Monitoring maternal, newborn and child health: understanding key progress indicators doc

Monitoring maternal,
newborn and child health:
understanding key progress indicators

Monitoring maternal,
newborn and child health:
understanding key progress indicators
© World Health Organizaon 2011
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Eding: Countdown to 2015, Health Metrics Network and World Health Organizaon.
Design: Punto Graco, Edward Cobos, Email:
Front cover photographs:
 Nineteen year-old pregnant woman at a mobile maternity clinic in Port-au-Prince, Hai. Credit: Panos/
Espen Rasmussen.
 Portrait of boy, Thailand. Credit: Health Metrics Network/Pierre Virot.

Back cover photographs:
 Portrait of woman, Mexico. Credit: Health Metrics Network/Pierre Virot.
 Health worker doing paperwork and updang paents’ records at a clinic, Mali. Credit: Panos/Giacomo
Pirozzi.
 Woman and her newly adopted baby, one of around 100 babies abandoned in Khartoum each month,
Sudan. Credit: Panos/Abbie Trayler-Smith.
Prinng: Imprimerie Chirat, France
WHO Library Cataloguing-in-Publicaon Data
Monitoring maternal, newborn and child health: understanding key progress indicators.
1.Women’s health. 2.Child welfare - stascs. 3.Vital stascs. 4.Data collecon - methods. 5.Health
status indicators. 6.Maternal mortality. 7.Infant mortality. 8.Financing, Health. 9.Health priories.
10.Millennium Development Goals. 11.Developing countries. I.Countdown to 2015. II.Health Metrics
Network.
ISBN 978 92 4 150281 8 (NLM classicaon: WA 310)
Contents
List of abbreviaons iv
Authors v
Relevant Millennium Development Goals vi
Introducon 1
Secon 1
Health informaon systems: gaps and opportunies 3
The global picture 3
Data sources for the 11 core indicators 4
Data availability 6
Strengthening countries’ capacity to monitor 7
and evaluate results
Secon 2
The Commission’s 11 core indicators 11
Impact indicators 11
Coverage Indicators 16

Secon 3
Commission recommendaons for resource tracking 35
Secon 4
Equity analyses of the Commission’s 11 core indicators 37
Conclusion 41
References 42
iv
List of abbreviaons
ANC: antenatal care
ART: anretroviral therapy
ARV: anretroviral
AZT: azidothymidine/zidovudine
CDC: United States Centers for Disease Control and Prevenon
CHERG: Child Health Epidemiology Reference Group
CPR: Contracepve Prevalence Rate
DESA: United Naons Department of Economic and Social Aairs
DHS: Demographic and Health Surveys
DTP3: diphtheria-tetanus-pertussis vaccine, three doses
FFS: European Ferlity and Family Surveys
HIV: human immunodeciency virus
HMN: Health Metrics Network
IGME: United Naons Inter-agency Group for Child Mortality Esmaon
IHME: Instute for Health Metrics and Evaluaon
IPTp: intermient prevenve treatment of malaria during pregnancy
MCH: maternal and child health
MDG: Millennium Development Goal
MICS: Mulple Indicator Cluster Surveys
MMEIG: Maternal Mortality Esmaon Interagency Group
MMR: maternal mortality rate
MNCH: maternal, newborn and child health

NVP: nevirapine
PAPFAM: Pan-Arab Project for Family Health
PMTCT: prevenon of mother-to-child transmission of HIV
RAMOS: reproducve age mortality studies
RED: Reach Every District
RHS: Reproducve Health Surveys
RMNCH: reproducve, maternal, newborn and child health
SDNVP: single-dose nevirapine
THE: total health expenditure
UN: United Naons
UNAIDS: Joint United Naons Programme on HIV/AIDS
UNFPA: United Naons Populaon Fund
UNICEF: United Naons Children’s Fund
UNPD: United Naons Populaon Division
USAID: United States Agency for Internaonal Development
WHO: World Health Organizaon
v
Authors
This report has been co-produced by Countdown to 2015 and the Health Metrics Network.
Countdown to 2015: Tracking Progress in Maternal, Newborn and
Child Survival
Countdown to 2015 is a global movement of academics, governments, internaonal agencies,
health-care professional associaons, donors and nongovernmental organizaons, with
The Lancet as a key partner. It uses country-specic data to smulate and support country
progress towards achieving the health-related Millennium Development Goals (MDGs),
parcularly MDGs 4 and 5. Countdown focuses on coverage of eecve intervenons for
maternal, newborn and child health and coverage determinants, including health systems
and policies, nancial ows and equity. It tracks progress in the 74 countries where more
than 95% of all maternal and child deaths occur, including the 49 lowest-income countries.
Countdown has agreed to take responsibility for major parts of the follow-up agenda of the

Commission for Informaon and Accountability for Women’s and Children’s Health, including
annual reporng and analysis of country-specic informaon on key indicators of coverage
and its determinants. More informaon is available at hp://www.countdown2015mnch.org
Health Metrics Network
Reliable, complete and mely informaon is essenal for public health decision-making and
acon, including policy making, planning, programming, monitoring and reaching the health-
related MDGs. Established in 2005, the Health Metrics Network (HMN) is the rst global
partnership dedicated to strengthening naonal health informaon systems. HMN is hosted
by the World Health Organizaon (WHO) and operates as a network of global, regional and
country partners, mobilizing them to increase the availability of informaon for decisions to
improve health outcomes in countries.
HMN currently has two technical work streams: 1. Monitoring of Vital Events including
through innovave approaches such as informaon and communicaon technology,
(MOVE-IT for the MDGs), is a renewed drive to record every birth, death, and cause of
death; 2. Progress Tracking Tool is under development to help countries measure health
informaon system improvements, while the State of the World Informaon Systems for
Health report will document the current state of health informaon systems in countries
and idenfy priority areas for strengthening. More informaon is available at: hp://www.
healthmetricsnetwork.org
vi
The Commission on Informaon and Accountability for Women’s
and Children’s Health
The Commission on Informaon and Accountability for Women’s and Children’s Health was
set up at the end of 2010 by WHO at the request of United Naons (UN) Secretary-General
Ban Ki-moon in support of the Global Strategy for Women’s and Children’s Health. Its objecve
was to develop a framework for global reporng, oversight and accountability on women’s
and children’s health in the 74 high-burden and low-income countries.
2
The Commission’s
framework aims to track whether donaons for women’s and children’s health are made on

