DHS METHODOLOGICAL 

REPORTS 13

AN ASSESSMENT OF DHS

MATERNAL MORTALITY DATA 

AND ESTIMATES

SEPTEMBER 2014

This publication was produced for review by the United States Agency for International Development. It was prepared by 

Saifuddin Ahmed, Qingfeng Li, and Carolyn Scrafford of Johns Hopkins University and Thomas W. Pullum of ICF International.

DHS Methodological Reports No. 13 

An Assessment of DHS Maternal Mortality Data and Estimates 

Saifuddin Ahmed1

Qingfeng Li1

Carolyn Scrafford1

Thomas W. Pullum2

ICF International 

Rockville, Maryland, USA 

September 2014 

1

 Bloomberg School of Public Health, Johns Hopkins University 

2 The DHS Program 

Corresponding author: Saifuddin Ahmed, Bloomberg School of Public Health, Johns Hopkins University, 

615 N Wolf e Street, MD 21205, U SA; telephone: +1 -410-614-4952; fax: +1-410-955-2303; email: 

sahmed@jhu.edu 
Acknowledgment: We acknowledge the contribution of Stephane Helleringer, Shea Rutstein, and Trevor 

Croft for their helpful review of the preliminary report. We would also like to acknowledge the assistance 

of Sidney Moore for editing and Natalie La Roche for the production of this report. 

Editor: Sidney Moore 

Document Production: Natalie La Roche 

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

Development (USAID) through the MEASURE DHS project (#GPO-C-00-08-000080-00). The views 

expressed are those of the author and do not necessarily reflect the views of USAID or the United States 

Government. 

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

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

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

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

Recommended citation: 

Ahmed, Saifuddin, Qingfeng Li, Carolyn Scrafford, and Thomas W. Pullum. 2014. An Assessment of DHS 

Maternal Mortality Data and Estimates. DHS Methodological Reports No. 13. Rockville, Maryland, USA: 

ICF International. 
iii 

Contents 

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

Figures ........................................................................................................................................................................ vii 

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

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

Executive Summary ..................................................................................................................................................xiii 

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

1.1. Objectives .................................................................................................................................................... 2 

1.2. Methods ....................................................................................................................................................... 3 

2. Contribution of DHS to Global Maternal Mortality Estimations .................................................................... 5 

2.1. Indicators of Maternal Mortality .............................................................................................................. 5 

2.1.1. Maternal Mortality Ratio (MMR) ............................................................................................... 6 

2.1.2. Maternal Mortality Rate (MMRate) ........................................................................................... 6 

2.1.3. Proportion of Female Deaths that are Maternal (PMDF) ......................................................... 6 

2.1.4. Lifetime Risk of Maternal Death (LTR) ..................................................................................... 7 

2.2. Maternal Mortality Measurement Challenges ........................................................................................ 7 

2.3. Use of DHS Data for Global Maternal Mortality Estimations ............................................................. 11

3. Quality of the Sibling History Data ................................................................................................................... 13 

3.1. Completeness of Vital Statistics .............................................................................................................. 13 

3.2. Accuracy and Completeness of Age Reporting ...................................................................................... 21 

4. Quality of Maternal Mortality Data ................................................................................................................. 61 

4.1. Timing of Maternal Deaths ..................................................................................................................... 61 

4.2. Maternal Mortality Estimates ................................................................................................................. 85 

4.3. Risk of Maternal Mortality Underreporting ....................................................................................... 103 

4.4. Completeness of Adult Death Reporting in Sibling History Module ................................................. 113 

5. Conclusions ....................................................................................................................................................... 125 

References ................................................................................................................................................................ 129 

Appendix .................................................................................................................................................................. 133 

v 

Tables 

Table 1.1 DHS survey countries included in this assessment of maternal mortality by number of survey 

rounds carried out in each country, 1990-2013 .......................................................................................... 2

Table 3.1 Percentage of siblings with unknown sex reporting, Demographic and Health Surveys 1990-2013 ....... 13

Table 3.2 Percentage of siblings with unknown survival status, Demographic and Health Surveys 1990-2013 ..... 18

Table 3.3 Digit preference in age reporting of surviving siblings according to the Whipple Index, 

Demographic and Health Surveys 1990-2013 ......................................................................................... 22

Table 3.4 Percentage of surviving siblings with current age missing by sex, Demographic and Health Surveys 

1990-2013 ................................................................................................................................................ 28

Table 3.5 Percentage of dead siblings with missing age at death and missing years since death, Demographic 

and Health Surveys 1990-2013 ................................................................................................................ 33

Table 3.6 Mean parity of mothers of respondents by age of respondent, Demographic and Health Surveys 

1990-2013 ................................................................................................................................................ 51

Table 3.7 Percent distribution of age of female respondents and their sisters, Demographic and Health Surveys 

1990-2013 ................................................................................................................................................ 55

Table 4.1 Percentage of adult female deaths with missing data on timing of maternal deaths, Demographic and 

Health Surveys 1990-2013 ....................................................................................................................... 61

Table 4.2 Percent distribution of timing of maternal deaths (during pregnancy, during delivery, during the 

postpartum period), Demographic and Health Surveys 1990-2013 ......................................................... 67 

Table 4.3 Percent distribution of timing of maternal deaths (during pregnancy, during delivery, during the 

postpartum period) according to two recall periods before survey (recent: 0-6 years; distant: 

7-13 years), Demographic and Health Surveys 1990-2013 ..................................................................... 76

Table 4.4 Estimates of maternal mortality rates (MMRates) and maternal mortality ratios (MMRs) with 95% 

confidence internals (CI) from 106 Demographic and Health Surveys 1990-2013 ................................. 85

Table 4.5 Extent of missing responses on timing of death for ascertainment of maternal mortality in 105 

Demographic and Health Surveys 1990-2013 ......................................................................................... 90

Table 4.6 Comparison of MMR estimates from imputation and complete case analysis using DHS data, 

Demographic and Health Surveys 1990-2013 ......................................................................................... 93

Table 4.7 Percentage distribution of maternal deaths and births (expected births among sisters) by age, 

Demographic and Health Surveys 1990-2013 ....................................................................................... 104

Table A.1 DHS country code list for the selected countries included in the report ................................................ 133

Table A.2 The distribution of reported timing of death before survey among sisters listed as dead in the sibling 

survival history (unweighted analysis), Demographic and Health Survey 1990-2013 .......................... 134

vii 

Figures 

Figure 3.1 Trends in reporting of missing sex of siblings by DHS survey rounds, Demographic and 

Health Surveys 1990-2013 ..................................................................................................................... 17

Figure 3.2 Percentage of siblings with missing survival status by sex, Demographic and Health Surveys 

1990-2013 .............................................................................................................................................. 21

Figure 3.3 Whipple Index values for digit preference in age reporting of surviving siblings by sex, 

Demographic and Health Surveys 1990-2013 ........................................................................................ 25

Figure 3.4 Trends in the Whipple Index for digit preference in age reporting of surviving siblings by sex and 

DHS survey rounds, Demographic and Health Surveys 1990-2013 ...................................................... 27

Figure 3.5 Percentage of living siblings with reported age missing by sex, Demographic and Health Surveys 

1990-2013 .............................................................................................................................................. 31

Figure 3.6 Trends in missing age for surviving sisters by DHS survey rounds, Demographic and Health 

Surveys 1990-2013 ................................................................................................................................. 32

Figure 3.7 Percentage of dead siblings with age imputed by timing of death (number of years ago death 

occurred), Demographic and Health Surveys 1990-2013 ...................................................................... 45

Figure 3.8 Distribution of mean parity of mothers of respondents by age of respondents, according to survey 

round, Demographic and Health Surveys 1990-2013 ............................................................................ 54

Figure 4.1 Percentage of adult female deaths with missing data on pregnancy status during the timing of death 

by recall period, Demographic and Health Surveys 1990-2013 ............................................................. 64

Figure 4.2 Trends in missing data on pregnancy status during the timing of death for sisters who died 0-6 years 

before the survey, Demographic and Health Surveys 1990-2013 .......................................................... 66

Figure 4.3 Distribution of timing of maternal deaths (during pregnancy, during delivery, during the postpartum 

period), Demographic and Health Surveys 1990-2013 .......................................................................... 71

Figure 4.4 Distribution of the timing of maternal deaths by DHS survey rounds, Demographic and Health 

Surveys 1990-2013 ................................................................................................................................. 74

Figure 4.5 Distribution of timing of maternal deaths (during pregnancy, during delivery, during the postpartum 

period) by recall periods: recent (0-6 years) and distant (7-13 years), Demographic and Health 

Surveys 1990-2013 ................................................................................................................................. 82

Figure 4.6 Relative margin-of-error by MMR estimates, Demographic and Heath Surveys 1990-2013 ................ 88

Figure 4.7 Comparison of five methods for estimating MMR (DHS method, complete case analysis, weighting 

for non-response, single imputation with hot deck method, and multiple imputation method), 

DHS data from sub-Saharan Africa, Demographic and Health Surveys 1990-2013 .............................. 97

Figure 4.8 Trends in the proportion of maternal deaths among female deaths (PMDF) and the maternal 

mortality ratio (MMR) by DHS survey rounds, Demographic and Health Surveys 1990-2013 .......... 102

Figure 4.9 Percentage distribution of maternal deaths and births (expected births among sisters) by age, 

Demographic and Health Surveys 1990-2013 ...................................................................................... 110

Figure 4.10 Death reporting completeness diagnostic plots using the Brass Growth Balance Method, 

Demographic and Heath Surveys 1990-2013 ....................................................................................... 114

Figure A.1 Listing table of household members who had died in recent period, BMMS 2001 ............................. 137

Figure A.2 Maternal death concentration curve, Demographic and Heath Surveys 1990-2013 ............................ 138 

ix 

Preface 

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

on fertility, family planning, m aternal and child health, nutrition, mortality, environmental health, 

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

One of the objectives of The DHS Program is to continually assess and improve the methodology and 

procedures used to carry out national-l evel surveys as well as t o offer additional tools for analy sis. 

Improvements in methods used will enhance the accuracy and depth of information collected by The DHS 

Program and relied on by policymakers and program managers in low- and middle-income countries. 

While data quality is a main top ic of the DHS Methodological Reports series, the reports also examine 

issues of sampling, questionnaire comparability, survey procedures, and methodological approaches. The 

topics explored in this series are selected by The DHS Program in consultation with the U.S. Agency for 

International Development. 

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

specialists, particularly those engaged in work i n low- and middle-income countries, and will be used t o 

enhance the quality and analysis of survey data. 

Sunita Kishor 

Director, The DHS Program 

xi 

Abstract 

This report evaluates the data quality of sibling survival history in DHS surveys and assesses its impact on 

maternal mortality estimates. The data are from 112 surveys conducted between 1990 and 2013; the surveys 

all included a sibling history module. We examined three aspects of data quality: completeness in sibling 

death reporting, completeness in reporting of all siblings and their age; and completeness in reporting of 

time of death during a calendar year and pregnancy status at the time of death. The overall quality of sibling 

history data is similar to the quality of data of individual women respondents in terms of age-misreporting. 

Reporting deaths in relation to preg nancy status and placing the deaths to calendar time rem ain major 

challenges for the respondents. The classification of maternal death relies on the reported timing of a sister’s 

death in relation to her pregnancy, delivery, and postpartum period. Many countries had very high nonresponse rates (10%-40%) for pregnancy status at the time of death, a situation that introduces substantial 

misclassification bias into identification of m aternal deaths. DH S surveys currently report maternal 

mortality estimates without any adjustment for missing responses to timing of death. This may substantially 

underestimate the maternal mortality ratio (MMR) and other maternal mortality indicators in countries with 

high non-response rates. Trend analy sis, however, s uggests that the m issing responses have declined 

significantly in the recent rounds of DHS survey s. We recommend developing a standard protocol for 

handling missing data on maternal status at the time of death and adjusting m aternal mortality estimates 

with an appropriate statistical method for handling missing data. 

KEY WORDS: maternal mortality, sibling survival history, sisterhood method, data quality 

xiii 

Executive Summary 

The Demographic and Health Surveys (DHS) remain the main source of empirical data for estimation of 

maternal mortality in developing countries. Through the direct sisterhood method, maternal mortality ratios 

(MMRs) are calculated u sing DHS data fro m sibling histories provided by survey respondents. For 

classification of female deaths as maternal deaths, this method relies on the reported tim ing of a sister’ s 

death in relation to her pregnancy, delivery, and postpartum period. The two main objectives of this report 

were to examine the qualit y of the sibling history data collected by DHS and to evaluate the extent of 

underestimation bias associated with MMRs produced from DHS data. 

In recent years, DHS has i mplemented a sibling surv ival history module for male respondents. The data 

from male respondents were not included in this analysis because they are not included in the DHS country 

reports. Moreover, the DH S maternal mortality data used by United Nations (UN) organizations (World 

Health Organization, United Nations Children’s Fund, United Nations Population Fund, and the World 

Bank) and the Institute for Health Metrics and Evaluation (IHME) to estimate global trends are limited to 

the female respondents. 

We examined the completeness of reporting of vital events, age, timing of death in relation to the calendar, 

and timing of death in relation to m aternal status (during pregnancy, during delivery, or during the 

postpartum period), which are the data used to ascertain maternal death. 

Our extensive analyses suggest that the overall quality of sibling history data is similar to the quality of 

data from individual respondents (women age 15-45) in DHS surveys in terms of age-reporting (e.g., ageheaping, missing in reported age and date of birth and age-displacement). We did not find any discerning 

patterns of sister underreporting or age-displacement to avoid responding to the questions on female deaths. 

Similarly, our findings did not suggest higher female death underreporting, in comparison to male deaths. 

However, reporting events and placing the events to calendar tim e remain major challenges by the 

respondents based on recall of memory. This was a problem for deaths in both recent and distant past 

periods. The examination of the countries with multiple rounds of DHS surveys suggests that the response 

rate improved significantly in recent DHS survey rounds in most countries. 

One of our key interests was to exa mine the i mpact of missing responses for clas sification of death 

(maternal or non-maternal) in MMR estimates. This was done by comparing MMR estimates based on the 

standard DHS method with MMR estimates adjusted for missing data. We used four statistical methods for 

analyzing data with missing values: c omplete case analysis, weighting for non-response rate, single 

imputation with hot deck, and multiple imputation methods.

Many countries reported very high non-response rates (10%-40%) for pregnancy status at the time of death, 

a situation that introduces substantial misclassification bias into identification of m aternal deaths. The 

MMR estimates for the standard DHS method (sisterhood method) and the complete case analysis method 

(with non-responses on maternal death classification questions removed) were compared and found to be 

similar—country average MMR: 531 deaths per 100,000 live births—indicating likely similar bias in the 

presence of high non-response rates for pregnancy status at the time of death. In contrast, all other methods 

(weighting, hot deck, and multiple imputations) show considerably higher MMR estimates (country average 

MMR 596, 605 and 609, respectively), suggesting substantial underestimation bias in the MMR values in 

DHS reports, specifically in countries with high non-response rates on the timing of female deaths.

Current reporting in DHS countr y reports substantially underestimates maternal mortality in several 

developing countries. Appropriate correction for non-response regarding the timing of female deaths may 

reduce the underestimation bias associated with DHS maternal mortality estimates. 
xiv 

Confidence interval of MMR estimates was quite large in most DHS surveys. The relative margin-of-error 

of MMR varied from 20% to 40% in most (71.3%) DHS surveys. All surveys have more than 10% relative 

margin-of-error (RME). Countries with low MMR had higher relative margin-of-errors. Given such a large 

margin-of-error, it will remain a challenge to track MDG 5 progress in reducing maternal mortality 75% by 

2015 in a co untry using DHS data alone. However, by applying modeling techniques, th e Maternal 

Mortality Estimation Interagency Group (MMEIG)—consisting of WHO/UNICEF/UNFPA and the World 

Bank—and the Institute for Health Metrics and Ev aluation (IHME) have successfully utilized the DHS 

sisterhood data for tracking global maternal mortality trends. Recent studies from these two organizations 

have consistently indicated that maternal mortality has declined substantially since 1990. It was possible to 

track such a remarkable achievement because of the availability of empirical MMR data from DHS surveys. 

While the overall value of DHS maternal mortality estimates is undeniable, our examination of the quality 

of data and estim ation methods suggests that ther e are additional opport unities for improving maternal 

mortality estimates in DHS surveys. We provide few recommendations in the report for improving sibling 

survival history module and addressing challenges of underestimation of MMR in DHS surveys. 
1 

1. Introduction 

At the Millennium Summit in Septem ber 2000, the Millennium Development Goals (MDGs) were 

developed by nations and world leaders to inspire cooperation and partnership to reduce extreme poverty 

and improve the status of health, education, and the environment of the global community (UN General 

Assembly 2000). Specific time-bound targets were established with an achievement deadline of 2015. The 

achievement of these targets is being measured using established indicators of health and poverty. With 

2015 quickly approaching, the accura te and standardized measurement of indicators becomes even m ore 

important to ensure and confirm that the goals have been achieved and to identify countries and populations 

that are still exposed to poverty and poor health conditions, thereby allowing a focused aid effort in these 

areas. 

The fifth of the eight MDGs is to im prove maternal health (MDG 5) with a key indicator to measure this 

goal identified as the maternal mortality ratio (MMR), a ratio of the number of maternal deaths that occur 

for every 100,000 live births. The target established at the Millennium Summit was to reduce the MMR by 

three-quarters between 1990 and 2015. 

Accurate estimation of maternal mortality, particularly in developing countries, is made difficult by the lack 

of complete vital registration systems. The evaluation of safe motherhood programs and the monitoring of 

progress in achieving Millennium Development Goal-5 (MDG 5)—reducing the m aternal mortality ratio 

by three-quarters between 1990 and 2015—rem ains a major challenge because of difficulties measuring 

maternal mortality in the face of weak information systems. Only 60% of 230 countries have at least 90% 

birth registration coverage, and only 47% of countries have at least 90% death registration coverage (United 

Nations 2014). According to the World Health Organizations (WHO), more than 100 developing countries 

do not have a functioning vital registration s ystem (WHO 2014). Even where a good vital registration 

system is available, as in most developed countri es, misclassification and underesti mation of maternal 

mortality is common. 

In the absence of complete vital registration with good attribution of causes of deaths, the most commonly 

employed methods for estimation of maternal mortality are household surveys with direct death inquiry, 

indirect and direct sisterhood methods, and reproductive age mortality surveys (RAMOS). For countries 

that have no data available on maternal mortality, regression-based methods are used to estimate maternal 

mortality (Graham et al. 2008b). 

The Demographic and Health Surve ys (DHS) Progra m has long been the primary source of data and 

information to monitor and track key indicators of a country’s health status through its population. With 

the launch of the Safe Motherhood I nitiative in 1987 a nd the subsequent increased interest i n maternal 

health and mortality, DHS responded the following year by introducing the maternal mortality module to 

the DHS questionnaire. Since 1988, the maternal mortality module has been implemented in 60 countries, 

representing all regions, including 39 countries in sub- Saharan Africa, 15 countries in North Africa/West 

Asia/Europe, and 6 countr ies in Latin America and the Caribbean. Further, a num ber of countries have 

collected data on maternal health and mortality in more than one survey round, allowing governments and 

donor agencies to track and measure a country’s progress toward achieving MDG 5 (Arifeen et al. 2014). 

Through modeling, the MMR estimates from the DHS survey data are also used by WHO/UNICEF/UNFPA 

and the World Bank and by the Institute for Health Metrics and Evaluation (I HME) for tracking global 

progress in reaching MDG 5. For several of the developing countries, the first DHS survey was conducted 

only recently, thus providing valuable insight into the maternal health status of the female population in the 

countries for the first time. Prior to t he DHS survey , information about m aternal deaths was largely 

unknown or was estimated using complex modeling. 
2 

1.1. Objectives 

The purpose of this report was to assess the data qua lity bias in estimates of the indicators of maternal 

mortality in the DHS survey s. The re port updates the previous assessment conducted by Stanton, 

Abderrahim, and Hill in 1997 (Stanton et al. 1997), which examined data from 14 DHS surveys conducted 

between 1989 and 1995. A further aim of this stu dy was to exa mine whether some of the deficienci es 

identified in the earlier report were resolved in subsequent survey rounds. 

This report is based on analy sis of data from 112 DHS surveys (in 46 countries) for which standardized 

data on sibling history were publicly available. These surveys were conducted between 1990 and 2012, 

which covered the five phases of DHS survey implementation: DHS-II (1989-93), DHS-III (1993-1997), 

MEASURE DHS+ (1997-2003), MEASURE DHS (2003- 2008), and MEASURE DHS Phase-III (2008-

2013). For purposes of chronological ordering in this report, the last three phases are r eferred to as DHSIV, DHS-V and DHS-VI, respectively. 

Of the 112 surveys included in this report, the number in each DHS phase is as follows: DHS-II (8 surveys), 

DHS-III (28 surveys), DHS-IV (28 surveys), DHS-V (28 surveys), and DHS-VI (20 surveys). Thirteen of 

the 46 countries have only one round of survey data, 11 countries have two rounds, 15 countries have three 

rounds, and five countries have four rounds of survey data. Indonesia is the only country with five rounds 

of survey data. In general, DHS surveys are conducted every five years in many countries. An exception is 

Peru, where surveys are conducted every year on a rolling sampling plan. In this report, we have included 

seven rounds of sur vey data from Peru. Table 1.1 shows the countries included in this a ssessment of 

maternal mortality and the number of survey rounds carried out in each country. 

Table 1.1 DHS survey countries included in this assessment of maternal mortality by number of 

survey rounds carried out in each country, 1990-2013 

Number of survey rounds

1 2 3 4 5 7* 

Brazil Benin Bolivia Madagascar Indonesia Peru

Burundi Chad Burkina Faso Malawi

Central African 

Republic 

Congo 

(Brazzaville) 

Cambodia Mali 

Congo Dem. 

Republic 

Dominican 

Republic 

Cameroon Uganda 

Guatemala Gabon Côte d’Ivoire Zimbabwe

Jordan Haiti Ethiopia

Liberia Lesotho Guinea

São Tomé and 

Príncipe 

Morocco Kenya 

Sierra Leone Nepal Mozambique

South Africa Nigeria Namibia 

Swaziland Philippines Niger 

Timor-Leste Rwanda Senegal 

Togo Tanzania 

 Zambia 

*Rolling sampling survey 
3 

On occasions, the DHS Program had implemented dedicated survey s aiming at exam ining maternal 

mortality and morbidities in some countries. Some examples are Bangladesh Maternal Mortality and Health 

Care Surveys in 2001 and 2010, Afghanistan Mortality Survey 2010, and Ghana Maternal Health Surve y 

2007. These surveys used different study instruments, including verbal autopsy, and were based on ve ry 

large sample size. The data from these specialized surveys were not included in the analysis for this report. 

In recent years, DHS implemented a sibling survival history module in the surveys of men (Merdad, Hill, 

and Graham 2013). Considering that the maternal mortality data from the surveys of women are currently 

included in DHS country reports and used b y the Maternal Mortalit y Estimation Interagency Group 

(MMEIG), consisting of WHO/UNICEF/UNFPA and the World Bank, and by the Institute for Health 

Metrics and Evaluation (IHME)—the two agencies that routinely report global maternal mortality—we 

limit our analysis of data for this report to women respondents only. 

1.2. Methods 

The valid estimation of maternal mortality requires accurate and complete reporting of the events (deaths 

due to maternal causes) among at-risk women (age 15-49) during a reference calendar period. To ascertain 

the quality of DHS data for maternal mortality estimation, we examined three related aspects of research: 

(1) completeness in sibling death reporting, (2) comple teness in reporting of all sisters and their age, and 

(3) completeness in reporting of the time of death during a calendar year. 

Completeness of sibling death reporting 

Maternal mortality is a subset of deaths from any cause. We examined the completeness of death reporting 

from any cause by the Br ass growth balance method (Brass 1975). We com pared the completeness o f 

reporting between male (brothers) and fem ale (sisters) populations to ascertai n whether there wer e any 

systematic biases (underreporting) in the reporting of death from any cause for females. 

Completeness of reporting of sisters and their age 

A comparison of the age structure of sisters to that of respondents was conducted to assess any possibility 

of age coverage errors, age-displacement, and/or underreporting of sisters. We estimated the Whipple Index 

for assessing digit preference in age reporting. We also examined the underreporting (under-enumeration) 

of siblings by comparing the respons es in the sib ling history records with the parit y distribution of 

respondents’ mothers. 

Completeness of reporting time of death and other vital events 

Studies suggest that maternal mortality risk is higher at younger and older ages t han at mid-reproductive 

ages between 20 and 40 years. We compared the age-specific distribution of deaths to the age-specifi c 

distribution of births for assessing the underreporting of deaths at the extremes of the repr oductive age 

boundary. 

Missing data are a common problem in surveys. This may be due to non-response to some questions by 

respondents. Some subjects may decline to provide values deliberately for fear of confidentiality or lack of 

appropriate knowledge. Missing data reduce the statistical power of the study and may introduce bias. We 

examined missingness in the reporting of vital events, age, calendar period of death, and timing of death in 

relation to pregnancy (during pregnancy, during delivery, or during the postpartum period). In statistical 

literature, missingness refers to the overall status of missing response or incomplete data/variables in the 

data set. 
4 

Adjustment for missing data on time of death in relation to pregnancy 

We applied four statistical methods for assessing the impact of underestimation bias (fr om missing 

responses) in estimates of the maternal mortality ratio (MMR). We compared the MMR estimates from the 

standard DHS method to a) complete case analysis (missing cases dropped from analysis), b) weighting for 

non-response (inversely weighted by the response rate which inflated the maternal death proportions by the 

extent of missingness), c) single imputation with hot deck method, and (d) multiple imputations method. 

Gakidou and King (2006) propose to apply a weighting method for correcting mortality selectivity bias 

when using the sisterhood method for mortality estimation because of the lower selection probability of 

sibships with high m ortality. Moreover, women who have died with no s urviving sister have zero 

probability of selection in the sisterhood sampling scheme, which may also introduce underestimation bias. 

Gakidou and King suggest correcting such selectivit y bias though weighting. However, subsequent 

simulation work shows that the application of such weighting overestimates mortality (Masquelier 2013). 

A similar weighting scheme applied by Ober meyer et al . (2010) also increas ed the mortality estimates 

substantially. Earlier, Trussell and Rodriguez (1990) had shown that maternal mortality estimates obtained 

by the DHS method are unbiased because of co mpensating mechanisms in the sister hood method: 

underestimation bias due to the non-inclusion of zer o surviving sisters is co mpensated for by the 

overestimation risk of excluding the surviving respondents, under the assumption that the mortality risks of 

the sisters are independen t. Reniers, Masquelier, and Gerland (2011) consider that the adj ustment with 

weighting is controversial and prefer to use u nweighted data. In this rep ort, we have not applied a ny 

weighting correction for s electivity bias, if any . However, we have used survey design w eights in t he 

analysis to yield the correct population representation of the sample. 
5 

2. Contribution of DHS to Global Maternal Mortality 

Estimations 

The Demographic and Health Surveys (DHS) Program collects data that allow for the calculation of several 

indicators of maternal mortality including the maternal mortality ratio (MMR), the maternal mortality rate

(MMRate), the proportion of maternal mortality among all adult female deaths (PMDF), and a woman’s 

lifetime risk of maternal death (LTR). These indicators and the data required to calculate and measure each 

are summarized below. 

2.1. Indicators of Maternal Mortality 

To standardize the measurement and calculation of maternal mortality indicators, determining the timing of 

death in relation to the woman’s pregnancy is critical. The following definitions are used to help define and 

measure maternal mortality (WHO 2011): 

Maternal death: A maternal death is the death of a woman while pregnant or within 42 days of termination 

of pregnancy, irrespective of the duration and the s ite of the pregnanc y, from any cause related to or 

aggravated by the pregnancy or its management, but not from accidental or incidental causes. 

Pregnancy-related death: A pregnancy-related death is the death of a woman while pregnant or within 42 

days of termination of pregnancy, irrespective of cause. Technically, DHS data provide pregnancy-related 

deaths, not maternal deaths. 

Late pregnancy-related death: A late pregnancy -related death is the death o f a woman from direct or 

indirect obstetric causes more than 42 da ys but l ess than one year after ter mination of pregnanc y. 

Pregnancy-related death and late pregnancy-related death definitions were introduced in the Tenth Revision 

of the International Classification of Diseases (ICD-10). 

A true mater nal death requires specific cause of d eath information while pr egnancy-related and late 

pregnancy-related deaths are defined on the basis of the tim ing of death with regards to the wo man’s 

pregnancy and delivery, irrespective of the relations hip between the cause of death and the pregnanc y. 

Therefore, accidental deaths or deaths due to viol ence that may or may not have occurred because of the 

condition of being pregnant will be included in the pregnancy-related death categories but not as maternal 

deaths. 

A significant interest has emerged in recent years regarding the late-pregnancy related deaths, especially in 

developed countries, after recognizing that about 14 % of pregnancy-related deaths in the United States 

occurred after 42 days but before 365 days of delivery (Berg et al. 2010). DHS surveys do not collect late 

pregnancy-related death information. 

In addition to data on the cause or timing of death of a woman during pregnancy, childbirth, and postpartum, 

information on fertility measures within the population are needed for maternal mortality indicators. Birth 

histories enable estimation of the number of live births and the general fertility rate (GFR) and are routinely 

collected as part of the DHS questionnaire. 

Using the definitions just described, the following indicators of maternal mortality can be calculated. 
6 

2.1.1. Maternal Mortality Ratio (MMR) 

The maternal mortality ratio (MMR) is the most commonly used indicator of maternal mortality and is 

defined as the number of maternal deaths per 100,000 live births: 

ݏhݐ݀݁ܽ	݈݊ܽݎ݁ݐ݉ܽ	݂݋	ݎܾ݉݁ݑܰ

݋݅ݐܴܽܯܯ = 100,000	ݔ		 ݏhݐݎܾ݅	݁ݒ݈݅	݂݋	ݎܾ݉݁ݑܰ

By definition, the MMR limits measurement of the risk of m aternal death to those deaths due to obstetric 

causes by expressing the relationship per number of live births as opposed to per women of childbearing 

age. Therefore, it expresses the risk of maternal death based on the frequency of childbearing. However, 

because data are limited or nonexistent on the number of pregnancies that do not end in a live birth, this 

also means that the MMR will overestimate obstetric risk by underestimating the number of pregnancies 

during which a woman is at risk of maternal death. Further, the MMRatio between countries or populations 

cannot be compared because the measure is not standardized to the age distribution within a country. 

2.1.2. Maternal Mortality Rate (MMRate) 

The maternal mortality rate (MMRate) is a measure of the risk of maternal death to a woman of reproductive 

age, typically defined as 15-49 years of age. 

ݏhݐ݀݁ܽ	݈݊ܽݎ݁ݐ݉ܽ	݂݋	ݎܾ݉݁ݑܰ

݁ݐܴܽܯܯ = 1000	ݔ	 49 − 15	ܽ݃݁	݉݁݊݋ݓ	݂݋	ݎܾ݉݁ݑܰ

This measure is clearly related to the number of pregnancies within a population for which a woman is at 

risk of maternal death yet it does not directly account or adjust for the fertility rate within a country and 

therefore is not directly comparable between countries. However, it does reflect the magnitude of the burden 

of maternal deaths as a cause of death among women. 

DHS estimates the maternal mortality rate using the following formula: 

ݏhݐ݀݁ܽ	݈݊ܽݎ݁ݐ݉ܽ	݂݋	ݎܾ݉݁ݑ݊

number	of	woman		person-years 	ݔ	1000 = ܯܯܴܽݐ݁

The MMRate and MMRatio can be calculated from each other by applying the general fertility rate (GFR) 

in a country and using the following formula: 

݁ݐܴܽܯܯ

݋݅ݐܴܽܯܯ = ܴܨܩ

The GFR is the ratio of live births to women age 15-49. 

2.1.3. Proportion of Female Deaths that are Maternal (PMDF) 

The proportion of maternal deaths among fem ales of reproductive age is a t hird indicator that provides 

information about the burden of maternal deaths compared to all other causes of death among women age 

15-49. This indicator is defined as follows: 

ݏhݐ݀݁ܽ	݈݊ܽݎ݁ݐ݉ܽ	݂݋	ݎܾ݉݁ݑܰ

ܨܦܯܲ = 49 − 15	ܽ݃݁	݉݁݊݋ݓ	݊݃݋ܽ݉	ݏhݐ݀݁ܽ	݂݋	ݎܾ݉݁ݑܰ
7 

2.1.4. Lifetime Risk of Maternal Death (LTR) 

The lifetime risk of maternal death is defined as the risk of a woman dying from maternal causes during the 

35 years of her reproductive lifeti me. It has been described as th e cumulative loss of human life due to 

maternal death over the course of a female life and can be used as an indicator of the im pact of maternal 

mortality in a population (Wilmoth 2009). There is m ore than one way of estimating LTR depending on 

how one defines lifetime risk and the starting point of either birth or 15 years of age. The general consensus 

is that the lifetim e risk of maternal death calcula tion should be conditional on the woman surviving to 

reproductive age (Wilmoth 2009). The equation for LTR that is reported in the DHS country reports is as 

follows: 

ிோ்)ܴܯܯ − 1) = (ܴܶܮ − 1)

2.2. Maternal Mortality Measurement Challenges 

Maternal mortality is one of the m ore difficult indicators to measure and track over tim e because of 

misclassification, sampling error, and non-sam pling error (Graham et al. 2008a). The identification of a 

death as a maternal death is defined based on both ti ming and cause of death. Ideally , maternal mortality 

measurement would be based on complete and accurate death registry records with validated and verified 

cause of death. However, identifying the cause of death as maternal is difficult even in developed countries 

with adequate vital registry systems and is often underreported. This lack of accurate classification of death 

is amplified in developing countries, which may have limited or no vital or civil registry systems to track 

and count deaths in the population. 

There are several opportunities and options for m easuring maternal mortality. Graham et al. (2008b) 

outlined five empirical methods in addition to a brief discussion of analytical methods available including 

statistical modeling and adjustments for known underreporting of deaths and maternal deaths. The empirical 

approaches include the use of data from death regist rations, health facility surveys, censuses, populationbased surveys, surveillance, and com posite approaches that draw on all five sources of data to identify 

female deaths of reproduc tive age, known as the reproductive age mortality studies (RAMOS). These 

empirical approaches all have benefits and drawbacks. The larger, m ore general approaches, such as a 

census providing a limited range of information on the maternal death (e.g., without causes of death), can 

be used to estimate maternal health indicators for a small geographical area, but they are done only every 

10 years. A death registrati on system may be considered the gold standard but is not full y functional in 

most developing countries. In contrast, surve ys or surveillance can provide more maternal mortality 

information in developing countries, but the potential for uncertainty in the estimates due to sampling and 

non-sampling error is larger (Graham et al. 2008b). 

To estimate maternal mortality, the number of maternal deaths over a period of time must be ascertained. 

This enumeration can be done actively or passively depending on the data source. Death registries or health 

facility statistics are based on passive identification of deaths through review of records and the subsequent 

determination of the fraction of those deaths that are maternal or pregnancy related. Active identification is 

conducted in surveys or surveillance through the interview process and active inquiry into deaths and cause 

or timing of death. In general, passive surveillan ce yields estimates that are more prone to non-sampling 

errors, including underreporting (i.e., omissions), and bias due to the underrepresentation of certain 

population subgroups (Graham et al. 2008b). 

Many measurement and sampling techniques rely on pregnancy-related deaths as a surrogate for maternal 

deaths because this estimate only requires the respondent or data gatherer to know the timing of the death 

(in relation to the pregnancy), without regard to the cause of the death. As a result of relying on timing 

alone to estimate maternal deaths, this definition can lead to the inclusion of accidental or incidental deaths 

that have no association with the pregnancy, therefore producing an overestimation of maternal deaths. It 
8 

has been argued, however, that this overestimation is counterbalanced by the inherent underreporting of 

maternal deaths. Further, recent studies have shown that a large portion of the accidental or violent deaths 

among pregnant women may actually be maternal deaths (considering aggravated risk due to pregnancy 

status), thus reducing the impact of overcounting. 

Further compounding the challenges of accurate a nd complete reporting associated with estimating 

maternal mortality is the fact that maternal mortality, relative to child m ortality and many other health 

indicators, is a rare event. Theref ore, to obtain estimate s that do not have extremely wide confidence 

intervals, a large sam ple size is required. For this reason, many of the surve y methods used in current 

practice have to include a very large sample population or else rely on the respondent’s recall over the past 

5 to 7 years in order to obtain enough deaths to estimate maternal mortality. Obtaining a large enough 

sample from a household survey is often costly and therefore may not be considered feasible. In addition, 

the longer the recall perio d prior to the survey, the greater the likelihood of reduced accuracy of age and 

date reporting as well as cause or tim ing of death, although this phenomenon is not strictly the case—for 

example, omission of deaths or siblings from a respondent’s history may be related to factors other tha n 

duration of recall (e.g., age of respondent, migration of sibling). 

Currently, more than 100 developing countries do not have registry systems in place to count the births and 

deaths in their population. Among researchers in the field of maternal mortality, new and enhanced methods 

have been developed to address this dat a gap in resource-poor countries (Graham et al. 2008a; Hill et al. 

2006). Information gathered by censuses and household su rveys that rely on respondent recall of sibling 

births and survival status have been used in many studies that es timate and compare adult and m aternal 

mortality (Blanc et al. 2013; Hogan et al. 2010; Kassebaum et al. 2014). The majority of the country-specific 

DHS modules have used sibling histories to estimate adult mortality for over 20 years. While these histories 

are not the gold standard approach to estimating maternal mortality, evaluations have shown the value and 

validity of these approaches in the absence of vital registry data (Graham et al. 2008b; Hill et al. 2006; 

Merdad et al. 2013), while recent research has provided insight into simple ways to improve the accuracy 

and completeness of the data collected through these methods (Helleringer et al. 2014a; Helleringer et al. 

2014b). 

Descriptions of the methods currently used to measure maternal mortality from survey data in the absence 

of vital registries are summarized here. 

Indirect sisterhood method of estimation 

The sisterhood method of collecting data to calculate maternal mortality is also referred to as t he indirect 

method and was the first method used in t he DHS mate rnal mortality module initiated in 1988. This 

approach is adapted from the method first developed by Graham et al. (1989) to estim ate adult mortality 

indirectly based on the survivorship of siblings. In the DHS, a series of questions was asked of a sample of 

adult respondents regarding their sisters born to the same mother, including (1) how many sisters were evermarried; (2) the vital status of these sisters; and (3) if dead, whether they died while pregnant, during 

childbirth, or during the six weeks following delivery (Graham et al. 1989). The reporting of deaths covers 

a large interval time, and as a result the indirect sisterhood method generates a maternal mortality estimate 

for a period centered around l0-12 years before the survey. Based on this series o f questions, the risk and 

magnitude of pregnancy-related death can be obtai ned; however, “true” maternal mortality cannot be 

estimated because the exact cause of death cannot be ascertained with this level of questioning and recall. 

Therefore, it is solely the timing of the sister’ s death that defines maternal mortality with the indirect 

sisterhood method used in the earliest DHS survey s. The amount of overestimation of maternal mortality 

that this non-cause- specific death variable creates is unclear, ho wever many experts believe that the 

overestimation is minimal. A study in Bangladesh reported that 63 of 304 maternal deaths were misreported 

as non-maternal deaths using the sisterhood method when a comparison was made with surveillance records 

(Shahidullah 1995). Further, the overestim ation that may occur by including potentially non-maternal 
9 

deaths may be compensated for by the fact that some deaths resulting from abortion may not be reported in 

developing countries. Many induced abortions are not reported by women in areas where the procedure is 

restricted or illegal. It may also be tha t the res pondent did not know that he r sister was pregnant and 

therefore, any death that occurred as a result of that pregnancy would not be included in the count of 

maternal deaths (Gerdts et al. 2013). Misclassification and u nderreporting of maternal deaths due to 

abortion was demonstrated by Walker et al. (2004), which showed that second trim ester deaths due to 

abortions were misclassified both as non-abortion-related maternal deaths as well as non-maternal deaths. 

Overall, the direction and amount of the bias in the sisterhood method is unclear from the existing studies. 

Direct sisterhood method of estimation 

The direct estimation of maternal mortality is the method currently used in the DHS maternal mortality 

module and in the datasets included in t his analysis. This method is based on the same principles as the 

indirect method but collects additional data to allo w for the calculation of person-years of exposure time 

necessary for the calculation of age-specific mortality rates. Maternal mortality is still defined based on the 

timing of the sister’s death in relation to pregnancy but includes deaths up to two months after the end of a 

pregnancy, as opposed to six weeks. This revision was made to ease the reporting and recall burden on the 

respondent, with little i mpact on the accuracy of indicators. The DHS maternal mortality module 

questionnaire begins by asking the respondent about brothers and sisters who were born to the respondent’s 

biological mother. The questions are presented in the following order: 

1. How many children did your mother give birth to including you? 

2. If more than one birth (the respondent), how many births occurred before the respondent was born? 

Then for each sibling reported in #2 above, the following questions were asked of the respondent: 

1. What was the name of your oldest brother or sister? 

2. Is that sibling male or female? 

3. Is that sibling still alive? 

4. How old is that sibling? 

5. How many years ago did the sibling die (if applicable)? Some surveys also ask the year the sibling 

died. 

6. How old was the sibling when they died? 

If the sibling was female and dead the following questions were asked: 

1. Was the sibling pregnant? 

2. Did she die during childbirth? 

3. Did she die within two months after the end of a pregnancy or childbirth? 

4. How many live born children did she give birth to during her lifetime? 

An earlier study suggests that completion of the sibling history module takes an average of about 10 minutes 

of the interview (Rutenberg and Sullivan 1991). 
10 

In the earlier DHS rounds, the postpartum period was specified as 6 weeks in several countries, as per the 

ICD-10 definition of m aternal mortality. These coun tries were Namibia (Phase-II), Malawi (Phase-II), 

Philippines (Phase-II), Central African Republic (Phase-III), Zimbabwe (Phase-III), Indonesia (Phase-III, 

IV, and V), and Cam bodia (Phase-V). Subsequently, DHS changed the postpartum period recall duration 

to 2 months, for easier interpretation in developing countries. The exceptions were two countries (Peru and 

Philippines) where an open-ended question was asked on when the sister’s death occurred: How long after 

giving birth to her last child did (NAME) die? 

Nine surveys in six countries (Côte d’Ivoire, Indonesia, Jordan, Morocco, Peru, Senegal) collected data on 

the marital status of t he siblings. In selected countries, the information on maternal-related deaths was 

collected for married sisters only. 

Both the indirect and direct methods include all pregnancy-related deaths as maternal deaths. However, the 

direct method also requir es and assu mes that the respondent can report accurately on the age of living 

siblings and the age at death and years since death for dead siblings. This is a big assumption, especially 

for those siblings that are the youngest of the family and may not remember or know about siblings that 

were born and died either before they were born or when they were too young to remember. Further, being 

aware of the pregnanc y status and timing of sibl ings requires significant recall as well. A previous 

evaluation of the direct sisterhood m ethod used by DHS reported relative errors in matern al mortality 

estimates of 15% across 13 countries (14 surveys) when the recall period was 0 to 6 years before the survey; 

errors were higher when the recall period was 7 to 13 years (Stanton et al. 2000). 

