1. 1
WORLD VISION ETHIOPIA
FOOD SECURITY MONITORING TRAINING MANUAL
COMPILED
BY
GIRMA LEGESSE
September 2003
Addis Ababa

2. 2
Table of contents ........................................................................................................pages
CHAPTER ONE INTRODUCTION............................................................................. 4
1.1 Purpose and contents of this manual ..................................................................... 4
1.2 Food Security Concepts......................................................................................... 4
1.3 Nutritional assessment methods ............................................................................ 6
1.4 Objectives of emergency nutrition assessment...................................................... 6
2.1 Fundamentals of sampling..................................................................................... 7
2.2 Sampling frame and sampling unit........................................................................ 7
2.3 Types of sampling ................................................................................................. 7
2.4 Calculating sample size ....................................................................................... 10
2.5. Practical steps to undertake a nutrition survey.................................................... 11
2.6 Data to be collected ............................................................................................. 11
CHAPTER THREE ANTHROPOMETRIC INDICES, ANALYSIS AND
INTERPRETATION OF RESULTS ................................................................................ 12
3.1. Anthropometry defined........................................................................................ 12
3.2. Nutrition indices: -............................................................................................... 12
3.3 Means of expressing nutritional indices and indicators....................................... 13
3.4. Nutrition indicators.............................................................................................. 14
3.5 Causes of malnutrition......................................................................................... 14
3.6. Data analysis, Interpretation of results and recommendations............................ 16
3.7. Differences between results expressed in percentage of the median & z-scores 20
3.8. Expression of results with their confidence intervals.......................................... 21
3.9. Analysis of Mortality rates .................................................................................. 21
3.10. Reporting.......................................................................................................... 22
CHAPTER FOUR HOW TO WEIGH AND MEASURE CHILDREN .................... 32
4.1 Procedures and precautions before measuring .................................................... 32
4.2. Summary procedures for body measurement ...................................................... 34
4.3 Age assessment.................................................................................................... 37
CHAPTER FIVE HOW TO USE EPI INFO COMPUTER SOFTWARE ................ 42
5.1. Definition............................................................................................................. 42
5.2. Steps in EPI -Info program.................................................................................. 42
5.3. Running EPI INFO program............................................................................... 42
5.4. The main programs of the EPI INFO system ...................................................... 42
5.5. Field Types in EPI INFO..................................................................................... 43
5.6. Creating a New Data (.REC) File (Menu Choice 2)............................................ 45
5.7. Entering Data....................................................................................................... 45
5.8. Moving from Record to Record........................................................................... 45
5.9. Finding Records that Match Criteria ................................................................... 45
5.10 Editing Records ................................................................................................... 46
5.11. Deleting or Undeleting Records....................................................................... 46
5.13. Producing a Line Listing.................................................................................. 49
5.14 Charts and graphs............................................................................................. 50
5.15. Sending Results to the Printer or to a File............................................................ 50

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CHAPTER SIX: MARKET SURVEY ........................................................................... 52
6.1 Introduction ......................................................................................................... 52
6.2. Objectives of the Manual..................................................................................... 55
6.3. Definition of Terms and Concepts....................................................................... 55
6.4 Type of Products for Which Market Information is collected............................. 56
6.5. Market Levels for which Market Information will be gathered ......................... 57
6.6. Timetable for Collecting Market Information.................................................... 57
6.7. Sample Size and Selection Procedure for Gathering Market Information ......... 57
6.8. Data Collection Forms and Mode of Form Filling............................................. 59
CHAPTER SEVEN: CROP AND LIVESTOCK ASSESSMENT ............................ 66
7.1. Objectives: -......................................................................................................... 66
7.2. Assessment schedule: .......................................................................................... 66
7.3. Checklist for meher pre-harvest crop & livestock assessment............................ 67
CHAPTER EIGHT REPORT WRITING ................................................................. 72
8.1. Introduction ......................................................................................................... 72
8.2. Report and its classifications............................................................................... 73
8.3. Preparatory steps in writing reports..................................................................... 75
8.4 Principles of organizing and writing report......................................................... 78
ANNEX .............................................................................................................. 86
Bibliography .............................................................................................................. 94

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CHAPTER ONE INTRODUCTION
1.1 Purpose and contents of this manual
This manual is intended to improve the skills of the workshop participants in monitoring
the impacts of a project (long term), understand the current food security situation of an
area, and to warn the concerned agencies about future prospects of food security situation
in an area. Methodologies and conceptual frameworks of nutritional assessments, market
survey and crop and livestock assessments and report writing are included in the manual.
The manual consists of eight chapters. The first chapter deals with nutrition assessment
methods, objectives of nutritional assessments, and concepts of household food security
and mal-nutrition. Different types of sampling methodologies with special emphasis to
two-stages cluster sampling were dealt in the second chapter of the manual. Furthermore,
other major points like practical steps to undertake nutritional survey, data to be
collected, nutritional indices and their meanings, means of expressing nutritional indices,
interpretation of nutritional indices, causes of malnutrition and report outline were
included in the third chapter of the manual. The fourth chapter explains how to weigh and
measure children. The measurements that are presented are standing height, recumbent
length, weight and mid-upper arm circumference.
How to use EPI Info computer software, market survey, crop and livestock assessment
checklist and report writing were discussed in the 5th
, 6th
, 7th
and 8th
chapters respectively.
Some important materials like definition of terms, formulas and others were also attached
as appendixes.
The materials used in this manual were extracted from different nutrition guidelines such
as that of Disaster Prevention and Preparedness commission, Manuals prepared by UN
Department of technical co-operation and statistical office, Oxfam practical guides, MSF
nutrition guidelines and WHO nutrition manuals. (For more detail, see the bibliography
attached).
1.2 Food Security Concepts
World Bank defines food security, as access by all people at all times to enough food for
an active and healthy life. Its' essential elements are the availability of food and the
ability to acquire it.
Components of food security
Availability sufficient food
safe and nutritious food
culturally acceptable
Access refers to purchasing power that they get from off-arm income, on-
farm income and credit.
Social infrastructure, market, road
community support system
food sharing
remittances
family kin-ship (go to relative to get food)

5. 5
Utilization refers to food quality, better preparation, proper handling, and processing
Asset creation
Asset is stock that can be changed to cash through time. The followings are some of the
examples of assets. Livestock, perennial crops, community wood lots, skill and
knowledge, savings are examples of assets.
Community copping mechanisms are also considered as assets such as cash, credit, sell of
small ruminants, temporary migration, animals, seeds, implements and distress migration.
Food Security Indicators
Food supply indicators
 meteorological data
 access to resources
 agricultural production data
 market information
 pest damage
 Infrastructure
 Regional conflict
Food access indicators
 Land use practice
 Dietary change
 Change of food sources
 Change of income sources
 livestock sell
 access to credit
 seasonal migration
 distress migration
Out come indicators
 household budget and expenditure
 food consumption frequency
 subsistence potential
 nutritional status
 storage estimate
Food insecurity: - a situation in which the individuals of a society have neither the
physical nor the economic access to the nourishment they need.
Two types of food insecurity are commonly identified in Ethiopia (Chronic and acute
food insecurity).
Chronic food insecurity: - it is when a household is continually unable to meet the food
needs of its members.
Acute/transitory food insecurity: - this occurs when a household faces a temporary
problem in meeting the food needs of its members.

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Malnutrition can occur when any of the different types of food insecurity are present. The
manual emphasizes mainly on transitory food insecurity situations and methods of
identifying it.
Main points
Food is central to both household food security and nutrition
Food has important contributions on diet quality
Under-nutrition synonymous with food insecurity at the same time under-nutrition can be
independent of food insecurity.
Anthropometric data used as key indicators for food security monitoring and famine early
warning system.
The examination of the causes of under-nutrition using UNICEF conceptual framework
clarifies this more. See figure 1
1.3 Nutritional assessment methods
Dietary methods: - intake assessment (affected by drugs, dietary components and disease)
Laboratory methods: - dark adaptation (vitamin A), taste acuity (zinc), capillary fragility
(vitamin C), and cognitive function (iron)
Clinical methods: - medical history and physical examination
1.4 Objectives of emergency nutrition assessment
General objectives: -
For disaster prevention and preparedness, relief planning and management and designing
of development programs.
Specific objectives:
Long-term: -Supplement to Early Warning Information and disaster prevention
Establish baseline data
Understand trends
Detect differences
Identify areas at chronic risk
Mid term: -Preparing action
Nutritional monitoring
Short term: -Make decision in planning and management of food relief
Where food relief should be planned
When to start or terminate food relief
Set priorities (screening)
Select for selective feeding program
Monitor nutritional status
Evaluate: relevance, effectiveness and impact of food relief

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CHAPTER TWO SAMPLING METHODOLOGIES
2.1 Fundamentals of sampling
If all children aged 6-59 months from a given population were measured, we would get a
precise picture of the nutrition status of the population. This is called a census, or
exhaustive survey, and it is possible in a small population. However, census is normally
long, costly and difficult to carry out in a large population. Instead of surveying all the
children, we normally survey only a sub-group of the population, called sample, which
represents the whole population.
2.2 Sampling frame and sampling unit
A sampling frame is a comprehensive list of all states, provinces, regions, zones, districts,
and communities, households or individuals in the population from which you can choose
your sample. The sampling unit is the smallest unit to be sampled example, household in
household study.
2.3 Types of sampling
There are two types of sampling, Probability sampling and non-probability sampling.
For our purpose we will try to see four main probability sampling methods commonly
used.
Probability sampling: - In probability sampling, each sampling unit has an equal
probability of being sampled. See the followings probability sampling methods.
a. Simple random sampling: -
 It is the simplest form of the probability sampling
 Each household is listed with a number
 The households are then randomly chosen for the survey
 The selection of one household is independent of the selection of another
household
 The least bias with this method is choosing the sample using random table,
currency notes etc. But it is also the most expensive and time consuming
often difficult in rural settings.
b. Systematic sampling
A modification of simple random sampling that picks every nth
household from list of
households. Every household should still have the same chance of being surveyed and
must ensure that the list is not ordered in any regular way that would bias your sample.
(E.g. listing of chief first). Potential for bias if the first household is not chosen randomly)
Steps
 List population
 Calculate sampling interval
 Choose a number between 1 and the sampling interval
 That number identifies the first sample
 Then add the sampling interval to that number (above) and continue like that until
you get your n.