me, resources are spent wisely and transparently, and the desired results are achieved. The
Commission was co-chaired by President Jakaya Kikwete of the United Republic of Tanzania
and Prime Minister Stephen Harper of Canada.
The Commission’s report was presented to the UN Secretary-General at a side event on 20
September 2011 during the UN General Assembly. Keeping Promises, Measuring Results
contains 10 recommendaons in the areas of beer informaon for beer results, beer
tracking of resources for women’s and children’s health, and beer oversight of results and
resources at global and naonal levels. More informaon is available at: hp://www.who.
int/topics/millennium_development_goals/accountability_commission/en/
Relevant Millennium Development Goals
MDG 1: Eradicate extreme poverty and hunger. Target 1A: Halve, between 1990 and 2015,
the proporon of people whose income is less than $1 a day. Target 1B: Achieve full and
producve employment and decent work for all, including women and young people. Target
1C: Halve, between 1990 and 2015, the proporon of people who suer from hunger.
MDG 4: Reduce child mortality. Target 4A: Reduce by two thirds, between 1990 and 2015,
the under-ve mortality rate.
MDG 5: Improve maternal health. Target 5A: Reduce by three quarters the maternal mortality
rao. Target 5B: Achieve universal access to reproducve health.
MDG 6: Combat HIV/AIDS, malaria and other diseases. Target 6A: Have halted by 2015 and
begun to reverse the spread of HIV/AIDS. Target 6B: Achieve, by 2010, universal access to
treatment for HIV/AIDS for all those who need it. Target 6C: Have halted by 2015 and begun
to reverse the incidence of malaria and other major diseases.
More informaon is available at: hp://www.un.org/millenniumgoals/

Monitoring maternal, newborn and child health
1
Introducon
The United Naons Commission on
Informaon and Accountability for Women’s
and Children’s Health (the Commission),

established in December 2010 by Secretary-
General Ban Ki-moon, was charged with
developing a framework for global reporng,
oversight, and accountability related to the
Global Strategy for Women’s and Children’s
Health. Specically, the Commission was
asked to develop a framework and suggest
mechanisms that would:
• track results and resource ows for
women’s and children’s health at the
global and country levels;
• idenfy a core set of indicators and
measurement needs for women’s and
children’s health;
• propose steps to improve health
informaon and registraon of births
and deaths in low-income countries;
and
• explore opportunies for innovaon
in informaon technology to improve
access to reliable informaon on
resources and outcomes.
In May 2011, the Commission issued
its Keeping promises, measuring results
report,
1
developed with input from working
groups on results and resources. The report
laid out a framework for accountability
built on three essenal and interconnected

processes — monitor, review, and act,
and called for the establishment of an
independent Expert Review Group to assess
and report on progress in terms of results
and resources in 74 high-burden priority
1
Commission on Informaon and Accountability
for Women’s and Children’s Health. Keeping
promises, measuring results. Geneva, World
Health Organizaon, 2011 (hp://www.
everywomaneverychild.org/images/content/les/
accountability_commission/nal_report/Final_EN_
Web.pdf, accessed 14 November 2011).
countries.
2
The Commission idened 11
core indicators
3
that, taken together, enable
stakeholders to track progress in improving
coverage of intervenons needed to ensure
the health of women and children across
the connuum of care. These indicators
include eight measures of intervenon
coverage and three measures of impact. For
all 11 indicators, the Commission urged that
the data be disaggregated by gender and
2
The 74 original high-burden countries account
for more than 95% of all maternal and child

deaths and include the 49 low-income countries
referred to in the Global Strategy for Women’s
and Children’s Health. South Sudan is also a high-
burden country and thus constutes the 75
th
country, but as few data are currently available,
South Sudan is not included in this report.
3
The 11 indicators were selected from the indicators
monitored for the Millennium Development Goals,
and those tracked by Countdown to 2015.
Credit: Panos/Giacomo Pirozzi. A mother with her newborn
baby soon aer delivery in the maternity ward of a hospital,
Uzbekistan.
2
Understanding key progress indicators
other equity consideraons. In addion, the
Commission idened two indicators for
tracking nancial ows related to women’s
and children’s health.
By focusing on a relavely small number
of core indicators to be tracked across all
high-burden and low-income countries, the
Commission sought to reduce the reporng
burden on naonal governments and health
systems, enhance countries’ capacity to
monitor and evaluate progress, and ensure
naonal leadership and ownership of
results.
In this report, the Health Metrics Network

(HMN) and Countdown to 2015 (Count-
down) summarize the main opportunies
and challenges to eecve monitoring of
the 11 core indicators in the 74 countries
covered by the Commission and Countdown
— countries that account for more than 95%
of the world’s maternal, newborn and child
deaths. The document rst explores the ex-
tent to which health informaon systems in
these countries are currently able to report
on the Commission’s recommended indica-
tors with the accuracy, frequency, meli-
ness, and quality needed to ensure that
stakeholders will be held to account for de-
livering on their commitments to women’s
and children’s health. The report’s second
secon provides detailed descripons of
each of the Commission’s 11 core indica-
tors, including a discussion of data sources
and areas of potenal improvement. A third
secon discusses the two nancing indica-
tors for resource tracking recommended
by the Commission, and a fourth secon
examines the feasibility of disaggregang
data on the 11 core indicators by key dimen-
sions of equity (e.g. wealth quinle, urban/
rural residence, gender, age, etc.).
Monitoring maternal, newborn and child health
3
Health

