of development and urban-rural classification (Elvidge et al. 2009; Ghosh et al. 

2010; Pezzulo et al. 2016; Uchida and Nelson 2010).

This analysis will treat these empirical generalizations as hypotheses, and will assess their applicability to 

a range of child outcomes in 30 low- and middle-income countries, using DHS data. The analysis will focus 

on four domains to measure child well-being: nutrition, health care, schooling, and child protection. Each 

domain can be measured with several outcomes that span different age groups within the age range 0-17. 

Due to the nature of DHS samples, this report focuses on children living in a household. It does not include 

children living in the streets or in orphanages, who may have a greater risk for poor outcomes than children 

living in a household. The indicators of child well-being used in this report follow the age categories in the 
3

DHS, referring to children age 0-4, children age 5-14, and children (specifically girls) age 15-17. The 

analysis highlights the household-level and community-level risk factors for adverse childhood outcomes, 

after controlling for orphanhood and household living arrangements. The findings can be used to identify 

children, households, and communities with high risk and can provide guidance for programs to improve 

outcomes for children.

5

2 DATA AND METHODS 

2.1 DHS Data 

The analysis uses data from DHS surveys in 30 countries—the most recent survey for each country. The 

first criterion for selection was high priority for USAID’s Center for Children in Adversity. That criterion 

led to the selection of the most recent DHS surveys in Armenia, Cambodia, Colombia, Moldova, Rwanda, 

and Uganda, as shown in Table 1. The second criterion was high priority for USAID’s activities related to 

maternal and child health (MCH). The third criterion was a low rank on the Human Development Index—

from a possible rank of 1 to 188 (UNDP 2016). The total number of countries was arbitrarily set at 30, for 

convenience of presentation.

Table 1 List of surveys used in the analysis by HDI rank and USAID priority status 

Country Survey year HDI rank Priority country

Armenia 2010 85 CA

Benin 2011-12 166 -

Burkina Faso 2010 183 -

Burundi 2010 184 -

Cambodia 2014 143 CA

Chad 2015 185 -

Colombia 2010 97 CA

Congo Democratic Republic 2013-14 176 MCH

Côte d’Ivoire 2011-12 172 -

Ethiopia 2011 174 MCH

Ghana 2014 140 MCH

Guinea 2012 182 -

Haiti 2012 163 MCH

Kenya 2014 145 MCH

Liberia 2013 177 MCH

Madagascar 2008-09 154 MCH

Malawi 2015-16 173 MCH

Mali 2012 179 MCH

Moldova 2005 107 CA

Mozambique 2011 180 MCH

Myanmar 2015-16 148 -

Nepal 2011 145 MCH

Nigeria 2013 152 MCH

Rwanda 2014-15 163 CA,MCH

Senegal 2015 170 MCH

Sierra Leone 2013 181 -

Tanzania 2015-16 151 MCH

Togo 2013-14 162 -

Uganda 2011 163 CA,MCH

Zambia 2013-14 139 MCH

Notes: HDI - Human Development Index; CA - USAID Children in Adversity priority country; MCH - USAID MCH 

priority country
6

2.2 Outcome Variables 

Ten outcomes in four domains were used in the analysis. The domains and their related outcomes are:

Nutrition: Stunted, wasted, any anemia (for children under age 5); underweight based on body 

mass index (BMI), and any anemia (for girls age 15-17)

Health care: No treatment sought in a health facility for symptoms of Acute Respiratory Infection, 

or ARI, possibly pneumonia (for children under age 5)

Schooling: Not in school (for children age 5-14)

Child protection: Adolescent fertility, first sex before age 15 (for girls age 15-17); no birth 

registration (for children under age 5)

The outcome “any anemia” was constructed for two age groups: children under age 5 and girls age 15-17. 

The DHS program does not generally collect biomarker data for boys age 15-17, so “underweight” and 

“any anemia” for age 15-17 were only available for girls. In addition, “adolescent fertility” and “first sex 

before age 15” are included for girls age 15-17 but not for boys. The outcome variables were constructed 

according to the definitions below, in all cases aligned in a negative (“bad outcome”) direction.

Children under age 5:

Stunting: The proportion of de facto children under age 5 with a height-for-age z-score below the 

median of the World Health Organization (WHO) 2007 reference population by more than two 

standard deviations.

Wasting: The proportion of de facto children under age 5 with a weight-for-height z-score below 

the median of the WHO 2007 reference population by more than 2 standard deviations.

Any anemia: The proportion of de facto children age 6-59 months with a hemoglobin level less 

than 11 grams per deciliter. Hemoglobin levels are adjusted for altitude.

Care seeking: Among children under age 5 who had symptoms of ARI in the 2 weeks before the 

survey, the proportion for whom advice or treatment was sought from a health facility or provider. 

Excludes treatment sought from pharmacies, shops, or traditional healers. The information for this 

variable is only available for those children whose mother was alive and living in the same 

household as the child.

No birth registration: The proportion of de jure children under age 5 without a birth certificate or 

birth registration.

Children age 5-14:

Not in school: The proportion of children age 5-14 who did not attend school at any time during 

the current school year.
7

Girls age 15-17:

Underweight: The proportion of girls age 15-17 with BMI lower than 18.5. Excludes girls who 

were pregnant or gave birth in the last 2 months before the survey.

Any anemia: The proportion of girls age 15-17 with a hemoglobin level lower than 12 grams per 

deciliter, if not pregnant, and lower than 11 grams per deciliter if pregnant. Hemoglobin levels are 

adjusted for altitude.

Adolescent fertility: The proportion of girls age 15-17 who are currently pregnant or have ever 

had a birth.

Sex before age 15: The proportion of girls age 15-17 who had sexual intercourse before age 15.

2.3 Risk Factors 

The risk factors were divided into variables at child, household, and community levels. The child-level 

variables include child’s sex (male, female), orphanhood status (both parents are alive, mother is alive but 

father is dead, father is alive but mother is dead, both parents are dead), and household living arrangements 

(living with both parents, living with mother only, living with father only, living with neither parent but 

household head is a relative, living with neither parent and household head is not a relative).

The household-level variables include a crowding index, the youth dependency ratio, and the number of 

women in the household who have had some schooling. The crowding index was computed by taking the 

number of household members who slept in the household the night before the survey and dividing by the 

number of rooms used for sleeping. The youth dependency ratio was computed by taking the total number 

of household members under age 15 and dividing by the total number of household members age 15-64. 

There was a high correlation between the youth dependency ratio and the total dependency ratio, which 

includes the number of household members age 65 and above as well as the number below age 15, but only 

the youth dependency ratio was used in the regression models. The number of educated women in the 

household was computed as the total number of women in the household age 18 and older with at least a 

primary education. The variable was categorized as none, one, two, and three or more. The total number of 

educated adults in the household was highly correlated with the total number of educated women, but only 

the number of educated women was included in the models.

In the typical design of DHS samples, the primary sampling units, or “clusters,” are enumeration areas from 

the country’s most recent census. Enumeration areas can range from villages in rural areas to neighborhoods 

in urban areas, with boundaries that roughly correspond with those of local administrative units. We will 

describe the enumeration area or cluster as a “community,” but it should be understood that this term is 

being used loosely. The cluster is a geographically defined context within which DHS data can be 

aggregated and that can be matched with spatially structured data, but we cannot infer that it has the social 

or cultural meaning that ideally would be captured by this label.

The community-level variables include the percentage of adult women in a DHS cluster who are educated, 

the travel time to the nearest city with a population of at least 50,000, and the nighttime lights indicator. 

These continuous cluster-level variables were found to be highly associated with place of residence and 

wealth quintile, as described in the introduction, and were used in place of urban-rural residence and 
8

household wealth quintile in the regression models. Any missing values for travel time and nighttime lights 

were replaced by the median value for the combination of region and place of residence.

The variables on travel time and nighttime lights were obtained from external sources and linked with the 

DHS data, using the geographic location of the DHS clusters (Burgert et al. 2013). The latitude and 

longitude of DHS clusters are collected using GPS receivers. These are verified and then geographically 

masked to protect respondent confidentiality. Geographic spatial data was extracted from the raster datasets. 

Urban locations use a 2 kilometer (km) buffer around the DHS geomasked location; for rural points the 

buffer is 10 km. The buffer size accounts for DHS displacement procedures used to protect the 

confidentiality of the respondents (Perez-Haydrich et al. 2013). Travel time to the nearest city of at least 

50,000 people is a measure of accessibility, as described by Nelson (2008). Travel time is measured using 

a cost-distance algorithm where cost is measured in units of time, taking into consideration the transport 

network (road, rail, rivers, etc.), environment (land cover and slope), and political factors (borders) that 

affect travel times between locations. The nighttime lights variable was obtained from the Earth 

Observations Group in NOAA (National Centers for Environmental Information 2015). This variable is 

based on observations of the average radiance composite images, eliminating stray light, lightning, lunar 

illuminations, and cloud-cover before averaging.

2.4 Methods 

The analysis involves studying the association between the outcomes and the described risk factors at the 

child, household, and community levels. Adjusted logit regressions were fitted for each survey and each 

outcome, using all the risk factors. Separate models were estimated for orphanhood status and household 

living arrangements, as these two variables are highly associated. A meta-analysis was then performed using 

the metan macro in Stata 14 (Harris et al. 2008). The meta-analysis provided a pooled odds ratio from all 

the surveys that accounted for the sample size by taking the sample from each survey divided by the total 

from all the surveys combined. Heterogeneity tests (I2 tests) were also generated to indicate the level of 

heterogeneity between the surveys. An I2 value of 25%-50% is considered to have low heterogeneity, 50%-

75% is moderate, and more than 75% is high (Higgin et al. 2003). A non-significant I2 test would indicate 

failure to reject the null hypothesis that the surveys are homogenous, a desirable result for this type of 

analysis. The Results section presents a summary of the regression results to show whether the resulting 

pooled odds ratio was in the expected direction for the outcomes. Note that a pooled odds ratio can be 

significant even if only a few countries have a significant odds ratio. All analyses were performed with 

Stata 14. DHS sampling design and stratification were taken into account in the analysis.
9

3 RESULTS 

3.1 Orphanhood and Household Living Arrangements 

In all the surveys studied, close to 90% of children age 0-17 live with both parents (Appendix Table 1). 

While orphanhood is generally rare, some types of orphanhood are more common than others. Figure 1 

shows that in all the surveys the most common type of orphanhood is for children whose father has died 

but whose mother is alive, with a range from 2.5% of children in Armenia and Mali to approximately 8% 

in Burundi and Mozambique. The percentage of children whose mother has died but whose father is alive 

ranges from 1% in Armenia and Moldova to 3% in Haiti and Mozambique. Having both parents dead 

(double orphanhood) is even rarer, ranging from just 0.2% in Colombia and Nepal to 2% in Burundi, 

Malawi, Mozambique, Sierra Leone, Uganda, and Zambia. In Cambodia, Malawi, Sierra Leone, Uganda, 

and Zambia there is no significant difference between double orphanhood and single orphanhood with only 

the father alive.

Figure 1 Percentages of orphanhood type among households with children less than age 18 

0

1

2

3

4

5

6

7

8

9

10

Only mother alive Only father alive Both dead

Note: The figure excludes children that have both parents alive.
10 

Household living arrangements are closely linked with orphanhood but also include situations where a 

parent may be alive but not present in the household. The most common household living arrangement for 

children is to have both parents present (Appendix Table 2), followed by the mother only, as Figure 2 shows. 

Colombia has the highest percentage of children living with the mother only (33%), followed by Nepal, 

Haiti, Senegal, Kenya, and Ghana, all above 25%. In several countries there is no significant percentage 

difference between children living with the mother only and children living with a relative other than a 

parent as the household head. For most surveys, the least common household living arrangement for 

children is to have neither parent present but have a non-relative as the household head. In some countries, 

however, there is no significant difference between this type of living arrangement and living with the father 

only. In Zambia the percentage of children living with the father only is significantly lower than the 

percentage of children living with no relatives.

