DEMOGRAPHIC

AND

HEALTH

RESEARCH

DHS WORKING PAPERS

2010 No. 73

Adébiyi Germain Boco

September 2010

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

International Development.

Individual and Community-level 

Effects on Child Mortality: 

An Analysis of 28 Demographic and 

Health Surveys in Sub-Saharan Africa
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 MEASURE 

DHS project (#GPO-C-00-08-00008-00). The views expressed are those of the authors and do not 

necessarily reflect the views of USAID or the United States Government. 

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

population, health, and nutrition programs. Additional information about the MEASURE DHS project can 

be obtained by contacting MEASURE DHS, ICF Macro, 11785 Beltsville Drive, Suite 300, Calverton, 

MD 20705 (telephone: 301-572-0200; fax: 301-572-0999; e-mail: reports@measuredhs.com; internet: 

www.measuredhs.com).
Individual and Community Level Effects on Child Mortality: 

An Analysis of 28 Demographic and Health Surveys in Sub-Saharan Africa

Adébiyi Germain Boco

ICF Macro

Calverton, Maryland, USA 

September 2010 

Corresponding author: Adébiyi Germain Boco, Département de Démographie, Université de Montréal, Pavillon 

Lionel-Groulx, 3150 Jean-Brillant, Montréal (QC) H3T 1N8; E-mail: a.boco@umontreal.ca
ACKNOWLEDGEMENT

Funding for this research was provided by a fellowship from the United States Agency 

for International Development (USAID) through the MEASURE DHS project at ICF Macro. The 

author is indebted to Simona Bignami for guidance and helpful advice. The author would like to 

thank Astou Coly for useful comments, Bryant Robey for editing, and Yuan Gu for formatting 

the working paper. 

Suggested citation: 

Boco, Adébiyi Germain. 2010. Individual and Community Level Effects on Child Mortality: An 

Analysis of 28 Demographic and Health Surveys in Sub-Saharan Africa. DHS Working Papers 

No. 73. Calverton, Maryland, USA: ICF Macro.
ABSTRACT

While researchers have devoted considerable attention to the impact of individual-level 

factors on child mortality, less is known about how community characteristics affect health 

outcomes for children, even though they have a prominent role in theoretical models. Using data 

from the latest round of Demographic Health Surveys (DHS) for all countries in sub-Saharan 

Africa, this study uses multivariate and multilevel discrete-time event history analysis to 

systematically examine the impact of contextual factors on the risk of dying before age five, and 

their relative importance in relation to individual factors. The results indicate that some attributes 

of the community influence the mortality risks of children, over and above the intermediate 

factors included in this investigation. For instance, in half of the countries under study a 1% 

increase in the proportion of children fully immunized in the community is associated with a 

decrease of 17-79% in the odds of dying before age five. The proportion of women in the 

community completing secondary school also significantly increases child survival. In some 

countries, this effect is in addition to the positive individual-level effect of the child’s own 

mother being educated. Net of individual and household characteristics, higher community-level 

ethnic homogeneity is associated with decreased odds of dying before age five, in some 

countries. Overall, the results of this study suggest that the challenge to reduce under-five 

mortality goes beyond addressing individual factors, and requires a better understanding of 

contextual factors. 

Keywords: child mortality; individual-level effects; community-level effects; multilevel 

modeling; sub-Saharan Africa

1 

INTRODUCTION 

Disparities in child health between and within countries have persisted and widened 

considerably during the last few decades (Bryce et al. 2006; Moser et al. 2005). The reduction of 

these disparities is a key goal of most developing countries’ public health policies, as outlined in 

the Millennium Development Goals 2015 (Lawn et al. 2007). It is well recognized that 

disparities in child health outcomes may arise not only from differences in the characteristics of 

the families that children are born into but also from differences in the socioeconomic attributes 

of the communities where they live (Fotso and Kuate-Defo 2005; Griffiths et al. 2004; Kravdal 

2004; Ladusingh and Singh 2006; Montgomery and Hewett 2005; Robert 1999; Sastry 1996). 

Indeed, the incorporation of community-level factors in the analysis of child mortality provides 

an opportunity to identify the health risks associated with particular social structures and 

community ecologies, which is a key policy tool for the development of public health 

interventions (Pickett and Pearl 2001; Stephenson et al. 2006). 

Nonetheless, while researchers have devoted considerable attention to the impact of 

individual-level factors on child mortality, less is known about how community characteristics 

affect health outcomes for children, even though they have a prominent role in theoretical 

models (most notably Mosley and Chen 1984; Schultz 1984). Existing studies generally have a 

limited focus (a single country) and are quite heterogeneous in the data, definitions, and methods 

adopted (Rajaratnama et al. 2006; Schaefer-McDaniel et al. 2010). To my knowledge, there are 

no recent studies that systematically examine contextual influences on child mortality crossnationally. 

The present study takes advantage of the most recent national survey data to reexamine 

the issue of contextual effects on childhood mortality in sub-Saharan Africa. In doing so, it 

contributes to the literature that explores the implications of contextual factors for child mortality 

by examining the effects of community context on the risk of dying before age five, net of the 

effect of individual factors. In many respects, the analysis updates previous work by Desai and 

Alva (1998), Gakidou and King (2002), and Rutstein (2000). However, it adds importantly to 

this stream of literature by providing consistent and comparable results from a multilevel 

analysis of the factors associated with child mortality in sub-Saharan Africa.
2 

LITERATURE REVIEW 

Despite the insights provided by the rare analyses of African data (Balk et al. 2004; 

Gakidou and King 2002), scientific knowledge on how community-level factors influence child 

survival remains fragmentary. Existing studies have been restricted to the analysis of clustering 

at a single level (family or community), and thus have ignored the complete hierarchical 

structure of the data (Gibbons and Hedeker 1997). I go beyond previous efforts in this field by 

developing a multilevel model to quantify the magnitude and importance of clustering mortality 

risks at the family and community levels. My model explicitly accounts for the unobserved 

heterogeneity by using—simultaneously—family and community random effects with a crosslevel correlation structure (Manda 1998). 

In this section, I summarize the literature that indicates how the community environment 

matters for the health of children. I also discuss the possibility of endogeneity bias when 

analyzing this relationship and provide an overview of the ways in which endogeneity has been 

addressed in the literature.

Community-Level Effects on Child Mortality

Mosley and Chen’s (1984) well-known framework of the proximate causes of child 

mortality links outcomes to socioeconomic determinants at individual, household, and 

community levels. Several theoretical and practical considerations support the idea that the 

community where a child is born is important for the child’s health and survival, particularly in 

Africa (Ellen et al. 2001; Entwisle et al. 2007; Huie 2001; Robert 1999). 

In many areas of African countries, families cannot easily access routine health services, 

and health outcomes depend on community-based services and norms (WHO 2005). It follows 

that “place and health are intimately linked, given that goods and services, exposure to hazards, 

and the availability of opportunities are all spatially distributed” (Do and Finch 2008). Generally, 

community is considered to be spatially-referenced and bounded, and its role in determining the 

health of individuals who live in a community becomes evident, as most government and nongovernment activities are spatially organized (Arguillas 2008). Provision of health care and other 
3 

public services, such as water supply, electricity, and sanitation are implemented at the level of a 

geographically defined community. The availability of a health infrastructure in the community 

has the potential to improve the survival chances of young children, because it provides more 

opportunities for health care and reduces the costs of obtaining health-related goods and services 

(The Cebu Study Team 1991). The prevailing norms and attitudes about health behaviors could 

also influence the health care decisions made by individuals (Rutenberg and Watkins 1997). 

Similarly, the quality of the physical environment in the community where children live has 

important consequences for their health. 

Studies during the past two decades have increasingly used multilevel methods to 

examine the independent effect of contextual factors on child mortality, as distinct from the more 

widely investigated individual factors. In particular, communities’ educational and literacy levels 

have been found to have a strong effect on children’s health outcomes (Kravdal 2004; Parashar 

2005). The level of socioeconomic development also appears to have a positive effect on child 

health and nutritional status (Boyle et al. 2006; Fotso and Kuate-Defo 2005; Montgomery and 

Hewett 2005), as well as on access to health care and health infrastructure (Andes 1989; 

Macintyre et al. 2002; Matteson et al. 1998; Pickett and Pearl 2001). Finally, variation in child 

health outcomes can be framed by contextual issues relating to culture (Say and Raine 2007), 

such as ethnic composition (Weeks et al. 2006) and polygyny (Omariba and Boyle 2007). 

In sum, several physical and social attributes of the community have been shown to affect 

the health of young children, regardless of the household context that the children are born into 

(Arguillas 2008). Thus, in this analysis I take a holistic approach by simultaneously examining 

several dimensions of the community environment that have the potential to influence the risk of 

a child dying before age five (Kravdal 2004; Macintyre et al. 2002; Matteson et al. 1998; Mosley 

and Chen 1984; Stephenson et al. 2006). 

Methodological Issues and Endogeneity Bias 

Separating the variations in health outcomes that may be due to area-level factors from 

those that may be due to the characteristics of individuals and families requires appropriate 

modeling, and poses methodological challenges (Angeles et al. 2005; Diez Roux 2004). The 
4 

primary methodological challenge in estimating the causal effect of community-level 

characteristics on individual health status is the endogeneity of residential location for health 

outcomes (Do and Finch 2008). This is because community characteristics are determined by the 

individual characteristics of their residents (Diez Roux 2004: 1956). An additional source of 

endogeneity is that certain community characteristics, such as a developed infrastructure or the 

availability of health services, may be purposively placed in areas with particularly poor health, 

or where there is higher demand for services, and more influence over governmental decisions 

(Burgard 2002). 

It is widely recognized that cross-sectional studies of community context and health are 

subject to upward biases due to unobserved heterogeneity, and to downward biases due to overadjustment for potential mediators in the pathway between community context and individual 

health (Do and Finch 2008: 611). A number of options are available to address the biasing effect 

of endogeneity (Kawachi and Subramanian 2007). For instance, Pritchett and Summers have 

carried out extensive econometric analysis using a range of instrumental variables to identify the 

“pure” income effect on infant and child mortality, isolated from reverse causation or incidental 

association (Pritchett and Summers 1996). Other analytic methods that have been used to adjust 

for endogeneity bias in cross-sectional analysis include propensity score matching (Do and Finch 

2008) and structural model estimation (Guilkey and Riphahn 1998). 

These techniques are beyond the scope of the present analysis and the readily available 

software. Rather, I compare three practical approaches that researchers can choose to produce a 

more accurate estimate of their standard errors: clustered robust estimation, fixed-effects 

modeling, and multilevel modeling (Allison 2009; Rabe-Hesketh and Skrondal 2006). This is in 

order to overcome the bias due to unobserved heterogeneity at the household and community 

levels, and to take into account the hierarchical structure in the data. I advocate using these three 

methods together because they complement one another, and each one contributes evidence that 

is missing from the other two (described in detail in the next section). Comparative analysis will 

reveal the robustness of the results. 
5 

DATA AND METHODS 

Data Sources 

The study uses data from all most recent Demographic and Health Surveys (DHS) 

available (as of July 2010) for sub-Saharan Africa: Benin (2006), Burkina Faso (2003), 

Cameroon (2004), Chad (2004), Congo Brazzaville (2005), Congo Democratic Republic (2007), 

Ethiopia (2005), Gabon (2000), Ghana (2008), Guinea (2005), Kenya (2008-2009), Lesotho 

(2004), Liberia (2007), Madagascar (2008-2009), Malawi (2004), Mali (2006), Mozambique 

(2000-2001), Namibia (2003), Niger (2006), Nigeria (2008), Rwanda (2003), Senegal (2005), 

Sierra Leone (2008), Swaziland (2006-2007), Tanzania (2004-2005), Uganda (2006), Zambia 

(2007), and Zimbabwe (2005-2006). 

For all 28 countries, information on child mortality is derived from full birth histories 

collected from women of reproductive age. The analysis is restricted to children born in the fiveyear period before the survey, because of the availability of information on maternal and child 

health. Details regarding sample design and data collection procedures can be found in the 

individual country reports. The number of children included in the analysis ranges from 2,829 in 

Swaziland to 28,100 in Nigeria (Table 1). Table 1 also gives the average number of births per 

family and community, by country. 
6 

Table 1: Total number of births, average number1 of births in families and communities, and 

under-five mortality rate: DHS in 28 countries in sub-Saharan Africa, 2001-2007

Country and Region

Year of 

survey

Total number 

of births 

during the 5 

years before 

the survey1

Average number of 

births1 Under-five 

mortality 

Family Community (5q0)*

Western Africa 

 Benin 2006 15,929 1.7 21.4 124.9

 Burkina Faso 2003 10,852 1.9 27.0 183.7

 Ghana 2008 2,909 1.5 6.9 80.0

 Guinea 2005 6,370 1.8 21.8 163.2

 Liberia 2007 5,594 1.6 19.5 109.5

 Mali 2006 14,420 1.8 35.9 190.5

 Niger 2006 9,954 1.9 29.1 197.6

 Nigeria 2008 28,100 1.8 30.8 156.9

 Senegal 2005 10,530 2.2 27.0 121.3

 Sierra Leone 2008 5,811 1.6 16.6 139.8

Middle Africa

 Cameroon 2004 8,097 1.8 17.6 143.6

 Chad 2004 5,989 1.8 32.3 190.6

 Congo Brazzaville 2005 4,948 1.6 23.2 116.6

 Congo Democratic Republic 2007 8,999 1.8 30.8 147.9

 Gabon 2000 4,031 1.8 15.8 88.6

Eastern Africa 

 Ethiopia 2005 11,163 1.6 20.4 123.5

 Kenya 2008-2009 5,852 1.6 15.1 114.6

 Madagascar 2008-2009 12,686 1.6 21.2 93.9

 Malawi 2004 10,771 1.5 18.7 133.2

 Mozambique 2000-2001 10,620 1.6 16.8 152.4

 Rwanda 2003 8,715 1.6 18.9 152.4

 Tanzania 2004-2005 8,725 1.7 18.0 112.0

 Uganda 2006 8,423 1.8 23.1 127.6

 Zambia 2007 6,435 1.7 20.1 118.7

 Zimbabwe 2005-2006 5,231 1.4 13.1 82.5

Southern Africa

 Lesotho 2004 3,572 1.3 8.6 112.8

 Namibia 2003 5,003 1.5 10.4 69.4

 Swaziland 2006-2007 2,829 1.6 10.7 119.9

1 Weighted.

Note: * Probability of dying between birth and age 5, refer to a 5-year period before the survey, and they are 

expressed as a rate per 1,000 live births. 

Source: Macro International Inc, 2010. MEASURE DHS STAT compiler. http://www.measuredhs.com, April 26 

2010. 
7 

Analytical Strategy

In this study I attempt to separate individual-level and household-level factors from 

contextual factors associated with child survival by using multivariate and multilevel event 

history models to account for right-censoring in the estimation of exposure time (Allison 1982; 

Reardon et al. 2002; Sear et al. 2002). The outcome variable of interest is the risk of death in 

childhood (0-59 months), measured as the duration from birth to the age at death, or censored. 

Children who were still alive at the time of the interview were right censored. Since in the DHS 

age at death (reported in days and months) is subject to heaping at certain ages, a discrete 

formulation of time is preferred to a continuous one. Discrete-time hazard models require that 

episodes be split into periods of risk (Singer and Willett 2003). Five exposure periods are defined 

here: 0, 1-5, 6-11, 12-23, and 24-59 months. 

The analytical strategy for the study relies on estimating three sets of models for each 

country (Table 2). 

Table 2: Summary of procedure and decision rules for variables entered and included in the 

multivariate and multilevel event history models

Model Estimation Technique Independent Variables Procedure and Software

Model 1 Standard logit discretetime model accounting 

for within-cluster 

correlation by using the 

Huber-White procedure

Conventional logistic regression predicting 

children’s probability of dying by their fifth 

birthday with only individual-level variables 

as predictors.

logit in Stata

Model 2 Conditional logit 

discrete-time model or 

fixed-effects logit model

Model 2 adds to Model 1 cluster-level fixed 

effects to control for unobserved 

community-level characteristics. The 

covariates are same as in Model 1.

clogit in Stata

Model 3 Multilevel discrete-time 

logit models with threelevel (community, 

family, child) random 

intercepts

The multilevel analysis uses a sequential 

approach to model building. First, I created 

an unconditional model (model 3a) in order 

to determine the proportion of variance in 

the outcome that is attributed to within- and 

between-group differences. Then, in model 

3b I added individual-level variables (child 

and family characteristics) as predictors. 

Finally, in model 3c I added communitylevel characteristics. 

Markov Chain Monte 

Carlo (MCMC) procedure 

in MLwin (version 2.16)
8 

First, I estimate “naïve” logistic regression models predicting children’s probability of 

dying by their fifth birthday, accounting for within-cluster correlation by using the Huber-White 

procedure (Huber 1967; Rogers 1993)1

Logit[pti] = αt + βXti 

. The basic formulation of the standard discrete-time 

model is: 

where pti is the probability of having an event (i.e., death) at time t, given that the event has not 

occurred before t. The logit function of pti is modeled by predictors Xti and corresponding 

coefficients β. In this step, covariates include only individual-level characteristics, as in many 

previous studies. This “naïve” model provides a baseline against which to compare the results of 

more complex models, to be estimated as indicated below. 

In the second step, I estimate cluster-level fixed-effects models, which include a linear 

effect for unobserved community-level factors on the risk of dying before age five. The fixedeffects approach has been used to analyze the role of individual, family, and community factors 

in determining infant mortality in other social contexts, using DHS data (Desai and Alva 1998; 

Frankenberg 1995). In their study exploring the causal effect of mother’s education on infant 

mortality, Desai and Alva (1998) used a fixed-effects logit model in order to understand the 

potential biases from omitted community unobservables. I follow the same approach in this step. 

The model is given by: 

Logit[ptij] = aj + αtj+ βXtij

Here, j indexes clusters (i.e. the primary sampling units (PSUs)), i (i=1, 2) indexes matched 

children within each cluster, and aj represents cluster effects (i.e. the effects of all unmeasured 

variables that are specific to each cluster but constant over time). Note that no time-invariant 

covariates are included in the model, as their effects are absorbed into the aj term. An indication 

of the extent to which the data for the present analysis are clustered is that each family 

contributes more than one child to the samples. As can be seen in Table 1, in 23 of the 28 

countries included in the analysis the average number of births per family is about two. Overall, 

the average number of births per community ranges from 7 in Ghana to 36 in Mali (Table 1). 

 

1 The Huber-White procedure produces results identical to those of the svylogit procedure (not shown), 

which is the specific Stata routine recommended to account for the DHS complex survey design. 
9 

PSUs, or clusters, are administratively-defined areas used as proxies for “neighborhoods” 

or “communities” (Diez Roux 2001), and are relevant when the hypothesis involves policies 

(Pearl et al. 2001: 1874). They are small and designed to be fairly homogenous units with respect 

to the population’s social and demographic characteristics, economic status, and living 

conditions, and they are made up of one or more enumeration areas (EAs), which are the smallest 

geographic units for which census data are available in the country (Montgomery and Hewett 

2005: 402). Generally, a rural community spans one village or settlement, whereas an urban 

community is a part of a city (Montgomery and Hewett 2005). As do Desai and Alva (1998: 73), 

I use the terms communities and clusters interchangeably. 

One important question about community-level effects that motivates this paper is 

whether they have a significant impact on the risk of death in poorly-equipped contexts, as in 

sub-Saharan Africa (WHO 2005). The fixed-effects logit estimates proposed here provide 

information with which to answer that question, conditional on the underlying specification. The 

fixed-effects models clarify which community variables affect mortality, the direction of the 

effects, and the magnitude of the effects on relative mortality risks (Frankenberg 1995). This 

specification allows for the possibility that unobserved heterogeneity affects child survival 

(Sastry 1997b). 

I estimate fixed effects logit regressions by relying on conditional logits (Allison 2009). 

This method is also known as the case-control technique (Chamberlain 1980), which requires 

that we must first pair children within clusters. Thus I randomly selected pairs of children from 

each cluster, consisting of one death reported during five years preceding the survey (cases) and 

one birth that survived during the same time period (controls). All pairs in which both children 

had an identical value for the dependent variable (death or alive), therefore, are excluded from 

the estimation of the fixed-effects logit model. Such exclusion leads to a reduction in the sample 

size, which can be quite substantial and may affect the precision of the estimated effects of the 

covariates. Here, the comparison of more than one estimation method indicates that the results

are robust in spite of this issue. In addition, because of this approach, the effect of any variable 

that does not vary between children in the cluster (for example, urban/rural residence) cannot be 

estimated in this model. 

