04 - ena manual acf

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TRAITEMENT OF NUTRITIONAL AND MORTALITY

SURVEYS

DATA ANALYSIS WITH NUTRISURVEY



ACKNOWLEDGEMENTS

We would like to thank Yvonne Grellety and Michal Golden for revising the present work.

TABLE OF CONTENTS

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A. Description & Preparation………………………………………….4

1. Opening…….……………………………………………………….4

1.1 Nutrisurve………………………………………………….4

1.2 An e!isting "#e……………………………………………..4

$. %seu# 'cons……………………………………………………..…4

(. P#anning………………………………….…………………………)

(.1. Na*ing t+e Surve…..……………………………...…..)

(.$. Sa*p#ing…………………………………………………….,

(.(. Sa*p#e si-e ca#cu#ation………………………………….,

(.4. Sa*p#e si-e or orta#it /ate Surve………………0

(.). Sa*p#e si-e or ot+ ant+ropo*etr

an2 *orta#it ana#sis…………………………………..3

(.,. Ca#cu#ating C#usters……………………………………...3

(.0. Se#ecting C#usters ...….……………………………….…

4. Training………………………………………………………….…11

). Options……………………………………………………………..1(

).1. Data Entr…………………………………………………..1(

).$. P#ausii#it C+ec5……………………….………….…….14

).(. /eport…………………………………………………..…..14

,. Data Entr Ant+ropo*etr……………………………………1,

,.1. 6aria#e 6ie7………………………………………………1,

0. Data Entr orta#it……………………………………………13

B. 'ntro2ucing Data

1. Ant+ropo*etr

1.1. Data Entr ………………….………..…….…………...1

1.$. Pasting 2ata ro* E!ce#……………………………….$8

2. orta#it…………………..……………………………………...$1

C. Data 9ua#it C+ec5………..…………………………………….....$(

D. /esu#ts & Data Ana#sis1. Ant+ropo*etr…….....……..………………………………...$4

$. orta#it………………………………………………………….$4

(. Ana#sis……………………………………………………………$)

(.1. E!ce#………………………………………………………..$)

(.$. EP' 'no…………………………………………………….$)

E. Anne!es…..………………………………………………..…..……..$,

N%T/'S%/6E:

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This program can be downloaded free from www.smartindicators.org orwww.nutrisurvey.de/ena/ena.html . (f it is already installed in a computer! it is importantto check that is the latest update".

A. DESC/'PT'ON AND P/EPA/AT'ON

1. OPEN'N;

1.1. Nutrisurve ena

#nce installed! the $rst things that will appear on the screen are the names of thepersons who designed this software! as well as the e%mail and website from where ena

has been downloaded. &ress click on 'OK .

1.$. An e!isting "#e

When closing down the software! after saving your $le! theway to open it (or any other e)isting *utrisurvey $le" is byopening $rst *utrisurvey ena! secondly by clicking on andthirdly by searching the $le.as that you want to open.

#r using the icon shown in chapter + (below"! after opening

*utrisurvey ena.

$. %SEF%L 'CONS

Ne7 #pens a new $le in .as format

Open #pens an e)isting .as $le

Save ,aves the actual $le.as

Save as ,aves $le.as with a chosen name

'*port mports $les .rec -&%nfo / or 01ase .2

E!it -)its from actual module and returns to principalmenu

The $rst page to appear will be Data Entr! but you have to go to2

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http://www.smartindicators.org/


http://www.nutrisurvey.de/ena/ena.html


http://www.nutrisurvey.de/ena/ena.html



3. PLANN'N;

STEPS TO FOLLO<

(.1. Na*ing t+e surve

You need to give a uni3ue name to your survey. 4owever! it is important to be consistentin the naming of $les and directories and to give all $les names that can be recogni5edlater by any team member.

The name of the $le should start with a three letter code for the country (e.g.! ,60 for,udan! 78M for 7ambia! 8*G for 8ngola! etc."! then the $le%name should have the date of the survey in YYMM format (year! year! month! month". n certain circumstances theregion! type of sub9ect (refugee! 0&! resident" or the agency involved can be usefullyincluded in the name of all the $les. Then there is a code for the type of $le2 :-& forreport! 08T for the data $le! etc.