Figure 2 Percentages of household living arrangements among households with children less than age 18

0

5

10

15

20

25

30

35

40

Lives with mother only Lives with father only Lives with relative, no parent Does not live with relatives

Note: The figure excludes children that are living with both parents.
11 

3.2 Household Risk Factors 

Figure 3 summarizes the three household-level variables used in the regression models: the crowding index, 

the youth dependency ratio, and the number of educated women in the household. The latter was converted 

into a categorical variable for the regression models. Figure 3 includes several countries with high 

crowding—highest in Madagascar and Ethiopia, both with a crowding index close to 5. All the countries 

other than Moldova have a crowding index above 2. The youth dependency ratio, which measures the 

number of children under age 15 relative to the total number of persons age 15-64 in the household, is close 

to 1.5 for most countries and reaches almost 2 in Chad. Armenia and Moldova have the lowest youth 

dependency ratios and also the lowest crowding index. The mean number of educated women in the 

household ranges from approximately 0.3 in Burkina Faso and Mali to 1.79 in Armenia. Most countries had 

a mean close to one. (Appendix Table 3 presents the overall dependency ratio and the number of educated 

adults in the household.)

Figure 3 Household risk factors 

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Crowding Youth dependency ratio Mean number of educated women in the household
12 

3.3 Cluster-level Variables 

As mentioned, community-level variables include the percentage of educated women in a DHS cluster, the 

travel time to the nearest large city, and the nighttime lights indicator. The values for these cluster-level 

variables are shown in Appendix Table 4. Figure 4 shows the mean for nighttime lights and travel time to 

the nearest major city. These two variables are generally inversely related—a longer travel time to a major 

city tends to correspond with a lower value for the nighttime lights indicator. This is most apparent in 

Colombia and Ethiopia. Zambia is an exception, however, with a relatively high value for travel time but 

also the third-highest value for nighttime lights. The highest values for travel time are in Ethiopia, Chad, 

Zambia, and the DRC, and the lowest in Armenia, Moldova, and Colombia. Armenia and Colombia also 

have the highest values for nighttime lights.

Figure 4 Cluster-level variables 

-5

0

5

10

15

20

25

0

50

100

150

200

250

300

350

400

450

500

Nighttime lights

Access to major city 

Travel time Nighttime lights
13 

Figure 5 shows the percentage of educated adults and educated women by cluster, averaged for each 

country. The highest percentage both for all adults and for women is in Armenia, followed by Moldova and 

Cambodia. The lowest values are in Burkina Faso and Mali. The regression models used only the percentage 

of educated women.

Figure 5 Mean percentage of educated adults and educated women within clusters 

0

10

20

30

40

50

60

70

80

90

100

Access to major city 

Educated adults Educated women
14 

3.4 Outcomes 

3.4.1 Children under age 5 

Figure 6 summarizes the nutrition indicators for children under age 5. In Burundi and Madagascar nearly 

half of children under age 5 were stunted, and most countries studied had stunting levels above 30%. 

Colombia, Ghana, and Armenia had the lowest stunting levels, all below 20%. In Nigeria, Benin, and 

Burkina Faso over 15% of children under age 5 were wasted, compared with less than 3% in Rwanda and 

Malawi. A high percentage of children age 6-59 months were anemic. All countries except Rwanda had 

percentages of anemic children above 40%. In Burkina Faso, Mali, Sierra Leone, Guinea, and Côte d’Ivoire, 

over 70% of children age 6-59 months were anemic, and in Burkina Faso close to 90%. Appendix Table 5 

shows the estimates and confidence intervals for all outcomes for children under age 5. Seven of the 30 

countries (Armenia, Chad, Colombia, Kenya, Liberia, Nigeria, and Zambia) did not conduct hemoglobin 

testing, and therefore the anemia indicator could not be computed. In addition, Madagascar did not have 

data available to compute wasting.

Figure 6 Nutrition indicators for children under age 5 

0

10

20

30

40

50

60

70

80

90

100

Stunted Wasted Anemic
15 

Figure 7 shows that more than 70% of children under age 5 in Chad, Mali, and Ethiopia had no treatment 

sought for their ARI symptoms. In almost half of the countries, a majority of the children under age 5 did 

not have treatment sought for their ARI symptoms. Malawi and Sierra Leone had the lowest percentage for 

this indicator, both under 30%.

Figure 7 No treatment for symptoms of ARI for children under age 5 

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

100
16 

As Figure 8 shows, in Zambia and Chad close to 90% of children under age 5 did not have their birth 

registered, or had no birth certificate. The percentage was also high in Liberia, the DRC, Tanzania, Uganda, 

and Nigeria, all close to 70%. In contrast, only 0.4% of children in Armenia did not have a birth registration 

or certificate, and less than 10% of children in Moldova. This indicator was not available for Colombia, 

Ethiopia, and Togo.

Figure 8 No birth registration or birth certificate for children under age 5 

0

10

20

30

40

50

60

70

80

90

100
17 

3.4.2 Children age 5-14

As Figure 9 and Appendix Table 6 indicate, more than half of children age 5-14 in Burkina Faso, Mali, 

Chad, and Guinea did not attend school during the current school year, and in Senegal and Ethiopia more 

than 40% of children did not. In contrast, in Armenia, Nepal, Malawi, Haiti, Moldova, Kenya, and 

Colombia, only about 10% or less had no school attendance.

Figure 9 No school attendance for children age 5-14

0

10

20

30

40

50

60

70

80

90

100
18 

3.4.3 Girls age 15-17

Figure 10 shows that Ethiopia had a significantly higher percentage of girls age 15-17 who were 

underweight compared with the other countries. In Ethiopia 42% of girls were underweight according to 

their BMI, while in many other countries the percentages were close to 30%. Benin, Rwanda, and Togo had 

the lowest percentages of underweight girls, all close to 15%. Armenia and Senegal did not have data 

available to compute this indicator. (See Appendix Table 7 for all outcomes for girls age 15-17.)

Also, Figure 10 shows that in 25 of the 30 countries more than a third of girls age 15-17 were anemic, and 

in Mozambique, Haiti, Ghana, Togo, and Côte d’Ivoire more than half of girls. The lowest percentage of 

anemia among girls age 15-17 was in Ethiopia, at 12%. Data were not available to compute this indicator 

for eight countries: Armenia, Chad, Colombia, Kenya, Liberia, Nigeria, Senegal, and Zambia.

Figure 10 Nutrition indicators for girls age 15-17

0

10

20

30

40

50

60

70

80

90

100

Underweight Anemic
19 

As Figure 11 shows, in Mali, Mozambique, Chad, and Guinea, at the time of the survey more than one in 

every five girls age 15-17 had begun childbearing. In contrast, in Ethiopia, Cambodia, Rwanda, Burundi, 

Moldova, Myanmar, and Armenia adolescent fertility was less than 5%. In Liberia, Mozambique, Guinea, 

and Côte d’Ivoire more than one in every five girls age 15-17 had sex before age 15, and in the DRC, Sierra 

Leone, and Mali nearly 20%. Myanmar, Cambodia, Moldova, Nepal, and Burundi had low percentages for 

this indicator, all at 3% or lower. In Armenia, no girls age 15-17 reported having sex before reaching age 

15, and adolescent fertility was the lowest of any country, at only 0.4%.

Figure 11 Adolescent fertility and sex before age 15 

3.5 Regression Results 

Tables 2-4 summarize the regression results for the 10 outcomes. These are based on the pooled odds ratios 

produced from the meta-analysis of each outcome for the 30 countries in the analysis. The pooled odds 

ratios are found in Appendix Tables 8-10, and the forest plots in Appendix Figures 1-56. In Tables 2-4, 

green indicates that a result is in the expected direction and orange indicates that it is opposite to the 

expected direction. Positive signs indicate odds ratios more than one and negative signs indicate odds ratios 

less than one. The number of positive signs (+, ++, and +++) and negative signs (-, --, ---) indicates the 

level of significance. The tables also illustrate whether the result has a significant and high level of 

heterogeneity (I2 more than 75%), highlighted by a red box, to indicate that the result is country-specific 

and cannot be generalized across all the surveys.

3.5.1 Children under age 5 

Nutrition outcomes. Table 2 summarizes the pooled regression results of the outcomes for children under 

age 5. The nutrition outcomes are stunting, wasting, and anemia. Stunting showed results in the expected 

0

5

10

15

20

25

30

35

40

Adolescent fertility Sex before age 15
20 

direction for all risk factors. In addition, having both parents dead (compared with both parents alive) and 

living with a non-relative (compared with living with both parents) were the only non-significant predictors 

of stunting, mainly due to the low counts in these two categories. The pooled odds ratio was significant for 

almost all the subgroups (see Appendix Figures 1-6). Only the subgroups for child’s sex, crowding, and the 

percentage of women in a household who are educated had significant odds ratios for more than half the 

countries. For the remaining subgroups, the odds ratios were mainly non-significant. The results of the I2

test of heterogeneity for child’s orphanhood (Appendix Figure 2), household living arrangements 

(Appendix Figure 3), and the number of educated women in the household (Appendix Figure 4) suggest 

that the model represents either low level of heterogeneity or for some categories the non-significant I2 test 

indicates homogeneity.

The wasting and anemia indicators showed some results opposite to the expected direction, especially for 

the variables for orphanhood status and household living arrangements. In general, we would expect worse 

outcomes for any type of orphan (compared with both parents alive), and any living arrangement other than 

living with both parents. For the wasting outcome, however, children whose mother only was alive 

(compared with both parents alive) and children living with a relative other than parent or living with father 

only (compared with living with both parents) had lower significant pooled odds of being wasted. As the 

forest plot in Appendix Figure 8 shows, this result was found only in Colombia, where the odds ratio of 

being wasted for children with only the mother alive (compared with both parents alive) was 0.14 (95% 

C.I. 0.02, 0.98). For the other counties, except Cambodia and the DRC, this result was not significant; hence 

the low significance level of the pooled odds ratio (i.e. p-value <0.05), as shown in Table 2. This result also 

had a low level of heterogeneity according to the I2

test (I2=44.8%, p-value=0.007).

Appendix Figure 9 shows that children living with mother only were significantly more likely to be wasted 

than children living with both parents. The I2test also indicated that the surveys were homogenous for this 

result (I2 =20.6%, p-value=1.162). The odds ratios for children living with the father only and living with a 

relative and no parents were both in the unexpected direction, and the I2 test indicated that the surveys were 

homogenous for both risk factors. However, Appendix Figure 9 shows that for children living with the 

father only, compared with living with both parents, only Nigeria and Tanzania showed significantly lower 

odds of being wasted. In addition, only five countries—Burkina Faso, Colombia, Côte d’Ivoire, 

Mozambique, and Nigeria—showed significantly lower odds of being wasted if the child lived with a 

relative other than parent, compared with living with both parents. The odds ratios were not significant for 

the remaining countries for these two categories, except for a significant odds ratio in the expected direction 

for Nepal and for living with father only. The pooled odds ratio for not living with a relative was not 

significant for the wasting outcome, but it was highly significant with very high odds ratios in Burundi and 

Ghana (Appendix Figure 9). However, the wide confidence intervals indicate that there were few 

observations, and the results should be interpreted with caution.

For anemia, the significance of the pooled odds ratio for double orphans (compared with both parents alive) 

was based on only a few countries (see Appendix Figure 14). For 17 countries, this category was omitted 

because there were too few observations, and none of the remaining countries showed a significant odds 

ratio. The remaining single-orphan categories were not significant predictors of anemia. Seven countries—

Burkina Faso, Cambodia, Guinea, Myanmar, Senegal, Tanzania, and Uganda—showed significantly lower 

odds of children being anemic if they lived with a relative other than parent (compared with living with 
21 

both parents). The remaining countries were not statistically significant, while Armenia and Zambia were 

omitted due to low number of observations in this category.

Table 2 Summary of meta-analysis of the outcomes for children under age 5 

Stunted Wasted Anemic

No careseeking sought 

for ARI

No birth 

registration or 

birth certificate

Child level variables

Child’s sex (female Ref.)

Male +++ +++ +++ NS -

Orphanhood status (both parents alive Ref.)

Mother alive, father dead + - NS NS +++

Father alive, mother dead ++ NS NS . +++

Both parents dead NS NS - . +++

Living arrangements (living with both parents Ref.)

Living with mother, not father +++ ++ ++ NS +++

Living with father, not mother ++ - NS . NS

Living with relative, no parent +++ --- --- . +++

Does not live with relatives NS NS NS . +++

Household risk factors

Number of educated women (none Ref.)

1 -- --- NS -- ---

2 -- --- NS NS ---

3+ -- - NS - ---

Crowding +++ +++ +++ + +++

Youth dependency +++ NS NS +++ NS

Community level variables

Percentage of educated women --- --- --- --- ---

Nighttime lights --- + NS -- NS

Travel time to major city +++ NS ++ NS +++

Note: NS - not significant. Green indicates result is in the expected direction, orange indicates a result in the opposite of the expected 

direction. + indicates an OR above 1 and - indicates an OR below 1. The number of signs indicates the level of significance. A red 

box indicates a high level of heterogeneity.

