nutritionsurvey .n. shahand mehartalukas istrict, sindh · shahdadkot and dadu districts, sindh...

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No 201 vembe 11 er K D Fu .N. Sha Dadu D unded by N ah and istrict, Nutritio Meha Sindh Fin on Surv r Taluk Provin Pakist al Repo vey kas nce tan ort

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ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������2�

Acknowledgements�

We�would� like� to� thank� the� district� authorities� (EDOͲHealth)� for� their� support� in� the� survey� undertakings� and�UNICEF� for� provision� of� anthropometric� equipments.� Also,�we�would� like� to� thank� the� Canadian� International�Development�Agency�(CIDA)�for�funding�this�nutrition�survey.��

Table�of�Contents�

1.� INTRODUCTION�.............................................................................................................................................�5�1.1� Background�...............................................................................................................................................�5�2.1�Survey�rationale�...............................................................................................................................................�5�

2.� OBJECTIVES�...................................................................................................................................................�6�2.1� General�Objective�............................................................................................................................... ......�6�2.2�Specific�Objectives�............................................................................................................................... ............�6�

3.� METHODOLOGY�............................................................................................................................... .............�6�3.1�Study�design�............................................................................................................................... .....................�6�3.2�Sample�size�determination�.............................................................................................................................. �6�3.3�Sampling�methodology�....................................................................................................................................�7�3.4�Survey�team�composition�and�training�............................................................................................................�7�3.5�Quantitative�data�collection�techniques�..........................................................................................................�8�

a.� Anthropometry�......................................................................................................................................�8�b.� Data�entry,�analysis�and�report�writing�..................................................................................................�9�4.� ETHICAL�CONSIDERATIONS�............................................................................................................................ �9�5.� FIELD�SUPERVISION�AND�QUALITY�ASSURANCE�............................................................................................�9�6.� RESULTS�........................................................................................................................................................�9�7.� CONCLUSIONS�AND�RECOMMENDATIONS�..................................................................................................�13�8.� ANNEXES�............................................................................................................................... ......................�14�

8.1.�Anthropometry�Questionnaire�.....................................................................................................................�14�8.2�Mortality�Questionnaire�................................................................................................................................�15�8.3�Age�And�Gender�Distribution�.........................................................................................................................�16�8.4�Distribution�Of�Anthropometry�Result�Compared�To�International�Reference�..............................................�17�8.5�Prevalence�of�acute�malnutrition�of�both�Talukas�by�age�group�....................................................................�17�8.6�Prevalence�of�acute�malnutrition�segregated�by�gender�(WHO�2006�and�NCHS�1977�Standards)�.................�18�8.7�Prevalence�of�acute�malnutrition�based�on�MUAC�segregated�by�gender.�....................................................�19�

�� �

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������3�

Acronyms��

ACF������������������������Action�Contre�la�Faim�International��ARI�������������������������Acute�Respiratory�Infection��BCG������������������������Bacillus�CalmetteͲGuérin��CI���������������������������Confidence�Interval��CIDA�����������������������Canadian�International�Development�Agency�CMR/CDR����������������Crude�Mortality�Rate/Crude�Death�Rate��CMAM���������������������Community�Management�of�Acute�Malnutrition��DCO������������������������District�Coordination�Officer��EDOͲH���������������������Executive�District�Officer�Ͳ�Health�ENA�������������������������Emergency�Nutrition�Assessment��EPI��������������������������Extended�Program�of�Immunization��GAM������������������������Global�Acute�Malnutrition��HFA�������������������������HeightͲforͲAge��HH���������������������������Household��ITN��������������������������Insecticide�Treated�Net��KG���������������������������Kilogram��MAM������������������������Moderate�Acute�Malnutrition��MUAC����������������������Middle�Upper�Arm�Circumference��NCHS�����������������������National�Center�for�Health�Statistics��NDMA����������������������National�Disaster�Management�Agency��NGO������������������������Non�Governmental�Organization��OTP�������������������������Outpatient�Therapeutic�Programme��PPS��������������������������Population�Proportional�Sampling��PLW�������������������������Pregnant�and�lactating�women�SAM�������������������������Severe�Acute�Malnutrition��SC���������������������������Stabilization�Centre��SMART���������������������Standardized�Monitoring�&�Assessment�of�Relief�and�Transition��TB���������������������������Tuberculosis��TFP��������������������������Therapeutic�Feeding�Programme��TSFP������������������������Targeted�Supplementary�Feeding�Programme��U5���������������������������UnderͲfive��UC���������������������������Union�Council��UNICEF��������������������United�Nations�Children’s�Fund��WFH������������������������WeightͲforͲHeight��WFP������������������������World�Food�Programme��WHO�����������������������World�Health�Organization��

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������4�

Key�Findings�

x Overall,� in�northern�Dadu�district� (Talukas�Mehar� and�KN� Shah),� the�prevalence�of�GAM� =�19.5%� (17.6%� Ͳ21.5%)�and�SAM�=�5.3%�(4.2%�Ͳ�6.6%;�based�on�weightͲforͲheight�zͲscores�results,�WHO�2006�standards,�95%�Confidence�Interval).���

x Mehar�Taluka�recorded�the�worst�results,�i.e.,�the�highest�prevalence�of�GAM�=�19.9%�(17.3%�Ͳ�22.7%)�and�the�highest� prevalence� of� SAM� 5.9%� (4.4%� Ͳ� 7.9%;� based� on� weightͲforͲheight� zͲscores� results,� WHO� 2006�standards,�95%�Confidence�Interval).�

x In�Mehar,�when�results�were�based�on�Middle�Upper�Arm�Circumference�(MUAC),�the�prevalence�of�GAM�was�25.4%�(20.6%�Ͳ�31.0%)�and�the�prevalence�of�SAM�was�11.8%�(9.0%�Ͳ�15.3%).��

x Across� the�area,� the�prevalence�of�underweight�was�49.6%� (46.2%� Ͳ�52.9%)�and� the�prevalence�of�stunting�was�52.7%�(49.2%�Ͳ�56.2%).��

x The�measles� vaccination� coverage�was� 63.4%� and� 71.3%� in� KN� Shah� and�Mehar� respectively,� below� the�national�80%�immunization�coverage�reported�in�2008�and�2009.�

x The�BCG�immunization�coverage�was�71.8%�and�80.6%�in�KN�Shah�and�Mehar�respectively,�here�again�below�the�national�90%�target�coverage�set�by�national�EPI�guidelines.�

x Vitamin�A�supplementation�coverage� in�northern�Dadu�was�95.2%,�above�the�national�coverage�reported� in�2009.����

x Across� northern�Dadu� district,� occurrence� of� illnesses�within� the� two�weeks� prior� to� the� survey�was� high�(63.3%).��

x Fever� (suspected�malaria)�was� the�most� prevalent� illness� found� in� both� Talukas,�with� overall� 40%� of� U5�children�in�northern�Dadu�district�being�affected.��

x Crude�mortality�rates�(CMR)�were�0.58�and�0.94�deaths/10,000�people/day�in�KN�Shah�and�Mehar�respectively�both�above�the�emergency�threshold�(0.4�deaths/�10,000people/day)�for�South�Asian�Region.�

x UnderͲfive�mortality�rate�(U5MR)�was�2.1�deaths/10,000�U5�children/day�in�Mehar�Taluka,�more�than�2�times�above�the�emergency�threshold�(0.9�deaths/10,000�U5�children/day).�

� �

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������5�

1. INTRODUCTION�

1.1 Background�

Over�the�last�ten�years�in�Pakistan,�underͲfive�malnutrition�rates�remained�persistently�high.�While�the�proportion�of�underweight�and�stunted�children�stagnated�slightly�above�30%�and�40%�respectively,�the�prevalence�of�wasting�increased� up� to� 15%� country�wide� according� the� latest� national� nutrition� survey� conducted� by� the� Aga� Khan�University1.��

In�Sindh�province,�the�situation�was�found�to�be�even�more�critical�than�at�national�level.�Six�months�after�the�2010�Pakistan�monsoon�floods�hit,�the�Flood�Affected�Nutrition�Survey�(FANS)2�results�showed�a�GAM�rate�of�23.1%�in�Northern� Sindh� and� of� 21.2%� in� Southern� Sindh.� These� rates� are�well� above� the�World� Health�Organization's�(WHO)�15%�emergency�threshold� level.�Furthermore,�results�revealed�a�Severe�Acute�Malnutrition�(SAM)�rate�of�6.1%�and�2.9%�in�Northern�and�Southern�Sindh�respectively.��

At�district� level,� in�November�2007�and� in� June�2008�ACF�conducted�surveys� in�the�Dadu�district�area� that�both�showed�high�prevalence�of�Global�Acute�Malnutrition�(GAM)�among�6Ͳ59�months�children�(18%�in�2007�and�22%�in�2008)�3,4.��

Considering� the�extent�of� the�2011� flood�damage� in�Sindh,� recurring�emergency� situations�are� likely� to�have�a�serious� impact�on� the�nutritional� status�of�underͲfive� children� (U5),�and�pregnant�and� lactating�women� (PLW),�situation�which�needs�to�be�continuously�monitored.�

2.1�Survey�rationale�

In�Dadu�district,�ACF,� funded�by� the�Canadian� International�Development�Agency� (CIDA)� implements�a�nutrition�program�(operational�since�September�2011)�aiming�at�reducing�mortality�and�morbidity�and�at�improving�health,�and�nutritional�status�of�most�vulnerable�groups�(U5�and�PLW)�through�a�CommunityͲbased�Management�of�Acute�

Malnutrition� (CMAM)�approach.��

In� order� to� have� accurate�information� regarding� the�current� nutritional� status� of�under� 5� children� located� in�areas�containing�most�of�the�CMAM� programme� sites,�ACF� undertook� a� nutrition�survey� in� collaboration�with�the�district�authorities� in�KN�Shah� and�Mehar� Talukas� of�Dadu�district�(�Figure�1)�from�the� 1st� through� the� 17th� of�October,�2011.�

�Figure�1:��Nutrition� survey� area� in�Dadu�district�

1�National�Nutrition�Survey,�Pakistan.�Sep�2011�2�Preliminary�Results�Ͳ�Anthropometry.�FANS�Ͳ�Southern�Sindh.�October�29th�Ͳ�November�4th�2010�3ACF�Final�Report.�Nutritional�Assessment�on�FloodͲAffected�Populations,�KamberͲShahdadkot�and�Dadu�Districts,�Sindh�Province,�Pakistan.�November�2007.�4ACF� Nutritional� Anthropometric� and� Retrospective�Mortality� Survey� Children� aged� 6� to� 59�months� KamberͲShahdadkot�and�Dadu�Districts,�Sindh�Province,�Pakistan.�May�–�June�2008�

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������6�

2. OBJECTIVES�

2.1 General�Objective�

The� general� objective� of� this� survey�was� to� assess� the� current� nutritional� status� of� under� 5� children,� and� to�estimate�mortality�rates�in�northern�Dadu�district�area.�

2.2�Specific�Objectives�

The�specific�objectives�of�the�survey�were:�

o To�determine� the�prevalence�of� acute�malnutrition� in� children� 6Ͳ59�months� (prevalence�of� global� and�severe�acute�malnutrition�in�terms�of�zͲscores�and/or�oedema�and�95�per�cent�confidence�intervals).�

o To�estimate� the� crude�mortality� rate� (CMR)�and� the�mortality� rate� in�children� less� than�5�years�of�age�(U5MR;�CMR�and�U5MR�and�95%confidence�intervals).�

o To� estimate� the� prevalence� of� measles� and� BCG� vaccination� coverage� and� the� rate� of� Vitamin� A�Supplementation.�

o To� make� recommendations� toward� improvement� of� current� nutrition� interventions� and� to� provide�guidance�for�future�operation�plan�strategies.�

3. METHODOLOGY�

3.1�Study�design�

The� survey� was� done� using� the� Standardized� Monitoring� &� Assessment� of� Relief� &� Transition� (SMART)�methodology.�The�survey�was�conducted�consecutively�in�two�Talukas�of�Dadu�districts,�i.e.,�KN�Shah�and�Mehar.�A�twoͲstage�cluster�sampling�method�was�used�to�select�clusters�and�households.��

x In�stage�one,�35�clusters�of�15�households�were�randomly�selected�in�each�according�to�village�population�size�(probability�proportional�to�population�using�ENA�for�SMART�software).�

x In�the�second�stage,�systematic�random�sampling�or�EPI�method�(depending�on�village�size�and�location)�was�used�to�select�15�households.��

x All�6Ͳ59�months�children�of�selected�households�were�assessed�and�mortality�questionnaire�administered�to�all�selected�households�to�estimate�crude�death�rate�and�underͲfive�mortality�(based�on�90�day�recall).�

3.2�Sample�size�determination�

Sample�size�for�malnutrition�and�mortality�is�calculated�separately�as�described�below.��

a) Sample�size�for�Anthropometry��

The�anthropometric� sample� size� calculation�was�performed�with�estimated�prevalence�of�acute�malnutrition�of�20%,�with�5%�precision,�a�design�effect�of�2�(based�on�the�fact�that�within�the�geographic�units�selected�population�were�expected�not�to�be�equally�affected),�and�the�estimated�proportion�of�the�underͲfive�populations�being�17%�of�total�population�(based�from�the�demographic�information�obtained�from�the�district�and�following�the�results�of�the�latest�available�nutrition�surveys�implemented�in�the�Province5).�Average�household�(HH)�was�estimated�to�be�7.�Estimated�proportion�of�non� response�HHs�used�was�5%.�Taken� these�parameters� into�ENA�software,�525�HHs�were�required�as�a�total�sample�size�for�anthropometry.�Considering�the�time�needed�to�travel�daily�to�survey�sites,� 15� households� per� team� per� day�was� set� as� achievable.� Therefore,� the� total� number� of� clusters� to� be�surveyed�was� equal� to� 35� (calculated� by� dividing� the� total� number� of� households� to� be� surveyed� by� 15� HHs�assessed�per�team�per�day).�These�35�clusters�were�randomly�selected�by�ENA�software�from�the�villages�list�with�their�respective�population.��

� �

5�ACF�Integrated�assessment�Survey�/�Mirpur�Bathoro�Thaluka�/�Pakistan,�December�2010��

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������7�

b) Sample�size�for�Mortality��

The�mortality�sample�size�was�estimated�based�on�the�expected�crude�mortality�rate�(CMR)�of�0.4�death�/10�000�people/day�with�a�precision�of�0.3;�a�design�effect�of�1.5;�90Ͳday�recall�period;�and�an�average�household�size�of�7.�Design�effect�for�CMR�was�estimated�to�be�1.5�because�it�was�assumed�that�the�expected�mortality�rate�would�be�below�emergency�threshold�and�similar�across�clusters.�Taken�these�parameters�into�ENA�software,�the�number�of�individuals�needed�to�mortality�rates�was�2,846,�i.e.,�428�HHs.�

Conclusion� about� the� survey� sample� size:� As� per� the� SMART� guidelines,� it� is� recommended� to� use� the� higher�number�of�households�when�the�anthropometric�and�mortality�sample�sizes�vary.�In�this�case,�the�anthropometric�sample� size�was�used� for� the� survey� and� 35� clusters�of�15�households�were� randomly� selected� in� each� Taluka�according�to�village�population�size�(probability�proportional�to�population�using�ENA�for�SMART�software).�

3.3�Sampling�methodology�

a) Sampling�universe�

Pakistan� comprises�of� four�provinces,�each�divided� into�districts,�and�districts�are�divided� in� to�Talukas,�Talukas�subdivided� in�Union�Councils� (UCs),�which� are� further�divided� into� ‘deh’.�A� ‘deh’� consists�of� several� villages�or�‘goth’.�Our�sampling�universe�in�the�present�survey�was�a�village.�The�local�government�provided�the�complete�list�of�villages�with�their�respective�population.��

b) Cluster�selection��

As�mentioned�earlier� (sample�size�determination�paragraph�3.2),�a�total�of�35�villages� (clusters)�per�Taluka�were�randomly�selected�based�on�the�probability�proportional�to�population�size�(PPS)�using�ENA�Beta�software.�

c) Household�selection�

Once�survey�teams�reached�the�selected�clusters,�and�village�leaders�were�met�and�the�purpose�of�the�survey�and�its� procedures� were� explained.� After� obtaining� the� permission� of� the� village� leader,� two� methodologies� for�selecting�households�were�employed�depending�on�the�population�size�of�the�selected�village.�

x Villages�with�less�than�1000�people�

In�small�villages,�systematic�sampling�was�used.�The�nutrition�survey�teams�first�listed�all�households�in�the�village.�The�sampling�interval�was�calculated�(amount�of�HH�present�in�the�village/15�HHs�to�be�surveyed).�Thereafter,�the�first�HH�was� chosen�using�and�a� random� table� that�was�drawn�between�one�and� the� sampling� interval� for� the�assignment�of� the� first�house,�and�using� the�sampling� interval� for�selection�of�all�other�HHs,�and�15�households�were�drawn.��

x Villages�with�more�than�1000�people�

In�large�villages,�the�EPI�method�was�employed.�In�this�case,�when�surveyors�arrived�at�the�selected�village,�after�discussions�held�with�village�leaders,�the�following�procedure�was�followed:�

In�the�centre�of�each�village,�the�survey�team�chose�a�direction�by�using�the�“spinning�pencil�method”,�whereby�a�pen�is�thrown�to�decide�the�way�of�direction.�All�team�members�walked�to�the�edge�of�the�village�following�the�direction�indicated�by�the�pen.�When�the�border�was�reached,�a�new�direction�was�randomly�selected�by�spinning�the�pen�again�until�it�pointed�into�the�body�of�the�village.�Then,�the�team�walked�through�the�end�of�the�selected�direction�labeling�all�available�HHs.�The�first�house�was�selected�by�using�a�random�table.�The�second�house�was�taken�by�proximity,�always�choosing�the�house�on�the�right�hand�side�when�leaving�the�first�house�and�continued�until�the�required�HHs�data�were�collected.��In�all�selected�households�the�retrospective�mortality�questionnaire�was�filled�out,�even�if�no�underͲfive�children�were�present.�In�addition,�in�some�villages,�a�segmentation�method�was�applied,�which�was�followed�by�systematic�random�sampling�as�mentioned�above.�

3.4�Survey�team�composition�and�training��

Prior� to� the� survey,� surveillance� staff� received�a�3�day� training�on�SMART�methodology�conducted�by� the�ACF�Nutrition�Surveillance�Program�Manager�(PM).�The�team�received�theoretical�trainings�on�topics�such�as�definition�of�malnutrition,� underlying� causes,� basic� sampling� concepts� and� the� SMART� survey�methodology.� That� was�followed�by�a�practical�exercise�on�anthropometric�measurements�techniques,�recognition�of�signs�and�symptoms�of�malnutrition� including�nutritional�oedema,�on�how�to� identify�selected�households,�on� interview�techniques,�

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������8�

how� to� fill�out�questionnaires,� complete� interviewing�households,� avoid/minimize�errors,� and�how� to� compile�data�files.�Surveillance�staff�was�also�briefed�about�ENA�software�and�examples�of�plausibility�checks�were�shown.�Two� surveillance� team�members�were�assigned� for� the�supervision�of� the� survey�and� six�other� team�members�were�assigned�as�team�leaders.�

To� assist� the� ACF� surveillance� team,� 12� enumerators� were� recruited.� These� enumerators� were� trained� on�sampling�methodology�and�anthropometric�measurements�during�2�days�right�prior�data�collection.�One�training�day�was� devoted� to� practical� training� including� standardization� and� pilot� test.�More� than� half� of� the� training�sessions� focused�on�anthropometric�measurements.�Adequate�attention�was�given� in� training�on�standardizing�equipment� and� keeping� record� of� the� procedure.� As� a� means� to� verify� anthropometric� skills� of�teams/enumerators,�to�detect�differences�among�measurers�and� identify�their�possible�causes,�anthropometric�standardization� test�was� carried� out� during� the� 2nd� day� of� the� training� as� the�main� purpose�was� qualifying�measurers6.�A� field� test�was�also� conducted�at� the�end�of� the� training�day� in�a�nearby� village� (which�was�not�included� in� the� survey� sample� size).� This�was� done� in� order� to� provide� practical� training� to� team�members�including�household�selection.��

Finally,�six�survey�teams�each�consisting�of�1�team�leader�and�2�enumerators�were�formed,�each�team�comprising�of�at� least�one� female�member.�Two�supervisors�were�assigned� three� teams�each,�and�supervised� them� in� the�field�every�day.��

3.5�Quantitative�data�collection�techniques�

Survey� tools� for� collection� of� both� anthropometric� and�mortality� data� were� derived� from� the� standard� ENA�questionnaire�with�some�additional� information�such�as� immunization�status�and�CMAM�programme�enrolment.�The�tool�used�for�collecting�the�quantitative�data�were�structured�and�preͲtested.�Under�this�technique,�modules�and�variables�covered�are�summarized�below.�

a. Anthropometry��

Measurements�were�taken�for�all�6Ͳ59�months�children�or�65Ͳ110�cm�height�of�selected�households.�

Age�of�the�child:�was�recorded�in�months�using�a�vaccination�card�and/or�a�calendar�of�local�events.�

Height/length:�was�taken�for�children�below�85�cm,�and�the�measurement�was�taken�by�lying�the�child�horizontally�on�the� length�board;�and�height�was�taken� for�children�equal�or�above�85�cm�while�standing.�Height�and� length�were�measured�using�standard�metre�height�board� (SECA).�Before�taking�the�height/length,�children/care�takers�were� requested� to�put�off� shoes� if�any�and� stand� in�a�plankfort�position�against� the�height�board,�on� flat� level�surface.�Length/height�was�recorded�to�the�nearest�0.1�cm.�

Weight:�was�measured� by� using� a� calibrated�UNISCALE� and� recorded� to� the� nearest� 0.1� kg.� The�UNISCALE� is�designed�to�allow�a�mother/caretaker�to�hold�the�child�was�being�weighed.�The�mother�first�stands�on�the�scale�without�the�child,�the�scale�was�reset�to�zero.�The�child�to�be�weighed�was�then�passed�to�the�mother�standing�on�the�scale�allowing�the�child's�weight�to�be�indicated�on�the�scale.��All�children�were�weighed�like�the�above�method�nude�or�with�light�cloth�to�ensure�accuracy�of�weight.�

Nutritional�bilateral�Oedema:�was�diagnosed�by�applying�a�moderate�finger�pressure�for�three�seconds�just�above�the�ankle�on� the� inside�of� the� leg�where� the� shinbone� is�below� the� skin,�or�on� the� tops�of� the� feet.� If� there� is�oedema,�an�impression�remains�for�some�time�(at�least�a�few�seconds)�where�the�oedema�fluid�has�been�pressed�out� of� the� tissue.� The� child� should� only� be� recorded� as� oedematous� if� both� feet� clearly� have� oedema.� Any�suspected�oedema�case�was�verified�by�the�survey�supervisors.��

MUAC�(mid�upper�arm�circumference):�was�measured�on�the�left�upper�arm�using�the�standard�MUAC�tape.�The�reading�of�the�measurement�was�from�the�window�of�the�tape�measure�and�recorded�to�the�nearest�0.1�cm.�

Retrospective�morbidity� of� children:�Mothers� or� caretakers�were� asked�whether� or� not� a� child� had� been� sick�

6�Ten� children�were�measured� twice� for�half�of� the�enumerators.�Normally,�each�enumerator�was� supposed� to�measure�10�different�children�twice�with�a�time�interval�between�individual�measures�that�means�one�child�to�be�measured�24�times.�However,�after�the�children�were�measured� for�some�times,�the�children�were�crying�and� it�was�not�possible�to�complete�the�test.�As�a�result,�it�was�not�possible�to�calculate�both�precision�and�accuracy�of�all�enumerators� using� ENA/SMART� standardization� exercise.� However,� the� accuracy�was� analyzed� partially.� Extra�training�and�support�was�given�based�on�the�scores�attained�by�each�enumerator�during�the�standardization�test.�

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������9�

within�the�last�fifteen�days�prior�to�the�survey.�Case�definitions�of�the�most�prevalent�illnesses�were�described�in�the�child�questionnaire�(Annex�8.1).���

Vaccination�and�Vitamin�A�supplementation�coverage:�Measles�immunization�coverage�was�assessed�among�9Ͳ59�months� children�by� checking� record�on� the� immunization� card.� In� case� the� card�was�misplaced�or� torn,� verbal�response� (yes,� no,� or� do� not� know)� from� the� mother� or� caretaker� was� recorded� on� the� data� sheet.� � BCG�immunization�coverage�was�assessed�for�all�surveyed�children�by�checking�record�on�the�immunization�card�and/or�scar�on�the� left�arm.��Vitamin�A�supplementation�coverage�was�also�assessed�within�a�period�of�six�months�prior�the�survey.�

UNIMIX� (Fortified�Blended�Food)�distribution:�All�mothers�were�asked�whether� their�children� received�and�ate�UNIMIX�within�six�months�prior�the�survey.�

PLUMPYNUT� (Therapeutic�Food)�distribution:�All�mothers�were�asked�whether� their� children� received�and�ate�PLUMPYNUT�within�six�months�prior�the�survey.�

Mortality�data:�Each�selected�HH�was�asked�about�the�number�of�people�living�in�the�household�at�the�time�of�the�survey�and�the�number�of�deaths�by�age�group�(underͲfive�and�above�five�years)�during�3�months�prior�to�the�start�of�the�survey�was�recorded.�Data�on�people� joining�the�household,�new�births�and�members�of� family�departed�from�the�households�during�the�3Ͳmonth�period�was�also�recorded.�Household�size�and�the�number�of�underͲfive�in�each�household�were�recorded.�Cause�of�death�was�only�confirmed�from�the�respondents.���

b. Data�entry,�analysis�and�report�writing�

Daily�data�quality�check�was�done�on�each�questionnaire�and�data�sheet�prior�to�data�entry.�The�data�entry�and�analysis�were�done�using�ENA�for�SMART�software.�

4. ETHICAL�CONSIDERATIONS�

Each�team�was�provided�with�referral�sheets�and�all�children� identified�as�severely�or�moderately�malnourished�based�on�MUAC�or�WHZ�were�referred�to�a�nearby�CMAM�program�site.��

5. FIELD�SUPERVISION�AND�QUALITY�ASSURANCE��

Data�collection�was�done�from�the�1st�through�the�17th�of�October�2011.�The�Surveillance�PM�was�responsible�for�the�supervision�of�the�teams�and�for�the�overall�coordination�of�nutrition�survey�activities.�Constant�supervision�and�monitoring�of�all�field�activities�were�done�during�the�course�of�the�survey�to�ensure�respect�of�methodology�standards� and� accuracy.� Concurrent� crosscheck� of� the� data� collected� by� the� teams� was� performed� by� the�Surveillance�PM�in�a�random�sample�of�households.�Team�leaders�were�consulted�for�any�erogenous�or�irregular�data�on�a�daily�basis.�Discussions�were�conducted�in�each�day�after�the�teams�returned�from�field.��

6. RESULTS�

A� total� of� 1035� selected� households� were� interviewed,� and� 1606� children� (6Ͳ59�months)� were� screened� for�anthropometric�indicators.�Table�1�lists�the�sample�size�obtained�for�each�Taluka�and�contains�information�about�missing�children�and�households’�replacement�(abandoned�house).�

� �

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������10�

Table�1:�Information�related�to�sample�size,�replaced/absent�households�and�missing�children�

� KN�Shah� Mehar� Total�

Households�interviewed� 518� 517� 1035�

Children�measured� 765� 841� 1606�

Replaced�households� 0� 0� 0�

Absent�households� 7� 8� 15�

Missing�children� 3� 4� 7�

6.1 Age�and�gender�distribution��

The�overall�boy:�girl�ratio�was�equal�to�1.1�and�0.9�in�KN�Shah�and�Mehar�respectively�indicating�that�boys�and�girls�were�overall�equally�represented� (Annex�8.2).�The�6Ͳ29�months� :�30Ͳ59�months�ratio�was�equal�to�1.0� in�Mehar�and�equal�to�0.78�in�KN�Shah�indicating�an�under�representation�of�the�under�30�months�in�that�Taluka.�Reasons�behind� this�underrepresentation�of� the�youngest�are�not�clear�and�as� they�are�most�vulnerable� to�malnutrition,�under�representation�of�this�group�implies�that�the�overall�prevalence�may�be�slightly�under�estimated.�

6.2.�Nutrition�indicators�

The� Global� Acute� Malnutrition� (GAM)� and� Severe� Acute� Malnutrition� (SAM)� results� shown� in� Table� 2� were�obtained�using�ENA�software�and�SMART�flags�were�excluded�(see�Annex�8.3�as�well).��

x Talukas�Mehar�and�KN�Shah�had�an�overall�prevalence�GAM�=�19.5%�(17.6%�Ͳ�21.5%)�and�SAM�=�5.3%�(4.2%�Ͳ�6.6%;�based�on�weightͲforͲheight�zͲscores� results,�WHO�2006� standards,�95%�Confidence� Interval,�Table�2).��According� to� WHO� interpretation� level� of� malnutrition� prevalence7,� these� results� showed� that� the� U5�nutritional�situation�was�critical.�

x The�prevalence�of�oedema�was�0.1%�for�the�overall�area.�

x Mehar�Taluka�recorded�the�worst�results,�i.e.,�the�highest�prevalence�of�GAM�=�19.9%�(17.3%�Ͳ�22.7%)�and�the�highest� prevalence� of� SAM� 5.9%� (4.4%� Ͳ� 7.9%;� based� on� weightͲforͲheight� zͲscores� results,� WHO� 2006�standards,�95%�Confidence�Interval,�Table�2).�

Table� 2:� Prevalence� of�wasting� among� 6Ͳ59�months� children� per� Taluka,�WHO� 2006� Standards� (SMART� flags�excluded).�Results� in�brackets�are�expressed�with�95%�confidence� intervals.�See�results�obtained�with�NCHS�1977�standard�in�Annex�8.5.�

7�World�Health�Organization.�The�Management�of�Nutrition� in�Major�Emergencies,�Geneva:�World�Health�Organization,�2000.�

Indicators� KN�Shah�n=760�

Mehar�n=826�

Overall(Northern�Dadu)�

n=1585�

WHO�2006�standards�

GAM�WHZ<�Ͳ2�z�and/or�oedema�

19.1%�(16.3%Ͳ�22.2%)�

19.9%�(17.3%�Ͳ�22.7%)�

19.5%�(17.6%�Ͳ�21.5%)�

SAM�WHZ�<�Ͳ3�z�and/or�oedema�

4.6%�(3.1%�Ͳ�6.7%)�

5.9%�(4.4%�Ͳ�7.9%)�

5.3%�(4.2%�Ͳ�6.6%)�

NCHS�1977�standards�

GAM�WHZ<�Ͳ2�z�and/or�oedema�

17.9%�(15.2%�Ͳ�21.0%)�

19.7%�(16.8%�Ͳ�23.0%)�

18.9%�(16.9%�Ͳ�21.1%)�

SAM�WHZ�<�Ͳ3�z�and/or�oedema�

1.2%�(0.7%�Ͳ�2.1%)�

3.3�%�(2.3%�Ͳ�4.7%)�

2.3%�(1.7%�Ͳ�3.2%)�

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������11�

x In�both�Talukas,�results�showed�that�the�prevalence�of�SAM�was�higher�in�the�6Ͳ29�months�age�group�than�in�the�30Ͳ59�months�(Annex�8.4).�

x When�results�were�based�on�Middle�Upper�Arm�Circumference�(MUAC),�in�Mehar,�the�prevalence�of�GAM�was�25.4%�(20.6%�Ͳ�31.0%)�and�the�prevalence�of�SAM�was�11.8%�(9.0%�Ͳ�15.3%;�Table�3).�MUACͲbased�results�also�showed� that� in�Mehar� there�was�a�significant�difference�between�boys�and�girls,�with�a�prevalence�of�SAM�equal� to�14.1%�among�girls�and�equal� to�9.3�%�among�boys� (Annex�8.6).�Further�studies�would�need� to�be�done�in�order�to�confirm�and�explain�why�in�Mehar�Taluka�girls�indeed�tend�to�be�more�at�risk�than�b�

Table�3:�Prevalence�of�GAM�and� SAM�based�on�MUAC.�Results� in�brackets�are�expressed�with�95%� confidence�intervals.�See�MUAC�based�results�segregated�by�gender�in�Annex�8.6.�

Indicators� KN�Shah� Mehar� Overall(Northern�Dadu)�

GAM�(MUAC<125mm)�

19.7%�(16.0%�Ͳ�24.1%)�

25.4%�(20.6%�Ͳ�31.0%)�

22.7%�(19.6%�Ͳ�26.2%)�

SAM�(MUAC<115mm)�

4.6%�(3.1%�Ͳ�6.6%)�

11.8%�(9.0%�Ͳ�15.3%)�

8.3%�(6.6%�Ͳ�10.6%)�

x Overall,� in� northern� Dadu� district,� the� prevalence� of� underweight� was� 49.6%� (46.2%� Ͳ� 52.9%)� and� the�prevalence�of�stunting�was�52.7%�(49.2%�Ͳ�56.2%;�Table�4).�These�findings�were�slightly�higher�and�consistent�with�results�obtained�by�the�MoH/Aga�Khan�University�in�September�20113,�which�were�40.5%�and�49.8%�for�underweight�and�stunting�respectively,�for�underͲfive�children�in�Sindh�province.�

Table�4:�Prevalence�of�chronic�malnutrition�(stunting)�and�underweight�per�Taluka,�WHO�2006�Standards�(SMART�flags�excluded).�The�results�in�brackets�are�expressed�with�95%�confidence�intervals.��

Indicators� KN�Shah� Mehar� Overall�(Northern�Dadu)�

Stunting�H/A<�Ͳ2�z�

51.3%�(45.4%�Ͳ�57.3%)�

54.1%�(50.0%�Ͳ�58.1%)�

52.7%�(49.2%�Ͳ�56.2%)�

Underweight�W/A<�Ͳ2�z�

46.2%�(41.5%�Ͳ�51.0%)�

52.6%�(47.9%�Ͳ�57.3%)�

49.6%�(46.2%�Ͳ�52.9%)�

6.3.�Health�Indicators�

x The�measles�vaccination�coverage�was�63.4%�and�71.3%�in�KN�Shah�and�Mehar�respectively�(Table�5),�below�the�national�80%�immunization�coverage�reported�in�20088�and�20099.�

x The�BCG� immunization� coverage�was�71.8%�and�80.6%� in�KN�Shah�and�Mehar� respectively� (Table�5),�here�again�below�the�national�90%�target�coverage�set�by�national�EPI�guidelines8.��

Table�5:�Measles�and�BCG�Vaccination�coverage�

Vaccination�Coverage� KN�Shah� Mehar� Total�

Measles�

Eligible�Children� n=744� n=815� n=1559�With�Vaccination�Card� 7%� 4.6%� 5.8%�

Without�Card� 56.4%� 66.7%� 61.5%�Total�Coverage� 63.4%� 71.3%� 67.4%�

BCG� 71.8%� 80.6%� 76.2%�

8Pakistan�Expanded�Programme�on�Immunization�(EPI)�guidelines,��PILDAT�May�2010�9Pakistan�statistics,�Unicef�report,�2009�

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������12�

x Vitamin�A� supplementation� coverage� in� northern�Dadu�was� 95.2%� (Table� 6),� above� the� national� coverage�reported�in�200913.��

Table�6:�Vitamin�A�Supplementation�Coverage�

Vit�A�Supplementation� Kn�Shah� Mehar� Total�

Eligible�Children� 765� 841� 1606�

Received�(Without�Record)� 94.1%� 96.2%� 95.2%��x There�were�94�children�(5.9%�of�total�surveyed�children)�reported�having�received�Unimix,�i.e.,�being�enrolled�

in�a�Supplementary�Feeding�Program� (SFP)�at�a�given� time�within� the�6Ͳmonth�period�preceding� the�survey�(Table�7).�There�were�99�children�(6.2%�of�total�surveyed�children)�reported�having�received�PlumpyNut,�i.e.,�being� enrolled� in� an� Outpatient� Therapeutic� Program� (OTP)� at� a� given� time� within� the� 6Ͳmonth� period�preceding�the�survey.�

Table�7:�Children�reported�to�have�received�UNIMIX�or�PLUMPYNUT�

�Kn�Shah� Mehar� Total�

n� %� n� %� n� %�

UNIMIX�Yes� 48� 6.3� 46� 5.5� 94� 5.9�

No� 717� 93.7� 795� 94.5� 1512� 94.1�

PLUMPYNUT�Yes� 50� 6.5� 49� 5.9� 99� 6.2�

No� 715� 93.5� 792� 94.1� 1507� 93.8�

6.4�Morbidity�

x Across�northern�Dadu�district,�occurrence�of�illnesses�was�high,�i.e.,�63.3%�of�surveyed�children�were�reported�sick�during�the�2Ͳweek�period�prior�the�survey�(Table�8).�

Table�8:�Occurrences�of�illness�among�6Ͳ59�months�children�

KN�Shah� Mehar� Total�

Illness�in�past�2�weeks� 61.4%� 65.3%� 63.3%�

�x Fever� (suspected�malaria)�was� the�most�prevalent� illness� reported� in�both�Talukas,�with�overall�40%�of�U5�

children�in�northern�Dadu�district�being�affected�(Table�9).��

x 12.6%�of�U5�children�were�reported�as�being�affected�by�diarrhoea�during�past�two�weeks�prior�to�the�survey.�This�percentage�is�slightly�below�the�September�2011�national�nutrition�survey4�results.��

Table�9:��Diagnosis�for�children�with�recorded�illness�in�past�2�weeks�

KN�Shah� Mehar� Total�Diarrhoea�

Malaria/Fever�ARI/cough�

17.7%34.6%�9.1%�

8.0%45.2%�12.1%�

12.6%39.9%�10.6%�

6.5�Mortality�

x Crude�mortality�rate�(CMR)�(total�deaths/10,000�people/day)�was�estimated�at�0.58�(0.33�Ͳ�1.0)�(95%�CI)�and�0.94�(0.57�Ͳ�1.56)�for�KN�Shah�and�Mehar,�respectively�(Table�10).��

x UnderͲfive� mortality� rate� (U5MR)� (deaths� in� children� underͲfive/10,000� children� underͲfive/day)� was�estimated�at�0.82�(0.38�Ͳ�1.80)�(95%�CI)�and�2.10�(1.08Ͳ�4.02),�respectively�for�KN�Shah�and�Mehar.��

x Both� the�crude�mortality�and�U5�mortality� rates�were�well�above�emergency� thresholds�of� for�South�Asian�Region9.�

ACF,�K.N.�Shah�and�Mehar�Talukas�Nutrition�Survey,�Pakistan,�November�2011�������������13�

Table�10:�CMR�and�U5MR�(90Ͳday�recall�period)�

KN�Shah� Mehar�

CMR�(deaths/10,000�people/day)�0.58

(0.33�Ͳ�1.0,�CI�95%)��

0.94�(0.57�Ͳ�1.56,�CI�95%)�

�U5MR�

(deaths�in�U5�children/10,000�U5�children�/day)�0.82

(0.38�Ͳ�1.80,�CI�95%)�2.10�

(1.08Ͳ�4.02,�CI�95%)�

7. CONCLUSIONS�AND�RECOMMENDATIONS�

x Survey�results�showed�that�the�nutritional�situation�of�U5�children�across�northern�Dadu�district�was�critical�with�an�overall�prevalence�of�GAM�=�19.5%�(17.6%�Ͳ�21.5%)�and�SAM�=�5.3%�(4.2%�Ͳ�6.6%;�based�on�weightͲforͲheight� zͲscores� results,�WHO� 2006� standards,� 95%� Confidence� Interval).� There�were� also� a� number� of�aggravating� factors� including� low� immunization� coverage,� high�morbidity,� and� high� rates� of�mortality.� In�Mehar� Taluka,� CMR� and� U5MR�were� significantly� above� emergency� thresholds� reflecting� how� critical� the�situation�was�in�this�Taluka.�Some�of�the�likely�causes�of�combined�high�mortality�and�malnutrition�rates�could�be�acute�food�insecurity�and�poor�coping�mechanisms�in�response�to�chronic�poverty.��

x Moreover,�the�prevalence�of�acute�malnutrition�was�high� in�the�age�range�of�6Ͳ29�months.� It� is�common�for�younger�children� to�be�at�higher� risk�of�acute�malnutrition.�This�might�be�due� to� inadequate�breastfeeding�practices�and�complementary�diets,�and�a� lower� resistance�of�young�children� to�diseases.�Generally,�young�children�are�most�susceptible�to�any�disease�and�as�a�result�easily�lose�weight.�Similar�trend�was�observed�in�the�national�nutrition�survey�of�Pakistan3,4,10.��

x Concerning�the�chronic�malnutrition,�the�prevalence�of�stunting�was�52.7%�(49.2%�Ͳ�56.2%)�while�underweight�was�49.6%� (46.2%� Ͳ�52.9%).�These� findings�were� slightly�higher�and�consistent�with� results�obtained�at� the�province�level�by�the�MoH/Aga�Khan�University�in�September�20113,�which�were�49.8%�and�40.5%�for�stunting�and�underweight�respectively,�for�underͲfive�children�in�Sindh�province.�

�Results�presented� in�this�report�confirmed�the�urgent�need�to�treat�current�malnourished�children�and�to�design�long�term�prevention�of�acute�malnutrition�strategies� in�order�to� improve�the�overall�nutritional�situation�of�the�population.�The�following�recommendations�are�made�as�possible�approaches�that�could�mitigate�the�severity�of�the�situation:��

x CMAM�programs�in�Dadu�district�to�scale�up��

x To�advocate�for�CMAM�approach�to�be�included�in�all�health�units�routine�activities.�

x Measles�and�BCG�vaccination�coverage�should�be�increased�and�where�possible�referrals�should�be�made�from�the�nutrition�programs�to�health�programs.�

x A�Nutrition�Causal�Analysis� should�be�planned� in�order� to�obtain�a�broader�understanding�of� the�causes�of�malnutrition�in�Dadu�district.��

x Nutrition�&�health�actors�to�work�together�with�partners� in�Food�Security�/�Livelihoods�and�Water,�Sanitation�and�Hygiene�to�address�the�underlying�causes�of�malnutrition.�

10�ACF,�Nutrition�Survey:�North�West�Frontier�Province,�Pakistan,�April/May�2006�

.