Thus! a $le named ';1<=>=?<rep.doc would be the report of a survey taken in 8ugust+==> in ;iberia. There may be several simultaneous surveys conducted in ;iberia aroundthat time! ';1<=>=?<0&<1uchanan<884<dat.)ls would be the data $le for a surveywith 0&s in 1uchanan! ;iberia in ,eptember +==> conducted by 8ction 8gainst 4unger.

(.$. Sa*p#ing

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The ne)t step is to choose the type of sample you will use2 @" random survey or +" clustersurvey.

(.(. Sa*p#e si-e ca#cu#ation

Aalculate the sample si5e for the anthropometric survey. ntroduce the target populationsi5e. The population will be children under %years%old. f that number is unknown! anestimate of +=B or less (in case of having a high mortality rate in the area" of totalpopulation will be used as our population si5e.

(.(.1. Esti*ate2 preva#ence

-nter estimated prevalence of G8M. With a $)ed sample si5e! the higher the malnutritionprevalence! the lower the precision obtained. When making this assessment alwaysdecide upon a plausible range of values! rather than a single one. n many situations! areasonable statement would be2 CGiven the situation! the malnutrition prevalence isunlikely to be above +=B or below @=BD.

n other words! if there is no certainty of this value! the higher (ma)imum"prevalence e)pected from a range of similar values must be introduced.

*evertheless! if you are interested in a particular prevalence (e.g. the level that wouldtrigger an emergency response"! and you suspect the actual prevalence is below thisthreshold! enter the threshold number.

(.(.$. Desire2 precision

The $rst consideration is the minimum precision needed to meet the ob9ectives of the

survey. (Eor further e)planation Fdescriptions and tables%! please go to the ,M8:TM-T4#0#;#GY manual." The desirable precision and e)pected malnutrition prevalence rate are interconnected. fthere is a very high prevalence of acute malnutrition (e.g. >=B" the precision does notneed to be high to enable agencies to make appropriate decisions. 8t a prevalence ofover B or so! services will be overwhelmed and urgent and substantial intervention willbe needed. 8 con$dence interval of plus or minus @=B (+%>B" is perfectly acceptableunder these circumstances. Normally, it can be set a 5% precision or more for high prevalence, falling to about 2.5% precision for lower prevalence.

'n genera#= t+e #o7er t+e preva#ence t+e greater t+e precision nee2e2.

-). Eor B &:-H8;-*A-! you will need +. to B precision

(.(.(. Design e>ect

f itIs a random sampling survey! then the design eJect will always be 1.

n cluster sampling! design eJects can vary from @ (if the population is homogeneous sothat all the clusters are similar to one another" to > or higher where some clusters are notaJected and others are severely aJected.n most nutritional emergencies! the design eJect is about @. increasing to + or more inmore heterogeneous or large%scale surveys.

f the design eJect is thought to be much greater than + then the population is

suKciently heterogeneous and therefore it is better to conduct two separate surveys!each focused upon more homogeneous sections of the population2 e.g. Two cluster

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surveys! each with a design eJect of @.! can be conducted with the same eJort as onesurvey with a design eJect of .

The advice to anticipate a range of likely values for the prevalence and for the designeJect! within which you anticipate the results will fall is important. n *utrisurvey enayou should enter2

• The 7i2est con$dence interval that is acceptable L the *ini*u* acceptableprecision

• The +ig+est prevalence that is anticipated

• The #argest design eJect that is likely to be encountered

(Eor further e)planation Fdescriptions and tables%! please go to the ,M8:TM-T4#0#;#GY manual."

6pon entering all these values in their respective bo)es! the sample si5e will beautomatically calculated and will appear in the tur3uoise bo).

(.(.4. 'ncrease sa*p#e si-e

1y B or @=B to allow unforeseen contingencies.

E?APLE 12;etIs look at the following e)ample2

#ur sample si5e is >. 8nd if we increase this number B! according to the last step!then our sample si5e will be ?+.