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c. Stratified sampling
Suppose we need to select a sample from population of a city and we want households
with different income levels to be equally represented in the sample. Instead of selecting
a simple random sample or systematic random sample, we may prefer to apply different
techniques. First we divide the whole population in to three different groups of low,
medium and high-income levels.
We have now three sub-populations, which are usually called strata. We then select
samples from different strata. The sample size to be selected from each stratum depends
up on the size of population of the strata. In rural settings, one can identify three different
agro-ecological zones (highland, mid-highland, and lowland) and we can similarly
calculate the sample size from each agro-ecological zones using Proportion to population
size (PPS).
d. Two stage cluster sampling/used for nutritional survey
List of every household are not available to random sampling. It is usually too expensive
and time consuming to construct such a list and then to locate those households. Cluster
sampling selects groups of households that are close to each other.
Developing sampling frame in two stage cluster sampling
Stage one selecting the cluster
 Determine the geographical units and their population
Cluster sampling requires the grouping of the population in smaller geographical
units. The smallest available geographical unit is always chosen as long as its
population can be estimated. The units can be villages, sections of a camp, or
naturally defined geographic areas (rivers, roads).
We take villages as the smallest geographical unit in Ethiopia. Hence, we prepare a list of
existing peasant associations and villages that will be included in the sampling frame
with their estimated population or number of households.
 Calculation of the cumulative population
A list of section/village is established, as well as their respective population. In a third
column, the cumulative total is calculated by adding the population of each unit to the
sum of the population of the preceding sections. See the following example, where we
take PAs as geographic unit and cumulative population was calculated for children under
five.
Geographical
unit or PAs
Estimated
population
Estimated
children
(6-59 moths) Cum. Pop.
Attribute
numbers
Location
of
clusters
PA1 3000 600 600 1 - 600 1, 2
PA2 2230 446 1046 601 - 1046 3
PA3 1324 265 1311 1046 - 1311 4
PA4 2340 468 1779 1311 - 1779
Etc.
Total

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To calculate cumulative population, we can either use the total population or estimated
children under five. The population of under-five is usually 20% of the total population in
the area.
 Calculation of the sampling interval
The sampling interval, in cluster sampling, is the total number of population divided by
the desired number of clusters, usually 30. Example 333
 Determination of the location of the first cluster
Select a random number between 1 and the sampling interval calculated in the above
section (333). It could be obtained from random number table or serial number on bill of
money. (See how to use random number). That random number identifies the first village
or cluster to be surveyed. Example 256. This number places the first cluster in locality 1
because it has the attribute number 1-600.
 Selection of the other clusters: Add the sampling interval sequentially to the
starting (random number) until 30 numbers are chosen. Each number chosen
represents the population of a geographic unit. In our example, the first cluster is
256 (locality 1), the second cluster will be at 256+333=589 and falls in Locality 1,
again, the third cluster is 589+333=922 locality 2. The fourth
cluster is at 922+333
= 1255 locality 3. Locality=PA in our example.
Stage two Selection of households/children in a cluster
Random walk method
 Having identified the 30 clusters, a team of data collectors goes to the center of
the selected village/unit.
 Randomly choose a direction in which to walk by throwing a pen in the air, and
walking in the direction that it points when it falls on the ground.
 Walk in the direction indicated by the pen, from the center to the outer perimeter
of the locality, counting the number of households along this line.
 Select the first household to be visited by drawing a random number between one
and the number of households counted when walking. For example, if the number
of households counted was 12, then select a random number between 1 and 12. If
the number five was chosen, then the fifth
household on the walking line is the
first household you should visit.
 Go to the first household and examine all children aged 6-59 months in the
household.
 The subsequent households are chosen by proximity. In a locality where there is a
high population concentration, proceed always by choosing the next house to the
right or to the left (Decide which at the beginning of the survey and stick to it).
Continue to go to left/right until the required number of children has been
measured. The same method should be used for all clusters. However, if the
locality has a very spread-out population, then proceed by simply choosing the
nearest house (the one with the door nearest to the last house surveyed) whether it
is on the right or left. And continue the process until the required number of
children has been measured (30 children).
 If there are no children under five in the household, proceed to the next house
after collecting other data like mortality and morbidity.

10. 10
 All eligible children are included and thus should be measured and weighed. This
means that all children in the last house should be measured even if it exceeds the
number required.
 If a child is not present at the time of the survey, go back to the house later to find
the child. If you cannot find the child then you need to replace it with another by
continuing the sampling methodology.
 If you run out of houses in a locality and have not found sufficient children then
you should proceed to the nearest locality. When you arrive the nearest locality
you should repeat the process of spinning a pen and randomly selecting a house to
start at (1-8 steps described above). Proceed from house to house until you have
measured sufficient children.
 Segmentation method
Divide the selected clusters into smaller segments of approximately equal size
Choose one segment randomly from clusters
Interview/measure all children in that chosen segment
2.4 Calculating sample size
For cluster sampling, number of children to be measured is usually 900 (30 clusters by 30
children). For other survey methodologies we need to calculate number of children to be
measured. Sample size needed is related to the following factors.
 The expected precision: - The greater the precision desired the more
households needed in the sample.
 The probability of error chosen: - The smaller the probability, the more
households needed in the sample
 Expected prevalence: - the nearer the expected proportion of children
presenting with malnutrition is to 50%, the greater the sample size required.
 The available means: - the ideal objective in determining the sample size is
to have the highest degree of precision for the smallest error risk. The limiting
factor is the available means. How many children can be surveyed in a day? How
much time do we have? How much money do we want to spend?
Sample size calculation
n = Z2
(pxq)(deff)
d2
Z = parameter related to the error risk, equals 1.96 for an error risk of 5%
P = expected prevalence of malnutrition in the population, expressed as a fraction of 1
q. = (1-P), expected proportion of children not presenting with malnutrition expressed
as fraction of 1
Deff = the expected design effect, 2 is commonly used for nutrition surveys
(cluster sampling)
d = absolute precision, expressed as a fraction of 1

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For Non-Cluster sampling we use the following formula
n = Z2
(pxq)/ d2
2.5. Practical steps to undertake a nutrition survey
 Decide whether or not the survey is necessary
 define objectives
 define geographical target area
 meet the people in charge
 determine timing
 select sampling method
 gather available information
 Decide what information to collect and design questionnaire
 Obtain and prepare equipment
 Field test questionnaires
 Select survey team
 Train survey team members
 Implement the survey
 Analyze and interpret your findings during the survey
 Write the report
2.6 Data to be collected
During Anthropometric survey the following basic data need to be collected.
 Weight
 Height/length
 Age
 Sex
 Oedema
 Other data like
 Mortality,
 Morbidity,
 Family size
 Vaccination coverage,
 Food security
 Copping mechanisms,
 Operational and relief activities,
 Causes of crises and agro-political context,
 Nutritional status and diet of the population
 Population figures, population movement and vulnerable groups.
 And so on.

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CHAPTER THREE ANTHROPOMETRIC INDICES, ANALYSIS
AND INTERPRETATION OF RESULTS
3.1. Anthropometry defined
Can be defined as the single most universally applicable, inexpensive, and non-invasive
method available to assess the size, proportions and compositions of the human body. Or
one can say Anthropometry is body measurement such as weight, height, and arm
circumference, which, are used as a direct, measures of an individual's nutrition and
growth (their nutrition status). Data such as low birth weight, stunting, thinness, and
overweight are obtained from measurements of height and weight. They reflect
inadequate or excess food intake, insufficient exercise and diseases.
3.2. Nutrition indices: -
Indices are a combination of measurements compared to a reference population.
Measurements such as weight or height alone do not give sufficient information on
nutritional status when analyzed individually. The combination of weight and height
make sense only when compared to a normal value, derived from a reference population.
Such combinations of measurements compared to a reference value are called indices.
There are about five nutrition indices discussed in this manual.
1. Weight for height index
 It expresses the weight of a child in relation to his height
 It is measure of current status
 Low weight for height is called wasting, some times called acute malnutrition
 It is very sensitive to the loss of weight, which can be influenced by illness, low
food consumption, or poor care.
 It reveals whether the child is thin or not, but does not discriminate between two
children of the same height and weight one being older than the other, and
possibly stunted.
 Errors can be made in height/Length measurements
 Very good indicator of short term problems i.e. famine or epidemics
 Not a good long-term indicator for monitoring and evaluation
Advantage: - does not depend on knowing the child's birth-date
2. Height for age index
 It expresses the height of a child in relation to his age
 Measure of long-term growth
 Low height for age is called stunting, some times called chronic malnutrition
 Good long-term indicator of general welfare (directly affected by food
consumption, health and care)
 Not sensitive to short term fluctuations
 Once stunting occurs, child may not catch up
 Errors can be made in measurement of height or age
 Does not discriminate between two children of the same age and height, one being
thin (wasted), the other one being heavier

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3. Weight for age index
 It expresses the weight of a child in relation to his age
 It is a composite measure
 Low weight for age is referred to as underweight, meaning less than expected
weight for a given age and sex
 Low weight for age can reflect either stunting or wasting
 Most useful as a monitoring indicator
 Errors can be made in determining age
 Does not allow differentiation between two children of the same age and weight,
one being tall and thin (wasted), the other shorter but not wasted.
4. Mid upper arm circumference/MUAC
 Can be measured on all ages
 Can give a quick estimate of wasting in a population
Theoretically, it correlates to WFH, but is a cruder measure and not as accurate. WHO
actually recommends using WFH instead, even in extreme emergency situations.
5. Body mass index (BMI)
A numerical index of the weights and heights of adults used as a basis for making
comparisons.
BMI = Weight in kg/(Height in m)2
 Measure of current status
 Sensitive to short term gains and losses in weight
 Can be used with all ages, so tends to be used for adults
 No standardization required, so independent of age
3.3 Means of expressing nutritional indices and indicators
a. The Percent of the median: - the ratio of a measured value in the individual, (for
instance weight) to the median value of the reference data for the same age or height,
expressed as a percentage. The index of weight for height median compares the weight of
the measured child to the median weight of children of the same height in the reference
population. The calculation of a WHM for each child is based on the child's weight.
Percent of the median = (individual weight/median reference weight) x100
b. The Z scores: - The Z scores express a child's weight as multiple of the standard
deviation of the reference population. A Z score is a measure of how far a child is from
the median weight of the reference population for children of the same height, taking
into account the standard deviation of the reference population.
Z score = Observed value of individual child - median reference value
Standard deviation of children of same height (reference population)
Example: - In a nutritional survey a male child of 84 cm height weighs 9.9kg. The
reference median weight for boys of 84 cm is 11.7kg. We can also see that the standard
deviation for the reference distribution for boys of height 84cm is 0.908.
Hence Z-score will be 9.9-11.7/0.908=-1.98