Almost all the significant pooled odds ratios for the nutrition outcomes by the remaining risk factors were 

in the expected direction, with the exception of the nighttime lights risk factor for the wasting outcome. 

Boys had significantly higher odds than girls of being stunted, wasted, or anemic. For wasting and anemia, 

the I2test was non-significant, indicating that the surveys were homogeneous for this result (see Appendix 

Figures 7 and 13), and for stunting the I2 tests results indicated a moderate level of heterogeneity (Appendix 

Figure 1). Having at least one educated woman in the household, compared with none, showed a significant 

pooled odds ratio for stunting and wasting, but this risk factor was not significant for being anemic. In 

addition, the percentage of women in a cluster who are educated showed a protective and highly significant 

effect against all three nutrition outcomes, although there was high heterogeneity for the stunting and 

anemia outcomes. Crowding was also highly significant and with a low to moderate level of heterogeneity, 

with a greater likelihood of being stunted, wasted, or having anemia for children in households with higher 

levels of crowding. Only the odds of being stunted were significantly higher for children in households with 

higher levels of the youth dependency ratio. The cluster-level variables of nighttime lights and travel time 

to major city were significant predictors of stunting and were in the expected direction. The higher the 

nighttime lights indicator, the lower the odds of stunting; and the greater the travel time to a major city, the 

higher the odds of stunting. However, as indicated with the red box in Table 2, these results had high 

heterogeneity. This indicates that the results for these variables are country-specific.
22 

Appendix Figure 6 shows that the odds ratios for the three community-level variables and stunting for all 

the surveys were either significant in the expected direction or not significant. The nighttime lights indicator 

was not in the expected direction for wasting but this was only true for Chad, Myanmar, and Nigeria, with 

the remaining countries showing no statistical significance (see Appendix Figure 12). The nighttime lights 

indicator was not a significant predictor of anemia, but with a moderate level of heterogeneity for this result. 

For five countries (Burkina Faso, Cambodia, the DRC, Moldova, and Mozambique), however, the result 

was significant and in the expected direction. Travel time to a major city was a significant predictor for 

anemia but not for wasting. For both these outcomes, there was moderate heterogeneity for the pooled 

odds ratios.

Care-seeking for ARI symptoms. Most of pooled odds ratios for the risk factors predicting no care-seeking 

for symptoms of ARI were non-significant. This outcome has fewer observations than the remaining 

outcomes for children under age 5 since it is restricted to children who had ARI symptoms in the last 2 

weeks before the survey. There was no significant difference between boys and girls for care-seeking for 

ARI, with the I2 test indicating that the surveys were homogenous for this result. As Appendix Figure 19 

shows, only Cambodia and Uganda had significant higher odds of no care-seeking for boys compared with 

girls. In addition, the variables for orphanhood status and living arrangement were either non-significant or 

were omitted from the regression due to low counts. The results showed several strong predictors of careseeking for ARI symptoms at the household and cluster levels, however, and all in the expected direction. 

Having an educated woman in the household, less crowding, and a lower youth dependency ratio were all 

protective against not seeking care for ARI symptoms. The I2 value for these risk factors was also not 

significant, indicating homogeneity between the surveys (see Appendix Figures 22-23). In addition, the 

higher the percentage of educated women in the cluster, and the higher the nighttime lights indicator, the 

less likelihood of no treatment sought for ARI symptoms. While the I2 test indicated that the surveys were 

homogenous for the pooled odds ratio for percentage of educated women in the cluster, the result was highly 

heterogeneous for the nighttime lights indicator (I2=90.5%, p-value<0.001) (see Appendix Figure 24).

Birth registration. All the results for not having a birth registration or birth certificate were in the expected 

direction. In addition, only a few categories were non-significant. Boys were less likely to not be registered 

at birth compared with girls; with an I2

test indicating homogeneity between the surveys. Being any type of 

orphan or not living with both parents also increased the odds of not having a birth registration or birth 

certificate. However, there was moderate to high heterogeneity for these two child-level risk factors (see 

Appendix Figures 26-27). Côte d’Ivoire exhibited an unexpected result—with lower odds of no birth 

registration for children who are any type of orphan compared with children who have living parents (see 

Appendix Figure 26), and for all categories of living arrangement except living with mother only (see 

Appendix Figure 27). This was also the case for double orphans in Haiti and for all categories of living 

arrangement except for living with mother only. Having an educated woman in the household was protective 

against not having a registered birth or a birth certificate, while high levels of crowding increased the odds 

of this outcome. Appendix Figure 29 shows that crowding was significant in several countries (although 

with high heterogeneity), but the youth dependency ratio was not significant. At the community level, 

having a higher percentage of educated women in the cluster was a protective factor against not being 

registered at birth. In addition, the longer the travel time to a major city the more likely the birth would not 

be registered or have a certificate. Appendix Figure 30 shows that most countries had a significant result 

for these two cluster variables, although both showed high heterogeneity with I2 values above 85%, also 
23 

highly significant. The pooled odds ratio for nighttime lights was not significant, and the results show mixed 

findings between the surveys and high heterogeneity according to the I2

test (Appendix Figure 30).

3.5.2 Children age 5-14

Table 3 summarizes the results for the pooled regression results of not attending school in the current school 

year. This was the only outcome available for children age 5-14. As expected, the pooled odds ratio showed 

that boys were less likely than girls to not attend school. However, as Appendix Figure 31 shows, there was 

very high heterogeneity (I2=95.5%, p-value<0.001), indicating that this is a country-specific finding, with 

mixed results among the surveys. Children who were double orphans or whose mother had died but father 

was alive were significantly more likely not to attend school compared with children with both parents 

living, according to the pooled odds ratio. As Appendix Figure 32 shows, these results had moderate 

heterogeneity, and significant odds ratios were found in some surveys, especially for double orphans, while 

in most countries the results were not significant. All the categories of living arrangement except for living 

with father only, significantly increased the odds of not attending school compared with the category of 

living with both parents, but with high heterogeneity. For living with a non-relative, it was almost twice the 

odds compared to living with both parents based on the meta-analysis, with increased odds found in most 

countries (Appendix Figure 33).

The household-level variables were also in the expected direction except for youth dependency, which was 

not significant. Appendix Figure 34 shows that most countries for all the categories of number of educated 

women in the household (one, two, and three or more educated women) were significant and in the expected 

direction, but the level of heterogeneity was very high, with I2 values for all the categories significant and 

above 90%. This high heterogeneity is most likely due to the finding for Armenia, which had very high 

odds ratios due to the low counts of children not attending school. As Appendix Figure 35 shows, crowding 

was significant in all countries except Senegal. The cluster-level variables were also in the expected 

direction except for nighttime lights, which was highly significant in the opposite direction—that is, the 

higher the value for nighttime lights, the less likely children were to attend school. In some countries, 

however—Burundi, Guinea, Rwanda, Tanzania, and Zambia—the result for nighttime lights was in the 

expected direction (Appendix Figure 36). The figure also shows that in all but two of the countries the 

percentage of educated women in the cluster was a significant protective factor against not attending school. 

All the community-level variables had high heterogeneity, with I2 values all above 90% and significant.
24 

Table 3 Summary of meta-analysis of no schooling for children age 5-14

Did not attend 

school

Child level variables

Child’s sex (female Ref.)

Male ---

Orphanhood status (both parents alive Ref.)

Mother alive, father dead NS

Father alive, mother dead +

Both parents dead +++

Living arrangements (living with both parents Ref.)

Living with mother, not father +++

Living with father, not mother NS

Living with relative, no parent +++

Does not live with relatives +++

Household risk factors

Number of educated women (none Ref.)

1 ---

2 ---

3+ ---

Crowding +++

Youth dependency NS

Community level variables

Percentage of educated women ---

Nighttime lights +++

Travel time to major city +++

Note: NS - not significant. Green indicates result is in the expected direction, orange 

indicates a result in the opposite of the expected direction. + indicates an OR above 

1 and - indicates an OR below 1. The number of signs indicates the level of 

significance. A red box indicates a high level of heterogeneity.

3.5.3 Girls age 15-17

Table 4 summarizes the regression results from the meta-analysis of the four outcomes for girls age 15-17. 

There were several significant findings for the outcomes of adolescent fertility and sex before age 15, all 

of which were in the expected direction. However, there were only a few significant findings for the 

underweight outcome, and no significant findings for anemia. For the outcome related to sex before age 15, 

Armenia had no observations and is therefore not represented in the tables and figures.

Adolescent fertility and sex before age 15. For adolescent fertility, all the significant pooled odds ratios 

were in the expected direction, as Table 4 shows, with only a few non-significant categories. Girls with 

only the mother alive, or girls who were double orphans, had significantly higher odds of being pregnant 

or having a child compared with girls with both parents alive. The I2 test for only mother alive was also not 

significant, indicating homogeneity, and the I2

test for the double orphan category was significant but with 

low heterogeneity, as Appendix Figure 37 shows. The figure also shows that in many countries these two 

orphan types were not significant predictors of adolescent fertility. In several countries, however, there was 

a large effect. For instance, in Guinea and Haiti girls with only mother alive had more than twice the odds 

of being pregnant or having a child compared with girls with both parents alive. For double orphans, the 

odds of adolescent fertility were even higher for some countries—for example over six times as high in 

Cambodia, five times in Guinea, and three times in Mali and Chad—compared with girls with both parents 

alive. Living with mother only, living with a relative other than parent, and living with no relative all had 

significantly higher odds of adolescent fertility compared with living with both parents. The pooled odds 

ratio was almost six (95% C.I. 5.3-6.5) for girls living with a relative other than parent compared with living 
25 

with both parents. This is expected, as these girls are more likely living with the father of the child than 

with their parents (see Appendix Table 10). However, the I2 value was very high for this category, at 87.5%, 

with a highly significant p-value, indicating high heterogeneity mainly due to a few non-significant findings 

for some surveys.

The findings for the household-level and cluster-level variables were all significant and in the expected 

direction, except that travel time to a major city was not significant. The heterogeneity for these results was 

low to moderate except for the number of educated women in the household and the nighttime lights 

indicator, both of which had high levels of heterogeneity.

Sex before age 15. All the significant pooled odds ratios for sex before age 15 were in the expected 

direction. Girls age 15-17 who were double orphans or whose mother had died but father was alive had 

significantly higher odds of having sex before age 15 compared with girls with both parents alive. Appendix 

Figure 42 shows that these two orphanhood categories also had low heterogeneity. The effect of the living 

arrangement variable was relatively stronger. For girls living with mother only, girls living with a relative 

other than parent, or girls living with no relatives, the odds of having sex before age 15 were significantly 

higher compared with girls living with both parents. As Appendix Figure 43 shows, this effect was strongest 

for girls living with a relative other than parent, where most countries had a significant increased odds of 

this outcome compared with the reference group, and the pooled odds ratio was above three (see Appendix 

Table 10). However, this result had high heterogeneity according to the I2 test. For living with a non-relative, 

the pooled odds ratio was approximately two compared with girls living with both parents, with moderate 

heterogeneity.

The number of educated women in a household and the crowding index were also highly significant 

predictors of having sex before age 15. Many countries had significantly lower odds of this outcome if there 

was at least one educated woman in the household (Appendix Figure 44). There was also low to moderate 

heterogeneity. For children in a household with three or more educated women, the I2

test failed to reject 

the null hypothesis that the surveys were homogeneous. Also, Appendix Figure 45 shows a higher 

likelihood of having sex before age 15 with higher crowding levels, with the I2 test indicating homogeneity 

between the surveys for this result. The pooled odds ratio of the percentage of educated women in a cluster 

was also highly significant, with a higher percentage indicating lower odds of the outcome. As Appendix 

Figure 46 shows, the relationship between having early sex and the number of educated women in the 

household was significant in several countries, and exhibited moderate heterogeneity, with a significant I2

test. The remaining two cluster-level variables, nighttime lights and travel time to a major city, were also 

significant in the expected direction, but significance occurred in fewer countries and heterogeneity 

was high.