The underreporting of siblings as well as deaths of si blings is common using this method. As mentioned 

above, the age of the respondent will affect the accuracy of the estimate. A recent record linkage study in 

Senegal noted that additional reasons for omission of siblings in a respondent’ s history include whether 

they were deceased, had migrated away from the home, had a different biological father than the respondent, 

or had never lived with the responde nt (Helleinger et al. 2014a). In this study, 9.1% of deceased sisters 

were omitted from the history in addition to 16.6% of the sisters that had migrated out of the area. Reasons 

for omission of siblings fr om a respondent’s history vary from country to country depending on cultural 

norms (e.g., matrilineal versus patrilineal social struct ure). It is also possible to overcount siblings by 

including those who were adopted into the family or of a different mother but the same father. 

A recent evaluation of the sisterhood method—using a modified version of the DHS questionnaire including 

a siblings’ survival calendar (SSC)—was conducted in Senegal with respondents from the Niakhar Health 

and Demographic Surveillance Sy stem (Helleringer et al. 2014b). The retrospective validation st udy 

randomly assigned respondents to be interviewed with either the DHS questionnaire or the SSC. The SSC 

included (1) prompting cues to help pr obe respondents for omitted siblings and (2) a calendar based on 

national landmark events to help with timing of death and age at death. Comparing the results, more female 

deaths were reported using the SSC (89.6%) than were reported using the DHS questionnaire (75.6%). At 

the same time, there was little diffe rence in the amount of missing data between the two questionnaires 

(Hellerringer et al. 2014b). 

A potential source of bias in the sisterhood m ethod results from the assumption that the risk of m ortality 

among siblings is independent. In other words, the risk of a sibling dying is not related to the risk of another 

sibling in that family dying. If m ortality risk is related, then siblings with a hi gher risk of d ying are less 

likely to be available to respond and thus bias the estimates downward. 

As discussed in Stanton et al. (2000), DHS evaluated both the indi rect and direct methods of estimating 

maternal mortality and determined that the direct method was the preferred approach for fut ure surveys 

because it enables (1) calculation of rates and ratios for specified time periods, (2) monitoring of trends, 

(3) analysis of maternal mortality by parity, and (4) more complete assessment of data quality. Another 

disadvantage of the indirect sisterhood method is that it only gives lifetime risks and assumes no trend in 
11 

either MMR or fertility. In contrast, the disadvantages of the direct method, such as the l onger average 

interview duration (8-10 minutes per interview), the need for additional training and field supervision, and 

the increased complexity of data analysis, wer e considered to be counter-balanced by the advantages 

(Stanton et al. 2000). 

Direct household method of estimation 

While the majority of the countries with DHS surveys rely on the direct sisterhood method of measuring 

maternal mortality, several countries have implemented the direct household method. The notable examples 

are the Bangladesh Maternal Mortalit y and Health Care Survey in 2001 and 2010, Afghanistan Mortality 

Survey 2010, and Ghana Maternal Health Survey 2007. The direct household m ethod incorporates 

questions into an existing census or a household survey with a sample population large enough to provide 

reliable estimates. Respondents are asked about deaths that occurred in the household, regardless of sibling 

status, for a recall period prior to the census or survey. For deaths of women of reproductive age, there are 

further questions related to the tim ing of death to determine if the death was pregnancy-related. As 

mentioned earlier, because of the relative rarity of maternal deaths, household surveys need to be very large 

to yield reliable estimates of maternal mortality; such surveys are often not feasible or co st effective in 

developing countries. For this reason, most countries rely on the sisterhood method as part of a DHS survey 

or another small sample survey. 

A study in B angladesh allowed for a u nique comparison of estimates of pregnancy -related deaths—the 

direct household method compared with the direct sisterhood method—compared maternal deaths from a 

household survey with ca use of death from a verbal autopsy (Hill et al. 2006). Results indicated that 

pregnancy-related deaths estimated with the ho usehold and sisterhood m ethods were similar, while 

estimates of maternal deaths from the household survey were about 15% lower—although not significantly 

different because of overlapping confi dence intervals. The sisterhood m ethod showed greater sam pling 

precision compared with the household m ethod because of higher person- years of exposure in the 

sisterhood method. However, it should be noted that the comparability of the sisterhood method with the 

household survey in Bangladesh may not be generalizable to other countries that use the sisterhood method 

because of the e mphasis in the Bangl adesh survey on training and the pr iority given to the maternal 

mortality questions; in most DHS surveys, the maternal mortality module is one of the last sections covered 

by the interviewer (Hill et al. 2006). Both t he respondent and interviewer may be tired by the time the 

sibling history is reached in the DHS surveys, which may affect the quality of responses. In the Afghanistan 

Mortality Survey 2010, the pregnancy-related mortality ratio from the direct household m ethod was 39% 

higher than the estimate from the direct sisterhood (sibling survival history) method. 

2.3. Use of DHS Data for Global Maternal Mortality Estimations 

Global estimations of maternal mortality have been routinely reported by the World Health Organization 

(WHO), UNICEF, UNFPA, and the World Bank since th e 1990s. The IHME has been reporting maternal 

mortality since 2008. DHS surveys are the major source of primary data for maternal mortality estimation 

in both the UN organizations and IHM E. As an example, of the 273 databases for MMR based on the 

sisterhood method in the WHO/UNICEF/UNFPA and the World Bank data repository, 87.8% are based on 

DHS survey data (WHO 2 010). The other two types of surveys providing MMR estimates based on the 

sisterhood method—the AIDS Indicator Survey (AIS) and the Maternal Mortality and Morbidity Surveys 

in Bangladesh (BMMS) and Ghana (MHS)—were carried out with technical assistance provided by DHS. 

IHME uses sisterhood-based maternal m ortality data from DHS and from CDC’s Reproductive Health 

Surveys (RHS)—97 surve ys from 53 countries in 2008— for global mortality estimation (Hogan et al. 

2010). Interested readers may consult the supplementary appendix in the Lancet for the list of the countries 

that used DHS in the IHME’ s maternal mortality estimations for the period 1990-2013 (Kassebaum et al. 

2014). 

13 

3. Quality of the Sibling History Data 

The data collected as part of the sibling history module in DHS surveys were significantly influenced by a 

study by Stanton et al. (1997) that first systematically examined the quality of maternal mortality data from 

DHS surveys. One of the main objectives of this st udy was to e xamine whether specific deficiencies 

identified in the earlier study were dealt with effectively in subsequent survey rounds. 

3.1. Completeness of Vital Statistics 

Table 3.1 shows that the sex of siblings was not reported or was missing in only a fraction of cases. In most 

countries the proportion of siblings with unknown sex was below 1%. The notable exceptions were Sierra 

Leone (9%) and Brazil (3.5%). Sierra Leone experienced civil war between 1991 and 2002, during which 

close to 1 million people were killed and 2.6 m illion were displaced. It may be that conflict played a role 

in the higher reporting of unknown sex of the siblings in Sierra Leone. 

It is likely that the siblings with unknown sex are th ose who died immediately after birth or who died in 

the distant past before the birth of the respondent or when the respondent was too young to remember. DHS 

reports MMR only for recent periods—the last 3, 5, or 7 years before the surve y—so the reporting of 

unknown sex of siblings may not have any major implications for maternal mortality estimation. 

Although reporting of unknown sex was low, an examination of the trends between DHS-II and DHS-VI 

shows that the proportion declined substantially over the period in most countries (Figure 3.1). 

Table 3.1 Percentage of siblings with unknown sex reporting, Demographic and Health Surveys 

1990-2013 

 Unknown sex 

Country 

DHS survey 

round 

Year of 

survey 

No. of 

sisters 

No. of

brothers Percent 

No. with 

unknown sex

No. of 

siblings 

Sub-Saharan Africa 

Benin DHS-III 1996 14,996 15,548 1.1 334 30,879 

Benin DHS-V 2006 47,311 49,081 0.4 362 96,754 

Burkina Faso DHS-III 1998-99 16,314 17,532 1.8 612 34,458 

Burkina Faso DHS-IV 2003 31,933 33,869 0.7 464 66,266 

Burkina Faso DHS-VI 2010 46,814 50,188 0.2 167 97,169 

Burundi DHS-VI 2010-11 29,517 30,731 0.0 27 60,274 

CAR DHS-III 1994-95 15,162 15,356 0.0 0 30,518 

Cameroon DHS-III 1998 15,777 16,522 1.9 632 32,930 

Cameroon DHS-IV 2004 31,722 33,746 0.0 27 65,495 

Cameroon DHS-VI 2011 44,938 47,008 0.2 196 92,143 

Chad DHS-III 1996-97 19,715 21,218 0.4 163 41,097 

Chad DHS-IV 2004 17,474 18,373 0.0 0 35,847 

Congo (Brazzaville) DHS-V 2005 20,351 20,402 0.1 39 40,792 

Congo (Brazzaville) DHS-VI 2011-12 28,432 29,128 0.0 18 57,579 

Congo Democratic 

Republic 

DHS-V 2007 28,334 30,002 0.1 68 58,404 

Côte d’Ivoire DHS-III 1994 21,879 22,509 0.0 0 44,388 

Côte d’Ivoire DHS-V 2005 13,555 14,499 0.6 158 28,212 

Côte d’Ivoire DHS-VI 2011-12 28,527 29,733 0.1 56 58,394 

Ethiopia DHS-IV 2000 43,933 47,872 0.4 372 92,176 

(Continued...)

 
14 

Table 3.1 – Continued

 Unknown sex 

Country 

DHS survey 

round 

Year of 

survey 

No. of 

sisters 

No. of

brothers Percent 

No. with 

unknown sex

No. of 

siblings 

Sub-Saharan Africa 

Ethiopia DHS-IV 2005 38,392 42,138 0.5 396 80,925 

Ethiopia DHS-VI 2011 47,107 51,558 0.3 262 98,927 

Gabon DHS-III 2000-01 17,991 18,003 0.6 232 36,227 

Gabon DHS-VI 2012 23,415 23,568 0.4 174 47,157 

Guinea DHS-III 1999 15,798 16,574 0.2 74 32,445 

Guinea DHS-IV 2005 19,958 21,346 0.1 55 41,359 

Guinea DHS-VI 2012 22,192 23,509 0.0 0 45,701 

Kenya DHS-III 1998 24,648 24,628 0.5 256 49,533 

Kenya DHS-IV 2003 25,508 26,165 0.4 216 51,889 

Kenya DHS-V 2008-09 24,825 24,770 0.4 210 49,804 

Lesotho DHS-IV 2004-05 16,551 17,145 0.1 34 33,730 

Lesotho DHS-V 2009-10 16,620 16,445 0.0 1 33,066 

Liberia DHS-V 2006-07 15,684 15,474 0.2 72 31,229 

Madagascar DHS-II 1992 19,845 20,389 0.0 0 40,234 

Madagascar DHS-III 1997 21,596 22,719 0.6 274 44,589 

Madagascar DHS-IV 2003-04 21,306 22,037 0.4 192 43,535 

Madagascar DHS-V 2008-09 51,193 52,466 0.1 58 103,717 

Malawi DHS-II 1992 15,107 14,792 0.9 270 30,169 

Malawi DHS-IV 2000 39,447 39,744 0.1 102 79,293 

Malawi DHS-IV 2004-05 31,195 31,538 0.1 57 62,790 

Malawi DHS-V 2010 68,386 68,532 0.2 228 137,147 

Mali DHS-III 1995-96 26,086 27,243 0.0 12 53,341 

Mali DHS-IV 2001 33,968 36,101 0.7 481 70,550 

Mali DHS-V 2006 40,897 44,708 0.5 426 86,031 

Mali DHS-V1 2012-13 20,104 21,707 0.0 0 41,811 

Mozambique DHS-III 1997 20,605 20,841 0.0 0 41,446 

Mozambique DHS-IV 2003-04 31,094 31,684 0.4 236 63,014 

Mozambique DHS-VI 2011 30,112 30,700 0.0 0 60,811 

Namibia DHS-II 1992 15,469 15,472 0.8 243 31,184 

Namibia DHS-IV 2000 19,537 18,071 0.4 168 37,776 

Namibia DHS-V 2006-07 25,974 25,270 0.3 177 51,421 

Niger DHS-II 1992 18,156 19,064 0.3 96 37,316 

Niger DHS-V 2006 26,755 28,435 0.1 58 55,248 

Niger DHS-VI 2012 34,732 36,410 0.1 59 71,201 

Nigeria DHS-III 1999 20,380 22,491 0.6 277 43,147 

Nigeria DHS-V 2008 86,223 92,541 0.6 1,155 179,919 

Rwanda DHS-IV 2000 31,993 32,882 0.8 514 65,388 

Rwanda DHS-IV 2005 35,963 36,405 0.2 159 72,527 

Rwanda DHS-VI 2010-11 41,562 42,048 0.2 170 83,779 

São Tomé and Príncipe DHS-V 2008-09 8,326 8,374 0.1 11 16,711 

Senegal DHS-II 1992-93 17,214 18,343 0.1 46 35,603 

Senegal DHS-IV 2005 42,600 43,774 0.3 220 86,594 

Senegal DHS-VI 2010-11 43,706 47,018 0.0 20 90,744 

Sierra Leone DHS-V 2008 14,619 14,750 9.0 2,921 32,291 

(Continued...)
15 

Table 3.1 – Continued

 Unknown sex 

Country 

DHS survey 

round 

Year of 

survey 

No. of 

sisters 

No. of

brothers Percent 

No. with 

unknown sex

No. of 

siblings 

Sub-Saharan Africa 

South Africa DHS-III 1998 25,053 25,270 1.9 968 51,291 

Swaziland DHS-V 2006-07 12,774 12,820 0.3 84 25,679 

Tanzania DHS-III 1996 23,775 23,952 0.2 86 47,813 

Tanzania DHS-IV 2004-05 32,015 32,004 0.1 64 64,083 

Tanzania DHS-V 2009-10 28,309 28,425 0.2 101 56,835 

Togo DHS-III 1998 24,364 25,070 0.4 189 49,624 

Uganda DHS-III 1995 21,762 22,084 0.6 282 44,128 

Uganda DHS-IV 2000-01 23,417 23,660 1.2 554 47,631 

Uganda DHS-V 2006 28,655 29,200 0.5 282 58,137 

Uganda DHS-VI 2011 28,824 28,525 0.4 202 57,551 

Zambia DHS-III 1996-97 25,650 25,499 0.1 61 51,210 

Zambia DHS-IV 2001-02 23,721 24,035 0.1 64 47,819 

Zambia DHS-V 2007 20,404 20,775 0.2 62 41,242 

Zimbabwe DHS-III 1994 19,200 19,265 0.1 56 38,521 

Zimbabwe DHS-IV 1999 17,344 17,074 0.2 76 34,494 

Zimbabwe DHS-V 2005-06 23,720 23,349 0.2 80 47,149 

Zimbabwe DHS-VI 2010-11 21,870 21,564 0.0 0 43,434 

North Africa 

Jordan DHS-III 1997 41,211 43,325 0.0 11 84,547 

Morocco DHS-II 1992 29,488 31,012 0.0 1 60,501 

Morocco DHS-IV 2003-04 52,962 55,289 0.1 69 108,321 

Asia 

Cambodia DHS-IV 2000 39,167 40,928 0.2 147 80,242 

Cambodia DHS-V 2005-06 44,039 46,040 0.0 0 90,079 

Cambodia DHS-V 2010-11 44,897 47,085 0.0 35 92,018 

Indonesia DHS-III 1994 86,744 91,884 0.4 675 179,302 

Indonesia DHS-III 1997 81,320 85,439 0.1 104 166,863 

Indonesia DHS-IV 2002-03 77,938 85,122 0.1 131 163,191 

Indonesia DHS-V 2007 87,620 91,617 0.1 267 179,503 

Indonesia DHS-VI 2012 91,067 96,274 0.2 395 187,736 

Nepal DHS-III 1996 25,349 27,057 0.0 12 52,418 

Nepal DHS-V 2006 26,377 27,418 0.1 41 53,836 

Philippines DHS-II 1993 43,047 44,641 0.3 221 87,909 

Philippines DHS-III 1998 39,134 40,745 0.1 120 79,998 

Timor-Leste DHS-VI 2009-10 30,861 32,621 0.0 12 63,494 

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 20,909 22,094 0.2 97 43,100 

Bolivia DHS-IV 2003-04 45,780 48,432 0.6 538 94,750 

Bolivia DHS-V 2008 42,066 44,328 0.2 151 86,679 

Brazil DHS-III 1996 35,426 36,889 3.5 2,631 74,945 

Dominican Republic DHS-IV 2002 30,892 31,795 0.9 573 63,260 

Dominican Republic DHS-V 2007 66,456 68,127 0.6 765 136,031 

(Continued...)
16 

Table 3.1 – Continued

 Unknown sex 

Country 

DHS survey 

round 

Year of 

survey 

No. of 

sisters 

No. of

brothers Percent 

No. with 

unknown sex

No. of 

siblings 

Latin America and 

Caribbean 

Guatemala DHS-III 1995 34,757 36,631 0.6 439 71,828 

Haiti DHS-IV 2000 28,693 29,738 0.2 92 58,523 

Haiti DHS-V 2005-06 30,321 30,978 0.0 5 61,305 

Peru DHS-II 1991-92 40,639 42,927 0.0 0 83,565 

Peru DHS-III 1996 81,636 85,036 1.0 1,756 168,427 

Peru DHS-IV 2000 75,210 79,685 0.8 1,317 156,212 

Peru DHS-V 2003-08 104,265 110,752 0.1 159 215,176 

Peru DHS-VI 2009 59,682 62,888 0.0 0 122,570 

Peru DHS-VI 2010 57,075 60,170 0.0 0 117,244 

Peru DHS-VI 2011 55,096 56,875 0.0 0 111,971 

 
17 

Figure 3.1 Trends in reporting of missing sex of siblings by DHS survey rounds, Demographic and 

Health Surveys 1990-2013 

0 .5 1 1.5 2 0 .5 1 1.5 2 0 .5 1 1.5 2 0 .5 1 1.5 2 0 .5 1 1.5 2 0 .5 1 1.5 2

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

Benin Bolivia Burkina Faso Cambodia Cameroon Chad

Congo (Brazzaville) Cote d'Ivoire Dominican Republic Ethiopia Gabon Guinea

Haiti Indonesia Kenya Lesotho Madagascar Malawi

Mali Morocco Mozambique Namibia Nepal Niger

Nigeria Peru Philippines Rwanda Senegal Tanzania

Uganda Zambia Zimbabwe

Percent

DHS Survey Round
18 

Unknown or missing response on the survival status of siblings was also low in the majority of countries 

(Table 3.2). Countries that experienced war or conflicts (e.g., Rwanda and Cambodia) have slightly higher 

reporting of unknown survival status of siblings, especially for brothers. However, there were no substantial 

differences in the reporting of unknown/missing survival status between sisters and brothers (Figure 3.2). 

Because there was no s ystematic overreporting of unknown survival status of sisters, co mpared with 

brothers, we consider that respondents were not underreporting th e deaths of sisters in order to avoid the 

series of questions on maternal mortality. 

Table 3.2 Percentage of siblings with unknown survival status, Demographic and Health Surveys 

1990-2013 

Country 

DHS survey 

round 

Year of 

survey 

Missing 

percent 

No. of 

sisters 

Missing 

percent 

No. of 

brothers 

Missing 

percent 

No. of all 

siblings 

Sub-Saharan Africa

Benin DHS-III 1996 0.1 14,996 0.0 15,548 0.1 30,545 

Benin DHS-V 2006 0.0 47,311 0.0 49,081 0.0 96,392 

Burkina Faso DHS-III 1998-99 0.2 16,314 0.2 17,532 0.2 33,846 

Burkina Faso DHS-IV 2003 0.0 31,933 0.0 33,869 0.0 65,802 

Burkina Faso DHS-VI 2010 0.0 46,814 0.0 50,188 0.0 97,002 

Burundi DHS-VI 2010-11 0.1 29,517 0.3 30,731 0.2 60,247 

CAR DHS-III 1994-95 0.1 15,162 0.0 15,356 0.1 30,518 

Cameroon DHS-III 1998 0.0 15,777 0.1 16,522 0.0 32,298 

Cameroon DHS-IV 2004 0.0 31,722 0.0 33,746 0.0 65,468 

Cameroon DHS-VI 2011 0.1 44,938 0.1 47,008 0.1 91,946 

Chad DHS-III 1996-97 0.1 19,715 0.0 21,218 0.0 40,933 

Chad DHS-IV 2004 0.0 17,474 0.0 18,373 0.0 35,847 

Congo (Brazzaville) DHS-V 2005 0.0 20,351 0.0 20,402 0.0 40,753 

Congo (Brazzaville) DHS-VI 2011-12 0.1 28,432 0.1 29,128 0.1 57,560 

Congo Democratic 

Republic 

DHS-V 2007 0.1 28,334 0.1 30,002 0.1 58,337 

Côte d’Ivoire DHS-III 1994 0.0 21,879 0.0 22,509 0.0 44,388 

Côte d’Ivoire DHS-V 2005 0.0 13,555 0.1 14,499 0.1 28,054

Côte d’Ivoire DHS-VI 2011-12 0.0 28,527 0.1 29,733 0.0 58,260 

Ethiopia DHS-IV 2000 0.1 43,933 0.5 47,872 0.3 91,804

Ethiopia DHS-IV 2005 0.1 38,392 0.2 42,138 0.2 80,530 

Ethiopia DHS-VI 2011 0.1 47,107 0.1 51,558 0.1 98,665

Gabon DHS-III 2000-01 0.0 17,991 0.0 18,003 0.0 35,995 

Gabon DHS-VI 2012 0.0 23,415 0.1 23,568 0.1 46,983

Guinea DHS-III 1999 0.1 15,798 0.1 16,574 0.1 32,372 

Guinea DHS-IV 2005 0.0 19,958 0.0 21,346 0.0 41,304

Guinea DHS-VI 2012 0.0 22,192 0.1 23,509 0.0 45,701 

Kenya DHS-III 1998 0.0 24,648 0.0 24,628 0.0 49,277

Kenya DHS-IV 2003 0.0 25,508 0.0 26,165 0.0 51,673 

Kenya DHS-V 2008-09 0.1 24,825 0.0 24,770 0.1 49,595

Lesotho DHS-IV 2004-05 0.1 16,551 0.1 17,145 0.1 33,696 

Lesotho DHS-V 2009-10 0.2 16,620 0.2 16,445 0.2 33,065

Liberia DHS-V 2006-07 0.3 15,684 0.3 15,474 0.3 31,157 

Madagascar DHS-II 1992 0.1 19,845 0.1 20,389 0.1 40,234

Madagascar DHS-III 1997 0.1 21,596 0.1 22,719 0.1 44,316 

Madagascar DHS-IV 2003-04 0.0 21,306 0.0 22,037 0.0 43,343

(Continued...)
19 

Table 3.2 – Continued

Country 

DHS survey 

round 

Year of 

survey 

Missing 

percent 

No. of 

sisters 

Missing 

percent 

No. of 

brothers 

Missing 

percent 

No. of all 

siblings 

Sub-Saharan Africa 

Madagascar DHS-V 2008-09 0.0 51,193 0.1 52,466 0.0 103,659

Malawi DHS-II 1992 0.1 15,107 0.2 14,792 0.1 29,899

Malawi DHS-IV 2000 0.0 39,447 0.0 39,744 0.0 79,191

Malawi DHS-IV 2004-05 0.0 31,195 0.0 31,538 0.0 62,733

Malawi DHS-V 2010 0.0 68,386 0.1 68,532 0.0 136,918

Mali DHS-III 1995-96 0.0 26,086 0.0 27,243 0.0 53,329

Mali DHS-IV 2001 0.1 33,968 0.1 36,101 0.1 70,069

Mali DHS-V 2006 0.0 40,897 0.1 44,708 0.0 85,605

Mali DHS-VI 2012-13 0.0 20,104 0.0 21,707 0.0 41,811

Mozambique DHS-III 1997 0.0 20,605 0.0 20,841 0.0 41,446

Mozambique DHS-IV 2003-04 0.1 31,094 0.2 31,684 0.1 62,778

Mozambique DHS-VI 2011 0.1 30,112 0.2 30,700 0.1 60,811

Namibia DHS-II 1992 0.3 15,469 0.5 15,472 0.4 30,941

Namibia DHS-IV 2000 0.1 19,537 0.1 18,071 0.1 37,608

Namibia DHS-V 2006-07 0.2 25,974 0.1 25,270 0.1 51,244

Niger DHS-II 1992 0.0 18,156 0.1 19,064 0.0 37,220

Niger DHS-V 2006 0.0 26,755 0.1 28,435 0.0 55,190

Niger DHS-VI 2012 0.0 34,732 0.0 36,410 0.0 71,142

Nigeria DHS-III 1999 0.1 20,380 0.1 22,491 0.1 42,871

Nigeria DHS-V 2008 0.2 86,223 0.2 92,541 0.2 178,764

Rwanda DHS-IV 2000 1.0 31,993 2.1 32,882 1.6 64,875

Rwanda DHS-IV 2005 0.6 35,963 0.0 36,405 1.0 72,368

Rwanda DHS-VI 2010-11 0.3 41,562 0.7 42,048 0.5 83,609

São Tomé and 

Príncipe 

DHS-V 2008-09 0.0 8,326 0.2 8,374 0.1 16,700

Senegal DHS-II 1992-93 0.0 17,214 0.1 18,343 0.1 35,557

Senegal DHS-IV 2005 0.0 42,600 0.1 43,774 0.0 86,373

Senegal DHS-VI 2010-11 0.0 43,706 0.1 47,018 0.1 90,724

Sierra Leone DHS-V 2008 0.4 14,619 0.4 14,750 0.4 29,370

South Africa DHS-III 1998 0.2 25,053 0.3 25,270 0.2 50,323

Swaziland DHS-V 2006-07 0.1 12,774 0.1 12,820 0.1 25,594

Tanzania DHS-III 1996 0.0 23,775 0.1 23,952 0.1 47,727

Tanzania DHS-IV 2004-05 0.0 32,015 0.0 32,004 0.0 64,019

Tanzania DHS-V 2009-10 0.0 28,309 0.1 28,425 0.1 56,734

Togo DHS-III 1998 0.0 24,364 0.0 25,070 0.0 49,435

Uganda DHS-III 1995 0.1 21,762 0.2 22,084 0.1 43,846

Uganda DHS-IV 2000-01 0.2 23,417 0.3 23,660 0.2 47,077

Uganda DHS-V 2006 0.8 28,655 0.8 29,200 0.8 57,855

Uganda DHS-VI 2011 0.2 28,824 0.2 28,525 0.2 57,349

Zambia DHS-III 1996-97 0.0 25,650 0.0 25,499 0.0 51,149

Zambia DHS-IV 2001-02 0.0 23,721 0.0 24,035 0.0 47,755

Zambia DHS-V 2007 0.1 20,404 0.1 20,775 0.1 41,180

Zimbabwe DHS-III 1994 0.0 19,200 0.1 19,265 0.1 38,465

Zimbabwe DHS-IV 1999 0.2 17,344 0.2 17,074 0.2 34,418

Zimbabwe DHS-V 2005-06 0.0 23,720 0.1 23,349 0.1 47,069

Zimbabwe DHS-VI 2010-11 0.1 21,870 0.1 21,564 0.1 43,434

(Continued...)
20 

Table 3.2 – Continued

Country 

DHS survey 

round 

Year of 

survey 

Missing 

percent 

No. of 

sisters 

Missing 

percent 

No. of 

brothers 

Missing 

percent 

No. of all 

siblings 

North Africa 

Jordan DHS-III 1997 0.0 41,211 0.0 43,325 0.0 84,536 

Morocco DHS-II 1992 0.1 29,488 0.1 31,012 0.1 60,500 

Morocco DHS-IV 2003-04 0.0 52,962 0.1 55,289 0.1 108,252 

Asia 

Cambodia DHS-IV 2000 0.6 39,167 1.4 40,928 1.0 80,095 

Cambodia DHS-V 2005-06 0.5 44,039 1.2 46,040 0.9 90,079 

Cambodia DHS-V 2010-11 0.1 44,897 0.0 47,085 0.2 91,982 

Indonesia DHS-III 1994 0.0 86,744 0.0 91,884 0.0 178,627 

Indonesia DHS-III 1997 0.0 81,320 0.0 85,439 0.0 166,759 

Indonesia DHS-IV 2002-03 0.1 77,938 0.0 85,122 0.1 163,060 

Indonesia DHS-V 2007 0.0 87,620 0.1 91,617 0.0 179,237 

Indonesia DHS-VI 2012 0.0 91,067 0.1 96,274 0.0 187,341 

Nepal DHS-III 1996 0.1 25,349 0.2 27,057 0.1 52,406 

Nepal DHS-V 2006 0.1 26,377 0.0 27,418 0.1 53,794 

Philippines DHS-II 1993 0.1 43,047 0.1 44,641 0.1 87,688 

Philippines DHS-III 1998 0.0 39,134 0.1 40,745 0.1 79,878 

Timor-Leste DHS-VI 2009-10 0.0 30,861 0.0 32,621 0.0 63,481 

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 0.1 20,909 0.0 22,094 0.1 43,003 

Bolivia DHS-IV 2003-04 0.1 45,780 0.1 48,432 0.1 94,212 

Bolivia DHS-V 2008 0.1 42,066 0.2 44,328 0.2 86,395 

Brazil DHS-III 1996 0.6 35,426 0.6 36,889 0.6 72,314 

Dominican Republic DHS-IV 2002 0.1 30,892 0.0 31,795 0.1 62,687 

Dominican Republic DHS-V 2007 0.0 66,456 0.1 68,127 0.0 134,583 

Guatemala DHS-III 1995 0.1 34,757 0.1 36,631 0.1 71,388 

Haiti DHS-IV 2000 0.0 28,693 0.0 29,738 0.0 58,430 

Haiti DHS-V 2005-06 0.0 30,321 0.0 30,978 0.1 61,300 

Peru DHS-II 1991-92 0.1 40,639 0.2 42,927 0.2 83,565 

Peru DHS-III 1996 0.2 81,636 0.2 85,036 0.2 166,671 

Peru DHS-IV 2000 0.1 75,210 0.1 79,685 0.1 154,895 

Peru DHS-V 2003-08 0.1 104,265 0.1 110,752 0.1 215,017 

Peru DHS-VI 2009 0.1 59,682 0.1 62,888 0.1 122,570 

Peru DHS-VI 2010 0.1 57,075 0.2 60,170 0.1 117,244 

Peru DHS-VI 2011 0.1 55,096 0.1 56,875 0.1 111,971 

 
21 

Figure 3.2 Percentage of siblings with missing survival status by sex, Demographic and Health 

Surveys 1990-2013 

Note: DHS country codes in two characters are listed in the Appendix (Table A1). 

3.2. Accuracy and Completeness of Age Reporting 

Age is an important variable in demographic studies. Knowing correct age is critical for identifying at-risk 

women (age 15-49) and a scertaining age-specific and age-adjusted risks of maternal mortality. In the 

countries lacking birth certificates and complete vital registration systems, misreporting of age is common 

in surveys and censuses. Age data frequently show excess digit preference, commonly at 0 or 5, leading to 

age heaping. Age heaping is often considered a measure of survey data quality. We use the Whipple Index 

as a demographic measure to examine the extent of age heaping. Compared to the Myers Index, which is 

used for age heaping asses sment of any preferred valu es, the Whipple Index is preferred for identify ing 

digit preference at 0 and 5. An early study examining the quality of age reporting foun d that the most 

common digit preferences in DHS surveys are the final digits of 0 and 5 (Pullum 2006). For this reason, 

we have limited the analysis of age heaping to calculation of the Whipple Index only. This index is obtained 

BR 1996 KH 2000

KH 2005-06

ET 2000

LB 2006-07

NM 1992

RW 2000

RW 2005

RW 2010-11

SL 2008

ZA 1998

UG 2006

0 .25 .5 .75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3

Sisters: % survival status missing

0 .25 .5 .75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3

Brothers: % survival status missing
22 

by summing age returns between 23 and 62 years inclusive and finding what percentage is reported by the 

sum of the returns of years ending with 0 and 5 to one-fifth of the total sum (United Nations 1955). T he 

UN recommends measuring age heaping using the Whipple Index, with the following classifications of 

data quality (United Nations 1974): 

 Value of Whipple index 

I. Highly accurate data Less than 105 

II. Fairly accurate data 105-109.9 

III. Approximate data 110-124.9 

IV. Rough data 125-1 74.9 

V. Very rough data 175 and more 

We have included all the reported siblings and appl ied the standard age range for the Whipple Index 

calculation so that the U N classification shown above may be used for assess ing the quality of age data. 

Table 3.3 shows the Whipple Index for age reporting of sisters and brot hers. Four of the 1 12 surveys—

Chad 1996-97, Lesotho 2004-05, Mala wi 1992, and Zambia 1996-97—have highly accurate data on age 

reporting with minimal digit preference (Whipple Inde x <105). None of the survey s have an index value 

of 175 or higher (very rough data). Digit preference in age reporting of brothers and sisters was similar in 

all countries (Figure 3.3). 

Table 3.3 Digit preference in age reporting of surviving siblings according to the Whipple Index, 

Demographic and Health Surveys 1990-2013 

 Whipple Index 

Country 

DHS survey

round 

Year of 

survey Sisters Brothers All siblings 

Sub-Saharan Africa 

Benin DHS-III 1996 122.6 124.9 123.7 

Benin DHS-V 2006 130.6 128.4 129.5 

Burkina Faso DHS-III 1998-99 128.9 133.9 131.5 

Burkina Faso DHS-IV 2003 119.8 123.7 121.8 

Burkina Faso DHS-VI 2010 126.9 124.7 125.8 

Burundi DHS-VI 2010-11 123.0 119.3 121.2 

CAR DHS-III 1994-95 109.0 117.6 113.3 

Cameroon DHS-III 1998 123.5 120.6 122.1 

Cameroon DHS-IV 2004 119.1 119.8 119.4 

Cameroon DHS-VI 2011 121.9 128.0 125.0 

Chad DHS-III 1996-97 104.2 98.1 101.1 

Chad DHS-IV 2004 104.1 109.5 106.8 

Congo (Brazzaville) DHS-V 2005 119.3 122.8 121.0 

Congo (Brazzaville) DHS-VI 2011-12 115.9 117.2 116.5 

Congo Democratic Republic DHS-V 2007 114.6 115.1 114.9 

Côte d’Ivoire DHS-III 1994 130.4 129.5 129.9 

Côte d’Ivoire DHS-V 2005 130.3 128.6 129.4 

Côte d’Ivoire DHS-VI 2011-12 133.1 133.9 133.5 

Ethiopia DHS-IV 2000 116.3 115.5 115.9 

Ethiopia DHS-IV 2005 123.5 127.0 125.3 

Ethiopia DHS-VI 2011 125.6 127.7 126.7 

Gabon DHS-III 2000-01 119.7 124.9 122.3 

(Continued...)
23 

Table 3.3 – Continued

 Whipple Index 

Country 

DHS survey

round 

Year of 

survey Sisters Brothers All siblings 

Sub-Saharan Africa 

Gabon DHS-VI 2012 117.7 121.3 119.5 

Guinea DHS-III 1999 115.5 116.9 116.2 

Guinea DHS-IV 2005 119.5 120.6 120.0 

Guinea DHS-VI 2012 128.4 123.3 125.8 

Kenya DHS-III 1998 123.1 123.8 123.4 

Kenya DHS-IV 2003 119.9 119.0 119.4 

Kenya DHS-V 2008-09 119.7 119.5 119.6 

Lesotho DHS-IV 2004-05 103.6 103.0 103.3 

Lesotho DHS-V 2009-10 104.9 110.4 107.5 

Liberia DHS-V 2006-07 123.3 124.3 123.8 

Madagascar DHS-II 1992 117.8 126.5 122.2 

Madagascar DHS-III 1997 130.8 124.2 127.5 

Madagascar DHS-IV 2003-04 124.7 123.8 124.3 

Madagascar DHS-V 2008-09 120.7 123.1 121.9 

Malawi DHS-II 1992 104.4 105.5 104.9 

Malawi DHS-IV 2000 114.9 113.7 114.3 

Malawi DHS-IV 2004-05 115.4 120.0 117.7 

Malawi DHS-V 2010 118.2 119.1 118.6 

Mali DHS-III 1995-96 114.0 121.3 117.7 

Mali DHS-IV 2001 132.6 135.8 134.3 

Mali DHS-V 2006 118.1 117.4 117.7 

Mali DHS-VI 2012-13 120.1 124.5 122.4 

Mozambique DHS-III 1997 119.4 121.7 120.5 

Mozambique DHS-IV 2003-04 112.1 112.8 112.5 

Mozambique DHS-VI 2011 114.1 116.0 115.0 

Namibia DHS-II 1992 109.3 110.3 109.8 

Namibia DHS-IV 2000 115.2 119.0 117.0 

Namibia DHS-V 2006-07 105.8 109.2 107.4 

Niger DHS-II 1992 120.9 122.5 121.7 

Niger DHS-V 2006 123.9 125.1 124.5 

Niger DHS-VI 2012 119.2 121.1 120.2 

Nigeria DHS-III 1999 144.4 153.1 148.9 

Nigeria DHS-V 2008 134.6 139.2 137.0 

Rwanda DHS-IV 2000 123.5 123.1 123.3 

Rwanda DHS-IV 2005 126.6 126.5 126.5 

Rwanda DHS-VI 2010-11 117.7 120.6 119.1 

São Tomé and Príncipe DHS-V 2008-09 119.1 116.9 118.0 

Senegal DHS-II 1992-93 118.2 116.6 117.4 

Senegal DHS-IV 2005 113.8 113.9 113.8 

Senegal DHS-VI 2010-11 113.6 117.5 115.6 

Sierra Leone DHS-V 2008 143.7 147.4 145.5 

South Africa DHS-III 1998 119.6 121.9 120.7 

Swaziland DHS-V 2006-07 105.5 113.8 109.6 

Tanzania DHS-III 1996 117.1 112.2 114.7 

(Continued...)
24 

Table 3.3 – Continued

 Whipple Index 

Country 

DHS survey

round 

Year of 

survey Sisters Brothers All siblings 

Sub-Saharan Africa 

Tanzania DHS-IV 2004-05 114.8 117.0 115.9 

Tanzania DHS-V 2009-10 120.1 120.0 120.1 

Togo DHS-III 1998 118.0 124.1 121.0 

Uganda DHS-III 1995 115.6 114.7 115.1 

Uganda DHS-IV 2000-01 121.6 124.9 123.3 

Uganda DHS-V 2006 119.7 118.2 119.0 

Uganda DHS-VI 2011 123.5 121.7 122.6 

Zambia DHS-III 1996-97 102.5 104.8 103.6 

Zambia DHS-IV 2001-02 106.6 106.2 106.4 

Zambia DHS-V 2007 114.6 110.8 112.6 

Zimbabwe DHS-III 1994 114.9 114.0 114.5 

Zimbabwe DHS-IV 1999 116.1 113.9 115.1 

Zimbabwe DHS-V 2005-06 113.7 118.7 116.2 

Zimbabwe DHS-VI 2010-11 116.1 121.1 118.6 

North Africa 

Jordan DHS-III 1997 125.8 124.9 125.4 

Morocco DHS-II 1992 114.6 118.7 116.7 

Morocco DHS-IV 2003-04 111.3 111.8 111.5 

Asia 

Cambodia DHS-IV 2000 124.8 127.9 126.2 

Cambodia DHS-V 2005-06 113.4 117.6 115.4 

Cambodia DHS-V 2010-11 113.0 115.3 114.1 

Indonesia DHS-III 1994 130.2 132.6 131.4 

Indonesia DHS-III 1997 129.5 129.8 129.7 

Indonesia DHS-IV 2002-03 127.5 127.3 127.4 

Indonesia DHS-V 2007 130.8 130.1 130.4 

Indonesia DHS-VI 2012 121.0 120.2 120.6 

Nepal DHS-III 1996 123.2 121.9 122.5 

Nepal DHS-V 2006 111.6 116.4 114.0 

Philippines DHS-II 1993 116.3 118.5 117.4 

Philippines DHS-III 1998 115.6 118.5 117.0 

Timor-Leste DHS-VI 2009-10 121.7 126.1 123.9 

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 132.8 130.3 131.5 

Bolivia DHS-IV 2003-04 128.0 129.8 128.9 

Bolivia DHS-V 2008 125.7 131.0 128.4 

Brazil DHS-III 1996 111.8 112.5 112.1 

Dominican Republic DHS-IV 2002 116.3 119.0 117.7 

Dominican Republic DHS-V 2007 116.0 118.8 117.4 

Guatemala DHS-III 1995 138.8 140.2 139.5 

Haiti DHS-IV 2000 110.2 113.4 111.8 

Haiti DHS-V 2005-06 107.7 105.6 106.6 

Peru DHS-II 1991-92 122.9 124.7 123.8 

(Continued...)
25 

Table 3.3 – Continued

 Whipple Index 

Country 

DHS survey

round 

Year of 

survey Sisters Brothers All siblings 

Latin America and 

Caribbean 

Peru DHS-III 1996 123.4 125.4 124.4 

Peru DHS-IV 2000 127.2 128.1 127.7 

Peru DHS-V 2003-08 121.6 121.8 121.7 

Peru DHS-VI 2009 120.1 120.7 120.4 

Peru DHS-VI 2010 122.8 125.1 123.9 

Peru DHS-VI 2011 121.9 122.8 122.3 

Figure 3.3 Whipple Index values for digit preference in age reporting of surviving siblings by sex, 

Demographic and Health Surveys 1990-2013 

Note: Some countries with high Whipple Index values are shown with the DHS country labels 

(the list of country codes is provided in the Appendix). 

BO 1993-94

BF 1998-99

CI 1994 CI 2005

CI 2011-12

GU 1995

ID 1994

ID 1997

ID 2007

ML 2001

NG 1999

NG 2008

SL 2008

100 110 120 130 140 150

Sisters: Whipple index

100 110 120 130 140 150

Brothers: Whipple index
26 

Figure 3.4 shows trends in the Whipple Index for countries with multiple DHS survey rounds. In some 

countries, age reporting has improved substantially over time, as suggested by the decreasing trend in the 

Whipple Index. These countries include Bolivia, Cambodia, the Republic of Congo (Brazzaville), Haiti, 

Indonesia, Nepal, Nigeria and Rwanda. In contrast, the Whipple Index increased substantially in three 

countries: Benin, Malawi, and Zambia. 

 
27 

Figure 3.4 Trends in the Whipple Index for digit preference in age reporting of surviving siblings 

by sex and DHS survey rounds, Demographic and Health Surveys 1990-2013 100 120 140 160 100 120 140 160 100 120 140 160 100 120 140 160 100 120 140 160 100 120 140 160

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

Benin Bolivia Burkina Faso Cambodia Cameroon Chad

Congo (Brazzaville) Cote d'Ivoire Dominican Republic Ethiopia Gabon Guinea

Haiti Indonesia Kenya Lesotho Madagascar Malawi

Mali Morocco Mozambique Namibia Nepal Niger

Nigeria Peru Philippines Rwanda Senegal Tanzania

Uganda Zambia Zimbabwe

Sisters Brothers All

Whipple index

DHS Survey Round
28 

Table 3.4 shows the extent of missingness in the age reporting of surviving siblings by sex. In most survey 

rounds and countries, t he percent missing rate was l ess than 1%. The notable exceptions were Brazil, 

Lesotho, Madagascar, Namibia, Sierra Leone, South Africa, and Zimbabwe, which exhibit substantially 

higher reporting of “age not known” for siblings. The pattern of missingness of age reporting was similar 

for both sisters and brothers (Figure 3.5). Therefore, it is unlikely that respondents intentionally reported 

lack of knowledge of the age of sisters to avoid the series of questions on maternal mortality. 