(.(.). Divi2e t+e sa*p#e si-e t+e average nu*er o %) c+i#2ren to +ave a+ouse+o#2 sa*p#e si-e.

e.g. if the average 6 children is @.! divide ?+ by @. L )$3

(.4. Sa*p#e si-e or *orta#it rate surve

Eor the death rate component of the survey (you may need information fromgovernmental and/or non%governmental organi5ations (*G#s" working in health"2

@.-nter an estimate of the total population that is targeted by the survey.+.-nter the e)pected mortality rate ().))/@=!=== persons/day".-nter the re3uired precision ().))/@=!=== persons/day". Eor e)ample! if your

e)pected mortality rate is +.=/@=!=== persons/per day and you want a con$denceinterval of @.> % +.! enter a re3uired precision of =. (that is +.= %/N =. which gives

@.> % +.". The precision chosen has a substantial eJect upon the sample si5eneeded.

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>.-nter the design eJect. The default design eJect for sample si5e calculations formortality is +.=. f violence%related%mortality is limited! a design eJect of @. forcrude death rate may also be suKcient. You can also use the last survey raw dataand check the design eJect in ena2 it calculates the design eJect.

.-nter the chosen recall period in days. n most situations! ?= days (or from = to @+=days" will be used. 4owever! the decision should be made individually for each

emergency conte)t according to the date of the last event that occurs in this area.

E?APLE $

(.4.1. Divi2e t+e sa*p#e si-e t+e average nu*er o persons per+ouse+o#2 to +ave a +ouse+o#2 sa*p#e si-e.

e.g. @> divided by the average persons per 44 e.g. > L 41,

(.). Sa*p#e si-e or ot+ ant+ropo*etr an2 *orta#it ana#sis

(.).1. For ant+ropo*etr ana#sis= e.g. )$3

(.).$. For *orta#it ana#sis= e.g. 41,

The $nal sample si5e per household that will be retained will be )$3

(.,. Ca#cu#ating C#usters

(.,.1. For Ant+ropo*etric Surve

n cluster surveys! sample si5e should be divided by the number ofhouseholds that can be visited each day. This will provide the number ofclusters.

To continue with E?APLE 1! letIs say that each of our teams can visit @> households(44" per day. (Eor further details on how to calculate this number! please go to ,M8:TMethodology Manual". 0ividing +O/@> L . Whenever the result has a decimal! it isadvised to round up to the ne)t whole number. Then we will have (3 clusters for oursurvey.

n pastoral/nomadic 5ones we can have diKculties $nding children. f this is

the case! it is advised to decrease the number of children/cluster andincrease the number of clusters.

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,tatistically! the minimum amount of clusters that each of the surveys (anthropometric P mortality" can have for them to be valid is +. 4owever!in 8AE we ,T:#*G;Y :-A#MM-*0 having = clusters! minimum.

3.7. Se#ecting c#usters

When designing a combined survey (with both components2 nutrition P mortality"! thesample si5e to estimate malnutrition prevalence! as well as the number of householdsneeded to estimate mortality rate are calculated! and then2

T+e greater o t+ese nu*ers is c+osen for the survey.

(.0.1. Ta#e or C#uster Sa*p#ing

@. -nter number of clusters

f you are attempting to undertake a survey in an area of nomads where the

population fre3uently moves large distances! it is likely that you may travel to anarea to $nd that there is no%one there and no%one nearby.

' ou suspect t+at t+is *ig+t +appen= ou s+ou#2 se#ect so*e e!trac#usters eore ou start t+e surve. This way! if one cluster is deserted youcan replace it with another one.

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To randomi5e the clusters obtain the best available census data for eachvillage! district! or section on the map using the smallest e)isting unit2 t is important to de$ne your geographical area very realistically in theplanning stage! taking into account2 travel! security! and any other factor thatcould inQuence your ability to get to the cluster site before listing the sites in



+. 0e$ne what constituents a CvillageD2 it should be the smallest unit with population$gure. Then! under ;eograp+ica# unit column enter the names of all the towns!cities! districts or other areas that will potentially be chosen to include in a cluster .8ll potential areas have to be entered. t does not matter what order the areas areentered. 1ut if any village is omitted at this step! it then will not be part of thesurveyed population.

. 6nder Popu#ation si-e column enter the estimated population si5e for eachCvillageD.

>. With the *umber of Alusters and their names entered! click on @Assign C#uster The computer will then select the areas where there will be clusters. T+is s+ou#2

e 2one on# ONCE. t will potentially introduce a bias if they are reselected.

(.0.$. /an2o* Nu*er Ta#e

f you want to do a random survey! then you need to generate a random table based inthe bo) @/an2o* Nu*er Ta#e. Eor that you need the following data2 for Rangefrom and to the total range of children of the total population! i.e. @%@!= and enter forNumbers the sample si5e to use. Then! click on @;enerate Ta#e.