Nutrition outcomes. For girls age 15-17, only the crowding index and the percentage of educated women 

in a cluster significantly predicted the underweight outcome in the expected direction. For the crowding 

index, Appendix Figure 50 shows that the I2

test was not significant, indicating homogeneity between the 

surveys. The I2 test was significant for the percentage of educated women in a cluster, but the I2 value 

indicated moderate heterogeneity (Appendix Figure 51). Living without a parent and living in a household 

headed by a relative or a non-relative, compared with living with both parents, gave a significant pooled 

odds ratio in the opposite of the expected direction. That is, girls age 15-17 in these two living arrangements 

had lower odds of being underweight than girls living with both parents. Appendix Figure 48 shows a non-
26 

significant I2

test, indicating homogeneity for these results. None of the remaining subgroups were 

significant for the underweight outcome.

None of the risk factors showed a significant pooled odds ratio for anemia for girls age 15-17. This is also 

apparent in Appendix Figures 52-56, where the odds ratios for all the subgroups were non-significant in 

almost all the countries. The I2

test results for all the risk factors indicated either a significant but low 

heterogeneity or a non-significant test, indicating homogeneity between the surveys.

Table 4 Summary of meta-analysis of the outcomes for girls age 15-17

Adolescent 

fertility

Had sex 

before age 15 Underweight Anemic

Child level variables

Orphanhood status (both parents alive Ref.)

Mother alive, father dead +++ NS NS NS

Father alive, mother dead NS + NS NS

Both parents dead ++ + NS NS

Living arrangements (living with both parents Ref.)

Living with mother, not father +++ +++ NS NS

Living with father, not mother NS NS NS NS

Living with relative, no parent +++ +++ --- NS

Does not live with relatives +++ +++ --- NS

Household risk factors

Number of educated women (none Ref.)

1 --- --- NS NS

2 --- --- NS NS

3+ --- --- NS NS

Crowding +++ +++ +++ NS

Youth dependency +++ NS NS NS

Community level variables

Percentage of educated women --- --- --- NS

Nighttime lights -- - NS NS

Travel time to major city NS +++ NS NS

Note: NS - not significant. Green indicates result is in the expected direction, orange indicates a result in the opposite of the 

expected direction. + indicates an OR above 1 and - indicates an OR below 1. The number of signs indicates the level of 

significance. A red box indicates a high level of heterogeneity.
27 

4 DISCUSSION 

This report focused on 10 outcomes in four domains of well-being for children age 0-17—nutrition, health 

care, schooling, and child protection. The 10 specific outcomes refer variously to ages 0-4, 5-14, and 15-17. 

No indicator refers to more than one of the age intervals, let alone to all three. The analysis has taken a 

comprehensive approach to identify risk factors that cut across all outcomes, domains, and age groups, in 

an attempt to identify a general set of risk factors that tend to be associated with a general set of child 

outcomes in many countries. The strategy to accomplish this is very different from what would be used if, 

say, the goal was to identify the risk factors for school attendance by children age 5-14 in a single country. 

We have been cautious about concluding that a relationship between risks and outcomes is generalizable, 

or homogeneous across countries, or instead is heterogeneous—that is, found in some countries but 

not others.

The risk factors that this report has considered are themselves in different domains—apart from the 

requirement that they must be included in DHS surveys or in spatial data that can be attached to DHS 

surveys. The three hierarchically structured domains or levels are the child, the household, and the sample 

cluster, which can be loosely described as the community in which the household is located. The main 

interest is in risks for individual children that arise from conditions in the household or from the community 

around it.

The household in which the child lives can potentially be described in many different ways that are relevant 

to these outcomes, and we have been selective in the choice of household-level variables. We have not 

included, for example, variables such as source of water, type of sanitary facilities, building materials, 

access to electricity, or access to the media, which other studies (Kanamori and Pullum 2013) have shown 

to be associated with child well-being. Rather, the household-level variables constructed for this analysis 

focus on the context of the child within the household, describing the position of the child relative to the 

adults who are potentially the primary caregivers. If the child is a single or double orphan, it is hypothesized 

that the child has greater risk of negative outcomes than if both parents are alive. If the child is not living 

with a parent, it is hypothesized that the child has greater risk of negative outcomes than if the child is living 

with both parents. Similarly, if the child is not living with a parent and is not even related to the household 

head, then risk is further increased.

The focus is on adult caregivers to whom the child is biologically related. Whether or not they are orphans, 

most children who are not living with a parent are living with a relative as the household head, mostly a 

grandparent or an aunt or uncle. In an effort not detailed in this report, we attempted to infer whether the 

context for some of those children might be altered by the presence of some other relative who is in the 

household but is not the household head. It is possible that the child’s parents are not in the household, and 

the child is not related to the household head, but the child’s grandmother, or an adult sibling, for example, 

may be in the household. Unfortunately, such living arrangements cannot be identified definitively with the 

data currently included in DHS surveys. The surveys include the relationship of every person in the 

household to the household head, but not to one another. But even if such relationships do exist, they would 

involve few children—too few for statistically significant inferences.
28 

In addition to variables that describe the presence or absence of primary caregivers in the household, the 

report has included three other indicators of the child’s social context at the household level. An index of 

crowding or density is calculated as the ratio of household members to sleeping rooms, and a measure of 

dependency is the ratio of children to adults. A high level of crowding indicates relatively low allocation of 

household resources per person, and a high dependency ratio indicates a relatively low share of resources 

per child, in particular. The third household-level indicator selected for its potential relevance to child wellbeing is the presence of educated adults, particularly women, in the household. This dimension of the 

household context was found by Akwara et al. (2010) to be an important risk factor in many countries, and 

was included as a risk factor in an earlier DHS report (Pullum 2015). Women’s education is well 

documented as an important aspect of development and welfare in general. The presence of educated 

women is also assessed at the cluster level as well as the household level, and is found to be important at 

both levels.

The other two cluster-level risk factors are distance from a city of 50,000 or more inhabitants and nighttime 

lights. These variables are peripheral to the central question of the relationship between child outcomes and 

the position of the child within the household support structure. In a broad interpretation, these are two 

continuous indicators of access to resources (such as schools and health facilities) and level of development. 

They are included as coarse controls, or proxies, for a large number of household-level and cluster-level 

indicators of social and economic infrastructure, including the wealth index, many of which have been 

included in other research but are omitted here.

The meta-analysis revealed that most results were in the expected direction, but it is important to examine 

the results from the heterogeneity tests. The level of heterogeneity indicates whether the result can be 

generalized across countries or instead is a country-specific finding (when a high level of heterogeneity is 

found). Across all the outcomes, except for anemia in girls, the strongest effects were for the percentage of 

educated women in a cluster and the crowding index, but as Figure 12 shows, there was high heterogeneity 

for the percentage of educated women in a cluster. The figure shows that for seven out of the 10 outcomes, 

the level of heterogeneity was significant and above 70%. The level of heterogeneity was relatively low 

only for the no treatment sought for ARI symptoms outcome. In contrast, Figure 13 shows lower levels of 

heterogeneity for most of the outcomes with the crowding index. There was low heterogeneity detected for 

the association between crowding and anemia in children, wasting, and adolescent fertility, and no 

significant heterogeneity for crowding and anemia in girls, underweight girls, no treatment sought for ARI, 

and sex before age 15. This indicates that the association between crowding and these outcomes can be 

generalized across the countries in the analysis.
29 

Figure 12 I2 values and test of heterogeneity for the pooled odds ratio of proportion of educated women 

in a cluster 

Figure 13 I2 values and test of heterogeneity for the pooled odds ratio of crowding 

*

***

*** ***

***

***

*** ***

***

0

10

20

30

40

50

60

70

80

90

100

No treatment

ARI

Anemia girls Underweight Adolescent

fertility

Sex before

age 15

Wasting Anemia

children

Stunting No birth

registration

No school

Note: Green indicates pooled OR was in expected direction and grey indicates not significant. The stars refer to the significance of the I2 value.

*

** **

***

*** ***

0

10

20

30

40

50

60

70

80

90

100

Anemia girls Underweight No treatment

ARI

Sex before

age 15

Anemia

children

Wasting Adolescent

fertility

Stunting No birth

registration

No school

Note: Green indicates pooled OR was in expected direction and grey indicates not significant. The stars refer to the significance of the I2 value.
30 

The effect of household structure—represented by the living arrangements variable—appeared to be 

stronger for the child protection and schooling outcomes. For these outcomes, the magnitude of the pooled 

odds ratio, as well as the significance level, were high and especially for the categories of living with a 

relative who is not a parent and living with no relative. However, as Figure 14 shows, there were high levels 

of heterogeneity for the association between these outcomes and children living with a household head who 

is a relative but not a parent, compared with children living with both parents. The heterogeneity levels 

were above 80% for the outcomes of children not in school, adolescent fertility, sex before age 15, and no 

birth registration, indicating that these findings cannot be generalized. The nutrition outcomes had lower 

levels of heterogeneity but the pooled odds ratios were in the expected direction only for the stunting 

outcome. Figure 15 shows the level of heterogeneity for all the outcomes for children living in a household 

where they are not related to the household head compared with children living with both parents. The 

outcomes of no birth registration and no schooling had high heterogeneity levels. The remaining outcomes 

had low to moderate heterogeneity, but only the outcomes of sex before age 15 and adolescent fertility had 

pooled odds ratios in the expected direction. These findings imply that the expected protective aspect of 

having a parent in the household is not universal by countries or by child well-being outcomes. It appears 

that for child well-being, the number of people in the household is more important than the relationships in 

the household. This is likely due to competition for limited resources in overcrowded households.

Figure 14 I2 values and test of heterogeneity for the pooled odds ratio of children living with relative 

compared with children living with both parents 

***

***

*** ***

0

10

20

30

40

50

60

70

80

90

100

Anemia girls Underweight Anemia

children

Wasting Stunting No school Adolescent

fertility

Sex before age

15

No birth

registration

Note: Green indicates pooled OR was in expected direction, orange indicates it was in the opposite of the expected direction, and grey indicates 

not significant. The stars above the bars refer to the significance of the I2 value.
31 

Figure 15 I2 values and test of heterogeneity for the pooled odds ratio of children not living with relative 

compared with children living with both parents 

One of the limitations with DHS data is finding appropriate outcomes. Some outcomes develop over a long 

period of time. For instance, the risk of stunting can begin from pregnancy. By contrast, the risk factors 

used in the analysis look at the current status of children in their living conditions. It is not possible to find 

outcomes that extend across all the age groups. The DHS Program does not collect a great deal of 

information for children age 5-14 or boys age 15-17. Small sample sizes for outcomes such as care-seeking 

for ARI symptoms and the outcomes for girls age 15-17 gave less power to detect significance in the 

predictors. Some subgroups of children, such as double orphans, especially under age 5, or children living 

separately from parents with a household head who is not a relative, are very small. Despite these 

limitations, the power obtained from pooling the surveys for a meta-analysis provided a view of the 

important factors that have an effect on the outcomes analyzed and relationships where more in-depth 

country-specific research is required.

**

***

***

***

***

0

10

20

30

40

50

60

70

80

90

100

Anemia girls Underweight Anemia

children

Stunting Sex before age

15

Adolescent

fertility

Wasting No birth

registration

No school

Note: Green indicates pooled OR was in expected direction, orange indicates it was in the opposite of the expected direction, and grey indicates 

not significant. The stars above the bars refer to the significance of the I2 value.