informaon
systems: gaps and
opportunies
The global picture
Country health informaon systems
draw on a broad range of data sources,
including censuses, household surveys,
health facility reporng systems, health
facility assessments, vital registraon
systems, other administrave data systems,
and surveillance. A recent HMN/World
Health Organizaon (WHO) publicaon,
Country health informaon systems: a
review of the current situaon and trends,
4

concluded that, while demands for reliable
and mely data are growing, informaon
systems in most low and middle-income
countries are currently not adequate to the
task. The most important challenges facing
country health informaon systems include
the following:
• The proliferaon of indicators used
for monitoring progress towards
globally-dened goals and targets,
health and disease programmes, and
4
World Health Organizaon/Health Metrics
Network. Country health informaon systems: A

review of the current situaon and trends. Advance
preprint copy. Geneva, World Health Organizaon,
2011 (hp://www.who.int/healthmetrics/news/
chis_report.pdf, accessed 3 November 2011).
Secon 1
specic projects and grants creates
a considerable reporng burden
for countries, without necessarily
strengthening the underlying health
informaon systems.
• Although countries have dened
core indicators and targets, data are
oen unavailable or of poor quality,
hampering countries’ ability to monitor
health system performance and
progress.
• Many countries are sll in the process
of establishing the foundaons of a
sound health informaon system — a
supporve policy and legal framework,
a comprehensive naonal health
plan, well-designed coordinaon and
oversight mechanisms, and sucient
human and nancial investments. Few
countries have put in place objecve and
independent data quality-assurance
mechanisms or explicit systems for
data sharing and disseminaon.
• Informaon and communicaon
technologies have the potenal to

Credit: World Health Organizaon/Evelyn Hockstein. Data
manager in Kenya.
4
Understanding key progress indicators
4
greatly facilitate data collecon,
compilaon, transmission, storage,
and disseminaon. However, many
countries do not have the norms and
standards in place that are needed for
their eecve implementaon.
While these dicules can be found in
many countries to varying degrees, those
that face the greatest health challenges
generally also have the weakest systems for
gathering, managing, analysing, and using
informaon. This situaon, oen referred
to as the “informaon paradox,” is most
evident in the absence of registraon and
counng of vital stascs such as births,
deaths, and causes of death in countries
with the highest ferlity and mortality rates.
An esmated 40 million births (one third
of the world’s annual total) and 40 million
deaths (two thirds of the annual total) go
unrecorded each year, most of them in
Africa and Asia.
Data sources for the 11
core indicators
For the two recommended mortality

indicators (maternal mortality rao and
under-ve mortality rate), complete and
accurate civil registraon and vital stascs
systems are the preferred data source.
Census data is generally made available
on a periodic basis in the 74 Commission
countries; however, coverage levels for
naonal registraon of births, deaths, and
causes of death are highly variable and
generally less than sasfactory. Because vital
registraon systems funcon poorly in most
of the Commission countries, household
surveys are the main source of mortality
data. The weakness of health informaon
systems in many low and middle-income
countries has resulted in the need for
stascal modelling exercises to develop
internaonally comparable mortality
esmates. These esmates, parcularly
for maternal mortality, are subject to
considerable uncertainty, and vary with
the assumpons and methods used. The
substanal eort and aenon devoted to
regular updang of these esmates reect
the global community’s commitment to
connuously improve assessment of the
maternal and child mortality burdens. The
lack of quality vital stascs data points to
the urgent need for investment in building
country vital registraon and health

informaon systems.
For most of the remaining nine core
indicators (children under ve years of age
who are stunted and the eight coverage
indicators), the opmal scenario is a
combinaon of high-quality facility reporng
— providing annual data by district for
sub-naonal analysis and for planning and
programmac purposes, including at annual
health sector reviews — with household
surveys. Household surveys and rounely-
collected data each have strengths and
limitaons, and are complementary. Both
sources need to be connuously assessed
for data quality, and adjustments made
Credit: Health Metrics Network photo library. Data collecon
in Ghana.
7
 Information and communication technologies have the potential to greatly facilitate data collection,
compilation, transmission, storage, and dissemination. However, many countries do not have the
norms and standards in place that are needed for their effective implementation.
While these difficulties can be found in many countries to varying degrees, those that face the greatest
health challenges generally also have the weakest systems for gathering, managing, analysing, and using
information. This situation, often referred to as the "information paradox," is most evident in the
absence of registration and counting of vital statistics such as births, deaths, and causes of death in
countries with the highest fertility and mortality rates. An estimated 40 million births (one third of the
world's annual total) and 40 million deaths (two thirds of the annual total) go unrecorded each year,
most of them in Africa and Asia.
Data sources for the 11 core indicators
Credit: Health Metrics Network photo library. Data collection in Ghana.

5
Monitoring maternal, newborn and child health
as needed, so that best esmates can be
generated for monitoring progress.
At present, as shown in Table 1, household
surveys are the main data source for nine of
the 11 indicators. The two main surveys used
to collect naonally representave data
for women’s and children’s health are the
United States Agency for Internaonal De-
velopment (USAID)-supported Demographic
and Health Surveys (DHS) and the United
Naons Children’s Fund (UNICEF)-supported
Mulple Indicator Cluster Surveys (MICS).
DHS and MICS are conducted approximately
every ve and three years, respecvely.
DHS and MICS programmes work together
closely to ensure comparability across
surveys.
Table 1 Current primary data sources and preferred data sources for the 11 core indicators
of women's and children's health
Indicator Current primary
data source
Preferred data
source
Maternal mortality rao Surveys Vital registraon
Under-ve child mortality (with the
proporon of newborn deaths)
Surveys Vital registraon
Stunng prevalence Surveys Surveys