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c. The Percentile: - The rank position of an individual on a given reference
distribution, stated in terms of what percentage of the group the individual equals or
exceeds.
3.4. Nutrition indicators
Nutrition indicators are an interpretation of nutrition indices based on cut-off points.
Whereas, indices are simply figures, indicators represent an interpretation of the indices.
Nutrition indicators are used for making a judgment or assessment.
Cut -off points for describing nutritional status
Status Z-score % of median Percentile MUAC
Moderate acute
malnutrition
between -3
and <-2
between 70%
and <80% 3rd
to 5th
between 11cm
and <12.5cm
Severely
malnourished
<-3.0 or
oedema
<70% or
oedema <3rd
<11cm or
oedema
Global Acute
malnutrition
<-2 or
oedema
<80% or
oedema
<12.5cm or
oedema
Results expressed in different methods are not directly comparable
3.5 Causes of malnutrition
The objectives of most emergency nutrition assessments include trying to understand
what the causes of malnutrition are. Malnutrition starts with either the failure of an
individual to acquire enough to eat, or ill health, which is known as immediate causes of
malnutrition and they frequently occur together. In turn these immediate causes are
determined by numerous underlying and basic causes. (See figure 1).
Adequate nutrition is the means, by which people thrive to maintain growth, resist and
recover from diseases and perform their daily tasks. When nutrition is inadequate,
vulnerable populations are likely to become malnourished. Malnutrition includes a wide
range of clinical disorders in which an individual's physical functions are handicapped.
Common consequences of malnutrition include growth failure, decrease resistance to
disease and reduced ability to work.
It is extremely important to understand the causes of malnutrition in order to plan and
undertake appropriate response and intervention. The cause of malnutrition should
always determine the intervention. For example, if malnutrition is due mainly to
infectious diseases, then it would be more appropriate to respond with a health
intervention.

15. 15
Fig. 1 UNICEF's conceptual framework of the causes of malnutrition.
IMMEDIATE CAUSES
Affecting the individual
UNDERLYING CAUSES
At the community or HH level
LOCAL PRIORITIES
BASIC CAUSES
FORMAL AND INFORMAL INFRASTRUCTURE
POLITICAL IDEOLOGY
RESOURCES
Human
Structural
Financial
Basic causes for malnutrition and death (potential resources human economic and
organizational resources and control)
Underlying causes: - insufficient household food security, inadequate maternal and
childcare and insufficient health services and unhealthy environment.
Immediate causes: - inadequate dietary intake and diseases leading to malnutrition and
death.
MALNUTRITION
HOUSEHOLD FOOD
SECURITY
Access to food
Availability of food
ADEQUATE CARE OF
WOMEN AND
CHILDREN
Access to health care
Direct caring behaviors
Women's' role, status and
rights
Social organization and
network
PUBLIC HEALTH
Basic health services
Health environment
INADEQUATE FOOD
INTAKE
DISEASE

16. 16
3.6. Data analysis, Interpretation of results and recommendations
3.6.1. Data Analysis
Data analysis means studying the organized material in order to discover inherent facts
and the data is studied from different angles to explore new facts.
Data preparation and cleaning
Missing data: If we are missing any important data (sex, weight, height, age, oedema) on
any of the children, then we cannot include this child in our analysis. For example, if data
on oedema is missing then we cannot know whether or not the child is malnourished.
Data out of required range: - Children outside of the standard range like 6-59 months of
age and 65-110 cm height should not be included in our analysis. (DPPC
guideline…pp105)
Extreme weight for height data: - As well as excluding children who have information
missing, or who are out of the required range, we also exclude children who have an
extremely high or low WFH index during data cleaning. By extreme we mean
biologically unlikely. It is very unusual to find any child with a WFH <-4.00 or >+6.00 Z
scores. In very extreme famine conditions, where many children are severely
malnourished, it is possible that there may be children with WHZ <-4.00 and that the
results are not false. In this case you can change lower level of exclusion to WHZ<-5.00.
Data analysis is composed of two parts:
There are two approaches when presenting and analyzing results:
Descriptive analysis consists of building distributions according to the variables and in
interpretive analysis cross tabulations are used to make comparisons between groups.
These two approaches are complementary. If the survey objectives are to quantify the
number of children who may benefit from intensive feeding program or from
supplementary rations based on a cut-off value of the index, the first approach is
appropriate. However, if the objective is to assess the overall impact of a program on the
whole population of children, the second approach is preferred. In this part, we will see
the first approach.
A. Descriptive analysis
1. Distribution according to age and sex, children 6-59 months, region X, period Y
Age in
months
Boys Girls Total
n % n % n %
6-17
18-29
30-41
42-53
54-59
Total

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2. Distribution according to the WFH index expressed in Z scores or presence
of oedema, by age, region X, period Y
Age in
months
Severe
malnutrition
<-3 Z scores
Moderate
malnutrition
>=-3 &<-2
Normal children
>=-2 Z scores Oedema
n % N % n % n %
6-17
18-29
30-41
42-53
54-59
Total
Children with oedema should not be included in the Z score column
Global Acute malnutrition
Proportion of children with a weight/height index <-2 Z scores or oedema
(Severe Acute Malnutrition + Moderate Acute Malnutrition)
Severe Acute malnutrition = proportion of children with a weight/height index <-3 Z
scores or oedema
Moderate Acute malnutrition = proportion of children with weight/height index
>= -3 and <-2 Z scores
Normal children = proportion of children with weight/height index >=-2 Z score
A distribution table can be drawn up using the value of index and presence of oedema in
order to determine the number and proportion of children presenting:
Kwashiorkor: Oedema + index > -2 Z scores
Marasmus/Kwashiorkor: Oedema + index <-2 Z scores
Marasmus: No Oedema + Index < -2 Z scores
Normal: No oedema + index > -2 Z scores
Weight/height index
< -2 Z scores >= -2 Z scores
Yes
Oedema
No
Marasmus/Kwashiorkor Kwashiorkor
Marasmus Normal

18. 18
B. Interpretive Analysis
Some variables can be cross-tabulated. For example, nutritional status (defined according
to a cut-off value) of the weight/height index and the date of arrival in the camp.
Nutritional status according to the date of arrival, children 6-59 months, region X,
period Y
Malnourished Not Malnourished Total
Last arrived
First arrived
In cluster sample survey figures should not be analyzed for each cluster. It is the whole
section, which is representative of the population.
3.6.2. Interpretation of results
Interpretation refers to the task of drawing inferences from the collected facts after
analytical and/or experimental study. The task of interpretation has two major aspects.
a. The establishment of some explanatory concepts
In one sense, interpretation is concerned with relationships within the collected data,
partially overlapping analysis. Interpretation also extends beyond the data of the study to
include the results of other research, theory and hypothesis. Thus, interpretation is the
device through which the factors that seem to explain what has been observed by
researcher in the course of the study can better understood and it also provides a
theoretical conception, which can serve as a guide for further researches.
Accordingly, the result of our nutrition survey could be compared to the following
standard prevalence of low Anthropometric values (<-2SD) for under five children.
(DPPC guidelines 2002)
Indicators Stage of Alert
Global Acute Malnutrition prevalence >=20%
AND/OR
Severe acute malnutrition prevalence >=5% Critical
Global Acute Malnutrition prevalence 15-19%
AND
Aggravating factors
Global Acute Malnutrition prevalence 15-19%
Serious
Global Acute Malnutrition prevalence 10-14%
AND
Aggravating factors
Global Acute Malnutrition prevalence 10-14%
PoorGlobal Acute Malnutrition prevalence 5-9%
AND Aggravating factors
Global Acute Malnutrition prevalence 2-9% Normal for chronically malnourished
population.

19. 19
Potential aggravating factors include
 Epidemics of measles, cholera, shigelloses and other important communicable diseases.
 Poor household food availability
 Inadequate shelter and severe cold
 Low levels of measles vaccination and vitamin A supplementation
 Inadequate safe water supplies (quality and quantity) and sanitation
Consideration of aggravating factors is an essential part of a good interpretation of anthropometric data. If more than one aggravating
factors are present then the situation may be worse than if there is just one.
Summary of nutritional survey indicators
Indicator Measures
Type of
malnutrition Program uses Problems to be aware of
WFH Current status
Wasting, Acute
malnutrition Emergency program Errors in measurement
HFA
Long term status
Past malnutrition
Stunting
Chronic
malnutrition
Development program
Program impact
Poverty indicator
Errors in measurement
Errors in birth date
Catch up problem
WFA
Composite measure of
stunting and or wasting Underweight
Child survival project
Growth monitoring with
EPI program
Errors in birth dates
Interpretation
MUAC Current status Wasting Emergency programs
High rate of error
Should follow up with a WFH
survey
BMI Current status Wasting
Emergency programs for
high risk adults

20. The classification of the severity of malnutrition rates in a population according to WHO
(WHO 2002).
Severity of malnutrition Prevalence of wasting (<-2 z scores)
Acceptable <5
Poor 5-9
Serious 10-14
Critical <=15
However, this is not suitable for use in Ethiopia due to different reasons. For decision-
making we use the above cut-off points presented in DPPC guidelines December 2002.
b. Interpretation in context
Nutrition status data only detects the symptom of malnutrition but can not explain the
causes of malnutrition. Nutrition status data should therefore, never be interpreted alone
for decision-making purpose. Corroborative information is needed to seek possible
explanations and causes for poor nutritional status and especially deterioration. In
planning response and intervention, we have to use UNICEF causal framework. High
mortality rates are also very important indicators of a crisis. See annex 3 for details.
When we interpret nutritional status data looking at copping mechanisms adopted by the
community will be very important. If a large section of the population is practicing
unusual copping mechanisms, particularly strategies that will affect their long-term
ability to survive, then this is an indication that the situation is severe.
Moreover, seasonal variations in food supply and in disease patterns will affect
nutritional status and must always be considered during the interpretation of nutritional
status data. The proportion of malnutrition observed in the sample can be compared to
malnutrition rates observed in a previous survey. If there is information from different
surveys, some idea of the trend in nutritional status can be inferred. One can only
conclude that there was statistically significant difference between two surveys if
confidence intervals do not overlap or P-value <0.05.
Example of variation of nutritional status in different seasons
Season
Global Acute Malnutrition
Woreda 1 Woreda 2 Woreda 3
No % No % No %
Belg 2002 900 36.7% 899 36% 912 32%
Meher 2001 905 22.9% 900 20% 900 19%
P-value
3.7. Differences between results expressed in percentage of the median & z-scores
When the results of malnutrition is expressed both in percentage of the median and Z
scores, it may lead to some confusions during interpretation. Malnutrition expressed in
percent of the median and Z-scores are not the same. Typically the prevalence of
malnutrition is higher in Z scores than in percentage of the median (often about 1.4 times
as much).