By using DHS data, it is possible to construct appropriate community-level measures for 

selected covariates of interest, and, in some cases, the surveys even directly provide information 
10 

on community-level characteristics (Van de Poel et al. 2009). On the basis of these measures 

(described in detail in the next section), in the final step of the analysis I apply logit discrete-time 

models with three-level random intercept to correctly account for the hierarchy in the DHS data, 

and properly assess the impact of community-level factors on child mortality net of individuallevel factors. The hierarchical structure of the data presents children (level 1), as nested within 

mothers (level 2), who are in turn nested within communities (level 3). 

The multilevel modeling strategy accommodates the hierarchical nature of the data and 

corrects the estimated standard errors to allow for clustering of observations within units 

(Goldstein 2003). A significant random effect may represent factors influencing the outcome 

variable that cannot be quantified in a large-scale social survey. A random effects model thus 

provides a mechanism for estimating the degree of correlation in the outcome that exists at the 

family level and community level, while also controlling a range of child-level, family-level, and 

community-level factors that may potentially influence the outcome.

Assuming a logit link between the hazard rate and the explanatory variable, the threelevel random-effects discrete-time hazard model can be expressed as: 

Logit[ (ptijk/(1- ptijk)] = αt + Xtijkβ + μjk + νk 

where ptijk is the probability that child i in household j in community k observed in the time 

interval t dies within that interval; Xtijk is a vector of community and family-child level 

explanatory variables; β is a vector of unknown regression parameters associated with the 

explanatory variables Xtijk; αt is a function of time and is defined for age; and μjk [~ Ν(0,σ2

μ)] and 

νk [~ Ν(0,σ2

ν) ] are error terms at the mother and community levels, respectively, that give an 

indication of the variation after controlling for the individual-level characteristics (Manda 1998). 

The error terms are standardized to have mean zero and variance of σ2

μ and σ2ν, respectively, and 

are assumed to be uncorrelated. In this paper, the variances can be interpreted in terms of intraclass correlations (ρν and ρμ; for the community and family, respectively) in a latent variable 

reflecting the unobserved factors that are shared among children in the same community or in the 

same family2

 

2 These intra-class correlations (ICC) are defined as ρν = σν

2

/[σν

2 + σμ2 + 3.29] and ρμ = (σν2 + σμ2

)/[σν

2 + 

σμ

2 + 3.29] at the community and family levels, respectively; where σ

2

μ and σ2ν represent the variance at 

the family and community levels, respectively, and 3.29 represents the fixed individual variance, which is 

π

2

/3 (Snijders and Bosker 1999). 

. (See Manda (1998) for an explanation of how this expression for the intra-class 
11 

correlation is derived.) The estimated variance represents the extent to which children in the 

same community are exposed to the same conditions (sanitation, hygiene, availability of 

services) even if they have different individual characteristics (Larsen and Merlo 2005). We can 

then interpret this as evidence of differential mortality levels between groups, for instance births 

in poor communities relative to rich communities. The higher the estimated variance, the higher 

is the level of inequality between groups. 

The analytical strategy in the case of multilevel analysis consists of applying three 

models for each country. The first model is the empty model, i.e., a model without covariates 

fitted to test random variability in the intercept and to estimate the intra-class correlation 

coefficient. The second model includes only the individual-level variables as predictors. The 

third model includes both the individual-level and the community-level variables. This approach 

allows the sequential measurement of the relative contributions of each set of variables to the 

community-level variance. Reduction in the intra-class correlations (ICC) relative to unadjusted 

analysis is evidence for explaining geographic variation by the variables included in a multilevel 

model. 

Fixed effects models are fitted using Stata 11.1 (Stata Corporation 2009). MLwiN version 

2.16 is used for the multilevel analysis. The multilevel logistic regression models are estimated 

with Markov Chain Monte Carlo (MCMC) methods in MLwiN. The MCMC procedure is used 

to fit multilevel models because it produces less biased estimates of variance parameters than 

quasi-likelihood methods for binary response models (Browne 2009). The default settings in 

MLwiN are used for the analyses, i.e., chains of length 5000 after a burn-in of 500. Bayesian 

deviance information criterion (DIC) is used to estimate the goodness of fit of consecutive 

models. Spiegelhalter et al. (2002) proposed using the DIC as a Bayesian equivalent of Akaike's 

Information Criterion (AIC)

3

 

3 The AIC is appropriate for comparing non-nested models such as those estimates here. The AIC is 

calculated as -2 (loglikelihood of fitted model) +2p, where p is number of parameters in the model. The 

AIC values for each model are compared and the model with the lowest value is considered the better one 

(Maddala 1988). 

for hierarchical models. A lower value on DIC indicates a better fit 

of the model (Spiegelhalter et al. 2002). As suggested by Browne, I fitted the model using firstorder marginal quasi-likelihood (MQL) to generate starting values for the MCMC process 

(Browne 2009: 6). 
12 

Fixed estimates presented in the results section are those of the full models. The β 

coefficients (standard errors) have been converted into odds ratios and are presented alongside 

95% confidence intervals. Estimates for the three analytical methods are presented side by side 

in the tables to facilitate comparisons.

Individual-Level and Community-Level Control Variables 

Individual-level and household-level factors considered in this study are a set of standard 

covariates that have been identified by previous studies as important determinants of child 

mortality, and that are available for all countries considered (Hobcraft et al. 1985; Rafalitnanana 

and Westoff 2000; Rutstein 2000). They include: the age of the child (in months); the child’s 

sex; the duration of the preceding birth interval; the mother’s age at the child’s birth; the 

mother’s education; whether the birth of the index child received skilled attendance (doctor, 

nurse, or midwife) at delivery; and household wealth. 

Community-level characteristics are not directly available for most surveys included in 

the analysis. Instead, they are constructed by aggregating individual-level and household-level 

characteristics at the cluster level (i.e. the primary sampling units for the DHS). They include: 

the type of place of residence (urban/rural); the cluster’s socioeconomic status (defined as the 

proportion poor in the cluster); the proportion of women in the cluster with secondary or higher 

education; the cluster’s level of ethnic fractionalization (defined as the probability that two 

individuals selected at random from a cluster will be from different ethnic groups) (Fearon 

2003); and the percentage of children who are fully immunized in the community (that is, who 

have received BCG, measles, and three doses of DPT and polio vaccines)4

. The last predictor is a 

continuous variable, whereas all others variables at the community level are dummy variables, 

representing discrete factors coded using the reference cell method. All variables and their 

operational definitions are described in detail in Appendix Table 1. 

 

4 It is not possible to include individual-level indicators of variables like immunization status and nutrition 

as predictors of mortality, since values are missing for deceased children. Rather, the DHS questionnaire 

collects information on vaccination status, height, and weight of each surviving child who was born in the 

3/5 years before the survey date. 
13 

RESULTS 

Levels of Under-Five Mortality Rates and Samples’ Characteristics 

Table 1 reports observed under-five mortality rates (U5MR) for each country included in 

the analysis, in the most recent five-year period. Globally, child mortality rates remain higher in 

sub-Saharan Africa (SSA) than in other regions. Within SSA, however, there is a large variation 

in U5MR among countries, from a high of 197.6 deaths per 1,000 live births in Niger to a low of 

69.4 deaths per 1,000 live births in Namibia. Overall, the highest SSA child mortality levels are 

in West Africa, except for Ghana, where the U5MR is 80.0 deaths per 1,000 live births. Other 

countries with relatively low child mortality rates include Gabon, Madagascar, and Zimbabwe, 

all with U5MR below 100 deaths per 1,000 live births. 

Disparities in U5MR at the national level between countries probably reflect the 

socioeconomic and health care contexts of the countries. Appendix Table 2 presents countryspecific demographic, socioeconomic, and health behavior data relevant to the analysis, 

providing a picture of the broader context for the 28 countries. The figures presented are 

weighted percentages, with weighted column totals presented at side. As shown in Appendix 

Table 2, there are large differences in the covariates between countries, but these differences 

seldom form clear regional patterns. In many countries most of the children live in rural areas 

(more than 60% in 24 out of 28 countries). There is substantial variation across countries in the 

use of health services. The proportion of births attended by a skilled health provider (doctor, 

nurse, or midwife) ranges from under 6% in two countries—Chad and Ethiopia—to 81.6% in 

Namibia. The proportion of births in the five years before the survey delivered in a health facility 

ranges from 5.7% in Ethiopia to 87.1% in Gabon. Levels of education remain relatively low in 

most sub-Saharan countries. In 9 of the 28 countries studied, the majority of children were born 

to uneducated mothers, and in 17 of the countries, more than 50% of children live in 

communities where the level of women’s education is low. 
14 

Unobserved Heterogeneity at Family and Community Levels in Under-Five Mortality

Table 3 shows the estimates of the family and community level variances, together with 

the intra-family and intra-community correlation coefficients for the 28 separate models, after 

adjusting for the child-level, family-level, and community-level characteristics. This analysis 

supports the numerous other studies that have found that children of the same family have 

correlated probabilities of survival. The between-family variance is highly significant (p-value 

<0.01) in almost all countries. It is less significant in Rwanda (p-value <0.05) and Cameroon (pvalue <0.10). The intra-family correlation coefficients range from 2% (Cameroon) to 38% 

(Lesotho). This result suggests that a significant unobserved heterogeneity exists in the underfive mortality risks between families. Overall, unobserved mother heterogeneity explains a 

substantial part of the random variance in the child mortality across countries. For instance, the 

intra-family correlation is 0.33 in Zambia, indicating that 33% of the variation in mortality risks 

is the result of unobserved family-level factors. 
15 

Table 3: Variance estimates between family and community, and intra-correlations coefficients 

for the discrete-time multilevel models of probability of dying before age 5, by country 

Country

Variance and level of significance Intra-unit correlationsa

Family Community Family Community

Benin 0.480 *** 0.141 *** 0.159 0.036 

Burkina Faso 0.533 *** 0.141 *** 0.170 0.036 

Cameroon 0.002 * 0.056 ns 0.017 0.017 

Chad 0.580 ** 0.113 ** 0.174 0.028 

Congo (Brazzaville) 1.198 *** 0.063 ns 0.277 0.014 

Congo Demo. Rep. 0.794 *** 0.23 *** 0.237 0.053 

Ethiopia 0.833 *** 0.113 ** 0.223 0.027 

Gabon 1.129 *** 0.139 ns 0.278 0.030 

Ghana 1.152 *** 0.216 ns 0.294 0.046 

Guinea 0.582 *** 0.061 ns 0.163 0.016 

Kenya 1.627 *** 0.273 ** 0.366 0.053 

Lesotho 1.976 *** 0.044 ns 0.380 0.008 

Liberia 1.140 *** 0.039 ns 0.264 0.009 

Madagascar 1.205 *** 0.085 ns 0.282 0.019 

Malawi 0.740 *** 0.085 ** 0.200 0.021 

Mali 0.888 *** 0.126 *** 0.236 0.029 

Mozambique 0.953 *** 0.039 ns 0.232 0.009 

Namibia 0.719 *** 0.02 ns 0.183 0.005 

Niger 0.377 *** 0.13 *** 0.134 0.034 

Nigeria 0.949 *** 0.084 *** 0.239 0.019 

Rwanda 0.436 ** 0.167 *** 0.155 0.043 

Senegal 0.480 *** 0.141 *** 0.159 0.036 

Sierra Leone 0.654 *** 0.304 *** 0.226 0.072 

Swaziland 1.171 *** 0.034 ns 0.268 0.008 

Tanzania 0.582 *** 0.128 ** 0.178 0.032 

Uganda 0.475 *** 0.04 ns 0.135 0.011 

Zambia 1.608 *** 0.012 ns 0.330 0.002 

Zimbabwe 1.340 *** 0.052 ns 0.297 0.011 

*** p-value < 0.001; ** p-value < 0.01; * p-value < 0.05; + p-value < 0.10; ns = not significant if at 10%. a Intra-group correlation coefficients measure the degree of clustering and include random intercepts with both 

individual- and community-level as predictors. Intra-community correlation (ρν), which measures the proportion of 

the total variance which is between communities, expresses similarity of children in probability of dying before age 5 

from the same community. Intra-family correlation coefficient (ρμ) expresses similarity of children in probability of 

dying before age 5 from the same household (and by definition, from the same community). These intra-class 

correlations (ICC) are calculated as ρν = σν

2

/[σν

2 + σμ2 + σe2

] and ρμ = (σν

2 + σμ2

)/[σν

2

+ σμ

2 + σe2

] at the community 

and family levels, respectively; where σν

2 denotes community-level variance, σ2

μ denotes family-level variance and 

σe

2 denotes individual-level variance, with this latter variance set to π2

/3 (equal to 3.29).
16 

The community variance is significant at the 5% level or lower in half of the countries 

under study. Intra-community variation associated with the risk of dying before age five ranges 

from below 5% in 11 countries to 7% in Sierra Leone. Overall, the results show that the variance 

between communities is smaller than the variance between families.

The community variance and the family variance are jointly significant in 14 of the 28 

countries, providing evidence that the variation in under-five mortality in a number of countries 

in sub-Saharan Africa is produced by the interaction between the family and geographic 

environment of the children. Thus the variation in mortality risks in these countries is 

simultaneously attributed to unobserved heterogeneity at the household and community levels, 

after accounting for child-level, household-level, and community-level characteristics. 

The much larger magnitude of the intra-family correlations than the intra-community 

correlations suggests that residence in a particular community may be a less important 

determinant of child survival across sub-Saharan African countries than is membership in a 

particular family.

Individual-level and Community-level Effects on the Risk of Dying before Age Five

Table 4 presents the adjusted odds ratios and 95 percent confidence intervals of predictor 

variables on the risk of dying before age five, in the three sets of models fitted for each country. 

As one would expect, fixed-effects discrete-time models (model 2) show a better 

adjustment than “naïve” discrete-time hazard models (model 1). In all countries, the AIC (at the 

bottom of the Table 4) of fixed-effects models is smaller, suggesting that the conditional logit 

estimation approach is probably better. This empirical finding demonstrates the need to take 

context into account while examining factors affecting child survival. However, this fixed-effects 

approach does not take into account the possibility that one particular community factor might 

influence child mortality. As mentioned above, these latter two sets of estimates, which include 

only individual variables, serve the purpose of comparing methods. 

This study is focused on contextual effects, and it addresses an important related 

question: what characteristics of the community are associated with the risk of child death, net of 

individual characteristics? Thus discussion of the results is based only on the multilevel discrete-
17 

time hazard models (model 3), which include both individual-level and community-level 

variables, and family and community random effects. 

The results reveal that individual-level and community-level effects on the risk of dying 

before age five vary across the 28 countries. 
18 

Table 4: Odds ratios (OR) and 95 percent confidence intervals (95% CIs) for the effect of 

individual-level and community-level factors on under-five mortality, by country

Benin

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.47 0.40 - 0.57 0.48 0.40 - 0.58 0.49 0.41 - 0.58

 6–11 months 0.64 0.53 - 0.76 0.66 0.55 - 0.78 0.67 0.57 - 0.78

 12–23 months 0.58 0.48 - 0.70 0.62 0.51 - 0.74 0.62 0.53 - 0.73

 24+ months 0.68 0.56 - 0.82 0.73 0.60 - 0.88 0.74 0.62 - 0.88

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.34 1.04 - 1.72 1.15 0.88 - 1.50 1.25 0.98 - 1.59

 2-3 and 24+ months 0.74 0.61 - 0.90 0.70 0.57 - 0.86 0.71 0.60 - 0.84

 4+ and < 24 months 1.39 1.08 - 1.79 1.19 0.92 - 1.55 1.28 1.01 - 1.60

 4+ and 24+ months 0.88 0.72 - 1.07 0.80 0.65 - 0.99 0.83 0.69 - 0.99

Child's sex

 Femaleref

 Male 1.10 0.98 - 1.23 1.14 1.01 - 1.28 1.10 0.99 - 1.22

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.94 0.77 - 1.14 1.01 0.83 - 1.23 0.96 0.79 - 1.16

 35 years or more 0.92 0.70 - 1.22 1.03 0.76 - 1.39 0.93 0.71 - 1.21

Mother's education

 No educationref

 Primary 1.06 0.90 - 1.24 1.07 0.89 - 1.28 1.07 0.91 - 1.27

 Secondary or higher 0.67 0.48 - 0.96 0.71 0.49 - 1.03 0.69 0.50 - 0.95

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.01 0.84 - 1.21 0.99 0.82 - 1.20 1.04 0.88 - 1.23

 3rd quintile 1.10 0.93 - 1.31 1.01 0.84 - 1.23 1.08 0.91 - 1.29

 4th quintile 0.95 0.78 - 1.16 0.96 0.74 - 1.23 0.93 0.76 - 1.15

 5th quintile (Richest) 0.69 0.53 - 0.89 0.71 0.49 - 1.02 0.73 0.55 - 0.96

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.88 0.76 - 1.03 0.95 0.79 - 1.13 0.92 0.80 - 1.06

Community-level variable

Place of residence

 Ruralref

 Urban 0.90 0.77 - 1.05

Proportion of households poor

 Low

 High 0.89 0.76 - 1.05

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low

 High 0.99 0.84 - 1.16

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.04 0.90 - 1.21

Proportion of children fully 

immunizedd 0.63 0.44 - 0.91

Intercept -3.24 -3.49 - -2.99 -3.33 -3.64 - -3.02

AIC/DIC (multilevel model) of 

full models 12,919 10,568 12,955

Cont’d..
19 

Table 4: Cont’d

Burkina Faso

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.80 0.64 - 1.00 0.81 0.65 - 1.02 0.83 0.70 - 0.99

 6–11 months 0.85 0.66 - 1.10 0.88 0.68 - 1.13 0.92 0.77 - 1.10

 12–23 months 1.39 1.14 - 1.69 1.45 1.20 - 1.76 1.40 1.18 - 1.65

 24+ months 1.43 1.13 - 1.82 1.55 1.22 - 1.96 1.58 1.32 - 1.88

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.27 0.89 - 1.81 1.17 0.80 - 1.70 0.99 0.74 - 1.31

 2-3 and 24+ months 0.90 0.71 - 1.13 0.90 0.71 - 1.15 0.83 0.68 - 1.02

 4+ and < 24 months 1.59 1.21 - 2.09 1.45 1.10 - 1.93 1.32 1.01 - 1.73

 4+ and 24+ months 0.87 0.66 - 1.15 0.86 0.65 - 1.15 0.75 0.60 - 0.93

Child's sex

 Femaleref

 Male 1.00 0.88 - 1.13 1.00 0.88 - 1.14 1.00 0.88 - 1.13

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.85 0.67 - 1.06 0.90 0.71 - 1.14 0.82 0.66 - 1.01

 35 years or more 0.88 0.65 - 1.20 0.96 0.70 - 1.32 0.90 0.69 - 1.17

Mother's education

 No educationref

 Primary 0.81 0.64 - 1.03 0.84 0.66 - 1.07 0.92 0.72 - 1.16

 Secondary or higher 0.72 0.47 - 1.10 0.86 0.54 - 1.37 0.72 0.47 - 1.10

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.95 0.76 - 1.18 1.00 0.80 - 1.24 0.96 0.80 - 1.15

 3rd quintile 0.83 0.66 - 1.03 0.83 0.66 - 1.04 0.84 0.70 - 1.01

 4th quintile 0.82 0.65 - 1.04 0.85 0.66 - 1.08 0.91 0.73 - 1.12

 5th quintile (Richest) 0.73 0.53 - 1.01 0.84 0.55 - 1.30 0.73 0.54 - 0.98

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.93 0.78 - 1.10 1.01 0.84 - 1.23 0.94 0.80 - 1.10

Community-level variable

Place of residence

 Ruralref

 Urban 0.87 0.65 - 1.18

Proportion of households poor

 Low

 High 1.01 0.86 - 1.19

Proportion of women aged 15-49 in the community with secondary or 

higher educationb

 Low

 High 1.17 0.93 - 1.46

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 0.97 0.83 - 1.12

Proportion of children fully 

immunizedd 0.49 0.34 - 0.70

Intercept -3.13 -3.41 - -2.86 -3.19 -3.46 - -2.93

AIC/DIC (multilevel model) of 

full models 11,853 9,714 11,273

Cont’d..
20 

Table 4: Cont’d

Cameroon

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.64 0.51 - 0.82 0.66 0.52 - 0.83 0.65 0.54 - 0.80

 6–11 months 0.96 0.76 - 1.20 0.99 0.79 - 1.24 0.91 0.76 - 1.11

 12–23 months 0.97 0.78 - 1.21 1.03 0.83 - 1.28 0.96 0.79 - 1.17

 24+ months 0.92 0.70 - 1.20 1.00 0.77 - 1.31 0.83 0.66 - 1.04

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.45 1.07 - 1.97 1.46 1.04 - 2.05 1.40 1.06 - 1.83