The children to be interviewed will be shown in a Word sheet.

The smallest available geographical unit is always chosen! as long aspopulation data are available and the geographical unit has a name. f thenumber of children is less than =! add another area with that one. -ach areashould have a local name! so that the inhabitants are familiar with theboundaries of the area when the local name for the area is used.

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4. T/A'N'N;

This page is used to standardi5e our teams in measuring weight and height (or length". The aim of the standardi5ation test consists on improving the 3uality of the

measurements. 8ll the members of the teams should measure twice @= or more childrenwith a time interval between individual measures. (Aheck ,M8:T M-T4#0#;#GY toobserve the appropriate procedure for standardi5ation." The outcome of this e)ercise will be analy5ed by *utrisurvey -na2 you only need to enterthe measures and then click on @/eport. &recision and accuracy are assessed by @"calculating the variation between their repeated measurements (repeatability of measurements"R +" calculating the variation between each team memberIsmeasurements and the ones of the supervisor. -ach team member is then given a scoreof competence in performing measures (O or POO/". f the results are O it means theenumerator is standardi5ed! if the results are POO/ the enumerator should repeat thee)ercise completely! perhaps with diJerent people paired in teams.

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Report for Evaluation of Enumerators

Weight:Precision: Accuracy:

Sum of Square Sum of Square[W2W1! [Su"er#.$W1%W2&

'num.$W1%W2!

Su"er#isor 7(29'numera)or 1 6(76 *+ 1(69 *+

Height:

Precision: Accuracy:

Sum of Square Sum of Square[W2W1! [Su"er#.$W1%W2&

'num.$W1%W2!

Su"er#isor 4(84

'numera)or 1 10(89 P**, 0(25 *+

-or e#aua)in/ )e enumera)ors )e "recision an )e accuracy of )eir measuremen)s is cacua)e.

-or "recision( )e sum of )e square of )e ifferences for )e oue measuremen)s is cacua)e. is #aue

sou e ess )an )o )imes )e #aue of )e su"er#isor.

-or )e accuracy( )e sum of )e square of )e ifferences e)een )e enumera)or #aues $ei/)1%ei/)2& an)e su"er#isor #aues $ei/)1%ei/)2& is cacua)e. is #aue sou e ess )an )ree )imes )e accuracy#aue of )e su"er#isor.

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). OPT'ONS

This is the last of the screens of *utrisurvey! but is useful to $ll out before entering the

data. The software has an automatic way for entering data in Data Entr. We couldagree and save these options or simply modify them based on our needs. f we savethem! we should always remember that we are establishing these options for futuresurveys. 4owever! they can be modi$ed any time a new survey is planned.

).1. Data Entr

).1.1. 8utomatic $lling out2

The program selects all these optionsR it is advised!nevertheless! that the number of household be introducedmanually! because the number of children in one householdcould be greater than one.

We recommend not $lling out 4ousehold *o. automatically.

).1.$. -ntering of age mainly2

-ither method can be selected depending on the document you$nd at household level2 e.g. in some countries like Tan5ania!

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every child has a birthday dateSin other countries! which ismostly the case! you have no birthdate and you have then toestimate the age in monthsR in this case! you should use CwithmonthsD.

).1.(. -ntering of data2

You can select introducing data directly or Cwith &ull 0own-ditorsD for some of the variables (se)! birthdate! edema". ,eethe e)ample below.We recommend using ● directly as 1.1.99, 10199 or 010199 option.

).1.4.n this page we can also select if we want the program to calculateanthropometric indices after

pasting data from another $le.

).1.). Weight of clothes4ere we canintroduceaverage

weight in grams of clothing of survey sub9ects to beautomatically subtracted from the weightintroduced in Data Entr page.

).1.,. Aorrection for -dema2 We can select automatic correction of weight foredema found2 Cn/yD L average weight of body weight edemaC=!@!+! L mild! moderate or severe edemaWe donIt recommend using it! unless strictly necessary.

).$. P#ausii#it C+ec5 -nter the 5%scores and the age range (in months" for theplausibility report in the bo). The plausibility check report! after entering all your data! willgive you the 3uestionable 0 no.(s" out of range that youhave selected! e.g. 7%score and '%7%score from the meanof the W4 of the sample si5e.

n the Data Entr s+eet= the software will highlight gross errors similar to Qag in -pi nfoin pink. but they are not the same as the ones in the plausibility check in this version.