In several countries the problem of missing responses for age of s iblings improved over successive DHS 

survey rounds. Figure 3.6 shows trends in missing data on age of surviving sisters between survey rounds 

DHS-II and DHS-VI. 

Table 3.4 Percentage of surviving siblings with current age missing by sex, Demographic and 

Health Surveys 1990-2013 

 

Percentage of surviving siblings 

with current age missing 

Country 

DHS

survey 

round 

Year of 

survey Sister Brother 

All 

siblings 

No. of 

siblings 

Sub-Saharan Africa 

Benin DHS-III 1996 0.2 0.2 0.2 22,802 

Benin DHS-V 2006 0.4 0.3 0.3 78,168 

Burkina Faso DHS-III 1998-99 1.5 1.4 1.5 26,295 

Burkina Faso DHS-IV 2003 0.4 0.5 0.4 53,124 

Burkina Faso DHS-VI 2010 0.2 0.2 0.2 77,447 

Burundi DHS-VI 2010-11 0.2 0.2 0.2 43,811 

CAR DHS-III 1994-95 0.0 0.0 0.0 24,688 

Cameroon DHS-III 1998 0.4 0.4 0.4 25,606 

Cameroon DHS-IV 2004 0.6 0.6 0.6 51,061 

Cameroon DHS-VI 2011 0.4 0.4 0.4 72,092 

Chad DHS-III 1996-97 0.1 0.1 0.1 31,268 

Chad DHS-IV 2004 0.7 0.6 0.7 27,011 

Congo (Brazzaville) DHS-V 2005 0.6 0.6 0.6 33,089 

Congo (Brazzaville) DHS-VI 2011-12 0.3 0.3 0.3 47,866 

Congo Democratic Republic DHS-V 2007 0.5 0.5 0.5 45,752 

Côte d’Ivoire DHS-III 1994 0.1 0.1 0.1 36,530 

Côte d’Ivoire DHS-V 2005 0.4 0.5 0.4 22,125 

Côte d’Ivoire DHS-VI 2011-12 0.9 0.9 0.9 46,206 

Ethiopia DHS-IV 2000 0.0 0.0 0.0 65,905 

Ethiopia DHS-IV 2005 0.5 0.5 0.5 62,752 

Ethiopia DHS-VI 2011 0.1 0.1 0.1 75,861 

Gabon DHS-III 2000-01 1.3 1.6 1.4 30,090 

Gabon DHS-VI 2012 2.2 2.0 2.1 39,718 

Guinea DHS-III 1999 0.4 0.4 0.4 24,670 

Guinea DHS-IV 2005 0.5 0.5 0.5 30,252 

Guinea DHS-VI 2012 0.1 0.1 0.1 35,368 

Kenya DHS-III 1998 0.9 1.0 0.9 43,151 

Kenya DHS-IV 2003 1.4 1.6 1.5 44,035 

Kenya DHS-V 2008-09 0.2 0.2 0.2 43,686 

Lesotho DHS-IV 2004-05 0.6 0.7 0.7 27,044 

Lesotho DHS-V 2009-10 5.8 6.1 5.9 26,209 

(Continued...)
29 

Table 3.4 – Continued

 

Percentage of surviving siblings 

with current age missing 

Country 

DHS

survey 

round 

Year of 

survey Sister Brother 

All 

siblings 

No. of 

siblings 

Sub-Saharan Africa 

Liberia DHS-V 2006-07 0.9 0.9 0.9 27,162 

Madagascar DHS-II 1992 9.7 9.5 9.6 33,264 

Madagascar DHS-III 1997 6.8 6.3 6.5 38,338 

Madagascar DHS-IV 2003-04 2.1 2.3 2.2 39,360 

Madagascar DHS-V 2008-09 0.5 0.5 0.5 89,502 

Malawi DHS-II 1992 0.1 0.1 0.1 20,746 

Malawi DHS-IV 2000 0.1 0.0 0.0 56,963 

Malawi DHS-IV 2004-05 0.2 0.3 0.2 48,686 

Malawi DHS-V 2010 0.2 0.2 0.2 99,547 

Mali DHS-III 1995-96 0.1 0.2 0.2 39,439 

Mali DHS-IV 2001 2.7 3.1 2.9 53,932 

Mali DHS-V 2006 0.8 0.9 0.9 63,429 

Mali DHS-VI 2012-13 12.9 12.6 12.7 37,728 

Mozambique DHS-III 1997 7.9 8.0 8.0 32,950 

Mozambique DHS-IV 2003-04 0.4 0.3 0.3 49,461 

Mozambique DHS-VI 2011 3.7 4.0 3.9 50,439 

Namibia DHS-II 1992 4.1 3.9 4.0 26,645 

Namibia DHS-IV 2000 6.6 6.5 6.6 32,774 

Namibia DHS-V 2006-07 1.1 1.0 1.0 43,570 

Niger DHS-II 1992 3.3 3.0 3.1 26,986 

Niger DHS-V 2006 0.4 0.4 0.4 41,645 

Niger DHS-VI 2012 0.5 0.4 0.5 52,975 

Nigeria DHS-III 1999 2.6 2.7 2.7 37,704 

Nigeria DHS-V 2008 1.1 1.1 1.1 148,258 

Rwanda DHS-IV 2000 0.4 0.2 0.3 44,504 

Rwanda DHS-IV 2005 0.8 1.0 0.9 49,062 

Rwanda DHS-VI 2010-11 0.1 0.1 0.1 60,805 

São Tomé and Príncipe DHS-V 2008-09 1.0 1.5 1.2 14,144 

Senegal DHS-II 1992-93 0.3 0.3 0.3 27,401 

Senegal DHS-IV 2005 0.7 0.6 0.6 71,118 

Senegal DHS-VI 2010-11 0.0 0.0 0.0 74,547 

Sierra Leone DHS-V 2008 3.9 3.9 3.9 23,124 

South Africa DHS-III 1998 4.7 4.8 4.7 43,834 

Swaziland DHS-V 2006-07 0.4 0.5 0.5 21,592 

Tanzania DHS-III 1996 0.4 0.5 0.5 39,189 

Tanzania DHS-IV 2004-05 0.0 0.1 0.1 50,839 

Tanzania DHS-V 2009-10 0.1 0.1 0.1 47,774 

Togo DHS-III 1998 0.1 0.1 0.1 38,389 

Uganda DHS-III 1995 1.1 1.0 1.1 34,278 

Uganda DHS-IV 2000-01 0.7 0.7 0.7 36,017 

Uganda DHS-V 2006 0.2 0.3 0.2 42,270 

Uganda DHS-VI 2011 0.4 0.3 0.4 43,875 

Zambia DHS-III 1996-97 0.5 0.4 0.5 41,083 

(Continued...)
30 

Table 3.4 – Continued

 

Percentage of surviving siblings 

with current age missing 

Country 

DHS

survey 

round 

Year of 

survey Sister Brother 

All 

siblings 

No. of 

siblings 

Sub-Saharan Africa 

Zambia DHS-IV 2001-02 0.1 0.1 0.1 37,893 

Zambia DHS-V 2007 0.6 0.7 0.6 33,466 

Zimbabwe DHS-III 1994 0.1 0.1 0.1 32,691 

Zimbabwe DHS-IV 1999 0.8 1.0 0.9 29,813 

Zimbabwe DHS-V 2005-06 0.6 0.6 0.6 40,161 

Zimbabwe DHS-VI 2010-11 3.3 2.8 3.1 36,753 

North Africa 

Jordan DHS-III 1997 0.0 0.0 0.0 75,264 

Morocco DHS-II 1992 0.2 0.1 0.2 49,787 

Morocco DHS-IV 2003-04 0.1 0.1 0.1 90,184 

Asia 

Cambodia DHS-IV 2000 0.0 0.1 0.1 63,011 

Cambodia DHS-V 2005-06 0.1 0.1 0.1 70,561 

Cambodia DHS-V 2010-11 0.1 0.1 0.1 76,733 

Indonesia DHS-III 1994 0.3 0.4 0.4 149,372 

Indonesia DHS-III 1997 0.2 0.2 0.2 145,848 

Indonesia DHS-IV 2002-03 0.3 0.3 0.3 145,823 

Indonesia DHS-V 2007 0.4 0.4 0.4 158,138 

Indonesia DHS-VI 2012 0.5 0.6 0.6 161,060 

Nepal DHS-III 1996 0.1 0.0 0.0 38,981 

Nepal DHS-V 2006 0.0 0.0 0.0 42,421 

Philippines DHS-II 1993 0.3 0.3 0.3 79,498 

Philippines DHS-III 1998 0.3 0.4 0.4 71,381 

Timor-Leste DHS-VI 2009-10 0.2 0.2 0.2 53,318 

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 0.4 0.4 0.4 35,205 

Bolivia DHS-IV 2003-04 2.8 3.2 3.0 76,744 

Bolivia DHS-V 2008 1.2 1.1 1.2 71,670 

Brazil DHS-III 1996 6.2 6.6 6.4 61,206 

Dominican Republic DHS-IV 2002 3.7 3.9 3.8 55,921 

Dominican Republic DHS-V 2007 0.7 0.6 0.7 120,473 

Guatemala DHS-III 1995 0.2 0.1 0.2 59,378 

Haiti DHS-IV 2000 0.1 0.0 0.0 43,829 

Haiti DHS-V 2005-06 0.1 0.1 0.1 46,724 

Peru DHS-II 1991-92 2.8 2.9 2.9 72,942 

Peru DHS-III 1996 0.7 0.7 0.7 138,164 

Peru DHS-IV 2000 0.3 0.3 0.3 129,828 

Peru DHS-V 2003-08 0.0 0.0 0.0 181,061 

Peru DHS-VI 2009 0.0 0.0 0.0 105,196 

Peru DHS-VI 2010 0.0 0.0 0.0 100,308 

Peru DHS-VI 2011 0.1 0.1 0.1 96,551 
31 

Figure 3.5 Percentage of living siblings with reported age missing by sex, Demographic and Health 

Surveys 1990-2013 

Note: The survey rounds with more than 2% age missing are shown with DHS country code labels 

(the list of country codes is provided in the Appendix) 

 

GA 2012

LS 2009-10

MD 1992

MD 1997

MD 2003-04

ML 2001

ML 2012-13

MZ 1997

MZ 2011

NM 1992

NM 2000

NI 1992

NG 1999

SL 2008

ZA 1998

ZW 2010-11

BO 2003-04

BR 1996

DR 2002

PE 1991-92

0 2 4 6 8 10 12 14

Sisters: % age missing

0 2 4 6 8 10 12 14

Brothers: % age missing
32 

Figure 3.6 Trends in missing age for surviving sisters by DHS survey rounds, Demographic and 

Health Surveys 1990-2013 

Conventionally, MMR is defined as the num ber of maternal deaths divided by the number of live births 

during a reference period. Considering the difficulti es, DHS does not collect data on live births from 

siblings (i.e., sisters). Instead, the MMR is estimated by dividing the age-standardized MMRate by the GFR 

from the respondents. The MMRate is estimated as an incidence rate from the number of maternal deaths 

0 5 10 15 0 5 10 15 0 5 10 15 0 5 10 15 0 5 10 15 0 5 10 15

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

Benin Bolivia Burkina Faso Cambodia Cameroon Chad

Congo (Brazzaville) Cote d'Ivoire Dominican Republic Ethiopia Gabon Guinea

Haiti Indonesia Kenya Lesotho Madagascar Malawi

Mali Morocco Mozambique Namibia Nepal Niger

Nigeria Peru Philippines Rwanda Senegal Tanzania

Uganda Zambia Zimbabwe

Percent

DHS Survey Round
33 

reported over women person-years of observation. The calculation of women person- years requires 

accurate and complete information on the age distribution of female siblings during the observation period 

(usually 5 or 7 years before the interview date). The DHS questionnaire directly asks the current age of the 

surviving siblings at the time of interview. The duration of exposure (person-years of observation) for each 

5-year age category of the surviving siblings is calculated from the reported age. However, for the siblings 

who died, the duration of survival during the observation period is ascertained from two data sources: age 

at death and how long ago (before the interview date) the sibling died. The complete information on these 

two variables is necessary to correctly measure the years of exposure and hence the estimation of maternal 

mortality indicators such as the MMR and the MMRate. Table 3.5 shows the extent of missing data on age 

and years since death. An important finding is that a large proportion of respondents had difficulty relating 

timing of death to a calendar. Additionally, several countries exhibited very high non-response rates for the 

variable, years since died from the date of interview. Similarly, age at death was missing in high proportions 

in some countries. These problems may displace the timing of deaths in rela tion to a calendar period, 

resulting in incorrect estimation of maternal mortality for the reference period. 

Table 3.5 Percentage of dead siblings with missing age at death and missing years since death, 

Demographic and Health Surveys 1990-2013 

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country 

DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings

No. of all 

siblings 

Sub-Saharan Africa 

Benin DHS-III 1996 Age at death 2.15 2.26 2.26 7,727 

 Years since death 1.32 1.30 1.30 

 Both 1.01 1.05 1.05 

Benin DHS-V 2006 Age at death 1.98 1.95 1.95 18,197 

 Years since death 1.33 1.46 1.46 

 Both 0.48 0.57 0.57 

Burkina Faso DHS-III 1998-99 Age at death 0.05 0.04 0.04 7,480 

 Years since death 9.13 9.59 9.59 

 Both 0.05 0.04 0.04 

Burkina Faso DHS-IV 2003 Age at death 3.12 3.38 3.38 12,660 

 Years since death 2.82 2.93 2.93 

 Both 2.59 2.70 2.70 

Burkina Faso DHS-VI 2010 Age at death 0.58 0.57 0.57 19,519 

 Years since death 0.47 0.44 0.44 

 Both 0.15 0.17 0.17 

Burundi DHS-VI 2010 Age at death 0.40 0.37 0.37 16,315 

 Years since death 0.29 0.26 0.26 

 Both 0.07 0.07 0.07 

(Continued...)
34 

Table 3.5 – Continued

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings No. of all siblings 

Sub-Saharan Africa 

Cameroon DHS-III 1998 Age at death 0.23 0.21 0.21 6,679

Years since death 0.80 0.94 0.94 

 Both 0.06 0.08 0.08 

Cameroon DHS-IV 2004 Age at death 2.42 2.72 2.72 14,394 

 Years since death 1.62 1.71 1.71 

 Both 1.20 1.27 1.27 

Cameroon DHS-VI 2011 Age at death 1.24 1.42 1.42 19,784

Years since death 0.94 0.99 0.99 

 Both 0.45 0.49 0.49 

Central African 

Republic DHS-III 1994-95 Age at death 0.20 0.17 0.17 5,814 

Years since death 0.24 0.34 0.34 

 Both 0.04 0.04 0.04 

Chad DHS-III 1996-97 Age at death 0.53 0.72 0.72 9,651

Years since death 0.49 0.62 0.62 

 Both 0.34 0.47 0.47 

Chad DHS-IV 2004 Age at death 0.98 0.99 0.99 8,835 

Years since death 0.55 0.57 0.57 

 Both 0.16 0.15 0.15 

Congo (Brazzaville) DHS-V 2005 Age at death 2.04 2.15 2.15 7,663

Years since death 2.42 2.10 2.10 

 Both 1.67 1.58 1.58 

Congo (Brazzaville) DHS-VI 2011-12 Age at death 0.35 0.35 0.35 9,661 

Years since death 1.74 1.56 1.56 

 Both 0.28 0.27 0.27 

Congo Democratic 

Republic DHS-V 2007 Age at death 2.17 2.45 2.45 12,522

 Years since death 2.03 2.49 2.49 

 Both 1.12 1.14 1.14 

Cote d’Ivoire DHS-V 1994 Age at death 1.79 2.56 2.56 7,852

Years since death 0.87 1.57 1.57 

 Both 0.68 1.33 1.33 

Cote d’Ivoire DHS-V 2005 Age at death 0.25 0.28 0.28 5,889

 Years since death 0.35 1.05 1.05 

 Both 0.09 0.14 0.14 

Cote d’Ivoire DHS-VI 2011-12 Age at death 3.41 3.15 3.15 12,038

Years since death 3.59 3.63 3.63 

 Both 1.93 1.70 1.70 

(Continued...)
35 

Table 3.5 – Continued

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings No. of all siblings 

Sub-Saharan Africa 

Ethiopia DHS-IV 2000 Age at death 0.27 0.27 0.27 25,598 

Years since death 0.36 0.38 0.38 

 Both 0.25 0.26 0.26 

Ethiopia DHS-V 2005 Age at death 1.21 1.26 1.26 17,648

Years since death 1.83 1.94 1.94 

 Both 1.09 1.14 1.14 

Ethiopia DHS-VI 2011 Age at death 0.21 0.23 0.23 22,708 

Years since death 0.59 0.46 0.46 

 Both 0.14 0.12 0.12 

Gabon DHS-IV 2000 Age at death 5.46 4.76 4.76 5,898

Years since death 2.05 2.48 2.48 

 Both 1.73 1.86 1.86 

Gabon DHS-VI 2012 Age at death 12.11 11.29 11.29 7,242 

Years since death 12.22 11.25 11.25 

 Both 8.72 7.33 7.33 

Guinea DHS-IV 1999 Age at death 2.01 1.98 1.98 7,675

Years since death 2.73 3.00 3.00 

 Both 0.58 0.47 0.47 

Guinea DHS-V 2005 Age at death 0.95 1.11 1.11 11,036 

Years since death 1.07 1.21 1.21 

 Both 0.31 0.45 0.45 

Guinea DHS-VI 2012 Age at death 0.27 0.29 0.29 10,319

Years since death 0.70 0.60 0.60 

 Both 0.07 0.07 0.07 

Kenya DHS-III 1998 Age at death 3.60 4.15 4.15 6,115 

 Years since death 2.50 3.18 3.18 

 Both 2.04 2.51 2.51 

Kenya DHS-IV 2003 Age at death 4.53 5.30 5.30 7,617

Years since death 2.50 3.25 3.25 

 Both 1.85 2.28 2.28 

Kenya DHS-V 2008-09 Age at death 2.24 2.06 2.06 5,866 

Years since death 2.79 2.78 2.78 

 Both 1.65 1.54 1.54 

Lesotho DHS-IV 2004 Age at death 3.41 3.00 3.00 6,612

Years since death 3.91 4.00 4.00 

 Both 2.01 1.85 1.85 

(Continued...)

 
36 

Table 3.5 – Continued

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings No. of all siblings 

Sub-Saharan Africa 

Lesotho DHS-VI 2009 Age at death 22.83 24.25 24.25 6,796

Years since death 22.84 25.29 25.29 

 Both 14.67 16.56 16.56 

Liberia DHS-V 2007 Age at death 1.93 1.65 1.65 3,891 

 Years since death 3.89 3.90 3.90 

 Both 1.36 1.22 1.22 

Madagascar DHS-II 1992 Age at death 30.49 31.23 31.23 6,920

Years since death 10.29 11.33 11.33 

 Both 8.06 8.96 8.96 

Madagascar DHS-III 1997 Age at death 0.00 0.04 0.04 5,934 

 Years since death 12.50 12.74 12.74 

 Both 0.00 0.01 0.01 

Madagascar DHS-IV 2003-04 Age at death 2.60 2.29 2.29 3,971

Years since death 5.80 4.87 4.87 

 Both 2.15 1.54 1.54 

Madagascar DHS-V 2008-09 Age at death 1.43 1.52 1.52 14,108 

 Years since death 2.58 2.58 2.58 

 Both 1.18 1.16 1.16 

Malawi DHS-II 1992 Age at death 0.49 0.48 0.48 9,110

Years since death 0.42 0.46 0.46 

 Both 0.09 0.12 0.12 

Malawi DHS-IV 2000 Age at death 0.19 0.15 0.15 22,211 

 Years since death 0.22 0.24 0.24 

 Both 0.07 0.05 0.05 

Malawi DHS-IV 2004 Age at death 0.84 1.09 1.09 14,031

Years since death 1.33 1.45 1.45 

 Both 0.51 0.73 0.73 

Malawi DHS-VI 2010 Age at death 0.21 0.28 0.28 37,305 

 Years since death 0.48 0.58 0.58 

 Both 0.11 0.15 0.15 

Mali DHS-III 1995-96 Age at death 0.99 1.14 1.14 13,885

Years since death 0.02 0.27 0.27 

 Both 0.00 0.09 0.09 

Mali DHS-IV 2001 Age at death 4.99 5.49 5.49 16,068 

 Years since death 5.33 5.45 5.45 

 Both 3.63 3.82 3.82 

(Continued...)

 
37 

Table 3.5 – Continued

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings No. of all siblings 

Sub-Saharan Africa 

Mali DHS-V 2006 Age at death 2.43 2.86 2.86 22,136

Years since death 2.30 2.86 2.86 

 Both 1.45 1.92 1.92 

Mali DHS-VI 2012-13 Age at death 11.29 12.26 12.26 4,067 

 Years since death 0.06 0.07 0.07 

 Both 0.00 0.05 0.05 

Mozambique DHS-III 1997 Age at death 60.29 59.33 59.33 8,493

Years since death 22.50 24.07 24.07 

 Both 18.14 19.43 19.43 

Mozambique DHS-IV 2003 Age at death 0.59 0.62 0.62 13,232 

 Years since death 3.43 3.80 3.80 

 Both 0.27 0.36 0.36 

Mozambique DHS-VI 2011 Age at death 0.00 0.00 0.00 10,291

Years since death 11.93 12.90 12.90 

 Both 0.00 0.00 0.00 

Namibia DHS-II 1992 Age at death 19.61 20.48 20.48 4,181 

 Years since death 13.99 15.47 15.47 

 Both 11.08 11.48 11.48 

Namibia DHS-IV 2000 Age at death 17.00 18.09 18.09 4,809

Years since death 15.97 17.05 17.05 

 Both 11.49 12.44 12.44 

Namibia DHS-V 2006-07 Age at death 2.56 2.68 2.68 7,600 

 Years since death 4.14 4.33 4.33 

 Both 1.94 2.09 2.09 

Nigeria DHS-IV 1999 Age at death 2.21 2.40 2.40 5,125

Years since death 25.15 26.89 26.89 

 Both 1.80 1.90 1.90 

Nigeria DHS-V 2008 Age at death 2.63 2.82 2.82 30,098 

 Years since death 3.96 4.22 4.22 

 Both 1.80 1.89 1.89 

Rwanda DHS-IV 2000 Age at death 1.37 1.51 1.51 19,347

Years since death 1.31 1.39 1.39 

 Both 0.75 0.83 0.83 

Rwanda DHS-V 2005 Age at death 4.43 4.27 4.27 22,578 

 Years since death 1.85 1.98 1.98 

 Both 1.03 1.09 1.09 

(Continued...)

 
38 

Table 3.5 – Continued

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings No. of all siblings 

Sub-Saharan Africa 

Rwanda DHS-VI 2010 Age at death 0.43 0.42 0.42 22,410

Years since death 0.45 0.47 0.47 

 Both 0.23 0.26 0.26 

Sao Tome and 

Principe DHS-V 2008-09 Age at death 8.91 8.14 8.14 2,533 

Years since death 2.88 2.82 2.82 

 Both 0.77 0.69 0.69 

Senegal DHS-II 1992-93 Age at death 0.77 1.14 1.14 8,138

Years since death 0.61 1.02 1.02 

 Both 0.45 0.76 0.76 

Senegal DHS-IV 2005 Age at death 2.80 2.82 2.82 15,213 

Years since death 2.67 2.80 2.80 

 Both 1.59 1.65 1.65 

Senegal DHS-VI 2010-11 Age at death 0.00 0.00 0.00 16,125

Years since death 0.00 0.00 0.00 

 Both 0.00 0.00 0.00 

Sierra Leone DHS-V 2008 Age at death 7.76 8.08 8.08 6,129 

Years since death 9.52 11.12 11.12 

 Both 5.18 5.76 5.76 

South Africa DHS-III 1998 Age at death 1.80 1.87 1.87 6,367

Years since death 22.24 22.58 22.58 

 Both 1.44 1.66 1.66 

Swaziland DHS-V 2006-07 Age at death 2.03 2.33 2.33 3,970 

Years since death 2.89 3.35 3.35 

 Both 1.30 1.40 1.40 

Tanzania DHS-III 1996 Age at death 10.61 11.45 11.45 8,508

Years since death 3.08 3.55 3.55 

 Both 2.51 2.82 2.82 

Tanzania DHS-IV 2004-05 Age at death 0.74 0.91 0.91 13,159 

Years since death 0.88 1.04 1.04 

 Both 0.55 0.73 0.73 

Tanzania DHS-VI 2010 Age at death 0.89 0.99 0.99 8,931

Years since death 0.97 0.98 0.98 

 Both 0.41 0.41 0.41 

Togo DHS-III 1998 Age at death 0.00 0.00 0.00 11,029 

Years since death 0.26 0.38 0.38 

 Both 0.00 0.00 0.00 

(Continued...)
39 

Table 3.5 – Continued

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings No. of all siblings 

Sub-Saharan Africa 

Uganda DHS-III 1995-96 Age at death 14.24 14.17 14.17 9,511

Years since death 5.40 5.21 5.21 

 Both 4.15 4.09 4.09 

Uganda DHS-IV 2000-01 Age at death 0.82 0.78 0.78 10,945 

 Years since death 6.19 7.22 7.22 

 Both 0.40 0.55 0.55 

Uganda DHS-V 2006 Age at death 0.89 0.97 0.97 15,128

Years since death 1.06 1.41 1.41 

 Both 0.51 0.62 0.62 

Uganda DHS-VI 2011 Age at death 2.06 2.29 2.29 13,351 

 Years since death 1.28 1.41 1.41 

 Both 1.17 1.29 1.29 

Zambia DHS-III 1996 Age at death 3.58 3.68 3.68 10,060

Years since death 3.00 3.16 3.16 

 Both 2.26 2.39 2.39 

Zambia DHS-IV 2001-02 Age at death 0.24 0.23 0.23 9,853 

 Years since death 0.75 0.82 0.82 

 Both 0.15 0.16 0.16 

Zambia DHS-V 2007 Age at death 0.98 1.37 1.37 7,689

Years since death 1.39 1.75 1.75 

 Both 0.90 1.20 1.20 

Zimbabwe DHS-III 1994 Age at death 0.35 0.43 0.43 5,752 

 Years since death 0.58 0.72 0.72 

 Both 0.14 0.12 0.12 

Zimbabwe DHS-IV 1999 Age at death 0.00 0.00 0.00 4,540

Years since death 4.06 4.70 4.70 

 Both 0.00 0.00 0.00 

Zimbabwe DHS-V 2005-06 Age at death 1.10 1.16 1.16 6,884 

 Years since death 2.03 2.09 2.09 

 Both 0.68 0.71 0.71 

Zimbabwe DHS-VI 2010-11 Age at death 8.41 9.24 9.24 6,640 

 Years since death 11.14 12.19 12.19 

 Both 6.47 6.75 6.75 

(Continued...)

 
40 

Table 3.5 – Continued

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings No. of all siblings 

North Africa 

Jordan DHS-III 1997 Age at death 0.00 0.00 0.00 9,270

Years since death 0.46 0.44 0.44 

 Both 0.00 0.00 0.00 

Morocco DHS-II 1992 Age at death 1.94 2.01 2.01 10,664

Years since death 1.27 1.22 1.22 

 Both 1.19 1.13 1.13 

Morocco DHS-IV 2003-04 Age at death 1.12 1.10 1.10 17,992

Years since death 0.62 0.80 0.80 

 Both 0.48 0.63 0.63 

Asia 

Cambodia DHS-IV 2000 Age at death 0.56 0.52 0.52 16,281 

 Years since death 1.05 1.06 1.06 

 Both 0.19 0.32 0.32 

Cambodia DHS-V 2005 Age at death 1.15 1.42 1.42 18,708 

 Years since death 1.14 1.41 1.41 

 Both 0.92 1.20 1.20 

Cambodia DHS-VI 2010 Age at death 0.20 0.22 0.22 15,101 

 Years since death 0.23 0.24 0.24 

 Both 0.12 0.12 0.12 

Indonesia DHS-III 1994 Age at death 7.56 7.82 7.82 29,226 

 Years since death 1.52 1.66 1.66 

 Both 1.23 1.36 1.36 

Indonesia DHS-III 1997 Age at death 0.00 0.05 0.05 20,869 

 Years since death 1.00 1.20 1.20 

 Both 0.00 0.01 0.01 

Indonesia DHS-IV 2002-03 Age at death 3.55 3.45 3.45 17,151 

 Years since death 2.16 2.73 2.73 

 Both 0.34 0.52 0.52 

Indonesia DHS-V 2007 Age at death 0.00 0.00 0.00 21,032 

 Years since death 3.12 2.87 2.87 

 Both 0.00 0.00 0.00 

Indonesia DHS-VI 2012 Age at death 0.00 0.00 0.00 26,191 

 Years since death 2.31 2.83 2.83 

 Both 0.00 0.00 0.00 

(Continued...)

 
41 

Table 3.5 – Continued

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings No. of all siblings 

Asia 

Nepal DHS-III 1996 Age at death 0.17 0.13 0.13 13,349

Years since death 0.42 0.33 0.33 

 Both 0.13 0.09 0.09 

Nepal DHS-V 2006 Age at death 0.00 0.00 0.00 11,333

Years since death 0.00 0.00 0.00 

 Both 0.00 0.00 0.00 

Niger DHS-II 1992 Age at death 9.37 9.60 9.60 10,217

Years since death 4.54 5.64 5.64 

 Both 3.84 4.84 4.84 

Niger DHS-V 2006 Age at death 1.00 1.18 1.18 13,520

Years since death 0.83 1.08 1.08 

 Both 0.35 0.58 0.58 

Niger DHS-VI 2012 Age at death 0.29 0.42 0.42 18,147

Years since death 0.54 0.63 0.63 

 Both 0.15 0.23 0.23 

Philippines DHS-III 1993 Age at death 2.50 2.25 2.25 8,110

Years since death 2.45 2.76 2.76 

 Both 1.24 1.32 1.32 

Philippines DHS-III 1998 Age at death 0.64 0.66 0.66 8,449

Years since death 4.89 4.90 4.90 

 Both 0.54 0.42 0.42 

TimorLeste DHS-VI 2009-10 Age at death 0.42 0.48 0.48 10,147

Years since death 0.46 0.55 0.55 

 Both 0.37 0.41 0.41 

Latin America and 

Caribbean 

Bolivia DHS-III 1994 Age at death 10.31 10.37 10.37 7,773

Years since death 2.31 2.39 2.39 

 Both 1.68 1.76 1.76 

Bolivia DHS-IV 2003 Age at death 0.14 0.12 0.12 17,347

Years since death 4.30 5.35 5.35 

 Both 0.05 0.04 0.04 

Bolivia DHS-V 2008 Age at death 0.00 0.00 0.00 14,594

Years since death 0.89 1.56 1.56 

 Both 0.00 0.00 0.00 

(Continued...)

 
42 

Table 3.5 – Continued

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings No. of all siblings 

Latin America and 

Caribbean 

Brazil DHS-III 1996 Age at death 47.92 45.65 45.65 10,697 

 Years since death 9.57 10.02 10.02 

 Both 7.13 6.87 6.87 

Dominican Republic DHS-IV 2002 Age at death 2.26 1.91 1.91 6,733 

 Years since death 13.42 14.35 14.35 

 Both 1.03 0.84 0.84 

Dominican Republic DHS-V 2007 Age at death 0.00 0.00 0.00 14,048 

 Years since death 4.79 5.81 5.81 

 Both 0.00 0.00 0.00 

Guatemala DHS-III 1995 Age at death 3.13 3.46 3.46 11,943 

 Years since death 3.34 3.83 3.83 

 Both 1.39 1.52 1.52 

Haiti DHS-IV 2000 Age at death 0.14 0.19 0.19 14,587 

 Years since death 0.21 0.27 0.27 

 Both 0.04 0.06 0.06 

Haiti DHS-V 2005-06 Age at death 0.38 0.30 0.30 14,541 

 Years since death 0.36 0.32 0.32 

 Both 0.25 0.21 0.21 

Peru DHS-II 1991-92 Age at death 19.49 19.48 19.48 10,480 

 Years since death 7.45 8.10 8.10 

 Both 5.82 6.44 6.44 

Peru DHS-III 1996 Age at death 23.23 23.73 23.73 28,141 

 Years since death 5.49 6.02 6.02 

 Both 4.26 4.79 4.79 

Peru DHS-IV 2000 Age at death 0.29 0.36 0.36 24,878 

 Years since death 1.98 2.28 2.28 

 Both 0.13 0.15 0.15 

Peru DHS-V 2004-06 Age at death 0.00 0.00 0.00 33,745 

 Years since death 0.42 0.45 0.45 

 Both 0.00 0.00 0.00 

Peru DHS-V 2007-08 Age at death 0.00 0.00 0.00 33,745 

 Years since death 0.42 0.45 0.45 

 Both 0.00 0.00 0.00 

(Continued...)

 
43 

Table 3.5 – Continued

 

Percentage of dead siblings with 

missing age at death and missing 

years since death 

Country DHS survey 

round 

Year of 

survey Missing information Sisters Brothers All siblings No. of all siblings 

Latin America and 

Caribbean 

Peru DHS-V 2009 Age at death 0.00 0.00 0.00 17,249 

 Years since death 0.66 0.80 0.80 

 Both 0.00 0.00 0.00 

Peru DHS-VI 2011 Age at death 0.00 0.00 0.00 15,338 

 Years since death 0.23 0.42 0.42 

 Both 0.00 0.00 0.00 

DHS imputes the missing values so that complete information on the year of death and age at death can be 

used for the calculation of the person-y ears of expo sure for eac h dead sibling. Figure 3.7 shows the 

percentage of dead sibling’s age imputed by the lag period of death (years ago died). Not surprisingly, the 

percentage of missing age data was higher for siblings who had died further in the past in most surveys. 

Respondents often have significant difficulty remembering age at death and calendar timing of death for 

siblings who died many years ago. Additionally, focusing on these questions can exert undue pressure on 

respondents to recall sensitive events in the distant past. It is well recognized that the reporti ng of recent 

deaths is substantially more reliable than reporting of deaths that occurred in the distant past, which is the 

reason DHS limits analysis of mortality data to the last five to seven years. We show in Appendix (Table 

A2) that in the majority of the surveys (66%), less than 20% of sisters died within seven years (30% in 97 

of 109 surveys for which timing of death data were publicly available). Information from only these sisters 

who died in the last seven years are used in mortality (maternal or from all causes) analysis. We expect a 

similar proportion of deaths within seven years among brothers. Considering the high level of non-response 

for death inf ormation—especially regarding deat hs that occurred a long tim e ago—and because th e 

information of deaths beyond the reference period (five to seven years before the survey) is never used by 

DHS for any analyses of the sibling survival data, we think it would be beneficial to examine the impact of 

limiting the histor y recall period with a truncated sibling history module. An exa mple is t he use of a 

truncated mortality listing table in the direct household maternal mortality estimation module of the 

Household Questionnaire of the Bangl adesh Maternal Health Services and Maternal Mortalit y Survey 

(NIPORT et al. 2003). In this table, only the individual household members who died in the reference 

observation period (last three years in case of BMMS) are listed. Instead of listing all siblings born to the 

biological mother, following the structure in the direct household maternal mortality estimation module, 

the DHS surveys may list only the surviving siblings first and then list the siblings that died in the last seven 

years, with a provision of birth ordering. The listing of birth ordering is likely to improve imputation when 

age/date of birth is missing. 

Truncated history often encourages interviewers to introduce age or calendar time displacement to avoid 

lengthy subsequent questions. The DHS Program’s experience of the direct household maternal mortality 

estimation module in the Bangladesh Maternal Mortality and Health Care Surve y in 2001 and 2010, 

Afghanistan Mortality Survey 2010, and Ghana Maternal Health Survey 2007 may help to minimize such 

biases. An example of the listing table for the household members who died during the reference period is 

shown in the Appendix from the BMMS questionnaire, which collected information on deaths only from 

the household members who died in the last three years. Despite the concerns of displacement of timing of 
44 

deaths in such tim e bounded, truncated survival ta ble questions, the m aternal mortality ratio (MMR) 

estimates in Bangladesh, Afghanistan, and Ghana showed overestimation, rather than underesti mation, 

compared with sibling history-based estimates for the same period (Bangladesh Maternal Mortality and 

Health Care Survey in 2001 and 2010, Afghanistan Mortality Survey 2010, and Ghana Mat ernal Health 

Survey 2007). 

However, if age or calendar displacement is a real or anticipated concern, the data collection observation 

period may be extended to siblings who died within eight years, instead of seven years, in the truncated 

sibling history module, and the information from the last year may be discarded during data analysis. 
45 

Figure 3.7 Percentage of dead siblings with age imputed by timing of death (number of years ago 

death occurred), Demographic and Health Surveys 1990-2013 

 (Continued...) 

0 1 2 3 4 5

Percent

0 10 20 30 40 50 Years ago died

Benin

1996

0 1 2 3 4

Percent

0 10 20 30 40 50 Years ago died

Benin

2006

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Bolivia

1993-94

0 5 10152025

Percent

0 10 20 30 40 50 Years ago died

Bolivia

2003-04

0 1 2 3 4 5

Percent

0 10 20 30 40 50

Years ago died

Bolivia

2008

0 5 10 15 20

Percent

0 10 20 30 40 50

Years ago died

Brazil

1996

5 10 15 20 25

Percent

0 10 20 30 40 50

Years ago died

Burkina Faso

1998-99

0 5 10 15

Percent

0 10 20 30 40 50

Years ago died

Burkina Faso

2003

0 1 2 3 4

Percent

0 10 20 30 40 50 Years ago died

Burkina Faso

2010

0 .5 1 1.5 2

Percent

0 10 20 30 40 50 Years ago died

Burundi

2010-11

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Cambodia

2000

-5 0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Cambodia

2005-06

0 1 2 3 4

Percent

0 10 20 30 40 50

Years ago died

Cambodia

2010-11

0 1 2 3

Percent

0 10 20 30 40 50

Years ago died

Cameroon

1998

0 2 4 6 8 10

Percent

0 10 20 30 40 50

Years ago died

Cameroon

2004

0 1 2 3 4 5

Percent

0 10 20 30 40 50

Years ago died

Cameroon

2011

0 1 2 3 4

Percent

0 10 20 30 40 50

Years ago died

CAR

1994-95

0 2 4 6

Percent

0 10 20 30 40 50

Years ago died

Chad

1996-97

0 1 2 3

Percent

0 10 20 30 40 50

Years ago died

Chad

2004

0 5 10 15

Percent

0 10 20 30 40 50

Years ago died

Congo (Brazzaville)

2005

0 2 4 6 8 10

Percent

0 10 20 30 40 50 Years ago died

Congo (Brazzaville)

2011-12

0 2 4 6 8 Percent

0 10 20 30 40 50 Years ago died

Congo Democratic Republic

2007

0 1 2 3 4

Percent

0 10 20 30 40 50 Years ago died

Cote d'Ivoire

1994

0 2 4 6 8 10

Percent

0 10 20 30 40 50 Years ago died

Cote d'Ivoire

2005

Congo Democratic Republic

2007

0 2 4 6 8

Percent
46 

Figure 3.7 – Continued

(Continued...) 

 

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Cote d'Ivoire

2011-12

5 10 15 20 25

Percent

0 10 20 30 40 50 Years ago died

Dominican Republic

2002

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Dominican Republic

2007

0 .5 1 1.5

Percent

0 10 20 30 40 50 Years ago died

Ethiopia

2000

0 2 4 6

Percent

0 10 20 30 40 50

Years ago died

Ethiopia

2005

0 .5 1 1.5 2 2.5

Percent

0 10 20 30 40 50

Years ago died

Ethiopia

2011

0 2 4 6 8 10

Percent

0 10 20 30 40 50

Years ago died

Gabon

2000-01

0 10 20 30 40

Percent

0 10 20 30 40 50

Years ago died

Gabon

2012

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Guatemala

1995

0 2 4 6 8 10

Percent

0 10 20 30 40 50 Years ago died

Guinea

1999

0 2 4 6

Percent

0 10 20 30 40 50 Years ago died

Guinea

2005

0 1 2 3 4

Percent

0 10 20 30 40 50 Years ago died

Guinea

2012

0 1 2 3 4

Percent

0 10 20 30 40 50

Years ago died

Haiti

2000

0 .5 1 1.5

Percent

0 10 20 30 40 50

Years ago died

Haiti

2005-06

0 2 4 6 8

Percent

0 10 20 30 40 50

Years ago died

Indonesia

1994

0 2 4 6 8

Percent

0 10 20 30 40 50

Years ago died

Indonesia

1997

0 5 10 15

Percent

0 10 20 30 40 50

Years ago died

Indonesia

2002-03

0 2 4 6 8 10

Percent

0 10 20 30 40 50

Years ago died

Indonesia

2007

0 2 4 6 8

Percent

0 10 20 30 40 50

Years ago died

Indonesia

2012

0 1 2 3 4

Percent

0 10 20 30 40 50

Years ago died

Jordan

1997

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Kenya

1998

0 2 4 6 8 10

Percent

0 10 20 30 40 50 Years ago died

Kenya

2003

0 5 10 15 20

Percent

0 10 20 30 40 50 Years ago died

Kenya

2008-09

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Lesotho

2004-05
47 

Figure 3.7 – Continued

(Continued...)

 

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Cote d'Ivoire

2011-12

5 10 15 20 25

Percent

0 10 20 30 40 50 Years ago died

Dominican Republic

2002

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Dominican Republic

2007

0 .5 1 1.5

Percent

0 10 20 30 40 50 Years ago died

Ethiopia

1992

0 2 4 6

Percent

0 10 20 30 40 50

Years ago died

Ethiopia

1997

0 .5 1 1.5 2 2.5

Percent

0 10 20 30 40 50

Years ago died

Ethiopia

2003

0 2 4 6 8 10

Percent

0 10 20 30 40 50

Years ago died

Gabon

2000-01

0 10 20 30 40

Percent

0 10 20 30 40 50

Years ago died

Gabon

2012

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Guatemala

1995

0 2 4 6 8 10

Percent

0 10 20 30 40 50 Years ago died

Guinea

1999

0 2 4 6

Percent

0 10 20 30 40 50 Years ago died

Guinea

2005

0 1 2 3 4

Percent

0 10 20 30 40 50 Years ago died

Guinea

2012

0 1 2 3 4

Percent

0 10 20 30 40 50 Years ago died

Haiti

2000

0 .5 1 1.5

Percent

0 10 20 30 40 50 Years ago died

Haiti

2005-06

0 2 4 6 8

Percent

0 10 20 30 40 50 Years ago died

Indonesia

1994

0 2 4 6 8

Percent

0 10 20 30 40 50 Years ago died

Indonesia

1997

0 5 10 15

Percent

0 10 20 30 40 50

Years ago died

Indonesia

2002-03

0 2 4 6 8 10

Percent

0 10 20 30 40 50

Years ago died

Indonesia

2007

0 2 4 6 8

Percent

0 10 20 30 40 50

Years ago died

Indonesia

2012

0 1 2 3 4

Percent

0 10 20 30 40 50

Years ago died

Jordan

1997

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Kenya

1998

0 2 4 6 8 10

Percent

0 10 20 30 40 50 Years ago died

Kenya

2003

0 5 10 15 20

Percent

0 10 20 30 40 50 Years ago died

Kenya

2008-09

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Lesotho

2004-05
48 

Figure 3.7 – Continued

(Continued...) 