 2-3 and 24+ months 0.80 0.63 - 1.03 0.82 0.63 - 1.08 0.85 0.68 - 1.06

 4+ and < 24 months 1.17 0.83 - 1.67 1.06 0.73 - 1.55 1.19 0.88 - 1.61

 4+ and 24+ months 0.82 0.62 - 1.08 0.80 0.59 - 1.10 0.85 0.66 - 1.10

Child's sex

 Femaleref

 Male 1.04 0.89 - 1.21 1.02 0.86 - 1.20 1.08 0.94 - 1.24

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.88 0.71 - 1.10 0.92 0.72 - 1.18 0.86 0.71 - 1.05

 35 years or more 1.12 0.83 - 1.53 1.21 0.85 - 1.72 1.10 0.81 - 1.49

Mother's education

 No educationref

 Primary 1.19 0.96 - 1.47 1.25 0.96 - 1.64 1.23 1.01 - 1.48

 Secondary or higher 0.98 0.75 - 1.26 1.11 0.81 - 1.53 1.02 0.79 - 1.32

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.88 0.70 - 1.11 0.88 0.69 - 1.12 0.87 0.72 - 1.07

 3rd quintile 0.92 0.73 - 1.15 0.93 0.69 - 1.26 0.90 0.72 - 1.13

 4th quintile 0.87 0.67 - 1.12 0.95 0.65 - 1.40 0.94 0.72 - 1.24

 5th quintile (Richest) 0.65 0.47 - 0.89 0.68 0.42 - 1.10 0.75 0.53 - 1.05

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.88 0.72 - 1.07 1.01 0.79 - 1.28 0.90 0.76 - 1.07

Community-level variable

Place of residence

 Ruralref

 Urban 0.84 0.67 - 1.05

Proportion of households poor

 Low

 High 0.89 0.70 - 1.14

Proportion of women aged 15-49 in the community with secondary or 

higher educationb

 Low

 High 0.93 0.76 - 1.14

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 0.95 0.78 - 1.15

Proportion of children fully 

immunizedd 0.63 0.43 - 0.93

Intercept -3.32 -3.60 - -3.05 -3.08 -3.43 - -2.73

AIC/DIC (multilevel model) of 

full models 7,531 6,245 7,678

Cont’d..
21 

Table 4: Cont’d

Chad

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.68 0.51 - 0.89 0.69 0.52 - 0.90 0.63 0.50 - 0.79

 6–11 months 0.89 0.65 - 1.21 0.91 0.67 - 1.25 1.00 0.80 - 1.24

 12–23 months 0.85 0.61 - 1.19 0.90 0.65 - 1.25 0.90 0.71 - 1.13

 24+ months 1.05 0.78 - 1.41 1.13 0.84 - 1.51 1.12 0.87 - 1.44

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 0.91 0.64 - 1.30 0.83 0.57 - 1.22 0.82 0.58 - 1.14

 2-3 and 24+ months 0.69 0.53 - 0.90 0.67 0.50 - 0.89 0.65 0.49 - 0.87

 4+ and < 24 months 1.36 0.93 - 1.99 1.29 0.84 - 1.98 1.13 0.81 - 1.59

 4+ and 24+ months 0.56 0.40 - 0.80 0.54 0.38 - 0.78 0.57 0.41 - 0.78

Child's sex

 Femaleref

 Male 1.24 1.04 - 1.47 1.25 1.04 - 1.50 1.12 0.95 - 1.31

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.91 0.70 - 1.20 0.91 0.67 - 1.22 0.86 0.68 - 1.09

 35 years or more 1.09 0.75 - 1.58 1.08 0.70 - 1.65 0.96 0.66 - 1.40

Mother's education

 No educationref

 Primary 1.23 0.92 - 1.64 1.21 0.91 - 1.60 1.00 0.80 - 1.26

 Secondary or higher 0.93 0.61 - 1.44 0.93 0.58 - 1.48 0.71 0.47 - 1.07

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.23 0.91 - 1.66 0.84 0.49 - 1.45 1.33 0.97 - 1.82

 3rd quintile 0.91 0.63 - 1.30 0.61 0.32 - 1.18 0.95 0.67 - 1.35

 4th quintile 1.35 1.02 - 1.80 0.89 0.50 - 1.58 1.43 1.01 - 2.02

 5th quintile (Richest) 1.03 0.77 - 1.39 0.66 0.33 - 1.34 1.20 0.77 - 1.89

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.85 0.54 - 1.36 1.03 0.67 - 1.59 1.10 0.74 - 1.62

Community-level variable

Place of residence

 Ruralref

 Urban 0.65 0.46 - 0.92

Proportion of households poor

 Low

 High 0.88 0.64 - 1.20

Proportion of women aged 15-49 in the community with secondary or 

higher educationb

 Low

 High 1.30 1.01 - 1.68

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 0.77 0.58 - 1.01

Proportion of children fully 

immunizedd 0.44 0.18 - 1.09

Intercept -3.21 -3.57 - -2.84 -3.19 -3.70 - -2.68

AIC/DIC (multilevel model) of 

full models 6,671 5,362 6,178

Cont’d..
22 

Table 4: Cont’d

Congo (Brazzaville) 

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.63 0.41 - 0.97 0.65 0.42 - 0.98 0.53 0.40 - 0.71

 6–11 months 0.66 0.46 - 0.95 0.69 0.48 - 0.98 0.59 0.44 - 0.81

 12–23 months 0.48 0.34 - 0.68 0.51 0.36 - 0.73 0.59 0.43 - 0.81

 24+ months 0.40 0.23 - 0.70 0.44 0.25 - 0.76 0.44 0.29 - 0.66

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 0.85 0.52 - 1.42 0.83 0.47 - 1.44 0.77 0.46 - 1.31

 2-3 and 24+ months 0.78 0.54 - 1.12 0.87 0.59 - 1.28 0.69 0.50 - 0.95

 4+ and < 24 months 1.04 0.60 - 1.82 1.01 0.57 - 1.79 0.68 0.37 - 1.24

 4+ and 24+ months 0.73 0.44 - 1.19 0.80 0.47 - 1.34 0.79 0.55 - 1.15

Child's sex

 Femaleref

 Male 1.00 0.79 - 1.26 1.00 0.80 - 1.26 1.09 0.88 - 1.36

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 1.01 0.72 - 1.43 0.92 0.63 - 1.33 0.98 0.71 - 1.36

 35 years or more 1.27 0.75 - 2.16 1.05 0.60 - 1.86 1.07 0.65 - 1.76

Mother's education

 No educationref

 Primary 0.86 0.59 - 1.25 0.91 0.60 - 1.38 1.07 0.72 - 1.58

 Secondary or higher 0.59 0.40 - 0.85 0.67 0.43 - 1.05 0.73 0.50 - 1.08

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.21 0.93 - 1.56 1.46 1.05 - 2.03 1.09 0.76 - 1.56

 3rd quintile 0.97 0.68 - 1.37 1.21 0.80 - 1.82 1.13 0.74 - 1.72

 4th quintile 0.92 0.57 - 1.47 1.52 0.81 - 2.83 1.20 0.72 - 2.00

 5th quintile (Richest) 0.75 0.47 - 1.19 0.90 0.44 - 1.87 0.94 0.53 - 1.66

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 1.08 0.82 - 1.42 1.03 0.76 - 1.39 0.95 0.74 - 1.22

Community-level variable

Place of residence

 Ruralref

 Urban 0.95 0.64 - 1.40

Proportion of households poor

 Low

 High 1.22 0.83 - 1.79

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.75 0.54 - 1.04

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.05 0.53 - 2.06

Proportion of children fully 

immunizedd 0.88 0.45 - 1.73

Intercept -2.97 -3.45 - -2.50 -3.68 -4.24 - -3.12

AIC/DIC (multilevel model) of 

full models 3,966 3,048 3,640

Cont’d..
23 

Table 4: Cont’d

Congo Democratic Republic

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.55 0.42 - 0.70 0.56 0.43 - 0.72 0.72 0.60 - 0.87

 6–11 months 0.64 0.50 - 0.83 0.68 0.53 - 0.87 0.82 0.68 - 0.99

 12–23 months 0.54 0.41 - 0.72 0.58 0.43 - 0.77 0.74 0.60 - 0.91

 24+ months 0.52 0.36 - 0.75 0.56 0.38 - 0.81 0.69 0.54 - 0.87

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.08 0.76 - 1.54 1.01 0.71 - 1.45 0.77 0.58 - 1.04

 2-3 and 24+ months 0.67 0.49 - 0.91 0.66 0.47 - 0.91 0.67 0.52 - 0.85

 4+ and < 24 months 1.31 0.91 - 1.91 1.18 0.81 - 1.70 1.16 0.89 - 1.53

 4+ and 24+ months 0.63 0.45 - 0.90 0.58 0.41 - 0.83 0.60 0.46 - 0.77

Child's sex

 Femaleref

 Male 1.22 1.04 - 1.43 1.21 1.02 - 1.44 1.10 0.96 - 1.27

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.98 0.71 - 1.34 1.13 0.80 - 1.60 1.01 0.80 - 1.27

 35 years or more 1.19 0.71 - 1.97 1.40 0.84 - 2.34 1.27 0.93 - 1.73

Mother's education

 No educationref

 Primary 0.80 0.63 - 1.02 0.74 0.57 - 0.96 0.90 0.75 - 1.08

 Secondary or higher 0.68 0.48 - 0.97 0.74 0.52 - 1.05 0.79 0.62 - 1.00

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.99 0.71 - 1.38 1.07 0.73 - 1.57 0.99 0.79 - 1.25

 3rd quintile 0.77 0.53 - 1.12 0.84 0.55 - 1.26 0.88 0.69 - 1.14

 4th quintile 0.97 0.68 - 1.38 0.98 0.65 - 1.49 1.07 0.79 - 1.45

 5th quintile (Richest) 0.60 0.40 - 0.89 0.63 0.30 - 1.31 0.65 0.44 - 0.97

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.76 0.60 - 0.97 0.86 0.65 - 1.15 0.84 0.71 - 0.99

Community-level variable

Place of residence

 Ruralref

 Urban 0.77 0.56 - 1.06

Proportion of households poor

 Low

 High 0.98 0.75 - 1.28

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 1.11 0.87 - 1.42

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.09 0.86 - 1.39

Proportion of children fully 

immunizedd 0.57 0.34 - 0.94

Intercept -2.72 -3.20 - -2.24 -3.31 -3.75 - -2.88

AIC/DIC (multilevel model) of 

full models 8,400 7,171 8,308

Cont’d..
24 

Table 4: Cont’d

Ethiopia 

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.62 0.50 - 0.76 0.64 0.52 - 0.79 0.69 0.57 - 0.82

 6–11 months 0.36 0.26 - 0.49 0.38 0.28 - 0.51 0.39 0.31 - 0.49

 12–23 months 0.32 0.23 - 0.44 0.34 0.24 - 0.47 0.36 0.28 - 0.47

 24+ months 0.47 0.34 - 0.65 0.52 0.37 - 0.72 0.60 0.47 - 0.75

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.21 0.86 - 1.71 1.25 0.85 - 1.84 1.09 0.80 - 1.48

 2-3 and 24+ months 0.53 0.39 - 0.72 0.49 0.35 - 0.69 0.58 0.45 - 0.76

 4+ and < 24 months 1.80 1.25 - 2.60 1.72 1.15 - 2.56 1.53 1.14 - 2.06

 4+ and 24+ months 0.67 0.49 - 0.91 0.64 0.45 - 0.91 0.63 0.48 - 0.83

Child's sex

 Femaleref

 Male 1.23 1.03 - 1.47 1.28 1.05 - 1.56 1.34 1.16 - 1.56

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.66 0.49 - 0.88 0.70 0.51 - 0.96 0.66 0.53 - 0.83

 35 years or more 0.74 0.48 - 1.12 0.75 0.48 - 1.18 0.81 0.59 - 1.12

Mother's education

 No educationref

 Primary 0.74 0.55 - 1.00 0.79 0.59 - 1.06 0.78 0.61 - 0.99

 Secondary or higher 0.35 0.20 - 0.63 0.39 0.19 - 0.80 0.56 0.34 - 0.91

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.14 0.88 - 1.48 1.05 0.79 - 1.40 1.12 0.88 - 1.44

 3rd quintile 1.34 1.06 - 1.69 1.26 0.96 - 1.65 1.25 0.97 - 1.61

 4th quintile 1.12 0.88 - 1.42 0.98 0.72 - 1.34 1.11 0.85 - 1.45

 5th quintile (Richest) 0.89 0.65 - 1.23 0.67 0.43 - 1.05 0.70 0.48 - 1.01

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 1.63 1.07 - 2.49 1.96 1.14 - 3.37 0.99 0.69 - 1.42

Community-level variable

Place of residence

 Ruralref

 Urban 1.14 0.77 - 1.68

Proportion of households poor

 Low

 High 0.81 0.66 - 1.00

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.96 0.74 - 1.24

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.04 0.86 - 1.25

Proportion of children fully 

immunizedd 0.60 0.34 - 1.06

Intercept -2.89 -3.22 - -2.57 -3.28 -3.64 - -2.93

AIC/DIC (multilevel model) of 

full models 8,377 6,220 7,704

Cont’d..
25 

Table 4: Cont’d

Gabon

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.46 0.31 - 0.70 0.49 0.33 - 0.73 0.58 0.42 - 0.81

 6–11 months 0.44 0.29 - 0.66 0.47 0.32 - 0.71 0.54 0.38 - 0.77

 12–23 months 0.44 0.28 - 0.68 0.48 0.32 - 0.74 0.54 0.37 - 0.79

 24+ months 0.57 0.34 - 0.96 0.65 0.39 - 1.08 0.67 0.45 - 1.01

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 0.66 0.36 - 1.23 0.53 0.27 - 1.04 0.70 0.39 - 1.26

 2-3 and 24+ months 0.77 0.50 - 1.19 0.72 0.45 - 1.15 0.69 0.45 - 1.04

 4+ and < 24 months 1.29 0.70 - 2.38 1.06 0.49 - 2.32 1.10 0.63 - 1.92

 4+ and 24+ months 0.63 0.36 - 1.07 0.57 0.29 - 1.11 0.54 0.33 - 0.87

Child's sex

 Femaleref

 Male 1.38 1.05 - 1.82 1.48 1.09 - 2.00 1.33 1.02 - 1.74

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.92 0.60 - 1.40 0.96 0.56 - 1.65 1.05 0.70 - 1.59

 35 years or more 1.34 0.72 - 2.51 1.51 0.73 - 3.11 1.38 0.76 - 2.52

Mother's education

 No educationref

 Primary 0.75 0.41 - 1.36 0.83 0.44 - 1.59 0.87 0.52 - 1.45

 Secondary or higher 0.87 0.46 - 1.65 0.84 0.42 - 1.69 0.83 0.48 - 1.42

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.35 0.95 - 1.91 1.05 0.65 - 1.69 1.33 0.91 - 1.93

 3rd quintile 1.10 0.74 - 1.64 1.08 0.56 - 2.07 1.42 0.81 - 2.48

 4th quintile 1.13 0.68 - 1.86 1.09 0.50 - 2.36 1.25 0.68 - 2.32

 5th quintile (Richest) 0.68 0.39 - 1.18 0.76 0.34 - 1.74 0.83 0.40 - 1.72

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.50 0.36 - 0.68 0.47 0.32 - 0.67 0.44 0.32 - 0.61

Community-level variable

Place of residence

 Ruralref

 Urban 1.27 0.84 - 1.91

Proportion of households poor

 Low

 High 1.49 0.92 - 2.41

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 1.36 0.98 - 1.89

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 0.77 0.47 - 1.26

Proportion of children fully 

immunizedd 0.19 0.04 - 0.81

Intercept -2.92 -3.69 - -2.15 -4.00 -4.79 - -3.21

AIC/DIC (multilevel model) of 

full models 2,773 2,115 2,777

Cont’d..
26 

Table 4: Cont’d

Ghana

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.34 0.22 - 0.54 0.38 0.24 - 0.58 0.40 0.27 - 0.61

 6–11 months 0.30 0.18 - 0.48 0.33 0.20 - 0.54 0.30 0.19 - 0.48

 12–23 months 0.33 0.20 - 0.54 0.38 0.24 - 0.63 0.37 0.23 - 0.60

 24+ months 0.27 0.14 - 0.51 0.34 0.18 - 0.64 0.33 0.18 - 0.59

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 0.94 0.43 - 2.07 0.69 0.29 - 1.62 0.59 0.25 - 1.37

 2-3 and 24+ months 0.71 0.44 - 1.16 0.73 0.41 - 1.30 0.71 0.43 - 1.17

 4+ and < 24 months 1.64 0.81 - 3.34 0.93 0.40 - 2.15 1.50 0.73 - 3.08

 4+ and 24+ months 0.70 0.41 - 1.20 0.64 0.32 - 1.29 0.72 0.41 - 1.26

Child's sex

 Femaleref

 Male 1.10 0.78 - 1.55 1.12 0.74 - 1.67 1.11 0.82 - 1.51

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 1.14 0.60 - 2.18 1.17 0.57 - 2.40 1.14 0.66 - 2.00

 35 years or more 1.82 0.80 - 4.12 2.22 0.85 - 5.78 1.77 0.86 - 3.63

Mother's education

 No educationref

 Primary 1.19 0.77 - 1.83 1.35 0.79 - 2.29 1.03 0.67 - 1.61

 Secondary or higher 0.79 0.49 - 1.26 1.03 0.58 - 1.84 0.85 0.51 - 1.42

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.75 0.46 - 1.22 0.62 0.31 - 1.25 0.74 0.44 - 1.25

 3rd quintile 1.17 0.71 - 1.94 0.71 0.26 - 1.90 0.82 0.42 - 1.61

 4th quintile 0.93 0.52 - 1.66 0.65 0.23 - 1.86 0.78 0.37 - 1.61

 5th quintile (Richest) 0.89 0.45 - 1.77 0.66 0.19 - 2.23 0.81 0.33 - 1.95

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 1.06 0.72 - 1.57 0.95 0.58 - 1.57 0.95 0.65 - 1.40

Community-level variable

Place of residence

 Ruralref

 Urban 0.89 0.54 - 1.48

Proportion of households poor

 Low

 High 0.51 0.30 - 0.87

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.64 0.40 - 1.02

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.04 0.73 - 1.49

Proportion of children fully 

immunizedd 0.69 0.30 - 1.56

Intercept -3.50 -4.22 - -2.77 -3.20 -4.02 - -2.38

AIC/DIC (multilevel model) of 

full models 1,784 1,241 1,914

Cont’d..
27 

Table 4: Cont’d

Guinea

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.65 0.52 - 0.82 0.66 0.53 - 0.83 0.60 0.48 - 0.75

 6–11 months 0.58 0.46 - 0.74 0.60 0.47 - 0.76 0.59 0.46 - 0.74

 12–23 months 0.59 0.46 - 0.77 0.63 0.49 - 0.80 0.58 0.46 - 0.74

 24+ months 0.73 0.54 - 0.99 0.77 0.57 - 1.05 0.76 0.59 - 0.98

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.13 0.78 - 1.65 0.95 0.65 - 1.39 1.12 0.72 - 1.74

 2-3 and 24+ months 0.60 0.44 - 0.83 0.56 0.40 - 0.79 0.65 0.48 - 0.89

 4+ and < 24 months 1.10 0.74 - 1.61 0.92 0.61 - 1.38 1.13 0.76 - 1.69

 4+ and 24+ months 0.73 0.54 - 0.98 0.68 0.49 - 0.94 0.76 0.56 - 1.04

Child's sex

 Femaleref

 Male 1.26 1.08 - 1.49 1.24 1.05 - 1.47 1.23 1.05 - 1.44

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 1.02 0.75 - 1.39 1.09 0.79 - 1.50 0.97 0.74 - 1.26

 35 years or more 1.26 0.88 - 1.82 1.39 0.95 - 2.06 1.20 0.86 - 1.68

Mother's education

 No educationref

 Primary 1.01 0.73 - 1.39 1.18 0.84 - 1.66 1.02 0.74 - 1.41

 Secondary or higher 0.64 0.37 - 1.10 0.61 0.33 - 1.14 0.71 0.43 - 1.17

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.82 0.65 - 1.04 0.83 0.64 - 1.09 0.86 0.67 - 1.10

 3rd quintile 0.83 0.65 - 1.06 0.77 0.57 - 1.03 0.87 0.67 - 1.12

 4th quintile 0.94 0.75 - 1.19 1.05 0.76 - 1.45 1.01 0.73 - 1.41

 5th quintile (Richest) 0.61 0.40 - 0.91 1.26 0.67 - 2.35 0.68 0.42 - 1.10

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.96 0.75 - 1.23 0.92 0.69 - 1.21 0.92 0.73 - 1.15

Community-level variable

Place of residence

 Ruralref

 Urban 0.97 0.69 - 1.35

Proportion of households poor

 Low

 High 0.92 0.73 - 1.16

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.96 0.76 - 1.22

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.01 0.84 - 1.21

Proportion of children fully 

immunizedd 0.70 0.42 - 1.18

Intercept -2.98 -3.28 - -2.68 -3.13 -3.50 - -2.75

AIC/DIC (multilevel model) of 

full models 6,306 5,275 6,299

Cont’d..
28 

Table 4: Cont’d

Kenya

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.41 0.28 - 0.59 0.43 0.30 - 0.61 0.48 0.36 - 0.64