Demand for family planning sased (met
need for contracepon)
Surveys Surveys
Antenatal care (four or more visits) Surveys Surveys and
facility reports
Anretrovirals for HIV-posive pregnant
women*
Facility reports Facility reports
Skilled aendant at birth Surveys Surveys and
facility reports
Postnatal care for mothers and babies within
two days of birth
Surveys Surveys and
facility reports
Exclusive breaseeding (0–5 months of age)** Surveys Surveys
Three doses of combined diphtheria-tetanus-
pertussis vaccine (DTP3) immunizaon
coverage
Surveys and
facility reports
Surveys and
facility reports
Anbioc treatment for childhood pneumonia Surveys Surveys and
facility reports
HIV: human immunodeciency virus
* This indicator comprises anretroviral drugs for HIV-posive pregnant women to both reduce the risk of
mother-to-child transmission of HIV and for their own health.
** Up to the last day of the h month of life
Household surveys are useful for collecng
populaon-level coverage data, and for

measuring ulizaon of available health-
care services and individual behaviours
such as contracepve use. Surveys are an
indispensable source of equity informaon,
because data can be disaggregated
according to dierent characteriscs of the
populaon (e.g. age, gender, household
wealth, educaon, urban/rural residence).
However, household surveys are not good
mechanisms for reporng on data at sub-
district levels — where many programming
decisions are made — because very large
sample sizes would be required, driving up
data collecon costs. Because household
surveys are typically not performed on an
7
 Information and communication technologies have the potential to greatly facilitate data collection,
compilation, transmission, storage, and dissemination. However, many countries do not have the
norms and standards in place that are needed for their effective implementation.
While these difficulties can be found in many countries to varying degrees, those that face the greatest
health challenges generally also have the weakest systems for gathering, managing, analysing, and using
information. This situation, often referred to as the "information paradox," is most evident in the
absence of registration and counting of vital statistics such as births, deaths, and causes of death in
countries with the highest fertility and mortality rates. An estimated 40 million births (one third of the
world's annual total) and 40 million deaths (two thirds of the annual total) go unrecorded each year,
most of them in Africa and Asia.
Data sources for the 11 core indicators
Credit: Health Metrics Network photo library. Data collection in Ghana.
6
Understanding key progress indicators

annual basis, their data are not generally
useful for annual or biannual planning and
programmac purposes.
Roune service delivery reports from
health-care facilies are potenally an
important data source for the eight
recommended coverage indicators. Data
from health facilies can be available on a
connuous basis and are thus more up-to-
date than household survey data. Facility
reports are, however, an incomplete and
potenally biased source of data, because
not all people use facilies to meet their
health-care needs. Family planning services,
for example, are provided through various
service delivery channels. Furthermore,
data quality in terms of completeness,
meliness, and accuracy of reporng is
oen problemac in the 74 Commission
countries. In some countries, the Ministry
of Health web site includes reports
providing district-level stascs based on
health facility data, but the availability
of these data are not consistent across
or within countries. Applying systemac
techniques to assess data quality and to
reconcile facility and survey data could
signicantly improve esmates for the eight
recommended coverage indicators, but is
not currently a standard procedure in most

of the Commission countries.
Data availability
Table 2 (p. 8-10) shows the status of
data sources in relaon to the 11 indicators
for each of the 74 countries (South Sudan is
not included in the table, as no data were
available at the me of publicaon). The
table includes the year of the most recent
census (or year for which it is planned as
part of the 2010 round of censuses) and the
coverage levels of systems of birth, death and
cause of death registraon. It also shows the
number of household surveys that included
child mortality, maternal mortality, child
anthropometry, and coverage of maternal,
newborn and child health indicators during
the ve-year period 2006-10, as well as
Naonal Health Accounts and subaccounts
for maternal, newborn and child health.
Overall, 56 out of the 74 countries
conducted a survey with data collecon
on child mortality during 2006-10. Most
countries that did not conduct a survey
obtain data from the birth and death
registraon system, or from a sample
registraon system, such as India, or a
mix of surveillance and vital registraon,
such as China. Of the 74 countries, 32 had
conducted a survey that included maternal
mortality data. In some countries, such as

India and China, child mortality data are
also generated from other data sources,
notably sample registraon systems. Lack
of data constutes a major gap for maternal
mortality because the measurement of
maternal deaths, regardless of data source,
is complex and oen inaccurate.
Data on child stunng and other nutrional
status indicators in low-income countries
are drawn mainly from household surveys.
All 74 countries have at least one data point
since 2000. Twenty-two countries have data
points for 2008-09, with most data points
from 2008.
Credit: Panos/Jenny Mahews. Register of births at the
Kabala Maternity Complex, Kabala, Northern Province, Sierra
Leone.
7
Monitoring maternal, newborn and child health
For the eight coverage indicators, DHS and
MICS provide a general picture of mid- to
long-term progress. Because household
surveys are the main and oen sole source
of data for the coverage indicators, data
availability largely depends on whether a
recent survey was conducted.
The frequency of surveys in the past 10-20
years in many of the priority countries has
been too low to reliably assess coverage
trends. For some of the core coverage

indicators, such as DTP3 immunizaon,
prevenon of mother-to-child transmission
of HIV, and skilled aendance at birth,
roune service delivery reports from health-
care facilies are potenally an important
complementary data source, and are oen
used by countries in annual reviews.
Strengthening countries’
capacity to monitor and
evaluate results
High quality data are crically needed
in order to enable global assessment
of progress on the Commission’s
recommended measures of coverage,
impact, nancing, and equity related to
women’s and children’s health. Perhaps
more importantly, the availability of
accurate, mely, and consistent data at the
naonal and sub-naonal levels is crucial for
countries to be able to eecvely manage
their health systems, allocate resources
according to need, and ensure accountability
for delivering on health commitments.
A key principle of the Commission’s
framework for accountability, therefore, is
the enhancement of countries’ capacity to
monitor and evaluate their own results.
To improve measurement of the core
indicators, signicant strengthening of
country health informaon systems is