 

0 10 20 30

Percent

0 10 20 30 40 50 Years ago died

Liberia

2006-07

0 10 20 30 40

Percent

0 10 20 30 40 50 Years ago died

Madagascar

1997

0 5 10152025

Percent

0 10 20 30 40 50 Years ago died

Madagascar

2003-04

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Madagascar

2008-09

0 1 2 3

Percent

0 10 20 30 40 50

Years ago died

Malawi

1992

0 .2 .4 .6 .8 1

Percent

0 10 20 30 40 50

Years ago died

Malawi

2000

0 2 4 6

Percent

0 10 20 30 40 50

Years ago died

Malawi

2004-05

0 .5 1 1.5 2

Percent

0 10 20 30 40 50

Years ago died

Malawi

2010

0 .5 1 1.5 2 2.5

Percent

0 10 20 30 40 50 Years ago died

Mali

1995-96

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Mali

2001

0 2 4 6 8 10

Percent

0 10 20 30 40 50 Years ago died

Mali

2006

0 .5 1 1.5

Percent

0 10 20 30 40 50 Years ago died

Mali

2012-13

0 1 2 3 4

Percent

0 10 20 30 40 50 Years ago died

Morocco

1992

0 1 2 3 4

Percent

0 10 20 30 40 50 Years ago died

Morocco

2003-04

0 20 40 60 80

Percent

0 10 20 30 40 50 Years ago died

Mozambique

1997

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Mozambique

2003-04

5 10 15 20 25

Percent

0 10 20 30 40 50 Years ago died

Mozambique

2011

0 10 20 30 40

Percent

0 10 20 30 40 50 Years ago died

Namibia

1992

0 20 40 60

Percent

0 10 20 30 40 50 Years ago died

Namibia

2000

0 5 10 15

Percent

0 10 20 30 40 50 Years ago died

Namibia

2006-07

0 .5 1 1.5 2 2.5

Percent

0 10 20 30 40 50 Years ago died

Nepal

1996

0 5 10 15 20

Percent

0 10 20 30 40 50 Years ago died

Niger

1992

0 2 4 6

Percent

0 10 20 30 40 50 Years ago died

Niger

2006

0 1 2 3 4 5

Percent

0 10 20 30 40 50 Years ago died

Niger

2012
49 

Figure 3.7 – Continued

(Continued...)

20 30 40 50 60

Percent

0 10 20 30 40 50 Years ago died

Nigeria

1999

2 4 6 8 10

Percent

0 10 20 30 40 50 Years ago died

Nigeria

2008

5 10 15 20 25

Percent

0 10 20 30 40 50 Years ago died

Peru

1991-92

2 4 6 8 1012

Percent

0 10 20 30 40 50 Years ago died

Peru

1996

1 2 3 4 5 6

Percent

0 10 20 30 40 50

Years ago died

Peru

2000

0 1 2 3

Percent

0 10 20 30 40 50

Years ago died

Peru

2011

0 1 2 3

Percent

0 10 20 30 40 50

Years ago died

Peru

2011

0 5 10 15

Percent

0 10 20 30 40 50

Years ago died

Philippines

1993

0 5 10 15 20

Percent

0 10 20 30 40 50 Years ago died

Philippines

1998

0 2 4 6 8

Percent

0 10 20 30 40 50 Years ago died

Rwanda

2000

0 2 4 6 8

Percent

0 10 20 30 40 50 Years ago died

Rwanda

2005

0 2 4 6

Percent

0 10 20 30 40 50 Years ago died

Rwanda

2010-11

0 5 10 15 20 Percent

0 10 20 30 40 50

Years ago died

Sao Tome and Principe

2008-09

0 2 4 6

Percent

0 10 20 30 40 50

Years ago died

Senegal

1992-93

0 2 4 6 8

Percent

0 10 20 30 40 50

Years ago died

Senegal

2005

0 10 20 30 40

Percent

0 10 20 30 40 50

Years ago died

Sierra Leone

2008

10 20 30 40 50

Percent

0 10 20 30 40 50

Years ago died

South Africa

1998

0 5 10 15

Percent

0 10 20 30 40 50

Years ago died

Swaziland

2006-07

0 2 4 6 8

Percent

0 10 20 30 40 50

Years ago died

Tanzania

1996

0 2 4 6

Percent

0 10 20 30 40 50

Years ago died

Tanzania

2004-05

0 2 4 6

Percent

0 10 20 30 40 50 Years ago died

Tanzania

2009-10

0 2 4 6

Percent

0 10 20 30 40 50 Years ago died

Timor-Leste

2009-10

0 .5 1 1.5 2

Percent

0 10 20 30 40 50 Years ago died

Togo

1998

0 5 10 15 20

Percent

0 10 20 30 40 50 Years ago died

Uganda

1995
50 

Figure 3.7 – Continued

Note: The Madagascar 1992, Peru 2009, and Peru 2010 survey rounds had no imputation in the 

publicly available files. 

 

It is expected that the mothers of older women have completed their fertility (parity completed) while the 

mothers of younger women may not have yet. Furthermore, in most countries, fertility has declined in 

recent years. In that case, sibship size (parity of mothers) of older respondents is likel y to be greater than 

or equal to the sibship size of younger respondents. A lower level of parity for mothers of older respondents 

may suggest underreporti ng of siblings. This may bias maternal mortality estimates because of 

underrepresentation of the siblings of older respondents. Table 3.6 shows the mean parity of mothers of 

respondents by five-year age groups o f the respondents. As an illustration, th e results fro m surveys in 

Indonesia during Phase-III and Phase-VI show that the mean sibship size of older wo men remained high 

through the five survey rounds, but it has declined for younger women. At each survey round, sibship size 

of older respondents was higher than or similar to the sibship si ze of younger respondents. This is an 

expected pattern with the recent trends in fertility reduction. In contrast, in a few countries (CAR 1994-95, 

Malawi 1992, Mali 1995 , Nigeria 1999) sibship si ze was substantially lower for older r espondents, 

suggesting under-enumeration in these settings. Figure 3.8 shows the changes in the distribution of sibship 

size between DHS survey rounds in each country where more than one survey was conducted. 

 

0 10 20 30

Percent

0 10 20 30 40 50

Years ago died

Uganda

2000-01

0 1 2 3 4

Percent

0 10 20 30 40 50

Years ago died

Uganda

2006

0 2 4 6 8

Percent

0 10 20 30 40 50

Years ago died

Uganda

2011

0 5 101520

Percent

0 10 20 30 40 50

Years ago died

Zambia

1996-97

0 2 4 6

Percent

0 10 20 30 40 50

Years ago died

Zambia

2001-02

0 2 4 6 810

Percent

0 10 20 30 40 50

Years ago died

Zambia

2007

0 1 2 3

Percent

0 10 20 30 40 50

Years ago died

Zimbabwe

1994

0 5 101520

Percent

0 10 20 30 40 50

Years ago died

Zimbabwe

1999

0 5 10 15

Percent

0 10 20 30 40 50

Years ago died

Zimbabwe

2005-06
51 

Table 3.6 Mean parity of mothers of respondents by age of respondent, Demographic and Health Surveys 

1990-2013 

 Age of respondent 

Country 

DHS 

survey 

round 

Year of 

survey 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

No. of 

respondents 

Sub-Saharan Africa 

Benin DHS-III 1996 6.7 7.0 6.9 6.6 6.4 6.3 6.0 5,491 

Benin DHS-V 2006 6.3 6.6 6.7 6.7 6.7 6.6 6.4 17,794 

Burkina Faso DHS-III 1998-99 6.6 6.8 6.6 6.4 6.2 5.8 5.4 6,445 

Burkina Faso DHS-IV 2003 6.4 6.6 6.6 6.5 6.4 6.2 6.0 12,477 

Burkina Faso DHS-VI 2010 6.6 6.7 6.9 6.8 6.8 6.6 6.4 17,087 

Burundi DHS-VI 2010-11 7.3 7.6 7.6 7.6 7.6 7.3 7.0 9,389 

CAR DHS-III 1994-95 6.6 6.6 6.4 6.1 5.8 5.3 4.9 5,884 

Cameroon DHS-III 1998 7.0 7.2 7.2 7.1 7.0 6.4 6.4 5,501 

Cameroon DHS-IV 2004 7.0 7.2 7.3 7.2 7.4 7.0 6.8 10,656 

Cameroon DHS-VI 2011 6.5 6.9 7.1 7.3 7.3 7.3 6.9 15,426 

Chad DHS-III 1996-97 7.0 6.9 6.6 6.4 6.2 5.6 5.6 7,454 

Chad DHS-IV 2004 7.3 7.0 7.1 6.9 6.7 6.4 5.9 6,085 

Congo (Brazzaville) DHS-V 2005 6.0 6.6 7.0 7.4 7.3 7.1 7.0 7,051 

Congo (Brazzaville) DHS-VI 2011-12 5.6 6.0 6.4 6.6 6.9 6.9 6.9 10,819 

Congo Democratic 

Republic 

DHS-V 2007 6.9 7.2 7.2 7.4 7.6 7.2 6.8 9,995 

Côte d’Ivoire DHS-III 1994 6.7 6.8 6.7 6.4 6.1 6.0 5.3 8,099 

Côte d’Ivoire DHS-V 2005 6.0 6.8 6.9 7.2 7.3 7.1 7.0 5,183 

Côte d’Ivoire DHS-VI 2011-12 6.1 6.7 6.8 7.1 7.5 7.1 7.4 10,060 

Ethiopia DHS-IV 2000 7.2 7.3 7.1 6.9 6.7 6.8 6.5 15,367 

Ethiopia DHS-IV 2005 7.0 7.0 7.0 7.0 6.7 6.6 6.4 14,070 

Ethiopia DHS-VI 2011 7.0 7.2 7.1 7.1 7.4 7.1 7.0 16,515 

Gabon DHS-III 2000-01 6.8 7.1 7.2 7.0 6.7 6.4 5.7 6,183 

Gabon DHS-VI 2012 6.0 6.4 6.8 6.9 6.6 7.1 7.6 8,422 

Guinea DHS-III 1999 6.1 6.1 6.0 5.9 5.5 5.4 5.2 6,753 

Guinea DHS-IV 2005 6.4 6.5 6.6 6.5 6.5 6.3 6.0 7,954 

Guinea DHS-VI 2012 6.0 6.0 6.1 6.0 6.0 5.9 5.9 9,142 

Kenya DHS-III 1998 6.9 7.3 7.5 7.7 7.6 7.3 6.8 7,881 

Kenya DHS-IV 2003 6.8 7.1 8.0 7.9 8.0 8.0 8.2 8,195 

Kenya DHS-V 2008-09 6.3 6.8 6.8 7.5 7.5 7.5 7.6 8,444 

Lesotho DHS-IV 2004-05 5.2 5.7 5.9 6.4 6.3 6.4 6.5 7,095 

Lesotho DHS-V 2009-10 4.8 5.3 5.6 6.0 6.2 6.2 6.2 7,624 

Liberia DHS-V 2006-07 5.7 5.8 5.8 5.7 5.8 5.5 5.1 7,092 

Madagascar DHS-II 1992 7.4 7.7 7.8 7.6 7.2 7.0 6.1 6,260 

Madagascar DHS-III 1997 7.0 7.4 7.7 7.6 7.5 7.1 6.4 7,060 

Madagascar DHS-IV 2003-04 6.5 6.6 6.5 6.9 7.2 6.8 6.6 7,949 

Madagascar DHS-V 2008-09 6.3 6.9 7.0 7.2 7.4 7.5 7.3 17,375 

Malawi DHS-II 1992 7.5 7.5 7.4 7.1 7.2 6.7 6.4 4,849 

Malawi DHS-IV 2000 6.9 7.1 7.2 7.1 7.0 6.8 6.5 13,220 

Malawi DHS-IV 2004-05 6.4 6.5 6.7 6.8 6.8 6.4 6.5 11,698 

Malawi DHS-V 2010 6.6 6.9 7.0 7.4 7.5 7.3 7.3 23,020 

Mali DHS-III 1995-96 7.0 7.0 6.7 6.4 6.0 5.9 5.5 9,704 

Mali DHS-IV 2001 6.9 6.8 6.7 6.5 6.2 6.0 5.6 12,849 

(Continued...)
52 

Table 3.6 – Continued

 Age of respondent 

Country 

DHS 

survey 

round 

Year of 

survey 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

No. of 

respondents 

Sub-Saharan Africa 

Mali DHS-V 2006 7.2 7.4 7.2 7.1 6.9 6.7 6.4 14,583 

Mali DHS-VI 2012-13 5.3 5.2 5.1 4.8 5.0 4.6 4.4 10,424 

Mozambique DHS-III 1997 6.0 5.9 5.9 5.8 5.5 5.3 5.3 8,779 

Mozambique DHS-IV 2003-04 6.3 6.4 6.4 6.4 6.2 6.1 6.0 12,418 

Mozambique DHS-VI 2011 5.4 5.4 5.6 5.5 5.4 5.1 5.3 13,745 

Namibia DHS-II 1992 6.7 7.0 7.0 6.8 6.7 6.4 6.3 5,421 

Namibia DHS-IV 2000 6.1 6.6 6.8 6.8 6.7 6.7 6.8 6,755 

Namibia DHS-V 2006-07 5.5 6.2 6.5 6.8 7.0 7.1 7.0 9,804 

Niger DHS-II 1992 7.1 6.9 6.8 6.4 6.6 6.4 6.4 6,503 

Niger DHS-V 2006 7.4 7.3 7.2 7.3 7.1 6.7 6.7 9,223 

Niger DHS-VI 2012 7.5 7.5 7.4 7.3 7.5 7.1 7.1 11,160 

Nigeria DHS-III 1999 5.7 5.7 5.3 5.3 5.0 4.7 4.7 9,810 

Nigeria DHS-V 2008 6.5 6.8 6.7 6.7 6.6 6.4 6.1 33,385 

Rwanda DHS-IV 2000 7.0 7.4 7.6 7.6 7.4 7.1 6.7 10,421 

Rwanda DHS-IV 2005 7.1 7.5 7.6 7.7 7.8 7.7 7.5 11,321 

Rwanda DHS-VI 2010-11 6.5 7.0 7.2 7.6 7.7 7.6 7.5 13,671 

São Tomé and 

Príncipe 

DHS-V 2008-09 6.4 6.9 7.8 7.7 8.4 8.1 7.5 2,615 

Senegal DHS-II 1992-93 7.0 7.1 6.8 6.5 6.2 5.9 5.5 6,310 

Senegal DHS-IV 2005 6.9 7.1 7.2 7.3 7.1 6.9 6.7 14,602 

Senegal DHS-VI 2010-11 6.6 6.8 6.9 7.0 6.9 6.9 6.4 15,688 

Sierra Leone DHS-V 2008 5.7 5.9 6.1 6.0 5.8 5.8 5.7 7,374 

South Africa DHS-III 1998 4.6 5.0 5.4 5.6 5.6 6.0 6.2 11,735 

Swaziland DHS-V 2006-07 5.8 6.2 6.5 6.7 6.8 6.5 6.8 4,987 

Tanzania DHS-III 1996 6.7 7.2 7.2 7.2 6.7 6.4 6.1 8,120 

Tanzania DHS-IV 2004-05 6.7 7.0 7.5 7.7 7.8 7.7 7.3 10,329 

Tanzania DHS-V 2009-10 6.1 6.5 6.6 6.9 6.9 6.9 6.9 10,139 

Togo DHS-III 1998 6.4 7.0 7.0 7.0 6.9 6.7 6.5 8,569 

Uganda DHS-III 1995 6.9 7.5 7.5 7.5 7.3 6.8 6.5 7,070 

Uganda DHS-IV 2000-01 7.3 7.5 7.7 8.0 7.7 7.6 7.4 7,246 

Uganda DHS-V 2006 7.7 7.7 8.0 8.3 8.4 8.1 8.0 8,531 

Uganda DHS-VI 2011 7.4 7.7 7.8 8.0 8.2 8.3 8.1 8,674 

Zambia DHS-III 1996-97 7.2 7.6 7.8 7.7 7.4 7.1 6.3 8,021 

Zambia DHS-IV 2001-02 6.9 7.2 7.5 7.5 7.6 7.3 6.7 7,658 

Zambia DHS-V 2007 6.3 6.5 7.0 7.2 7.4 7.2 6.9 7,146 

Zimbabwe DHS-III 1994 6.7 7.3 7.5 7.6 7.7 7.6 7.2 6,128 

Zimbabwe DHS-IV 1999 6.1 6.7 7.2 7.5 7.4 7.1 7.0 5,907 

Zimbabwe DHS-V 2005-06 5.5 6.0 6.6 6.9 7.4 7.3 7.5 8,907 

Zimbabwe DHS-VI 2010-11 4.7 5.4 5.8 6.1 6.5 6.7 6.6 9,171 

North Africa 

Jordan DHS-III 1997 9.5 9.5 9.4 9.3 9.2 9.1 8.5 10,165 

Morocco DHS-II 1992 7.7 7.8 7.9 7.8 7.4 6.8 6.1 9,256 

Morocco DHS-IV 2003-04 6.5 7.2 7.8 8.0 8.1 8.1 7.8 16,798 

(Continued...)
53 

Table 3.6 – Continued

 Age of respondent 

Country 

DHS 

survey 

round 

Year of 

survey 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

No. of 

respondents 

Asia 

Cambodia DHS-IV 2000 6.2 6.3 6.1 6.4 6.3 6.2 6.0 15,351 

Cambodia DHS-V 2005-06 6.0 6.4 6.6 6.8 6.6 6.7 6.6 16,823 

Cambodia DHS-V 2010-11 5.2 5.7 6.0 6.3 6.3 6.3 6.3 18,754 

Indonesia DHS-III 1994 5.3 5.8 5.9 5.9 5.8 5.7 5.3 38,334 

Indonesia DHS-III 1997 4.6 5.3 5.5 5.6 5.6 5.5 5.2 38,590 

Indonesia DHS-IV 2002-03 4.3 5.0 5.5 5.7 5.8 5.9 5.8 39,315 

Indonesia DHS-V 2007 4.5 4.6 5.1 5.4 5.7 5.9 5.7 42,951 

Indonesia DHS-VI 2012 4.0 4.4 4.8 5.3 5.7 5.9 6.1 45,607 

Nepal DHS-III 1996 6.2 6.3 6.4 6.2 6.1 6.0 5.9 10,101 

Nepal DHS-V 2006 5.7 5.9 6.1 6.3 6.5 6.2 6.3 10,793 

Philippines DHS-II 1993 6.1 6.5 7.0 7.3 7.3 7.3 7.1 15,029 

Philippines DHS-III 1998 5.7 6.2 6.7 7.2 7.4 7.5 7.6 13,983 

Timor-Leste DHS-VI 2009-10 6.5 6.2 5.8 5.5 5.3 5.3 5.1 13,137 

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 6.1 6.1 6.2 6.3 5.9 5.7 5.2 8,603 

Bolivia DHS-IV 2003-04 6.1 6.3 6.6 6.8 6.7 6.7 6.6 17,654 

Bolivia DHS-V 2008 5.8 6.2 6.4 6.4 6.4 6.6 6.6 16,939 

Brazil DHS-III 1996 5.3 6.3 7.1 7.4 7.8 8.0 8.0 12,612 

Dominican Republic DHS-IV 2002 4.7 5.5 6.6 7.3 7.5 8.0 8.2 23,384 

Dominican Republic DHS-V 2007 4.3 5.0 5.9 6.6 7.4 7.8 8.3 27,195 

Guatemala DHS-III 1995 6.4 7.0 7.1 6.9 6.8 6.9 6.5 12,403 

Haiti DHS-IV 2000 6.4 6.9 6.8 6.9 7.0 6.8 6.6 10,159 

Haiti DHS-V 2005-06 6.5 6.9 6.9 7.1 7.1 6.9 6.8 10,757 

Peru DHS-II 1991-92 6.0 6.2 6.5 6.5 6.4 6.3 6.0 15,882 

Peru DHS-III 1996 6.1 6.7 7.1 7.4 7.6 7.4 7.4 28,951 

Peru DHS-IV 2000 5.6 6.2 6.7 7.1 7.3 7.2 7.2 27,843 

Peru DHS-V 2003-08 5.1 5.7 6.2 6.7 7.0 7.2 7.3 40,552 

Peru DHS-VI 2009 4.8 5.4 6.0 6.4 6.7 7.0 7.1 24,213 

Peru DHS-VI 2010 4.8 5.4 5.9 6.5 6.7 7.1 7.2 22,947 

Peru DHS-VI 2011 4.6 5.0 5.9 6.4 6.7 7.1 7.0 22,517 
54 

Figure 3.8 Distribution of mean parity of mothers of respondents by age of respondents, according 

to survey round, Demographic and Health Surveys 1990-2013 

4 6 8 10

4 6 8 10

4 6 8 10

4 6 8 10

4 6 8 10

4 6 8 10

15-1920-2425-2930-3435-3940-4445-4915-1920-2425-2930-3435-3940-4445-4915-1920-2425-2930-3435-3940-4445-49

15-1920-2425-2930-3435-3940-4445-4915-1920-2425-2930-3435-3940-4445-4915-1920-2425-2930-3435-3940-4445-49

Benin Bolivia Burkina Faso Cambodia Cameroon Chad

Congo (Brazzaville) Cote d'Ivoire Dominican Republic Ethiopia Gabon Guinea

Haiti Indonesia Kenya Lesotho Madagascar Malawi

Mali Morocco Mozambique Namibia Nepal Niger

Nigeria Peru Philippines Rwanda Senegal Tanzania

Uganda Zambia Zimbabwe

DHS-II DHS-III DHS-III

DHS-IV DHS-V

Parity of mother (sibship size)

Age group
55 

In the nationally representative DHS surveys, respondents are sampled in such a way that the survey sample 

represents the population (women age 15-49) of the country. In the sisterhood method, it is assumed that 

the reported sisters also constitute a representative sam ple of the population of the country and that it is 

possible to calculate unbiased estimates of maternal mortality indicators from these data. So, naturally it is 

expected that the age distr ibution of the DHS respondents and their siblings of reproductive age will be 

similar. We test this assum ption by comparing the age distributions of the respondents with the age 

distributions of reported surviving sisters. The distributions are shown in Table 3.7. A consistent pattern 

emerges for a large majority of co untries: the proportions of youngest (15-19) and oldest (45-49) siblings 

(sisters) are lower than th e proportions of youngest and oldest respondents. St ated differently, the two 

groups of siblings in the age below 20 and above 45 are underrepresented in the sibling data set. This 

problem may be due to age displacement during age reporting or a shift in the observation window of the 

birth cohort between respondents and siblings. However, it should be noted that the data on siblings are 

collected from respondents age 15-49 only, which by the study design truncates the siblings in extreme age 

groups in the reproductive period. A respondent of age 15 is unlikely to have a sibling above age 45, and 

similarly a respondent of 49 is unlikely to have a sibling below 20. As a result, the siblings in the age range 

below 20 or above 45 may not be captured adequately from the DHS survey respondents. Ther efore, it is 

difficult to assess age truncation or underreporting of adult sisters in these two extreme age groups from 

sibling survival history data. 

However, this problem is unlikel y to affect the maternal mortality estimates in DHS surv eys. During 

estimation, DHS surveys perform the age-standardization of the maternal mortality rates (MMRates) to 

match the age-distribution of sisters to the age dist ribution of the respondents. The age-standardization 

procedure washes out any effect of imbalance between the age-distributions of the survey respondents and 

their sisters. 

Table 3.7 Percent distribution of age of female respondents and their sisters, Demographic and Health 

Surveys 1990-2013 

 Age of female respondents/sisters 

Country 

DHS 

survey 

round 

Year of 

survey 

Respondents/ 

sisters 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

Median

year of 

birth Number

Sub-Saharan 

Africa 

Benin DHS-III 1996 Respondents 19.6 18.6 17.5 14.0 12.6 9.6 8.1 1968 5,491 

DHS-III Sisters 16.4 19.6 19.2 17.3 13.1 9.3 5.2 1970 17,468 

Benin DHS-V 2006 Respondents 17.2 17.9 20.5 15.7 11.9 9.0 7.9 1978 17,794 

DHS-V Sisters 14.9 19.5 20.1 17.8 13.3 9.1 5.3 1979 63,586 

Burkina Faso DHS-III 1998-99 Respondents 22.4 18.0 16.4 13.2 12.9 9.4 7.7 1971 6,445 

DHS-III Sisters 18.3 20.5 19.8 16.2 12.3 8.2 4.7 1974 20,035 

Burkina Faso DHS-IV 2003 Respondents 22.3 18.2 16.6 12.7 12.2 9.6 8.4 1975 12,477 

DHS-IV Sisters 16.9 20.4 19.4 16.3 12.7 9.0 5.3 1978 41,397 

Burkina Faso DHS-VI 2010 Respondents 19.4 19.4 17.3 15.1 11.7 9.6 7.5 1982 17,087 

DHS-VI Sisters 14.8 19.4 20.2 18.0 13.6 8.9 5.1 1984 62,824 

Burundi DHS-VI 2010-11 Respondents 25.1 19.5 17.1 11.3 11.4 7.9 7.6 1984 9,389 

DHS-VI Sisters 18.1 21.6 20.0 16.1 11.1 8.1 5.0 1986 33,478 

CAR DHS-III 1994-95 Respondents 21.9 19.1 17.5 14.4 12.0 7.8 7.2 1967 5,884 

DHS-III Sisters 16.4 20.7 20.8 17.8 12.2 8.0 4.1 1969 19,229 

Cameroon DHS-III 1998 Respondents 23.3 20.5 16.7 13.0 11.2 8.7 6.5 1972 5,501 

DHS-III Sisters 18.0 20.9 19.5 16.5 12.3 8.4 4.4 1973 19,676 

(Continued...)

 
56 

Table 3.7 – Continued

 Age of female respondents/sisters 

Country 

DHS 

survey 

round 

Year of 

survey 

Respondents/ 

sisters 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

Median

year of 

birth Number

Sub-Saharan 

Africa 

Cameroon DHS-IV 2004 Respondents 25.2 21.1 16.4 12.7 10.1 7.8 6.7 1978 10,656 

 DHS-IV Sisters 17.9 21.4 19.9 16.4 11.5 8.2 4.8 1979 39,559 

Cameroon DHS-VI 2011 Respondents 23.3 20.3 17.4 12.6 10.9 8.1 7.5 1984 15,426 

 DHS-VI Sisters 15.8 20.3 20.5 17.1 12.4 8.8 5.1 1984 56,850 

Chad DHS-III 1996-97 Respondents 23.0 18.4 18.1 13.1 11.7 8.0 7.7 1970 7,454 

 DHS-III Sisters 17.1 22.1 20.1 17.3 11.6 7.8 4.0 1972 24,078 

Chad DHS-IV 2004 Respondents 22.4 17.6 18.7 12.9 10.8 8.6 9.0 1978 6,085 

 DHS-IV Sisters 16.1 21.8 19.1 17.6 11.9 8.4 5.1 1980 21,141 

Congo (Brazzaville) DHS-V 2005 Respondents 22.2 21.2 17.6 13.2 11.8 7.8 6.2 1978 7,051 

 DHS-V Sisters 14.2 18.6 20.4 18.5 13.7 9.4 5.1 1978 27,148 

Congo (Brazzaville) DHS-VI 2011-12 Respondents 20.3 18.8 18.7 14.4 12.6 8.4 6.9 1983 10,819 

 DHS-VI Sisters 12.8 17.3 19.5 18.0 15.2 10.9 6.4 1983 38,585 

Congo Democratic 

Republic DHS-V 2007 Respondents 20.3 22.7 16.6 13.4 10.4 9.1 7.4 1980 9,995 

 DHS-V Sisters 15.7 19.1 18.9 17.2 13.8 9.1 6.2 1980 35,948 

Côte d’Ivoire DHS-III 1994 Respondents 24.2 19.4 18.0 14.7 9.9 7.7 6.1 1968 8,099 

 DHS-III Sisters 18.7 20.9 20.8 16.5 12.1 7.1 3.9 1970 28,151 

Côte d’Ivoire DHS-V 2005 Respondents 23.8 21.8 17.6 13.2 9.7 7.8 6.1 1979 5,183 

 DHS-V Sisters 17.1 20.8 20.4 16.4 12.7 8.1 4.5 1980 17,761 

Côte d’Ivoire DHS-VI 2011-12 Respondents 20.1 19.4 19.1 15.0 11.2 8.5 6.7 1984 10,060 

 DHS-VI Sisters 14.8 19.5 20.9 17.6 13.4 8.7 5.1 1984 37,727 

Ethiopia DHS-IV 2000 Respondents 24.1 18.6 16.8 12.0 11.2 9.1 8.2 1965 15,367 

 DHS-IV Sisters 17.6 21.2 18.8 15.9 12.5 8.8 5.3 1967 48,750 

Ethiopia DHS-IV 2005 Respondents 23.2 18.1 17.9 12.8 11.4 8.4 8.1 1971 14,070 

 DHS-IV Sisters 17.2 21.0 19.2 16.7 12.5 8.5 5.1 1972 47,449 

Ethiopia DHS-VI 2011 Respondents 24.3 17.7 19.1 12.4 11.6 7.6 7.2 1977 16,515 

 DHS-VI Sisters 16.4 21.1 19.8 17.3 12.3 8.4 4.7 1977 57,742 

Gabon DHS-III 2000-01 Respondents 25.7 20.4 15.8 14.0 10.8 8.0 5.4 1974 6,183 

 DHS-III Sisters 18.3 20.3 20.1 16.8 12.5 8.0 3.9 1976 23,138 

Gabon DHS-VI 2012 Respondents 21.2 19.4 17.6 14.4 11.7 8.9 6.8 1984 8,422 

 DHS-VI Sisters 15.0 18.9 19.8 16.6 13.4 9.8 6.4 1984 31,518 

Guinea DHS-III 1999 Respondents 19.6 16.1 18.5 14.3 14.0 9.2 8.4 1971 6,753 

 DHS-III Sisters 15.2 19.1 19.2 18.1 13.8 9.6 5.1 1973 19,358 

Guinea DHS-IV 2005 Respondents 20.7 14.5 15.8 14.1 14.7 10.3 9.9 1975 7,954 

 DHS-IV Sisters 14.0 18.6 18.7 17.9 14.3 10.4 6.1 1977 23,739 

Guinea DHS-VI 2012 Respondents 22.1 17.9 17.6 12.8 12.3 9.5 7.8 1984 9,142 

 DHS-VI Sisters 15.7 19.7 19.4 17.5 13.1 9.1 5.5 1986 27,699 

Kenya DHS-III 1998 Respondents 23.5 19.6 17.4 12.5 12.6 8.1 6.3 1971 7,881 

 DHS-III Sisters 16.0 19.3 20.0 17.2 13.3 9.0 5.0 1971 34,762 

Kenya DHS-IV 2003 Respondents 22.6 20.6 16.9 13.3 10.6 9.6 6.4 1976 8,195 

 DHS-IV Sisters 15.7 19.6 19.6 17.0 13.4 9.3 5.5 1976 35,510 

Kenya DHS-V 2008-09 Respondents 20.8 20.3 17.2 14.3 10.4 9.1 7.8 1981 8,444 

 DHS-V Sisters 13.5 18.6 19.6 17.9 14.0 10.1 6.3 1981 35,149 

(Continued...)
57 

Table 3.7 – Continued

 Age of female respondents/sisters 

Country 

DHS 

survey 

round 

Year of 

survey 

Respondents/ 

sisters 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

Median

year of 

birth Number

Sub-Saharan 

Africa 

Lesotho DHS-IV 2004-05 Respondents 24.1 20.6 14.7 11.5 10.3 10.4 8.3 1978 7,095 

 DHS-IV Sisters 16.9 19.9 19.7 15.6 12.1 9.8 6.0 1978 20,992 

Lesotho DHS-V 2009-10 Respondents 23.4 20.4 16.3 12.9 10.0 8.6 8.4 1983 7,624 

 DHS-V Sisters 15.4 20.6 21.0 16.9 11.9 8.3 5.9 1983 21,095 

Liberia DHS-V 2006-07 Respondents 18.5 19.2 16.4 13.5 13.5 9.4 9.5 1978 7,092 

 DHS-V Sisters 13.4 17.7 19.0 17.0 14.9 11.1 7.0 1979 21,822 

Madagascar DHS-II 1992 Respondents 22.7 20.2 16.4 14.5 12.0 8.8 5.4 1965 6,260 

 DHS-II Sisters 16.5 19.9 19.5 17.8 13.2 8.5 4.5 1966 25,719 

Madagascar DHS-III 1997 Respondents 22.0 18.8 16.9 14.3 12.0 9.2 6.8 1970 7,060 

DHS-III Sisters 15.5 19.5 19.5 17.3 13.7 9.5 5.0 1971 30,708 

Madagascar DHS-IV 2003-04 Respondents 19.2 17.5 17.0 14.5 11.8 11.7 8.2 1975 7,949 

 DHS-IV Sisters 13.1 17.6 18.6 17.8 14.8 11.3 6.9 1975 31,832 

Madagascar DHS-V 2008-09 Respondents 22.8 16.2 15.9 14.4 12.3 10.0 8.5 1980 17,375 

 DHS-V Sisters 14.3 17.5 18.5 17.4 14.5 10.9 7.0 1981 70,457 

Malawi DHS-II 1992 Respondents 22.3 19.4 16.0 13.6 11.1 10.5 7.1 1965 4,849 

 DHS-II Sisters 16.3 19.7 18.2 17.3 12.9 9.9 5.7 1967 15,808 

Malawi DHS-IV 2000 Respondents 21.7 22.4 18.2 11.8 10.8 8.0 7.2 1974 13,220 

 DHS-IV Sisters 17.5 21.6 19.9 16.2 11.6 8.4 4.7 1976 43,811 

Malawi DHS-IV 2004-05 Respondents 20.4 24.5 18.4 12.6 9.5 8.0 6.4 1978 11,698 

 DHS-IV Sisters 17.7 21.8 21.0 16.1 11.1 7.7 4.6 1979 37,684 

Malawi DHS-V 2010 Respondents 21.7 19.8 19.1 14.1 11.0 7.5 6.8 1983 23,020 

 DHS-V Sisters 16.1 19.9 20.6 18.0 12.6 8.1 4.8 1984 77,384 

Mali DHS-III 1995-96 Respondents 19.4 16.4 17.5 15.7 14.0 9.2 7.8 1967 9,704 

DHS-III Sisters 15.7 20.1 19.5 17.7 13.4 8.9 4.8 1970 31,051 

Mali DHS-IV 2001 Respondents 20.0 18.2 17.2 14.8 12.6 9.7 7.5 1973 12,849 

 DHS-IV Sisters 16.3 19.9 19.2 16.9 13.3 9.1 5.3 1975 42,141 

Mali DHS-V 2006 Respondents 21.3 18.4 18.0 13.5 11.6 9.3 8.0 1979 14,583 

 DHS-V Sisters 16.9 21.0 19.3 17.2 12.1 8.7 4.7 1980 50,147 

Mali DHS-VI 2012-13 Respondents 18.1 17.7 19.9 16.0 12.8 8.8 6.6 1984 10,424 

 DHS-VI Sisters 14.5 20.2 20.7 19.1 12.8 8.5 4.2 1986 31,283 

Mozambique DHS-III 1997 Respondents 20.9 18.9 18.1 13.6 11.7 8.3 8.4 1970 8,779 

DHS-III Sisters 16.4 20.1 20.1 16.8 12.9 8.9 4.7 1971 26,106 

Mozambique DHS-IV 2003-04 Respondents 19.8 19.8 17.9 14.4 11.4 9.1 7.7 1976 12,418 

 DHS-IV Sisters 14.9 19.6 20.5 17.5 13.6 8.9 5.1 1977 40,014 

Mozambique DHS-VI 2011 Respondents 22.3 17.9 16.6 14.5 12.4 8.4 8.0 1984 13,745 

 DHS-VI Sisters 15.5 18.3 20.1 17.5 13.9 9.0 5.7 1984 39,493 

Namibia DHS-II 1992 Respondents 23.2 20.6 16.4 13.3 10.5 9.3 6.6 1966 5,421 

 DHS-II Sisters 17.4 20.7 19.9 16.3 12.3 8.4 5.2 1967 20,714 

Namibia DHS-IV 2000 Respondents 22.2 19.8 16.4 15.0 11.1 9.4 6.2 1973 6,755 

 DHS-IV Sisters 15.1 19.3 19.9 17.0 13.6 9.4 5.7 1973 25,741 

Namibia DHS-V 2006-07 Respondents 22.9 18.9 16.6 14.5 10.7 9.5 7.0 1979 9,804 

 DHS-V Sisters 14.6 18.4 19.9 17.5 13.7 9.8 6.1 1979 34,655 

(Continued...)