21. 21
When the prevalence of acute global malnutrition shows a difference >=5% between the
results expressed in percentage of the median and z-scores, it is necessary to consider the
prevalence of severe malnutrition and mortality rate to correctly interpret the results.
3.8. Expression of results with their confidence intervals
When calculating the sample size, the notion of precision was introduced. This is the
reason why the proportion of children presenting with malnutrition should be expressed
with a corresponding precision, which determines the 95% confidence interval. The
confidence interval is the prevalence found plus or minus the precision achieved.
Calculation of the precision uses the formula already used for determining the sample
size (n), but in another way. As a mater of fact, when calculating the sample size (n), an
expected prevalence (p) was estimated and a desired precision (d) was used. Now that the
survey has been carried out, the approach is reversed: the sample size is known, and the
prevalence has been measured, what is going to vary is the precision achieved.
Simplified formula for calculation of cluster survey precision:
d = Zx2xpq/n
Z = 1.96
P = proportion of children with malnutrition
q. = Proportion of children with out malnutrition
Therefore, a 95% confidence interval is
C.I. = p+d
Confidence interval could be calculated for both Global Acute Malnutrition and Severe
Acute Malnutrition.
For non cluster sampling d = Zxpq/n
Recommendations to be drawn from nutrition survey results
1. General ration :-It is intended to provide every body with their nutritional
requirement.
2. Supplementary feeding: - It is set up to treat children who are moderately
malnourished and to prevent severe malnutrition and vulnerable groups could be
included.
3. Therapeutic feeding: - Intended to rehabilitate severely malnourished children
and adults through intensive feeding of special food and health care.
4. Health care especially in therapeutic feeding programs.
3.9. Analysis of Mortality rates
High mortality rates are very important indicators of a crisis. If the rates of both acute
malnutrition and mortality rates are high, then it is clear that you have a more serious
situation than if the malnutrition rates are high and crude mortality rate is low.
The following table shows some rates for crude and under five mortality in developing
countries and stage of alert (USAID 200). We can use the table as a guide to classifying
the stage of alert with regards to mortality, but remember that the classification was not
specifically designed for Ethiopia.

22. 22
Mortality rates and stage of alert
CMR U5MR
Average for developing
world 0.27 deaths/10,000/day 1.0 deaths/10,000/day
In an emergency not critical <1 deaths/10,000/day <2 deaths/10,000,day
In emergency serious 1-2 deaths/10,000/day 2-4 deaths/10,000/day
In an emergency out of
control > 2 deaths/10,000/day >4 deaths/10,000/day
For more details see annex 3, the standard that is widely used.
3.10. Reporting
A report should have at least the following contents
1. Summary of the Report (1-2 pages only)
Area surveyed
 Date of survey
 Methodology employed
 Main anthropometric results (prevalence of global & severe acute malnutrition in
terms of z-score and/ or oedema and 95% confidence intervals)
 Other important results (mortality rates, food security indicators etc)
 Explanation of the causes of malnutrition in the area
 Recommendations
2. Introduction
Description of survey area
 Survey area
 Name of town/ woreda/ zone/ region/ country
 Name of nearest large town / city – administrative center
Population data
 Number of people living in survey area
 Population density
 Ethnic group
Geography of area
 Town / camp/ rural etc
 Altitude/ mountainous / flat etc
 Total area (hectares)
 Way in which people live
 Agriculturalists/ pastoralists / agro-pastoralists / refugees / merchants etc
 Type of land farmed or animals kept
Any important political/ security information
 If refugees, how long have they been there
 Any instability in the area
Services available
 Health
 Education
 Markets, roads

23. 23
Assistance received by the population
 Relief program in area
 Number of people on food aid etc
 Other initiatives, particularly work of your agency in the area
Date survey undertaken
Other survey results from the area or nearby areas
3. Survey Objectives
For example,
 Estimate the prevalence of acute malnutrition
 Estimate retrospective mortality rates
 Understand the causes of malnutrition
 Estimate the coverage of a feeding program
 Estimate the measles vaccination rate
 Make recommendations for a program
4. Methodology
General approach
 Type of sampling (for example, 30*30 cluster)
 Age of children measured
 Number of children measured
 Date of survey
Sampling procedure and Sample size
 How did you choose the clusters?
 What population figures did you get and who from (for example, kebele population
figures from woreda council)?
 How did you calculate the sampling interval (for example, the cumulative population
was calculated and a sampling interval determined)?
 How did you assign the clusters (for example, thirty clusters were randomly selected
by assigning probability proportional to population size)?
 Did you alter the method from the standard method at all (for example, because of
insecurity etc.)?
 Describe any changes to the selection of the clusters during the survey.
Selection of Households and Children
 How did you choose the households and children within a cluster?
 Where was the starting place? (Middle of the kebele? Or did you randomly choose a
Village within a kebele and start in the middle of the village)
 How did you choose the direction to follow? (Spin a pen?)
 Did you walk to the end of the village/kebele and count the houses?
 How did you choose subsequent houses?
 How did you choose children within the houses?
 Did you measure all children aged 6-59 months in the houses selected?

24. 24
 If age was unknown how did you decide whether or not to measure children? (Height
between)
 What happened when the child was away?
 Did you measure all children in the last house?
5. Training and Supervision
 Who was trained?
 Who did the training?
 What did the training cover (survey design, anthropometric measurements, signs and
symptoms of malnutrition, data collection and interview skills)?
 Did the survey teams measure children and compare their results? (Inter-observer
error)?
6. Pilot survey
 Was there a practice/ pilot survey?
 Who supervised the teams during the practice survey?
 Were data collection forms piloted during the practice survey and changes made to
them if necessary?
7. Supervision during the survey
 Who supervised the teams (a nutritionist, a nurse or someone else)?
 How many times did the supervisor visit the teams?
 Who were the team leaders, were they experienced?
8. Data Collected
Children’s data
 Anthropometric data
 Age, proxy heights used for age
 Weight (type of scales used, precision of measurement)
 Height (type of height board used, how children were measured (standing-up/
lying down/ both), precision of measurement)
 Oedema (how did you define oedema)
Retrospective morbidity of children
 Who did you ask about the children’s illness?
 Over how long were questions about illness asked?
 How did you define illness?
Vaccination Status and Coverage
 How did you check for vaccinations?
 Did you look at MCH cards?
Program Coverage
 How did you assess this?
 What did you do if you found a malnourished child who was not registered?

25. 25
Mortality data
 Which households did you ask the mortality questionnaires to?
 Over how long did you estimate mortality (number of months)?
 Did you categorize deaths by age?
 Did you record cause of death? How did you define causes?
Household questionnaires
 How were the household questionnaires developed?
 Were the questionnaires adjusted after the practice survey?
 What kind of data did you collect in the household questionnaires (health/food
security/care/relief)?
 Were the data qualitative or quantitative?
 Who did you ask the questions to (how many households, which people in the
household)?
Key informant questionnaires and interviews
 How were the key informant questionnaires developed?
 Were the questionnaires adjusted after the practice survey?
 What kind of data did you collect in the key informant questionnaires (health/food
security/care/relief)?
 Were the data qualitative or quantitative?
 Who did you ask the questions to (community leaders/ women etc)?
 Did you visit any woreda officials? Who? For what information? Any other NGOs?
9. Data analysis
 How did you analyze the data?
 What type of computer program did you use or did you do it by hand?
10. Results
Anthropometric Results:
Definitions of acute malnutrition should be given (e.g., global acute malnutrition is
defined as <-2 z scores weight-for height and/or oedema, severe acute malnutrition is
defined as <-3z scores weight for height and/or oedema)
The following tables should be included in the result part of the report.
Table 1: Distribution of age and sex of sample
Age
(mth)
Boys Girls Total Ratio
No. % No % No. % Boy: Girl
6-17
18-29
30-41
42-53
54-59
Total

26. 26
Table 2: Prevalence of acute malnutrition based on weight for height z-scores and/or
oedema
6 - 59 months
n=
6 - 29 months
n=
Prevalence of global malnutrition
(<-2 z-score and/or oedema)
(no.) %
(95% C.I.)
(no.) %
(95% C.I.)
Prevalence of severe malnutrition
(<-3 z-score and/or oedema)
(no.) %
(95% C.I.)
(no.) %
(95% C.I.)
The prevalence of oedema is ____ %
Table 3: Prevalence of malnutrition by age based on weight for height z-scores and
oedema
Severe
Malnutrition
(<-3 z-score)
Moderate
Malnutrition
(>= -3 and <-2
z-score)
Normal
(> = -2 z score)
Oedema
Age
(mths)
Total
No
No. % No. % No. % No. %
06 - 17
18 - 29
30 - 41
42 - 53
54 - 59
Total
Table 4: Distribution of acute malnutrition and oedema based on weight for height
z-scores
<-2 z-score >=-2 z-score
Oedema present Marasmic Kwashiorkor
No.
(%)
Kwashiorkor
No.
(%)
Oedema absent Marasmic
No.
(%)
Normal
No.
(%)
Table 5: Prevalence of acute malnutrition based on the percentage of the median
and/or oedema
6 – 59 months
n=
6 - 29 months
n=
Prevalence of global acute
malnutrition
(<80% and/or oedema)
(no.) %
(95% C.I.)
(no.) %
(95% C.I.)
Prevalence of severe acute
malnutrition
(<70% and/or oedema)
(no.) %
(95% C.I.)
(no.) %
(95% C.I.)
The prevalence of oedema is ___ %