 6–11 months 0.27 0.17 - 0.43 0.28 0.18 - 0.46 0.35 0.25 - 0.49

 12–23 months 0.39 0.26 - 0.60 0.43 0.28 - 0.65 0.45 0.33 - 0.63

 24+ months 0.17 0.10 - 0.30 0.19 0.11 - 0.34 0.23 0.14 - 0.39

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.85 1.17 - 2.93 1.78 1.10 - 2.88 1.56 0.98 - 2.50

 2-3 and 24+ months 1.12 0.70 - 1.80 1.16 0.70 - 1.95 1.18 0.80 - 1.74

 4+ and < 24 months 1.68 0.93 - 3.01 1.54 0.79 - 3.00 1.78 1.06 - 2.97

 4+ and 24+ months 1.11 0.65 - 1.90 1.18 0.64 - 2.16 1.41 0.90 - 2.20

Child's sex

 Femaleref

 Male 1.33 1.00 - 1.78 1.44 1.07 - 1.93 1.34 1.06 - 1.69

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.65 0.44 - 0.95 0.69 0.43 - 1.09 0.72 0.50 - 1.04

 35 years or more 1.09 0.57 - 2.08 1.12 0.55 - 2.28 0.95 0.55 - 1.61

Mother's education

 No educationref

 Primary 1.02 0.66 - 1.57 0.70 0.33 - 1.46 1.23 0.83 - 1.82

 Secondary or higher 0.97 0.59 - 1.61 0.77 0.38 - 1.54 1.20 0.74 - 1.94

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.86 0.59 - 1.27 0.75 0.49 - 1.15 1.12 0.75 - 1.68

 3rd quintile 0.96 0.60 - 1.55 0.92 0.54 - 1.58 1.24 0.80 - 1.92

 4th quintile 0.54 0.32 - 0.93 0.69 0.37 - 1.29 0.76 0.45 - 1.28

 5th quintile (Richest) 0.89 0.52 - 1.54 1.51 0.65 - 3.50 1.00 0.55 - 1.82

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 1.17 0.85 - 1.59 1.22 0.87 - 1.70 1.07 0.81 - 1.41

Community-level variable

Place of residence

 Ruralref

 Urban 0.77 0.48 - 1.23

Proportion of households poor

 Low

 High 0.83 0.57 - 1.20

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.94 0.66 - 1.34

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 0.91 0.68 - 1.22

Proportion of children fully 

immunizedd 0.46 0.21 - 1.04

Intercept -3.44 -4.16 - -2.73 -4.23 -4.89 - -3.57

AIC/DIC (multilevel model) of 

full models 4,881 3,520 4,398

Cont’d..
29 

Table 4: Cont’d

Lesotho

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.62 0.46 - 0.84 0.66 0.49 - 0.89 0.66 0.49 - 0.88

 6–11 months 0.45 0.31 - 0.66 0.49 0.34 - 0.72 0.49 0.35 - 0.70

 12–23 months 0.22 0.14 - 0.35 0.25 0.15 - 0.39 0.32 0.21 - 0.49

 24+ months 0.19 0.10 - 0.34 0.22 0.12 - 0.39 0.22 0.13 - 0.38

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 2.12 1.27 - 3.55 1.70 0.91 - 3.18 1.69 0.98 - 2.89

 2-3 and 24+ months 0.82 0.55 - 1.22 0.77 0.50 - 1.19 0.78 0.54 - 1.12

 4+ and < 24 months 1.27 0.55 - 2.92 1.05 0.45 - 2.44 1.00 0.47 - 2.11

 4+ and 24+ months 0.66 0.39 - 1.11 0.61 0.34 - 1.09 0.58 0.37 - 0.90

Child's sex

 Femaleref

 Male 1.02 0.79 - 1.34 1.04 0.78 - 1.39 1.09 0.83 - 1.43

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 1.09 0.76 - 1.55 1.06 0.70 - 1.62 1.19 0.80 - 1.79

 35 years or more 1.55 0.83 - 2.90 1.62 0.82 - 3.17 1.72 0.98 - 3.01

Mother's education

 No educationref

 Primary 0.56 0.32 - 0.98 0.50 0.26 - 0.96 0.56 0.28 - 1.14

 Secondary or higher 0.50 0.27 - 0.92 0.60 0.28 - 1.26 0.53 0.25 - 1.13

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.13 0.77 - 1.65 1.40 0.90 - 2.20 1.17 0.78 - 1.74

 3rd quintile 1.34 0.91 - 1.99 1.89 1.11 - 3.21 1.70 1.03 - 2.80

 4th quintile 1.28 0.84 - 1.95 1.58 0.87 - 2.88 1.79 1.04 - 3.09

 5th quintile (Richest) 1.13 0.73 - 1.75 1.45 0.72 - 2.90 1.74 0.95 - 3.19

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.96 0.70 - 1.32 0.83 0.57 - 1.21 0.84 0.62 - 1.14

Community-level variable

Place of residence

 Ruralref

 Urban 1.22 0.78 - 1.91

Proportion of households poor

 Low

 High 1.42 0.91 - 2.20

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.90 0.64 - 1.27

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous

Proportion of children fully 

immunizedd 1.08 0.57 - 2.06

Intercept -2.73 -3.40 - -2.07 -4.01 -5.09 - -2.93

AIC/DIC (multilevel model) of 

full models 3,065 2,191 2,919

Cont’d..
30 

Table 4: Cont’d

Liberia

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.66 0.47 - 0.93 0.68 0.48 - 0.95 0.68 0.53 - 0.88

 6–11 months 0.49 0.35 - 0.70 0.52 0.36 - 0.74 0.56 0.42 - 0.75

 12–23 months 0.44 0.30 - 0.65 0.47 0.32 - 0.68 0.54 0.40 - 0.73

 24+ months 0.31 0.20 - 0.48 0.33 0.21 - 0.51 0.42 0.29 - 0.60

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.18 0.64 - 2.15 1.10 0.57 - 2.13 1.30 0.87 - 1.95

 2-3 and 24+ months 0.84 0.51 - 1.39 0.87 0.52 - 1.47 0.80 0.59 - 1.10

 4+ and < 24 months 1.70 0.95 - 3.05 1.51 0.82 - 2.75 2.05 1.38 - 3.04

 4+ and 24+ months 0.92 0.54 - 1.58 0.87 0.50 - 1.53 0.92 0.66 - 1.30

Child's sex

 Femaleref

 Male 1.21 0.96 - 1.52 1.27 0.97 - 1.67 1.20 0.98 - 1.47

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.58 0.36 - 0.95 0.55 0.33 - 0.90 0.65 0.47 - 0.89

 35 years or more 0.71 0.40 - 1.27 0.72 0.40 - 1.29 0.66 0.43 - 1.02

Mother's education

 No educationref

 Primary 0.95 0.71 - 1.28 1.09 0.78 - 1.52 0.96 0.76 - 1.23

 Secondary or higher 1.00 0.63 - 1.58 1.13 0.67 - 1.92 0.90 0.62 - 1.29

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.78 0.56 - 1.10 0.63 0.44 - 0.91 0.93 0.67 - 1.28

 3rd quintile 0.84 0.56 - 1.25 0.71 0.43 - 1.18 1.02 0.70 - 1.49

 4th quintile 0.94 0.64 - 1.38 0.81 0.47 - 1.38 0.96 0.62 - 1.49

 5th quintile (Richest) 0.79 0.48 - 1.30 0.69 0.36 - 1.30 0.91 0.54 - 1.54

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.99 0.72 - 1.35 1.00 0.66 - 1.50 0.91 0.73 - 1.15

Community-level variable

Place of residence

 Ruralref

 Urban 1.24 0.91 - 1.68

Proportion of households poor

 Low

 High 0.88 0.65 - 1.19

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.91 0.68 - 1.23

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 0.83 0.62 - 1.11

Proportion of children fully 

immunizedd 0.78 0.40 - 1.50

Intercept -2.99 -3.43 - -2.56 -3.60 -4.11 - -3.09

AIC/DIC (multilevel model) of 

full models 4,352 3,500 4,411

Cont’d..
31 

Table 4: Cont’d

Madagascar

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.47 0.36 - 0.60 0.48 0.37 - 0.62 0.51 0.41 - 0.63

 6–11 months 0.49 0.38 - 0.62 0.51 0.40 - 0.65 0.54 0.44 - 0.68

 12–23 months 0.24 0.17 - 0.34 0.25 0.18 - 0.36 0.30 0.22 - 0.41

 24+ months 0.44 0.31 - 0.63 0.47 0.33 - 0.67 0.45 0.34 - 0.60

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.06 0.77 - 1.47 0.98 0.70 - 1.39 0.85 0.61 - 1.20

 2-3 and 24+ months 0.80 0.59 - 1.08 0.80 0.58 - 1.10 0.70 0.53 - 0.91

 4+ and < 24 months 1.42 0.98 - 2.05 1.33 0.88 - 1.99 1.18 0.86 - 1.63

 4+ and 24+ months 0.85 0.60 - 1.21 0.83 0.57 - 1.20 0.76 0.57 - 1.01

Child's sex

 Femaleref

 Male 1.08 0.88 - 1.33 1.12 0.89 - 1.41 1.19 1.02 - 1.40

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.94 0.69 - 1.27 0.94 0.68 - 1.31 0.89 0.69 - 1.15

 35 years or more 1.54 1.02 - 2.31 1.61 1.05 - 2.47 1.38 0.98 - 1.95

Mother's education

 No educationref

 Primary 1.05 0.83 - 1.34 0.97 0.74 - 1.26 1.09 0.88 - 1.35

 Secondary or higher 1.05 0.67 - 1.63 0.92 0.59 - 1.43 0.97 0.69 - 1.36

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.96 0.74 - 1.25 1.02 0.75 - 1.37 1.09 0.86 - 1.38

 3rd quintile 0.86 0.63 - 1.16 0.89 0.61 - 1.30 0.99 0.74 - 1.34

 4th quintile 0.81 0.59 - 1.12 0.99 0.68 - 1.43 1.11 0.80 - 1.54

 5th quintile (Richest) 0.82 0.52 - 1.30 1.37 0.70 - 2.67 1.14 0.72 - 1.81

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.87 0.70 - 1.08 0.90 0.70 - 1.17 0.85 0.70 - 1.04

Community-level variable

Place of residence

 Ruralref

 Urban 0.95 0.68 - 1.33

Proportion of households poor

 Low

 High 1.21 0.95 - 1.54

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.88 0.70 - 1.11

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous

Proportion of children fully 

immunizedd 1.12 0.72 - 1.76

Intercept -3.65 -3.99 - -3.31 -4.43 -4.82 - -4.05

AIC/DIC (multilevel model) of 

full models 3,525 2,353 3,094

Cont’d..
32 

Table 4: Cont’d

Malawi

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.87 0.71 - 1.06 0.89 0.73 - 1.09 0.81 0.68 - 0.97

 6–11 months 0.92 0.76 - 1.11 0.96 0.80 - 1.16 0.95 0.79 - 1.13

 12–23 months 0.76 0.60 - 0.96 0.81 0.64 - 1.02 0.75 0.61 - 0.91

 24+ months 0.66 0.50 - 0.88 0.71 0.54 - 0.95 0.63 0.48 - 0.81

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.19 0.87 - 1.62 0.98 0.70 - 1.36 0.97 0.73 - 1.31

 2-3 and 24+ months 0.70 0.56 - 0.87 0.62 0.48 - 0.79 0.68 0.55 - 0.83

 4+ and < 24 months 1.57 1.15 - 2.16 1.23 0.87 - 1.72 1.31 0.97 - 1.78

 4+ and 24+ months 0.63 0.48 - 0.83 0.55 0.41 - 0.74 0.60 0.48 - 0.75

Child's sex

 Femaleref

 Male 1.24 1.08 - 1.44 1.24 1.06 - 1.45 1.30 1.14 - 1.48

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.92 0.74 - 1.13 0.97 0.77 - 1.22 0.87 0.71 - 1.06

 35 years or more 0.92 0.67 - 1.28 1.03 0.74 - 1.45 0.88 0.65 - 1.18

Mother's education

 No educationref

 Primary 0.85 0.72 - 1.00 0.79 0.65 - 0.95 0.88 0.76 - 1.03

 Secondary or higher 0.59 0.40 - 0.88 0.56 0.37 - 0.85 0.62 0.45 - 0.84

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.04 0.83 - 1.30 0.99 0.77 - 1.28 0.99 0.80 - 1.21

 3rd quintile 1.01 0.82 - 1.25 1.02 0.81 - 1.28 0.97 0.79 - 1.20

 4th quintile 0.90 0.71 - 1.14 0.86 0.66 - 1.12 0.90 0.72 - 1.14

 5th quintile (Richest) 0.80 0.56 - 1.15 0.93 0.65 - 1.34 0.89 0.65 - 1.20

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.83 0.70 - 0.97 0.78 0.65 - 0.93 0.84 0.72 - 0.96

Community-level variable

Place of residence

 Ruralref

 Urban 0.70 0.51 - 0.97

Proportion of households poor

 Low

 High 0.96 0.81 - 1.13

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 1.01 0.85 - 1.19

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 0.93 0.75 - 1.14

Proportion of children fully 

immunizedd 1.06 0.66 - 1.71

Intercept -3.18 -3.49 - -2.88 -3.41 -3.76 - -3.06

AIC/DIC (multilevel model) of 

full models 9,324 7,925 9,677

Cont’d..
33 

Table 4: Cont’d

Mali

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.53 0.44 - 0.64 0.54 0.44 - 0.65 0.52 0.45 - 0.60

 6–11 months 0.58 0.48 - 0.70 0.59 0.49 - 0.71 0.59 0.51 - 0.68

 12–23 months 0.72 0.59 - 0.88 0.74 0.60 - 0.91 0.75 0.65 - 0.87

 24+ months 0.95 0.79 - 1.14 0.98 0.81 - 1.18 1.01 0.86 - 1.18

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 0.96 0.76 - 1.22 0.94 0.74 - 1.21 0.88 0.70 - 1.10

 2-3 and 24+ months 0.66 0.54 - 0.81 0.67 0.54 - 0.82 0.65 0.53 - 0.78

 4+ and < 24 months 1.22 0.97 - 1.53 1.15 0.91 - 1.46 1.14 0.91 - 1.42

 4+ and 24+ months 0.71 0.55 - 0.90 0.69 0.53 - 0.89 0.66 0.54 - 0.81

Child's sex

 Femaleref

 Male 1.02 0.91 - 1.15 1.02 0.90 - 1.15 1.09 0.98 - 1.21

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.85 0.70 - 1.03 0.83 0.67 - 1.03 0.87 0.73 - 1.03

 35 years or more 0.80 0.61 - 1.07 0.79 0.58 - 1.07 0.88 0.70 - 1.11

Mother's education

 No educationref

 Primary 0.91 0.74 - 1.13 0.95 0.76 - 1.18 0.95 0.78 - 1.16

 Secondary or higher 0.54 0.34 - 0.86 0.57 0.34 - 0.94 0.52 0.35 - 0.75

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.03 0.87 - 1.21 1.06 0.88 - 1.26 0.99 0.83 - 1.17

 3rd quintile 0.89 0.74 - 1.06 0.89 0.73 - 1.08 0.82 0.69 - 0.98

 4th quintile 0.93 0.78 - 1.11 0.98 0.82 - 1.17 0.89 0.73 - 1.07

 5th quintile (Richest) 0.65 0.51 - 0.84 0.96 0.69 - 1.32 0.73 0.55 - 0.96

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.86 0.69 - 1.07 0.96 0.77 - 1.19 0.83 0.70 - 0.98

Community-level variable

Place of residence

 Ruralref

 Urban 0.92 0.74 - 1.14

Proportion of households poor

 Low

 High 1.16 0.99 - 1.37

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.93 0.79 - 1.11

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 0.75 0.61 - 0.92

Proportion of children fully 

immunizedd 1.38 0.97 - 1.98

Intercept -2.63 -2.86 - -2.40 -3.20 -3.46 - -2.93

AIC/DIC (multilevel model) of 

full models 15,774 13,388 14,837

Cont’d..
34 

Table 4: Cont’d

Mozambique

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 1.00 0.82 - 1.22 1.03 0.84 - 1.25 1.04 0.88 - 1.23

 6–11 months 0.73 0.58 - 0.91 0.77 0.61 - 0.96 0.86 0.72 - 1.03

 12–23 months 0.50 0.40 - 0.64 0.55 0.43 - 0.69 0.67 0.55 - 0.83

 24+ months 0.52 0.38 - 0.69 0.58 0.43 - 0.78 0.60 0.47 - 0.76

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.06 0.79 - 1.44 0.87 0.62 - 1.21 1.01 0.79 - 1.31

 2-3 and 24+ months 0.59 0.47 - 0.75 0.55 0.43 - 0.71 0.59 0.48 - 0.71

 4+ and < 24 months 1.40 1.05 - 1.88 1.31 0.94 - 1.82 1.23 0.92 - 1.64

 4+ and 24+ months 0.61 0.47 - 0.79 0.57 0.43 - 0.76 0.56 0.44 - 0.71

Child's sex

 Femaleref

 Male 1.05 0.91 - 1.20 1.04 0.89 - 1.21 1.08 0.95 - 1.23

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.79 0.66 - 0.96 0.88 0.71 - 1.08 0.81 0.66 - 0.99

 35 years or more 0.70 0.50 - 0.99 0.71 0.50 - 1.01 0.72 0.54 - 0.96

Mother's education

 No educationref

 Primary 0.86 0.72 - 1.04 0.87 0.70 - 1.07 0.90 0.77 - 1.05

 Secondary or higher 0.68 0.41 - 1.13 0.82 0.46 - 1.48 0.86 0.58 - 1.27

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.18 0.94 - 1.48 1.01 0.78 - 1.31 1.09 0.89 - 1.34

 3rd quintile 1.11 0.90 - 1.36 0.83 0.63 - 1.08 0.99 0.80 - 1.24

 4th quintile 0.94 0.73 - 1.22 0.70 0.50 - 0.98 0.92 0.71 - 1.19

 5th quintile (Richest) 0.85 0.62 - 1.16 0.68 0.42 - 1.11 0.60 0.43 - 0.83

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.93 0.73 - 1.17 1.04 0.80 - 1.37 0.94 0.79 - 1.13

Community-level variable

Place of residence

 Ruralref

 Urban 1.15 0.93 - 1.42

Proportion of households poor

 Low

 High 0.83 0.66 - 1.04

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 1.03 0.83 - 1.28

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.28 1.10 - 1.49

Proportion of children fully 

immunizedd 0.75 0.50 - 1.13

Intercept -2.82 -3.11 - -2.54 -3.14 -3.50 - -2.79

AIC/DIC (multilevel model) of 

full models 10,323 8,379 7,704

Cont’d..
35 

Table 4: Cont’d

Namibia

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.49 0.34 - 0.69 0.52 0.37 - 0.72 0.59 0.43 - 0.81

 6–11 months 0.45 0.31 - 0.67 0.48 0.33 - 0.71 0.54 0.38 - 0.77

 12–23 months 0.49 0.33 - 0.72 0.53 0.36 - 0.78 0.59 0.42 - 0.84

 24+ months 0.35 0.21 - 0.59 0.39 0.23 - 0.65 0.47 0.30 - 0.73

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.75 0.86 - 3.55 1.35 0.61 - 3.01 1.35 0.78 - 2.35

 2-3 and 24+ months 1.35 0.91 - 2.01 1.40 0.92 - 2.12 1.08 0.78 - 1.51

 4+ and < 24 months 2.05 0.93 - 4.50 1.79 0.86 - 3.71 1.44 0.76 - 2.75

 4+ and 24+ months 1.84 1.12 - 3.02 1.67 1.04 - 2.68 1.36 0.89 - 2.07

Child's sex

 Femaleref

 Male 1.34 1.03 - 1.75 1.36 1.02 - 1.82 1.26 1.00 - 1.61

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.71 0.42 - 1.22 0.69 0.40 - 1.20 0.77 0.53 - 1.12

 35 years or more 0.74 0.39 - 1.40 0.80 0.43 - 1.50 0.98 0.58 - 1.64

Mother's education

 No educationref

 Primary 1.59 0.93 - 2.71 1.20 0.64 - 2.26 1.59 1.01 - 2.52

 Secondary or higher 1.53 0.85 - 2.75 1.12 0.55 - 2.29 1.45 0.87 - 2.40

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.89 0.59 - 1.32 0.89 0.53 - 1.49 0.92 0.63 - 1.36