an urgent need. Recommended steps to
achieve this goal include:
• development of a harmonized
programme of health surveys to collect
data;
• investment in building a complete
and universal registraon of vital
events, including births, deaths and
cercaon of cause of death;
5
• investment in health facility and
administrave data recording systems
to improve data quality and monitoring
eorts;
• evaluaon of current iniaves to
explore the potenal of informaon
and communicaon technologies to
improve the speed and accuracy of
reporng, parcularly at community
level, and scaling up where there is
evidence of their eecveness; and
• support to build country capacity to
monitor, review and act on data.
These improvements will require a long-
term approach with short-term milestones,
and individual country plans need to be
developed that take into consideraon
the baseline situaon and investments
required. A priority for the Commission
countries is capacity building on data

use, including assessment of data quality,
triangulaon and reconciliaon of data from
dierent sources, as well as the use of data
for monitoring purposes and strengthening
reporng mechanisms at all levels of the
health system.
Secon 2 describes the programmac
relevance of the 11 core indicators and
shows that while a good deal of relevant
data are currently available, eorts to
measure, collect, and use available data
on the Commission’s 11 core indicators sll
face signicant challenges.
5
The Health Metrics Network MOVE-IT for the
MDGs iniave, as well as regional partner
networks, are supporng the strengthening of civil
registraon and vital stascs systems in Africa and
Asia (hp://www.who.int/healthmetrics/move_it/
en/, accessed 3 November 2011). These will be
evaluated and should be scaled up where there is
evidence of eecveness.
8
Understanding key progress indicators
Table 2: Data availability for the 74 countries of the Commission on Informaon and Accountability for
Women’s and Children’s Health
Registraon
(2000-09)
Surveys
(2006-10)

Naonal Health Account
(2006-09)
World
Bank
Regions
Country Census Births Deaths Causes
of
death
Child
mortality
Child
anthropometry
MCH
coverage
Years
produced
MNCH
expenditures
East Asia
& Pacic Cambodia 2008 66 <25 - 2 2 2 0 0
China 2010 - <25 <25 4* 0 1 2 0
Democrac
People's
Republic of
Korea 2008 99 <25 - 1 1 1 0 0
Indonesia 2010 53 <25 - 1 1 1 3 0
Lao People's
Democrac
Republic 2005 72 <25 - 1 1 1 0 0
Myanmar 2013 65 <25 <25 0 0 0 2 0

Papua New
Guinea 2011 - - - 0 0 0 0 0
Philippines 2010 >90 90-100 90-100 1 1 2 2 0
Solomon Islands 2009 80 - - 1 1 0 0 0
Viet Nam 2009 >90 <25 - 2 3 2 2 0
Europe &
Central
Asia Azerbaijan 2009 >90 50-74 50-74 1 1 1 0 0
Kyrgyzstan 2009 >90 75-89 75-89 0 0 0 4 0
Tajikistan 2010 88 50-74 50-74 0 0 0 2 0
Turkmenistan 2012 96 - - 1 1 1 0 0
Uzbekistan 1989 100 75-89 75-89 1 1 1 0 0
Lan
America &
Caribbean
Bolivia
(Plurinaonal
State of) 2012 74 <25 - 1 1 1 2 0
Brazil 2010 91 75-89 75-89 0 1 0 1 0
Guatemala 2012 >90 75-89 75-89 0 1 0 3 0
Hai 2013 81 <25 <25 0 0 0 0 0
Mexico 2010 - 90-100 90-100 0 1 0 4 1
Peru 2007 93 50-74 50-74 2 2 2 0 0
Middle
East &
North
Africa Djibou 2009 89 <25 - 1 1 1 0 0
Egypt 2006 >90 90-100 90-100 1 1 1 2 0
Iraq 2011 95 <25 - 2 1 2 0 0
Morocco 2014 85 25-49 25-49 3 3 3 1 0

Yemen 2014 22 <25 - 2 1 2 2 0
MCH: maternal and child health; MNCH: maternal, newborn and child health
* Data points from sample registraon systems.
9
Monitoring maternal, newborn and child health
Registraon
(2000-09)
Surveys
(2006-10)
Naonal Health Account
(2006-09)
World
Bank
Regions
Country Census Births Deaths Causes
of
death
Child
mortality
Child
anthropometry
MCH
coverage
Years
produced
MNCH
expenditures
South
Asia Afghanistan 2011-13 6 <25 - 0 0 0 0 0
Bangladesh 2011 10 <25 - 3 3 3 3 0

India 2011 41 <25 <25 2* 0 0 0 0
Nepal 2011 35 <25 - 1 1 1 0 0
Pakistan 2011 27 <25 - 1 0 1 1 0
Sub-
Saharan
Africa Angola 2013 29 <25 - 2 0 0 0 0
Benin 2012 60 <25 - 1 1 1 2 0
Botswana 2011 72 <25 - 0 0 0 0 0
Burkina Faso 2006 64 <25 - 3 3 2 3 0
Burundi 2008 60 <25 - 1 1 1 1 0
Cameroon 2005 70 <25 - 1 1 1 0 0
Central African
Republic 2013 49 <25 - 1 1 1 0 0
Chad 2009 9 <25 - 1 1 1 0 0
Comoros 2013 83 <25 - 0 0 0 0 0
Congo 2007 81 <25 - 1 1 1 0 0
Côte d'Ivoire 2011 55 <25 - 1 2 1 2 0
Democrac
Republic of the
Congo 2012 31 <25 - 2 2 2 2 1
Equatorial
Guinea 2013 32 <25 - 0 0 0 0 0
Eritrea 2011 - <25 - 0 0 0 0 0
Ethiopia 2007 7 <25 - 1 1 1 1 1
Gabon 2013 89 <25 - 0 0 0 0 0
Gambia 2013 55 <25 - 0 0 0 0 0
Ghana 2010 71 <25 <25 2 2 3 0 0
Guinea 2012 43 <25 - 0 1 0 0 0
Guinea-Bissau 2009 39 <25 - 2 3 2 0 0
Kenya 2009 60 25-49 25-49 3 2 3 1 2