27. 27
Table 6: Prevalence of malnutrition by age based on weight for height medians and
oedema
Severe
Malnutrition
(<70% median)
Moderate
Malnutrition
(>=70% and
<80% median)
Normal
(> =80%
median)
Oedema
Age
(mths)
Total
No
no. % no. % no. % no. %
06 - 17
18 - 29
30 - 41
42 - 53
54 - 59
Total
Table 7: Mean percentage of the median weight-for-height
6-59 months
n=
6-29 months
n=
Mean percentage of weight-for-
height median
%
(95% C.I.)
%
(95% C.I.)
Children’s morbidity
Table 8: Prevalence of reported illness in children in the two weeks prior to
interview (n=)
6-59 months
Prevalence of reported
illness
%
Table 9: Symptom breakdown in the children who reported illness in the two weeks
prior to interview (n=)
6-59 months
Diarrhoea %
Cough %
Fever %
Measles %
Other %
Vaccination Results
Table 10: Vaccination coverage: BCG for 6-59 months and Measles for 9-59 months
BCG
n=
Measles (with card)
n=
Measles
(With card or confirmation from
mother) n=
YES (No.) %
(95% C.I.)
(No.) %
(95% C.I.)
(No.) %
(95% C.I.)

28. 28
Mortality Results (retrospective over.__ Months prior to interview)
The Crude Mortality Rate (CMR) for the total population is estimated at:
Deaths/10,000/day
The under-five Mortality Rate (U5MR) for the population is estimated at:
Deaths/10,000/day
Main causes of death.
The mean household size is calculated as. (Mode =, range)
Programme Coverage
The program coverage = 100 * number of registered malnourished children
Number of malnourished children found
Causes of malnutrition
Quantitative data
Give proportions, or use frequency tables and/or bar charts to show the results of the
quantitative data
For example, in answer to the question what was the main source of staple food over last
month?
43% sourced their main staple from EGS.
20% sourced their main staple from purchasing.
18% sourced their main staple from the sale of assets.
17% sourced their main staple from their own production.
Source of staple Proportion
EGS 43%
Purchasing 20%
Sale of assets 18%
Own production 17%
Qualitative data
 Leave this for the discussion
11. Discussion
Nutritional status
 Discuss sample sex ratio – any bias? If so, explain why you think there is bias.
 Prevalence of acute malnutrition
 If previous survey results are available, how do these results compare to before or to
other areas nearby?
 How does the prevalence compare to national international benchmarks of
malnutrition (e.g., DPPC, MSF or WHO)?
 What is the community’s current food source? What are they eating?

29. 29
Food security
Agriculture
 General discussion on agricultural practices in the area (Belg-dependent/ meher-
dependent etc)
 Current situation – try to compare to a normal year. What are the farmers doing now?
What would they normally be doing?
 What are the prices of the agricultural products compared to other years? Seasons?
 Future prospects – for the next 3-6 months. What are the constraints (no seeds, rain
etc)
Livestock
 Uses of livestock in the area
 Current pasture and livestock condition
 Terms of trade data compared to other years/seasons/areas?
 Future prospects - what are the constraints?
Relief
 Amount and type of relief food going into the area
 Who is receiving the relief
 Is the targeting working (what are the constraints)
 What is future plans for relief?
 What other relief projects are ongoing (restocking, supplementary feeding etc) and
what effects are they having on the community?
Income generating activities & migration
 What are they?
 Are they normal for this time of year?
 Are more people than normal migrating to find work?
 Are whole households migrating? Why?
Health & Care
Mortality rates
 CMR and U5MR compared to international benchmarks
 Causes of death – any epidemics?
Morbidity
 Rates reported by mothers for children.
 Any epidemics?
 Possible effects of morbidity reported on nutritional status
Vaccination
 Rates and 95% confidence intervals for different vaccination rates
 Any recent campaigns
 Are rates high or low compared to internationally recommended standards?
Mother’s caring practices

30. 30
 Information from questionnaires
 General information from discussions and observations
 Possible effects of caring practices on nutritional status
General health care in area
 Number of clinics etc for the population (compare to Government policy guidelines)
 Health education programs
 Access to clean water etc
 Living conditions
 Possible effects of health care on nutritional status
12. Program Coverage
 Rate of coverage for any SFP/TFC programs
 Explanation for rates (good/bad/why)
 Given the prevalence of malnutrition found, how many children should be enrolled?
13. Conclusions
 Diagram to show causal framework of malnutrition may be useful to show the most
important factors affecting nutritional status, or food security in the study area.
 Nutritional status
 Food security
 Health and care
 Other issues
14. Recommendations and Priorities
Remember to prioritize recommendations and try to put a time for when action should be
appropriate (e.g., immediate, medium term or longer term).
Food security
 Does the amount of relief food need to be increased? How should it be provided –
EGS / free general ration / supplementary feeding program / blanket feeding
program? For how long should relief be given? What should the ration be? Who
should implement the program? How should the ration be targeted?
 Does the community need other inputs to promote food security
(seeds/tools/restocking/fertilizers/ water/veterinary care program)? Who should get
these inputs? Who will carry out the program?
 Are program needed to improve income generating opportunities?
Health and care
 Has there been an epidemic – has it been treated or is action still needed? Who should
act? When?
 Vaccination – do the rates need to be improved? With a campaign or by increasing
regular EPI?
 Should access to clean water be improved as a priority?

31. 31
 Is a health education campaign needed? Who will carry out the training? Who will the
beneficiaries be?
Other recommendations
Future nutrition monitoring
 Is it necessary to carry out another nutritional survey in this area in the near future?
Who should do it? Should there be any changes to the survey methodology? When
should the survey take place?
 Should there be food security indicator monitoring in this area? Who should do it?
15. References
 List all documents referred to.
Annex
 Maps of area
 Questionnaires
 List of clusters (village and kebele names)

32. 32
CHAPTER FOUR HOW TO WEIGH AND MEASURE CHILDREN
(Adapted from UN Department of Technical Co-operation
for Development and Statistics office.)
4.1 Procedures and precautions before measuring
A. Layout of the Procedures
Each step of the measurement procedures is directed at specific participants, who are
named in bold letters at the beginning of each step: e.g. 'Measurer", "Assistant", etc.
B. Two Trained People Required
Two trained people are required to measure a child's height and length. The measurer
holds the child and takes the measurements. The assistant helps hold the child and
records the measurements on the questionnaire. If there is an untrained assistant such as
the mother, then the trained measurer should also record the measurements on the
questionnaire. One person alone can take the weight or arm circumference of a child and
record the results if an assistant is not available.
C. Measuring Board and Scale Placement
Begin to observe possible places where the board can be positioned and the scale hung as
soon as you walk towards a sample household. Be selective about where you place the
measuring board and scale. It is best to measure outdoors during daylight hours. If it is
cold, raining, or too many people congregate and interfere with the measurements, it may
be more comfortable to weigh and measure a child indoors. Make sure there is adequate
light.
D. Age Assessment
Before you measure, determine the child's age. If the child is less than two years, measure
length. If the child is two years of age or older, measure height in standing position. If
accurate age is not possible to obtain, measure length if the child is less than 85-cm.
Measure heights if the child is equal to or greater than 85 cm.
E. When to Weigh and Measure
Weigh and measure after verbal information has been recorded on the questionnaire. This
will allow you to become familiar with the members of the household. DO NOT weigh
and measure at the beginning of the interview, i.e. as soon as you enter a household,
which would be more of an upsetting intrusion.
F. Weigh and Measure One Child at a Time
If there is more than one eligible child in a household, complete the entire questionnaire,
including the weighing and measuring of one child. Then proceed with the next eligible
child's questionnaire in the household. DO NOT weigh and measure all the children
together. This can easily cause confusion and will create a greater chance for error such
as recording one child's measurements on another child's questionnaire. Return measuring
equipment to their storage bags immediately after you complete the measurements for
each household.

33. 33
G. Control the Child
When you weigh and measure, you must control the child. The strength and mobility of
even very young children should not be underestimated. Be firm and gentle with children.
The mother and the child will feel your own sense of calm and self-confidence.
When a child has contact with any measuring equipment, i.e. on a measuring board, in
the weighing pants or with an arm circumference tape, you must hold and control the-
child so the child will not trip or fall. Never leave a child alone with a piece of
equipment. Always have physical contact with the child except when you must let go of
a child for a few seconds while taking the weight.
H. Coping with Stress
Since weighing and measuring requires touching and handling children, normal stress
levels for this type of survey work are higher than for surveys where only verbal
information is collected.
Explain the weighing and measuring procedures to the mother, and to a limited extent,
the child, to help minimise possible resistance, fears or discomfort they may feel. You
must determine if the child or mother is under so much stress that the weighing and
measuring must stop' Remember, young children are often uncooperative; they tend to
cry, scream, kick and sometimes bite. If a child is under severe stress and is crying
excessively, try to calm the child or return the child to the mother for a moment before
proceeding with the weighing and measuring.
Do not weigh or measure a child if:
a. The mother refuses.
b. The child is too sick or too distressed.
C. The child is physically deformed which will interfere with or give an incorrect
measurement. To be kind, you may want to measure such a child and make a note of the
deformity on the questionnaire.
Recording Measurements and Being Careful
Record the measurements in pencil. If you make an error, completely erase the error and
rewrite the correct numbers. Keep objects out of your hands and pencils out of your
mouth, hair or breast pocket when you weigh and measure so that neither the child nor
you will get hurt due to carelessness. When you are not using a pencil, place it in your
equipment pack, pencil case or on the survey form. Make sure you do not have long
fingernails. Remove interfering rings and watches before you weigh and measure. Do not
smoke when you are in a household or when you weigh and measure.
Strive for Improvement
You can be an expert measurer if you strive for improvement and follow every step of
every procedure the same way every time. The quality and speed of your measurements
will improve with practice. You may be working with a partner to form a team. If so, you
will be responsible for not only your own work, but also for the quality of work of your
team.