 3rd quintile 1.01 0.67 - 1.52 1.03 0.58 - 1.83 1.03 0.68 - 1.54

 4th quintile 0.77 0.48 - 1.24 0.70 0.33 - 1.47 0.69 0.41 - 1.15

 5th quintile (Richest) 0.52 0.28 - 0.97 0.45 0.17 - 1.15 0.58 0.31 - 1.07

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.89 0.61 - 1.28 0.72 0.47 - 1.11 0.76 0.54 - 1.05

Community-level variable

Place of residence

 Ruralref

 Urban 1.37 0.95 - 1.96

Proportion of households poor

 Low

 High 1.04 0.73 - 1.49

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 1.12 0.82 - 1.54

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.15 0.86 - 1.54

Proportion of children fully 

immunizedd 1.31 0.67 - 2.54

Intercept -4.11 -4.81 - -3.42 -4.70 -5.43 - -3.97

AIC/DIC (multilevel model) of 

full models 2,964 2,148 3,113

Cont’d..
36 

Table 4: Cont’d

Niger

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.61 0.46 - 0.81 0.62 0.46 - 0.82 0.64 0.52 - 0.77

 6–11 months 0.75 0.58 - 0.99 0.77 0.59 - 1.01 0.74 0.61 - 0.90

 12–23 months 1.19 0.96 - 1.47 1.24 1.00 - 1.53 1.17 0.97 - 1.40

 24+ months 1.26 1.00 - 1.58 1.33 1.06 - 1.68 1.37 1.12 - 1.68

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.14 0.82 - 1.59 1.05 0.75 - 1.46 1.02 0.76 - 1.37

 2-3 and 24+ months 0.81 0.62 - 1.06 0.77 0.59 - 1.00 0.79 0.63 - 1.01

 4+ and < 24 months 1.74 1.20 - 2.52 1.60 1.13 - 2.26 1.48 1.12 - 1.95

 4+ and 24+ months 0.99 0.68 - 1.43 0.96 0.69 - 1.34 0.87 0.67 - 1.12

Child's sex

 Femaleref

 Male 1.02 0.90 - 1.16 1.00 0.88 - 1.14 1.13 0.98 - 1.29

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.68 0.48 - 0.96 0.72 0.53 - 0.97 0.69 0.55 - 0.87

 35 years or more 0.67 0.44 - 1.02 0.73 0.49 - 1.07 0.72 0.52 - 0.98

Mother's education

 No educationref

 Primary 1.00 0.78 - 1.29 0.94 0.70 - 1.27 1.08 0.85 - 1.38

 Secondary or higher 0.69 0.33 - 1.43 0.79 0.40 - 1.55 0.67 0.42 - 1.06

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.98 0.77 - 1.26 0.94 0.72 - 1.24 1.10 0.87 - 1.39

 3rd quintile 0.97 0.76 - 1.24 0.97 0.74 - 1.27 1.09 0.86 - 1.38

 4th quintile 1.12 0.90 - 1.41 1.04 0.79 - 1.36 1.22 0.97 - 1.55

 5th quintile (Richest) 0.81 0.58 - 1.11 1.00 0.68 - 1.47 0.92 0.66 - 1.29

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.78 0.62 - 0.99 0.94 0.74 - 1.19 0.89 0.70 - 1.14

Community-level variable

Place of residence

 Ruralref

 Urban 0.76 0.55 - 1.06

Proportion of households poor

 Low

 High 1.05 0.86 - 1.28

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.89 0.70 - 1.14

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 0.80 0.67 - 0.97

Proportion of children fully 

immunizedd 1.00 0.59 - 1.67

Intercept -3.09 -3.37 - -2.80 -3.42 -3.74 - -3.11

AIC/DIC (multilevel model) of 

full models 9,762 7,339 8,596

Cont’d..
37 

Table 4: Cont’d

Nigeria

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.43 0.38 - 0.49 0.44 0.39 - 0.50 0.46 0.41 - 0.51

 6–11 months 0.44 0.39 - 0.50 0.45 0.40 - 0.51 0.50 0.44 - 0.56

 12–23 months 0.81 0.71 - 0.91 0.84 0.74 - 0.95 0.92 0.83 - 1.02

 24+ months 0.82 0.72 - 0.94 0.87 0.76 - 0.99 0.99 0.89 - 1.11

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.60 1.37 - 1.87 1.52 1.29 - 1.79 1.37 1.17 - 1.60

 2-3 and 24+ months 0.84 0.73 - 0.98 0.85 0.73 - 0.99 0.76 0.67 - 0.87

 4+ and < 24 months 1.99 1.71 - 2.33 1.84 1.55 - 2.18 1.67 1.43 - 1.94

 4+ and 24+ months 1.04 0.90 - 1.21 0.99 0.84 - 1.15 0.92 0.80 - 1.06

Child's sex

 Femaleref

 Male 1.12 1.04 - 1.22 1.14 1.05 - 1.24 1.18 1.09 - 1.28

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.71 0.62 - 0.81 0.76 0.67 - 0.87 0.77 0.68 - 0.87

 35 years or more 0.83 0.70 - 0.99 0.89 0.74 - 1.07 0.89 0.75 - 1.05

Mother's education

 No educationref

 Primary 0.94 0.84 - 1.05 1.04 0.90 - 1.19 0.99 0.87 - 1.12

 Secondary or higher 0.84 0.73 - 0.97 0.90 0.75 - 1.08 0.85 0.72 - 1.01

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.92 0.82 - 1.03 0.87 0.76 - 0.99 0.97 0.87 - 1.08

 3rd quintile 0.88 0.77 - 1.01 0.93 0.78 - 1.10 1.03 0.90 - 1.19

 4th quintile 0.74 0.64 - 0.85 0.88 0.72 - 1.07 0.94 0.78 - 1.12

 5th quintile (Richest) 0.52 0.41 - 0.65 0.73 0.54 - 0.98 0.73 0.59 - 0.91

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 1.05 0.94 - 1.18 1.24 1.09 - 1.42 1.10 0.97 - 1.24

Community-level variable

Place of residence

 Ruralref

 Urban 0.85 0.74 - 0.98

Proportion of households poor

 Low

 High 1.17 1.02 - 1.33

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.87 0.75 - 1.00

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.11 1.00 - 1.23

Proportion of children fully 

immunizedd 0.93 0.65 - 1.33

Intercept -2.94 -3.08 - -2.79 -3.62 -3.81 - -3.42

AIC/DIC (multilevel model) of 

full models 26,983 23,628 26,471

Cont’d..
38 

Table 4: Cont’d

Rwanda

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.65 0.53 - 0.80 0.67 0.54 - 0.81 0.62 0.51 - 0.75

 6–11 months 0.67 0.53 - 0.84 0.70 0.55 - 0.88 0.66 0.54 - 0.80

 12–23 months 0.62 0.49 - 0.79 0.66 0.52 - 0.85 0.63 0.51 - 0.78

 24+ months 0.60 0.47 - 0.76 0.66 0.52 - 0.84 0.63 0.49 - 0.81

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.01 0.76 - 1.34 0.98 0.72 - 1.33 1.00 0.77 - 1.31

 2-3 and 24+ months 0.72 0.57 - 0.91 0.74 0.57 - 0.95 0.75 0.59 - 0.94

 4+ and < 24 months 1.18 0.88 - 1.58 1.13 0.83 - 1.52 1.19 0.91 - 1.56

 4+ and 24+ months 0.58 0.45 - 0.75 0.59 0.44 - 0.77 0.63 0.50 - 0.80

Child's sex

 Femaleref

 Male 1.01 0.88 - 1.16 0.99 0.85 - 1.15 1.03 0.89 - 1.18

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.75 0.57 - 1.00 0.74 0.55 - 1.00 0.66 0.50 - 0.87

 35 years or more 0.83 0.59 - 1.17 0.84 0.58 - 1.21 0.72 0.51 - 1.01

Mother's education

 No educationref

 Primary 0.88 0.74 - 1.03 0.89 0.75 - 1.06 0.89 0.75 - 1.04

 Secondary or higher 0.62 0.42 - 0.91 0.62 0.41 - 0.94 0.61 0.41 - 0.88

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.83 0.67 - 1.01 0.82 0.66 - 1.01 0.83 0.67 - 1.03

 3rd quintile 0.71 0.57 - 0.89 0.74 0.58 - 0.95 0.73 0.57 - 0.94

 4th quintile 1.02 0.82 - 1.26 1.03 0.81 - 1.29 1.08 0.87 - 1.35

 5th quintile (Richest) 0.62 0.46 - 0.83 0.74 0.53 - 1.04 0.70 0.52 - 0.94

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.79 0.65 - 0.96 0.89 0.71 - 1.10 0.89 0.74 - 1.08

Community-level variable

Place of residence

 Ruralref

 Urban 0.70 0.54 - 0.91

Proportion of households poor

 Low

 High 1.08 0.89 - 1.32

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.99 0.83 - 1.17

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous

Proportion of children fully 

immunizedd 0.49 0.29 - 0.83

Intercept -2.49 -2.82 - -2.17 -2.32 -2.80 - -1.83

AIC/DIC (multilevel model) of 

full models 8,156 6,432 7,988

Cont’d..
39 

Table 4: Cont’d

Senegal

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.35 0.27 - 0.44 0.36 0.28 - 0.45 0.49 0.41 - 0.58

 6–11 months 0.36 0.28 - 0.46 0.38 0.29 - 0.48 0.67 0.57 - 0.78

 12–23 months 0.36 0.27 - 0.46 0.37 0.29 - 0.48 0.62 0.53 - 0.73

 24+ months 0.75 0.57 - 0.98 0.79 0.60 - 1.04 0.74 0.62 - 0.88

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 0.79 0.58 - 1.09 0.69 0.49 - 0.97 1.25 0.98 - 1.59

 2-3 and 24+ months 0.63 0.47 - 0.84 0.65 0.48 - 0.88 0.71 0.60 - 0.84

 4+ and < 24 months 0.97 0.71 - 1.32 0.83 0.59 - 1.18 1.28 1.01 - 1.60

 4+ and 24+ months 0.64 0.49 - 0.84 0.61 0.45 - 0.82 0.83 0.69 - 0.99

Child's sex

 Femaleref

 Male 1.24 1.07 - 1.43 1.28 1.10 - 1.49 1.10 0.99 - 1.22

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.78 0.61 - 1.00 0.86 0.64 - 1.16 0.96 0.79 - 1.16

 35 years or more 1.13 0.81 - 1.57 1.29 0.87 - 1.91 0.93 0.71 - 1.21

Mother's education

 No educationref

 Primary 0.63 0.47 - 0.83 0.60 0.43 - 0.82 1.07 0.91 - 1.27

 Secondary or higher 0.92 0.53 - 1.60 0.84 0.45 - 1.56 0.69 0.50 - 0.95

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.98 0.79 - 1.21 0.96 0.76 - 1.22 1.04 0.88 - 1.23

 3rd quintile 0.82 0.60 - 1.13 0.82 0.58 - 1.15 1.08 0.91 - 1.29

 4th quintile 0.68 0.49 - 0.94 0.57 0.36 - 0.91 0.93 0.76 - 1.15

 5th quintile (Richest) 0.47 0.31 - 0.71 0.35 0.18 - 0.67 0.73 0.55 - 0.96

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.99 0.79 - 1.23 1.04 0.82 - 1.32 0.92 0.80 - 1.06

Community-level variable

Place of residence

 Ruralref

 Urban 0.90 0.77 - 1.05

Proportion of households poor

 Low

 High 0.89 0.76 - 1.05

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.99 0.84 - 1.16

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.04 0.90 - 1.21

Proportion of children fully 

immunizedd 0.63 0.44 - 0.91

Intercept -2.78 -3.03 - -2.53 -3.33 -3.64 - -3.02

AIC/DIC (multilevel model) of 

full models 7,895 6,501 7,773

Cont’d..
40 

Table 4: Cont’d

Sierra Leone

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.64 0.48 - 0.85 0.66 0.50 - 0.88 0.66 0.52 - 0.84

 6–11 months 0.67 0.50 - 0.89 0.71 0.54 - 0.95 0.72 0.56 - 0.92

 12–23 months 0.48 0.35 - 0.66 0.52 0.38 - 0.72 0.56 0.42 - 0.76

 24+ months 0.48 0.32 - 0.73 0.54 0.36 - 0.82 0.51 0.35 - 0.73

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.22 0.80 - 1.86 1.21 0.76 - 1.93 1.17 0.82 - 1.68

 2-3 and 24+ months 0.58 0.42 - 0.80 0.58 0.41 - 0.80 0.58 0.43 - 0.78

 4+ and < 24 months 1.56 1.02 - 2.38 1.49 0.94 - 2.37 1.67 1.18 - 2.38

 4+ and 24+ months 0.78 0.55 - 1.12 0.70 0.48 - 1.01 0.77 0.57 - 1.04

Child's sex

 Femaleref

 Male 0.88 0.72 - 1.08 0.86 0.70 - 1.06 0.84 0.70 - 1.00

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.85 0.61 - 1.18 0.93 0.66 - 1.31 0.77 0.58 - 1.02

 35 years or more 1.01 0.64 - 1.60 1.16 0.73 - 1.85 0.94 0.64 - 1.38

Mother's education

 No educationref

 Primary 1.16 0.81 - 1.66 1.14 0.76 - 1.71 1.14 0.86 - 1.50

 Secondary or higher 1.11 0.76 - 1.64 1.10 0.71 - 1.70 1.01 0.73 - 1.40

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.57 0.39 - 0.82 0.55 0.37 - 0.81 0.63 0.46 - 0.87

 3rd quintile 0.76 0.55 - 1.05 0.74 0.49 - 1.11 0.86 0.63 - 1.18

 4th quintile 0.70 0.48 - 1.00 0.58 0.33 - 1.00 0.70 0.48 - 1.03

 5th quintile (Richest) 0.87 0.59 - 1.28 0.65 0.34 - 1.25 0.80 0.52 - 1.23

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.81 0.64 - 1.01 0.85 0.65 - 1.11 0.89 0.70 - 1.12

Community-level variable

Place of residence

 Ruralref

 Urban 1.73 1.22 - 2.46

Proportion of households poor

 Low

 High 1.00 0.70 - 1.42

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.73 0.55 - 0.98

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 0.86 0.66 - 1.13

Proportion of children fully 

immunizedd 1.12 0.60 - 2.08

Intercept -2.71 -3.07 - -2.36 -3.14 -3.75 - -2.53

AIC/DIC (multilevel model) of 

full models 4,803 3,816 4,844

Cont’d..
41 

Table 4: Cont’d

Swaziland

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 1.89 1.34 - 2.66 1.94 1.39 - 2.72 1.96 1.44 - 2.69

 6–11 months 0.95 0.65 - 1.40 1.04 0.71 - 1.52 1.04 0.72 - 1.52

 12–23 months 0.75 0.45 - 1.23 0.84 0.51 - 1.38 0.70 0.44 - 1.10

 24+ months 0.56 0.30 - 1.03 0.65 0.35 - 1.18 0.67 0.40 - 1.14

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 0.92 0.47 - 1.81 0.82 0.45 - 1.51 0.79 0.42 - 1.49

 2-3 and 24+ months 0.78 0.52 - 1.16 0.77 0.50 - 1.19 0.78 0.53 - 1.14

 4+ and < 24 months 1.33 0.79 - 2.26 1.24 0.67 - 2.33 1.34 0.73 - 2.48

 4+ and 24+ months 0.83 0.50 - 1.36 0.75 0.44 - 1.28 0.77 0.49 - 1.20

Child's sex

 Femaleref

 Male 1.00 0.78 - 1.28 1.00 0.75 - 1.35 1.01 0.78 - 1.30

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 1.13 0.76 - 1.69 1.14 0.73 - 1.76 1.17 0.80 - 1.71

 35 years or more 0.86 0.46 - 1.60 0.93 0.47 - 1.83 0.77 0.40 - 1.47

Mother's education

 No educationref

 Primary 0.90 0.54 - 1.50 0.99 0.60 - 1.63 0.98 0.62 - 1.56

 Secondary or higher 0.73 0.44 - 1.23 0.92 0.56 - 1.52 0.76 0.46 - 1.25

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.85 0.54 - 1.34 1.01 0.61 - 1.68 0.77 0.48 - 1.23

 3rd quintile 1.07 0.70 - 1.62 0.96 0.59 - 1.55 0.89 0.54 - 1.44

 4th quintile 1.28 0.78 - 2.09 0.95 0.56 - 1.64 0.91 0.54 - 1.52

 5th quintile (Richest) 1.19 0.76 - 1.86 0.81 0.46 - 1.45 0.81 0.45 - 1.45

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 1.00 0.75 - 1.33 1.05 0.77 - 1.42 0.92 0.68 - 1.26

Community-level variable

Place of residence

 Ruralref

 Urban 1.27 0.84 - 1.91

Proportion of households poor

 Low

 High 0.80 0.55 - 1.18

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.87 0.63 - 1.20

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous

Proportion of children fully 

immunizedd 0.65 0.28 - 1.48

Intercept -3.63 -4.23 - -3.02 -3.61 -4.26 - -2.96

AIC/DIC (multilevel model) of 

full models 2,527 1,834 2,520

Cont’d..
42 

Table 4: Cont’d

Tanzania

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.57 0.45 - 0.72 0.59 0.46 - 0.74 0.56 0.46 - 0.70

 6–11 months 0.52 0.40 - 0.69 0.55 0.42 - 0.72 0.54 0.44 - 0.67

 12–23 months 0.52 0.38 - 0.72 0.56 0.41 - 0.76 0.57 0.45 - 0.72

 24+ months 0.59 0.43 - 0.81 0.64 0.46 - 0.88 0.60 0.46 - 0.78

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 0.94 0.62 - 1.43 0.88 0.55 - 1.38 0.86 0.59 - 1.23

 2-3 and 24+ months 0.96 0.72 - 1.28 0.99 0.73 - 1.33 0.90 0.68 - 1.20

 4+ and < 24 months 1.56 1.08 - 2.27 1.43 0.97 - 2.12 1.40 0.97 - 2.03

 4+ and 24+ months 0.79 0.56 - 1.12 0.82 0.57 - 1.19 0.78 0.56 - 1.08

Child's sex

 Femaleref

 Male 1.09 0.91 - 1.31 1.11 0.91 - 1.36 1.17 0.98 - 1.38

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.83 0.61 - 1.14 0.79 0.57 - 1.10 0.74 0.56 - 0.98

 35 years or more 0.96 0.62 - 1.49 0.83 0.54 - 1.28 0.81 0.55 - 1.21

Mother's education

 No educationref

 Primary 0.84 0.68 - 1.03 0.78 0.60 - 1.00 0.91 0.75 - 1.10

 Secondary or higher 0.69 0.37 - 1.27 0.70 0.35 - 1.40 0.58 0.38 - 0.88

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.36 1.07 - 1.74 1.26 0.96 - 1.67 1.22 0.95 - 1.55

 3rd quintile 1.26 0.97 - 1.64 1.24 0.91 - 1.67 1.13 0.87 - 1.48

 4th quintile 0.93 0.69 - 1.26 0.96 0.67 - 1.36 0.93 0.69 - 1.25

 5th quintile (Richest) 0.95 0.66 - 1.37 0.99 0.51 - 1.91 0.79 0.53 - 1.18

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 1.05 0.85 - 1.31 1.03 0.77 - 1.37 1.02 0.84 - 1.23

Community-level variable

Place of residence

 Ruralref

 Urban 1.05 0.77 - 1.43

Proportion of households poor

 Low

 High 0.99 0.77 - 1.27

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.98 0.78 - 1.24

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous

Proportion of children fully 

immunizedd 0.63 0.37 - 1.07

Intercept -3.29 -3.60 - -2.97 -3.35 -3.85 - -2.84

AIC/DIC (multilevel model) of 

full models 6,984 5,318 6,710

Cont’d..
43 

Table 4: Cont’d

Uganda

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.75 0.59 - 0.95 0.76 0.60 - 0.97 0.80 0.65 - 0.98

 6–11 months 0.82 0.64 - 1.04 0.84 0.66 - 1.07 0.94 0.77 - 1.15

 12–23 months 0.93 0.73 - 1.18 0.98 0.77 - 1.24 1.00 0.80 - 1.24

 24+ months 0.51 0.37 - 0.70 0.54 0.40 - 0.74 0.51 0.38 - 0.69

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.09 0.77 - 1.54 1.03 0.71 - 1.51 1.17 0.86 - 1.59

 2-3 and 24+ months 0.80 0.59 - 1.09 0.79 0.56 - 1.09 0.76 0.57 - 1.01

 4+ and < 24 months 1.20 0.86 - 1.68 1.13 0.78 - 1.63 1.09 0.81 - 1.48

 4+ and 24+ months 0.74 0.55 - 0.99 0.72 0.53 - 0.98 0.71 0.54 - 0.95

Child's sex

 Femaleref

 Male 1.25 1.07 - 1.47 1.27 1.07 - 1.49 1.31 1.13 - 1.52

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.87 0.67 - 1.15 0.93 0.69 - 1.26 0.96 0.74 - 1.24