).(. /eport

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f we want our report to be grouped by ages (in months".We can change the age groups by only changing the $rst number in each range! ena isautomatically changing the other one from the range above.

#nce $nished introducing desired parameters! click on which is located atthe bottom right hand side of the page.

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,. DATA ENT/: ANT/OPOET/:

Eill out this page with the data gathered in the $eld 3uestionnaire.

Take in account that the $eld 3uestionnaire follows theprogramIs same order to facilitate data entry.

*utrisurvey ena has a form that we can use and can be obtained clicking on2

Eorm for anthropometric survey

#ther uses of this module are2

For* or *orta#it Eorm to gather mortality informationPaste Data &astes data from clipboardCop Data Aopies data from current survey to -)cel formatP#ausii#it C+ec5 Heri$es presence of errorsC+ec5 o 2ou#e entr Aorroborates presence of errors when two

persons are entering the same data/eport in <or2 :eproduces report in Word format

,.1. 6aria#e 6ie7

This is one of the two sections of page 0ata -ntry. n Hariable Hiew we should save the$le using the same instructions we used in P#anning. (We can $nd these in the @st.step." n 'Hariable Hiew section and before introducing data we should establish ranksto be used in the survey.

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,ome variables in ena are automatically rankedR however! you can change some of them!like for e)ample height ranks if the targeted population has growth retardation. Thesechanges should be included in the report.

-na will then check all those data which are out of range and highlight them in pink in

'0ata Hiew section.n this latter section! data cleaning also can be made by using C&lausibility checkD clickingon Check Table every time you enter some dataR this facilitates to underline errors.

The entered data have to be checked using the original written data collection sheets.8ny error in data entry should be corrected immediately.

f a child is e)cluded from the survey! his information willdisappear from the page and we should click again on Check Table.

Co#u*n6aria#e

• Add : place mouse in '0ata Hiew section and over line *o. @ of the column where we want a variable to appear and click on !!. 8little bo) will appear! where the name of the e)tra column should beentered (e). Measles"! then click on -nter or #.

• Delete: place mouse in '0ata Hiew section on any spot belowthe column title we want to eliminate and click on "eleteR a bo) willappear asking if we want to erase this column. Alick on Yes or-nter.

• Sort : place mouse in '0ata Hiew section on any spot below thecolumn title that we want to use to classify our database. Alick onit. 8 bo) will appear telling that our database will be classi$ed by2column name. Alick on Yes or -nter.

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• Filter : click on #ilter. 8 bo) will appear asking us to de$ne which variable weneed for selecting cases from database. ,elect the variable!introduce the desired ranges! and then click #.

:ow/0ata2Eor adding a child to the survey we click on *ew. 8 new line will

appear at the end of the listing.Eor adding data and to insert a blank line in a speci$c place of yourlist! place the mouse and click over the line where you want the newone to appear and then click on nsert. To erase data of a child! place mouse on the line you want toeliminate and click on 0elete.

We can choose the references for evaluating our data! *A4, or W4#.:esults will automatically be shown in '0ata Hiew and in /esu#tsAnt+ropo*etr page.

8t clicking on "isclaimer youIll see the following2

t will disappear with a second click.

Go To2

f you click on this icon! you automatically go to sub9ect 0 @.f you click on this icon! you automatically go to the last sub9ect.

f you click on this icon! a bo) will ask you the 0 number you are looking forR enterthe number and click on #! then the software will automatically go to this 0number.

0. Data Entr orta#it

To enter the data in this sheet! you can use the Word sheet of the software as a3uestionnaire. This form is located under the command $%tras at the left top of the

screenR click on #orm for mortality rate survey . There is one called the &'RT &tan!ar!form and the other one called &imple form (one sheet)cluster*.0onIt use the simple form at the moment but the standard form as a 3uestionnaire.

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'cons on t+is page

,ave ,urvey

8dd line

-rase line

&aste data from clipboard

Transfer data to -)cel format

B. 'NT/OD%C'N; DATA

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1. Ant+ropo*etr

1.1. Data Entr in Data 6ie7 Section

#n the $rst line introduce surve 2ate! c#uster nu*er (if used"! and tea* nu*er.