Lesotho 2006 26 <25 - 1 1 1 0 0
Liberia 2008 4 <25 - 2 2 1 1 1
Madagascar 2011 75 <25 - 1 1 1 1 0
Malawi 2008 - <25 - 2 2 2 1 0
Mali 2009 53 <25 - 1 1 1 0 0
10
Understanding key progress indicators
Registraon
(2000-09)
Surveys
(2006-10)
Naonal Health Account
(2006-09)
World
Bank
Regions
Country Census Births Deaths Causes
of
death
Child
mortality
Child
anthropometry
MCH
coverage
Years
produced
MNCH
expenditures
Mauritania 2012 56 <25 - 1 2 1 0 0

Mozambique 2007 31 <25 - 1 4 1 1 0
Niger 2012 32 <25 - 2 1 2 1 0
Nigeria 2006 30 <25 - 4 2 3 0 1
Rwanda 2012 82 <25 - 2 1 2 1 2
Sao Tome and
Principe 2011 69 - - 2 2 2 0 0
Senegal 2012 55 <25 - 0 0 0 0 0
Sierra Leone 2014 51 <25 - 1 1 1 1 0
Somalia 1987 3 <25 - 1 2 1 0 0
South Africa 2011 92 90-100 90-100 1 1 0 0 0
Sudan 2008 33 <25 - 0 1 0 1 0
Swaziland 2007 30 <25 - 1 1 1 0 0
Togo 2010 78 <25 - 1 2 1 0 0
Uganda 2012 21 <25 - 5 3 1 1 0
United Republic
of Tanzania 2012 22 <25 - 3 3 3 1 2
Zambia 2010 14 <25 - 1 1 1 1 0
Zimbabwe 2012 74 25-49 25-49 1 1 1 0 0
Sources:
Census: United Naons Stascal Division
Registraon: World Health Organizaon. World Health Stascs 2011. Geneva, World Health Organizaon, 2011.
Surveys: World Health Organizaon.
Naonal Health Account: World Health Organizaon.
Monitoring maternal, newborn and child health
11
The Commission’s
11 core indicators
Secon 2
Indicator Maternal mortality rao (MMR)
Indicator

denion
The rao of the number of recorded (or esmated) maternal deaths during a given
me period per 100 000 live births during the same me period (the number of
maternal deaths in a populaon divided by the number of live births – depicng the
risk of maternal death relave to the number of live births)
A maternal death refers to a female death from any cause related to or aggravated
by pregnancy or its management (excluding accidental or incidental causes) during
pregnancy and childbirth or within 42 days of terminaon of pregnancy, irrespecve
of the duraon and site of the pregnancy.
6
Programme
relevance
Maternal mortality is a sensive measure of health system strength, access to quality
care and coverage of eecve intervenons to prevent maternal deaths. The MMR
represents the risk associated with each pregnancy and is also a useful barometer
of social and economic condions such as women's and girls’ access to educaon,
equality, and polical commitment to health and development. Reducon of the
MMR by three quarters between 1990 and 2015 is a tracking indicator for MDG 5
target 5A.
Data source(s) The MMR can be calculated from data collected through vital registraon systems,
household surveys (direct methods), sisterhood methods (where respondents are
asked about the survival of all their adult sisters), verbal autopsies, reproducve
age mortality studies (RAMOS), disease surveillance or sample registraon systems,
special studies on maternal mortality, health services records, and naonal populaon
censuses. Weaknesses in many countries’ health informaon systems have required
the use of stascal modelling exercises to develop comparable maternal mortality
esmates. Esmaon procedures use available data and adjust for underreporng
and potenal misclassicaon of deaths.
For ocial MDG tracking, the United Naons uses interagency-adjusted esmates
produced by the Maternal Mortality Esmaon Interagency Group (MMEIG), which is

composed of WHO, UNICEF, United Naons Populaon Fund (UNFPA) and the World
Bank, together with demographic experts from academic instuons. Maternal
mortality esmates using an alternate set of assumpons and methods have been
produced by the Instute of Health Metrics and Evaluaon (IHME), a global health
research centre at the University of Washington, United States of America.
1. Impact indicators
>>>>
6
Internaonal stascal classicaon of diseases and related health problems, 10th revision. Geneva, World Health
Organizaon, 2010 (1989).
Credit: Panos/Mads Nissen, Berlingske. A pregnant woman
has her abdomen and unborn fetus examined at a rural
health clinic in Hetauda, Makwanpur, Nepal.
12
Understanding key progress indicators
Indicator Maternal mortality rao (MMR)
Data
availability and
quality
A recent analysis of empirical observaons from the late 1980s to 2008 found only
484 data points globally, an average per country of less than three over about two
decades.
7
In sub-Saharan Africa, there were only 74 naonal data observaons
over the same period. MMRs may be calculated from vital registraon data for 63
countries in the world. For other countries, to ensure internaonal comparability,
model-based esmates are used.
Maternal mortality is dicult to measure. Idenfying a maternal death requires
accurate data on cause of death, pregnancy status and the me of death in relaon
to pregnancy or childbirth for women of reproducve age. Vital registraon and

health informaon systems in most developing countries are weak, and thus, cannot
provide an accurate assessment of maternal mortality. Esmates derived from all of
the possible data sources, even esmates derived from complete vital registraon
systems in industrialized countries, suer from missing data, misclassicaon and
underreporng of maternal deaths.
Because maternal mortality is a relavely rare event, large sample sizes are needed if
household surveys are used, increasing the cost of data collecon. Surveys (including
sisterhood methods) idenfy pregnancy-related deaths, and provide a retrospecve
rather than a current mortality esmate.
In addion, owing to the very large condence limits around maternal mortality
esmates because of sample size issues, trends in maternal mortality should
be interpreted with cauon. It is recommended that process indicators, such as
aendance by skilled health personnel at delivery and use of health facilies for
delivery, be considered in assessing progress towards the reducon of maternal
mortality.
Censuses can provide esmates of maternal mortality by including a limited number
of quesons on household deaths in the last 12 months to two years prior to the
census. They are carried out in 10-year intervals, liming the use of census data for
regular monitoring.
Specic data
improvements
needed
Generang accurate esmates of maternal mortality poses a considerable challenge
due to the limited availability of high-quality data for many low and middle-income
countries. Complete vital registraon systems are the preferred source of data because
they collect informaon as events occur and cover the enre populaon. Investments
in vital registraon systems to ensure correct reporng of births, maternal deaths,
and causes of maternal deaths are needed. Connued advancements in stascal
modelling approaches, data collecon through household surveys, improvements in
the reporng of maternal deaths from health-care facilies, and methods for properly