 35 years or more 1.13 0.79 - 1.61 1.19 0.81 - 1.74 1.23 0.87 - 1.75

Mother's education

 No educationref

 Primary 0.90 0.71 - 1.14 0.97 0.76 - 1.24 0.98 0.81 - 1.19

 Secondary or higher 0.70 0.47 - 1.04 0.77 0.50 - 1.19 0.68 0.49 - 0.95

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 0.97 0.77 - 1.23 0.99 0.74 - 1.32 0.88 0.71 - 1.10

 3rd quintile 0.86 0.67 - 1.12 0.88 0.63 - 1.24 0.78 0.59 - 1.02

 4th quintile 0.98 0.75 - 1.28 1.01 0.69 - 1.48 0.86 0.66 - 1.13

 5th quintile (Richest) 0.87 0.62 - 1.21 0.86 0.55 - 1.34 0.77 0.53 - 1.11

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.90 0.76 - 1.08 0.92 0.76 - 1.12 0.94 0.79 - 1.11

Community-level variable

Place of residence

 Ruralref

 Urban 1.05 0.77 - 1.44

Proportion of households poor

 Low

 High 0.95 0.76 - 1.18

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.90 0.75 - 1.08

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous

Proportion of children fully 

immunizedd 0.45 0.21 - 0.99

Intercept -3.32 -3.72 - -2.92 -3.49 -3.93 - -3.05

AIC/DIC (multilevel model) of 

full models 7,109 6,009 7,271

Cont’d..
44 

Table 4: Cont’d

Zambia

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 0.49 0.37 - 0.66 0.50 0.38 - 0.68 0.58 0.45 - 0.75

 6–11 months 0.52 0.39 - 0.69 0.53 0.40 - 0.71 0.62 0.47 - 0.80

 12–23 months 0.51 0.38 - 0.69 0.53 0.40 - 0.71 0.65 0.50 - 0.86

 24+ months 0.60 0.44 - 0.83 0.63 0.46 - 0.88 0.65 0.47 - 0.89

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 1.40 0.91 - 2.15 1.20 0.75 - 1.93 1.01 0.66 - 1.54

 2-3 and 24+ months 0.74 0.54 - 1.00 0.68 0.49 - 0.94 0.69 0.50 - 0.93

 4+ and < 24 months 1.17 0.74 - 1.84 0.95 0.61 - 1.48 0.79 0.50 - 1.23

 4+ and 24+ months 0.63 0.43 - 0.92 0.56 0.37 - 0.84 0.56 0.41 - 0.78

Child's sex

 Femaleref

 Male 1.23 1.01 - 1.50 1.18 0.96 - 1.45 1.26 1.04 - 1.53

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 1.07 0.79 - 1.43 1.07 0.78 - 1.46 1.08 0.80 - 1.45

 35 years or more 1.34 0.87 - 2.07 1.36 0.87 - 2.12 1.29 0.81 - 2.04

Mother's education

 No educationref

 Primary 1.08 0.80 - 1.46 1.39 0.97 - 1.99 1.05 0.76 - 1.45

 Secondary or higher 0.89 0.60 - 1.33 1.18 0.73 - 1.92 0.97 0.64 - 1.46

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.04 0.76 - 1.42 1.25 0.88 - 1.79 1.11 0.81 - 1.52

 3rd quintile 1.11 0.82 - 1.49 1.36 0.95 - 1.95 1.28 0.90 - 1.82

 4th quintile 1.35 0.97 - 1.89 1.62 0.98 - 2.67 1.54 0.99 - 2.41

 5th quintile (Richest) 1.21 0.85 - 1.72 1.01 0.53 - 1.95 1.38 0.81 - 2.34

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.97 0.76 - 1.24 0.96 0.72 - 1.29 0.96 0.77 - 1.20

Community-level variable

Place of residence

 Ruralref

 Urban 1.55 1.07 - 2.23

Proportion of households poor

 Low

 High 1.17 0.82 - 1.68

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 0.68 0.51 - 0.90

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous 1.34 0.95 - 1.89

Proportion of children fully 

immunizedd 0.82 0.35 - 1.93

Intercept -3.48 -3.92 - -3.04 -4.33 -4.93 - -3.72

AIC/DIC (multilevel model) of 

full models 5,301 4,155 5,034

Cont’d..
45 

Table 4: Cont’d

Zimbabwe

Model 1 Model 2 Model 3 

OR 95% CI OR 95% CI OR 95% CI

Individual-level variables

Age of the child 

 < 1 monthref

 1–5 months 1.03 0.77 - 1.38 1.07 0.80 - 1.43 1.05 0.81 - 1.37

 6–11 months 0.55 0.39 - 0.76 0.59 0.42 - 0.83 0.61 0.44 - 0.84

 12–23 months 0.44 0.30 - 0.66 0.49 0.33 - 0.73 0.50 0.35 - 0.73

 24+ months 0.41 0.26 - 0.65 0.45 0.29 - 0.71 0.50 0.33 - 0.77

Birth order and preceding birth 

interval

 First birthref

 2-3 and < 24 months 2.40 1.44 - 4.01 1.94 1.13 - 3.32 1.69 1.03 - 2.78

 2-3 and 24+ months 0.92 0.59 - 1.46 0.92 0.56 - 1.51 0.97 0.70 - 1.34

 4+ and < 24 months 3.52 1.76 - 7.05 3.50 1.74 - 7.04 2.29 1.32 - 3.97

 4+ and 24+ months 1.03 0.60 - 1.76 1.15 0.65 - 2.04 0.96 0.64 - 1.44

Child's sex

 Femaleref

 Male 1.02 0.80 - 1.30 1.07 0.82 - 1.39 1.18 0.94 - 1.49

Mother's age at child's birth

 Less than 20 yearsref

 20-34 years 0.82 0.54 - 1.24 0.82 0.53 - 1.27 0.89 0.63 - 1.26

 35 years or more 0.86 0.45 - 1.64 0.88 0.45 - 1.75 1.04 0.59 - 1.83

Mother's education

 No educationref

 Primary 1.23 0.65 - 2.32 1.46 0.67 - 3.16 1.12 0.58 - 2.16

 Secondary or higher 1.46 0.73 - 2.91 1.73 0.82 - 3.63 1.16 0.58 - 2.31

Household wealth Index

 1st quintile (Poorest)ref

 2nd quintile 1.11 0.75 - 1.65 1.06 0.73 - 1.55 1.07 0.76 - 1.50

 3rd quintile 1.05 0.66 - 1.66 0.95 0.59 - 1.53 1.08 0.73 - 1.61

 4th quintile 0.92 0.60 - 1.40 0.71 0.42 - 1.20 0.81 0.46 - 1.42

 5th quintile (Richest) 0.91 0.55 - 1.50 0.71 0.32 - 1.60 0.81 0.40 - 1.66

Skilled attendant at delivery

 Other (incl. none)ref

 Doctor, nurse, or midwife 0.75 0.57 - 0.99 0.67 0.47 - 0.95 0.73 0.57 - 0.94

Community-level variable

Place of residence

 Ruralref

 Urban 1.04 0.61 - 1.76

Proportion of households poor

 Low

 High 0.98 0.69 - 1.41

Proportion of women aged 15-49 in the community with secondary or higher 

educationb

 Low

 High 1.10 0.80 - 1.52

Ethnic Homogeneityc

 Not homogenous

 Totally homogenous

Proportion of children fully 

immunizedd 0.75 0.40 - 1.38

Intercept -3.84 -4.63 - -3.05 -4.34 -5.22 - -3.46

AIC/DIC (multilevel model) of 

full models 3,529 2,673 3,544

Cont’d..
46 

Table 4: Cont’d

Note: ref= reference category for each variable. n/a = no data available

Model 1: Ordinary discrete-time logistic regression predicting children’s probability of dying by their fifth birthday with 

only individual-level variables as predictors (Age of the child ; Birth order and preceding birth interval; Child’s sex; 

Mother's age at child's birth; Mother’s education; Skilled attendant at delivery; Household wealth Index).

Model 2: Conditional discrete-time logistic, adds to Model 1 cluster-level fixed effects to control for unobserved 

community-level characteristics. The covariates are same as in Model 1.

Model 3: Multilevel logit discrete-time model with three-level random intercept: child (level 1), family (level 2) and 

cluster (level 3). Included as predictors, both individual- and community-level covariates. The Models were fitted 

using the Markov Chain Monte Carlo (MCMC) procedure in MLwin (version 2.16). To implement estimation using 

MCMC procedure, the first-order marginal quasi-likelihood (MQL) model is used to obtain initial start values for the 

parameter estimates.

a Proportion of households poor (two lowest wealth quintiles) in the community. 

b Dichotomous variables indicating whether the proportion of women aged 15-49 in the community with secondary or 

higher education is high or low (cut-off at mean proportion).

c Based on the measures of the ethno-linguistic fractionalization index (EFL), defined as the probability that two 

individuals selected at random from primary sampling unit, will be from different ethnic groups. Theoretically, for each 

cluster, the scale goes from 0 (totally homogenous) to 1 (complete diversity). For the purposes of the present 

analysis, the resulting scale ethno-linguistic fractionalization Index was then classified into dichotomous variables 

indicating whether the ethnic composition of the community is totally homogenous (ELF equal 0) categorized as 1; if 

cluster is not totally homogenous (EFL more than 0), then categorized as 0.

d Percentage of children who received full immunization in the community (Child has received BCG, measles, and 

three doses of DPT and polio vaccines).
47 

At the individual level, the results show that in many countries, consistent with earlier 

studies, the child’s birth order and preceding birth interval are significantly associated with 

under-five mortality. The combination of a higher birth order and a shorter birth interval 

increases the odds of dying before age five. Fourth or higher-order births preceded by an interval 

of less than 24 months have a higher mortality risk than first births; this effect is significant in 11 

of the 28 countries studied. Correspondingly, children of second and third birth order and a 

preceding birth interval of 24+ months have a risk of dying before age five that is 17-42% lower 

than first-born children (ORs are significant in 19 of 28 countries). 

The results show a systematically higher mortality for male children compared to females 

in all countries except Sierra Leone, and the relationship is significant in 14 of 28 countries. In 

Sierra Leone, males have 16% lower odds than females of dying before age five (p < 0.10). 

Mother's older age at birth reduce the odds of the child’s dying during the first five years, 

in 10 of the 28 countries. Older mothers tend to be more experienced than younger mothers and 

better able to care for a newborn. Children born to mothers age 20–34 have on average 13-35% 

lower odds of dying in childhood compared to children born to mothers below age 20. In 

Lesotho and Madagascar, however, children born to mothers age 35 or older are 72% and 38% 

more likely, respectively, to die before age five than children born to mothers under age 20. 

The results show a consistent inverse relationship between maternal education and child 

mortality—the more schooling a mother has, the less likely her child is to die before age five. 

Children of mothers who attended primary school are less likely to die young than children of 

mothers with no education, and children of mothers with a secondary and higher education are 

the least likely to die before age five. Among the 28 countries, this effect is statistically 

significant in 4 countries for primary education, and in 13 countries for secondary or higher 

education. The two education variables are jointly significant only in Ethiopia. 

The results also show that maternal education is not significantly associated with underfive mortality in several countries (Burkina Faso, Congo, Ghana, and Lesotho). Many past 

studies (as in my model 1) have concluded that maternal education is a significant predictor of 

child survival in these countries (see: Desai and Alva 1998; Gakidou et al. 2010; Hobcraft et al. 

1985). Most of those studies, however, have failed to account for many important variables, 

including household-level and community-level heterogeneity, and community context variables 
48 

including community-level maternal education. This present study suggests that failure to 

account for those factors probably has led to overestimated effects of maternal own education on 

child survival. 

The effect of wealth status is relevant in 11 countries, where children from the richest 

households have a risk of dying before age five that is 24-57% lower than children from the 

poorest households. 

Regarding the effects of use of health care services, the presence of a skilled attendant at 

the child’s delivery is significantly associated with child survival in 5 of the 28 countries 

examined. Children delivered by health professionals have an odds of dying before age five that 

is 17-25% lower than children delivered by others or born at home (p < 0.05 in Congo 

Democratic Republic, Gabon, Malawi, Mali, and Zimbabwe). 

This research also contributes to the literature on the implications of community-level 

factors for child mortality. The results show that in a number of countries some attributes of the 

community influence mortality risks of children, over and above the intermediate factors 

included in this investigation. The results are mixed concerning the association between urban 

residence and the odds of dying before age five. Urban residence is significant in seven 

countries. In Chad, Malawi, Nigeria, and Rwanda, mortality is lower in urban areas than in rural 

areas. In Namibia, Sierra Leone, and Zambia, however, urban residence increases the odds of 

under-five mortality. 

The results show that in most countries community-level poverty is not associated with 

increased risk of dying before age five. In Kenya and Nigeria, clusters with a higher percentage 

of mothers living in poor households are significantly associated with increased odds of underfive deaths. 

Health care context appears to play a major role in child survival in most countries. A 1% 

increase in the proportion of children fully immunized in the community is associated with a 

significant decrease of 17-79% in the odds of dying before age five, in 11 of 28 countries under 

study. The results also show that, even when household-level and community-level factors are 

controlled, the influence of community-level maternal education on child survival is robust. In 

Congo, Ghana, and Nigeria, clusters with a higher proportion of women with secondary or 

higher education are significantly associated with reduced odds of under-five deaths. 
49 

The results reveal that, in 7 of 28 countries, the ethnic composition within the community 

affects mortality risk. In Chad, Kenya, Mali, and Niger, higher levels of community ethnic 

concentration are significantly associated with decreased odds of dying before age five. In 

Mozambique, Nigeria, and Zambia, however, higher community-level ethnic homogeneity is 

significantly associated with increased odds of child mortality.

Finally, in Guinea, Lesotho, Liberia, Madagascar, and Swaziland, none of the 

community-level factors considered in this analysis is significantly associated with under-five 

mortality.
50 

DISCUSSION AND CONCLUSIONS

In this paper I have examined the effects of child, family, and community characteristics 

on the risk of dying before age five, across 28 sub-Saharan African countries. Following the

recent applications in this field, this paper develops a new empirical conceptualization of 

childhood mortality research to explain the strong heterogeneity of mortality risks between 

families and communities across the sub-Saharan countries. This study is the first, to my 

knowledge, to have an intra-continental scope, comparing determinants of under-five mortality 

simultaneously at three levels (child, family, and community) across sub-Saharan Africa 

countries, using DHS data from the most recent national surveys. 

The estimates obtained from the analysis show that under-five mortality is jointly 

determined by the observed individual demographic and socioeconomic characteristics of the 

child and mother, and by community-level covariates, as well as unobserved household-level and 

community-level effects, in most of the countries under study. 

The results indicate large residual family-level effects and moderately large and 

statistically significant community-level effects on the risk of dying before age five, even after 

controlling for a range of child-level, family-level, and community-level variables. I found 

systematic evidence of higher child mortality clustering at the family-level compared with the 

community-level. These results suggest that membership in particular families and in particular 

communities is a major determinant of the risk of dying before age five, in most countries in subSaharan Africa. 

Because children’s contact with institutions outside of the family during the first five 

years of life (especially < 2 years) is fairly limited, it is not surprising that very few community 

attributes are associated with the individual-level mortality risks of children (Arguillas 2008). It 

also is well recognized that household environment is an important determinant of whether 

young children are exposed to pathogens and other physical risk factors for ill health (David 

1999). At this age, the child is kept within the household and often with the mother. Therefore, 

family-level effects are stronger than community effects, since the child does not have much 

exposure to the community’s culture, customs, and environment (Manda 1998: 154). 
51 

The relative importance of family-level random effects observed in child mortality is not 

uncommon in health research (Bolstad and Manda 2001; Griffiths et al. 2004; Madise et al. 

1999; Van de Poel et al. 2009). Like the present study, Bolstad and Manda (2001) used 1992 

Malawi DHS data to investigate the existence of variation in under-five mortality risks at both 

the household level and community level. They estimated the intra-family correlation of child 

mortality to be about 28% (variance at the family level was 0.843), and the intra-community 

correlation to be 18% (variance at the community level was 0.417), after controlling for a large 

number of observed characteristics of individuals and families (Bolstad and Manda 2001:18). In 

an investigation of the determinants of weight-for-age among young children in six sub-Saharan 

countries, Madise et al. (1999:339) reported intra-family correlations that ranged from 24% to 

40%, while the intra-community correlation ranged from 1% to 6%. 

The finding of this present study, which is robust, implies that there are unmeasured or 

unmeasurable factors other than those included in my analysis that are causing the clustering of 

child mortality in some families and communities. In general, unobserved effects reflect a 

diversity of factors that can be broadly classified as genetic, behavioral, and environmental, 

occurring at individual, family, and community levels (Omariba et al. 2007; Sastry 1997a). 

Particularly, the explanations for this clustering have centered on childcare practices, use of 

health services, and personal attitudes of the mothers (Bolstad and Manda 2001; Curtis et al. 

1993; Das Gupta 1990; Madise et al. 1999; Pebley et al. 1996; Sastry 1997a). In addition, the 

unobserved family-level factors could include cultural practices and such household 

environmental factors as personal hygiene and general cleanliness (Van Poppel et al. 2002). 

Finally, while information on birth weight, breastfeeding, delivery care, and 

immunization is unavailable for the majority of children, these also are part of the unobserved 

behavioral factors at the family level (Omariba et al. 2007). Other factors that were not measured 

but that may have helped to reduce the unobserved household heterogeneity in mortality risk 

include details of specific practices of the mother regarding childcare and hygiene (for example, 

changes, if any, in the food or water given to children suffering from fever or diarrhea, regular 

use of soap after defecation, and frequency of bathing). The introduction of HIV as a factor at the 

community level also may improve the models in countries with relatively high HIV prevalence 

(DeRose and Kulkarni 2005). 
52 

Despite the presence of both unobserved family and community effects, there are 

different mechanisms that might also predict variation in under-five mortality risks across 

countries. Results reveal that the standard relationships between child mortality risks and 

individual and household covariates hold in the countries examined. I discuss below the key 

findings concerning the effects of some individual-level and community-level factors. 

This study found that child’s birth order and preceding birth interval, in combination, are 

strongly associated with under-five mortality. This association is consistent with findings 

elsewhere that short preceding birth intervals and high parity largely increase child mortality 

risk, after accounting for unobserved heterogeneity (Bolstad and Manda 2001; Curtis et al. 1993; 

Miller et al. 1992; Sastry 1997a). This could be related to maternal depletion syndrome and 

resource competition between siblings, in addition to a lack of care and attention experienced by 

high-order children (Rutstein 2005; Zenger 1993). 

This point is important because short birth intervals remain relatively common in many 

sub-Saharan countries (Ngianga-Bakwin and Stones 2005). In addition, use of modern 

contraceptive methods is quite low—often less than 10%—in many countries, especially in 

Middle and Western Africa (African Population and Health Research Center and Population 

Reference Bureau 2008:3). Thus the use of contraception to space births could make an 

important contribution to reducing the risks of child mortality (Curtis et al. 1993). Recently, one 

multi-country analysis of pregnancy outcomes found that 12 months of contraception-only 

coverage in the preceding birth interval can reduce the mortality risk for the next newborn by 

31%, while 12 months of contraceptive use overlapping with breastfeeding reduces the risk by 

68% (Tsui and Creanga 2009). 

Child survival to a large extent also depends on mother’s age at the time of the child’s 

birth, in several developing countries studied (Bolstad and Manda 2001; Ladusingh and Singh 

2006; Sastry 1997a). The present analysis found that in the most of the 28 countries under study 

the older the mother, the better the child’s probability of survival. A similar result is reported by 

Forste (1994) who found that, in Bolivia, mother's age at childbirth reduced the risk of death 

during the first two years. The relationship between mother’s age at birth and child mortality is 

sometime difficult to understand. A variety of relationships have been reported and a number of 

mechanisms have been proposed to account for them (Hobcraft et al. 1985). Forste (1994:506) 
53 

has pointed out that older mothers tend to be more experienced and better able to care for a 

newborn, than younger mothers.

The results show systematically that male children have higher mortality risks than 

female children. This finding seems to confirm the theory of male biological disadvantage in 

early life (Waldron 1998) in sub-Saharan Africa. 

Findings regarding the effects of maternal education on child mortality generally indicate 

a negative relationship between the educational attainment of the mother and her risk of 

experiencing an infant and child death (see, e.g., Desai and Alva 1998; Kravdal 2004; Ladusingh 

and Singh 2006). The results of the present analysis confirm the strong relationship between 

increased maternal education and improved child survival, even after accounting for other 

measures of individual-level, child-level, and mother-level demographic and socioeconomic 

characteristics, and community-level covariates. That is, a strong association remains between 

the level of maternal education and the odds of child survival, independent of wealth. It appears 

that more educated mothers can use limited resources more effectively than mothers with less 

education. More educated mothers may also have better information on health and nutritionrelated practices that translate to better survival chances for children (Griffiths et al. 2004). There 

are a number of plausible mechanisms that could link the level of maternal education to underfive mortality, including both mediation and moderation effects (Cleland and van Ginneken 

1988; Thrane 2006). 