The i2enti"cation nu*er o eac+ c+i#2 <'LL BE ENTE/ED auto*atica## one byone for each new introduced case.

The +ouse+o#2 nu*er s+ou#2 NOT BE ENTE/ED auto*atica##! because you canhave more than one child in the same household. The 0 4ousehold number should bethe same as the one in mortality entry data.

-nter age in *ont+s in corresponding s3uare.

8nthropometrical variables are calculated automatically. 8ny ma9or error or CQagD willappear in pink but they are not the same as the ones selected in the plausibility check.

1.$. Pasting 2ata ro* E!ce# to Nutrisurve ena

f you have survey data in e)cel format! *utrisurvey can analy5e it by pasting it inData Entr sheet. To do so! follow the steps2

a. #n your e)cel sheet select only those data of the variables that you included inyour '0ata Hiew section! then click on Aopy icon.

. Go to *utrisurvey ena '0ata Hiew section and place your mouse and click overline @! under ,6:H08T- column! and then click on &aste icon.

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The population that has been chosen for a cluster has alreadybeen introduced with a number in our database during &lanningstage! so we should use that same number of cluster in this



$. orta#it

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This screen has the instructions written down at the top of it. t is important to take inaccount the following2

• n bo) of + members- CtotalD enter the total number of members in the 44 andC'D the total number of children ' years of age in this 44.

• n oin e)clude births during :ecall &eriod.

• n leave e)clude deaths during this same period.

C. DATA 9%AL'T: CEC

This step is useful for $nding and interpreting errors.

n Data Entr page we $nd the bo)2

n &lausibility /rint Report ! ena lists values out of range from the ones that you put inOptions (e.g. W4'% P W47%score". t points errors in your data! $rst for your totalsample and then by teams. See Anne! 1 7it+ an e!a*p#e o t+e 7a Nutrisurve

reports errors oun2 7it+ t+eir interpretationG.

:emember that in order to $nd errors as soon as possible! we mentioned before to enterthe ranges of the variables needed in your survey in both 'Hariable Hiew of Data Entrand in Options pages.

We can also check mistakes by making two persons entering the same data. 6sing theExtras icon! and if you click on2

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C+ec5 o 2ou#e entr! the software willcheck data 3uality corroborating data introduced bytwo persons.

D. /ES%LTS & DATA ANAL:S'S

1. Ant+ropo*etr

When all the data are entered! we can move on to /esu#ts Ant+ropo*etr sheet. 4ereyou will $nd your results based on the references you chose earlier in Data EntrAnt+ropo*etr sheet2 (*A4, or W4#" and also you are able to obtain the graphsaccording to the chosen indicators! and then by se)! age or clusterR you can also obtain a

partial report in Word and -)cel formats.

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$. orta#it

#nce introduced all mortality data in this screen! the software will automatically calculateand show results in /esu#ts orta#it sheet. 4ere! it is the Arude 0eath :ate which iscalculated as well as its components UaV! UbV! UcV! UdV! UeV! and UfV.

(. Ana#sis

*utrisurvey does not analy5e M68A or any additional variables! so we can choosebetween -)cel or -& nfo 8nalysis.

(.1. E!ce# Ana#sis

You can enter your data directly on e)cel or transfer your data from -na to -)cel formatby clicking on Data Entr sheets for both 8nthropometry and Mortality.

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#r using the bo) displayed by clicking on $%tras! and then clicking again on Aopy 0ata to-)cel.

-)cel will show in the last columns all the data in percentage of the medians.

8t the same time that you enter the data! you should transferthem to -)cel to save your data.

To sort your data by variables in -)cel! place the mouse over line @ (the one with thevariables names" and select the whole line with a left click. Then click on 0atos! placeMouse over Eiltros! click and then re%click on 8uto$ltro.

8t this moment wecan use $lters! also!to select for e.g.M68A or whichchildren are eligibleto get admitted to acenter.

(.$. EP' 'no Ana#sis

6nlike -)cel! this type of analysis can calculate con$dence interval easily. You can$nd it under Eile icon.