 
58 

Table 3.6 – Continued

 Age of female respondents/sisters 

Country 

DHS 

survey 

round 

Year of 

survey 

Respondents/ 

sisters 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

Median

year of 

birth Number

Sub-Saharan 

Africa 

Niger DHS-II 1992 Respondents 21.2 18.3 19.7 15.0 11.5 8.1 6.2 1965 6,503

DHS-II Sisters 16.0 20.7 19.9 17.9 12.5 8.3 4.7 1966 20,893

Niger DHS-V 2006 Respondents 18.6 17.9 19.4 14.7 12.6 9.6 7.1 1979 9,223

DHS-V Sisters 15.3 19.8 18.9 17.5 13.5 9.6 5.4 1980 32,981

Niger DHS-VI 2012 Respondents 16.4 17.8 20.4 16.6 12.9 8.9 7.0 1984 11,160

DHS-VI Sisters 15.4 19.5 19.4 17.5 13.4 9.3 5.5 1985 42,277

Nigeria DHS-III 1999 Respondents 34.4 15.5 15.5 11.6 10.1 7.1 5.8 1974 9,810

DHS-III Sisters 21.1 21.6 19.2 15.2 11.2 7.5 4.2 1975 27,483

Nigeria DHS-V 2008 Respondents 19.4 18.4 18.9 13.9 11.7 9.1 8.6 1981 33,385

DHS-V Sisters 14.8 20.0 20.2 17.8 13.1 8.9 5.2 1982 118,971

Rwanda DHS-IV 2000 Respondents 25.1 18.3 15.3 12.2 11.5 10.2 7.4 1974 10,421

DHS-IV Sisters 17.2 19.6 17.7 16.4 13.3 9.9 5.9 1975 34,042

Rwanda DHS-IV 2005 Respondents 22.8 20.8 15.4 12.9 10.0 10.0 8.0 1978 11,321

DHS-IV Sisters 17.2 21.2 18.7 15.2 12.6 9.1 6.0 1979 38,268

Rwanda DHS-VI 2010-11 Respondents 21.5 19.6 18.2 13.3 10.6 8.5 8.1 1983 13,671

DHS-VI Sisters 14.0 20.4 20.8 17.2 12.3 9.2 6.2 1984 48,299

São Tomé and 

Príncipe DHS-V 2008-09 Respondents 21.2 17.6 17.3 15.2 9.9 10.8 8.1 1980 2,615

DHS-V Sisters 12.9 18.5 19.2 16.9 14.1 11.5 7.0 1980 11,300

Senegal DHS-II 1992-93 Respondents 22.6 19.0 16.5 14.0 12.7 9.3 5.9 1965 6,310

DHS-II Sisters 17.2 19.8 19.5 17.2 13.3 8.4 4.6 1968 20,643

Senegal DHS-IV 2005 Respondents 24.4 19.5 16.3 13.4 11.0 8.6 6.9 1979 14,602

DHS-IV Sisters 16.8 20.5 19.3 16.2 12.6 9.2 5.4 1979 55,257

Senegal DHS-VI 2010-11 Respondents 21.9 20.5 17.5 13.7 11.6 8.8 6.1 1984 15,688

DHS-VI Sisters 14.9 20.3 20.3 18.1 12.6 8.9 4.9 1984 56,885

Sierra Leone DHS-V 2008 Respondents 16.2 16.1 22.3 14.1 15.3 8.8 7.0 1980 7,374

DHS-V Sisters 14.3 18.8 19.6 18.2 14.3 9.2 5.6 1980 18,624

South Africa DHS-III 1998 Respondents 19.2 17.7 15.8 14.1 13.9 11.0 8.3 1969 11,735

DHS-III Sisters 11.6 15.6 18.4 17.7 16.5 12.3 7.8 1968 35,120

Swaziland DHS-V 2006-07 Respondents 25.5 21.0 14.6 12.3 10.1 8.8 7.7 1980 4,987

DHS-V Sisters 17.4 21.1 19.4 15.8 12.4 8.6 5.2 1981 16,832

Tanzania DHS-III 1996 Respondents 21.3 20.6 17.7 13.8 10.9 8.4 7.2 1969 8,120

DHS-III Sisters 16.2 20.3 19.6 17.3 12.8 8.9 4.9 1971 30,682

Tanzania DHS-IV 2004-05 Respondents 21.7 19.4 18.3 14.9 10.2 8.1 7.4 1977 10,329

DHS-IV Sisters 14.6 19.4 19.9 18.1 13.3 9.3 5.4 1978 40,390

Tanzania DHS-V 2009-10 Respondents 21.4 18.8 16.5 14.0 12.7 9.2 7.3 1982 10,139

DHS-V Sisters 14.7 18.1 18.8 17.3 14.5 10.1 6.5 1982 38,125

Togo DHS-III 1998 Respondents 20.9 17.1 18.0 15.7 12.5 8.4 7.4 1970 8,569

DHS-III Sisters 15.6 19.2 19.6 17.3 13.8 9.2 5.3 1971 30,471

Uganda DHS-III 1995 Respondents 22.7 22.0 18.0 13.8 11.1 7.1 5.4 1969 7,070

DHS-III Sisters 17.9 21.9 21.7 17.1 11.3 6.7 3.5 1970 27,005

Uganda DHS-IV 2000-01 Respondents 22.3 20.8 18.5 13.6 11.2 7.9 5.8 1974 7,246

DHS-IV Sisters 16.2 20.3 20.1 17.6 13.1 8.6 4.2 1975 27,699

(Continued...)
59 

Table 3.6 – Continued

 Age of female respondents/sisters 

Country 

DHS 

survey 

round 

Year of 

survey 

Respondents/ 

sisters 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

Median

year of 

birth Number

Sub-Saharan 

Africa 

Uganda DHS-V 2006 Respondents 22.7 20.0 16.6 14.3 11.0 8.6 6.8 1979 8,531

DHS-V Sisters 15.9 20.0 19.7 17.2 13.3 8.8 5.1 1980 32,314

Uganda DHS-VI 2011 Respondents 23.6 18.8 18.1 12.5 11.8 8.4 6.8 1984 8,674

DHS-VI Sisters 16.8 19.6 19.1 16.3 13.1 9.2 5.9 1986 33,055

Zambia DHS-III 1996-97 Respondents 25.0 22.8 16.0 13.5 9.5 7.1 6.2 1970 8,021

DHS-III Sisters 17.5 22.7 20.0 16.4 11.7 7.6 4.1 1972 31,539

Zambia DHS-IV 2001-02 Respondents 23.7 21.7 18.0 12.7 10.0 7.9 6.1 1975 7,658

DHS-IV Sisters 17.0 21.0 21.2 16.8 11.8 7.7 4.5 1976 29,468

Zambia DHS-V 2007 Respondents 22.0 19.2 19.1 14.8 10.5 7.9 6.6 1980 7,146

DHS-V Sisters 15.1 19.8 20.0 18.1 13.4 8.6 5.0 1981 26,640

Zimbabwe DHS-III 1994 Respondents 24.0 20.7 14.9 14.2 10.8 8.7 6.6 1968 6,128

DHS-III Sisters 15.8 19.4 19.0 17.6 13.5 9.3 5.4 1968 25,418

Zimbabwe DHS-IV 1999 Respondents 24.5 21.9 17.5 11.3 10.8 7.9 6.1 1973 5,907

DHS-IV Sisters 17.4 19.5 19.8 16.1 12.8 9.1 5.4 1973 23,456

Zimbabwe DHS-V 2005-06 Respondents 24.2 21.9 16.5 13.6 9.4 7.8 6.6 1979 8,907

DHS-V Sisters 15.0 20.9 20.9 16.6 12.8 8.4 5.5 1979 32,502

Zimbabwe DHS-VI 2010-11 Respondents 21.2 20.1 18.4 14.1 11.5 8.0 6.8 1983 9,171

DHS-VI Sisters 12.6 19.2 21.9 18.6 13.3 9.0 5.4 1983 30,201

North Africa 

Jordan DHS-III 1997 Respondents 24.8 20.2 17.6 13.7 10.2 7.7 5.8 1965 10,165

DHS-III Sisters 17.8 22.3 21.3 16.2 11.7 6.6 4.1 1968 59,579

Morocco DHS-II 1992 Respondents 23.2 18.2 15.9 14.8 12.7 8.0 7.2 1964 9,256

DHS-II Sisters 15.8 20.1 20.1 18.4 13.2 8.2 4.3 1965 39,803

Morocco DHS-IV 2003-04 Respondents 19.6 17.9 15.4 13.4 12.2 11.4 10.0 1975 16,798

DHS-IV Sisters 12.4 17.0 18.1 17.5 15.1 12.3 7.6 1974 75,406

Asia 

Cambodia DHS-IV 2000 Respondents 23.6 12.9 13.8 14.3 14.1 12.0 9.3 1970 15,351

DHS-IV Sisters 16.0 14.9 17.7 18.0 16.0 10.5 6.9 1972 48,266

Cambodia DHS-V 2005-06 Respondents 21.4 18.1 12.2 12.4 13.2 12.6 10.1 1977 16,823

DHS-V Sisters 15.8 20.2 15.9 14.4 14.5 11.6 7.6 1979 56,658

Cambodia DHS-V 2010-11 Respondents 19.9 16.8 17.4 11.6 10.9 12.3 11.2 1982 18,754

DHS-V Sisters 13.6 19.2 20.7 15.0 12.7 10.9 7.9 1982 63,909

Indonesia DHS-III 1994 Respondents 19.8 17.1 16.5 15.6 13.1 9.8 8.1 1961 38,334

DHS-III Sisters 13.5 17.7 19.7 18.0 15.2 10.1 5.7 1963 123,921

Indonesia DHS-III 1997 Respondents 18.9 16.5 16.5 14.7 13.8 10.7 9.0 1964 38,590

DHS-III Sisters 11.7 16.3 19.3 18.5 16.0 11.5 6.7 1966 123,149

Indonesia DHS-IV 2002-03 Respondents 16.6 16.8 15.9 14.7 13.6 11.9 10.6 1969 39,315

DHS-IV Sisters 10.3 15.1 17.6 18.3 17.2 13.2 8.3 1969 123,113

Indonesia DHS-V 2007 Respondents 14.8 15.6 15.9 15.1 14.5 12.8 11.4 1973 42,951

DHS-V Sisters 8.7 13.3 17.5 17.9 18.3 14.3 10.0 1973 132,013

Indonesia DHS-VI 2012 Respondents 15.2 13.8 15.3 15.1 15.1 13.7 11.9 1981 45,607

DHS-VI Sisters 8.2 12.0 15.9 18.5 18.6 15.7 11.1 1979 131,583

(Continued...)
60 

Table 3.6 – Continued

 Age of female respondents/sisters 

Country 

DHS 

survey 

round 

Year of 

survey 

Respondents/ 

sisters 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

Median

year of 

birth Number

Asia 

Nepal DHS-III 1996 Respondents 22.1 18.9 16.5 13.7 11.2 9.2 8.3 1922 10,101

DHS-III Sisters 16.2 20.1 19.3 16.6 13.1 9.1 5.5 1924 30,481

Nepal DHS-V 2006 Respondents 22.6 18.5 16.4 12.4 11.3 10.4 8.4 2035 10,793

DHS-V Sisters 15.5 19.6 18.8 16.7 13.8 9.7 5.9 2035 34,719

Philippines DHS-II 1993 Respondents 21.0 17.6 16.2 14.6 12.6 10.5 7.6 1964 15,029

DHS-II Sisters 12.6 17.9 19.6 17.8 15.3 10.3 6.5 1964 65,525

Philippines DHS-III 1998 Respondents 20.9 16.4 15.8 14.7 13.2 10.6 8.4 1969 13,983

DHS-III Sisters 12.3 16.1 18.8 17.5 16.1 11.8 7.5 1968 58,946

Timor-Leste DHS-VI 2009-10 Respondents 23.9 17.8 14.4 11.7 12.8 10.6 8.7 1982 13,137

DHS-VI Sisters 18.4 20.5 18.4 13.5 12.6 9.8 6.7 1985 39,312

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 Respondents 21.0 17.9 15.6 14.8 12.5 9.8 8.3 1965 8,603

DHS-III Sisters 15.2 19.1 19.4 16.0 14.6 9.3 6.3 1967 27,614

Bolivia DHS-IV 2003-04 Respondents 21.9 17.7 15.1 14.0 12.1 10.7 8.4 1975 17,654

DHS-IV Sisters 14.7 18.8 18.8 15.7 14.5 10.3 7.1 1976 59,858

Bolivia DHS-V 2008 Respondents 20.8 16.2 16.2 13.9 12.7 10.6 9.7 1979 16,939

DHS-V Sisters 14.3 17.7 19.0 16.1 14.9 10.4 7.7 1979 56,611

Brazil DHS-III 1996 Respondents 19.5 15.0 15.4 15.2 13.7 11.7 9.4 1966 12,612

DHS-III Sisters 11.6 16.1 18.1 17.6 16.3 12.0 8.3 1965 51,576

Dominican Republic DHS-IV 2002 Respondents 19.5 17.7 15.5 14.1 13.6 10.3 9.4 1973 23,384

DHS-IV Sisters 10.8 16.1 17.3 17.8 16.5 12.6 8.8 1971 47,295

Dominican Republic DHS-V 2007 Respondents 20.5 16.6 14.6 13.9 13.4 11.6 9.4 1978 27,195

DHS-V Sisters 9.8 14.1 16.3 17.3 17.2 14.6 10.7 1974 100,098

Guatemala DHS-III 1995 Respondents 23.7 18.4 14.4 13.0 12.4 10.0 8.2 1968 12,403

DHS-III Sisters 16.0 19.1 17.6 16.3 14.2 10.4 6.4 1969 45,937

Haiti DHS-IV 2000 Respondents 23.1 18.9 15.9 12.8 11.3 9.5 8.6 1972 10,159

DHS-IV Sisters 15.5 19.2 18.8 16.6 13.7 10.3 5.9 1973 34,669

Haiti DHS-V 2005-06 Respondents 25.1 18.6 16.4 11.6 10.8 8.7 8.7 1979 10,757

DHS-V Sisters 16.5 20.4 18.9 16.0 12.7 9.6 5.9 1979 36,878

Peru DHS-II 1991-92 Respondents 21.9 19.3 16.1 13.3 12.1 9.7 7.5 1964 15,882

DHS-II Sisters 15.3 19.6 19.7 16.5 13.6 9.2 6.1 1965 58,446

Peru DHS-III 1996 Respondents 21.2 18.2 15.8 14.3 12.5 10.3 7.6 1968 28,951

DHS-III Sisters 13.9 18.7 19.0 16.8 14.8 10.1 6.8 1969 111,036

Peru DHS-IV 2000 Respondents 20.3 17.0 15.2 14.6 12.5 11.2 9.1 1971 27,843

DHS-IV Sisters 12.3 17.4 18.6 17.0 15.7 11.4 7.6 1972 105,508

Peru DHS-V 2003-08 Respondents 18.6 15.7 14.8 14.3 13.3 12.4 10.9 1976 40,552

DHS-V Sisters 10.6 15.7 17.3 17.3 16.7 13.1 9.3 1976 147,952

Peru DHS-VI 2011 Respondents 18.3 15.3 14.6 14.2 14.2 12.6 10.8 1980 22,517

DHS-VI Sisters 10.1 14.6 16.8 17.3 17.3 13.8 10.2 1979 79,250
61 

4. Quality of Maternal Mortality Data 

In this section, we present the results pertaining to reporting of events (deaths) and pregnancy status at the 

time of death (during pregnancy, at delivery, or in the postpartum period) that are used for classifying 

women’s deaths as maternal or non-maternal deaths. Any errors in the reporting of these variables 

(misclassification, missing response, misreporting) will directly affect and bias the m aternal mortality 

estimates. 

4.1. Timing of Maternal Deaths 

Table 4.1 shows the percentage of adult female deaths with missing data on timing of death in relation to 

the pregnancy—during pregnancy, at delivery, in the postpartum period —by duration of recall period 

(age 0-6 or 7-13). In most DHS surveys, the postpartum period for maternal mortality estimates refers to 

two months after delivery. 

In many DHS surveys, the extent of missing responses on the pregnancy status at the time of death was 

substantially high (>10%). Because of the possibility of recall bias, it was expected that the percentage of 

missingness would be higher in the more distant period (7-13 years) than in the recent period (0-6 years). 

However, the results show that the problem is similar in both periods (Figure 4.1). In case of higher recall 

problems in the distant period, compared with the recent period, we would expect most points above the 

diagonal line. 

Table 4.1 Percentage of adult female deaths with missing data on timing of maternal deaths, 

Demographic and Health Surveys 1990-2013 

0-6 years before survey 7-13 years before survey 

Country 

DHS 

survey 

round 

Year of 

survey 

Percentage 

missing 

No. of 

deaths 

Percentage 

missing No. of deaths

Sub-Saharan Africa 

Benin DHS-III 1996 5.7 165 5.3 112 

Benin DHS-V 2006 11.1 674 10.7 409 

Burkina Faso DHS-III 1998-99 11.8 280 14.7 145 

Burkina Faso DHS-VI 2010 3.8 732 2.5 516 

Burundi DHS-VI 2010-11 3.1 406 3.9 492 

CAR DHS-III 1994-95 4.8 493 3.3 211 

Cameroon DHS-III 1998 12.6 232 9.3 102 

Cameroon DHS-IV 2004 11.5 795 6.7 300 

Cameroon DHS-VI 2011 4.9 1,151 6.3 706 

Chad DHS-III 1996-97 3.6 344 3.9 175 

Chad DHS-IV 2004 5.1 402 6.8 214 

Congo (Brazzaville) DHS-V 2005 10.4 594 7.4 480 

Congo (Brazzaville) DHS-VI 2011-12 7.2 686 4.9 618 

Congo Democratic Republic DHS-V 2007 7.2 715 6.0 391 

Côte d’Ivoire DHS-III 1994 7.0 400 5.3 192 

Côte d’Ivoire DHS-V 2005 8.9 381 8.9 181 

Côte d’Ivoire DHS-VI 2011-12 17.1 711 10.5 532 

Ethiopia DHS-IV 2000 2.7 1,039 3.4 674 

Ethiopia DHS-IV 2005 8.3 925 6.7 664 

Ethiopia DHS-VI 2011 4.7 732 6.2 816 

(Continued...)
62 

Table 4.1 – Continued

 0-6 years before survey 7-13 years before survey 

Country 

DHS 

survey 

round 

Year of 

survey 

Percentage 

missing 

No. of 

deaths 

Percentage 

missing No. of deaths

Sub-Saharan Africa 

Gabon DHS-III 2000-01 16.8 307 14.4 136 

Gabon DHS-VI 2012 15.3 404 22.8 309 

Guinea DHS-III 1999 21.9 209 13.7 163 

Guinea DHS-IV 2005 8.0 431 5.1 262 

Guinea DHS-VI 2012 7.2 418 5.6 296 

Kenya DHS-III 1998 3.9 529 6.5 161 

Kenya DHS-IV 2003 4.5 759 6.4 262 

Kenya DHS-V 2008-09 9.2 677 7.1 365 

Lesotho DHS-IV 2004-05 9.7 880 7.1 176 

Lesotho DHS-V 2009-10 18.9 1,017 25.4 378 

Liberia DHS-V 2006-07 22.7 359 21.5 152 

Madagascar DHS-III 1997 10.2 414 9.3 254 

Madagascar DHS-IV 2003-04 18.6 351 12.5 211 

Madagascar DHS-V 2008-09 15.0 923 11.9 613 

Malawi DHS-II 1992 17.4 335 11.9 104 

Malawi DHS-IV 2000 7.3 1,597 7.1 501 

Malawi DHS-IV 2004-05 6.9 1,376 7.0 536 

Malawi DHS-V 2010 8.0 2,134 6.2 1,671 

Mali DHS-III 1995-96 6.4 375 2.5 267 

Mali DHS-IV 2001 14.1 625 14.8 349 

Mali DHS-V 2006 22.7 601 19.8 440 

Mali DHS-VI 2012-13 0.0 239 0.7 161 

Mozambique DHS-III 1997 24.4 313 25.2 224 

Mozambique DHS-IV 2003-04 6.5 769 9.4 289 

Mozambique DHS-VI 2011 10.8 715 13.2 469 

Namibia DHS-II 1992 35.5 211 34.3 113 

Namibia DHS-IV 2000 31.3 458 34.2 127 

Namibia DHS-V 2006-07 12.5 1,133 12.9 396 

Niger DHS-II 1992 13.2 306 7.4 231 

Niger DHS-V 2006 12.4 433 12.3 299 

Niger DHS-VI 2012 6.6 503 6.3 351 

Nigeria DHS-III 1999 35.5 177 39.7 74 

Nigeria DHS-V 2008 19.2 1,699 16.0 928 

Rwanda DHS-IV 2000 5.0 2,498 4.7 567 

Rwanda DHS-IV 2005 9.4 950 8.3 2,118 

Rwanda DHS-VI 2010-11 3.3 539 3.0 859 

São Tomé and Príncipe DHS-V 2008-09 41.6 95 28.1 65 

Senegal DHS-II 1992-93 11.1 199 6.8 133 

Senegal DHS-IV 2005 18.1 512 12.7 255 

Senegal DHS-VI 2010-11 0.0 543 0.0 284 

Sierra Leone DHS-V 2008 25.8 358 23.4 186 

South Africa DHS-III 1998 22.5 348 29.2 172 

(Continued...)

 
63 

Table 4.1 – Continued

 0-6 years before survey 7-13 years before survey 

Country 

DHS 

survey 

round 

Year of 

survey 

Percentage 

missing 

No. of 

deaths 

Percentage 

missing No. of deaths

Sub-Saharan Africa 

Swaziland DHS-V 2006-07 10.3 841 14.6 186 

Tanzania DHS-III 1996 7.4 441 7.2 140 

Tanzania DHS-IV 2004-05 5.0 894 2.5 437 

Tanzania DHS-V 2009-10 4.8 646 4.9 457 

Togo DHS-III 1998 15.9 357 9.8 182 

Uganda DHS-III 1995 14.9 753 12.8 219 

Uganda DHS-IV 2000-01 11.7 794 12.1 425 

Uganda DHS-V 2006 7.3 874 5.2 685 

Uganda DHS-VI 2011 1.9 565 2.4 590 

Zambia DHS-III 1996-97 7.6 1,129 6.5 316 

Zambia DHS-IV 2001-02 6.9 1,412 5.2 547 

Zambia DHS-V 2007 7.1 1,153 4.1 638 

Zimbabwe DHS-III 1994 8.7 333 6.6 119 

Zimbabwe DHS-IV 1999 13.4 677 15.3 135 

Zimbabwe DHS-V 2005-06 10.0 1,467 12.2 478 

Zimbabwe DHS-VI 2010-11 5.9 1,174 10.4 636 

North Africa 

Jordan DHS-III 1997 0.0 115 2.3 74 

Morocco DHS-II 1992 25.0 176 34.3 166 

Morocco DHS-IV 2003-04 8.3 266 12.9 193 

Asia 

Cambodia DHS-IV 2000 5.5 546 5.8 351 

Cambodia DHS-V 2005-06 4.0 574 3.1 407 

Cambodia DHS-V 2010-11 1.8 474 1.7 426 

Indonesia DHS-III 1994 9.6 824 11.8 534 

Indonesia DHS-III 1997 5.1 609 6.1 400 

Indonesia DHS-IV 2002-03 10.6 718 16.8 416 

Indonesia DHS-V 2007 14.9 800 15.8 520 

Indonesia DHS-VI 2012 12.9 951 13.6 583 

Nepal DHS-III 1996 1.0 320 5.7 252 

Nepal DHS-V 2006 2.7 217 0.3 178 

Philippines DHS-II 1993 29.1 375 25.4 211 

Philippines DHS-III 1998 19.9 326 21.5 226 

Timor-Leste DHS-VI 2009-10 0.5 288 0.9 233 

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 10.8 231 13.6 157 

Bolivia DHS-IV 2003-04 10.9 386 9.8 291 

Bolivia DHS-V 2008 5.6 320 2.7 250 

Brazil DHS-III 1996 20.5 238 20.1 128 

Dominican Republic DHS-IV 2002 22.6 286 21.1 153 

Dominican Republic DHS-V 2007 10.6 605 6.2 425 

(Continued...)
64 

Table 4.1 – Continued

 0-6 years before survey 7-13 years before survey 

Country 

DHS 

survey 

round 

Year of 

survey 

Percentage 

missing 

No. of 

deaths 

Percentage 

missing No. of deaths

Latin America and 

Caribbean 

Guatemala DHS-III 1995 25.5 233 27.6 164 

Haiti DHS-IV 2000 7.8 686 2.9 498 

Haiti DHS-V 2005-06 6.0 591 5.3 434 

Peru DHS-II 1991-92 17.1 341 13.7 256 

Peru DHS-III 1996 13.9 627 11.6 432 

Peru DHS-IV 2000 19.1 454 16.9 366 

Peru DHS-V 2003-08 3.7 595 3.1 555 

Peru DHS-VI 2011 0.1 257 0.0 257 

Figure 4.1 Percentage of adult female deaths with missing data on pregnancy status during the 

timing of death by recall period, Demographic and Health Surveys 1990-2013 

0 5 10 15 20 25 30 35 40

% Pregnancy status at death missing (7-13 years)

0 5 10 15 20 25 30 35 40

% Pregnancy status at death missing (0-6 years)
65 

Our specific interest was to examine whether the extent of missing responses to the timing of death in 

relationship to pregnancy—during pregnancy, at delivery, or in the postpartum period—declined in the 

subsequent rounds of the DHS surveys. The percentage of missing data on pregnancy status during the 

timing of death for sisters who died during the recent period (0-6 years before the survey) by DHS phases 

is shown in Figure 4.2. The examination of the countries with multiple rounds of DHS surveys suggests 

that the response rate improved substantially in successive rounds in most countries. A trend analysis by 

random-coefficient model shows that the extent of missing responses declined significantly (p <0.05). A 

coefficient value of -1.94 (95% CI: -3.09 t o -0.79) suggests that on an average, adjusted for the 

heterogeneity in the trend slopes at the countr y level, the missing response to maternal status at the time 

of death declined about 2% by each successive DHS survey round (detail results not shown). 

However, in four countries—Benin, Cote d’Ivoire, Kenya, and Lesotho—the missing response to maternal 

status at death substantially increased. 
66 

Figure 4.2 Trends in missing data on pregnancy status during the timing of death for sisters who 

died 0-6 years before the survey, Demographic and Health Surveys 1990-2013 

0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

Benin Bolivia Burkina Faso Cambodia Cameroon Chad

Congo (Brazzaville) Cote d'Ivoire Dominican Republic Ethiopia Gabon Guinea

Haiti Indonesia Kenya Lesotho Madagascar Malawi

Mali Morocco Mozambique Namibia Nepal Niger

Nigeria Peru Philippines Rwanda Senegal Tanzania

Uganda Zambia Zimbabwe

Percent

DHS Survey Round
67 

Clinical studies suggest that there ar e five major causes of maternal mortality: postpartum hemorrhage, 

puerperal sepsis, ecla mpsia, obstructed labor, and abortion. Most maternal deaths occur durin g the 

postpartum period due to hemorrhage and puerperal sepsis. Deaths during the pregnancy period are due 

to abortion and eclampsia. About 5%-8% of women die during delivery from obstructed labor (ruptured 

uterus and he morrhage). The recent Global Burden of Disease Study 2013 (Kassebaum et al. 2014) 

estimated that about a quarter of maternal deaths occur during the antepartum (pregnancy) period (24.6%; 

95% CI: 24.1-25.2); a quarter are intrapartum and immediate postpartum (27.7%, 95% CI: 27.1-28.2); 

one-third are during the subacute and delayed postpartum period (35.6%; 34.9-36.2); and 12.1% (11.9-

12.5) occur during the late postpartum period. 

Table 4.2 and Figure 4.3 show the distribution of timing of death in relation to pregnancy status. Contrary 

to expectation, in many countries maternal deaths occur mostly during the pregnancy (antepartum) period. 

Deaths during delivery were also very high in many countries. The high death rates during pregnancy and 

during delivery may be related to high levels of un safe abortion, HIV am ong pregnant wo men, and 

endemic malaria in some countries. In summary, it is difficult to ascertain or explain the variability in 

timing of death or to assess the quality of pregnancy-related data in DHS surveys in the absence of cause 

of death information. 

Table 4.2 Percent distribution of timing of maternal deaths (during pregnancy, during delivery, 

during the postpartum period), Demographic and Health Surveys 1990-2013 

Timing of maternal death 

Country 

DHS 

survey 

round 

Year of 

survey 

During 

pregnancy 

During 

delivery 

During the 

postpartum 

period 

No. of 

maternal 

deaths 

Sub-Saharan Africa 

Benin DHS-III 1996 33.0 27.3 39.7 162 

Benin DHS-V 2006 31.5 33.1 35.4 359 

Burkina Faso DHS-III 1998-99 34.7 23.4 41.9 115 

Burkina Faso DHS-VI 2010 29.8 29.0 41.2 345 

Burundi DHS-VI 2010-11 48.5 15.6 35.9 348 

CAR DHS-III 1994-95 23.1 54.8 22.1 301 

Cameroon DHS-III 1998 45.0 20.7 34.3 147 

Cameroon DHS-IV 2004 36.6 25.4 38.0 313 

Cameroon DHS-VI 2011 39.7 25.9 34.3 544 

Chad DHS-III 1996-97 47.6 34.9 17.5 320 

Chad DHS-IV 2004 32.8 35.7 31.5 375 

Congo (Brazzaville) DHS-V 2005 45.3 29.0 25.7 236 

Congo (Brazzaville) DHS-VI 2011-12 38.3 44.0 17.7 269 

Congo Democratic Republic DHS-V 2007 50.7 22.4 26.9 324 

Côte d’Ivoire DHS-III 1994 30.4 34.5 35.1 196 

Côte d’Ivoire DHS-V 2005 40.6 14.9 44.5 104 

Côte d’Ivoire DHS-VI 2011-12 28.0 31.5 40.5 287 

Ethiopia DHS-IV 2000 45.6 26.5 27.9 691 

Ethiopia DHS-IV 2005 44.2 30.3 25.6 533 

Ethiopia DHS-VI 2011 39.7 33.7 26.6 709 

Gabon DHS-III 2000-01 57.3 23.8 19.0 123 

Gabon DHS-VI 2012 50.7 22.9 26.4 115 

Guinea DHS-III 1999 42.7 33.9 23.4 203 

Guinea DHS-IV 2005 36.3 34.8 28.9 378 

(Continued...)

 
68 

Table 4.2 – Continued

Timing of maternal death 

Country 

DHS 

survey 

round 

Year of 

survey 

During 

pregnancy 

During 

delivery 

During the 

postpartum 

period 

No. of 

maternal 

deaths 

Sub-Saharan Africa 

Guinea DHS-VI 2012 29.9 37.4 32.7 300 

Kenya DHS-III 1998 46.2 25.5 28.3 240 

Kenya DHS-IV 2003 41.1 28.9 29.9 204 

Kenya DHS-V 2008-09 32.6 37.4 30.0 205 

Lesotho DHS-IV 2004-05 30.9 18.3 50.8 131 

Lesotho DHS-V 2009-10 28.2 13.5 58.3 191 

Liberia DHS-V 2006-07 48.0 36.0 16.0 227 

Madagascar DHS-III 1997 44.1 23.4 32.6 242 

Madagascar DHS-IV 2003-04 38.2 29.0 32.9 224 

Madagascar DHS-V 2008-09 39.3 30.4 30.4 473 

Malawi DHS-II 1992 46.1 21.8 32.1 145 

Malawi DHS-IV 2000 25.8 46.2 28.0 581 

Malawi DHS-IV 2004-05 34.6 35.1 30.3 400 

Malawi DHS-V 2010 28.5 43.1 28.4 785 

Mali DHS-III 1995-96 45.4 26.4 28.3 308 

Mali DHS-IV 2001 30.6 32.6 36.8 390 

Mali DHS-V 2006 37.7 31.5 30.8 411 

Mali DHS-VI 2012-13 31.0 39.1 29.9 132 

Mozambique DHS-III 1997 57.0 13.7 29.3 177 

Mozambique DHS-IV 2003-04 51.5 18.0 30.5 273 

Mozambique DHS-VI 2011 61.5 13.6 24.9 198 

Namibia DHS-II 1992 65.9 15.3 18.8 67 

Namibia DHS-IV 2000 49.4 21.3 29.3 79 

Namibia DHS-V 2006-07 34.0 14.4 51.6 135 

Niger DHS-II 1992 30.4 44.1 25.4 306 

Niger DHS-V 2006 35.5 29.3 35.2 386 

Niger DHS-VI 2012 38.5 22.7 38.8 448 

Nigeria DHS-III 1999 53.8 25.0 21.2 80 

Nigeria DHS-V 2008 53.6 27.7 18.7 846 

Rwanda DHS-IV 2000 37.6 32.8 29.6 538 

Rwanda DHS-IV 2005 34.8 32.2 33.0 582 

Rwanda DHS-VI 2010-11 33.2 29.3 37.5 580 

São Tomé and Príncipe DHS-V 2008-09 57.1 26.6 16.3 25 

Senegal DHS-II 1992-93 48.1 30.8 21.2 156 

Senegal DHS-IV 2005 36.3 31.6 32.0 339 

Senegal DHS-VI 2010-11 35.0 32.3 32.8 326 

Sierra Leone DHS-V 2008 38.9 41.1 20.0 204 

South Africa DHS-III 1998 47.3 10.2 42.5 45 

Swaziland DHS-V 2006-07 44.8 17.9 37.3 75 

Tanzania DHS-III 1996 43.5 29.6 26.9 216 

Tanzania DHS-IV 2004-05 32.7 30.4 36.9 377 

Tanzania DHS-V 2009-10 32.7 28.4 38.9 273 

Togo DHS-III 1998 42.8 24.3 32.9 178 

(Continued...)
69 

Table 4.2 – Continued

Timing of maternal death 

Country 

DHS 

survey 

round 

Year of 

survey 

During 

pregnancy 

During 

delivery 

During the 

postpartum 

period 

No. of 

maternal 

deaths 

Sub-Saharan Africa 

Uganda DHS-III 1995 49.0 28.8 22.3 221 

Uganda DHS-IV 2000-01 39.9 28.1 32.0 251 

Uganda DHS-V 2006 30.4 33.0 36.6 320 

Uganda DHS-VI 2011 31.0 36.0 33.1 367 

Zambia DHS-III 1996-97 46.1 15.7 38.2 249 

Zambia DHS-IV 2001-02 43.2 18.3 38.5 251 

Zambia DHS-V 2007 36.4 20.6 43.0 223 

Zimbabwe DHS-III 1994 30.1 42.4 27.5 108 

Zimbabwe DHS-IV 1999 46.6 21.2 32.2 115 

Zimbabwe DHS-V 2005-06 43.9 13.8 42.3 169 

Zimbabwe DHS-VI 2010-11 40.3 21.7 38.0 222 

North Africa 

Jordan DHS-III 1997 46.3 21.0 32.6 48 

Morocco DHS-II 1992 37.4 23.4 39.2 171 

Morocco DHS-IV 2003-04 28.9 24.3 46.8 222 

Asia 

Cambodia DHS-IV 2000 37.6 29.6 32.7 295 

Cambodia DHS-V 2005-06 31.6 32.4 36.0 323 

Cambodia DHS-V 2010-11 45.3 20.3 34.4 214 

Indonesia DHS-III 1994 0.0 88.3 11.7 432 

Indonesia DHS-III 1997 9.9 82.9 7.2 297 

Indonesia DHS-IV 2002-03 0.0 81.6 18.4 287 

Indonesia DHS-V 2007 0.0 82.3 17.7 318 

Indonesia DHS-VI 2012 33.7 40.7 25.6 334 

Nepal DHS-III 1996 36.7 15.1 48.2 298 

Nepal DHS-V 2006 39.5 21.5 39.0 181 

Philippines DHS-II 1993 52.2 26.0 21.7 141 

Philippines DHS-III 1998 41.2 33.7 25.1 147 

Timor-Leste DHS-VI 2009-10 23.7 54.0 22.3 326 

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 58.0 23.2 18.8 138 

Bolivia DHS-IV 2003-04 67.2 15.1 17.7 229 

Bolivia DHS-V 2008 40.5 41.2 18.3 227 

Brazil DHS-III 1996 45.3 31.0 23.8 106 

Dominican Republic DHS-IV 2002 51.1 24.0 24.8 109 

Dominican Republic DHS-V 2007 57.4 14.6 28.0 176 

Guatemala DHS-III 1995 55.3 26.8 17.9 129 

Haiti DHS-IV 2000 28.1 22.5 49.4 289 

Haiti DHS-V 2005-06 23.9 35.0 41.1 257 

Peru DHS-II 1991-92 35.8 64.2 0.0 132 

Peru DHS-III 1996 60.0 23.4 16.6 367 

Peru DHS-IV 2000 51.1 36.1 12.8 274 

(Continued...)
70 

Table 4.2 – Continued

Timing of maternal death 

Country 

DHS 

survey 

round 

Year of 

survey 

During 

pregnancy 

During 

delivery 

During the 

postpartum 

period 

No. of 

maternal 

deaths 

Latin America and 

Caribbean 

Peru DHS-V 2003-08 49.6 34.8 15.6 452 

Peru DHS-VI 2011 55.0 26.2 18.9 197 

Figure 4.4 shows the per cent distribution of timing of death in each count ry by surve y rounds. In 

Indonesia, deaths during pregnancy and delivery were combined in the early rounds. With few exceptions 

(Kenya, Zimbabwe), the distribution patterns are similar for most countries. 

When the percent distribution patterns were co mpared by duration of recall peri ods—recent (0-6 years) 

and distant (7-13 years)—we did not detect any systematic shifts in the distribution patterns (Table 4.3 

and Figure 4.5). 

 
71 

Figure 4.3 Distribution of timing of maternal deaths (during pregnancy, during delivery, during 

the postpartum period), Demographic and Health Surveys 1990-2013 

(Continued...)

 

0 25 50 75 100

Percent

Rwanda 2005

Burkina Faso 1998-99

Malawi 2004-05

Namibia 2006-07

Indonesia 2012

Rwanda 2010-11

Benin 1996

Chad 2004

Tanzania 2009-10

Tanzania 2004-05

Kenya 2008-09

Cambodia 2005-06

Benin 2006

Mali 2012-13

Uganda 2011

Lesotho 2004-05

Mali 2001

Niger 1992

Uganda 2006

Cote d'Ivoire 1994

Zimbabwe 1994

Guinea 2012

Burkina Faso 2010

Morocco 2003-04

Malawi 2010

Lesotho 2009-10

Haiti 2000

Cote d'Ivoire 2011-12

Malawi 2000

Haiti 2005-06

Timor-Leste 2009-10

Central African Republic 1994

Indonesia 1997

Indonesia 2007

Indonesia 2002-03

Indonesia 1994

Pregnancy Delivery Postpartum
72 

Figure 4.3 – Continued

(Continued...)

 

0 25 50 75 100

Percent

Cameroon 1998

Swaziland 2006-07

Ethiopia 2005

Madagascar 1997

Zimbabwe 2005-06

Tanzania 1996

Zambia 2001-02

Togo 1998

Guinea 1999

Philippines 1998

Kenya 2003

Cote d'Ivoire 2005

Bolivia 2008

Zimbabwe 2010-11

Uganda 2000-01

Cameroon 2011

Ethiopia 2011

Nepal 2006

Madagascar 2008-09

Sierra Leone 2008

Niger 2012

Congo (Brazzaville) 2011-12

Madagascar 2003-04

Mali 2006

Cambodia 2000

Rwanda 2000

Morocco 1992

Nepal 1996

Cameroon 2004

Zambia 2007

Senegal 2005

Guinea 2005

Peru 1991-92

Niger 2006

Senegal 2010-11

Pregnancy Delivery Postpartum
73 

Figure 4.3 – Continued

0 25 50 75 100

Percent

Bolivia 2003-04

Namibia 1992

Mozambique 2011

Peru 1996

Bolivia 1993-94

Dominican Republic 2007

Gabon 2000-01

Sao Tome and Principe 2008-09

Mozambique 1997

Guatemala 1995

Peru 2011

Nigeria 1999

Nigeria 2008

Philippines 1993

Mozambique 2003-04

Dominican Republic 2002

Peru 2000

Gabon 2012

Congo Democratic Republic 2007

Peru 2003-08

Namibia 2000

Uganda 1995

Burundi 2010-11

Senegal 1992-93

Liberia 2006-07

Chad 1996-97

South Africa 1998

Zimbabwe 1999

Jordan 1997

Kenya 1998

Zambia 1996-97

Malawi 1992

Ethiopia 2000

Mali 1995-96

Cambodia 2010-11

Brazil 1996

Pregnancy Delivery Postpartum
74 

Figure 4.4 Distribution of the timing of maternal deaths by DHS survey rounds, Demographic and 

Health Surveys 1990-2013 

(Continued...) 

 

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

Benin Bolivia Burkina Faso Cambodia

Cameroon Chad Congo (Brazzaville) Cote d'Ivoire

Dominican Republic Ethiopia Gabon Guinea

Haiti Indonesia Kenya Lesotho

Madagascar Malawi Mali Morocco

Mozambique Namibia Nepal Niger

Pregnancy Delivery Postpartum

Maternal deaths during

Percent
75 

Figure 4.4 – Continued

 

0 25 50 75 100 0 25 50 75 100 0 25 50 75 100

0 25 50 75 100

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

DHS-VI

DHS-V

DHS-IV

DHS-III

DHS-II

Mozambique Namibia Nepal Niger

Nigeria Peru Philippines Rwanda

Senegal Tanzania Uganda Zambia

Zimbabwe

Pregnancy Delivery Postpartum

Maternal deaths during

Percent
76 

Table 4.3 Percent distribution of timing of maternal deaths (during pregnancy, during delivery, 

during the postpartum period) according to two recall periods before survey (recent: 0-6 years; 

distant: 7-13 years), Demographic and Health Surveys 1990-2013 

 Timing of maternal deaths 

Country 

DHS 

survey 

round 

Year of 

survey 

Years before 

survey 

During 

pregnancy

During 

delivery 

During the 

postpartum 

period 

No. of 

maternal 

deaths 

Sub-Saharan Africa 

Benin DHS-III 1996 0-6 years 27.9 27.0 45.1 59 

 DHS-III 7-13 years 32.6 22.4 45.0 33 

Benin DHS-V 2006 0-6 years 31.1 36.8 32.1 160 

 DHS-V 7-13 years 32.6 30.9 36.6 108 

Burkina Faso DHS-III 1998-99 0-6 years 28.7 24.9 46.4 62 

 DHS-III 7-13 years 38.6 13.3 48.2 22 

Burkina Faso DHS-VI 2010 0-6 years 26.2 26.7 47.1 137 

 DHS-VI 7-13 years 32.6 21.4 46.0 88 

Burundi DHS-VI 2010-11 0-6 years 40.1 21.6 38.3 102 

 DHS-VI 7-13 years 50.5 12.7 36.8 121 

CAR DHS-III 1994-95 0-6 years 21.1 53.8 25.1 160 

 DHS-III 7-13 years 21.9 55.2 23.0 69 

Cameroon DHS-III 1998 0-6 years 47.8 16.8 35.4 61 

 DHS-III 7-13 years 36.2 34.5 29.3 28 

Cameroon DHS-IV 2004 0-6 years 34.7 24.1 41.3 154 

 DHS-IV 7-13 years 44.5 17.3 38.2 80 

Cameroon DHS-VI 2011 0-6 years 39.7 22.8 37.5 252 

 DHS-VI 7-13 years 34.3 29.4 36.3 129 

Chad DHS-III 1996-97 0-6 years 45.1 34.5 20.4 140 

 DHS-III 7-13 years 43.9 41.6 14.5 78 

Chad DHS-IV 2004 0-6 years 28.4 42.7 28.8 176 

 DHS-IV 7-13 years 41.3 25.4 33.3 84 

Congo (Brazzaville) DHS-V 2005 0-6 years 45.1 31.0 23.9 114 

 DHS-V 7-13 years 51.3 22.8 25.9 64 

Congo (Brazzaville) DHS-VI 2011-12 0-6 years 39.6 47.1 13.3 96 

 DHS-VI 7-13 years 41.6 34.7 23.7 77 

Congo Democratic 

Republic 

DHS-V 2007 0-6 years 47.6 24.4 28.0 129 

 DHS-V 7-13 years 40.7 26.1 33.2 90 

Côte d’Ivoire DHS-III 1994 0-6 years 30.2 30.1 39.8 101 

 DHS-III 7-13 years 35.0 31.5 33.5 46 

Côte d’Ivoire DHS-V 2005 0-6 years 42.8 13.0 44.2 49 

 DHS-V 7-13 years 35.6 19.4 45.0 39 

Côte d’Ivoire DHS-VI 2011-12 0-6 years 28.8 34.3 37.0 125 

 DHS-VI 7-13 years 28.7 21.5 49.8 98 

Ethiopia DHS-IV 2000 0-6 years 45.6 25.6 28.8 267 

 DHS-IV 7-13 years 40.0 31.4 28.5 179 

Ethiopia DHS-IV 2005 0-6 years 39.5 32.3 28.2 199 

 DHS-IV 7-13 years 46.0 30.4 23.7 158 

Ethiopia DHS-VI 2011 0-6 years 44.6 31.9 23.5 220 

 DHS-VI 7-13 years 34.2 31.1 34.8 210 

(Continued...)

 
77 

Table 4.3 – Continued

 Timing of maternal deaths 

Country 

DHS 

survey 

round 

Year of 

survey 

Years before 

survey 

During 

pregnancy

During 

delivery 

During the 

postpartum 

period 

No. of 

maternal 

deaths 

Sub-Saharan Africa 

Gabon DHS-III 2000-01 0-6 years 48.6 30.1 21.3 60 

 DHS-III 7-13 years 59.8 12.4 27.8 31 

Gabon DHS-VI 2012 0-6 years 42.1 21.5 36.4 43 

 DHS-VI 7-13 years 65.0 15.6 19.4 33 

Guinea DHS-III 1999 0-6 years 29.6 37.6 32.8 62 

 DHS-III 7-13 years 44.3 38.3 17.4 61 

Guinea DHS-IV 2005 0-6 years 38.0 32.3 29.7 161 

 DHS-IV 7-13 years 27.9 42.4 29.7 106 

Guinea DHS-VI 2012 0-6 years 30.2 35.5 34.3 116 

 DHS-VI 7-13 years 28.5 39.4 32.1 89 

Kenya DHS-III 1998 0-6 years 48.0 23.4 28.6 144 

 DHS-III 7-13 years 48.4 22.6 29.0 40 

Kenya DHS-IV 2003 0-6 years 39.8 31.0 29.2 106 

 DHS-IV 7-13 years 50.2 16.1 33.7 46 

Kenya DHS-V 2008-09 0-6 years 29.4 37.2 33.4 99 

 DHS-V 7-13 years 36.3 31.1 32.6 60 

Lesotho DHS-IV 2004-05 0-6 years 31.8 17.0 51.3 83 

 DHS-IV 7-13 years 31.5 29.3 39.2 21 

Lesotho DHS-V 2009-10 0-6 years 27.4 10.5 62.1 111 

 DHS-V 7-13 years 29.7 6.1 64.1 47 

Liberia DHS-V 2006-07 0-6 years 52.6 38.0 9.5 128 

 DHS-V 7-13 years 40.3 37.8 21.9 56 

Madagascar DHS-III 1997 0-6 years 48.4 18.7 32.9 99 

 DHS-III 7-13 years 40.9 26.5 32.6 80 

Madagascar DHS-IV 2003-04 0-6 years 28.2 31.1 40.7 95 

 DHS-IV 7-13 years 54.2 18.7 27.1 64 

Madagascar DHS-V 2008-09 0-6 years 40.5 29.9 29.6 191 

 DHS-V 7-13 years 38.0 32.5 29.5 127 

Malawi DHS-II 1992 0-6 years 40.7 31.3 28.1 71 

 DHS-II 7-13 years 46.1 12.0 41.9 37 

Malawi DHS-IV 2000 0-6 years 22.7 46.4 30.9 348 

 DHS-IV 7-13 years 29.1 55.0 15.9 98 

Malawi DHS-IV 2004-05 0-6 years 33.1 36.2 30.7 243 

 DHS-IV 7-13 years 22.0 42.3 35.7 91 

Malawi DHS-V 2010 0-6 years 25.5 47.6 27.0 345 

 DHS-V 7-13 years 28.2 41.4 30.4 261 

Mali DHS-III 1995-96 0-6 years 46.9 24.7 28.4 125 

 DHS-III 7-13 years 44.5 26.1 29.4 91 

Mali DHS-IV 2001 0-6 years 31.1 33.6 35.3 179 

 DHS-IV 7-13 years 28.9 22.8 48.3 94 

Mali DHS-V 2006 0-6 years 40.1 23.8 36.1 170 

 DHS-V 7-13 years 35.3 35.7 29.0 127 

(Continued...)