As would be expected, and has been found in a previous study (Fotso and Kuate-Defo 

2005), this study also observed a negative association between household wealth and child 

mortality. Compared to children from the poorest households, children from richer households 

are less likely to die before their fifth birthday, in more than 10 of the 28 countries studied. 

The present analysis provides empirical support that, in many countries under study, 

uptake of safe delivery practices protects children from dying before age five. As would be 

expected, medical assistance by skilled medical personnel significantly lowers the risk of underfive mortality (WHO 2005). This finding points to the need to continue to invest resources in 

health care services that promote child health-seeking behavior. 

One of the findings of this study is that certain characteristics of the mother’s community 

have independent effects on the survival chances of their children, even after individual and 
54 

household factors are accounted for. In the most of the countries under study, as in other 

previous findings (Van de Poel et al. 2009), urban residence lowers child mortality risks. In some 

countries, however, urban residence increases the odds of under-five mortality. While it is widely 

recognized that child health outcomes are better in urban than in rural areas of developing 

countries (Van de Poel et al. 2007), recent evidence suggests that infant and child mortality rates 

are increasing in many urban areas in sub-Saharan Africa (Fotso et al. 2007; Garenne 2010). 

The drivers of excess urban mortality are multiple, and may vary over time and across 

geographic areas (Sastry 2004; Van de Poel et al. 2009). They are probably the result of growing 

urban poverty in the context of rapid and unplanned urbanization (Brockerhoff and Brennan 

1998). In this analysis, Sierra Leone is illustrative, “primarily because of a worsening economic 

situation in urban areas, in the context of a dramatic recession following the 1991–2002 civil 

war” (Garenne 2010:4). Vorster et al. reported that the “African population is experiencing rapid 

urbanization characterized by a double burden of disease in which non-communicable diseases 

become more prevalent and infectious diseases remain undefeated” (Vorster et al. 1999:341). 

Historians and demographers have long debated the existence, causes, and consequences of 

historical differences between urban and rural mortality levels (Woods 2003). The debate 

continues, because a number of pertinent questions remain unresolved. Many studies have 

pointed out that the way in which mortality is measured may influence the apparent extent of the 

differential, as may the way in which “urban” and “rural” are defined (Bloom et al. 2010; Woods 

2003). 

Some of the effects of the other community-level variables are difficult to understand. For 

instance, in many of the countries studied, poverty concentration within a community is not 

significantly associated with increased under-five mortality. Although this finding is consistent 

with other research (Chen et al. 2007), it is an unexpected result. A study by Chen et al. 

(2007:174) highlights that the weakness of the relationship between community characteristics 

and child deaths is probably due to more frequent underreporting of child deaths in poor 

communities. 

As has been found elsewhere (Kravdal 2004), this present research confirms the presence 

of the community-level effect of mother’s education on child mortality, in three of the countries 

studied. Residence in areas where levels of education are generally high is associated with 
55 

decreased odds of dying before age five. In Nigeria, this effect is in addition to the positive 

individual-level effect of the child’s own mother being educated. Most interestingly, even 

children whose own mothers have little education appear to benefit from the education of other 

mothers in the community, providing evidence of positive externality (spillover effect) of 

community-level maternal education in shaping child survival. The effect of community 

education may operate through a wide range of variables related to health and health care 

(Kravdal 2004:190). In addition, Gage (2007:1680) highlights the role that high levels of social 

capital can play as a plausible mechanism through which an area’s education level can influence 

maternal health care-seeking behavior. 

This study shows that in some countries an ethnic concentration within a community is 

predictive of child mortality risks, although it appears likely that neighborhood ethnic 

composition is a surrogate for neighborhood socioeconomic status and/or other contextual 

factors (Wight et al. 2010) not examined in this study. Because of higher ethnic diversity in subSaharan Africa (Fearon 2003; Obono 2003), the effects of the ethnic composition of the 

community on child mortality are complex and sometimes difficult to understand. Brockerhoff 

and Hewett (1998:5) have pointed out that “ethnic child mortality differences probably reflect 

the heterogeneity of social and ecological settings in Africa.” In addition, in many countries child 

survival is also affected indirectly by the prominence of ethnic groups in the national political 

economy (Brockerhoff and Hewett 1998:7). 

In a number of countries, results of the present study agree with the observations made by 

Kravdal (2004) in India that low mortality is indicated for children who live in communities 

where relatively many are members of the same ethnic group (e.g.: scheduled castes or tribes) 

(Kravdal 2004: 186). However, in some countries my results show that higher community-level 

ethnic homogeneity is associated with increased odds of child mortality. 

Possible explanations for such findings are generally centered on cultural models and 

social mechanisms (Adams et al. 2002; Brockerhoff and Hewett 1998; Rutenberg and Watkins 

1997; Weeks et al. 2006). Cultural factors may play a role in shaping women’s decisions about 

child delivery and related medical care. Studies have demonstrated the existence of ethnic 

variation in attitudes and norms surrounding childbirth and medicine that have direct effects on 

maternal and infant mortality outcomes (Glei and Goldman 2000). 
56 

In more than half of the 28 countries studied, having a high proportion of children fully 

immunized in a community is associated with lower under-five mortality. This finding highlights 

that the importance of preventive health measures such as vaccination in improving child 

survival (WHO 2005). A country-specific estimate of immunization coverage has been 

considered to be a proxy for availability and accessibility of maternal and child health services 

(Ahmed and Mosley 2002). Previous studies have shown that individual maternal and child 

health-seeking behaviors are strongly influenced by the practices of others in the community 

(Stephenson et al. 2006). 

In Guinea, Lesotho, Liberia, Madagascar, and Swaziland, none of the community-level 

factors considered in this analysis has a statistically significant effect on the risk of under-five 

mortality. This finding is not surprising, since the full multilevel models show non-significant 

community-level random effects for these countries. It suggests either that the individual-level 

covariates are relatively more important than the community-level factors, or that the variables 

used in the models are not able to capture the contextual effect. Robert (1999) has stated that, “if 

the association between community socioeconomic context and health simply reflects the sum of 

relationships at the individual level, we might choose to improve health by targeting individuals 

with lower socioeconomic position rather than targeting communities with lower socioeconomic 

profiles” (Robert 1999: 490-491). 

This research has inherent limitations that should be noted when interpreting the results. 

As discussed in other analyses, using DHS data and considering primary sampling units 

(clusters) as the community level (Montgomery and Hewett 2005), results may be biased toward 

a well-functioning population, due to both endogeneity and selection effects (Kravdal 2004:190; 

Wight et al. 2010:212) (as detailed in the literature review section of this paper). In addition, the 

use of cross-sectional individual-level data restricts the inferences to associations between 

independent and dependent individual-level variables, not causal relationships. 

There are also limitations associated with the community-level characteristics used in this 

analysis. With the exception of “urban-rural residence,” all community-level variables are 

constructed by aggregating individual-level and household-level characteristics at the community 

level (the primary sampling units). That is, the community contextual variables are actually 

compositional variables, aggregated upwards. There are two potential problems with this 
57 

approach (Rajaratnama et al. 2006). First, it could result in multicollinearity, since the same 

variables used to derive the “contextual” variables are also included as individual variables. 

Second, the approach is subject to atomistic fallacy, or the problem of making inferences at a 

higher level based on data collected at a lower level (Duncan et al. 1998). 

In addition, the lack of adequate measurement of community-level data (such as distance 

and travel time to a health facility) has probably reduced the predicting models’ power, and 

hence has contributed to the weakness of the community-level effects on child mortality 

observed in certain countries. 

Finally, although this is a comparative study, the 28 countries could not be fitted with a 

common statistical model. Each country is unique in its demographic and cultural characteristics, 

and the DHS data differ significantly by some variables across the countries (e.g., the ethnicity 

variable was not included in models in seven countries). The lack of the same variables in all the 

data sets primarily limited our analytical attempts. For this reason, the countries could not be 

easily compared.

Notwithstanding these limitations, these findings represent a further step toward an 

improved understanding of the complex determinants of child survival in sub-Saharan Africa. 

The present study provides empirical evidence for the thesis that information about family and 

community is essential for a better understanding of inequalities in child mortality. Specially, 

this study demonstrates that there is no single community influence on child mortality, and the 

significant community-level factors vary across the 28 study settings, as community-level 

indicators reflect the socioeconomic context and the health care context, as well as culturally and 

contextually specific practices. This finding has both theoretical value and important policy 

implications. Finally, this research suggests that the challenge to reduce under-five mortality 

goes beyond addressing individual factors, and requires a better understanding of contextual 

factors. 
58 

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69 

APPENDIX Table 1: Description of variables used in the analysis (variable names and 

definitions)

Names Description

Individual-level variable

Age of the child in months Number of months from time of birth until time of death or censoring (interview) 

(categorized as 1= 0 month; 2= 1 to 5 months; 3= 6 to 11 months; 4= 12 to 23 

months; 5= 24 to 59 months).

Sex Whether the child is male or female (1 = male; 0 = female).

Birth order and preceding 

birth interval

Birth order and preceding birth interval were combined in one variable and is 

classified as follows: first birth, birth order 2-4 with short birth interval (< 24 

months), birth order 2-4 with medium birth interval (24 – 47 months), birth order 2-

4 with long birth interval (48+ months), birth order 5+ with short birth interval (< 24 

months), birth order 5+ with medium birth interval (24 – 47 months), birth order 5+ 

with long birth interval (48+ months).

Mother’s age at child birth Respondent’s age (in years) at child birth (1 = less than 20 years; 2 = 20-34 

years; 3 = greater than 35 years.

Mother’s education Categorical variable indicating highest educational level that respondents 

completed (1 = no education; 2 = primary; 3 = secondary or higher education).

Household wealth Index Index provided with the dataset is used. DHS program provides a composite 

index of household amenities based on the principal component analysis (PCA) 

and classified the population into quintiles: (1st quintile (Poorest); 2nd quintile; 3rd 

quintile; 4th quintile and 5th quintile (Richest). A quintile is assigned to each 

household as a measure of its relative socioeconomic level (for details see 

Rutstein and Johnson 2004).

Place of delivery Whether the place of delivery is in a health facility categorized as 1; if place of 

delivery is in home or other then as 0.

Skilled attendant at delivery Deliveries assisted by either doctor, nurse/midwife categorized as 1; if no 

assistance then categorized as 0.

Community-level variable

Urban Whether the cluster is urban community according the definition of the country 

categorized as 1; if cluster is rural community then categorized as 0.

Community-level socioeconomic statusProportion of households poor (two lowest wealth quintiles) in the community. 

Community-level education Dichotomous variables indicating whether the proportion of women aged 15-49 in 

the community with secondary or higher education is high or low (cut-off at mean 

proportion).

Community-level Ethnic 

Homogeneity

Measure based on the concept of the index of Ethno-linguistic fractionalization 

(ELF). Ethno-linguistic fractionalization is the probability that two people randomly 

drawn from the population are from distinct ethnic groups (Fearon, 2003: 208). 

This Index is calculated as ELF = 1 – ∑i (Proportion of Ethno-linguistic groupi in 

the population)2

. Theoretically, for each primary sampling unit, the scale goes 

from 0 (totally homogenous) to 1 (complete diversity). For the purposes of the 

present analysis, the resulting scale ethno-linguistic fractionalization Index was 

then classified into dichotomous variables indicating whether the ethnic 

composition of the community is totally homogenous (ELF equal 0) categorized as 

1; if cluster is not totally homogenous (EFL more than 0), then categorized as 0.

Community child 

immunization coverage

Percentage of children who received full immunization in the community (Child 

has received BCG, measles, and three doses of DPT and polio vaccines). 
70 

APPENDIX Table 2: Number and percentage1 of children by selected characteristics and country: 

births in the five years preceding the survey

Benin Burkina Faso Cameroon 

Characteristics Number % Number % Number %

Number of children 15,929 100.0 10,852 100.0 8,097 100.0

Individual-level variables

Birth order and preceding birth interval

 First birth 3,058 19.3 2,053 18.9 1,902 23.6

 2-3 and < 24 months 790 5.0 473 4.4 591 7.3

 2-3 and 24+ months 4,804 30.3 2,948 27.2 2,112 26.2

 4+ and < 24 months 1,025 6.5 690 6.4 755 9.4

 4+ and 24+ months 6,194 39.0 4,673 43.1 2,707 33.6

Child's sex

 Female 7,901 49.6 5,303 48.9 4,060 50.1

 Male 8,028 50.4 5,549 51.1 4,038 49.9

Mother's age at child's birth

 Less than 20 years 1,890 11.9 1,667 15.4 1,843 22.8

 20-34 years 12,013 75.4 7,260 66.9 5,368 66.3

 35 years or more 2,026 12.7 1,924 17.7 886 10.9

Mother's education

 No education 11,940 75.0 9,574 88.2 2,397 29.6

 Primary 2,829 17.8 862 7.9 3,462 42.8

 Secondary or higher 1,161 7.3 416 3.8 2,238 27.6

Household wealth Index

 1st quintile (Poorest) 3,550 22.3 2,100 19.3 2,058 25.4

 2nd quintile 3,248 20.4 2,297 21.2 1,648 20.3

 3rd quintile 3,320 20.8 2,900 26.7 1,681 20.8

 4th quintile 3,206 20.1 1,972 18.2 1,489 18.4

 5th quintile (Richest) 2,605 16.4 1,583 14.6 1,221 15.1

Place of delivery

 Home/Other 3,433 21.6 6,655 61.4 3,237 40.2

 Health facility 12,462 78.4 4,187 38.6 4,824 59.8

Skilled attendant at delivery

 Other (incl. none) 4,083 25.7 6,741 62.2 3,293 40.8

 Doctor, nurse, or midwife 11,777 74.3 4,104 37.8 4,773 59.2

Community-level variables

Place of residence

 Rural 10,480 65.8 9,466 87.2 4,547 56.2

 Urban 5,450 34.2 1,386 12.8 3,550 43.8

Community-level socio-economic statusa

 Low 8,297 52.1 5,291 48.8 4,041 49.9

 High 7,632 47.9 5,561 51.2 4,057 50.1

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low 9,015 56.6 8,227 75.8 4,373 54.0

 High 6,915 43.4 2,625 24.2 3,724 46.0

Community-level ethnic homogeneityc

 Not totally homogenous (EFL more than 0) 11,646 73.1 6,252 57.6 6,525 80.6

 Totally homogenous (ELF equal 0) 4,283 26.9 4,600 42.4 1,572 19.4

Community-level child immunization coveraged

 Low 5,294 33.2 4,086 37.7 2,893 35.7

 Middle 5,439 34.1 3,518 32.4 2,433 30.0

 High 5,197 32.6 3,248 29.9 2,772 34.2

Cont’d..
71 

APPENDIX Table 2: Cont’d

Chad 

Congo 

(Brazzaville) 

Congo 

Democratic 

Republic 

Characteristics Number % Number % Number %

Number of children 5,989 100.0 4,948 100.0 8,999 100.0

Individual-level variables

Birth order and preceding birth interval

 First birth 1,039 17.4 1,271 25.8 1,850 20.6

 2-3 and < 24 months 445 7.4 271 5.5 705 7.9

 2-3 and 24+ months 1,385 23.2 1,707 34.6 2,171 24.2

 4+ and < 24 months 817 13.7 212 4.3 1,141 12.7

 4+ and 24+ months 2,291 38.3 1,474 29.9 3,106 34.6

Child's sex

 Female 2,931 48.9 2,434 49.2 4,589 51.0

 Male 3,058 51.1 2,514 50.8 4,410 49.0

Mother's age at child's birth

 Less than 20 years 1,277 21.3 1,009 20.4 1,454 16.2

 20-34 years 4,013 67.0 3,320 67.1 6,090 67.7

 35 years or more 699 11.7 619 12.5 1,455 16.2

Mother's education

 No education 4,580 76.5 443 8.9 2,117 23.5

 Primary 1,164 19.4 1,796 36.3 3,770 41.9

 Secondary or higher 245 4.1 2,710 54.8 3,112 34.6

Household wealth Index

 1st quintile (Poorest) 1,019 17.0 1,182 23.9 1,873 20.8

 2nd quintile 1,356 22.6 1,119 22.6 2,035 22.6

 3rd quintile 1,187 19.8 1,060 21.4 1,864 20.7

 4th quintile 1,333 22.3 856 17.3 1,844 20.5

 5th quintile (Richest) 1,093 18.3 732 14.8 1,383 15.4

Place of delivery

 Home/Other 5,153 86.2 811 16.5 2,503 28.2

 Health facility 827 13.8 4,111 83.5 6,382 71.8

Skilled attendant at delivery

 Other (incl. none) 5,839 97.5 3,404 68.8 5,135 57.8

 Doctor, nurse, or midwife 147 2.5 1,545 31.2 3,756 42.2

Community-level variables

Place of residence

 Rural 4,866 81.2 2,691 54.4 5,509 61.2

 Urban 1,123 18.8 2,258 45.6 3,490 38.8

Community-level socio-economic statusa

 Low 2,222 37.1 2,122 42.9 4,560 50.7

 High 3,766 62.9 2,826 57.1 4,439 49.3

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low 3,779 63.1 2,805 56.7 4,078 45.3

 High 2,210 36.9 2,143 43.3 4,921 54.7

Community-level ethnic homogeneityc

 Not totally homogenous (EFL more than 0) 4,018 67.1 4,817 97.3 2,841 31.6

 Totally homogenous (ELF equal 0) 1,970 32.9 132 2.7 6,158 68.4

Community-level child immunization coveraged

 Low 2,733 45.6 1,826 36.9 3,212 35.7

 Middle 2,068 34.5 1,632 33.0 2,914 32.4

 High 1,188 19.8 1,490 30.1 2,873 31.9

Cont’d..
72 

APPENDIX Table 2: Cont’d

Ethiopia Gabon Ghana 

Characteristics Number % Number % Number %

Number of children 11,163 100.0 4,031 100.0 2,909 100.0

Individual-level variables

Birth order and preceding birth interval

 First birth 1,933 17.3 1,083 27.0 688 23.7

 2-3 and < 24 months 754 6.8 297 7.4 157 5.4

 2-3 and 24+ months 2,593 23.2 1,063 26.5 946 32.6

 4+ and < 24 months 1,219 10.9 332 8.3 153 5.3

 4+ and 24+ months 4,661 41.8 1,243 30.9 961 33.1

Child's sex

 Female 5,440 48.7 1,979 49.1 1,399 48.1

 Male 5,723 51.3 2,052 50.9 1,510 51.9

Mother's age at child's birth

 Less than 20 years 1,715 15.4 1,069 26.5 333 11.5

 20-34 years 7,702 69.0 2,566 63.6 2,079 71.4

 35 years or more 1,746 15.6 397 9.8 497 17.1

Mother's education

 No education 8,838 79.2 268 6.6 952 32.7

 Primary 1,855 16.6 1,697 42.1 722 24.9

 Secondary or higher 470 4.2 2,066 51.3 1,232 42.4

Household wealth Index

 1st quintile (Poorest) 2,440 21.9 811 20.1 744 25.6

 2nd quintile 2,356 21.1 926 23.0 641 22.0

 3rd quintile 2,486 22.3 857 21.3 549 18.9

 4th quintile 2,222 19.9 784 19.4 560 19.3

 5th quintile (Richest) 1,660 14.9 653 16.2 415 14.3

Place of delivery

 Home/Other 10,502 94.3 510 12.9 1,223 42.2

 Health facility 635 5.7 3,454 87.1 1,675 57.8

Skilled attendant at delivery

 Other (incl. none) 10,505 94.3 671 16.8 1,302 45.0

 Doctor, nurse, or midwife 635 5.7 3,330 83.2 1,594 55.0

Community-level variables

Place of residence

 Rural 10,348 92.7 1,069 26.5 1,806 62.1

 Urban 815 7.3 2,962 73.5 1,104 37.9

Community-level socio-economic statusa

 Low 5,893 52.8 2,710 67.2 1,719 59.1

 High 5,270 47.2 1,322 32.8 1,190 40.9

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low 8,825 79.1 1,666 41.3 1,336 45.9