ANNE? 1

Plausibility check:

Anthropometric Inices out of usual range !mean "3#$# mean %3#$&:

ine 104: W $4(187&( "roay ei/) is incorrec)ine 193: W $3(562&( "roay ei/) is incorrec)

ine 282: A $3(413&( "roay a/e is incorrec)

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ine 363: W $3(318&( "roay ei/) is incorrec)ine 497: A $3(674&( W $3(272&( "roay ei/) is incorrec)ine 647: A $5(486&( "roay a/e is incorrec)ine 703: A $4(397&( W $4(491&( "roay ei/) is incorrec)ine 754: W $3(267&( "roay ei/) is incorrec)

Age istribution:

on) 6 : on) 7 : on) 8 : on) 9 : on) 10 : on) 11 :

on) 12 : on) 13 :

on) 14 : on) 15 : on) 16 : on) 17 :

on) 18 : on) 19 : on) 20 : on) 21 : on) 22 : on) 23 :

on) 24 : on) 25 : on) 26 :

on) 27 : on) 28 : on) 29 :

on) 30 : on) 31 : on) 32 : on) 33 : on) 34 : on) 35 :

on) 36 : on) 37 : on) 38 : on) 39 :

on) 40 : on) 41 :

on) 42 : on) 43 : on) 44 : on) 45 : on) 46 : on) 47 :

on) 48 : on) 49 : on) 50 : on) 51 : on) 52 :

on) 53 : on) 54 :

26

ere( )e sof)are inica)es

)a) a o) of cases ere

59mon)s o( eac case

ein/ no)e y a ;

accorin/ )o i)s a/e in mon).

<n )is e=am"e( a/e 59

mon)s as )e ma>ori)y ofcases. <) ou e a""ro"ria)e

)o #erify if )a) is )e case.



on) 55 : on) 56 : on) 57 : on) 58 : on) 59 :

'igit preference Weight:

?i/i) .0 : ?i/i) .1 : ?i/i) .2 : ?i/i) .3 : ?i/i) .4 :

?i/i) .5 : ?i/i) .6 :

?i/i) .7 : ?i/i) .8 :?i/i) .9 :

'igit preference Height:

?i/i) .0 : ?i/i) .1 : ?i/i) .2 :

?i/i) .3 : ?i/i) .4 : ?i/i) .5 :

?i/i) .6 : ?i/i) .7 : ?i/i) .8 : ?i/i) .9 :

(tanar eviation of WH):

S)anar ?e#ia)ion S?: 0(929 $e S? sou e e)een 0.8 an 1.2&

0,929 is the SD of our survey, in this case is between 0,8 and 1,2. It is ok

Pre#aence $@ 2& coun)e: 2(52,5 % is the % of chidren wasted in the survey

Pre#aence $@ 2& cacua)e i) curren) S?: 2(9

2,9% is the !revaence of wastin" with SD of 0,929

27

ere( 'na sof)are )es you if )e )eams measure

re"ea)ey )e ei/) an roune or no) )o .$ or .* .

<n )is e=am"e( i) is o#ious )a) )e )eams roune

of)en )o .$ an .*. ere is a i/i) "reference( so you

i a#e )o /o acB an re#ie ere )e mis)aBe

occurs.

ere( )e 'na sof)are )es you if )e)eams roune or no) )o a cer)ain i/i)

"reference ecima en )ey )ooB )e

ei/)Cen/). <) is o#ious )a) )ey

roune )o .$ an $.*( so you i a#e

)o /o acB an re#ie ere )e mis)aBe

occurs.



Pre#aence $@ 2& cacua)e i) a S? of 1: 3(9#,9% is the !revaence of wastin" with a SD of 1

(tanar eviation of HA):

S)anar ?e#ia)ion S?: 1(206 $e S? sou e e)een 1.10 an 1.30&Pre#aence $@ 2& coun)e: 64(6Pre#aence $@ 2& cacua)e i) curren) S?: 61(0Pre#aence $@ 2& cacua)e i) a S? of 1: 63(1

(ke+ness an ,urtosis of WH):

SBeness of W: 0.078 DE "roay no) sBee $#aue @ 2F$6Cn&G&$SBeness carac)eriHes )e e/ree of asymme)ry aroun )e mean( "osi)i#e sBeness inica)es a on/ ri/) )ai(

ne/a)i#e sBeness a on/ ef) )ai&

+ur)osis of W: 1.478 DE "roay Bur)osis "roem $#aue E 2F$24Cn&G&$+ur)osis carac)eriHes )e rea)i#e "eaBeness or fa)ness com"are i) )e norma is)riu)ion( "osi)i#eBur)osis inica)es a rea)i#ey "eaBe is)riu)ion( ne/a)i#e Bur)osis inica)es a rea)i#ey fa) is)riu)ion&

See )e /ra"ic eo ic ius)ra)es en e a#e a no) sBee $green graphic&( u) Bur)osis $re

graphic& of W.