 
78 

Table 4.3 – Continued

 Timing of maternal deaths 

Country 

DHS 

survey 

round 

Year of 

survey 

Years before 

survey 

During 

pregnancy

During 

delivery 

During the 

postpartum 

period 

No. of 

maternal 

deaths 

Sub-Saharan Africa 

Mali DHS-VI 2012-13 0-6 years 32.5 34.4 33.1 76 

 DHS-VI 7-13 years 28.0 50.9 21.0 38 

Mozambique DHS-III 1997 0-6 years 56.9 28.4 14.7 50

 DHS-III 7-13 years 43.6 3.3 53.1 77 

Mozambique DHS-IV 2003-04 0-6 years 52.6 18.6 28.8 121

 DHS-IV 7-13 years 61.4 13.9 24.7 60 

Mozambique DHS-VI 2011 0-6 years 60.0 11.6 28.4 106

 DHS-VI 7-13 years 55.4 15.6 29.0 47 

Namibia DHS-II 1992 0-6 years 78.8 11.2 10.0 31

 DHS-II 7-13 years 45.0 31.5 23.5 12 

Namibia DHS-IV 2000 0-6 years 63.0 11.2 25.8 43

 DHS-IV 7-13 years 36.9 28.8 34.3 26 

Namibia DHS-V 2006-07 0-6 years 33.9 10.7 55.4 71

 DHS-V 7-13 years 23.8 25.9 50.3 33 

Niger DHS-II 1992 0-6 years 26.6 45.3 28.0 103

 DHS-II 7-13 years 30.1 47.5 22.4 106 

Niger DHS-V 2006 0-6 years 34.6 28.5 36.9 180

 DHS-V 7-13 years 34.7 26.6 38.7 111 

Niger DHS-VI 2012 0-6 years 44.8 18.4 36.8 194

 DHS-VI 7-13 years 30.3 29.7 40.0 113 

Nigeria DHS-III 1999 0-6 years 65.8 23.8 10.4 42

 DHS-III 7-13 years 32.5 31.6 35.9 16 

Nigeria DHS-V 2008 0-6 years 51.0 28.8 20.2 403

 DHS-V 7-13 years 53.1 24.0 22.9 238 

Rwanda DHS-IV 2000 0-6 years 40.7 29.3 30.0 351

 DHS-IV 7-13 years 32.4 37.4 30.2 127 

Rwanda DHS-IV 2005 0-6 years 24.0 36.7 39.3 179

 DHS-IV 7-13 years 42.2 26.5 31.3 293 

Rwanda DHS-VI 2010-11 0-6 years 24.7 27.4 47.9 129

 DHS-VI 7-13 years 30.5 34.9 34.6 160 

São Tomé and Príncipe DHS-V 2008-09 0-6 years 64.1 0.0 35.9 7

 DHS-V 7-13 years 71.5 14.7 13.8 11 

Senegal DHS-II 1992-93 0-6 years 45.3 31.3 23.4 64

 DHS-II 7-13 years 48.9 35.6 15.6 45 

Senegal DHS-IV 2005 0-6 years 39.3 33.9 26.8 121

 DHS-IV 7-13 years 37.6 28.5 33.9 81 

Senegal DHS-VI 2010-11 0-6 years 29.4 34.9 35.8 149

 DHS-VI 7-13 years 35.7 30.2 34.1 71 

Sierra Leone DHS-V 2008 0-6 years 34.6 42.5 22.9 99

 DHS-V 7-13 years 42.5 38.7 18.8 55 

South Africa DHS-III 1998 0-6 years 48.1 4.1 47.8 19

 DHS-III 7-13 years 39.0 16.2 44.8 16 

(Continued...)

 
79 

Table 4.3 – Continued

 Timing of maternal deaths 

Country 

DHS 

survey 

round 

Year of 

survey 

Years before 

survey 

During 

pregnancy

During 

delivery 

During the 

postpartum 

period 

No. of 

maternal 

deaths 

Sub-Saharan Africa 

Swaziland DHS-V 2006-07 0-6 years 40.5 18.6 40.9 48

 DHS-V 7-13 years 57.4 27.7 14.9 13 

Tanzania DHS-III 1996 0-6 years 41.5 28.0 30.5 122

 DHS-III 7-13 years 44.1 28.0 27.9 37 

Tanzania DHS-IV 2004-05 0-6 years 33.8 25.7 40.6 156 

 DHS-IV 7-13 years 31.9 27.9 40.2 104 

Tanzania DHS-V 2009-10 0-6 years 33.3 25.5 41.1 115 

 DHS-V 7-13 years 31.0 24.5 44.4 87 

Togo DHS-III 1998 0-6 years 39.1 19.6 41.3 70 

 DHS-III 7-13 years 45.9 28.0 26.1 48 

Uganda DHS-III 1995 0-6 years 53.0 28.0 19.0 112 

 DHS-III 7-13 years 32.4 30.7 36.9 66 

Uganda DHS-IV 2000-01 0-6 years 34.6 29.6 35.8 120 

 DHS-IV 7-13 years 39.1 25.2 35.7 66 

Uganda DHS-V 2006 0-6 years 32.9 32.6 34.5 105 

 DHS-V 7-13 years 31.2 23.5 45.3 107 

Uganda DHS-VI 2011 0-6 years 31.7 29.9 38.5 109 

 DHS-VI 7-13 years 29.1 31.1 39.8 88 

Zambia DHS-III 1996-97 0-6 years 45.7 13.6 40.6 149 

 DHS-III 7-13 years 55.0 16.6 28.4 53 

Zambia DHS-IV 2001-02 0-6 years 43.6 16.2 40.2 148 

 DHS-IV 7-13 years 35.5 22.6 41.9 62 

Zambia DHS-V 2007 0-6 years 29.7 22.2 48.1 106 

 DHS-V 7-13 years 38.8 15.1 46.1 68 

Zimbabwe DHS-III 1994 0-6 years 34.2 43.8 22.0 50 

 DHS-III 7-13 years 25.1 27.7 47.2 16 

Zimbabwe DHS-IV 1999 0-6 years 49.3 16.8 33.8 78 

 DHS-IV 7-13 years 28.6 30.3 41.1 16 

Zimbabwe DHS-V 2005-06 0-6 years 46.4 13.5 40.1 101 

 DHS-V 7-13 years 38.4 22.0 39.7 44 

Zimbabwe DHS-VI 2010-11 0-6 years 38.8 21.7 39.4 139 

 DHS-VI 7-13 years 37.9 18.6 43.4 48 

North Africa 

Jordan DHS-III 1997 0-6 years 32.1 36.6 31.3 9 

 DHS-III 7-13 years 43.2 25.9 30.8 11 

Morocco DHS-II 1992 0-6 years 36.8 24.6 38.6 57 

 DHS-II 7-13 years 27.4 25.8 46.8 62 

Morocco DHS-IV 2003-04 0-6 years 28.0 17.2 54.8 59 

 DHS-IV 7-13 years 39.7 20.2 40.1 48 

Asia 

Cambodia DHS-IV 2000 0-6 years 38.7 32.1 29.2 101 

 DHS-IV 7-13 years 34.4 29.9 35.7 68 

(Continued...)

 
80 

Table 4.3 – Continued

 Timing of maternal deaths 

Country 

DHS 

survey 

round 

Year of 

survey 

Years before 

survey 

During 

pregnancy

During 

delivery 

During the 

postpartum 

period 

No. of 

maternal 

deaths 

Asia 

Cambodia DHS-V 2005-06 0-6 years 26.6 30.6 42.8 99 

 DHS-V 7-13 years 32.1 28.1 39.7 68 

Cambodia DHS-V 2010-11 0-6 years 30.1 20.7 49.3 45 

 DHS-V 7-13 years 38.3 25.7 36.1 61 

Indonesia DHS-III 1994 0-6 years 0.0 87.2 12.8 164 

 DHS-III 7-13 years 0.0 88.3 11.7 117 

Indonesia DHS-III 1997 0-6 years 8.3 89.7 2.1 109 

 DHS-III 7-13 years 6.7 80.5 12.7 87 

Indonesia DHS-IV 2002-03 0-6 years 0.0 82.6 17.4 106 

 DHS-IV 7-13 years 0.0 73.4 26.6 76 

Indonesia DHS-V 2007 0-6 years 0.0 86.7 13.3 79 

 DHS-V 7-13 years 0.0 79.2 20.8 101 

Indonesia DHS-VI 2012 0-6 years 39.9 35.4 24.7 113 

 DHS-VI 7-13 years 31.4 37.9 30.7 64 

Nepal DHS-III 1996 0-6 years 44.8 13.8 41.4 87 

 DHS-III 7-13 years 28.3 7.4 64.3 81 

Nepal DHS-V 2006 0-6 years 33.5 23.9 42.6 39 

 DHS-V 7-13 years 38.3 29.6 32.1 39 

Philippines DHS-II 1993 0-6 years 49.7 18.1 32.2 52 

 DHS-II 7-13 years 47.5 35.4 17.1 46 

Philippines DHS-III 1998 0-6 years 35.9 23.8 40.3 44 

 DHS-III 7-13 years 43.9 36.7 19.4 51 

Timor-Leste DHS-VI 2009-10 0-6 years 22.6 55.7 21.7 122 

 DHS-VI 7-13 years 21.5 46.7 31.8 98 

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 0-6 years 70.4 14.1 15.5 50 

 DHS-III 7-13 years 44.4 25.1 30.5 34 

Bolivia DHS-IV 2003-04 0-6 years 65.8 24.4 9.8 56 

 DHS-IV 7-13 years 81.8 7.5 10.8 63 

Bolivia DHS-V 2008 0-6 years 38.7 38.7 22.6 60 

 DHS-V 7-13 years 40.2 37.2 22.6 61 

Brazil DHS-III 1996 0-6 years 45.3 24.1 30.6 29 

 DHS-III 7-13 years 35.2 25.0 39.8 20 

Dominican Republic DHS-IV 2002 0-6 years 40.3 33.3 26.4 30 

 DHS-IV 7-13 years 51.5 11.6 37.0 30 

Dominican Republic DHS-V 2007 0-6 years 51.1 1.9 47.0 61 

 DHS-V 7-13 years 67.0 9.6 23.3 38 

Guatemala DHS-III 1995 0-6 years 59.8 29.1 11.1 40 

 DHS-III 7-13 years 65.9 13.0 21.1 32 

Haiti DHS-IV 2000 0-6 years 27.4 22.4 50.2 96 

 DHS-IV 7-13 years 34.4 10.6 55.0 97 

(Continued...)

 
81 

Table 4.3 – Continued

 Timing of maternal deaths 

Country 

DHS 

survey 

round 

Year of 

survey 

Years before 

survey 

During 

pregnancy

During 

delivery 

During the 

postpartum 

period 

No. of 

maternal 

deaths 

Latin America and 

Caribbean 

Haiti DHS-V 2005-06 0-6 years 23.1 30.7 46.2 104 

 DHS-V 7-13 years 28.4 37.7 33.9 72 

Peru DHS-II 1991-92 0-6 years 48.0 52.0 0.0 40 

 DHS-II 7-13 years 33.5 66.5 0.0 37 

Peru DHS-III 1996 0-6 years 65.6 17.9 16.6 113 

 DHS-III 7-13 years 55.5 27.2 17.3 89 

Peru DHS-IV 2000 0-6 years 50.9 27.1 22.0 63 

 DHS-IV 7-13 years 53.8 43.2 3.0 67 

Peru DHS-V 2003-08 0-6 years 53.6 29.4 17.0 85 

 DHS-V 7-13 years 47.5 39.8 12.7 101 

Peru DHS-VI 2011 0-6 years 56.0 34.0 10.0 36 

 DHS-VI 7-13 years 59.7 16.4 23.9 47 

 
82 

Figure 4.5 Distribution of timing of maternal deaths (during pregnancy, during delivery, during 

the postpartum period) by recall periods: recent (0-6 years) and distant (7-13 years), Demographic 

and Health Surveys 1990-2013 

(Continued...)

0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

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7 to 13 yrs

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7 to 13 yrs

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7 to 13 yrs

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7 to 13 yrs

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7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

Benin, 1996 Benin, 2006 Bolivia, 1993-94 Bolivia, 2003-04

Bolivia, 2008 Brazil, 1996 Burkina Faso, 1998-99 Burkina Faso, 2010

Burundi, 2010-11 Cambodia, 2000 Cambodia, 2005-06 Cambodia, 2010-11

Cameroon, 1998 Cameroon, 2004 Cameroon, 2011 Central African Republic, 1994-95

Chad, 1996-97 Chad, 2004 Congo (Brazzaville), 2005 Congo (Brazzaville), 2011-12

Congo Democratic Republic, 2007 Cote d'Ivoire, 1994 Cote d'Ivoire, 2005 Cote d'Ivoire, 2011-12

Dominican Republic, 2002 Dominican Republic, 2007 Ethiopia, 2000 Ethiopia, 2005

Ethiopia, 2011 Gabon, 2000-01 Gabon, 2012 Guatemala, 1995

Guinea, 1999 Guinea, 2005 Guinea, 2012 Haiti, 2000

During

Pregnancy

During

Delivery

During

Postpartum Period

Timing of Death
83 

Figure 4.5 – Continued

(Continued...)

0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

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7 to 13 yrs

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7 to 13 yrs

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7 to 13 yrs

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7 to 13 yrs

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0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

Haiti, 2005-06 Indonesia, 1994 Indonesia, 1997 Indonesia, 2002-03

Indonesia, 2007 Indonesia, 2012 Jordan, 1997 Kenya, 1998

Kenya, 2003 Kenya, 2008-09 Lesotho, 2004-05 Lesotho, 2009-10

Liberia, 2006-07 Madagascar, 1997 Madagascar, 2003-04 Madagascar, 2008-09

Malawi, 1992 Malawi, 2000 Malawi, 2004-05 Malawi, 2010

Mali, 1995-96 Mali, 2001 Mali, 2006 Mali, 2012-13

Morocco, 1992 Morocco, 2003-04 Mozambique, 1997 Mozambique, 2003-04

Mozambique, 2011 Namibia, 1992 Namibia, 2000 Namibia, 2006-07

Nepal, 1996 Nepal, 2006 Niger, 1992 Niger, 2006

During

Pregnancy

During

Delivery

During

Postpartum Period

Timing of Death
84 

Figure 4.5 – Continued

0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

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7 to 13 yrs

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7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

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7 to 13 yrs

0 to 6 yrs

7 to 13 yrs

0 to 6 yrs

Niger, 2012 Nigeria, 1999 Nigeria, 2008 Peru, 1991-92

Peru, 1996 Peru, 2000 Peru, 2003-08 Peru, 2011

Philippines, 1993 Philippines, 1998 Rwanda, 2000 Rwanda, 2005

Rwanda, 2010-11 Sao Tome and Principe, 2008-09 Senegal, 1992-93 Senegal, 2005

Senegal, 2010-11 Sierra Leone, 2008 South Africa, 1998 Swaziland, 2006-07

Tanzania, 1996 Tanzania, 2004-05 Tanzania, 2009-10 Timor-Leste, 2009-10

Togo, 1998 Uganda, 1995 Uganda, 2000-01 Uganda, 2006

Uganda, 2011 Zambia, 1996-97 Zambia, 2001-02 Zambia, 2007

Zimbabwe, 1994 Zimbabwe, 1999 Zimbabwe, 2005-06 Zimbabwe, 2010-11

During

Pregnancy

During

Delivery

During

Postpartum Period

Timing of Death
85 

4.2. Maternal Mortality Estimates 

In DHS survey reports, only deaths that are reported to have occurred during pregnancy, delivery, or the 

postpartum period (2 months in recent DHS surveys; 6 weeks in some earlier DHS surveys) are considered 

maternal deaths. Deaths with unknown status about pregnancy—i.e., missing or not sure response to the 

questions: Was the sibling pregnant (when died)? Di d she die during childbirth? Did she die within two 

months after the end of a pregnancy or childbirth?—are classified as non-maternal. 

It is possible that respondents may be unware of the pregnancy status of sisters who died, especially in 

the first trimester, or they may deliberately underreport pregnancy status—for example, if a sister died 

from abortion-related complications in a setting w here abortion is illegal or socially unacceptable. In 

summary, all deaths lacking pregnancy status are not necessarily non-maternal deaths. We consider that 

DHS may underestimate maternal mortality in areas with high non-response rates for the timing of death 

variable. 

Table 4.4 shows the maternal mortality rate (maternal deaths per 1,000 wom an-years of exposure) and 

maternal mortality ratio (deaths per 100,000 live births) with 95% confidence intervals based on standard 

DHS practice based on 7 years of recall (observation) period from the survey date. Confidence intervals 

were estimated using the jackknife method. 

Confidence interval of MMR estimates was quite large in most DHS surveys. This was not unexpected. 

Maternal deaths are rare events in the statistical sense. The estimation of maternal mortality indicators 

with a reasonably small margin-of-error requires a very large sample size, which is beyond the scope of 

DHS surveys. The relative margin-of-error of MMR (RME: margin-of-error divided by MMR), shown in 

Figure 4.6, varied between 20% and 40% in most (71.3%) DHS surveys. All surveys have more than 10% 

RME. Countries with low MMR had higher relative margins-of-error. 

Table 4.4 Estimates of maternal mortality rates (MMRates) and maternal mortality ratios (MMRs) 

with 95% confidence internals (CI) from 106 Demographic and Health Surveys 1990-2013 

 95% CI 

Country 

DHS

survey 

round

Year of 

survey GFR MMRate MMR LL UL LTR

Sub-Saharan Africa 

Benin DHS-III 1996 205 1.020 498 375 621 0.032

Benin DHS-V 2006 193 0.773 400 328 472 0.023

Burkina Faso DHS-III 1998-99 219 0.962 440 305 575 0.031

Burkina Faso DHS-VI 2010 200 0.682 341 276 405 0.021

Burundi DHS-VI 2010-11 194 0.972 500 379 621 0.033

Cameroon DHS-III 1998 178 0.909 511 375 647 0.028

Cameroon DHS-IV 2004 174 1.198 689 568 810 0.036

Cameroon DHS-VI 2011 170 1.330 782 649 914 0.040

Central African Republic DHS-III 1994-95 185 2.553 1380 1141 1620 0.076

Chad DHS-III 1996-97 223 1.863 836 665 1007 0.055

Chad DHS-IV 2004 225 2.472 1098 685 1512 0.074

Congo (Brazzaville) DHS-V 2005 154 1.204 781 495 1068 0.036

Congo (Brazzaville) DHS-VI 2011-12 161 0.687 426 277 575 0.021

Congo Democratic Republic DHS-V 2007 201 1.087 542 409 674 0.034

Cote d’Ivoire DHS-III 1994 197 1.179 597 418 777 0.036

Cote d’Ivoire DHS-V 2005 163 0.880 539 325 754 0.026

Cote d’Ivoire DHS-VI 2011-12 164 1.004 614 448 780 0.031

Ethiopia DHS-IV 2000 181 1.577 872 707 1036 0.051

(Continued...)
86 

Table 4.4 – Continued

 95% CI 

Country 

DHS

survey 

round 

Year of 

survey GFR MMRate MMR LL UL LTR 

Sub-Saharan Africa 

Ethiopia DHS-IV 2005 185 1.240 671 549 793 0.040 

Ethiopia DHS-VI 2011 169 1.140 675 543 808 0.036 

Gabon DHS-III 2000-01 149 0.771 519 331 707 0.023 

Gabon DHS-VI 2012 131 0.412 316 180 451 0.013 

Guinea DHS-III 1999 196 1.033 528 380 676 0.032 

Guinea DHS-IV 2005 181 2.030 1119 912 1327 0.065 

Guinea DHS-VI 2012 173 1.250 724 536 911 0.039 

Kenya DHS-III 1998 160 1.191 743 594 892 0.036 

Kenya DHS-IV 2003 165 0.834 506 400 612 0.025 

Kenya DHS-V 2008-09 157 0.818 520 348 691 0.025 

Lesotho DHS-IV 2004-05 114 1.066 936 684 1187 0.034 

Lesotho DHS-V 2009-10 108 1.347 1244 931 1558 0.041 

Liberia DHS-V 2006-07 172 1.698 990 683 1297 0.053 

Madagascar DHS-III 1997 202 0.990 490 367 614 0.030 

Madagascar DHS-IV 2003-04 172 0.887 517 348 686 0.028 

Madagascar DHS-V 2008-09 163 0.812 498 404 593 0.026 

Malawi DHS-II 1992 212 1.302 615 406 824 0.042 

Malawi DHS-IV 2000 210 2.357 1123 959 1288 0.070 

Malawi DHS-IV 2004-05 204 1.997 981 823 1138 0.058 

Malawi DHS-V 2010 197 1.331 675 571 778 0.040 

Mali DHS-III 1995-96 234 1.265 541 437 645 0.039 

Mali DHS-IV 2001 231 1.340 581 453 710 0.042 

Mali DHS-V 2006 224 1.036 462 377 548 0.032 

Mali DHS-VI 2012-13 214 0.790 368 261 476 0.024 

Mozambique DHS-III 1997 186 0.538 289 123 455 0.017 

Mozambique DHS-IV 2003-04 188 0.877 466 366 566 0.027 

Mozambique DHS-VI 2011 187 0.763 408 305 511 0.024 

Namibia DHS-II 1992 161 0.473 294 194 394 0.015 

Namibia DHS-IV 2000 134 0.442 330 203 458 0.014 

Namibia DHS-V 2006-07 114 0.580 509 360 658 0.018 

Niger DHS-II 1992 250 1.535 614 475 753 0.046 

Niger DHS-V 2006 242 1.716 708 578 838 0.052 

Niger DHS-VI 2012 264 1.411 535 427 643 0.043 

Nigeria DHS-III 1999 173 0.497 287 189 384 0.015 

Nigeria DHS-V 2008 186 1.014 545 477 614 0.032 

Rwanda DHS-IV 2000 179 2.789 1559 1324 1795 0.094 

Rwanda DHS-IV 2005 176 1.330 757 623 891 0.045 

Rwanda DHS-VI 2010-11 154 0.751 487 395 579 0.025 

Sao Tome and Principe DHS-V 2008-09 152 0.177 116 27 205 0.006 

Senegal DHS-II 1992-93 200 0.998 498 367 629 0.031 

Senegal DHS-IV 2005 166 0.666 401 314 487 0.021 

Senegal DHS-VI 2010-11 163 0.790 484 340 628 0.024 

Sierra Leone DHS-V 2008 175 1.487 849 615 1082 0.045 

(Continued...)
87 

Table 4.4 – Continued

 95% CI 

Country 

DHS

survey 

round 

Year of 

survey GFR MMRate MMR LL UL LTR 

Sub-Saharan Africa 

South Africa DHS-III 1998 97 0.146 150 79 222 0.005 

Swaziland DHS-V 2006-07 131 0.774 589 394 783 0.023 

Tanzania DHS-III 1996 193 1.179 612 461 764 0.036 

Tanzania DHS-IV 2004-05 185 1.119 605 476 735 0.034 

Tanzania DHS-V 2009-10 178 0.880 494 376 611 0.027 

Togo DHS-III 1998 175 0.732 417 302 532 0.023 

Uganda DHS-III 1995 235 1.245 529 401 657 0.037 

Uganda DHS-IV 2000-01 236 1.248 529 420 638 0.037 

Uganda DHS-V 2006 225 0.939 418 317 519 0.029 

Uganda DHS-VI 2011 211 0.912 433 318 548 0.028 

Zambia DHS-III 1996-97 206 1.337 649 522 777 0.040 

Zambia DHS-IV 2001-02 198 1.443 729 589 869 0.043 

Zambia DHS-V 2007 198 1.170 591 453 730 0.035 

Zimbabwe DHS-III 1994 152 0.556 365 253 477 0.017 

Zimbabwe DHS-IV 1999 140 0.904 647 476 819 0.027 

Zimbabwe DHS-V 2005-06 135 0.829 613 461 764 0.024 

Zimbabwe DHS-VI 2010-11 132 1.262 960 781 1139 0.037 

North Africa 

Jordan DHS-III 1997 145 0.051 35 8 62 0.002 

Morocco DHS-II 1992 130 0.493 378 255 501 0.017 

Morocco DHS-IV 2003-04 81 0.221 272 186 359 0.007 

Asia 

Cambodia DHS-IV 2000 127 0.554 437 328 547 0.019 

Cambodia DHS-V 2005-06 106 0.499 472 341 603 0.017 

Cambodia DHS-V 2010-11 95 0.197 206 125 287 0.006 

Indonesia DHS-III 1994 96 0.396 411 284 537 0.012 

Indonesia DHS-III 1997 91 0.262 288 137 438 0.008 

Indonesia DHS-IV 2002-03 82 0.271 331 222 440 0.009 

Indonesia DHS-V 2007 80 0.166 209 137 281 0.005 

Indonesia DHS-VI 2012 75 0.235 313 222 404 0.008 

Nepal DHS-III 1996 162 0.875 539 395 683 0.026 

Nepal DHS-V 2006 252 0.334 133 84 181 0.010 

Philippines DHS-II 1993 131 0.229 175 120 230 0.007 

Philippines DHS-III 1998 119 0.206 172 123 222 0.007 

Timor-Leste DHS-VI 2009-10 172 0.959 557 411 703 0.034 

Latin America 

Bolivia DHS-III 1993-94 160 0.577 360 218 503 0.018 

Bolivia DHS-IV 2003-04 134 0.281 210 146 274 0.009 

Bolivia DHS-V 2008 115 0.309 268 183 353 0.010 

Brazil DHS-III 1996 83 0.153 184 104 263 0.005 

Dominican Republic DHS-IV 2002 99 0.163 165 75 254 0.005 

Dominican Republic DHS-V 2007 88 0.152 173 104 242 0.005 

Guatemala DHS-III 1995 166 0.257 155 96 214 0.008 

(Continued...)
88 

Table 4.4 – Continued

 95% CI 

Country 

DHS

survey 

round 

Year of 

survey GFR MMRate MMR LL UL LTR 

Latin America 

Haiti DHS-IV 2000 148 0.773 523 364 682 0.026 

Haiti DHS-V 2005-06 124 0.777 628 481 776 0.026 

Peru DHS-II 1991-92 121 0.205 169 113 224 0.006 

Peru DHS-III 1996 119 0.316 265 208 322 0.010 

Peru DHS-IV 2000 99 0.183 185 130 241 0.006 

Peru DHS-V 2003-08 81 0.163 203 150 256 0.005 

Peru DHS-VI 2011 80 0.126 157 96 219 0.004 

Note: Data from 4 survey rounds could not be used for MMR estimation because some standard 

variables were missing (e.g., imputed age, cause of death maternal). 

Figure 4.6 Relative margin-of-error by MMR estimates, Demographic and Heath Surveys 

1990-2013 

Note: Surveys with high relative margin-of-error > 0.4 are labeled. 

Gabon 2012

Mozambique 1997

Sao Tome and Principe 2008-09

South Africa 1998

Jordan 1997

Indonesia 1997

Brazil 1996

Dominican Republic 2002

0 .2 .4 .6 .8

Relative margin-of-error

50 100 250 500 1000 1500

MMR
89 

The extent of missingness of the variable on timing of death in relation to pregnancy status for the sisters 

included in the analysis (died during last 7 years) for 108 DHS surveys is shown in Table 4.5 by rank 

order (from lowest to highest). Almost half of the surveys have more than 10% missing responses for this 

variable. 

There are several methods suggested in the statistical literature to handle missing data. Missing values are 

often handled during statistical analysis by the complete case analysis method in which the missing cases 

are dropped from the analysis. However, there are concerns that this procedure is inefficient due to sample 

size reduction (increases margin-of-errors and reduces statistical power) and may introduce bias. 

A simple approach is the weighting method. Under an assumption that the distribution of maternal deaths 

among sisters with unknown pregnancy status is si milar to the distribution among sisters with known 

pregnancy status, we may correct for missing responses by a weighting factor of 1/(1- f ), where f is the 

fraction of non-response rate. It is also possible to take into account the sample characteristics in the 

weighting method, which is often used in longitudinal surveys for correcting drop-out rates. 

A preferred simple data adjustment procedure is to perform imputation that takes uncertainty into account 

in the distribution of missingness. Two common procedures of imputation are single imputation (such as 

hot deck) and multiple imputation methods, such as suggested by Rubin (1987). 

For assessing the extent of underestimation of MMR due to missing values in the pregnancy status during 

female deaths, which is used for classifying maternal mortality, we used all these three methods (complete 

case analysis, weighting, imputation) for esti mating corrected M MRs and co mparing them to DHS 

reported MMRs. 

In case of com plete case analysis, woman pers on-years for m issing cases were excluded from the 

denominator of the MMRate calculation. We have used two methods of imputation: single imputation 

with hot deck method (Andridge and Little 2010), and multiple imputation (Rubin 1987). 

Hot deck is a simple method in which the missing values are populated with the values from other values 

in the data set, either randomly or based on responses from similar subjects. In recent years, the multiple 

imputation method has superseded the single imputation method. However, multiple imputation is better 

implemented by individuals who are both imputers and analysts. It is difficult to distribute multiple 

imputed data sets for public use. On the other hand, single imputed data are convenient for distribution. 

Missing values are often classified into three ty pes: missing completely at random (MCAR), missing at 

random (MAR), and no nignorable (NI) missing values. We consider that the MAR is a more realistic 

assumption, which assumes that the missingness is related to some observed characteristics of the subjects. 

Our preliminary analyses suggest that the missing values were substantially related to respondents ’ 

characteristics, including age, urban/rural residence, education, and wealth quintile in several settings. For 

multiple imputation method, we used 10 im putations and used these variables for dete rmining the 

probabilities of missing values. Multinom ial logistic regressions using respondents’ characteristi cs, 

including age, urban/rural residence, education, and wealth quintile, were utilized for imputing the missing 

values in the timing of the death. 

The corrected MMR estimates with weighting are shown in the last column of Table 4.5. The mean values 

of MMR of the stud y countries with missing response in the tim ing of death was 531 per 100,000l live 

births; in case of weighted analysis, the mean value of MMR was 596. In this adjustment procedure, the 

extent of underestimation bias is proportional to the extent of missingness. 

Side-by-side comparisons of complete case analysis and imputation methods are shown in Table 4.6. 

Complete case analysis results are similar to the standard DHS estimates for the MMR (mean MMR for 
90 

the study surveys with missing values: 531). Maternal deaths are rare events; so the exclusion of personyears of sisters with missing responses from denominators had negligible effects on the MMRate and thus 

on MMR estimates. 

Imputation methods, however, increased MMR estimates substantially. Mean MMRs for h ot deck and 

multiple imputation methods were 605 and 609, respectively. MMR estimates corrected with weighting 

and two imputation methods are quite similar. 

The MMR estimates from all five methods (DHS standard method, weighted with the inverse probability 

of missing response; complete case analysis, hot deck imputation, and multiple imputations) are shown 

graphically in Figure 4.7. 

Table 4.5 Extent of missing responses on timing of death for ascertainment of maternal mortality 

in 105 Demographic and Health Surveys 1990-2013 

Rank in 

underestimation Region Country 

DHS 

survey 

round 

Year of 

survey 

Percent 

missing 

timing of 

death 

(maternal or 

non-maternal) MMR 

MMR 

corrected 

for 

missing 

response

1 North Africa Jordan DHS-III 1997 0.0 35 35 

2 Sub-Saharan Africa Mali DHS-VI 2012-13 0.0 368 368 

3 Sub-Saharan Africa Senegal DHS-VI 2010-11 0.0 484 484 

4 Latin America & 

Caribbean 

Peru DHS-VI 2011 0.1 157 158 

5 Asia Timor-Leste DHS-VI 2009-10 0.5 557 560 

6 Asia Nepal DHS-III 1996 1.0 539 544 

7 Asia Cambodia DHS-V 2010-11 1.8 206 210 

8 Sub-Saharan Africa Uganda DHS-VI 2011 1.9 433 441 

9 Asia Nepal DHS-V 2006 2.7 133 136 

10 Sub-Saharan Africa Ethiopia DHS-IV 2000 2.7 872 896 

11 Sub-Saharan Africa Burundi DHS-VI 2010-11 3.1 500 516 

12 Sub-Saharan Africa Rwanda DHS-VI 2010-11 3.3 487 504 

13 Sub-Saharan Africa Chad DHS-III 1996-97 3.6 836 867 

14 Latin America & 

Caribbean 

Peru DHS-V 2003-08 3.7 203 211 

15 Sub-Saharan Africa Burkina Faso DHS-VI 2010 3.8 341 354 

16 Sub-Saharan Africa Kenya DHS-III 1998 3.9 743 773 

17 Asia Cambodia DHS-V 2005-06 4.0 472 492 

18 Sub-Saharan Africa Kenya DHS-IV 2003 4.5 506 529 

19 Sub-Saharan Africa Ethiopia DHS-VI 2011 4.7 675 709 

20 Sub-Saharan Africa Tanzania DHS-V 2009-10 4.8 494 518 

21 Sub-Saharan Africa Central African 

Republic 

DHS-III 1994-95 4.8 1,380 1,451 

22 Sub-Saharan Africa Cameroon DHS-VI 2011 4.9 782 822 

23 Sub-Saharan Africa Tanzania DHS-IV 2004-05 5.0 605 637 

24 Sub-Saharan Africa Rwanda DHS-IV 2000 5.0 1,559 1,642 

25 Sub-Saharan Africa Chad DHS-IV 2004 5.1 1,098 1,157 

(Continued...)
91 

Table 4.5 – Continued

Rank in 

underestimation Region Country 

DHS 

survey 

round 

Year of 

survey 

Percent 

missing 

timing of 

death 

(maternal or 

non-maternal) MMR 

MMR 

corrected 

for 

missing 

response

26 Asia Indonesia DHS-III 1997 5.1 288 303 

27 Asia Cambodia DHS-IV 2000 5.5 437 463 

28 

Latin America & 

Caribbean 

Bolivia DHS-V 2008 5.6 268 284 

29 Sub-Saharan Africa Benin DHS-III 1996 5.7 498 528 

30 Sub-Saharan Africa Zimbabwe DHS-VI 2010-11 5.9 960 1,020 

31 

Latin America & 

Caribbean 

Haiti DHS-V 2005-06 6.0 628 668 

32 Sub-Saharan Africa Mali DHS-III 1995-96 6.4 541 578 

33 Sub-Saharan Africa Mozambique DHS-IV 2003-04 6.5 466 499 

34 Sub-Saharan Africa Niger DHS-VI 2012 6.6 535 573 

35 North Africa Morocco DHS-II 1992 6.8 378 406 

36 Sub-Saharan Africa Malawi DHS-IV 2004-05 6.9 981 1,054 

37 Sub-Saharan Africa Zambia DHS-IV 2001-02 6.9 729 784 

38 Sub-Saharan Africa Cote d’Ivoire DHS-III 1994 7.0 597 642 

39 Sub-Saharan Africa Zambia DHS-V 2007 7.1 591 636 

40 Sub-Saharan Africa Guinea DHS-VI 2012 7.2 724 780 

41 Sub-Saharan Africa Congo 

Democratic 

Republic 

DHS-V 2007 7.2 542 584 

42 Sub-Saharan Africa Congo 

(Brazzaville) 

DHS-VI 2011-12 7.2 426 460 

43 Sub-Saharan Africa Malawi DHS-IV 2000 7.3 1,123 1,212 

44 Sub-Saharan Africa Uganda DHS-V 2006 7.3 418 451 

45 Sub-Saharan Africa Tanzania DHS-III 1996 7.4 612 661 

46 Sub-Saharan Africa Zambia DHS-III 1996-97 7.6 649 703 

47 Latin America & 

Caribbean 

Haiti DHS-IV 2000 7.8 523 567 

48 Sub-Saharan Africa Guinea DHS-IV 2005 8.0 1,119 1216 

49 Sub-Saharan Africa Malawi DHS-V 2010 8.0 675 733 

50 Sub-Saharan Africa Ethiopia DHS-IV 2005 8.3 671 732 

51 Sub-Saharan Africa Zimbabwe DHS-III 1994 8.7 365 400 

52 Sub-Saharan Africa Cote d’Ivoire DHS-V 2005 8.9 539 592 

53 Sub-Saharan Africa Kenya DHS-V 2008-09 9.2 520 572 

54 Sub-Saharan Africa Rwanda DHS-IV 2005 9.4 757 835 

55 Asia Indonesia DHS-III 1994 9.6 411 455 

56 Sub-Saharan Africa Lesotho DHS-IV 2004-05 9.7 936 1,036 

57 Sub-Saharan Africa Zimbabwe DHS-V 2005-06 10.0 613 681 

58 North Africa Morocco DHS-IV 2003-04 10.0 272 303 

(Continued...)
92 

Table 4.5 – Continued

Rank in 

underestimation Region Country 

DHS 

survey 

round 

Year of 

survey 

Percent 

missing 

timing of 

death 

(maternal or 

non-maternal) MMR 

MMR 

corrected 

for 

missing 

response

59 Sub-Saharan Africa Madagascar DHS-III 1997 10.2 490 546 

60 Sub-Saharan Africa Swaziland DHS-V 2006-07 10.3 589 656 

61 Sub-Saharan Africa 

Congo 

(Brazzaville) DHS-V 2005 10.4 781 872 

62 Asia Indonesia DHS-IV 2002-03 10.6 331 370 

63 Latin America & 

Caribbean 

Dominican 

Republic 

DHS-V 2007 10.6 173 193 

64 Sub-Saharan Africa Mozambique DHS-VI 2011 10.8 408 457 

65 Latin America & 

Caribbean 

Bolivia DHS-III 1993-94 10.8 360 404 

66 Latin America & 

Caribbean 

Bolivia DHS-IV 2003-04 10.9 210 236 

67 Sub-Saharan Africa Senegal DHS-II 1992-93 11.1 498 560 

68 Sub-Saharan Africa Benin DHS-V 2006 11.1 400 450 

69 Sub-Saharan Africa Cameroon DHS-IV 2004 11.5 689 779 

70 Sub-Saharan Africa Uganda DHS-IV 2000-01 11.7 529 599 

71 Sub-Saharan Africa Burkina Faso DHS-III 1998-99 11.8 440 499 

72 Sub-Saharan Africa Niger DHS-V 2006 12.4 708 808 

73 Sub-Saharan Africa Namibia DHS-V 2006-07 12.5 509 582 

74 Sub-Saharan Africa Cameroon DHS-III 1998 12.6 511 584 

75 Asia Indonesia DHS-VI 2012 12.9 313 359 

76 Sub-Saharan Africa Niger DHS-II 1992 13.2 614 707 

77 Sub-Saharan Africa Zimbabwe DHS-IV 1999 13.4 647 747 

78 Latin America & 

Caribbean 

Peru DHS-III 1996 13.9 265 307 

79 Sub-Saharan Africa Mali DHS-IV 2001 14.1 581 677 

80 Asia Indonesia DHS-V 2007 14.9 209 245 

81 Sub-Saharan Africa Uganda DHS-III 1995 14.9 529 622 

82 Sub-Saharan Africa Madagascar DHS-V 2008-09 15.0 498 586 

83 Sub-Saharan Africa Gabon DHS-VI 2012 15.3 316 373 

84 Sub-Saharan Africa Togo DHS-III 1998 15.9 417 496 

85 Sub-Saharan Africa Gabon DHS-III 2000-01 16.8 519 623 

86 Sub-Saharan Africa Cote d’Ivoire DHS-VI 2011-12 17.1 614 740 

87 Latin America & 

Caribbean 

Peru DHS-II 1991-92 17.1 169 204 

88 Sub-Saharan Africa Malawi DHS-II 1992 17.4 615 744 

89 Sub-Saharan Africa Senegal DHS-IV 2005 18.1 401 489 

90 Sub-Saharan Africa Madagascar DHS-IV 2003-04 18.6 517 635 

91 Sub-Saharan Africa Lesotho DHS-V 2009-10 18.9 1,244 1,535 

92 Latin America & 

Caribbean 

Peru DHS-IV 2000 19.1 185 229 

(Continued...)
93 

Table 4.5 – Continued

Rank in 

underestimation Region Country 

DHS 

survey 

round 

Year of 

survey 

Percent 

missing 

timing of 

death 

(maternal or 

non-maternal) MMR 

MMR 

corrected 

for 

missing 

response

93 Sub-Saharan Africa Nigeria DHS-V 2008 19.2 545 674 

94 Asia Philippines DHS-III 1998 19.9 172 215 

95 Latin America & 

Caribbean 

Brazil DHS-III 1996 20.5 184 231 

96 Sub-Saharan Africa Guinea DHS-III 1999 21.9 528 676 

97 Sub-Saharan Africa South Africa DHS-III 1998 22.5 150 194 

98 Latin America & 

Caribbean 

Dominican 

Republic 

DHS-IV 2002 22.6 165 213 

99 Sub-Saharan Africa Mali DHS-V 2006 22.7 462 598 

100 Sub-Saharan Africa Liberia DHS-V 2006-07 22.7 990 1,280 

101 Sub-Saharan Africa Mozambique DHS-III 1997 24.4 289 382 

102 Latin America & 

Caribbean 

Guatemala DHS-III 1995 25.5 155 209 

103 Sub-Saharan Africa Sierra Leone DHS-V 2008 25.8 849 1,143 

104 Asia Philippines DHS-II 1993 29.1 175 247 

105 Sub-Saharan Africa Namibia DHS-IV 2000 31.3 330 481 

106 Sub-Saharan Africa Namibia DHS-II 1992 35.5 294 456 

107 Sub-Saharan Africa Nigeria DHS-III 1999 35.5 287 445 

108 Sub-Saharan Africa Sao Tome and 

Principe 

DHS-V 2008-09 41.6 116 199 

Table 4.6 Comparison of MMR estimates from imputation and complete case analysis using DHS data, 