34. 34
You will be required to weigh and measure many children. Do not take these procedures
for granted even though they may seem simple and repetitious. It is easy to make errors
when you are not careful. Do not omit any steps. Concentrate on what you are doing.
4.2. Summary procedures for body measurement
A. Child Height Summary Procedure (Illustration 1. photo copy to be attached.)*
1. Measurer or Assistant: Place the measuring board on a hard flat surface against a
wall, table, tree, staircase, etc. Make sure the board is stable.
2. Measurer or Assistant: Ask the mother to remove the child's shoes and unbraid
any hair that would interfere with the height measurement. Ask her to walk the
child to the board and to kneel in front of the child (if she is not the assistant).
3. Assistant: Place the questionnaire and pencil on the ground (Arrow 1).
Kneel with both knees on the right side of the child (Arrow 2).
4. Measurer: Kneel on your right knee only, for maximum mobility, on the child's
left side (Arrow 3).
5. Assistant: Place the child's feet flat and together in the centre of and against the
back and base of the board. Place your right hand just above the child's ankles on
the shins (Arrow 4), your left hand on the child's knees (Arrow 5) and push
against the board. Make sure the child's legs are straight and the heels and calves
are against the board (Arrows 6 and 7). Tell the measurer when you have
completed positioning the feet and legs.
6. Measurer: Tell the child to look straight ahead at the mother if she is in front of
the child. Make sure the child's line of sight is level with the ground (Arrow 8).
Place your open left hand on the child's chin. Gradually close your hand (Arrow
g). Do not cover the child's mouth or ears. Make sure the shoulders are level
(Arrow 10), the hands are at the child's side (Arrow 11), and the head, shoulder
blades and buttocks are against the board (Arrows 12, 13, and 14). With your
right hand, lower the headpiece on top of the child's head. Make sure you push
through the child's hair (Arrow 15).
7. Measurer and Assistant: Cheek the child's positions (Arrows 1-15).
Repeat any steps as necessary.
8. Measurer: When the child's position is correct, read and call out the measurement
to the nearest 0.1 cm. Remove the headpiece from the child's head, your left hand
from the child's chin and support the child during the recording.
Assistant: Immediately record the measurement and show it to the measurer.
NOTE:If the assistant is untrained, the measurer records the height.
10. Measurer: Cheek the recorded measurement on the questionnaire for accuracy and
legibility. Instruct the assistant to erase and correct any errors.
*If the assistant is untrained, e.g. the mother, then the measurer should help the assistant
with the height procedure.

35. 35
B. Child Length Summary Procedure (Illustration 2)*
1. Measurer or Assistant: Place the measuring board on a hard flat surface, i.e.
ground, floor or steady table.
2. Assistant: Place the questionnaire and pencil on the ground, floor or table
(Arrow 1). Kneel with both knees behind the base of the board, if it is on the
ground or floor (Arrow 2).
3. Measurer: Kneel on the right side of the child so that you can hold the foot-piece
with your right hand (Arrow 3).
4. Measurer and Assistant: With the mother's help, lay the child on the board by
doing the following:
Assistant: Support the back of the child's head with your hands and gradually lower
the child onto the board.
Measurer: Support the child at the trunk of the body.
Measurer or Assistant: If she is not the assistant, ask the mothers to kneel on the opposite
side of the board facing the measurer to help keep the child calm.
Assistant: Cup your hands over the child's ears (Arrow 4). With your arms comfortably
straight (Arrow 5), place the child's head against the base of the board so that the child is
looking straight up. The child's line of sight should be perpendicular to the ground
(Arrow 6). Your head should be straight over the child's head. Look directly into the
child's eyes.
5. Measurer: Make sure the child is lying flat and in the centre of the board (Arrows
6. Place your left hand on the child's shins (above the ankles) or on the knees (Arrow
7. Press them firmly against the board. With your right hand, place the foot-piece
firmly against the child's heels (Arrow 9).
8. Measurer and Assistant: Cheek the child's position (Arrows 1-9). Repeat any steps
as necessary.
9. Measurer: When the child's position is correct, read and call out the measurement
to the nearest 0.1 cm. Remove the foot-piece, release your left hand from the
child's shins or knees and support the child during the recording.
10. Assistant: Immediately release the child's head, record the measurement, and
show it to the measurer.
NOTE:If the assistant is untrained, the measurer records the length on the questionnaire.
11. Measurer: Check the recorded measurement on the questionnaire for accuracy and
legibility. Instruct the assistant to erase and correct any errors.
If the assistant is untrained, e.g. the mother, then the measurer should help the assistant
with the length procedure.

36. 36
C. Child Weight Summary Procedure (Illustration 3)*
1. Measurer or Assistant: Hang the scale from a tree branch, ceiling beam, tripod or
pole held by two people. You may need a piece of rope to hang the scale at eye
level. Ask the mother to undress the child.
2. Measurer: Attach a pair of the empty weighing pants, infant sling or basket to the
hook of the scale and adjust the scale to zero, and then remove from the scale.
3. Measurer: Have the mother hold the child. Put your arms through the leg holes of
the pants (Arrow 1). Grasp the child's feet and pull the legs through the leg holes
(Arrow 2). Make certain the strap of the pants is in front of the child.
4. Measurer: Attach the strap of the pants to the hook of the scale. DO NOT
CARRY THE CHILD BY THE STRAP ONLY. Gently lower the child and allow
the child to hang freely (Arrow 3).
5. Assistant: Stand behind and to one side of the measurer ready to record the
measurement. Have the questionnaire ready (Arrow 4).
6. Measurer and Assistant: Cheek the child's position. Make sure the child is
hanging freely and not touching anything. Repeat any steps as necessary.
7. Measurer: Hold the scale and read the weight to the nearest 0.1kg. (Arrow 5). Call
out the measurement when the child is still and the scale needle is stationary.
Even children, who are very active, which causes the needle to wobble greatly,
will become still long enough to take a reading. WAIT FOR THE NEEDLE TO
STOP MOVING.
8. Assistant: Immediately record the measurement and show it to the measurer.
9. Measurer: As the assistant records the measurement, hold the child in one arm and
gently lift the child by the body. DO NOT LIFT THE CHILD BY THE STRAP
OF THE WEIGHING PANTS. Release the strap from the hook of the scale with
your free hand.
10. Measurer: Cheek the recorded measurement on the questionnaire for accuracy and
legibility. Instruct the assistant to erase and correct any errors.
*If the assistant is untrained, e.g. the mother, then weight should be taken by one person
only, the trained measurer, who should also record the measurement on the questionnaire.
D. Summary Procedure (MUAC) (Illustration 4)*
1. Measurer: Keep your work at eye level. Sit down when possible. The mother
during this procedure can hold Very young children. Ask the mother to remove
clothing that may cover the child's left arm.
2. Measurer: Calculate the midpoint of the child's left upper arm by first locating the
tip of the child's shoulder (Arrows 1 and 2) with your fingertips. Bend the child's

37. 37
elbow to make a right angle (Arrow 3). Place the tape at zero, which is indicated
by two arrows, on the tip of the shoulder (Arrow 4) and pull the tape straight
down past the tip of the elbow (Arrow 5). Read the number at the tip of the elbow
to the nearest centimetre. Divide this number by two to estimate the midpoint. As
an alternative, bend the tape up to the middle length to estimate the midpoint. A
piece of string can also be used for this purpose. Either you or an assistant can
mark the midpoint with a pen on the arm (Arrow 6).
3. Measurer: Straighten the child's arm and wrap the tape around the arm at the
midpoint. Make sure the numbers are right side up. Make sure the tape is flat
around the skin (Arrow 7).
4. Measurer and Assistant: Inspect the tension of the tape on the child's arm. Make
sure the tape has the proper tension (Arrow 7) and is not too tight or too loose
(Arrows 8-9). Repeat any steps as necessary.
5. Assistant: Have the questionnaire ready.
6. Measurer: When the tape is in the correct position on the arm with the correct
tension, read and call out the measurement to the nearest 0.1cm. (Arrow 10).
7. Assistant: Immediately record the measurement on the questionnaire and show it
to the measurer.
8. Measurer: While the assistant records the measurement, loosen the tape on the
child's arm.
9. Measurer: Check the recorded measurement on the questionnaire for accuracy and
legibility. Instruct the assistant to erase and correct any errors.
10. Measurer: Remove the tape from the child's arm.
If the assistant is untrained, e.g. the mother, then arm circumference should be measured
by one person only, the trained measurer, who should also record the measurement on the
questionnaire.
4.3 Age assessment
A. Introduction
Determining the correct age of a child is extremely important in evaluating
anthropometric data since reference standards for growth are broken down into age
categories by month. The age of a child should be determined as the number of years or
months of life completed. For example, a child who is three years old has completed
three years of life.

38. 38
B. Birth-date Sources
Birth-dates can best be determined by obtaining a documented record such as a birth
record, clinic card, baptismal record, etc., where a birth-dates is recorded. Written home
records may be reliable in some settings but should be verified. A "Local Calendar of
Events" can be used to estimate age or to verify stated ages, home or other records. Using
this method, a child's birth-dates can be estimated by relating the year and month of birth
to well known local or national events.
C. How to Make a Local Calendar of Events
1. The objective of a local event calendar is to identify a discrete monthly event for
each of the twelve months and a discrete special event for each of the years of age
covered, i.e. below six.
Determine well-known local or national events for a period of one year more than
the upper age limit of children who will be weighed and measured in the survey.
For example, if the population of children being surveyed is 3-59 months of age,
then determine events for the past six years. You may have to meet with local
officials, village leaders, etc. to determine events that took place in the area where
the survey will be conducted.
Ask about important special events that took place that everyone who lives in the
area would know, such as a marriage or death of an important person, a flood, an
election, etc. Begin with the current year and work backwards when you ask
people to remember events. Place these events on a calendar, with the years on the
top of the page and the months on one side. Try to obtain at least one special
event per year.
In the columns marked "Repeated Annual Events", place well known events that
take place each year next to the appropriate month, such as Christmas, Rainy
Season, Independence Day, etc. Try to obtain at least one event per month.