Poisson istribution of clusters for WH):

numer of cus)ers1 cirenCcus)er i) W @ 2:

2 cirenCcus)er i) W @ 2:3 cirenCcus)er i) W @ 2:4 cirenCcus)er i) W @ 2:5 cirenCcus)er i) W @ 2:

6 cirenCcus)er i) W @ 2:7 cirenCcus)er i) W @ 2:

8 cirenCcus)er i) W @ 2:

28

e sof)are inica)es o manyas)e ciren you a#e in yourcus)ers usin/ )e .<n )is e=am"e( i) )es you )a):

3 cus)ers eac a#e 10 as)eciren.2 cus)ers a#e eac 12 as)eciren(1 cus)er as 13 as)e ciren( e)c.(e)c.



9 cirenCcus)er i) W @ 2:10 cirenCcus)er i) W @ 2: 11 cirenCcus)er i) W @ 2:12 cirenCcus)er i) W @ 2: 13 cirenCcus)er i) W @ 2:


15 cirenCcus)er i) W @ 2: 16 cirenCcus)er i) W @ 2: 17 cirenCcus)er i) W @ 2:18 cirenCcus)er i) W @ 2: 19 cirenCcus)er i) W @ 2:

20 cirenCcus)er i) W @ 2: 21 cirenCcus)er i) W @ 2:22 cirenCcus)er i) W @ 2:23 cirenCcus)er i) W @ 2:24 cirenCcus)er i) W @ 2:

'etaile -eam Evaluation

-eam / 3 0

'igit preference Weight !1&:.0 : 6 4 10 9.1 : 8 14 11 8.2 : 9 10 9 17

.3 : 9 8 15 8

.4 : 13 10 11 13

.5 : 13 11 6 10

.6 : 8 14 7 9

.7 : 7 8 8 7

.8 : 14 8 9 8

.9 : 13 14 12 11'igit preference Height !1&:

.0 : 10 5 25 13

.1 : 10 10 12 15

.2 : 14 11 14 13

.3 : 13 6 11 17

.4 : 8 11 8 9

.5 : 11 12 3 11

.6 : 9 12 8 8

.7 : 8 11 5 3

.8 : 9 6 5 7

.9 : 7 15 8 4

2lobal malnutrition !WH) "/&:

S? 0(81 0(79 0(82 0(87Pre#aence $@ 2& coun)e: 7(1 9(1 7(7 11(6

Pre#aence $@ 2& cacua)e i) curren) S?: 8(3 8(4 11(1 13(6

Pre#aence $@ 2& cacua)e i) a S? of 1: 13(2 13(7 15(7 17(1(tunting !HA) "/&:

S? 1(60 1(24 1(30 1(55Pre#aence $@ 2& coun)e: 18(1 15(6 9(8 16(7

Pre#aence $@ 2& cacua)e i) curren) S?: 17(9 15(5 14(6 16(4Pre#aence $@ 2& cacua)e i) a S? of 1: 7(0 10(4 8(4 6(4

F is is )e a)a e sou consier as #ai.

29

e sof)are aso /i#es e)aie

information per team.

ere( i) )es you i/i) "reference

"er )eam for ei/).

Ii) aso oes )e same i) ei/).

S? foun y eac )eam for 2lobal

4alnutrition

of ciren i) Joa anu)ri)ion F

Pre#aence of as)in/ i) curren) S?

Pre#aence of as)in/ i) S? of 1

Pre#aence of s)un)in/ i) S? of 1

Pre#aence of s)un)in/ i) curren) S?

S? foun y eac )eam for (tunting

of ciren i) S)un)in/ F



Poisson istribution of clusters for WH):

numer of cus)ers1 cirenCcus)er i) W @ 2: 2 cirenCcus)er i) W @ 2:



$Same as ao#e Poisson

is)riu)ion of cus)ers

W&

04 - ena manual acf

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