carrying out RAMOS are a crical interim measure as vital registraon systems
are strengthened. Furthermore, the Commission's recommendaons provide an
excellent opportunity to develop or strengthen maternal death surveillance and
response systems in countries, beneng from the rapid spread of informaon
technology.
7
Wilmoth J. Technical paper on maternal mortality esmaon 2011 (forthcoming).
Monitoring maternal, newborn and child health
13
Indicator Under-ve child mortality rate (with the proporon of newborn deaths)
Indicator
denion
The probability that a child born in a specic year or me period will die before
reaching the age of ve, if subject to current age-specic mortality rates (expressed
as a rate per 1000 live births: number of deaths of children less than ve years of age
per 1000 live births)
The proporon of newborn deaths is the proporon of all child deaths that occur
among infants up to four weeks (28 days) of age.
Programme
relevance
The under-ve mortality rate is a key indicator for measuring child well-being,
including health and nutrional status. It is also a key indicator of the coverage of
child survival intervenons and, more broadly, of social and economic development.
Reducon of under-ve mortality by two thirds between 1990 and 2015 is a target
indicator of MDG 4.
Proven prevenve and curave intervenons are oen packaged together to target
the leading causes of death of children under the age of ve (e.g. pneumonia,
diarrhoea, malaria and under-nutrion). More than 40% of all child deaths now
occur in the neonatal period, and in many countries reducon of neonatal mortality
is progressing more slowly than reducon of child mortality. Systemac acon is

required by governments and their partners to reach all women and newborns in
addion to children under ve with eecve care. Highly cost-eecve intervenons
are available and feasible for delivery even at the community level.
>>>>
Credit: Panos/Kieran Dodds. A nomadic Khampa child receives basic medical treatment in a small clinic in Dengke, Sichuan
Province, China.
14
Understanding key progress indicators
Indicator Under-ve child mortality rate (with the proporon of newborn deaths)
Data source(s) Under-ve mortality rates are computed from data collected in vital registraon
systems, local demographic surveillance systems, household surveys (full or
summary birth histories) and censuses (summary birth histories). In most of the 74
countries, household surveys conducted as part of DHS and MICS are the main data
source.
The United Naons Inter-agency Group for Child Mortality Esmaon (IGME)
produces comparable esmates for 195 countries on an annual basis. The IGME uses
all available naonal-level data aer reviewing data quality, and produces country-
specic child mortality esmates with publicly available data inputs, adjustments
and a replicable stascal model (hp://www.childmortality.org, accessed 3
November 2011). IHME has produced esmates using an alternave set of stascal
assumpons. The two sets of esmates are generally consistent in terms of measures
of overall global trends in mortality declines.
Data
availability and
quality
Complete vital registraon systems are considered the gold standard for mortality
measurement. The majority of low and middle-income countries, however, does not
have fully funconing vital registraon systems. Populaon-based survey data are
crical for developing sound mortality esmates for these countries. The number
of such surveys has increased dramacally in the last two decades, notably because

of the DHS and MICS internaonal survey programmes, with 56 of the 74 countries
conducng a survey between 2006 and 2010. Data from more than one survey are
available for 21 of the 74 countries.
Informaon from mothers about the survival of their children is collected through
these two household surveys. The most common approach is the full birth history
(used in all DHS and some MICS) whereby each woman, aged 15 to 49 at the me
of the survey, is asked about the date of birth and, if the child has died, age at death
of each live-born child she has had. Many MICS collect only summary birth histories
from mothers to gather informaon on the number of children ever-born, surviving
or dead.
Censuses can provide esmates of child mortality by including summary birth
histories or quesons on household deaths in the last 12 months prior to the census.
Under-ve mortality calculated from household surveys is oen subject to sampling
and non-sampling errors and those derived from census or vital registraon systems
may also have non-sampling errors. Age misreporng, selecon bias and recall
bias can all negavely impact the accuracy of esmates of the under-ve mortality
rate. Underreporng of births and parcularly early neonatal deaths is also very
common. Pregnancy history data available in some DHS and other surveys may allow
for measurement of sllbirths and a more accurate approach for capturing early
neonatal deaths.
Specic data
improvements
needed
Generang accurate esmates of child mortality poses a considerable challenge
because of the limited availability of high-quality data for many low and middle-
income countries. Complete vital registraon systems are the preferred source
of data because they collect informaon as events occur and cover the enre
populaon. Strengthening vital registraon systems to ensure correct reporng of
births and deaths is essenal for improving esmates of neonatal and child mortality.
For esmates derived from household surveys, well-designed quesonnaires, proper

training and supervision of survey interviewers, as well as reasonable interview
length, are important measures for improving data quality. Lengthy quesonnaires
may aect data quality, parcularly for those data derived from full birth histories.
Household surveys that include data collecon on child mortality through a full birth
history or pregnancy history should ideally be carried out at least once every ve
years. Sample sizes should be large enough for the detecon of signicant trends
in equity.
15
Monitoring maternal, newborn and child health
Indicator Stunng prevalence
Indicator
denion
Percentage of children under ve who are stunted
Numerator Number of children under ve years of age whose length-for-age or height-for-
age is below minus two standard deviaons from the median of the WHO Child
Growth Standards
Denominator Number of children under ve years of age with a valid length or height
measurement
Programme
relevance
Stunng is widely recognized as the most important anthropometric indicator for
young children, because adequate linear growth depends on opmal nutrion,
disease prevenon and child-care pracces. Stunng reects connued, long-
term exposure to poor health and nutrion, parcularly during the rst two years
of life. The indicator for nutrion (under MDG 1 target 1C) is the proporon of
children who are underweight (low weight for age) that captures a mix of children
suering from chronic and acute under-nutrion. Children from populaons
undergoing the nutrion transion (the shi from high levels of under-nutrion
and reducons in famines to increases in the prevalence of overweight and
nutrion-related non-communicable diseases that typically occurs as countries