Demographic and Health Surveys 1990-2013 

Country Year 

Hot deck imputation Multiple imputation Complete case analysis 

MMR LL UL MMR LL UL MMR LL UL 

Sub-Saharan Africa 

Benin 1996 561 424 699 541 410 674 505 381 630 

Benin 2006 474 397 552 458 382 534 403 331 476 

Burkina Faso 1998-99 518 374 663 493 352 635 442 307 578 

Burkina Faso 2010 369 302 437 359 293 425 343 279 408 

Burundi 2010 515 394 637 521 399 645 500 380 621 

CAR 1994-95 1481 1236 1727 1454 1211 1697 1397 1157 1638 

Cameroon 1998 630 475 786 632 472 793 524 380 669 

Cameroon 2004 829 699 960 803 668 939 699 578 821 

Cameroon 2011 826 692 961 820 686 955 782 650 915 

Chad 1996-97 853 678 1029 875 697 1055 845 670 1021 

Chad 2004 1220 753 1688 1227 760 1694 1174 709 1640 

Congo (Brazzaville) 2005 887 590 1185 912 598 1228 824 524 1125 

Congo (Brazzaville) 2011-12 476 322 631 476 320 633 432 283 582 

(Continued...)
94 

Table 4.6 – Continued

Country Year 

Hot deck imputation Multiple imputation Complete case analysis 

MMR LL UL MMR LL UL MMR LL UL 

Sub-Saharan Africa 

Congo Democratic 

Republic 

2007 615 476 755 633 483 784 548 414 683 

Côte d’Ivoire 1994 659 476 843 637 456 820 606 427 786 

Côte d’Ivoire 2005 610 387 834 605 383 828 558 341 776 

Côte d’Ivoire 2011-12 770 587 954 754 572 937 615 450 781 

Ethiopia 2000 907 740 1075 918 748 1089 883 718 1049 

Ethiopia 2005 796 661 932 743 614 873 681 558 805 

Ethiopia 2011 708 574 843 713 578 850 676 544 809 

Gabon 2000 672 474 871 676 469 884 526 338 715 

Gabon 2012 465 298 633 425 263 587 319 184 455 

Guinea 1999 720 551 890 703 533 875 539 389 690 

Guinea 2005 1257 1033 1482 1246 1025 1469 1161 947 1376 

Guinea 2012 803 609 998 806 610 1002 743 554 933 

Kenya 1998 786 634 939 785 632 938 744 596 893 

Kenya 2003 550 435 666 560 446 675 514 406 623 

Kenya 2008-09 604 427 782 595 419 773 522 351 694 

Lesotho 2004 1125 842 1409 1045 782 1308 945 692 1199 

Lesotho 2009 1550 1203 1898 1579 1222 1936 1256 939 1574 

Liberia 2007 1265 941 1590 1277 951 1603 1002 693 1312 

Madagascar 1997 560 431 690 565 436 696 492 369 616 

Madagascar 2003-04 609 435 784 635 444 828 520 351 690 

Madagascar 2008-09 618 509 728 604 499 710 503 409 598 

Malawi 1992 679 466 893 742 522 963 618 409 828 

Malawi 2000 1243 1066 1421 1216 1047 1387 1131 966 1297 

Malawi 2004 1106 942 1271 1082 916 1249 987 829 1146 

Malawi 2010 740 634 847 733 626 842 675 572 779 

Mali 1995-96 575 466 685 591 484 700 546 442 651 

Mali 2001 685 545 826 681 544 819 583 455 712 

Mali 2006 631 525 738 616 512 720 474 387 562 

Mozambique 1997 360 185 536 423 220 628 290 123 458 

Mozambique 2003 533 424 643 525 417 635 487 382 593 

Mozambique 2011 468 360 577 462 355 570 412 309 516 

Namibia 1992 505 366 645 438 312 564 295 195 396 

Namibia 2000 490 325 656 536 369 705 333 205 462 

Namibia 2006-07 573 418 729 591 434 749 510 362 659 

Niger 1992 766 593 940 809 636 982 616 477 756 

Niger 2006 834 691 978 812 674 950 723 593 854 

(Continued...)
95 

Table 4.6 – Continued

Country Year 

Hot deck imputation Multiple imputation Complete case analysis 

MMR LL UL MMR LL UL MMR LL UL 

Sub-Saharan Africa 

Nigeria 1999 447 325 570 464 338 590 294 196 393 

Nigeria 2008 712 634 791 705 626 785 552 483 622 

Rwanda 2000 1647 1406 1889 1726 1477 1977 1588 1349 1828 

Rwanda 2005 847 709 986 835 695 975 760 626 895 

Rwanda 2010 512 420 605 511 418 604 492 401 584 

São Tomé and Príncipe 2008-09 165 65 266 290 127 453 117 29 206 

Senegal 1992-93 611 468 755 625 478 773 499 368 631 

Senegal 2005 560 456 665 517 417 618 417 328 507 

Sierra Leone 2008 1173 909 1438 1242 966 1518 903 667 1140 

South Africa 1998 179 103 256 201 116 287 151 80 223 

Swaziland 2006-07 686 477 896 680 469 892 593 398 789 

Tanzania 1996 682 525 840 674 516 833 616 465 768 

Tanzania 2004-05 629 497 762 657 522 793 613 484 743 

Tanzania 2010 563 438 689 545 423 668 507 389 626 

Togo 1998 498 377 620 485 361 610 419 304 535 

Uganda 1995-96 626 489 764 643 499 788 539 410 669 

Uganda 2000-01 625 504 747 636 517 757 541 432 651 

Uganda 2006 442 339 546 463 357 571 424 321 528 

Uganda 2011 446 330 563 447 331 564 433 318 549 

Zambia 1996 695 564 827 714 581 847 652 524 781 

Zambia 2001-02 807 658 957 796 649 945 733 593 874 

Zambia 2007 633 492 775 643 500 787 592 454 731 

Zimbabwe 1994 377 263 492 405 285 526 366 254 479 

Zimbabwe 1999 766 587 946 784 596 972 649 478 821 

Zimbabwe 2005-06 680 525 836 693 537 849 613 462 765 

Zimbabwe 2010 995 813 1178 1007 825 1191 963 784 1143 

North Africa 

Morocco 1992 513 362 665 544 400 689 379 257 502 

Morocco 2003-04 321 230 413 321 229 414 273 187 360 

Asia 

Cambodia 2000 481 366 597 473 360 588 438 329 548 

Cambodia 2005 488 357 620 494 362 627 472 342 603 

Cambodia 2010 207 127 288 211 130 293 207 127 288 

Indonesia 1994 471 340 603 470 334 607 413 287 540 

Indonesia 1997 345 184 507 334 175 494 315 158 473 

Indonesia 2002-03 378 262 495 378 261 496 334 224 445 

Indonesia 2007 258 181 336 277 197 358 209 138 281 

Indonesia 2012 345 252 439 358 262 455 313 222 405 

(Continued...)
96 

Table 4.6 – Continued

Country Year 

Hot deck imputation Multiple imputation Complete case analysis 

MMR LL UL MMR LL UL MMR LL UL 

Asia 

Nepal 1996 546 401 692 550 405 696 539 395 684 

Nepal 2006 136 88 185 139 88 190 133 85 182 

Niger 2012 575 466 685 573 462 686 540 433 648 

Philippines 1993 274 208 341 264 198 331 176 121 232 

Philippines 1998 227 170 285 250 188 313 173 124 223 

Timor-Leste 2009-10 562 416 709 561 415 708 558 412 705 

Latin America and 

Caribbean 

Bolivia 1994 411 265 558 416 267 566 361 219 504 

Bolivia 2003 248 179 318 248 178 318 211 148 275 

Bolivia 2008 296 205 388 290 202 379 271 187 356 

Brazil 1996 259 159 360 262 163 362 184 105 264 

Dominican Republic 2002 228 130 327 244 146 343 168 79 258 

Dominican Republic 2007 201 124 279 202 128 276 174 106 243 

Guatemala 1995 252 167 338 238 158 319 156 97 216 

Haiti 2000 531 371 692 568 389 747 524 365 684 

Haiti 2005-06 649 501 798 671 518 826 630 483 778 

Peru 1991-92 299 224 375 304 226 383 176 119 234 

Peru 1996 329 264 395 325 261 389 269 212 327 

Peru 2000 234 170 299 254 186 323 188 133 244 

Peru 2004-06 221 166 277 220 165 276 207 154 261 

Peru 2007-08 221 166 277 220 165 276 207 154 261 

Peru 2011 159 98 221 171 102 242 158 97 220 

 
97 

Figure 4.7 Comparison of five methods for estimating MMR (DHS method, complete case analysis, 

weighting for non-response, single imputation with hot deck method, and multiple imputation 

method), DHS data from sub-Saharan Africa, Demographic and Health Surveys 1990-2013 

(Continued...)

 

0 500 1,000 1,500 0 500 1,000 1,500 0 500 1,000 1,500 0 500 1,000 1,500 0 500 1,000 1,500

Benin 1996 Benin 2006 Bolivia 1994 Bolivia 2003 Bolivia 2008

Brazil 1996 Burkina Faso 1998-99 Burkina Faso 2010 Burundi 2010 CAR 1994-95

Cambodia 2000 Cambodia 2005 Cambodia 2010 Cameroon 1998 Cameroon 2004

Cameroon 2011 Chad 1996-97 Chad 2004 Congo (Brazzaville) 2005 Congo (Brazzaville) 2011-12

Congo Democratic Republic 2007 Cote d'Ivoire 1994 Cote d'Ivoire 2005 Cote d'Ivoire 2011-12 Dominican Republic 2002

Dominican Republic 2007 Ethiopia 2000 Ethiopia 2005 Ethiopia 2011 Gabon 2000

DHS estimate Weighted Hotdeck imputation

Multiple imputation Complete case analysis
98 

Figure 4.7 – Continued

(Continued...)

 

0 500 1,000 1,500 0 500 1,000 1,500 0 500 1,000 1,500 0 500 1,000 1,500 0 500 1,000 1,500

Gabon 2012 Guatemala 1995 Guinea 1999 Guinea 2005 Guinea 2012

Haiti 2000 Haiti 2005-06 Indonesia 1994 Indonesia 1997 Indonesia 2002-03

Indonesia 2007 Indonesia 2012 Kenya 1998 Kenya 2003 Kenya 2008-09

Lesotho 2004 Lesotho 2009 Liberia 2007 Madagascar 1997 Madagascar 2003-04

Madagascar 2008-09 Malawi 1992 Malawi 2000 Malawi 2004 Malawi 2010

Mali 1995-96 Mali 2001 Mali 2006 Morocco 1992 Morocco 2003-04

DHS estimate Weighted Hotdeck imputation

Multiple imputation Complete case analysis
99 

Figure 4.7 – Continued

(Continued...)

 

0 500 1,000 1,500 0 500 1,000 1,500 0 500 1,000 1,500 0 500 1,000 1,500 0 500 1,000 1,500

Mozambique 1997 Mozambique 2003 Mozambique 2011 Namibia 1992 Namibia 2000

Namibia 2006-07 Nepal 1996 Nepal 2006 Niger 1992 Niger 2006

Niger 2012 Nigeria 1999 Nigeria 2008 Peru 1991-92 Peru 1996

Peru 2000 Peru 2004-06 Peru 2007-08 Peru 2011 Philippines 1993

Philippines 1998 Rwanda 2000 Rwanda 2005 Rwanda 2010 Sao Tome and Principe 2008-09

Senegal 1992-93 Senegal 2005 Sierra Leone 2008 South Africa 1998 Swaziland 2006-07

DHS estimate Weighted Hotdeck imputation

Multiple imputation Complete case analysis
100 

Figure 4.7 – Continued

Instead of modeling maternal mortality with the MMR as done by IHME, the World Health Organization, 

UNICEF, UNFPA, and the World Bank use the proportion of deaths to women age 15-49 that are 

maternal (PMDF), which is considered more stable than the MMR. Age-specific maternal mortality ratio 

estimation also used PMDF (Nove et al. 2014). 

Maternal deaths are a subset of adult female deaths, and the underestimation of adult mortality thus also 

underestimates maternal mortality. However, PMDF may not be affected by the underestimation of adult 

mortality. Hill, AbouZahr, and Wardlaw (2001) consider that PMDF is a more robust and reliable estimate 

from the sisterhood method than the MMR estimate. As a proportion, PMDF may be used as logit, which 

bounds the predicted model values between 0 and 1; this specification in m odeling guarantees that the 

estimated MMR is never a negative value. 

0 500 1,0001,500 0 500 1,0001,500 0 500 1,0001,500 0 500 1,0001,500

0 500 1,0001,500

Tanzania 1996 Tanzania 2004-05 Tanzania 2010 Timor-Leste 2009-10 Togo 1998

Uganda 1995-96 Uganda 2000-01 Uganda 2006 Uganda 2011 Zambia 1996

Zambia 2001-02 Zambia 2007 Zimbabwe 1994 Zimbabwe 1999 Zimbabwe 2005-06

Zimbabwe 2010

DHS estimate Weighted Hotdeck imputation

Multiple imputation Complete case analysis
101 

Despite several advantages of using PMDF for maternal mortality estimation, the empirical relationship 

between PMDF and MMR is not well known. Figure 4.8 compares PMDF and MMR trend patterns for 

maternal deaths in DHS countries. It is difficult to draw any inference from this comparison that the PMDF 

is more stable than the MMR. For example, in Ethiopia, while the MMR remains about the same between 

the two DHS survey rounds, the PMDF increased. A comparison of global MMR estimates from PMDF 

and MMR may provide additional insight into the suitability or preference of one indicator over the other 

for estimating global maternal mortality trends. 

 
102 

Figure 4.8 Trends in the proportion of maternal deaths among female deaths (PMDF) and the 

maternal mortality ratio (MMR) by DHS survey rounds, Demographic and Health Surveys 1990-

2013 

0 500 1000 1500 0 500 1000 1500 0 500 1000 1500 0 500 1000 1500 0 500 1000 1500

0 500 1000 1500

10 20 30 40 10 20 30 40 10 20 30 40 10 20 30 40 10 20 30 40 10 20 30 40

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

DHS-II

DHS-III

DHS-IV

DHS-V

DHS-VI

Benin Bolivia Burkina Faso Cambodia Cameroon Chad

Congo (Brazzaville) Cote d'Ivoire Dominican Republic Ethiopia Gabon Guinea

Haiti Indonesia Kenya Lesotho Madagascar Malawi

Mali Morocco Mozambique Namibia Nepal Niger

Nigeria Peru Philippines Rwanda Senegal Tanzania

Uganda Zambia Zimbabwe

PMDF MMR

Percent

DHS survey round
103 

4.3. Risk of Maternal Mortality Underreporting 

Epidemiological studies suggest that the risk of maternal death is highest at the extre me ends of the 

reproductive years. Maternal m ortality risk is higher at younger ages, when pelvic development is 

incomplete, and at older ages and higher parities, when a mother’s health condition is more compromised. 

If this risk profile holds, it is expected that the share of maternal mortality will be higher in these age 

groups. A recent study of 144 countries shows a J- shaped age distribution of maternal mortality, with a 

slightly increased risk of mortality in adolescents compared with women in the age group 20-24 (Nove at 

al. 2014). Ab ortion-related deaths are o ften high in the youngest age group, so there is co ncern that 

maternal deaths may be underreported in the youngest group, especially in settings where abortions are 

prohibited or socially unacceptable. 

It could be possible to examine the possibilities of underreporting of maternal mortality in the youngest 

age group or in the extreme reproductive age groups due to age-displacement by looking at age-specific 

MMR estimates. With high obstetrical risks, MMRs ar e expected to be high in the youngest and oldest 

age groups of reproductive period. However, the estimation of age-specific MMRs at the country level is 

unreliable from DHS survey data due to small sample size, especially in these two age groups. Blanc, 

Winfrey, and Ross (2013) combined data from 38 DHS surveys to circumvent the problems of small 

sample size for a reasonable analysis of maternal mortality age patterns. Similarly, the analysis by Nove 

at al. (2014) for age-specific MMR is also based on a ggregate data. It is, however, difficult t o examine 

underreporting of age-specific maternal mortality from aggregate data. 

Instead, we examined underreporting by comparing the age-specific maternal death distribution to birth 

distribution. With a birth-specific constant risk at each age group, we expect a proportional covariation in 

these two distributions. In the presence of maternal mortality underreporting, we expect that the proportion 

of maternal deaths will be lower than their relative share. Table 4.7 shows the distribution of deaths and 

births by age distribution of the sibling sisters. The results are shown graphically in Figure 4.7. The total 

births are calculated by summing the expected number of births, given the current age-specific fertility 

rates (ASFRs) of the respondents—i.e ., ASFR equals the distribution of deaths and births b y age 

distribution of sibling sisters [respondents] × number of sisters in the age category—over the age range. 

In cases where deaths are proportional to births, we expect that the distribution of births and deaths will 

be similar. This pattern is observed in Cameroon 1998, Ethiopia 2000, Niger 2102, and Peru 1991-1992. 

In the absence of maternal m ortality underreporting, we expect that the proport ional share of maternal 

deaths will be higher in the youngest and oldest age groups, compared with the corresponding distribution 

of births in the respective age groups. 

Many DHS surveys show a disproportionately higher proportion of births in the youngest age group but 

a lower proportion of deaths (e.g., Côte d’ Ivoire, Zambia, Zimbabwe). These survey rounds may have 

underreporting of maternal deaths in the youngest age group. 

Although we are able to assess the indications of underestimations based on the relationship between the 

distribution of maternal deaths and births from the graphs (Figure 4.9) or the table (Table 4.7), it is to not 

possible to s ummarize the magnitude of the underestimation. Using an e conometric method that 

graphically shows the concentration of inequality using the Gini coefficient concentration index, it may 

be possible to summarize the level of age-specific underestimation of maternal mortality. We show the 

concentration curves in the Appendix (Figure A2) fo r additional insights into the relationship between 

birth and maternal death distribution. The x-axis shows the cumulative proportion of births and the y-axis 

shows the cumulative proportion of deaths over the age range. A complete thick diagonal line suggests 

proportional distributions of maternal deaths and births. A thick curved line above the diagonal line (e.g., 

Chad 2004) suggests higher proportional deaths in the youngest group. This suggests that underreporting 
104 

of maternal deaths in these surveys may be absent or minimal. The concentration graph showing a large 

downward curve (e.g., Cam bodia 2005-06, Malawi 2004-05, Swaziland 2006-07, Zambia 2007) may 

indicate the presence of underreporting of maternal deaths in the survey round. 

Table 4.7 Percentage distribution of maternal deaths and births (expected births among sisters) 

by age, Demographic and Health Surveys 1990-2013 

 Age 

Country 

DHS 

survey 

round 

Year of 

survey 

Maternal

deaths/

births 15-19 20-24 25-29 30-34 35-39 40-44 45-49

Sub-Saharan Africa 

Benin DHS-III 1996 Deaths 11.8 18.8 19.6 32.4 8.0 7.5 2.0 

DHS-III Births 11.6 27.6 26.7 19.2 11.0 3.3 0.6 

Benin DHS-V 2006 Deaths 7.0 13.7 25.3 28.4 17.8 6.2 1.6 

 DHS-V Births 11.7 28.8 28.2 18.8 9.1 2.7 0.7 

Burkina Faso DHS-III 1998-99 Deaths 20.8 36.0 14.7 7.1 13.4 6.0 1.9 

 DHS-IV Births 13.9 29.1 24.7 17.8 10.1 3.7 0.8 

Burkina Faso DHS-VI 2010 Deaths 8.5 23.1 21.0 19.7 17.2 7.0 3.5 

 DHS-VI Births 13.2 28.2 25.9 19.0 10.1 3.1 0.4 

Burundi DHS-VI 2010-11 Deaths 13.8 15.8 21.3 17.9 18.4 6.7 6.1 

 DHS-VI Births 7.7 30.1 27.2 19.6 10.9 3.9 0.7 

Cameroon DHS-III 1998 Deaths 10.1 31.5 26.6 18.3 10.4 3.0 0.0 

DHS-III Births 16.8 30.4 25.8 15.9 8.2 2.5 0.4 

Cameroon DHS-IV 2004 Deaths 17.3 14.8 26.6 22.8 7.0 8.2 3.3 

 DHS-IV Births 18.0 30.3 25.3 16.3 7.4 2.3 0.4 

Cameroon DHS-VI 2011 Deaths 11.1 25.4 22.3 21.1 11.4 5.2 3.4 

 DHS-VI Births 15.1 30.0 27.3 16.9 8.1 2.2 0.4 

Central African Republic DHS-III 1994-95 Deaths 14.0 18.7 23.4 18.2 14.6 9.3 1.6 

DHS-III Births 18.1 30.4 25.2 16.6 7.0 2.3 0.4 

Chad DHS-III 1996-97 Deaths 18.1 24.5 12.1 26.2 12.8 5.4 0.9 

DHS-III Births 18.5 30.4 26.3 16.0 6.9 1.7 0.2 

Chad DHS-IV 2004 Deaths 30.6 23.2 20.8 16.6 3.9 3.4 1.6 

 DHS-IV Births 18.9 29.0 24.3 17.2 8.2 2.1 0.2 

Congo (Brazzaville) DHS-V 2005 Deaths 8.8 27.6 22.5 16.7 15.1 9.0 0.3 

 DHS-V Births 15.8 28.2 25.1 17.9 9.7 2.8 0.5 

Congo (Brazzaville) DHS-VI 2011-12 Deaths 10.6 15.1 14.7 26.9 24.0 3.4 5.3 

 DHS-VI Births 14.8 25.4 25.7 20.0 11.1 2.6 0.3 

Congo Democratic Republic DHS-V 2007 Deaths 12.0 18.2 26.3 21.6 6.7 11.5 3.6 

 DHS-V Births 12.1 26.1 25.8 20.8 10.5 3.9 0.7 

Côte d’Ivoire DHS-III 1994 Deaths 8.9 16.0 28.1 20.0 9.8 12.7 4.7 

DHS-III Births 17.1 29.2 25.4 16.9 8.6 2.5 0.3 

Côte d’Ivoire DHS-V 2005 Deaths 12.4 24.4 20.9 14.4 11.8 13.0 3.1 

 DHS-V Births 17.1 29.7 24.6 16.6 9.0 2.5 0.4 

Côte d’Ivoire DHS-VI 2011-12 Deaths 8.5 18.9 19.7 18.3 21.4 7.7 5.4 

 DHS-VI Births 14.8 28.3 26.6 18.0 8.9 2.9 0.6 

Ethiopia DHS-IV 2000 Deaths 12.0 23.9 21.3 23.4 12.9 4.6 1.9 

 DHS-IV Births 12.6 27.8 25.4 19.3 10.8 3.7 0.6 

Ethiopia DHS-IV 2005 Deaths 7.7 22.1 26.9 22.8 17.8 2.1 0.6 

 DHS-IV Births 13.1 28.3 25.6 19.1 9.7 3.5 0.7 

(Continued...)
105 

Table 4.7 – Continued

 Age 

Country 

DHS 

survey 

round 

Year of 

survey 

Maternal

deaths/

births 15-19 20-24 25-29 30-34 35-39 40-44 45-49

Sub-Saharan Africa 

Ethiopia DHS-VI 2011 Deaths 9.4 17.9 17.3 32.0 13.5 7.6 2.2 

 DHS-VI Births 12.0 29.1 28.1 17.9 9.3 3.0 0.6 

Gabon DHS-III 2000-01 Deaths 12.1 22.8 35.9 12.0 7.9 7.2 2.1 

DHS-III Births 21.3 28.5 22.9 17.1 8.2 1.8 0.2 

Gabon DHS-VI 2012 Deaths 34.5 11.0 21.2 6.7 17.8 7.0 1.8 

 DHS-VI Births 17.0 25.7 25.3 18.1 10.4 3.3 0.3 

Guinea DHS-III 1999 Deaths 4.3 18.7 29.5 23.0 16.5 6.2 1.9 

DHS-III Births 16.4 26.4 25.1 19.4 8.9 3.1 0.7 

Guinea DHS-IV 2005 Deaths 15.4 18.0 16.5 19.6 18.5 8.7 3.4 

 DHS-IV Births 15.5 26.1 24.6 19.0 10.7 3.6 0.5 

Guinea DHS-VI 2012 Deaths 18.5 21.9 18.9 18.3 15.7 4.6 2.1 

 DHS-VI Births 17.0 26.5 25.5 17.9 9.2 3.2 0.6 

Kenya DHS-III 1998 Deaths 11.0 27.6 24.5 17.9 11.1 7.5 0.4 

DHS-III Births 13.4 31.6 27.1 17.6 7.6 2.4 0.3 

Kenya DHS-IV 2003 Deaths 10.3 24.6 23.5 21.8 15.1 3.3 1.4 

 DHS-IV Births 13.4 31.6 26.1 17.5 8.3 2.6 0.5 

Kenya DHS-V 2008-09 Deaths 8.1 16.6 21.2 16.8 24.8 6.5 6.0 

 DHS-V Births 12.5 30.7 26.1 18.4 9.2 2.8 0.4 

Lesotho DHS-IV 2004-05 Deaths 6.6 13.1 22.9 19.2 21.1 16.3 0.7 

 DHS-IV Births 14.6 30.8 24.8 15.7 10.2 3.5 0.5 

Lesotho DHS-V 2009-10 Deaths 5.4 18.5 32.1 21.7 13.4 6.5 2.2 

 DHS-V Births 14.8 33.1 25.3 15.5 8.5 2.7 0.3 

Liberia DHS-V 2006-07 Deaths 16.5 12.8 19.5 20.4 13.9 12.5 4.4 

 DHS-V Births 13.9 26.7 24.0 18.7 11.6 4.0 1.1 

Madagascar DHS-III 1997 Deaths 12.5 21.2 24.0 17.3 18.5 4.2 2.4 

DHS-III Births 16.2 28.7 24.1 17.4 9.8 3.4 0.4 

Madagascar DHS-IV 2003-04 Deaths 6.6 33.4 13.9 13.7 18.1 13.1 1.1 

 DHS-IV Births 14.8 27.9 25.1 18.0 10.2 3.5 0.5 

Madagascar DHS-V 2008-09 Deaths 18.0 17.4 20.4 18.6 14.8 7.7 3.1 

 DHS-V Births 15.5 27.7 24.1 17.9 10.6 3.6 0.5 

Malawi DHS-II 1992 Deaths 19.2 7.6 22.4 21.3 17.7 5.2 6.6 

 DHS-II Births 14.7 27.1 24.5 17.1 10.8 4.4 1.4 

Malawi DHS-IV 2000 Deaths 3.9 23.1 21.7 22.9 12.8 12.6 3.1 

 DHS-IV Births 16.4 32.2 24.0 15.1 8.3 3.1 0.9 

Malawi DHS-IV 2004-05 Deaths 3.3 21.6 26.5 20.9 13.5 9.1 5.1 

 DHS-IV Births 17.4 33.4 23.6 14.6 7.5 2.8 0.7 

Malawi DHS-V 2010 Deaths 8.4 15.3 23.6 18.9 18.9 10.4 4.4 

 DHS-V Births 16.3 30.9 25.3 16.0 8.1 2.8 0.6 

Mali DHS-III 1995-96 Deaths 14.2 22.4 21.6 17.3 13.3 9.4 1.8 

DHS-III Births 16.6 28.4 25.0 17.4 9.5 2.8 0.4 

Mali DHS-IV 2001 Deaths 17.8 20.7 20.4 19.2 11.8 7.7 2.4 

 DHS-IV Births 17.2 27.3 23.6 17.6 10.2 3.6 0.6 

(Continued...)

 
106 

Table 4.7 – Continued

 Age 

Country 

DHS 

survey 

round 

Year of 

survey 

Maternal

deaths/

births 15-19 20-24 25-29 30-34 35-39 40-44 45-49

Sub-Saharan Africa 

Mali DHS-V 2006 Deaths 15.6 22.7 24.8 18.7 13.4 3.7 1.1 

 DHS-V Births 18.1 28.7 24.6 16.8 8.7 2.8 0.3 

Mali DHS-VI 2012-13 Deaths 12.2 13.9 21.6 35.3 10.1 5.4 1.5 

 DHS-VI Births 16.4 29.0 26.6 16.9 8.2 2.3 0.6 

Mozambique DHS-III 1997 Deaths 22.4 47.5 9.4 5.4 5.9 9.3 0.1 

DHS-III Births 18.1 31.0 25.0 15.0 7.6 2.9 0.4 

Mozambique DHS-IV 2003-04 Deaths 8.5 20.2 21.9 21.9 17.3 10.2 0.0 

 DHS-IV Births 18.4 29.0 24.4 15.9 8.6 2.8 0.9 

Mozambique DHS-VI 2011 Deaths 14.0 27.9 26.3 13.2 9.7 4.5 4.4 

 DHS-VI Births 16.0 28.3 24.2 17.4 10.0 3.4 0.8 

Namibia DHS-II 1992 Deaths 6.7 20.4 19.0 6.7 22.2 17.6 7.4 

 DHS-II Births 12.7 26.4 26.4 18.0 11.3 4.3 0.9 

Namibia DHS-IV 2000 Deaths 7.6 18.8 34.8 23.2 12.1 3.5 0.0 

 DHS-IV Births 12.0 26.2 25.7 19.2 11.5 4.3 1.2 

Namibia DHS-V 2006-07 Deaths 9.6 16.9 19.0 24.6 10.1 7.9 11.9 

 DHS-V Births 11.7 27.6 25.9 19.7 11.3 3.4 0.4 

Niger DHS-II 1992 Deaths 10.4 28.5 24.1 17.8 11.9 6.8 0.5 

 DHS-II Births 19.3 28.3 25.1 16.3 7.9 2.6 0.6 

Niger DHS-V 2006 Deaths 15.6 23.6 19.2 17.1 11.7 10.8 1.9 

 DHS-V Births 17.7 27.7 23.5 17.6 9.7 3.2 0.7 

Niger DHS-VI 2012 Deaths 15.4 26.8 18.3 21.1 10.7 5.9 1.8 

 DHS-VI Births 16.5 27.4 24.5 17.6 10.0 3.2 0.8 

Nigeria DHS-III 1999 Deaths 24.0 23.4 21.3 11.4 12.8 5.0 1.9 

DHS-III Births 16.3 29.5 25.6 17.5 8.1 2.6 0.4 

Nigeria DHS-V 2008 Deaths 15.7 22.2 19.0 23.7 11.8 6.3 1.3 

 DHS-V Births 13.2 26.5 27.5 19.4 9.2 3.3 0.9 

Rwanda DHS-IV 2000 Deaths 4.9 18.6 19.0 24.1 18.7 11.7 3.1 

 DHS-IV Births 6.2 26.2 27.3 21.8 12.8 4.9 0.8 

Rwanda DHS-IV 2005 Deaths 4.3 19.9 19.5 24.7 15.8 13.1 2.7 

 DHS-IV Births 5.4 27.2 27.7 20.9 12.8 5.2 0.8 

Rwanda DHS-VI 2010-11 Deaths 4.3 15.7 25.5 23.8 17.6 10.2 2.9 

 DHS-VI Births 5.0 26.6 30.3 20.9 11.8 4.8 0.6 

São Tomé and Príncipe DHS-V 2008-09 Deaths 0.0 0.0 12.4 33.7 8.4 45.6 0.0 

 DHS-V Births 12.1 28.3 23.4 19.2 12.6 4.1 0.2 

Senegal DHS-II 1992-93 Deaths 14.3 20.6 17.5 11.1 27.0 9.5 0.0 

 DHS-II Births 13.7 27.1 25.8 19.2 10.5 3.0 0.6 

Senegal DHS-IV 2005 Deaths 13.6 23.8 18.3 14.0 20.2 8.5 1.7 

 DHS-IV Births 12.2 26.6 26.8 19.8 10.8 3.3 0.5 

Senegal DHS-VI 2010-11 Deaths 8.7 20.7 22.3 28.9 12.8 5.7 0.9 

 DHS-VI Births 11.6 27.5 28.2 19.5 10.0 3.0 0.3 

Sierra Leone DHS-V 2008 Deaths 21.5 19.8 19.7 24.6 9.3 3.9 1.2 

 DHS-V Births 16.9 26.9 24.9 17.5 9.9 3.3 0.7 

(Continued...)

 
107 

Table 4.7 – Continued

 Age 

Country 

DHS 

survey 

round 

Year of 

survey 

Maternal

deaths/

births 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

Sub-Saharan Africa 

South Africa DHS-III 1998 Deaths 8.6 29.7 25.1 21.9 10.5 4.1 0.0 

DHS-III Births 12.0 25.7 26.8 20.4 11.3 3.2 0.6 

Swaziland DHS-V 2006-07 Deaths 3.3 19.4 18.6 22.9 23.7 12.2 0.0 

 DHS-V Births 17.3 30.3 23.8 17.8 8.8 1.8 0.1 

Tanzania DHS-III 1996 Deaths 12.1 27.9 20.7 17.1 12.4 4.9 5.0 

DHS-III Births 14.2 29.3 25.4 17.1 9.9 3.2 0.8 

Tanzania DHS-IV 2004-05 Deaths 7.5 23.3 24.9 20.7 13.2 7.2 3.2 

 DHS-IV Births 13.9 29.7 25.9 18.0 9.2 2.9 0.4 

Tanzania DHS-V 2009-10 Deaths 5.1 20.5 18.5 27.9 14.9 11.3 1.8 

 DHS-V Births 13.6 28.2 24.4 18.9 10.9 3.4 0.6 

Togo DHS-III 1998 Deaths 7.2 8.9 23.2 14.4 23.5 17.4 5.4 

DHS-III Births 10.3 26.8 27.2 19.4 11.5 3.9 0.8 

Uganda DHS-III 1995 Deaths 10.8 19.2 24.3 30.6 9.8 2.8 2.4 

DHS-III Births 17.8 31.0 26.5 15.5 6.8 2.1 0.4 

Uganda DHS-IV 2000-01 Deaths 5.3 15.0 35.2 26.1 12.3 5.2 0.9 

 DHS-IV Births 16.5 30.5 24.9 17.0 8.5 2.1 0.5 

Uganda DHS-V 2006 Deaths 11.5 19.7 27.1 22.9 11.0 4.6 3.1 

 DHS-V Births 14.4 29.1 25.7 17.9 9.5 2.9 0.5 

Uganda DHS-VI 2011 Deaths 6.2 23.9 12.1 28.6 13.5 9.8 5.9 

 DHS-VI Births 13.9 29.8 25.8 17.6 9.4 2.9 0.5 

Zambia DHS-III 1996-97 Deaths 12.2 23.1 29.2 20.9 10.7 2.1 1.8 

DHS-III Births 16.8 30.7 24.3 16.8 8.6 2.4 0.4 

Zambia DHS-IV 2001-02 Deaths 11.2 19.4 34.7 18.1 7.9 8.4 0.3 

 DHS-IV Births 16.9 30.2 24.5 16.6 8.5 2.7 0.5 

Zambia DHS-V 2007 Deaths 4.5 13.0 22.1 30.5 19.8 6.9 3.2 

 DHS-V Births 14.6 28.2 25.7 18.2 9.8 3.0 0.5 

Zimbabwe DHS-III 1994 Deaths 7.1 23.4 26.6 33.5 3.8 1.7 3.7 

DHS-III Births 13.4 28.2 25.6 18.8 10.2 3.3 0.5 

Zimbabwe DHS-IV 1999 Deaths 7.6 25.1 23.3 23.9 12.8 7.3 0.0 

 DHS-IV Births 15.0 30.8 24.7 16.5 9.6 3.0 0.5 

Zimbabwe DHS-V 2005-06 Deaths 8.0 10.7 20.5 24.1 22.0 11.4 3.2 

 DHS-V Births 15.5 33.1 25.0 15.6 7.6 2.7 0.4 

Zimbabwe DHS-VI 2010-11 Deaths 8.6 20.3 28.9 18.4 14.7 6.1 3.0 

 DHS-VI Births 14.2 33.0 26.9 15.9 7.7 2.0 0.5 

North Africa 

Jordan DHS-III 1997 Deaths 0.0 0.0 39.5 15.4 30.5 14.6 0.0 

DHS-III Births 6.8 29.6 32.8 20.1 8.5 2.0 0.2 

Morocco DHS-II 1992 Deaths 19.3 7.0 21.1 21.1 19.3 7.0 5.3 

 DHS-II Births 6.8 24.6 30.2 22.5 11.3 3.8 0.8 

Morocco DHS-IV 2003-04 Deaths 3.5 21.7 12.4 25.2 16.7 20.5 0.0 

 DHS-IV Births 7.0 23.8 27.9 24.1 13.2 3.6 0.3 

(Continued...)

 
108 

Table 4.7 – Continued

 Age 

Country 

DHS 

survey 

round 

Year of 

survey 

Maternal

deaths/

births 15-19 20-24 25-29 30-34 35-39 40-44 45-49

Asia 

 

Cambodia DHS-IV 2000 Deaths 3.1 11.4 26.3 22.9 27.4 6.7 2.3 

 DHS-IV Births 6.5 24.7 28.5 22.6 13.0 4.1 0.6 

Cambodia DHS-V 2005-06 Deaths 5.0 9.5 14.0 28.7 21.9 16.0 4.9 

 DHS-V Births 10.0 29.2 24.2 19.9 12.5 4.1 0.2 

Cambodia DHS-V 2010-11 Deaths 7.5 7.7 21.9 18.8 10.9 27.8 5.5 

 DHS-V Births 8.5 33.6 29.5 15.9 9.3 2.9 0.3 

Indonesia DHS-III 1994 Deaths 15.1 20.9 26.5 10.9 18.3 7.5 0.8 

DHS-III Births 11.5 30.6 29.0 18.3 8.3 2.1 0.2 

Indonesia DHS-III 1997 Deaths 4.5 6.4 18.8 33.6 14.1 21.4 1.3 

DHS-III Births 10.8 28.7 29.1 20.1 8.5 2.4 0.3 

Indonesia DHS-IV 2002-03 Deaths 4.7 10.8 23.7 16.8 19.4 14.3 10.3 

 DHS-IV Births 9.2 27.4 29.9 20.5 10.5 2.2 0.3 

Indonesia DHS-V 2007 Deaths 7.9 9.9 34.3 22.5 11.3 10.7 3.5 

 DHS-V Births 7.7 25.6 28.2 23.5 11.6 2.9 0.5 

Indonesia DHS-VI 2012 Deaths 4.6 12.3 21.6 21.4 18.3 15.8 6.1 

 DHS-VI Births 6.4 23.8 29.5 23.8 13.0 3.1 0.4 

Nepal DHS-III 1996 Deaths 19.6 22.6 26.8 12.7 15.2 1.0 2.2 

DHS-III Births 16.1 34.3 25.9 14.8 6.9 1.6 0.3 

Nepal DHS-V 2006 Deaths 20.4 15.7 12.9 29.2 11.8 9.9 0.0 

 DHS-V Births 17.8 39.0 23.2 12.7 5.7 1.6 0.1 

Philippines DHS-II 1993 Deaths 1.9 25.9 26.1 16.6 15.6 5.2 8.6 

 DHS-II Births 6.5 27.9 29.9 21.0 11.0 3.3 0.3 

Philippines DHS-III 1998 Deaths 1.1 11.9 26.6 22.7 27.4 10.4 0.0 

DHS-III Births 6.4 26.4 30.3 21.8 11.5 3.3 0.3 

Timor-Leste DHS-VI 2009-10 Deaths 6.4 18.7 20.4 26.5 10.4 12.5 5.1 

 DHS-VI Births 6.9 27.1 26.2 20.2 13.5 5.0 1.2 

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 Deaths 6.4 18.9 16.6 22.4 18.7 13.6 3.4 

DHS-III Births 11.4 29.6 26.4 18.7 10.4 3.1 0.4 

Bolivia DHS-IV 2003-04 Deaths 11.4 10.7 30.3 13.7 19.0 9.1 5.8 

 DHS-IV Births 13.2 29.1 25.1 17.8 10.8 3.5 0.6 

Bolivia DHS-V 2008 Deaths 10.6 10.6 22.3 11.0 29.7 9.1 6.7 

 DHS-V Births 13.3 28.4 25.7 18.4 10.4 3.3 0.4 

Brazil DHS-III 1996 Deaths 13.2 18.4 26.2 25.2 9.0 1.9 6.0 

DHS-III Births 14.5 32.0 27.4 16.4 7.5 2.0 0.2 

Dominican Republic DHS-IV 2002 Deaths 8.2 9.9 48.4 29.6 2.5 1.3 0.0 

 DHS-IV Births 17.6 34.0 26.7 14.9 5.8 0.9 0.1 

Dominican Republic DHS-V 2007 Deaths 16.8 11.6 22.3 30.2 12.9 5.1 1.1 

 DHS-V Births 16.1 31.0 28.4 15.7 7.3 1.4 0.1 

Guatemala DHS-III 1995 Deaths 16.5 30.1 17.5 13.5 14.8 4.2 3.4 

DHS-III Births 14.7 30.3 24.9 17.4 9.6 2.8 0.3 

(Continued...)
109 

Table 4.7 – Continued

 Age 

Country 

DHS 

survey 

round 

Year of 

survey 

Maternal

deaths/

births 15-19 20-24 25-29 30-34 35-39 40-44 45-49

Latin America and 

Caribbean 

Haiti DHS-IV 2000 Deaths 2.9 16.3 32.5 22.2 15.5 7.7 2.8 

 DHS-IV Births 9.8 25.1 25.0 22.8 12.5 4.3 0.5 

Haiti DHS-V 2005-06 Deaths 2.1 19.2 16.7 25.5 22.9 12.2 1.3 

 DHS-V Births 11.2 26.3 25.3 20.4 12.1 4.2 0.5 

Peru DHS-II 1991-92 Deaths 17.6 27.5 21.7 20.6 0.0 12.5 0.0 

 DHS-II Births 11.1 30.3 27.5 18.5 9.2 2.8 0.5 

Peru DHS-III 1996 Deaths 17.4 20.5 13.4 13.6 17.9 13.5 3.6 

DHS-III Births 11.5 30.0 25.6 18.9 10.6 3.2 0.3 

Peru DHS-IV 2000 Deaths 20.1 20.8 13.4 11.2 21.2 12.7 0.6 

 DHS-IV Births 11.2 28.2 26.0 20.0 11.1 3.2 0.4 

Peru DHS-V 2003-08 Deaths 12.3 13.6 17.8 26.9 13.2 12.3 4.0 

 DHS-V Births 10.7 26.5 26.3 20.1 12.4 3.6 0.4 

Peru DHS-VI 2011 Deaths 15.9 7.4 19.7 19.6 24.7 12.6 0.0 

 DHS-VI Births 10.2 25.2 25.8 21.7 12.8 3.9 0.4 
110 

Figure 4.9 Percentage distribution of maternal deaths and births (expected births among sisters) 

by age, Demographic and Health Surveys 1990-2013 

(Continued...)

 

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49

Benin, 1996 Benin, 2006 Bolivia, 1993-94 Bolivia, 2003-04

Bolivia, 2008 Brazil, 1996 Burkina Faso, 1998-99 Burkina Faso, 2010

Burundi, 2010-11 Cambodia, 2000 Cambodia, 2005-06 Cambodia, 2010-11

Cameroon, 1998 Cameroon, 2004 Cameroon, 2011 Central African Republic, 1994-95

Chad, 1996-97 Chad, 2004 Congo (Brazzaville), 2005 Congo (Brazzaville), 2011-12

Congo Democratic Republic, 2007 Cote d'Ivoire, 1994 Cote d'Ivoire, 2005 Cote d'Ivoire, 2011-12

Deaths Births*

Percent

Age

*Expected births among sisters
111 

Figure 4.9 – Continued

(Continued...)

 

0

50

0

50

0

50

0

50

0

50

0

50

15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49

Dominican Republic, 2002 Dominican Republic, 2007 Ethiopia, 2000 Ethiopia, 2005

Ethiopia, 2011 Gabon, 2000-01 Gabon, 2012 Guatemala, 1995

Guinea, 1999 Guinea, 2005 Guinea, 2012 Haiti, 2000

Haiti, 2005-06 Indonesia, 1994 Indonesia, 1997 Indonesia, 2002-03

Indonesia, 2007 Indonesia, 2012 Jordan, 1997 Kenya, 1998

Kenya, 2003 Kenya, 2008-09 Lesotho, 2004-05 Lesotho, 2009-10

Deaths Births*

Percent

Age

*Expected births among sisters
112 

Figure 4.9 – Continued

(Continued...)

 

0

50

0

50

0

50

0

50

0

50

0

50

15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49

Niger, 2012 Nigeria, 1999 Nigeria, 2008 Peru, 1991-92

Peru, 1996 Peru, 2000 Peru, 2003-08 Peru, 2011

Philippines, 1993 Philippines, 1998 Rwanda, 2000 Rwanda, 2005

Rwanda, 2010-11 Sao Tome and Principe, 2008-09 Senegal, 1992-93 Senegal, 2005

Senegal, 2010-11 Sierra Leone, 2008 South Africa, 1998 Swaziland, 2006-07

Tanzania, 1996 Tanzania, 2004-05 Tanzania, 2009-10 Timor-Leste, 2009-10

Deaths Births*

Percent

Age

*Expected births among sisters
113 

Figure 4.9 – Continued

4.4. Completeness of Adult Death Reporting in Sibling History Module 

Maternal deaths are a subs et of all fe male deaths. Underreporting of adult female deaths may thus bias 

and underestimate maternal mortality. Reniers, Masquelier, and Gerland (2011) show that adult mortality 

estimates from sibling survival data are generally lower than the UN estimates. 