 High 2,338 20.9 2,365 58.7 1,573 54.1

Community-level ethnic homogeneityc

 Not totally homogenous (EFL more than 0) 4,923 44.1 3,740 92.8 1,655 56.9

 Totally homogenous (ELF equal 0) 6,240 55.9 291 7.2 1,254 43.1

Community-level child immunization coveraged

 Low 3,304 29.6 1,214 30.1 1,255 43.1

 Middle 4,841 43.4 1,274 31.6 649 22.3

 High 3,018 27.0 1,543 38.3 1,005 34.6

Cont’d..
73 

APPENDIX Table 2: Cont’d

Guinea Kenya Lesotho 

Characteristics Number % Number % Number %

Number of children 6,370 100.0 6,102 100.0 3,572 100.0

Individual-level variables

Birth order and preceding birth interval

 First birth 1,098 17.3 1,469 24.1 1,238 34.8

 2-3 and < 24 months 211 3.3 534 8.8 145 4.1

 2-3 and 24+ months 1,751 27.6 1,634 26.8 1,178 33.1

 4+ and < 24 months 392 6.2 526 8.6 100 2.8

 4+ and 24+ months 2,899 45.6 1,929 31.7 901 25.3

Child's sex

 Female 3,075 48.3 2,992 49.0 1,737 48.6

 Male 3,294 51.7 3,110 51.0 1,834 51.4

Mother's age at child's birth

 Less than 20 years 1,140 17.9 1,070 17.5 727 20.3

 20-34 years 4,128 64.8 4,287 70.3 2,290 64.1

 35 years or more 1,103 17.3 745 12.2 555 15.5

Mother's education

 No education 5,546 87.1 938 15.4 94 2.6

 Primary 524 8.2 3,901 63.9 2,318 64.9

 Secondary or higher 300 4.7 1,263 20.7 1,160 32.5

Household wealth Index

 1st quintile (Poorest) 1,563 24.5 1,509 24.7 746 20.9

 2nd quintile 1,376 21.6 1,271 20.8 861 24.1

 3rd quintile 1,323 20.8 1,159 19.0 638 17.9

 4th quintile 1,164 18.3 1,032 16.9 721 20.2

 5th quintile (Richest) 943 14.8 1,131 18.5 605 17.0

Place of delivery

 Home/Other 4,378 69.1 3,584 58.9 1,623 45.9

 Health facility 1,960 30.9 2,498 41.1 1,913 54.1

Skilled attendant at delivery

 Other (incl. none) 4,502 71.1 3,545 58.3 1,556 44.0

 Doctor, nurse, or midwife 1,828 28.9 2,536 41.7 1,978 56.0

Community-level variables

Place of residence

 Rural 4,932 77.4 4,959 81.3 3,069 85.9

 Urban 1,438 22.6 1,143 18.7 503 14.1

Community-level socio-economic statusa

 Low 3,352 52.6 2,868 47.0 1,995 55.8

 High 3,017 47.4 3,234 53.0 1,577 44.2

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low 4,150 65.1 3,096 50.7 1,733 48.5

 High 2,220 34.9 3,006 49.3 1,839 51.5

Community-level ethnic homogeneityc

 Not totally homogenous (EFL more than 0) 4,140 65.0 3,004 49.2 3,572 100.0

 Totally homogenous (ELF equal 0) 2,229 35.0 3,098 50.8 3,572 100.0

Community-level child immunization coveraged

 Low 2,250 35.3 1,996 32.7 1,127 31.5

 Middle 2,114 33.2 2,153 35.3 1,350 37.8

 High 2,005 31.5 1,952 32.0 1,095 30.7

Cont’d..
74 

APPENDIX Table 2: Cont’d

Liberia Madagascar Malawi 

Characteristics Number % Number % Number %

Number of children 5,594 100.0 12,686 100.0 10,771 100.0

Individual-level variables

Birth order and preceding birth interval

 First birth 1,266 22.7 2,845 22.5 2,530 23.5

 2-3 and < 24 months 326 5.8 969 7.7 622 5.8

 2-3 and 24+ months 1,582 28.3 3,375 26.6 3,299 30.7

 4+ and < 24 months 436 7.8 1,281 10.1 613 5.7

 4+ and 24+ months 1,974 35.3 4,196 33.1 3,684 34.3

Child's sex

 Female 2,682 48.0 6,222 49.0 5,390 50.0

 Male 2,911 52.0 6,465 51.0 5,381 50.0

Mother's age at child's birth

 Less than 20 years 956 17.1 2,673 21.1 2,205 20.5

 20-34 years 3,702 66.2 8,038 63.4 7,321 68.0

 35 years or more 935 16.7 1,975 15.6 1,246 11.6

Mother's education

 No education 2,729 48.9 3,219 25.4 2,785 25.9

 Primary 1,951 34.9 7,010 55.3 6,860 63.7

 Secondary or higher 906 16.2 2,457 19.4 1,127 10.5

Household wealth Index

 1st quintile (Poorest) 1,254 22.4 3,270 25.8 2,099 19.5

 2nd quintile 1,332 23.8 2,839 22.4 2,426 22.5

 3rd quintile 1,197 21.4 2,539 20.0 2,446 22.7

 4th quintile 1,137 20.3 2,252 17.8 2,091 19.4

 5th quintile (Richest) 673 12.0 1,787 14.1 1,709 15.9

Place of delivery

 Home/Other 3,411 61.7 8,082 64.0 3,164 29.4

 Health facility 2,113 38.3 4,539 36.0 7,593 70.6

Skilled attendant at delivery

 Other (incl. none) 2,965 53.9 7,058 55.9 4,702 43.8

 Doctor, nurse, or midwife 2,539 46.1 5,571 44.1 6,042 56.2

Community-level variables

Place of residence

 Rural 3,900 69.7 11,309 89.1 9,347 86.8

 Urban 1,694 30.3 1,377 10.9 1,425 13.2

Community-level socio-economic statusa

 Low 2,848 50.9 6,771 53.4 5,499 51.1

 High 2,745 49.1 5,915 46.6 5,272 48.9

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low 2,901 51.9 6,235 49.1 5,363 49.8

 High 2,693 48.1 6,451 50.9 5,408 50.2

Community-level ethnic homogeneityc

 Not totally homogenous (EFL more than 0) 4,433 79.3 12,686 100.0 8,784 81.5

 Totally homogenous (ELF equal 0) 1,160 20.7 12,686 100.0 1,988 18.5

Community-level child immunization coveraged

 Low 1,761 31.5 3,798 29.9 3,688 34.2

 Middle 1,709 30.6 4,231 33.4 3,560 33.1

 High 2,124 38.0 4,657 36.7 3,524 32.7

Cont’d..
75 

APPENDIX Table 2: Cont’d

Mali Mozambique Namibia 

Characteristics Number % Number % Number %

Number of children 14,420 100.0 10,620 100.0 5,003 100.0

Individual-level variables

Birth order and preceding birth interval

 First birth 2,536 17.6 2,303 21.7 1,608 32.3

 2-3 and < 24 months 1,009 7.0 599 5.7 271 5.4

 2-3 and 24+ months 3,385 23.5 3,037 28.6 1,770 35.5

 4+ and < 24 months 1,578 11.0 758 7.1 182 3.7

 4+ and 24+ months 5,894 40.9 3,909 36.9 1,148 23.1

Child's sex

 Female 7,104 49.3 5,379 50.6 2,434 48.7

 Male 7,316 50.7 5,241 49.4 2,569 51.3

Mother's age at child's birth

 Less than 20 years 2,901 20.1 2,380 22.4 793 15.9

 20-34 years 9,494 65.8 6,865 64.6 3,482 69.6

 35 years or more 2,026 14.0 1,375 12.9 728 14.5

Mother's education

 No education 12,334 85.5 4,906 46.2 553 11.1

 Primary 1,452 10.1 5,315 50.0 1,436 28.7

 Secondary or higher 634 4.4 399 3.8 3,014 60.2

Household wealth Index

 1st quintile (Poorest) 2,958 20.5 2,822 26.6 1,072 21.4

 2nd quintile 2,985 20.7 2,050 19.3 956 19.1

 3rd quintile 3,025 21.0 2,286 21.5 1,121 22.4

 4th quintile 2,939 20.4 1,775 16.7 1,041 20.8

 5th quintile (Richest) 2,514 17.4 1,687 15.9 813 16.3

Place of delivery

 Home/Other 7,783 54.3 5,370 50.7 933 18.7

 Health facility 6,550 45.7 5,214 49.3 4,055 81.3

Skilled attendant at delivery

 Other (incl. none) 10,450 73.0 8,499 80.4 919 18.4

 Doctor, nurse, or midwife 3,864 27.0 2,077 19.6 4,071 81.6

Community-level variables

Place of residence

 Rural 10,529 73.0 7,533 70.9 2,926 58.5

 Urban 3,891 27.0 3,087 29.1 2,077 41.5

Community-level socio-economic statusa

 Low 6,983 48.4 4,556 42.9 2,484 49.6

 High 7,438 51.6 6,064 57.1 2,519 50.4

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low 8,811 61.1 8,233 77.5 2,329 46.5

 High 5,609 38.9 2,387 22.5 2,674 53.5

Community-level ethnic homogeneityc

 Not totally homogenous (EFL more than 0) 12,639 87.6 6,298 59.3 2,703 54.0

 Totally homogenous (ELF equal 0) 1,782 12.4 4,322 40.7 2,300 46.0

Community-level child immunization coveraged

 Low 4,779 33.1 4,199 39.5 1,707 34.1

 Middle 5,299 36.7 3,418 32.2 1,621 32.4

 High 4,343 30.1 3,003 28.3 1,675 33.5

Cont’d..
76 

APPENDIX Table 2: Cont’d

Niger Nigeria Rwanda 

Characteristics Number % Number % Number %

Number of children 9,954 100.0 28,100 100.0 8,715 100.0

Individual-level variables

Birth order and preceding birth interval

 First birth 1,544 15.5 5,371 19.1 1,616 18.6

 2-3 and < 24 months 603 6.1 2,324 8.3 802 9.2

 2-3 and 24+ months 2,146 21.6 6,969 24.8 2,079 23.9

 4+ and < 24 months 1,142 11.5 3,071 10.9 841 9.7

 4+ and 24+ months 4,503 45.3 10,324 36.8 3,353 38.6

Child's sex

 Female 4,853 48.8 13,811 49.2 4,287 49.2

 Male 5,101 51.2 14,289 50.8 4,428 50.8

Mother's age at child's birth

 Less than 20 years 1,848 18.6 4,159 14.8 533 6.1

 20-34 years 6,653 66.8 19,636 69.9 6,366 73.1

 35 years or more 1,452 14.6 4,305 15.3 1,815 20.8

Mother's education

 No education 8,709 87.5 13,071 46.5 2,470 28.3

 Primary 934 9.4 6,521 23.2 5,513 63.3

 Secondary or higher 311 3.1 8,508 30.3 732 8.4

Household wealth Index

 1st quintile (Poorest) 2,144 21.5 6,525 23.2 1,845 21.2

 2nd quintile 1,989 20.0 6,395 22.8 1,794 20.6

 3rd quintile 1,903 19.1 5,417 19.3 1,785 20.5

 4th quintile 2,100 21.1 5,003 17.8 1,742 20.0

 5th quintile (Richest) 1,818 18.3 4,760 16.9 1,548 17.8

Place of delivery

 Home/Other 8,168 82.6 17,437 62.7 6,139 70.6

 Health facility 1,722 17.4 10,377 37.3 2,553 29.4

Skilled attendant at delivery

 Other (incl. none) 8,101 82.2 18,045 65.1 6,212 71.5

 Doctor, nurse, or midwife 1,757 17.8 9,660 34.9 2,479 28.5

Community-level variables

Place of residence

 Rural 8,451 84.9 19,741 70.3 7,487 85.9

 Urban 1,503 15.1 8,359 29.7 1,228 14.1

Community-level socio-economic statusa

 Low 4,146 41.7 15,483 55.1 4,152 47.6

 High 5,808 58.3 12,617 44.9 4,563 52.4

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low 7,616 76.5 13,075 46.5 4,523 51.9

 High 2,337 23.5 15,025 53.5 4,192 48.1

Community-level ethnic homogeneityc

 Not totally homogenous (EFL more than 0) 6,509 65.4 16,963 60.4 8,715 100.0

 Totally homogenous (ELF equal 0) 3,445 34.6 11,137 39.6 8,715 100.0

Community-level child immunization coveraged

 Low 4,387 44.1 9,029 32.1 2,875 33.0

 Middle 3,251 32.7 8,980 32.0 2,914 33.4

 High 2,316 23.3 10,091 35.9 2,926 33.6

Cont’d..
77 

APPENDIX Table 2: Cont’d

Senegal Sierra Leone Swaziland 

Characteristics Number % Number % Number %

Number of children 10,530 100.0 5,811 100.0 2,829 100.0

Individual-level variables

Birth order and preceding birth interval

 First birth 2,299 21.9 1,148 19.8 890 31.6

 2-3 and < 24 months 741 7.0 366 6.3 160 5.7

 2-3 and 24+ months 2,767 26.3 1,785 30.8 904 32.1

 4+ and < 24 months 845 8.0 459 7.9 141 5.0

 4+ and 24+ months 3,860 36.7 2,038 35.2 725 25.7

Child's sex

 Female 5,109 48.5 2,931 50.4 1,401 49.5

 Male 5,421 51.5 2,880 49.6 1,428 50.5

Mother's age at child's birth

 Less than 20 years 1,669 15.8 977 16.8 661 23.4

 20-34 years 7,236 68.7 4,002 68.9 1,852 65.5

 35 years or more 1,625 15.4 832 14.3 315 11.1

Mother's education

 No education 7,577 72.0 4,443 76.5 263 9.3

 Primary 2,194 20.8 713 12.3 992 35.1

 Secondary or higher 759 7.2 655 11.3 1,574 55.6

Household wealth Index

 1st quintile (Poorest) 2,425 23.0 1,327 22.8 572 20.2

 2nd quintile 2,332 22.1 1,220 21.0 603 21.3

 3rd quintile 2,238 21.3 1,288 22.2 554 19.6

 4th quintile 1,908 18.1 1,102 19.0 554 19.6

 5th quintile (Richest) 1,627 15.5 873 15.0 546 19.3

Place of delivery

 Home/Other 3,916 37.4 4,172 73.8 715 25.3

 Health facility 6,550 62.6 1,479 26.2 2,110 74.7

Skilled attendant at delivery

 Other (incl. none) 5,780 55.2 3,892 68.6 873 30.9

 Doctor, nurse, or midwife 4,683 44.8 1,783 31.4 1,951 69.1

Community-level variables

Place of residence

 Rural 6,688 63.5 4,226 72.7 2,199 77.7

 Urban 3,842 36.5 1,585 27.3 630 22.3

Community-level socio-economic statusa

 Low 5,686 54.0 2,671 46.0 1,445 51.1

 High 4,843 46.0 3,140 54.0 1,384 48.9

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low 5,459 51.8 3,414 58.8 1,384 48.9

 High 5,071 48.2 2,397 41.2 1,445 51.1

Community-level ethnic homogeneityc

 Not totally homogenous (EFL more than 0) 9,224 87.6 3,512 60.4 2,829 100.0

 Totally homogenous (ELF equal 0) 1,306 12.4 2,299 39.6 2,829 100.0

Community-level child immunization coveraged

 Low 3,670 34.9 2,164 37.2 926 33.8

 Middle 3,501 33.2 1,788 30.8 946 33.4

 High 3,359 31.9 1,860 32.0 2,828 100.0

Cont’d..
78 

APPENDIX Table 2: Cont’d

Tanzania Uganda Zambia 

Characteristics Number % Number % Number %

Number of children 8,725 100.0 8,423 100.0 6,435 100.0

Individual-level variables

Birth order and preceding birth interval

 First birth 1,922 22.1 1,450 17.2 1,270 19.8

 2-3 and < 24 months 503 5.8 658 7.8 348 5.4

 2-3 and 24+ months 2,620 30.1 1,749 20.8 1,866 29.1

 4+ and < 24 months 586 6.7 1,097 13.0 437 6.8

 4+ and 24+ months 3,072 35.3 3,458 41.1 2,496 38.9

Child's sex

 Female 4,347 49.8 4,243 50.4 3,231 50.2

 Male 4,377 50.2 4,180 49.6 3,204 49.8

Mother's age at child's birth

 Less than 20 years 1,502 17.2 1,436 17.0 1,102 17.1

 20-34 years 6,153 70.5 5,857 69.5 4,485 69.7

 35 years or more 1,070 12.3 1,131 13.4 849 13.2

Mother's education

 No education 2,318 26.6 1,910 22.7 870 13.5

 Primary 6,020 69.0 5,358 63.6 4,089 63.5

 Secondary or higher 387 4.4 1,155 13.7 1,477 22.9

Household wealth Index

 1st quintile (Poorest) 1,974 22.6 1,893 22.5 1,524 23.7

 2nd quintile 1,857 21.3 1,900 22.6 1,445 22.4

 3rd quintile 1,866 21.4 1,676 19.9 1,351 21.0

 4th quintile 1,681 19.3 1,604 19.0 1,227 19.1

 5th quintile (Richest) 1,347 15.4 1,351 16.0 889 13.8

Place of delivery

 Home/Other 4,599 52.8 4,870 57.9 3,325 51.8

 Health facility 4,115 47.2 3,539 42.1 3,092 48.2

Skilled attendant at delivery

 Other (incl. none) 5,030 57.8 4,889 58.1 3,491 54.4

 Doctor, nurse, or midwife 3,677 42.2 3,526 41.9 2,924 45.6

Community-level variables

Place of residence

 Rural 7,034 80.6 7,470 88.7 4,553 70.7

 Urban 1,691 19.4 953 11.3 1,883 29.3

Community-level socio-economic statusa

 Low 4,174 47.8 4,421 52.5 2,969 46.1

 High 4,551 52.2 4,002 47.5 3,466 53.9

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low 6,361 72.9 4,125 49.0 3,407 52.9

 High 2,364 27.1 4,298 51.0 3,028 47.1

Community-level ethnic homogeneityc

 Not totally homogenous (EFL more than 0) 8,725 100.0 8,423 100.0 5,664 88.0

 Totally homogenous (ELF equal 0) 8,725 100.0 8,423 100.0 771 12.0

Community-level child immunization coveraged

 Low 2,944 33.7 2,811 33.4 2,276 35.4

 Middle 2,924 33.5 2,827 33.6 2,066 32.1

 High 8,725 100.0 8,423 100.0 2,093 32.5

Cont’d..
79 

APPENDIX Table 2: Cont’d

Zimbabwe 

Characteristics Number %

Number of children 5,231 100.0

Individual-level variables

Birth order and preceding birth interval

 First birth 1,654 31.7

 2-3 and < 24 months 208 4.0

 2-3 and 24+ months 1,988 38.1

 4+ and < 24 months 159 3.1

 4+ and 24+ months 1,210 23.2

Child's sex

 Female 2,563 49.0

 Male 2,668 51.0

Mother's age at child's birth

 Less than 20 years 1,070 20.5

 20-34 years 3,668 70.1

 35 years or more 492 9.4

Mother's education

 No education 213 4.1

 Primary 1,922 36.7

 Secondary or higher 3,096 59.2

Household wealth Index

 1st quintile (Poorest) 1,296 24.8

 2nd quintile 1,093 20.9

 3rd quintile 911 17.4

 4th quintile 1,091 20.9

 5th quintile (Richest) 839 16.0

Place of delivery

 Home/Other 1,627 31.2

 Health facility 3,595 68.8

Skilled attendant at delivery

 Other (incl. none) 1,637 31.4

 Doctor, nurse, or midwife 3,583 68.6

Community-level variables

Place of residence

 Rural 3,718 71.1

 Urban 1,513 28.9

Community-level socio-economic statusa

 Low 2,767 52.9

 High 2,464 47.1

Proportion of women aged 15-49 in the community with secondary or higher educationb

 Low 2,489 47.6

 High 2,742 52.4

Community-level ethnic homogeneityc

 Not totally homogenous (EFL more than 0) 5,231 100.0

 Totally homogenous (ELF equal 0) 5,231 100.0

Community-level child immunization coveraged

 Low 1,999 38.2

 Middle 1,575 30.1

 High 5,231 100.0

Cont’d..
80 

APPENDIX Table 2: Cont’d

Note: Percentages may not add to 100 because of missing values. 

1 Weighted percentage. Figures were calculated using appropriate individual country weights.

n/a = Not available. Item not measured

a Proportion of households poor (two lowest wealth quintiles) in the community. 

b Dichotomous variables indicating whether the proportion of women aged 15-49 in the community with secondary 

or higher education is high or low (cut-off at mean proportion).

c Based on the measures of the ethno-linguistic fractionalization index (EFL), defined as the probability that two 

individuals selected at random from primary sampling unit, will be from different ethnic groups. Theoretically, for 

each cluster, the scale goes from 0 (totally homogenous) to 1 (complete diversity). For the purposes of the present 

analysis, the resulting scale ethno-linguistic fractionalization Index was then classified into dichotomous variables 

indicating whether the ethnic composition of the community is totally homogenous (ELF equal 0) categorized as 1; if 

cluster is not totally homogenous (EFL more than 0), then categorized as 0.

d Percentage of children who received full immunization in the community (Child has received BCG, measles, and 

three doses of DPT and polio vaccines).