develop) can experience a combinaon of stunng and overweight, and, as a
consequence, underweight prevalence in the populaon may be low. For this
reason, stunng is a beer indicator of under-nutrion than underweight.
Children under the age of ve around the world have the same growth potenal,
and prevalence of stunng above what would be expected in a well-nourished
populaon (about 3% prevalence) indicates the need for remedial acons.
Data source(s) In low and middle-income countries, health facility data do not provide reliable
esmates of stunng rates in the child populaon. DHS, MICS, and other naonal
household surveys usually collect data on stunng. Their results are available
in the UNICEF Global Database on Under-nutrion (hp://www.childinfo.org,
accessed 3 November 2011) as well as in the WHO Global Database on Child
Growth and Malnutrion (hp://www.who.int/nutgrowthdb/, accessed 3 No-
vember 2011).
Data availability
and quality
All 74 Commission countries had at least one survey with child anthropometry
data collecon in the last decade: 24 countries had one survey, 29 had two
surveys and 21 had three or more surveys. Viet Nam and Indonesia had 12 and
nine surveys respecvely with anthropometric data collecon during this me
period. On average, the last survey in the Commission countries was about six
years ago (in 2005). More than half of these countries (45) conducted a survey in
2006 or later. DHS and MICS are the main vehicles, but countries also conducted
other socioeconomic and nutrion surveys with anthropometric data collecon.
Unlike measurement of weight, which is relavely simple, measuring recumbent
length (in children under two years of age) or standing height (in children aged two
to ve years) requires thorough interviewer training, compliance with standard
anthropometric protocols, and regular sessions to standardize data collecon
procedures in the eld. Extreme length/height-for-age values (dened as plus or
minus four standard deviaons from the sample median value) are usually due to
measurement errors, and are rounely excluded from data analyses.

Specic data
improvements
needed
At global and regional levels, data availability is adequate, but it is strongly
recommended that at least one survey with anthropometric data collecon
should be carried out every four to ve years in every country. Thorough
training and standardizaon of measurement approaches, in addion to use of
appropriate equipment, are essenal for ensuring data quality.
Understanding key progress indicators
16
2. Coverage Indicators
Intervenon Demand for family planning sased (met need for contracepon)
Indicator
denion
Percentage of women of reproducve age (15-49 years or age), either
married or in a union, who have their need for family planning sased
This indicator is determined by the current levels of contracepve use and the
unmet need for family planning.
Numerator The Contracepve Prevalence Rate (CPR) is the percentage of women of
reproducve age (15-49 years old) who are married or in a union and who
are currently using, or whose sexual partner is currently using, at least one
contracepve method, regardless of the method used (modern or tradional).
Denominator Total demand for family planning is dened as the sum of the CPR (as dened
above) and the unmet need for family planning. Unmet need for family planning
is the proporon of women of reproducve age (15-49 years old) either married
or in a consensual union, who are fecund and sexually acve but who are not
using any method of contracepon (modern or tradional), and report not
wanng any more children or wanng to delay the birth of their next child for at
least two years. Included are:
• all pregnant women (married or in a consensual union) whose pregnancies

were unwanted or mismed at the me of concepon;
• all postpartum amenorrhoeic women (married or in consensual union)
who are not using family planning and whose last birth was unwanted or
mismed;
• all fecund women (married or in consensual union) who are neither pregnant
nor postpartum amenorrhoeic, and who either do not want any more
children (want to limit family size), or who wish to postpone the birth of a
child for at least two years or do not know when or if they want another child
(want to space births), but are not using any contracepve method.
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Credit: Panos/Giacomo Pirozzi. Family planning movator, North Cameroon.
17
Monitoring maternal, newborn and child healthMonitoring maternal, newborn and child health
Intervenon Demand for family planning sased (met need for contracepon)
Programme
relevance
The proporon of demand for family planning sased (met need for
contracepon) indicator enables assessment of family planning programmes
and progress in providing contracepve services to women who wish to avoid
geng pregnant. Access to family planning provides women and their partners
opportunies to make decisions about family size and ming of pregnancies.
This contributes to maternal and child health by prevenng unintended
pregnancies and pregnancies that are too closely spaced, which are at higher
risk for poor obstetrical outcomes. Unmet need for family planning shows
the gap between women’s reproducve intenons and their access to or use
of contracepves. The CPR provides an esmate of contracepve use in a
populaon. Both the unmet need for family planning and CPR indicators are
used for tracking progress towards the MDG 5 target 5B of achieving universal
access to reproducve health.
The proporon of demand sased (met need for contracepon) indicator

can range from a value of 1 to 100% with 100% coverage as the target, and is
therefore easier to interpret and compare across countries than either CPR or
unmet need for family planning. CPR and unmet need for family planning never
approximate 100% in a populaon since, at any one me, some women wish
to become pregnant and others are not at risk of pregnancy. The relaonship
between unmet need for family planning and CPR is also not straighorward,
as it depends upon a range of factors including where countries are along the
transion from high to low ferlity. For example, both CPR and unmet need may
increase at the same me in countries where the demand for family planning is
growing as the number of children desired declines.
Data source(s) Informaon on CPR and unmet need for family planning is collected through
household surveys such as DHS, MICS, RHS, and naonal surveys based on
similar methodologies. Other survey programmes, like the Pan-Arab Project for
Family Health (PAPFAM) and the European Ferlity and Family Surveys (FFS),
can also be used.
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