We applied the Brass Growth Balance Method (Brass 1975), which is used for assessing completeness of 

death reporting in census data, to ass ess the extent of underestimation of adult female deaths in DHS 

sibling survival data (Figure 4.10). The Afghanistan Mortality Survey 2010 also applied Brass Growth 

Balance Method for assessing underreporting of adult deaths from sibling survival history data. We also 

compared the results of female deaths to reporte d male deaths to exa mine whether there was any 

systematic underreporting for female population. The utilit y or suitability of the method for use with 

truncated mortality survey data—e.g., young respondents may not have siblings over 50 years of age—is 

not well known. Moreover, instead of fitting the best-fitted line for each survey data set, we applied the 

fitted line at two pre-determined age values. The re sults should be interpreted with caution, and the 

analysis may require further exploration. The r esults suggest the possibilit y of underreport ing. Some 

results are implausible but are shown here for the sake of completeness. 

 

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49 15-19

20-24

25-29

30-34

35-39

40-44

45-49

Togo, 1998 Uganda, 1995 Uganda, 2000-01 Uganda, 2006

Uganda, 2011 Zambia, 1996-97 Zambia, 2001-02 Zambia, 2007

Zimbabwe, 1994 Zimbabwe, 1999 Zimbabwe, 2005-06 Zimbabwe, 2010-11

Deaths Births*

Percent

Age

*Expected births among sisters
114 

Figure 4.10 Death reporting completeness diagnostic plots using the Brass Growth Balance 

Method, Demographic and Heath Surveys 1990-2013 

(Continued...) 

 

Slope: 2.060

C: 0.485

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 1.170 C: 0.855 0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Female

Benin

1996

Slope: 1.062

C: 0.942 0

.02

.04

.06

.08

.1

.12

N(X)/N(X+)

0 .02 .04 .06 .08 .1 .12 D(X+)/N(X+)

Male

Slope: 2.811 C: 0.356

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Benin

2006

Slope: 1.734

C: 0.577

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 3.233

C: 0.309

0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Bolivia

1993-94

Slope: 3.521

C: 0.284

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 2.055 C: 0.487

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Bolivia

2003-04

Slope: 3.606

C: 0.277

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 3.171

C: 0.315

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Bolivia

2008

Slope: 2.146

C: 0.466

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 3.046

C: 0.328

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Brazil

1996

Slope: 1.201

C: 0.832 0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 2.608

C: 0.383

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Burkina Faso

1998-99

Slope: 1.566

C: 0.638

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 2.422 C: 0.413

0

.02

.04

.06

.08

.1

.12

N(X)/N(X+)

0 .02 .04 .06 .08 .1 .12 D(X+)/N(X+)

Female

Burkina Faso

2003

Slope: 2.714

C: 0.369

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 5.799

C: 0.172 0

.03

.06

.09

.12

N(X)/N(X+)

0 .03 .06 .09 .12 D(X+)/N(X+)

Female

Burkina Faso

2010

Slope: 1.295

C: 0.772

0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Male

Slope: 1.758

C: 0.569 0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Female

Burundi

2010-11
115 

Figure 4.10 – Continued

(Continued...)

 

Slope: 1.548

C: 0.646 0

.03

.06

.09

.12

.15

N(X)/N(X+)

0 .03 .06 .09 .12 .15 D(X+)/N(X+)

Male

Slope: 5.134 C: 0.195

0

.02

.04

.06

.08

.1

.12

N(X)/N(X+)

0 .02 .04 .06 .08 .1 .12 D(X+)/N(X+)

Female

Cambodia

2000

Slope: 1.921

C: 0.521

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 3.987

C: 0.251

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Cambodia

2005-06

Slope: 2.374

C: 0.421

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 3.279

C: 0.305

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Cambodia

2010-11

Slope: 0.787

C: 1.270 0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 1.643

0 C: 0.609

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Cameroon

1998

Slope: 1.969

C: 0.508

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 5.517 C: 0.181

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Cameroon

2004

Slope: 0.424 C: 2.359 0

.08

.16

.24

.32

.4

N(X)/N(X+)

0 .08 .16 .24 .32 .4 D(X+)/N(X+)

Male

Slope: 0.806

C: 1.241 0

.06

.12

.18

.24

.3

N(X)/N(X+)

0 .06 .12 .18 .24 .3 D(X+)/N(X+)

Female

Cameroon

2011

Slope: 2.541 C: 0.394

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 4.043

C: 0.247

0

.02

.04

.06

.08

.1

.12

N(X)/N(X+)

0 .02 .04 .06 .08 .1 .12 D(X+)/N(X+)

Female

Central African Republic

1994-95

Slope: 12.071 C: 0.083

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 4.426

C: 0.226

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Chad

1996-97

Slope: 0.503

C: 1.989 0

.94

1.88

2.82

3.76

4.7

N(X)/N(X+)

0 .94 1.882.823.76 4.7 D(X+)/N(X+)

Male

Slope: 0.640

C: 1.563 0

.3

.6

.9

1.2

1.5

N(X)/N(X+)

0 .3 .6 .9 1.2 1.5 D(X+)/N(X+)

Female

Chad

2004

Slope: 1.547

C: 0.647

0

.03

.06

.09

.12

.15

.18

N(X)/N(X+)

0 .03 .06 .09 .12 .15 .18 D(X+)/N(X+)

Male

Slope: 6.855

C: 0.146

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Congo (Brazzaville)

2005
116 

Figure 4.10 – Continued

(Continued...)

 

Slope: 1.590

C: 0.629

0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Male

Slope: 6.251 0 C: 0.160

.03

.06

.09

.12

N(X)/N(X+)

0 .03 .06 .09 .12 D(X+)/N(X+)

Female

Congo (Brazzaville)

2011-12

Slope: 2.941

C: 0.340

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 2.204 C: 0.454 0

.03

.06

.09

.12

.15

N(X)/N(X+)

0 .03 .06 .09 .12 .15 D(X+)/N(X+)

Female

Congo Democratic Republic

2007

Slope: 1.713

C: 0.584

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 3.089

C: 0.324

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Cote d'Ivoire

1994

Slope: 0.229

C: 4.366 0

.1

.2

.3

.4

.5

N(X)/N(X+)

0 .1 .2 .3 .4 .5 D(X+)/N(X+)

Male

Slope: 0.414

C: 2.415 0

.05

.1

.15

.2

.25

N(X)/N(X+)

0 .05 .1 .15 .2 .25 D(X+)/N(X+)

Female

Cote d'Ivoire

2005

Slope: 0.531

C: 1.884

0

.03

.06

.09

.12

.15

.18

N(X)/N(X+)

0 .03 .06 .09 .12 .15 .18 D(X+)/N(X+)

Male

Slope: 2.404

C: 0.416 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Cote d'Ivoire

2011-12

Slope: 2.473

C: 0.404

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 4.296

C: 0.233 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Dominican Republic

2002

Slope: 3.681 C: 0.272

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 3.269 C: 0.306

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Dominican Republic

2007

Slope: 1.478 C: 0.676

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 1.698

C: 0.589

0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Ethiopia

2000

Slope: 2.119

C: 0.472 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 8.617

C: 0.116 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Ethiopia

2005

Slope: 1.914

C: 0.523 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 2.591 C: 0.386

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Ethiopia

2011
117 

Figure 4.10 – Continued

(Continued...)

 

Slope: 1.525

C: 0.656 0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Male

Slope: 2.773

C: 0.361

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Gabon

2000-01

Slope: 0.211

C: 4.741 0

.16

.32

.48

.64

.8

N(X)/N(X+)

0 .16 .32 .48 .64 .8 D(X+)/N(X+)

Male

Slope: 0.249

C: 4.019 0

.28

.56

.84

1.12

1.4

N(X)/N(X+)

0 .28 .56 .84 1.12 1.4 D(X+)/N(X+)

Female

Gabon

2012

Slope: 1.948

C: 0.513 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 2.396

C: 0.417 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Guatemala

1995

Slope: 3.180

C: 0.314 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 1.908 C: 0.524

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Guinea

1999

Slope: 0.469

C: 2.132 0

.09

.18

.27

.36

.45

N(X)/N(X+)

0 .09 .18 .27 .36 .45 D(X+)/N(X+)

Male

Slope: 0.568

C: 1.760 0

.08

.16

.24

.32

.4

N(X)/N(X+)

0 .08 .16 .24 .32 .4 D(X+)/N(X+)

Female

Guinea

2005

Slope: 2.134

C: 0.469 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 4.594

C: 0.218 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Guinea

2012

Slope: 1.163 C: 0.860

0

.02

.04

.06

.08

.1

.12

N(X)/N(X+)

0 .02 .04 .06 .08 .1 .12 D(X+)/N(X+)

Male

Slope: 1.089 C: 0.918

0 .01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Haiti

2000

Slope: 2.781

C: 0.360

0

.04

.08

.12

.16

.2

N(X)/N(X+)

0 .04 .08 .12 .16 .2 D(X+)/N(X+)

Male

Slope: 2.833

C: 0.353

0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Haiti

2005-06

Slope: 0.998 C: 1.002

0

.02

.04

.06

.08

.1

.12

N(X)/N(X+)

0 .02 .04 .06 .08 .1 .12 D(X+)/N(X+)

Male

Slope: 2.635

C: 0.380 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Indonesia

1994

Slope: 1.138

C: 0.879 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 3.002

C: 0.333 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Indonesia

1997
118 

Figure 4.10 – Continued

(Continued...)

 

Slope: 1.174

C: 0.852 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 1.416 C: 0.706

0 .01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Indonesia

2002-03

Slope: 1.530 C: 0.654

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 2.114

C: 0.473 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Indonesia

2007

Slope: 1.504 C: 0.665

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 1.852

C: 0.540

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Indonesia

2012

Slope: 1.704 C: 0.587

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 4.474

C: 0.224

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Jordan

1997

Slope: 1.714

C: 0.583

0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Male

Slope: 3.853

C: 0.260 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Kenya

1998

Slope: 1.687

C: 0.593

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 2.098

C: 0.477

0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Kenya

2003

Slope: 2.111

C: 0.474 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: -5.605

C: -0.178 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Kenya

2008-09

Slope: 1.135

0 C: 0.881 .01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 1.653

C: 0.605 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Lesotho

2004-05

Slope:0.818

0 C: 1.222 .01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 2.036

C: 0.491 0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Lesotho

2009-10

Slope: 2.346

C: 0.426 0

.03

.06

.09

.12

N(X)/N(X+)

0 .03 .06 .09 .12 D(X+)/N(X+)

Male

Slope: 13.988

C: 0.071 0 .01

.02

.03

.04 .05

.06 .07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Liberia

2006-07
119 

Figure 4.10 – Continued

(Continued...)

 

Slope: 0.695

C: 1.440

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 0.793

C: 1.260

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Madagascar

1997

Slope: 0.601

C: 1.663 0

.03

.06

.09

.12

.15

N(X)/N(X+)

0 .03 .06 .09 .12 .15 D(X+)/N(X+)

Male

Slope: 3.486

C: 0.287 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Madagascar

2003-04

Slope: 1.570

C: 0.637 0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Male

Slope: 5.289

C: 0.189

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Madagascar

2008-09

Slope: 1.145

C: 0.873

0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Male

Slope: 0.895

C: 1.118 0

.03

.06

.09

.12

.15

N(X)/N(X+)

0 .03 .06 .09 .12 .15 D(X+)/N(X+)

Female

Malawi

1992

Slope: 2.499

C: 0.400

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 2.168

C: 0.461 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Malawi

2000

Slope: 1.076

C: 0.930

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 3.290 C: 0.304 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Malawi

2004-05

Slope: 1.221

C: 0.819 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 2.445 C: 0.409

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Malawi

2010

Slope: 2.324

C: 0.430

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 1.317 C: 0.759 0 .01

.02 .03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Mali

1995-96

Slope: 1.432

C: 0.698 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 1.256

C: 0.796 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Mali

2001

Slope: 1.079

C: 0.927 0

.04

.08

.12

.16

.2

N(X)/N(X+)

0 .04 .08 .12 .16 .2 D(X+)/N(X+)

Male

Slope: 1.027 C: 0.974 0

.05

.1

.15

.2

.25

N(X)/N(X+)

0 .05 .1 .15 .2 .25 D(X+)/N(X+)

Female

Mali

2006
120 

Figure 4.10 – Continued

(Continued...)

 

Slope: 7.562

C: 0.132

0

.01

.02

.03

.04

N(X)/N(X+)

0 .01 .02 .03 .04 D(X+)/N(X+)

Male

Slope: 1.987

C: 0.503

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Mali

2012-13

Slope: 2.681

C: 0.373

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 2.803

C: 0.357

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Morocco

1992

Slope: 2.608

C: 0.383

0 .01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 6.102

C: 0.164 0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Female

Morocco

2003-04

Slope: 4.058

C: 0.246

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 1.255

C: 0.797

0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Mozambique

1997

Slope: 1.243

C: 0.805 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 1.342

C: 0.745 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Mozambique

2003-04

Slope: 2.346 C: 0.426

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 3.875 C: 0.258

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Mozambique

2011

Slope: 1.800

C: 0.555 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: -8.561 C: -0.117

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Namibia

1992

Slope: 1.213

C: 0.825

0

.01

.02

.03

.04

N(X)/N(X+)

0 .01 .02 .03 .04 D(X+)/N(X+)

Male

Slope: 2.220 C: 0.450

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Namibia

2000

Slope: 1.090

C: 0.917 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 3.521

C: 0.284 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Namibia

2006-07

Slope: 1.117

C: 0.895

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 0.988

C: 1.012

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Nepal

1996
121 

Figure 4.10 – Continued

(Continued...)

 

Slope: 2.664 C: 0.375 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 3.446 C: 0.290

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Nepal

2006

Slope: 3.622

C: 0.276 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 5.275

C: 0.190 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Niger

1992

Slope: 1.020

0 C: 0.980 .05

.1

.15

.2

.25

N(X)/N(X+)

0 .05 .1 .15 .2 .25 D(X+)/N(X+)

Male

Slope: 0.832 C: 1.202 0

.17

.34

.51

.68

.85

N(X)/N(X+)

0 .17 .34 .51 .68 .85 D(X+)/N(X+)

Female

Niger

2006

Slope: 10.962

C: 0.091 0

.03

.06

.09

.12

.15

N(X)/N(X+)

0 .03 .06 .09 .12 .15 D(X+)/N(X+)

Male

Slope: 2.053

0 C: 0.487

.03

.06

.09

.12

N(X)/N(X+)

0 .03 .06 .09 .12 D(X+)/N(X+)

Female

Niger

2012

Slope: 3.314

C: 0.302 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 2.378

C: 0.421 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Nigeria

1999

Slope: 2.214

C: 0.452

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 2.540

C: 0.394

0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Nigeria

2008

Slope: 1.935 C: 0.517

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 2.145

C: 0.466 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Peru

1991-92

Slope: 2.635

C: 0.379 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 3.165 C: 0.316

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Peru

1996

Slope: 2.306 C: 0.434

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 3.803

C: 0.263

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Peru

2000

Slope: 3.128

C: 0.320 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 13.466

C: 0.074 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Peru

2003-08
122 

Figure 4.10 – Continued

(Continued...)

 

Slope: 5.459 C: 0.183

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 4.693

C: 0.213 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Peru

2011

Slope: 1.603

C: 0.624

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 4.793

C: 0.209

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Philippines

1993

Slope: 2.652 C: 0.377

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 4.219

C: 0.237

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Philippines

1998

Slope: 1.885 C: 0.530

0

.02

.04

.06

.08

.1

.12

N(X)/N(X+)

0 .02 .04 .06 .08 .1 .12 D(X+)/N(X+)

Male

Slope: 3.884

C: 0.257

0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Female

Rwanda

2000

Slope: 0.049 C: 20.248 0

.88

1.76

2.64

3.52

4.4

N(X)/N(X+)

0 .88 1.762.643.52 4.4 D(X+)/N(X+)

Male

Slope: 0.064 C: 15.631 0

.73

1.46

2.19

2.92

3.65

N(X)/N(X+)

0 .73 1.462.192.923.65 D(X+)/N(X+)

Female

Rwanda

2005

Slope: 2.038

C: 0.491

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 3.085

C: 0.324

0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Female

Rwanda

2010-11

Slope: 0.126 C: 7.941 0

.36

.72

1.08

1.44

1.8

N(X)/N(X+)

0 .36 .72 1.081.44 1.8 D(X+)/N(X+)

Male

Slope: 0.095 C: 10.564 0

1.38

2.76

4.14

5.52

6.9

N(X)/N(X+)

0 1.382.764.145.52 6.9 D(X+)/N(X+)

Female

Sao Tome and Principe

2008-09

Slope: 2.312 C: 0.433 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 3.191

C: 0.313 0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Senegal

1992-93

Slope: 3.197

C: 0.313 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 3.473

C: 0.288 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Senegal

2005

Slope: 2.190

C: 0.457

N(X)/N(X+)

D(X+)/N(X+)

Male

Slope: 8.127

C: 0.123

N(X)/N(X+)

D(X+)/N(X+)

Female

Senegal

2010-11
123 

Figure 4.10 – Continued

(Continued...)

 

Slope: 0.198 C: 5.045 0

.31

.62

.93

1.24

1.55

N(X)/N(X+)

0 .31 .62 .93 1.241.55 D(X+)/N(X+)

Male

Slope: 0.189

C: 5.287 0

.36

.72

1.08

1.44

1.8

N(X)/N(X+)

0 .36 .72 1.081.44 1.8 D(X+)/N(X+)

Female

Sierra Leone

2008

Slope: 1.116

0 C: 0.896

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 2.614 C: 0.383 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

South Africa

1998

Slope: 1.105

C: 0.905 0 .01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 2.899

C: 0.345 0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Swaziland

2006-07

Slope: 1.621

C: 0.617 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 6.853

C: 0.146

0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Tanzania

1996

Slope: 1.170

C: 0.855 0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Male

Slope: 4.300

C: 0.233 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Tanzania

2004-05

Slope: 2.637

C: 0.379 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 6.299

C: 0.159 0

.01

.02

.03

.04

N(X)/N(X+)

0 .01 .02 .03 .04 D(X+)/N(X+)

Female

Tanzania

2009-10

Slope: 6.406 C: 0.156

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 10.207

C: 0.098 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Timor-Leste

2009-10

Slope: 2.239

C: 0.447

0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 3.298 C: 0.303

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Togo

1998

Slope: 2.391

C: 0.418

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 2.993 C: 0.334

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Uganda

1995

Slope: 1.948

C: 0.513

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Male

Slope: 3.123

C: 0.320 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Uganda

2000-01
124 

Figure 4.10 – Continued

Slope: 1.299

C: 0.770

0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Male

Slope: 3.272

C: 0.306

0

.01

.02

.03

.04

.05

.06

.07

N(X)/N(X+)

0 .01.02.03.04.05.06.07 D(X+)/N(X+)

Female

Uganda

2006

Slope: 1.680

C: 0.595 0

.01

.02

.03

.04

N(X)/N(X+)

0 .01 .02 .03 .04 D(X+)/N(X+)

Male

Slope: 2.524 C: 0.396

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Uganda

2011

Slope: 1.438

C: 0.695

0

.04

.08

.12

.16

.2

N(X)/N(X+)

0 .04 .08 .12 .16 .2 D(X+)/N(X+)

Male

Slope: 8.514

C: 0.117 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Zambia

1996-97

Slope: 1.455

C: 0.688 0

.02

.04

.06

.08

.1

N(X)/N(X+)

0 .02 .04 .06 .08 .1 D(X+)/N(X+)

Male

Slope: 2.008

C: 0.498 0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Female

Zambia

2001-02

Slope: 1.043

C: 0.958 0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Male

Slope: 3.984

C: 0.251 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Zambia

2007

Slope: 1.839

C: 0.544 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: 1.686 C: 0.593

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Zimbabwe

1994

Slope: 2.087

0 C: 0.479

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Male

Slope: -3.821 C: -0.262 0

.02

.04

.06

.08

N(X)/N(X+)

0 .02 .04 .06 .08 D(X+)/N(X+)

Female

Zimbabwe

1999

Slope: 1.089

C: 0.919

0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 1.937

C: 0.516

0

.01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Zimbabwe

2005-06

Slope: 1.059

C: 0.944

0

.01

.02

.03

.04

.05

N(X)/N(X+)

0 .01 .02 .03 .04 .05 D(X+)/N(X+)

Male

Slope: 1.825

0 C: 0.548 .01

.02

.03

.04

.05

.06

N(X)/N(X+)

0 .01 .02 .03 .04 .05 .06 D(X+)/N(X+)

Female

Zimbabwe

2010-11
125 

5. Conclusions 

The Demographic and Health Surveys (DHS) Program uses the sisterhood method for maternal mortality 

estimations. The li mitations of the sisterhood m ethod are discussed extensiv ely in t he demographic 

literature. The most notable li mitation is that the method is not suitable for t racking progress in safe 

motherhood over a short period of time. Because the place of death of sibling sisters is not known (i.e., not 

asked) the method is also not suitable for assessing geogr aphical variations or for helping t o target highrisk regions. Nevertheless, the DHS surveys remain the major source of empirical data on maternal 

mortality in developing countries. Utilizing modeling techniques, the United Nations Maternal Mortalit y 

Estimation Inter-agency Group (MMEIG) (consisting of WHO/UNICEF/UNFPA, and the World Bank ) 

and IHME have utilized the DHS sisterhood data for tracking global maternal mortality trends. 

Recent studies have consistently indicated that m aternal mortality has declined substantially worldwide 

since 1990. The reduction is largel y due to declines in maternal mortality in developing countries. This 

achievement became known after mat ernal mortality estimates became widely available as the result of 

many rounds of DHS surveys, which have been used in tracking mortality. 

In addition to sampling errors, survey data are a ffected also by non-sampling errors, such as reporting 

errors, missing responses, and biased responses. Data from DHS sibling survival history are not exceptions. 

Our in-depth analyses suggest that the overall quality of sibling history data is similar to the quality of data 

from individual respondents (women age 15-45) i n DHS survey s in terms of age-reporting (e.g., ageheaping, missing in reported age and date of birth, and age-displacement). Reporting events a nd placing 

the events in calendar time remain major challenges by the respondents based on memory recall. 

While the overall value of DHS maternal mortality estimates is undeniable, our examination of the quality 

of the DHS maternal mortality estimation suggests that there is a major problem with the current sibship 

survival method that has resulted in underestimation bias in D HS maternal mortality estimation. The 

problem is the high non-response rates associated with both the calendar timing reference for deaths and 

the reporting of pregnancy status at the time of death. 

In current practice, deaths that are reported to have occurred during pregnancy, delivery, or the postpartum 

period (2 months in recent DHS surveys; 6 weeks in some earlier DHS surveys) are considered maternal 

deaths by DHS. Deaths with unknown pregnancy status are classified as non-maternal. T his assumption 

introduces significant bias and underestimates maternal mortality in countries with a high non-response 

rate for the pregnanc y status variable. The DHS an alytical manual, titled “ Guide to DHS Statistics” 

(Rutstein and Rojas 2006), suggests to address the missing responses on maternal status at the time of death 

by allocating those proportionally to the maternal death distribution in the complete case reporting. The 

specific recommendation is as follows: 

“Siblings whose maternal status at the ti me of death is unknown to the respondent or is 

missing in the data set are allocated to maternal deaths in the proportion they are to deaths 

of any maternal status. For each age group of siblings, the num ber of deaths of known 

maternal status is divided by the number of deaths of any status to get the proportion of 

maternal deaths. This proportion is then multiplied by the number of deaths of unknow n 

status to calculate the number of deaths to add to the known maternal deaths to get the total 

number of maternal deaths in each age group.” 

The maternal mortality estimates by Stanton et al. (1997) are adjusted b ased on this recommended 

procedure. However, the procedure was not fully implemented by DHS. The DHS country reports, which 

are the main source of maternal mortality data for MMEIG, IHME, and country officials, are based on no 

adjustment for missing values in maternal status during death. DHS surveys do not routinely collect data 
126 

on marital status of the siblings. In many countries, out-of-wedlock pregnancies ar e not s ocially and 

culturally acceptable. Although these countries experien ce abortion-related deaths, it was o f significant 

uncertainty that all sist ers with missing responses in such settings were likely to experience a maternal 

death rate similar to the sisters with com plete responses on maternal status at the tim e of death. While 

debating the concerns, the DHS survey s moved away from the recommendation of correcting m aternal 

death counts for missing values. 

In this report, we have shown the implications of missing responses on maternal status during death for 

maternal mortality indicators, such as MMR. We suggest that some simple statistical adjustments can be 

made that will substantially reduce the underestimation bias. 

The sibling survival module collects information on all siblings, including those who died s everal years 

ago. Many respondents have difficulty remembering the age at death and the calendar timing of death for 

siblings who died in the distant past. In addition, focusing on these questions can put undue pressure on 

respondents to recall sensitive events in the distant past and can be time consuming for the interviewer. It 

is well recognized that the reporting of recent deaths is substantially more reliable than reporting of deaths 

that occurred in the distant past, which is the reason D HS limits analysis of mortality data to the last fiv e 

to seven years. This is als o done recognizing that the age-structur e of respondents and hence the agestructure and parity of sisters may vary between recent and distant periods. Considering the high level of 

non-response for death information—especially regarding deaths that occurre d many years ago—and 

considering that the information is never used by DHS for any analysis, we think it would be beneficial to 

examine the impact of limiting the history recall period with a truncated sibling history module. As an 

example, instead of listin g all siblings in order of birth, list the surviving siblings first and t hen list the 

siblings that died in the last seven y ears. A similar approach was used in the direct household maternal 

mortality estimation module in the Household Questionnaire for the Bangladesh Maternal Health Services 

and Maternal Mortality Survey (NIPORT et al. 2003); a separate table was included for listing the 

individual household members who died during the last three years. An illustration is shown in Appendix 

1. Despite the concerns of displacement of timing of deaths in such a truncated survival table, the maternal 

mortality ratio (MMR) estimates in Bangladesh, Afgha nistan, and Ghana showed overesti mation, rather 

than underestimation, compared with sibling hist ory-based estimates for the same period (Bangladesh 

Maternal Mortality and Health Care Survey in 2001 and 2010, Afghanistan Mo rtality Survey 2010, and 

Ghana Maternal Health Survey 2007). 

However, if age or calendar displacement is a real or anticipated concern, the data collection observation 

period in the truncated sibling history module may be extended by one year to siblings who died within 8 

years, instead of seven years, and the information from the last year may discarded during data analysis. 

Recommendations 

We provide the following sets of recommendations to improve the quality of the DHS sibling survival data. 

1. Develop a standard protocol for addre ssing missing responses in the sibl ing survival history 

module. Considering the high non-response rate in age and date of birth, DHS routinely performs 

imputation in age- and date-related variables. All the publicly available DHS data are imputed. A 

similar standardizing approach may be undertaken for missing values in pregn ancy status at th e 

time of death. 

2. The current method of maternal mortality estimation considers all deaths with unknown pregnancy 

status at the time of death as non-maternal. The MMR estimates are biased under this assumption. 

We suggest correcting the underestimation with a suitable statistical method. Multiple imputations 

may be the best way to take into account uncertainty in the missingness. However, replication of 

the results will be a chall enge for external data users. Moreover, this may not be practical for 
127 

distributing data for public use with multiple imputation. Weighting is a simple method but may 

not be efficient (proportion of maternal deaths is considered constant in both missing and nonmissing groups, which m ay not be true). In addressing the problem, DHS may need to strike a 

balance between efficiency and convenience. 

3. Although information is c ollected on all sib lings, DHS does not utilize i nformation from the 

siblings who died in the distant past. Co nsidering the high level of non-response associ ated with 

the collection of death info rmation, especially regarding deaths that occurred a long tim e ago, it 

may be useful for DHS to test a modified sibling survival history tool that collects information on 

deaths only for the recent period. Truncated histories, however, have been shown to be more subject 

to biases due to omissions than full histories. Nevertheless, the experience of household reporting 

of recent deaths in the “direct household maternal mortality module” in Bangladesh, Afghanistan, 

Ghana, and other countri es suggests that it is pos sible to coll ect truncated survival his tory. 

Respondents experience considerable challenge in placing deaths in reference to calendar tim ing. 

It would be useful to incorporate country-specific milestone events into the calendar to provide 

time references for the respondents. T hese milestone events can also be i ncorporated into the 

training manual and emphasized during interviewer tr aining. It is i mportant that the interviewer 

training specifically addresses the challenges asso ciated with collecting de ath information. 

Innovative attempts should be made to reduce missing responses. 

4. Safe motherhood programs need to identif y high-risk population groups and target geographical 

regions with high maternal mortality levels. Unfortunately, the current method used by DHS to 

estimate maternal mortality (sisterhood method) is suitable for assessing maternal mortality at the 

national level only. As a result, DHS estimates have little utility for local health administrators who 

need data at the regio nal level. We suggest im proving the sibl ing history module to capture 

subnational variability in m aternal deaths. With the advancements in sm all area estimation 

methods, it may not be difficult to capture subnational maternal deaths at the regional level (Ahmed 

and Hill 2011). 

 

129 

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133 

Appendix 

Table A.1 DHS country code list for the selected countries included in the report 

Country DHS code

Benin BJ

Bolivia BO

Brazil BR

Burkina Faso BF

Burundi BU

Cambodia KH

Cameroon CM

Central African Republic CF

Chad TD

Congo (Brazzaville) CG

Congo Democratic Republic CD

Cote d’Ivoire CI

Dominican Republic DR

Ethiopia ET

Gabon GA

Guatemala GU

Guinea GN

Haiti HT

Indonesia ID

Jordan JO

Kenya KE

Lesotho LS

Liberia LB

Madagascar MD

Malawi MW

Mali ML

Morocco MA

Mozambique MZ

Namibia NM

Nepal NP

Niger NI

Nigeria NG

Peru PE

Philippines PH

Rwanda RW

Sao Tome and Principe ST

Senegal SN

Sierra Leone SL

South Africa ZA

Swaziland SZ

Tanzania TZ

Timor-Leste TL

Togo TG

Uganda UG

Zambia ZM

Zimbabwe ZW
134 

Table A.2 The distribution of reported timing of death before survey among sisters listed as dead in 

the sibling survival history (unweighted analysis), Demographic and Health Survey 1990-2013 

 

Sisters died in

0-6 years 

Sisters died in

7-13 years 

Country 

DHS 

survey 

round 

Year of 

survey 

No. of 

sisters 

ever died Number Percent Number Percent 

Sub-Saharan 

Benin DHS-III 1996 3,681 380 10.3 520 14.1 

Benin DHS-V 2006 8,244 1,105 13.4 1,142 13.9 

Burkina Faso DHS-III 1998-99 3,340 638 19.1 569 17.0 

Burkina Faso DHS-IV 2003 5,672 1,043 18.4 1,020 18.0 

Burkina Faso DHS-VI 2010 8,714 1,235 14.2 1,538 17.6 

Burundi DHS-VI 2010-11 6,984 748 10.7 1,346 19.3 

Cameroon DHS-III 1998 2,884 447 15.5 415 14.4 

Cameroon DHS-IV 2004 6,529 1,326 20.3 1,021 15.6 

Cameroon DHS-VI 2011 9,065 1,821 20.1 1,744 19.2 

Central African Republic DHS-III 1994-95 2,788 678 24.3 511 18.3 

Chad DHS-III 1996-97 4,411 691 15.7 788 17.9 

Chad DHS-IV 2004 4,017 734 18.3 858 21.4 

Congo (Brazzaville) DHS-V 2005 3,565 841 23.6 811 22.7 

Congo (Brazzaville) DHS-VI 2011-12 5,009 967 19.3 1,068 21.3 

Congo Democratic Republic DHS-V 2007 6,100 1,335 21.9 1,269 20.8 

Cote d’Ivoire DHS-III 1994 3,531 653 18.5 558 15.8 

Cote d’Ivoire DHS-V 2005 2,144 453 21.1 353 16.5 

Cote d’Ivoire DHS-VI 2011-12 5,825 1,042 17.9 1,076 18.5 

Ethiopia DHS-IV 2000 11,203 1,798 16.0 1,944 17.4 

Ethiopia DHS-IV 2005 7,522 1,441 19.2 1,494 19.9 

Ethiopia DHS-VI 2011 10,054 1,340 13.3 1,827 18.2 

Gabon DHS-III 2000-01 2,507 478 19.1 368 14.7 

Gabon DHS-VI 2012 3,314 740 22.3 612 18.5 

Guinea DHS-III 1999 3,634 468 12.9 600 16.5 

Guinea DHS-IV 2005 5,006 786 15.7 844 16.9 

Guinea DHS-VI 2012 4,848 805 16.6 808 16.7 

Kenya DHS-III 1998 2,903 736 25.4 459 15.8 

Kenya DHS-IV 2003 3,530 1,001 28.4 549 15.6 

Kenya DHS-V 2008-09 2,795 819 29.3 617 22.1 

Lesotho DHS-IV 2004-05 3,052 1,092 35.8 369 12.1 

Lesotho DHS-V 2009-10 3,075 1,190 38.7 550 17.9 

Liberia DHS-V 2006-07 1,762 508 28.8 347 19.7 

Madagascar DHS-III 1997 2,753 663 24.1 635 23.1 

Madagascar DHS-IV 2003-04 1,731 467 27.0 360 20.8 

Madagascar DHS-V 2008-09 6,594 1,397 21.2 1,363 20.7 

Malawi DHS-II 1992 4,158 628 15.1 621 14.9 

Malawi DHS-IV 2000 10,602 2,291 21.6 1661 15.7 

Malawi DHS-IV 2004-05 7,133 1,998 28.0 1,244 17.4 

Malawi DHS-V 2010 18,363 3,042 16.6 3,200 17.4 

Mali DHS-III 1995-96 6,667 807 12.1 1,059 15.9 

Mali DHS-IV 2001 7,801 1,200 15.4 1,284 16.5 

Mali DHS-V 2006 9,679 1,293 13.4 1,635 16.9 

(Continued...)
135 

Table A.2 – Continued

 

Sisters died in

0-6 years 

Sisters died in

7-13 years 

Country 

DHS 

survey 

round 

Year of 

survey 

No. of 

sisters 

ever died Number Percent Number Percent 

Sub-Saharan 

Mali DHS-VI 2012-13 1,895 378 19.9 387 20.4 

Mozambique DHS-III 1997 3,385 670 19.8 646 19.1 

Mozambique DHS-IV 2003-04 6,051 1,205 19.9 932 15.4 

Mozambique DHS-VI 2011 4,359 1,036 23.8 890 20.4 

Namibia DHS-II 1992 1,878 384 20.4 338 18.0 

Namibia DHS-IV 2000 2,003 604 30.2 289 14.4 

Namibia DHS-V 2006-07 3,421 1,428 41.7 584 17.1 

Niger DHS-II 1992 4,685 658 14.0 903 19.3 

Niger DHS-V 2006 5,960 941 15.8 1,135 19.0 

Niger DHS-VI 2012 7,885 997 12.6 1,304 16.5 

Nigeria DHS-III 1999 2,260 580 25.7 433 19.2 

Nigeria DHS-V 2008 13,993 3,030 21.7 2,736 19.6 

Rwanda DHS-IV 2000 8,564 3,537 41.3 1,387 16.2 

Rwanda DHS-IV 2005 9,980 1,694 17.0 4,237 42.5 

Rwanda DHS-VI 2010-11 9,785 827 8.5 1,844 18.8 

Sao Tome and Principe DHS-V 2008-09 1,194 288 24.1 362 30.3 

Senegal DHS-II 1992-93 3,752 417 11.1 609 16.2 

Senegal DHS-IV 2005 7,212 983 13.6 1,130 15.7 

Senegal DHS-VI 2010-11 7,874 994 12.6 1,134 14.4 

Sierra Leone DHS-V 2008 2,725 703 25.8 472 17.3 

South Africa DHS-III 1998 2,445 495 20.2 341 13.9 

Swaziland DHS-V 2006-07 1,894 1,001 52.9 298 15.7 

Tanzania DHS-III 1996 3,908 702 18.0 580 14.8 

Tanzania DHS-IV 2004-05 6,205 1,150 18.5 1,011 16.3 

Tanzania DHS-V 2009-10 4,358 763 17.5 794 18.2 

Togo DHS-III 1998 5,091 610 12.0 644 12.6 

Uganda DHS-III 1995 4,327 1,183 27.3 712 16.5 

Uganda DHS-IV 2000-01 4,908 1,170 23.8 987 20.1 

Uganda DHS-V 2006 6,854 1,226 17.9 1,392 20.3 

Uganda DHS-VI 2011 6,188 900 14.5 1,156 18.7 

Zambia DHS-III 1996-97 4,681 1,466 31.3 862 18.4 

Zambia DHS-IV 2001-02 4,751 1,756 37.0 985 20.7 

Zambia DHS-V 2007 3,793 1,371 36.1 942 24.8 

Zimbabwe DHS-III 1994 2,583 475 18.4 370 14.3 

Zimbabwe DHS-IV 1999 2,028 813 40.1 238 11.7 

Zimbabwe DHS-V 2005-06 3,324 1,665 50.1 639 19.2 

Zimbabwe DHS-VI 2010-11 3,082 1,341 43.5 768 24.9 

North Africa 

Jordan DHS-III 1997 2,718 113 4.2 139 5.1 

Morocco DHS-II 1992 5,049 337 6.7 548 10.9 

Morocco DHS-IV 2003-04 8,148 394 4.8 559 6.9 

(Continued...)

 
136 

Table A.2 – Continued

 

Sisters died in

0-6 years 

Sisters died in

7-13 years 

Country 

DHS 

survey 

round 

Year of 

survey 

No. of 

sisters 

ever died Number Percent Number Percent 

Asia 

Cambodia DHS-IV 2000 6,731 918 13.6 1,080 16.0 

Cambodia DHS-V 2005-06 7,958 881 11.1 1,191 15.0 

Cambodia DHS-V 2010-11 6,017 654 10.9 809 13.4 

Indonesia DHS-III 1994 9,607 1,041 10.8 1,024 10.7 

Indonesia DHS-III 1997 7,314 835 11.4 788 10.8 

Indonesia DHS-IV 2002-03 6,523 863 13.2 688 10.5 

Indonesia DHS-V 2007 7,952 1,078 13.6 869 10.9 

Indonesia DHS-VI 2012 11,975 1,521 12.7 1,179 9.8 

Nepal DHS-III 1996 5,643 441 7.8 647 11.5 

Nepal DHS-V 2006 5,427 336 6.2 542 10.0 

Philippines DHS-II 1993 3,472 604 17.4 556 16.0 

Philippines DHS-III 1998 3,701 566 15.3 583 15.8 

Timor-Leste DHS-VI 2009-10 4,896 516 10.5 776 15.8 

Latin America and 

Caribbean 

Bolivia DHS-III 1993-94 3,646 408 11.2 557 15.3 

Bolivia DHS-IV 2003-04 8,111 721 8.9 1,045 12.9 

Bolivia DHS-V 2008 6,547 540 8.2 706 10.8 

Brazil DHS-III 1996 4,929 406 8.2 451 9.1 

Dominican Republic DHS-IV 2002 3,079 438 14.2 358 11.6 

Dominican Republic DHS-V 2007 6,034 865 14.3 667 11.1 

Guatemala DHS-III 1995 5,515 509 9.2 729 13.2 

Haiti DHS-IV 2000 7,170 955 13.3 1,030 14.4 

Haiti DHS-V 2005-06 7,027 897 12.8 1,056 15.0 

Peru DHS-II 1991-92 4,928 687 13.9 806 16.4 

Peru DHS-III 1996 13,209 1,245 9.4 1,603 12.1 

Peru DHS-IV 2000 11,971 902 7.5 1,291 10.8 

Peru DHS-V 2003-08 16,874 975 5.8 1,383 8.2 

Peru DHS-VI 2011 7,925 474 6.0 514 6.5 

 
137 

Figure A.1 Listing table of household members who had died in recent period, BMMS 2001 

 

 
138 

Figure A.2 Maternal death concentration curve, Demographic and Heath Surveys 1990-2013 

(Continued...) 

 

0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1

0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1

Benin, 1996 Benin, 2006 Bolivia, 1993-94 Bolivia, 2003-04 Bolivia, 2008 Brazil, 1996

Burkina Faso, 1998-99Burkina Faso, 2010 Burundi, 2010-11 Cambodia, 2000 Cambodia, 2005-06 Cambodia, 2010-11

Cameroon, 1998 Cameroon, 2004 Cameroon, 2011 Central African Republic, 1994-95 Chad, 1996-97 Chad, 2004

Congo (Brazzaville), 2005 Congo (Brazzaville), 2011-12 Congo Democratic Republic, 2007 Cote d'Ivoire, 1994 Cote d'Ivoire, 2005 Cote d'Ivoire, 2011-12

Dominican Republic, 2002 Dominican Republic, 2007 Ethiopia, 2000 Ethiopia, 2005 Ethiopia, 2011 Gabon, 2000-01

Gabon, 2012 Guatemala, 1995 Guinea, 1999 Guinea, 2005 Guinea, 2012 Haiti, 2000

Cumulative maternal deaths proportion

Cumulative births proportion
139 

Figure A.2 – Continued

(Continued...) 

 

0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1

0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1

Haiti, 2005-06 Indonesia, 1994 Indonesia, 1997 Indonesia, 2002-03 Indonesia, 2007 Indonesia, 2012

Jordan, 1997 Kenya, 1998 Kenya, 2003 Kenya, 2008-09 Lesotho, 2004-05 Lesotho, 2009-10

Liberia, 2006-07 Madagascar, 1997 Madagascar, 2003-04Madagascar, 2008-09 Malawi, 1992 Malawi, 2000

Malawi, 2004-05 Malawi, 2010 Mali, 1995-96 Mali, 2001 Mali, 2006 Mali, 2012-13

Morocco, 1992 Morocco, 2003-04 Mozambique, 1997 Mozambique, 2003-04 Mozambique, 2011 Namibia, 1992

Namibia, 2000 Namibia, 2006-07 Nepal, 1996 Nepal, 2006 Niger, 1992 Niger, 2006

Cumulative maternal deaths proportion

Cumulative births proportion
140 

Figure 4.10 – Continued

0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1

0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1

Niger, 2012 Nigeria, 1999 Nigeria, 2008 Peru, 1991-92 Peru, 1996 Peru, 2000

Peru, 2003-08 Peru, 2011 Philippines, 1993 Philippines, 1998 Rwanda, 2000 Rwanda, 2005

Rwanda, 2010-11 Sao Tome and Principe, 2008-09 Senegal, 1992-93 Senegal, 2005 Senegal, 2010-11 Sierra Leone, 2008

South Africa, 1998 Swaziland, 2006-07 Tanzania, 1996 Tanzania, 2004-05 Tanzania, 2009-10 Timor-Leste, 2009-10

Togo, 1998 Uganda, 1995 Uganda, 2000-01 Uganda, 2006 Uganda, 2011 Zambia, 1996-97

Zambia, 2001-02 Zambia, 2007 Zimbabwe, 1994 Zimbabwe, 1999 Zimbabwe, 2005-06 Zimbabwe, 2010-11

Cumulative maternal deaths proportion

Cumulative births proportion