39. 39
Sample Local Calendar of events
Month
Repeated
Annual
events
Special annual events
1981 1982 1983 1984 1985 1986
January New year
February
Presidents'
birth date
Fire in
village
March
Annual
spring
festival
Village
chief
died
April Easter
Flood
in
village
May
Spring
harvest
National
census
June
Schools
summer
holidays
July
Independenc
e day, July
21
Chief's
son
married
August Planting
September
School
begins
National
election
October
Autumn
harvest
November Rains
December Christmas
How to Use a Local Calendar of Events?
1. The objective is first to locate a child's birth date between two special events.
First, select an event on the calendar, for example the fire, which took place in
February 1986. Next, ask the mother, "Was your child born before or after the fire
in the village?"
2. If the mother responds, "Before", identify the next special event that took place
just before the fire. In this case, the event before the fire was, the marriage of the
village chief's son, which took place in July 1985. Ask the mothers "Was your
child born before or- after the marriage of village chief's son?"
3. If the mother responds ''after", then you know that the child was born between
July 1985 and February 1986. You have just located the child's birth-date between
two special events, which took place in the village. If the mother responds
''before'' you should continue to search for an event where the parent will respond
after so that the birth-date will fall between two special events.

40. 40
4. Once you have located the birth-date between two events, look at the repeated
annual events, which take place every year between the two, identified special
events, i.e. between July and February.
5. You will now determine the exact month of birth. Choose one event that takes
place every year, for example, Christmas. Follow the same procedure to locate the
child's birth-date between two repeated annual events. In this case ask the mother,
''was your child born before or after Christmas?" If she responds after, select a
repeated annual event after Christmas. Continue this process until you have
located the month of birth.
Remember
a. Locate the birth-date between two special annual events.
b. Next, locate the birth-date between two repeated annual events until the exact
month of birth is determined.
c. Use the question, "Was your child born before or after _____________? (Select
an event)
E. Training for Age Assessment
Role-playing is a useful training tool to practice using a local calendar of events. Sketch
the calendar of events on a blackboard in front of the enumerators. Have two enumerators
sit in front the room. One plays the role of a mother. the other plays the role of the
enumerator. Write down a fictitious birth-date of the mother's child on a piece of paper.
Show it to the mother, so the mother will know how to respond to the question. Show the
birth date to the rest of the enumerators in the training room so they can follow the
questioning. DO NOT show the birth date to the person playing the role of the
enumerator.
F To get rough estimate of the age of a child of under 2 years old, use the
following general methods:
A. Number of teeth
Child's age in months = Number of teeth + 6.
However, please note that some children get their erupted very late while occasionally a
newborn baby might be born with one or two teeth and a child that has 20 teeth may be
aged between 2 and 6 years. So, the developmental stage of the child has to be also
observed simultaneously when assessing age. The following Table shows the ages at
which the deciduous or baby teeth erupt and will give some guide in the estimation of the
ages of children:
Ages (in months) for early, average and late eruption of deciduous teeth
Deciduous teeth Early Average Late
Lower central incisors 5 7.8 11
Upper central incisors 6 9.6 1
Lower lateral incisors 7 11.5 15
Upper lateral incisors 7 12.4 18

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Lower 1st
" molar 10 15.1 20
Upper 1st
" molar 10 15.7 20
Lower cuspid 11 18.2 24
Upper cuspid 11 18.3 24
Lower 2nd
molar 13 26.0 31
Upper 2nd
molar 13 26.2 31
B. Locomotion
The locomotion of the first year is creeping, of the second year, walking. Each of these
patterns of moving can be traced from early beginning. Thus, for an infant the age can be
estimated by using the following various stages of development reached:
Locomotion Average age (in month)
Chin up (Lying on chest) 1
Chest up (lying on chest) 2
Reach and miss 3
Sit with support 4
Sit on lap, grasp objects 5
Sit on high chair, grasp-dangling object 6
Sit alone 7
Stand with help 8
Stand holding furniture 9
Creep 10
Walk when led 11
Pull to stand by furniture 12
Climb stair steps 13
Stand alone 14
Walk alone 15
Walk 10 steps without support 18
Say single words 21
Speak short phrases 36
In addition to the above age estimation methods, one has to consider the child's siblings.
If the mother can recall the age of the sibling at the time when she gave birth to the index
child, make an estimate of the age of the index child on the basis of this age recalled. If
the age can not be recalled ask for the developmental stage of the sibling at the time of
the delivery of the index child. Make an estimate and use this estimated age to use it as a
basis and make comparison with the estimated age of the index child.
Never estimate the age of a child by looking at the size. If the child is malnourished, the
small size will deceive you and think that the child is younger than he/she actually is.
Only children more than 65 cm and less than 110 cm tall should be included in the
sample.

42. 42
CHAPTER FIVE HOW TO USE EPI INFO COMPUTER
SOFTWARE
Extracted from ‘The EPI INFO Manual, Version 6, by Andrew G.Dean, April, 1994’
5.1. Definition
EPI-INFO is a series of microcomputer programs for handling epidemiological data. It
has a database system to record data and statistical programs to analyze and produce
frequencies, cross tabulations, means, graphs and other related statistics.
5.2. Steps in EPI -Info program
There are three main steps in EPI-INFO for processing questionnaire or other structured
data.
Step I Make a questionnaire to use in entering data into EPI INFO using EPED Program
Step II Entering data in the questionnaire using the ENTER
Program
Step III Analyzing the data using the ANALYSIS Program
5.3. Running EPI INFO program
Start your computer in DOS Prompt:
C:>
If you have already installed EPI INFO in your computer,
CDEPI6 and press <Enter>.
Type: EPI6 and Press <Enter>. You should see the main EPI INFO menu.
But, if you do not have EPI INFO in your computer, follow the following steps to install
it.
-Restart your computer in DOS prompts or changes your computer to DOS prompt
-Place Disk 1 of EPI INFO System in Drive A
-Type
A: INSTALL and press <Enter>
Then, follow the directions given by the program.
After installation is completed, change the directory to EPI6, then
Type EPI6 and press <Enter>.
You should see the main EPI INFO Menu.
At the top of the menu you will see Programs -
5.4. The main programs of the EPI INFO system
Tutorials - Interactive tutorials to introduce EPI INFO
Examples - Sample files that illustrate particular aspects
Manual - The entire manual for EPI INFO
File - Open, create, view, or print text files from the EPI6 menu

43. 43
EDIT - Edit, copy, cut, and paste text files opened with the FILE menu.
To select an item from the menu:
Move the highlighter bar with the arrow keys. When the correct item is highlighted, press
the <Enter> key to run the program. You may also type the highlighted capital letter of
the selection, for example, E for the EPED editor or N for ENTER, and then press
<Enter>.
Pressing the <F10> key will exit from the menu or any other EPI INFO program.
Leaving the menu will bring back to the DOS prompt.
Step I: Creating Questionnaire Using EPED
Run the main EPI6 menu.
Select EPED to make a questionnaire.
Press <F6> to see the SETUP menu. The first choice is WW/TXT/QES mode. Press the
space bar one or more times until QES mode is selected and then press <Esc>. This
establishes page size and other settings with convenient values to make a questionnaire.
When a questionnaire is being developed for data entry, a few simple rules are necessary
to tell the program where to create data entry fields or variables and what kind of data to
accept at these locations.
5.5. Field Types in EPI INFO
Text or “underline” fields: _________
Indicated by continuos underline characters. The length of the variable or field will be the
number of underline characters used. The maximum length of a text field is 80 characters.
Example: the filed type for name is text or underline.
Numeric fields: ######
Only numbers or spaces will be accepted. If nothing is entered, the result will be a blank.
The number of digits is indicated by the number of #s. If a decimal point is given, the
field will be in “fixed decimal” format, allowing exactly the indicated number of digits to
the right of the decimal point. ###.### to enter data from 000.000 to 999.999
EPI INFO has more facilities to choice the filed type, like
Date filed <mm/dd/yy> or <dd/mm/yy>
“Yes/No” field. Only Y, N and Space or <Enter> are accepted.
There is a special command in EPED to make it easy to insert fields in your
questionnaire. To see it in action, type <Ctrl-QQ> (hold down the control key, type Q
twice). It can also be accessed from the Text menu, but <Ctrl-QQ> is easy to remember.
A menu of filed will appear on the screen. To insert one in the questionnaire, move the
bar cursor to the choice and press <Enter>. For text and numeric fields EPED may ask
about the length of the field or he number of digits. After you have provided this
information, the field will be inserted in the questionnaire at the current position of the
cursor.

44. 44
Suppose you want to create a questionnaire consisting of Name, Age, Sex and Salary of
respondents.
The variable names and the filed types will be as follows.
Name _______________ (Length of the filed is 15 characters and type of filed is text).
That means you can enter names that have utmost 15 letters).
Age ## ( Age will have a numeric field and the length is 2. Ages between 0 to 99 can be
entered)
Sex _ (can be a one length text field to enter either “m” or “f” or a six length text field to
enter “male” or “female”).
Salary ####.## (Salary will be a numeric filed with decimal point. The length of the filed
depends on the maximum salary).
The questionnaire looks like
Name_______________ Age ## Sex______ Salary ####.##
If you have a long question in the questionnaire, the filed name can be shorten by using
curly brackets {} or EPED considers the first 10 letters only as a field name.
Example: {Edu}cational status of {Moth}er: the filed name will be
Edumoth
But if you write the question as it is without curly brackets {} EPEP will give a
variable name as Educational. Therefore, it is advisable to choice a field name which is
more convenient to remember.
When you have finished typing or developing a questionnaire, press <F9> key to save the
file, give it a name with extension .QES. (Example, MARY.QES) and press <F10> key to
leave EPED.
Note: for additional options go through the tutorial section.
Step II.Entering data using Enter program
On the main EPI menu, move the cursor bar to the ENTER program choice “Enter data”
and press <Enter> or simply type “N” and press <Enter>. A screen will appear, asking for
the name of the data file, and displaying the following menu choices:
1. Enter or Edit data
2. Create new data file from .QES file
3. Revise structure of data file using revised .QES
4. Reenter and verify records in existing data file
5. Rebuild index file(s) specified in .CHK file