33 

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37 

APPENDICES 

Appendix Table 1 Percentage of orphanhood type among households with children under age 18

Year

Orphan Type

Country Both parents alive

Mother alive, 

father dead

Father alive, 

mother dead Both parents dead

Armenia 2010 96.9 [96.1,97.6] 2.5 [1.9,3.2] (0.6 [0.3,1.1]) ND

Benin 2011-12 93.9 [93.5,94.3] 4.1 [3.8,4.5] 1.6 [1.4,1.8] 0.4 [0.4,0.5]

Burkina Faso 2010 94.4 [94.0,94.8] 3.6 [3.3,4.0] 1.4 [1.3,1.6] 0.5 [0.5,0.6]

Burundi 2010 86.6 [85.7,87.5] 8.4 [7.7,9.2] 2.9 [2.6,3.4] 2.0 [1.7,2.3]

Cambodia 2014 94.1 [93.5,94.7] 4.0 [3.6,4.5] 1.1 [1.0,1.4] 0.8 [0.6,1.0]

Chad 2015 92.5 [91.9,93.0] 5.3 [4.8,5.8] 1.5 [1.4,1.8] 0.7 [0.6,0.9]

Colombia 2010 94.5 [94.2,94.8] 4.4 [4.2,4.7] 0.9 [0.8,1.0] 0.2 [0.1,0.2]

Congo Democratic Republic 2013-14 91.1 [90.4,91.7] 5.1 [4.7,5.6] 2.6 [2.3,2.9] 1.2 [1.0,1.4]

Côte d’Ivoire 2011-12 91.3 [90.7,91.8] 5.3 [4.8,5.9] 2.4 [2.1,2.7] 1.0 [0.9,1.3]

Ethiopia 2011 90.6 [89.8,91.4] 6.4 [5.8,7.1] 2.1 [1.9,2.4] 0.8 [0.7,1.0]

Ghana 2014 92.5 [91.8,93.1] 5.0 [4.5,5.6] 1.7 [1.4,2.0] 0.8 [0.7,1.0]

Guinea 2012 90.7 [89.9,91.4] 5.7 [5.1,6.3] 2.6 [2.3,3.0] 1.0 [0.8,1.2]

Haiti 2012 87.8 [87.1,88.4] 7.6 [7.0,8.2] 3.3 [3.0,3.7] 1.3 [1.1,1.5]

Kenya 2014 90.0 [89.6,90.5] 6.9 [6.5,7.3] 1.8 [1.6,2.0] 1.2 [1.1,1.4]

Liberia 2013 92.7 [92.1,93.3] 5.3 [4.8,5.8] 1.5 [1.3,1.8] 0.5 [0.4,0.7]

Madagascar 2008-09 92.7 [92.1,93.1] 4.4 [4.1,4.8] 2.4 [2.1,2.7] 0.6 [0.5,0.7]

Malawi 2015-16 88.4 [88.0,88.9] 7.2 [6.8,7.6] 2.4 [2.2,2.6] 2.0 [1.8,2.2]

Mali 2012 95.5 [95.1,96.0] 2.5 [2.2,2.9] 1.5 [1.3,1.8] 0.4 [0.3,0.5]

Moldova 2005 95.5 [94.7,96.1] 3.5 [2.9,4.1] 0.8 [0.6,1.2] ND

Mozambique 2011 87.0 [86.4,87.7] 8.0 [7.5,8.6] 3.2 [2.9,3.6] 1.7 [1.5,1.9]

Myanmar 2015-16 92.3 [91.5,93.0] 5.6 [5.0,6.4] 1.5 [1.3,1.8] 0.5 [0.4,0.7]

Nepal 2011 95.1 [94.6,95.6] 3.2 [2.8,3.6] 1.5 [1.2,1.8] 0.2 [0.2,0.3]

Nigeria 2013 94.3 [94.0,94.7] 3.8 [3.5,4.1] 1.4 [1.3,1.6] 0.4 [0.3,0.5]

Rwanda 2014-15 90.7 [90.2,91.2] 6.7 [6.3,7.2] 1.6 [1.4,1.8] 1.0 [0.9,1.1]

Senegal 2015 93.8 [93.3,94.3] 4.5 [4.0,5.0] 1.4 [1.2,1.7] 0.3 [0.2,0.4]

Sierra Leone 2013 89.6 [88.9,90.2] 6.4 [6.0,7.0] 2.2 [2.0,2.5] 1.8 [1.5,2.1]

Tanzania 2015-16 91.6 [91.0,92.1] 5.5 [5.1,6.1] 2.1 [1.8,2.3] 0.8 [0.7,0.9]

Togo 2013-14 91.2 [90.6,91.8] 5.9 [5.4,6.5] 2.2 [1.9,2.4] 0.7 [0.6,0.9]

Uganda 2011 88.4 [87.3,89.5] 7.3 [6.5,8.2] 2.4 [2.0,2.8] 1.9 [1.6,2.2]

Zambia 2013-14 88.6 [88.1,89.1] 7.2 [6.8,7.7] 2.1 [1.9,2.3] 2.1 [1.9,2.3]

Notes: ND values not displayed because they were based on less than 25 unweighted cases. Values in parenthesis are based on 

25-49 unweighted cases.
38 

Appendix Table 2 Percentage of household living arrangements among households with children under 

age 18

Year

Living arrangements

Country

Living with 

both parents

Living with 

mother only

Living with 

father only

Living with 

relative, 

no parent

Does not live 

with relatives

Armenia 2010 82.4 [80.2,84.3] 15.2 [13.4,17.2] 1.0 [0.7,1.5] 1.2 [0.9,1.7] ND

Benin 2011-12 64.7 [63.7,65.7] 13.3 [12.6,14.0] 7.4 [7.0,7.8] 12.9 [12.3,13.5] 1.7 [1.5,1.9]

Burkina Faso 2010 77.7 [76.7,78.6] 8.3 [7.7,8.9] 4.5 [4.2,4.9] 7.9 [7.5,8.4] 1.5 [1.4,1.7]

Burundi 2010 68.4 [67.0,69.8] 18.5 [17.3,19.8] 3.1 [2.8,3.5] 8.2 [7.6,8.8] 1.8 [1.6,2.1]

Cambodia 2014 77.5 [76.5,78.4] 9.1 [8.5,9.6] 1.8 [1.5,2.0] 11.0 [10.4,11.7] 0.7 [0.6,0.9]

Chad 2015 69.1 [67.9,70.2] 14.6 [13.8,15.6] 4.9 [4.5,5.3] 8.0 [7.6,8.5] 3.4 [3.1,3.7]

Colombia 2010 52.6 [51.9,53.3] 32.7 [32.0,33.4] 3.5 [3.3,3.7] 9.4 [9.1,9.8] 1.8 [1.6,1.9]

Congo Democratic Republic 2013-14 59.3 [58.0,60.7] 20.4 [19.4,21.4] 6.1 [5.6,6.6] 10.2 [9.6,10.8] 4.0 [3.7,4.3]

Côte d’Ivoire 2011-12 53.1 [51.3,54.8] 16.7 [15.6,17.8] 8.5 [7.8,9.3] 17.7 [16.8,18.7] 4.0 [3.6,4.5]

Ethiopia 2011 71.0 [69.7,72.4] 14.5 [13.5,15.5] 3.0 [2.7,3.4] 7.8 [7.2,8.4] 3.7 [3.3,4.1]

Ghana 2014 54.7 [52.9,56.6] 25.0 [23.5,26.6] 4.7 [4.2,5.2] 14.2 [13.2,15.2] 1.4 [1.2,1.7]

Guinea 2012 61.3 [59.6,63.0] 13.2 [12.1,14.3] 7.0 [6.5,7.6] 15.4 [14.5,16.4] 3.0 [2.7,3.5]

Haiti 2012 44.1 [42.6,45.6] 29.1 [27.8,30.5] 6.0 [5.4,6.6] 13.7 [13.0,14.5] 7.1 [6.5,7.7]

Kenya 2014 54.7 [53.8,55.6] 27.5 [26.7,28.2] 3.3 [3.0,3.5] 13.6 [13.1,14.0] 1.0 [0.9,1.1]

Liberia 2013 43.5 [42.0,45.0] 23.5 [22.4,24.5] 7.8 [7.1,8.6] 23.0 [21.9,24.1] 2.2 [1.8,2.7]

Madagascar 2008-09 65.5 [64.4,66.5] 15.1 [14.4,15.8] 4.6 [4.3,5.0] 11.1 [10.5,11.8] 3.7 [3.4,4.0]

Malawi 2015-16 52.9 [52.0,53.9] 24.3 [23.5,25.0] 2.8 [2.6,3.0] 19.1 [18.5,19.7] 0.9 [0.8,1.0]

Mali 2012 80.3 [79.0,81.5] 6.5 [5.8,7.2] 3.1 [2.7,3.5] 7.8 [7.3,8.4] 2.4 [2.1,2.7]

Moldova 2005 63.8 [62.0,65.6] 19.1 [17.9,20.4] 5.3 [4.6,6.2] 9.8 [8.9,10.8] 1.9 [1.5,2.4]

Mozambique 2011 52.0 [50.5,53.4] 25.8 [24.7,26.9] 4.1 [3.7,4.6] 17.0 [16.2,17.8] 1.1 [1.0,1.3]

Myanmar 2015-16 74.1 [72.7,75.4] 13.2 [12.2,14.3] 2.2 [1.9,2.6] 9.7 [8.9,10.5] 0.8 [0.6,1.0]

Nepal 2011 60.1 [58.1,62.1] 29.5 [27.6,31.4] 2.3 [1.9,2.8] 7.4 [6.7,8.2] 0.7 [0.5,0.9]

Nigeria 2013 73.5 [72.6,74.3] 10.8 [10.2,11.4] 5.4 [5.1,5.7] 7.4 [7.1,7.8] 2.9 [2.7,3.1]

Rwanda 2014-15 62.6 [61.5,63.7] 21.8 [20.9,22.7] 2.2 [2.0,2.5] 10.3 [9.8,10.9] 3.0 [2.7,3.3]

Senegal 2015 53.0 [51.0,54.9] 28.9 [27.1,30.7] 3.1 [2.7,3.6] 13.6 [12.9,14.5] 1.4 [1.2,1.7]

Sierra Leone 2013 50.3 [49.0,51.6] 17.4 [16.6,18.2] 7.9 [7.4,8.4] 21.7 [20.9,22.6] 2.7 [2.4,3.0]

Tanzania 2015-16 57.5 [56.2,58.8] 18.6 [17.7,19.6] 5.1 [4.7,5.6] 15.3 [14.6,16.1] 3.4 [3.1,3.7]

Togo 2013-14 60.5 [58.5,62.4] 17.8 [16.6,19.0] 5.6 [5.0,6.1] 14.2 [13.3,15.2] 2.0 [1.7,2.3]

Uganda 2011 55.6 [53.8,57.4] 19.9 [18.6,21.3] 5.3 [4.8,5.8] 14.1 [13.3,15.0] 5.1 [4.7,5.5]

Zambia 2013-14 59.6 [58.6,60.7] 19.2 [18.4,20.0] 3.7 [3.4,4.0] 12.1 [11.5,12.7] 5.5 [5.1,5.8]

Note: ND values not displayed because they were based on less than 25 unweighted cases. 
39 

Appendix Table 3 Household risk factors

Country Year

Mean 

crowding

Mean 

dependency 

ratio

Mean youth 

dependency

Mean number of 

educated adults

Mean number of 

educated 

women

Armenia 2010 2.13 [2.08,2.19] 0.82 [0.79,0.86] 0.68 [0.65,0.71] 3.17 [3.09,3.24] 1.79 [1.74,1.83]

Benin 2011-12 3.42 [3.36,3.48] 1.77 [1.74,1.81] 1.66 [1.64,1.69] 1.01 [0.97,1.05] 0.38 [0.36,0.4]

Burkina Faso 2010 2.67 [2.62,2.71] 1.61 [1.58,1.63] 1.53 [1.5,1.55] 0.64 [0.59,0.69] 0.28 [0.25,0.3]

Burundi 2010 2.51 [2.45,2.56] 1.54 [1.51,1.58] 1.49 [1.46,1.53] 1.24 [1.19,1.29] 0.59 [0.56,0.61]

Cambodia 2014 4.37 [4.27,4.46] 1.06 [1.04,1.09] 0.96 [0.94,0.98] 2.43 [2.37,2.48] 1.19 [1.16,1.22]

Chad 2015 3.34 [3.28,3.4] 1.98 [1.94,2.01] 1.9 [1.87,1.94] 1.12 [1.06,1.19] 0.45 [0.42,0.48]

Colombia 2010 2.3 [2.27,2.34] 0.99 [0.98,1.01] 0.91 [0.9,0.93] 2.56 [2.54,2.59] 1.42 [1.4,1.43]

Congo Democratic Republic 2013-14 3.16 [3.08,3.24] 1.79 [1.76,1.83] 1.73 [1.7,1.76] 2.29 [2.24,2.35] 1.13 [1.1,1.17]

Côte d’Ivoire 2011-12 3.05 [2.97,3.14] 1.49 [1.45,1.53] 1.39 [1.35,1.42] 1.57 [1.45,1.68] 0.68 [0.62,0.74]

Ethiopia 2011 4.7 [4.58,4.82] 1.56 [1.52,1.6] 1.48 [1.44,1.52] 1.06 [1.01,1.11] 0.4 [0.38,0.43]

Ghana 2014 3.28 [3.21,3.36] 1.51 [1.47,1.54] 1.4 [1.37,1.44] 1.65 [1.6,1.7] 0.87 [0.84,0.9]