45. 45
5.6. Creating a New Data (.REC) File (Menu Choice 2)
ENTER constructs a new data file by reading the questionnaire (.QES) file and using the
information to set up a new data (.REC) file.
To make a new data file, first make a .QES file as described in the previous section. In
the ENTER program, give the name of the data file to be created (the .REC file), press
<Enter>, and then enter “2” for the menu choice. ENTER will now ask for the name of
the .QES file. Usually it is convenient to use the same file name for the data and
questionnaire files, calling MARY.QES and MARY.REC for example. There is no need
to type the suffixes .REC and .QES because they are supplied by the program.
When you specified both the .REC and .QES files, ENTER takes a few seconds to read
the questionnaire and make a data file and then displays the questionnaire on the screen.
Your are now ready to enter data.
5.7. Entering Data
Entering data means typing the appropriate responses in the blanks on the screen. The
cursor will move automatically from blank to blank. Each blank is called a “field”. Each
copy of the questionnaire you complete is called a “record”. The records are stored in the
file with the name ending in .REC, called either the data file or the .REC file.
At the bottom of the cursor the prompt line displays the available commands with the
current record number at the right end of the line.
After the information has been entered in the last filed of a questionnaire, the question
“write data to disk (Y/N)?” appears at the bottom of the screen. Replying “Y” saves the
record and brings up the next available empty record. Note that the record number on the
lower right changes. If the reply is “N”, the cursor jumps to the first filed in the
questionnaire and you have the opportunity to edit the record.
To exit from the program at any time, use the F10 function key. If you
Haven’t saved the current record, ENTER asks if you would like to save it and then
returns to the EPI6 menu or to DOS.
5.8. Moving from Record to Record
The current record number is always shown in the lower right corner of the screen. To
move to the previous record, press the <F7> key. <F8> will go to the next record in the
file, if any.
5.9. Finding Records that Match Criteria
ENTER allows you to search the data file and find records that match your criteria. To
find a record, first be sure the current record has been saved, if necessary. Then press
<Ctrl-F> for ‘Find,’ and type in the items you want to find, followed by <F3> for ‘Find
first’. You might type the entered name in a “Name” field and then press the <F3> key.
All the records with the specified name will be listed on the screen.

46. 46
5.10 Editing Records
To edit a previously entered record, first find and retrieve it as described above. Then
change any of the items in the record, entering a new item with the aid of the arrow,
delete, and insert keys. Be sure to press <Enter> when leaving a field that has been
changed. When you have made all the desired changes, go to the last field in the record
and press <Enter> or press END key. The question “Write data to disk (Y/N)?” will
appear at the bottom of the screen. If you reply “Y”, the record as it now appears will
replace the old record in the file. If you type “N” the cursor will return to the
questionnaire. If you move to another record with <F7> or <F8> without saving the edits
you have made, they will be discarded and the edited record will revert to its previous
form in the file.
5.11. Deleting or Undeleting Records
Pressing the <F6> key will mark the current record as deleted. An asterisk (*) will appear
next to the record number in the lower right corner of the screen. The data items in the
record are still visible in the ENTER program, but tabulations done in the ANALYSIS
program will skip this record. Record, once deleted, may be made active again
(undeleted) by pressing the <F6> key again. This key thus alternates between deleting
and un-deleting.
Step III. Calculating Anthropometric Indices Using Epinut Program
What are the anthropometric Indices? Anthropometric indices are the most commonly
used proxy measures of nutritional status. Anthropometric measures reflect the adequacy
of nutrition over time to support linear growth in children (Height/age) and the adequacy
of energy stores (weight-for Height) in children.
Weight-for-height (WFH)
 Defined as the ratio of weight in grams to height in centimeters.
 Measure of current status
 Low weight for height is called wasting
 Sometimes called acute malnutrition
 WFH is sensitive to the loss of weight which can be influenced by illness, low
food consumption and poor care
 Advantage: doesn’t depend on knowing the child’s birth-date
 Very good indicator of short-term problems. i.e. famine or epidemics
 Error can be in height measurements
 Not a good long term indicator for monitoring and evaluation
Height for Age:
 Measure of long-term growth
 Low HFA is called stunting
 Sometimes called chronic malnutrition
 Good long-term indicator of general welfare, affected by food consumption &
health care
 Not sensitive to short term fluctuation
 Error can be made in measurement of height and age.

47. 47
Weight for Age:
 A composite measure
 Low WFA is referred to as underweight, meaning less than expected weight for a
given age and sex
 Low WFA can reflect either stunting or wasting
 Most useful as monitoring indicator
 Error can be made in determining age
Calculation of WFA, WFH and HFA
To calculate the anthropometric indices information is needed on each individual’s sex,
age, weight and height. From these data it is possible to form different indices, including
those that relate to height-for-age, weight-for-age and weight for height. These indices
can be expressed in terms of Z-scores, percentiles, and percent of median relative to the
international growth reference population. Z-scores are the most frequently used.
The Z-score in the reference population has a normal distribution with mean of zero and
standard deviation of 1. Mean, median and mode are the same in normal distribution. For
example, if a study population has a mean of 0, this would mean that it has the same
median WFH as the reference population. The Z-score cutoff point recommended by
WHO and others to classify low anthropometric level is less than –2 Z-score for the three
indices. The proportion of the population that falls below a Z-score of –2 is generally
compared with the reference in which 2.3% fall below this cutoff. The cutoff for very low
anthropometric levels is usually less that –3 Z-score.
Z-Score = Individual’s Value – Mean value of reference PopulationS.D value of
reference Population
Z-Scores are useful because they have the statistical property of being normally
distributed, thus allowing a meaningful average and standard deviation for a population
to be calculated. In addition, Z-scores have a greater capacity to determine the proportion
of a population that falls below extreme anthropometric values than do percentiles.
Percentiles range from zero to 100, with the 50th
percentile representing the median of the
reference population. Cutoff points for low anthropometric results are generally< 5th
percentile or 3rd
percentile. In the reference population, 5% of the population falls below
the 5th
percentile; this can be compared with the proportion that falls below this cutoff
point in the study population.
The calculation of the percent of median does not take into account the distribution of the
reference population around the median. Therefore, interpretation of the percent of
median is not consistent across age and height levels or across the different
anthropometric indices.

48. 48
5.12. Anthropometric calculation using EPINUT
EPINUT is a program for performing calculations with anthropometric data in EPI Info
files and for displaying summary statistics from the data. To use EPINUT, you must have
a .rec file with relevant information already entered (e.g., sex, age, weight, and height).
EPINUT can be used to add nutrition indices to an existing Epi Info data file containing
these variables, or to display frequency distribution tables and graphs for each nutrition
index.
EPINUT can add anthropometric indices to an Epi Info file that already contains data in
fields called AGE, SEX, WEIGHT, and HEIGHT.
AGE should represent biologic age, in months
SEX can be coded as “1”, “m” or “M” for boys and “2”, “f” or “F” for girls
WEIGHT and HEIGHT should be numeric, in Kg and Centimeters, respectively
When all indices are calculated, 10 new variables are added to the file: HAZ, HAM,
HAP, WAZ, WAM, WAP, WHZ, WHM, WHP and FLAG.
The first nine fields contain the results of the anthropometric calculations. For the Z-
scores, a code of 9.99 means that the index could not be calculated because if missing
data or data values that were out of the appropriate range. Example: an age of 18 years.
A code of 9.98 for Z-scores denotes that the Z-score was greater than or equal 9.98 and
most likely indicates an error in measurement.
For percentiles and percent of median, a similar coding scheme is used (99.9 and 99.8 for
percentiles and 999.9 and 999.8 for percent of median, respectively)
A tenth field, the record FLAG field, is used to identify records where there are missing
data points or a strong likelihood that some of the data items are incorrect (based on
extreme Z-Scores). The criteria for “flagging” an anthropometric index is as follows:
Index Minimum Maximum
HAZ -6.00 +6.00
WHZ -4.00 +6.00
WAZ -6.00 +6.00
Two additional criteria for “flagging” a record are combination of data items:
(HAZ > 3.09 and WHZ < -3.09) or (HAZ < -3.09 and WHZ > 3.09)
Common errors include incorrect data entry, incorrect age/dates, weight or height
measurements entered incorrectly or in the wrong units, and missing/blank data. When
anthropometric data are being analyzed in the EPI Info Analysis program, or elsewhere, it
is recommended that missing cases excluded from analyses.

49. 49
Step IV: Analyzing the Data using ANALYSIS Program
ANALYSIS produces lists, frequencies, tables, statistics and graphs from EPI INFO
Files.
 Run the ANALYSIS program from the main menu.
 To leave the program at any time, press <F10>.
 By running ANALYSIS from the EPI6 menu, you will see a lower window for
entering commands and a larger one above where the results of the commands
will appear.
 Pressing the function keys shown at the bottom of the screen allow selection of
help topics, and variable names from lists that appear on the screen.
 After pressing one of the function keys, choose an item by moving the highlight
bar with the up- and down- arrow keys and pressing <Enter>.
The First Step- Reading a File
Analysis must be performed on the records in a file. The command that tells ANALYSIS
what file to use are READ <file name>, and this is usually the first command given in
ANALYSIS.
To see a list of available files, type
EPI>READ and press <Enter>. A directory of files will appear in a window. Move the
cursor bar with the arrow keys and choose a file by pressing <Enter>.
Whether you use the file directory or simply type READ and the file name, ANALYSIS
will use this file for all subsequent operations until another READ are performed. It has
become the ‘active data set’.
5.13. Producing a Line Listing
The first step in data analysis is to scan the data visually to gain an overall impression
and see what further analysis might be appropriate. A ‘line listing’ is helpful for this
purpose. To produce a listing of the records in the file, type:
EPI>LIST
The command LIST will display only as many variables as will fit across the current
screen width. EPI>LIST *
The ‘*’ is shorthand for ‘all fields’. LIST followed by one or two variable names lists
only these variables.
Frequencies
The frequency command (FREQ) will count each category for a specified variable and
give the absolute and relative frequencies for each category.
EPI> FREQ SEX
Produces this result:
Sex Freq PercentCum.
----------------------------------------------------------
M 44 58.7% 58.7%
F 31 41.3% 100%
----------------------------------------------------------
Total 75 100.0%