Guinea 2012 2.64 [2.57,2.72] 1.61 [1.56,1.65] 1.48 [1.44,1.52] 1.19 [1.08,1.3] 0.45 [0.4,0.5]

Haiti 2012 3.52 [3.45,3.59] 1.27 [1.24,1.31] 1.16 [1.13,1.19] 2.09 [2.01,2.17] 1.1 [1.04,1.15]

Kenya 2014 3.5 [3.44,3.56] 1.59 [1.57,1.62] 1.51 [1.49,1.54] 2.02 [1.99,2.05] 1.09 [1.07,1.11]

Liberia 2013 3.08 [3.0,3.15] 1.51 [1.47,1.56] 1.4 [1.36,1.45] 1.93 [1.83,2.04] 0.85 [0.79,0.9]

Madagascar 2008-09 4.79 [4.71,4.87] 1.55 [1.52,1.58] 1.48 [1.45,1.51] 1.91 [1.86,1.95] 0.93 [0.91,0.96]

Malawi 2015-16 2.82 [2.78,2.87] 1.65 [1.62,1.67] 1.52 [1.5,1.55] 1.9 [1.87,1.93] 0.98 [0.96,1.0]

Mali 2012 2.51 [2.46,2.57] 1.77 [1.74,1.81] 1.69 [1.66,1.73] 0.74 [0.67,0.8] 0.29 [0.26,0.32]

Moldova 2005 1.73 [1.68,1.78] 0.85 [0.82,0.88] 0.76 [0.73,0.78] 2.31 [2.28,2.35] 1.25 [1.23,1.27]

Mozambique 2011 2.87 [2.81,2.93] 1.72 [1.69,1.75] 1.63 [1.6,1.66] 1.6 [1.55,1.65] 0.77 [0.74,0.8]

Myanmar 2015-16 3.64 [3.54,3.74] 1.04 [1.01,1.07] 0.93 [0.9,0.96] 2.34 [2.26,2.42] 1.24 [1.2,1.29]

Nepal 2011 2.9 [2.77,3.02] 1.29 [1.24,1.34] 1.18 [1.13,1.24] 1.46 [1.38,1.55] 0.66 [0.61,0.71]

Nigeria 2013 2.9 [2.86,2.94] 1.62 [1.6,1.64] 1.54 [1.52,1.56] 1.61 [1.55,1.66] 0.75 [0.72,0.78]

Rwanda 2014-15 2.37 [2.34,2.4] 1.4 [1.37,1.42] 1.33 [1.3,1.35] 1.88 [1.85,1.91] 1.02 [1.0,1.04]

Senegal 2015 2.61 [2.55,2.66] 1.4 [1.36,1.44] 1.29 [1.25,1.33] 2.16 [1.98,2.33] 1.03 [0.94,1.12]

Sierra Leone 2013 2.76 [2.7,2.83] 1.5 [1.47,1.54] 1.37 [1.34,1.4] 1.25 [1.18,1.32] 0.55 [0.51,0.59]

Tanzania 2015-16 2.63 [2.59,2.68] 1.55 [1.51,1.58] 1.44 [1.41,1.47] 2.3 [2.25,2.36] 1.13 [1.1,1.16]

Togo 2013-14 2.92 [2.86,2.98] 1.62 [1.58,1.67] 1.52 [1.48,1.56] 1.69 [1.62,1.75] 0.77 [0.72,0.82]

Uganda 2011 3.57 [3.47,3.68] 1.86 [1.81,1.9] 1.76 [1.72,1.81] 2.01 [1.96,2.05] 1.02 [0.99,1.05]

Zambia 2013-14 3.27 [3.22,3.33] 1.64 [1.61,1.67] 1.56 [1.54,1.59] 2.38 [2.33,2.43] 1.23 [1.2,1.25]
40 

Appendix Table 4 Cluster-level variables

Country Year

Poorest 

households

Educated 

adults

Educated

women

Nighttime 

lights

Travel time to 

major city

Armenia 2010 21.92 [17.96,25.87] 75.47 [74.76,76.18] 42.47 [41.86,43.07] 5.98 [4.69,7.27] 71.35 [62.86,79.85]

Benin 2011-12 21.3 [19.65,22.94] 18.63 [17.93,19.32] 6.9 [6.56,7.23] 1.39 [1.27,1.52] 132.75 [126.77,138.74]

Burkina Faso 2010 21.06 [19.67,22.44] 9.94 [9.4,10.47] 4.03 [3.77,4.29] 1.22 [1.03,1.4] 221.97 [213.51,230.43]

Burundi 2010 20.24 [18.77,21.71] 23.08 [22.35,23.82] 10.49 [10.07,10.92] 0.13 [0.11,0.15] 158.49 [149.7,167.28]

Côte d’Ivoire 2011-12 21.02 [18.1,23.95] 23.54 [22.22,24.86] 9.26 [8.58,9.95] 4.47 [3.9,5.04] 148.99 [134.13,163.85]

Congo Democratic 

Republic 2013-14 20.34 [18.45,22.22] 36.65 [35.9,37.4] 17.31 [16.82,17.8] 1.97 [1.61,2.33] 240.54 [218.75,262.32]

Colombia 2010 24.08 [22.63,25.54] 58.14 [57.73,58.55] 30.97 [30.69,31.26] 22.95 [22.08,23.82] 100.44 [94.53,106.35]

Ethiopia 2011 20.95 [18.62,23.27] 20.55 [19.66,21.43] 7.89 [7.42,8.36] 0.43 [0.35,0.5] 395.02 [360.05,429.99]

Ghana 2014 22.49 [19.78,25.21] 39.36 [38.1,40.62] 19.32 [18.53,20.1] 3.48 [3.11,3.86] 123.32 [114.5,132.13]

Guinea 2012 20.81 [17.84,23.77] 15.31 [14.19,16.44] 5.59 [5.07,6.12] 1.23 [1.02,1.45] 163.85 [152.39,175.3]

Haiti 2012 22.48 [19.64,25.32] 40.18 [38.88,41.48] 19.27 [18.46,20.09] 2.07 [1.76,2.38] 116.22 [108.74,123.7]

Kenya 2014 23.24 [21.87,24.61] 42.31 [41.75,42.88] 20.87 [20.54,21.2] 1.96 [1.76,2.16] 202.32 [194.94,209.7]

Cambodia 2014 21.73 [19.42,24.03] 49.35 [48.54,50.16] 24.2 [23.66,24.73] 1.12 [0.89,1.36] 183.45 [172.64,194.26]

Liberia 2013 19.82 [17.33,22.3] 31.28 [30.18,32.38] 12.39 [11.83,12.95] 0.64 [0.45,0.83] 198.93 [185.74,212.12]

Moldova 2005 22.3 [19.93,24.68] 70.72 [69.96,71.47] 37.69 [37.17,38.22] 2.96 [2.7,3.22] 81.58 [77.27,85.89]

Madagascar 2008-09 21.11 [19.45,22.77] 36.12 [35.34,36.9] 17.42 [16.97,17.86] 0.45 [0.38,0.52] 199.8 [190.42,209.18]

Mali 2012 20.19 [18.01,22.36] 10.94 [10.17,11.7] 4.28 [3.94,4.62] 1.45 [1.3,1.61] 194.3 [181.64,206.95]

Malawi 2015-16 20.53 [19.54,21.52] 38.6 [38.1,39.09] 19.23 [18.92,19.54] 0.78 [0.69,0.87] 184.6 [177.06,192.14]

Myanmar 2015-16 22.67 [20.52,24.81] 49.66 [48.2,51.13] 26.59 [25.72,27.46] 1.45 [1.14,1.77] 169.96 [157.79,182.12]

Mozambique 2011 20.44 [18.47,22.41] 30.68 [29.84,31.52] 14.01 [13.49,14.53] 2.49 [2.23,2.75] 214.36 [197.61,231.11]

Nigeria 2013 22.09 [19.96,24.22] 28.86 [27.91,29.82] 12.77 [12.28,13.27] 1.62 [1.34,1.9] 136.92 [128.74,145.11]

Nepal 2011 22.36 [18.79,25.93] 29.66 [27.77,31.55] 13.08 [12.07,14.1] 0.37 [0.29,0.45] 202.46 [185.36,219.56]

Rwanda 2014-15 20.53 [19.44,21.62] 39.72 [39.18,40.25] 20.59 [20.24,20.94] 0.64 [0.53,0.74] 191.1 [182.92,199.29]

Sierra Leone 2013 20.21 [18.15,22.27] 18.49 [17.58,19.39] 7.74 [7.28,8.2] 0.39 [0.31,0.48] 142.4 [134.01,150.8]

Senegal 2015 22.35 [19.03,25.66] 19.13 [17.84,20.43] 8.92 [8.22,9.63] 3.1 [2.41,3.79] 118.1 [109.34,126.85]

Togo 2013-14 22.46 [20.33,24.59] 30.8 [29.35,32.25] 13.42 [12.63,14.2] 2.14 [1.86,2.41] 144.74 [135.92,153.56]

Chad 2015 20.37 [18.78,21.96] 15.32 [14.72,15.93] 5.87 [5.56,6.17] 0.74 [0.6,0.89] 280.67 [266.4,294.94]

Tanzania 2015-16 21.64 [19.38,23.9] 37.77 [36.96,38.58] 18.11 [17.62,18.59] 0.94 [0.81,1.06] 180.24 [168.48,192.01]

Uganda 2011 20.75 [18.54,22.97] 34.59 [33.83,35.34] 16.6 [16.15,17.05] 0.53 [0.36,0.7] 159.19 [149.88,168.5]

Zambia 2013-14 21.31 [19.92,22.7] 39.73 [39.24,40.22] 19.84 [19.51,20.16] 5.12 [4.55,5.69] 261.22 [245.73,276.71]
41 

Appendix Table 5 Childhood outcomes for children under age 5

Country Year Stunted Wasted Anemic

No Care-seeking 

sought for ARI

No birth 

registration or birth

certificate

Armenia 2010 19.3 [16.7,22.2] 4.0 [2.9,5.6] 43.2 [27.1,60.9] 0.4 [0.2,1.0]

Benin 2011-12 44.6 [43.2,46.1] 16.0 [14.9,17.2] 58.3 [56.2,60.5] 68.6 [60.3,76.0] 19.8 [18.3,21.4]

Burkina Faso 2010 34.6 [33.2,36.1] 15.5 [14.2,16.8] 87.8 [86.7,88.8] 44.5 [37.5,51.8] 23.1 [21.4,24.9]

Burundi 2010 57.7 [55.7,59.7] 5.8 [4.9,6.9] 44.5 [42.3,46.8] 45.4 [42.1,48.7] 24.8 [22.7,27.1]

Cambodia 2014 32.4 [30.6,34.3] 9.6 [8.6,10.8] 55.5 [53.4,57.6] 31.4 [25.2,38.3] 26.7 [24.7,28.8]

Chad 2015 39.9 [38.5,41.4] 13.0 [12.1,14.0] 74.4 [70.1,78.2] 88.0 [86.7,89.1]

Colombia 2010 13.2 [12.5,13.9] 0.9 [0.7,1.1] 35.5 [31.9,39.4]

Congo Democratic Republic 2013-14 42.7 [40.9,44.5] 7.9 [7.0,8.9] 59.8 [57.5,62.1] 58.0 [51.8,64.0] 75.4 [72.5,78.1]

Côte d’Ivoire 2011-12 29.8 [27.7,31.9] 7.5 [6.4,8.9] 74.8 [72.9,76.7] 63.0 [54.4,70.8] 13.0 [11.7,14.4]

Ethiopia 2011 44.5 [42.7,46.2] 9.7 [8.7,10.7] 44.2 [42.1,46.4] 72.9 [67.5,77.6]

Ghana 2014 18.8 [17.0,20.6] 4.7 [3.5,6.1] 65.7 [62.9,68.5] 47.3 [37.2,57.6] 29.5 [26.8,32.4]

Guinea 2012 31.2 [29.1,33.3] 9.6 [8.4,10.9] 76.6 [74.5,78.6] 62.1 [56.0,67.9] 42.1 [38.4,45.9]

Haiti 2012 21.9 [20.0,23.8] 5.1 [4.4,5.9] 65.0 [63.0,66.9] 61.6 [57.4,65.7] 20.2 [18.5,22.1]

Kenya 2014 26.1 [25.1,27.0] 4.1 [3.6,4.5] 34.5 [31.5,37.7] 33.1 [31.9,34.4]

Liberia 2013 31.7 [29.4,34.1] 6.0 [5.0,7.3] 47.7 [41.2,54.4] 75.4 [72.8,77.8]

Madagascar 2008-09 50.2 [48.0,52.3] 50.3 [48.4,52.3] 57.9 [51.2,64.4] 20.3 [18.7,22.0]

Malawi 2015-16 37.1 [35.6,38.7] 2.7 [2.3,3.3] 62.6 [60.7,64.5] 22.9 [19.1,27.3] 32.8 [31.5,34.1]

Mali 2012 38.3 [36.2,40.4] 12.6 [11.1,14.3] 81.6 [79.9,83.2] 73.3 [64.1,80.8] 15.7 [13.8,17.8]

Moldova 2005 10.2 [8.7,12.0] 5.0 [3.8,6.6] 32.1 [29.2,35.1] 40.3 [30.6,50.8] 7.7 [6.2,9.4]

Mozambique 2011 42.6 [41.0,44.2] 5.9 [5.3,6.6] 68.7 [66.6,70.7] 50.4 [41.4,59.4] 52.1 [50.1,54.2]

Myanmar 2015-16 29.2 [27.3,31.1] 7.0 [6.1,8.1] 57.8 [55.7,59.8] 42.0 [34.0,50.3] 18.7 [16.2,21.5]

Nepal 2011 40.5 [37.8,43.3] 10.9 [9.4,12.6] 46.2 [42.9,49.6] 50.8 [42.7,59.0] 57.7 [54.9,60.6]

Nigeria 2013 36.8 [35.7,38.0] 18.0 [17.1,18.9] 65.8 [61.0,70.4] 69.2 [67.5,70.9]

Rwanda 2014-15 37.9 [36.1,39.6] 2.2 [1.8,2.7] 36.5 [34.7,38.4] 46.5 [41.8,51.2] 44.0 [42.1,45.9]

Senegal 2015 20.5 [19.0,22.1] 7.8 [7.0,8.8] 66.3 [64.2,68.3] 52.2 [44.4,59.8] 31.7 [28.7,35.0]

Sierra Leone 2013 38.0 [36.0,40.0] 9.3 [8.2,10.6] 79.9 [78.4,81.4] 27.9 [22.1,34.5] 23.3 [20.8,26.0]

Tanzania 2015-16 34.4 [33.0,35.9] 4.5 [4.0,5.0] 57.7 [56.1,59.4] 44.0 [37.5,50.8] 73.6 [71.9,75.3]

Togo 2013-14 27.5 [25.7,29.4] 6.5 [5.7,7.5] 70.1 [68.0,72.1] 51.4 [43.5,59.2]

Uganda 2011 33.4 [30.9,35.9] 4.7 [3.8,5.9] 49.3 [46.0,52.6] 21.2 [17.8,24.9] 70.1 [67.6,72.5]

Zambia 2013-14 40.1 [38.9,41.3] 6.0 [5.5,6.6] 30.4 [25.3,36.1] 88.7 [87.4,89.9]
42 

Appendix Table 6 Percentage of children age 5-14 not attending school 

Country Year % [C.I.]

Armenia 2010 10.2 [8.9,11.6]

Benin 2011-12 29.0 [27.6,30.4]

Burkina Faso 2010 58.1 [56.6,59.5]

Burundi 2010 39.1 [37.9,40.4]

Côte d’Ivoire 2011-12 36.5 [34.5,38.6]

Congo Democratic Republic 2013-14 23.4 [22.2,24.6]

Colombia 2010 5.1 [4.8,5.4]

Ethiopia 2011 46.0 [43.7,48.3]

Ghana 2014 19.5 [16.3,23.1]

Guinea 2012 50.3 [47.5,53.2]

Haiti 2012 7.5 [6.5,8.7]

Kenya 2014 5.6 [5.1,6.1]

Cambodia 2014 15.7 [14.7,16.8]

Liberia 2013 22.0 [20.1,24.1]

Moldova 2005 6.3 [5.5,7.2]

Madagascar 2008-09 26.7 [25.4,28.0]

Mali 2012 54.0 [51.5,56.4]

Malawi 2015-16 8.7 [8.1,9.3]

Myanmar 2015-16 14.1 [12.5,15.8]

Mozambique 2011 32.9 [31.2,34.7]

Nigeria 2013 32.0 [29.9,34.2]

Nepal 2011 8.8 [6.8,11.4]

Rwanda 2014-15 16.6 [15.7,17.5]

Sierra Leone 2013 32.9 [31.0,34.8]

Senegal 2015 47.5 [44.3,50.8]

Togo 2013-14 14.3 [12.6,16.2]

Chad 2015 51.7 [49.8,53.7]

Tanzania 2015-16 27.8 [26.2,29.5]

Uganda 2011 14.0 [12.9,15.1]

Zambia 2013-14 28.8 [27.9,29.8]
43 

Appendix Table 7 Childhood outcomes for girls age 15-17

Country Year

Pregnant or have 

a child

Had sex before 

age 15 Underweight Anemic

Armenia 2010 0.4 [0.1,2.7]

Benin 2011-12 8.3 [7.0,10.0] 12.9 [11.3,14.6] 14.1 [12.2,16.2] 43.2 [38.5,48.0]

Burkina Faso 2010 8.6 [7.3,10.2] 7.4 [6.1,8.9] 28.1 [25.1,31.3] 45.5 [42.1,49.1]

Burundi 2010 2.2 [1.4,3.4] 3.4 [2.5,4.7] 28.6 [24.9,32.7] 15.8 [12.8,19.2]

Cambodia 2014 4.0 [3.0,5.2] 0.7 [0.4,1.3] 31.0 [27.6,34.6] 48.1 [44.8,51.4]

Chad 2015 21.4 [19.3,23.6] 14.8 [13.0,16.7] 28.9 [25.7,32.2]

Colombia 2010 11.2 [10.1,12.3] 13.5 [12.4,14.7] 15.8 [14.6,17.2]

Congo Democratic Republic 2013-14 15.4 [13.4,17.6] 19.2 [16.7,21.9] 24.6 [21.2,28.5] 39.4 [35.3,43.7]

Côte d’Ivoire 2011-12 15.1 [12.4,18.2] 20.2 [16.7,24.3] 19.2 [15.4,23.7] 51.3 [46.1,56.6]

Ethiopia 2011 4.4 [3.2,6.1] 5.0 [3.7,6.7] 42.0 [38.9,45.2] 12.2 [10.2,14.7]

Ghana 2014 6.6 [4.8,9.0] 13.5 [11.1,16.3] 17.4 [13.6,21.9] 53.6 [48.3,58.9]

Guinea 2012 21.0 [18.0,24.3] 20.8 [17.8,24.1] 22.9 [19.6,26.6] 44.0 [39.3,48.8]

Haiti 2012 6.5 [5.3,7.8] 13.5 [11.8,15.4] 27.7 [24.8,30.8] 55.3 [52.2,58.3]

Kenya 2014 8.2 [7.1,9.4] 10.5 [9.3,11.8] 21.3 [19.0,23.8]

Liberia 2013 16.3 [14.1,18.9] 24.6 [21.6,27.8] 19.3 [15.0,24.5]

Madagascar 2008-09 17.9 [16.0,20.1] 15.9 [14.1,18.0] 29.6 [26.7,32.8] 33.4 [30.0,37.1]

Malawi 2015-16 13.6 [12.1,15.2] 14.4 [12.9,16.1] 16.7 [13.8,20.0] 33.8 [30.3,37.4]

Mali 2012 23.4 [20.0,27.1] 18.0 [15.1,21.2] 20.4 [16.9,24.5] 47.8 [43.1,52.5]

Moldova 2005 2.1 [1.2,3.5] 1.0 [0.5,2.2] 18.4 [15.8,21.3] 25.8 [22.8,29.0]

Mozambique 2011 22.0 [19.6,24.5] 22.0 [19.8,24.3] 17.7 [15.2,20.4] 55.3 [52.3,58.3]

Myanmar 2015-16 1.5 [0.9,2.6] 0.6 [0.3,1.4] 29.2 [25.8,32.9] 48.7 [44.8,52.6]

Nepal 2011 5.5 [4.3,7.0] 3.2 [2.2,4.6] 28.0 [23.7,32.8] 38.4 [34.2,42.8]

Nigeria 2013 12.5 [11.0,14.1] 15.0 [13.4,16.8] 27.7 [26.0,29.5]

Rwanda 2014-15 2.2 [1.6,3.2] 7.6 [6.3,9.0] 14.4 [12.0,17.0] 18.6 [16.1,21.5]

Senegal 2015 8.0 [6.5,9.8] 5.2 [3.9,6.8]

Sierra Leone 2013 12.7 [11.1,14.4] 18.3 [16.2,20.6] 19.0 [15.7,22.9] 49.5 [45.5,53.5]

Tanzania 2015-16 12.4 [10.3,14.8] 13.3 [11.5,15.3] 22.1 [19.7,24.7] 46.1 [43.1,49.2]

Togo 2013-14 6.7 [5.1,8.7] 12.1 [10.0,14.5] 15.1 [12.2,18.5] 53.3 [48.7,57.8]

Uganda 2011 8.4 [6.8,10.5] 11.0 [9.1,13.4] 16.8 [13.0,21.5] 17.8 [13.7,22.7]

Zambia 2013-14 14.1 [12.5,16.0] 12.3 [10.6,14.2] 20.2 [18.1,22.5]
44 

Appendix Table 8 Pooled odds ratios and 95% confidence intervals from the meta-analysis of the outcomes for children 

under age 5

Stunted Wasted Anemic

No care-seeking 

sought for ARI

No birth registration 

or birth certificate

Child level variables

Child’s sex

Female (Ref.) 1 1 1 1 1

Male 1.23*** [1.2,1.26] 1.20*** [1.14,1.27] 1.08*** [1.05,1.12] .99 [.91,1.08] .96* [.92,.99]

Orphanhood status

Both parents alive (Ref.) 1 1 1 1 1

Mother alive, father dead 1.12* [1.03,1.23] .79* [.64,.98] .89 [.78,1] 1.07 [.76,1.5] 1.23*** [1.12,1.35]

Father alive, mother dead 1.29** [1.09,1.53] .97 [.72,1.3] .99 [.8,1.22] . 1.57*** [1.33,1.86]

Both parents dead .83 [.57,1.23] .96 [.53,1.74] .55* [.33,.91] . 2.35*** [1.6,3.45]

Living arrangements

Living with both parents (Ref.) 1 1 1 1 1

Living with mother, not father 1.07*** [1.04,1.11] 1.09** [1.02,1.17] 1.07** [1.02,1.12] 1.03 [.91,1.16] 1.27*** [1.22,1.33]

Living with father, not mother 1.17** [1.05,1.29] .76* [.6,.97] .87 [.76,1] . 1.08 [.98,1.19]

Living with relative, no parent 1.22*** [1.15,1.3] .68*** [.59,.79] .8*** [.74,.86] . 1.32*** [1.24,1.41]

Does not live with relatives 1.17 [.96,1.43] .80 [.57,1.12] .94 [.74,1.2] . 1.62*** [1.36,1.93]

Household risk factors

Number of educated women

None (Ref.) 1 1 1 1 1

1 .94** [.9,.98] .86*** [.79,.94] .96 [.92,1.01] .82** [.71,.94] .76*** [.73,.8]

2 .91** [.85,.96] .81*** [.72,.9] .93 [.86,1.01] .86 [.69,1.08] .78*** [.72,.84]

3+ .86** [.79,.94] .83* [.7,.97] .94 [.82,1.07] .71* [.52,.97] .81*** [.72,.91]

Crowding 1.05*** [1.04,1.06] 1.03*** [1.02,1.05] 1.02*** [1.01,1.04] 1.03* [1.01,1.06] 1.06*** [1.05,1.08]

Youth dependency 1.06*** [1.04,1.08] .98 [.95,1.01] .99 [.97,1.01] 1.12*** [1.06,1.19] 1 [.98,1.02]

Community level variables

Percentage of educated women .97*** [.96,.97] .98*** [.97,.98] .97*** [.97,.98] .98*** [.97,.99] .94*** [.93,.95]

Nighttime lights .97*** [.96,.98] 1.01* [1,1.03] 1 [.99,1.01] .95** [.91,.98] .99 [.98,1]

Travel time to major city 1*** [1,1] 1 [1,1] 1** [1,1] 1 [1,1] 1*** [1,1]

Note: * p<0.05, ** p<0.01, *** p<0.001
45 

Appendix Table 9 Pooled odds ratios and 95% confidence intervals from the meta-analysis of no 

schooling for children age 5-14

No schooling

Child level variables

Child’s sex

Female (Ref.) 1

Male .96*** [.93,.98]

Orphanhood status

Both parents alive (Ref.) 1

Mother alive, father dead 1.02 [.98,1.07]

Father alive, mother dead 1.07* [1,1.15]

Both parents dead 1.38*** [1.22,1.55]

Living arrangements

Living with both parents (Ref.) 1

Living with mother, not father 1.12*** [1.09,1.16]

Living with father, not mother .96 [.92,1.01]

Living with relative, no parent 1.19*** [1.15,1.23]

Does not live with relatives 1.93*** [1.8,2.08]

Household risk factors

Number of educated women

None (Ref.) 1

1 .68*** [.66,.7]

2 .63*** [.6,.67]

3+ .64*** [.59,.7]

Crowding 1.09*** [1.08,1.1]

Youth dependency 1.00 [.99,1.02]

Community level variables

Percentage of educated women .90*** [.9,.91]

Nighttime lights 1.02*** [1.01,1.03]

Travel time to major city 1*** [1,1]

Note: * p<0.05, ** p<0.01, *** p<0.001 
46 

Appendix Table 10 Pooled odds ratios and 95% confidence intervals from the meta-analysis of the outcomes 

for girls age 15-17

Pregnant or have 

a child

Had sex before 

age 15 Underweight Anemic

Child level variables

Orphanhood status

Both parents alive (Ref.) 1 1 1 1

Mother alive, father dead 1.34*** [1.18,1.52] 1.13 [.98,1.3] .96 [.87,1.06] 1.01 [.89,1.14]

Father alive, mother dead 1.02 [.83,1.26] 1.25* [1.03,1.52] .94 [.78,1.14] .88 [.71,1.08]

Both parents dead 1.50** [1.12,2] 1.36* [1.06,1.75] .87 [.66,1.16] 1.11 [.84,1.46]

Living arrangements

Living with both parents (Ref.) 1 1 1 1

Living with mother, not father 1.94*** [1.69,2.22] 1.51*** [1.31,1.74] .99 [.91,1.08] 1.11 [.99,1.24]

Living with father, not mother .98 [.78,1.23] 1.23 [.99,1.53] .89 [.76,1.04] 1.07 [.88,1.3]

Living with relative, no parent 5.87*** [5.28,6.52] 3.44*** [3.08,3.84] .80*** [.73,.87] 1.10 [.99,1.23]

Does not live with relatives 1.59*** [1.27,1.99] 2.18*** [1.84,2.58] .56*** [.47,.66] 1.09 [.92,1.3]

Household risk factors

Number of educated women

None (Ref.) 1 1 1 1

1 .36*** [.32,.4] .52*** [.46,.58] 1.07 [.98,1.17] .99 [.89,1.1]

2 .30*** [.25,.35] .46*** [.39,.54] 1.08 [.95,1.23] 1.00 [.86,1.17]

3+ .29*** [.22,.37] .44*** [.35,.55] .94 [.79,1.12] 1.19 [.96,1.48]

Crowding 1.07*** [1.04,1.1] 1.05*** [1.02,1.08] 1.06*** [1.03,1.08] 1.02 [1,1.05]

Youth dependency 1.37*** [1.28,1.47] 1.09 [.99,1.19] .95 [.89,1.01] 1.02 [.94,1.1]

Community level variables

Percentage of educated women .97*** [.97,.98] .97*** [.96,.98] .98*** [.97,.98] 1.00 [.99,1]

Nighttime lights .94** [.91,.98] .89* [.8,.98] .99 [.97,1] .98 [.96,1.01]

Travel time to major city 1 [1,1] 1*** [1,1] 1 [1,1] 1 [1,1]

Note: * p<0.05, ** p<0.01, *** p<0.001 
47 

Appendix Figure 1 Adjusted odds of being stunted, among children under age 5, for males vs. females 

(reference) 
48 

Appendix Figure 2 Adjusted odds of being stunted, among children under age 5, for three types of 

orphans vs. non-orphans (reference) 
49 

Appendix Figure 3 Adjusted odds of being stunted, among children under age 5, for four types of 

living arrangements vs. living with both parents (reference) 
50 

Appendix Figure 4 Adjusted odds of being stunted, among children under age 5, for the number of 

educated women in the household vs. no educated women (reference) 
51 

Appendix Figure 5 Adjusted odds of being stunted, among children under age 5, for the household 

crowding index and the youth dependency ratio 
52 

Appendix Figure 6 Adjusted odds of being stunted, among children under age 5, for the percentage of 

educated women in a cluster, nighttime lights, and travel time to a major city 
53 

Appendix Figure 7 Adjusted odds of being wasted, among children under age 5, for males vs. females 

(reference) 
54 

Appendix Figure 8 Adjusted odds of being wasted, among children under age 5, for three types of 

orphans vs. non-orphans (reference) 
55 

Appendix Figure 9 Adjusted odds of being wasted, among children under age 5, for four types of living 

arrangements vs. living with both parents (reference) 
56 

Appendix Figure 10 Adjusted odds of being wasted, among children under age 5, for the number of 

educated women in the household vs. no educated women (reference) 
57 

Appendix Figure 11 Adjusted odds of being wasted, among children under age 5, for the household 

crowding index and the youth dependency ratio 
58 

Appendix Figure 12 Adjusted odds of being wasted, among children under age 5, for the percentage of 

educated women in a cluster, nighttime lights, and travel time to a major city 
59 

Appendix Figure 13 Adjusted odds of anemia, among children under age 5, for males vs. females 

(reference) 
60 

Appendix Figure 14 Adjusted odds of anemia, among children under age 5, for three types of orphans 

vs. non-orphans (reference) 
61 

Appendix Figure 15 Adjusted odds of anemia, among children under age 5, for four types of living 

arrangements vs. living with both parents 
62 

Appendix Figure 16 Adjusted odds of anemia, among children under age 5, for the number of educated 

women in the household vs. no educated women (reference) 
63 

Appendix Figure 17 Adjusted odds of anemia, among children under age 5, for the household crowding 

index and the youth dependency ratio 
64 

Appendix Figure 18 Adjusted odds of anemia, among children under age 5, for the percentage of 

educated women in a cluster, nighttime lights, and travel time to a major city 
65 

Appendix Figure 19 Adjusted odds of receiving no treatment for ARI, among children under age 5 with 

ARI symptoms, for males vs. females (reference) 

Appendix Figure 20 Adjusted odds of receiving no treatment for ARI, among children under age 5 with 

ARI symptoms, for only mother alive vs. non-orphans (reference). 

Note: Other orphan status categories did not have enough 

observations to produce estimates. 
66 

Appendix Figure 21 Adjusted odds of receiving no treatment for ARI, among children under age 5 with 

ARI symptoms, for living with mother only vs. living with both parents (reference). 

Note: Other living arrangement categories did not have 

enough observations to produce estimates. 
67 

Appendix Figure 22 Adjusted odds of receiving no treatment for ARI, among children under age 5 with 

ARI symptoms, for the number of educated women in the household vs. no 

educated women (reference) 
68 

Appendix Figure 23 Adjusted odds of receiving no treatment for ARI, among children under age 5 with 

ARI symptoms, for the household crowding index and the youth dependency ratio 
69 

Appendix Figure 24 Adjusted odds of receiving no treatment for ARI, among children under age 5 with 

ARI symptoms, for the percentage of educated women in a cluster, nighttime lights, 

and travel time to a major city 
70 

Appendix Figure 25 Adjusted odds of not having a birth certificate or birth registration, among children 

under age 5, for males vs. females (reference) 
71 

Appendix Figure 26 Adjusted odds of not having a birth certificate or birth registration, among children 

under age 5, for three types of orphans vs. non-orphans (reference) 
72 

Appendix Figure 27 Adjusted odds of not having a birth certificate or birth registration, among children 

under age 5, for four types of living arrangements vs. living with both parents 

(reference) 
73 

Appendix Figure 28 Adjusted odds of not having a birth certificate or birth registration, among children 

under age 5, for the number of educated women in the household vs. no educated 

women (reference) 
74 

Appendix Figure 29 Adjusted odds of not having a birth certificate or birth registration, among children 

under age 5, for the household crowding index and the youth dependency ratio 
75 

Appendix Figure 30 Adjusted odds of not having a birth certificate or birth registration, among children 

under age 5, for the percentage of educated women in a cluster, nighttime lights, 

and travel time to a major city 
76 

Appendix Figure 31 Adjusted odds of not attending school, among children age 5-14, for males vs. 

females (reference) 
77 

Appendix Figure 32 Adjusted odds of not attending school, among children age 5-14, for three types of 

orphans vs. non-orphans (reference) 
78 

Appendix Figure 33 Adjusted odds of not attending school, among children age 5-14, for four types of 

living arrangements vs. living with both parents (reference) 
79 

Appendix Figure 34 Adjusted odds of not attending school, among children age 5-14, for the number of 

educated women in the household vs. no educated women (reference) 
80 

Appendix Figure 35 Adjusted odds of not attending school, among children age 5-14, for the household 

crowding index and the youth dependency ratio 
81 

Appendix Figure 36 Adjusted odds of not attending school, among children age 5-14, for the percentage 

of educated women in a cluster, nighttime lights, and travel time to a major city 
82 

Appendix Figure 37 Adjusted odds of adolescent fertility, among girls age 15-17, for three types of 

orphans vs. non-orphans (reference) 
83 

Appendix Figure 38 Adjusted odds of adolescent fertility, among girls age 15-17, for four types of living 

arrangements vs. living with both parents (reference) 
84 

Appendix Figure 39 Adjusted odds of adolescent fertility, among girls age 15-17, for the number of 

educated women in the household vs. no educated women (reference) 
85 

Appendix Figure 40 Adjusted odds of adolescent fertility, among girls age 15-17, for the household 

crowding index and the youth dependency ratio 
86 

Appendix Figure 41 Adjusted odds of adolescent fertility, among girls age 15-17, for the percentage of 

educated women in a cluster, nighttime lights, and travel time to a major city 
87 

Appendix Figure 42 Adjusted odds of sex before age 15, among girls age 15-17, for three types of 

orphans vs. non-orphans (reference) 
88 

Appendix Figure 43 Adjusted odds of sex before age 15, among girls age 15-17, for four types of living 

arrangements vs. living with both parents (reference) 
89 

Appendix Figure 44 Adjusted odds of sex before age 15, among girls age 15-17, for the number of 

educated women in the household vs. no educated women (reference) 
90 

Appendix Figure 45 Adjusted odds of sex before age 15, among girls age 15-17, for the household 

crowding index and the youth dependency ratio 
91 

Appendix Figure 46 Adjusted odds of sex before age 15, among girls age 15-17, for the percentage of 

educated women in a cluster, nighttime lights, and travel time to a major city 
92 

Appendix Figure 47 Adjusted odds of being underweight, among girls age 15-17, for three types of 

orphans vs. non-orphans (reference) 
93 

Appendix Figure 48 Adjusted odds of being underweight, among girls age 15-17, for four types of living 

arrangements vs. living with both parents (reference) 
94 

Appendix Figure 49 Adjusted odds of being underweight, among girls age 15-17, for the number of 

educated women in the household vs. no educated women (reference) 
95 

Appendix Figure 50 Adjusted odds of being underweight, among girls age 15-17, for the household 

crowding index and the youth dependency ratio 
96 

Appendix Figure 51 Adjusted odds of being underweight, among girls age 15-17, for the percentage of 

educated women in a cluster, nighttime lights, and travel time to a major city 
97 

Appendix Figure 52 Adjusted odds of anemia, among girls age 15-17, for three types of orphans vs. 

non-orphans (reference) 
98 

Appendix Figure 53 Adjusted odds of anemia, among girls age 15-17, for four types of living 

arrangements vs. living with both parents (reference) 
99 

Appendix Figure 54 Adjusted odds of anemia, among girls age 15-17, for the number of educated 

women in the household vs. no educated women (reference) 
100 

Appendix Figure 55 Adjusted odds of anemia, among girls age 15-17, for the household crowding index 

and the youth dependency ratio 
101 

Appendix Figure 56 Adjusted odds of anemia, among girls age 15-17, for the percentage of educated 

women in a cluster, nighttime lights, and travel time to a major city