8. ANNEXES��

8.1.�Anthropometry�Questionnaire�

Survey�Date:�____/____/2011���UC;�Name_______________� ‘Deh’�Name�_______________;�Village�Name:_______�� �

Cluster�Number:�______________;�Team�Number:�______________;�T.�Leader:�_____________________��

�Child�No.�

�HH�No.�

��Name�

Sex��(F/M)�

Date�of�Birth�(DD/MM/YY)�

�Age�(months)�

Wt.�(kg)�100g�

Ht�(cm)�0.1�cm�

Oedema��(Y/N)�

MUAC�in�cm�

WH%� Vitamin� A�in� the� last�six�months�0=�no�1=yes�

Vaccination� in� the�last�6�months�

Illness�in�the�last�2�weeks�No=�0�Diarrhea=1�Cough=3�Fever=3�Other=4�

Did� child�receive�CSB/�unimix� in�last� 6�months�0=N�1=Y�

Did� child�receive�RUTF� in�last� 6�months�0=N�1=Y�

BCG�Mark�0=�no�1=yes�

Measles�yes� card=�1�yes� no�card=2�no=�0�

1� � � � � � � � � � � � � � � � �2� � � � � � � � � � � � � � � � �3� � � � � � � � � � � � � � � � �4� � � � � � � � � � � � � � � � �5� � � � � � � � � � � � � � � � �6� � � � � � � � � � � � � � � � �7� � � � � � � � � � � � � � � � �8� � � � � � � � � � � � � � � � �9� � � � � � � � � � � � � � � � �10� � � � � � � � � � � � � � � � �1=Diarrhea,�more�than�three�loose�stools/day;�2=�cough�or�difficulty�breathing;�3=�Fever�or�high�temperature;�4=�other�illness�in�the�two�weeks�before�the�survey.��

��� �

.

8.2�Mortality�Questionnaire�

Survey�date� ____/____/2011� � ��UC;�Name_______________� ‘Deh’�Name�______________�Village�Name:�______________________� Cluster�Number:�_____________;�Team�Number:�_____________;��T.�Leader:�_______________��

HH�HH�Members� Join�HH�since�

Start�date�Leave�HH�since�Start�date� No.�births�

Since�start�date�

Deaths�since�Start�date� Cause�of�

death�Total� <� 5�

years�Total� <� 5�

years�Total <� 5�

years�Total� <� 5�

years�1� � � � � �

�2� � � � � �

�3� � � � � �

�4� � � � � �

�5� � � � � �

�Key�for�cause�of�death:�1�=�Diarrhea,�2=ARI/cough,�3=�fever,�4=�measles,�5�=�accident,�6�=unknown,�7=�other�(specify)�ARI=Acute�Respiratory�Infection��

.

8.3�Age�And�Gender�Distribution�

Tables�11�and�12�show�age�and�gender�distributions�among�surveyed�children.�It�is�not�clear�why�there�were�more�males�than�females�in�the�6Ͳ29�months�age�bracket�in�KN�Shah�and�in�the�54–59�month�age�group�in�Mehar.�In�the�later�case,�it�could�be�due�to�the�fact�that�in�some�villages�survey�teams�were�not�allowed�to�enter�houses,�and�it�is�possible�that�families�preferred�not�to�allow�their�older�female�children�to�be�included�in�the�survey.��

Table�11:�Age�and�gender�distribution�among�surveyed�children�in�KN�Shah.�

Age�group�in�months�

Boys� Girls Total Ratio�no.� %� no. % no. % Boy:Girl

6Ͳ17� 97� 57.7� 71 42.3 168 22.0 1.4�18Ͳ29� 93� 55.7� 74 44.3 167 21.8 1.3�30Ͳ41� 109� 52.9� 97 47.1 206 26.9 1.1�42Ͳ53� 78� 46.7� 89 53.3 167 21.8 0.9�54Ͳ59� 24� 42.1� 33 57.9 57 7.5 0.7�Total� 401� 52.4� 364 47.6 765 100.0� 1.1�

Table�12:�Age�and�gender�distribution�among�surveyed�children�in�Mehar�

Age�group�in�months�

Boys� Girls Total Rationo.� %� no. % no. % Boy:Girl

6Ͳ17� 106� 48.2� 114 51.8 220 26.2� 0.9�18Ͳ29� 87� 43.3� 114 56.7 201 23.9� 0.8�30Ͳ41� 94� 48.2� 101 51.8 195 23.2� 0.9�42Ͳ53� 89� 51.7� 83 48.3 172 20.5� 1.1�54Ͳ59� 31� 58.5� 22 41.5 53 6.3 1.4�Total� 407� 48.4� 434 51.6 841 100.0� 0.9�

�� �

.

8.4�Distribution�Of�Anthropometry�Result�Compared�To�International�Reference��

The�entire�weight� for�height�distribution�curve�of� the� sample� is� skewed� to� the� left� (Figure�2)�with�a� fairly�even�distribution,�which�indicated�that�the�sample�population�has�a�poorer�nutritional�status�than�that�of�the�reference�one.�Figure�2� shows� the�weight� for�height�distribution�curve�of� the� survey� sample� in�ZͲscores�compared� to� the�WHO�standard�population�

Figure�2.�Weight�for�height�distribution�curve�compared�to�WHO�standards��

8.5�Prevalence�of�acute�malnutrition�of�both�Talukas�by�age�group�

Age�(mo)�

Total�no.�

Severe�wasting�

(<Ͳ3�zͲscore)�

Moderate�wasting�(>=�Ͳ3�and�<Ͳ2�zͲ

score�)�

Normal(>�=�Ͳ2�z�score)�

No.� %� No. % No. %6Ͳ17� 375� 54� �14.4� 79 21.1 241 64.318Ͳ29� 365� 18� ��4.9� 65 17.8 282 77.330Ͳ41� 398� 6� ��1.5� 45 11.3 347 87.242Ͳ53� 339� 3� ��0.9� 24 �7.1 312 92.054Ͳ59� 109� 2� ��1.8� 12 11.0 95 87.2Total� 1586� 83� ��5.2� 225 14.2 1277 80.5

� �

.

8.6�Prevalence�of�acute�malnutrition�segregated�by�gender�(WHO�2006�and�NCHS�1977�Standards)�

20�children�with�SMART�flags�were�excluded�of�the�analysis.�

Figures�provided�with�a�95%�of�Confidence�interval.�

Indicator�KN�Shah� Mehar� Over�all��Boys�n�=�398�

Girls�n�=�362�

All�n�=�760�

Boys�n�=�401�

Girls�n�=�425�

All�n�=�826�

All�n�=�1586�

WHO�2006�Prevalence�of�global�malnutrition��(<Ͳ2�zͲscore�and/or�oedema)�

(86)�21.6�%�(17.7�Ͳ�26.1)�

(59)�16.3�%�(12.3�Ͳ�21.3�)�

(145)�19.1�%�(16.3�Ͳ�22.2�)�

(87)�21.7%�(17.7�Ͳ�26.3)�

(77)�18.1%�(15.1�Ͳ�21.6)�

(164)�19.9%�(17.3�Ͳ�22.7)�

(309)�19.5%�(17.7�Ͳ�21.4)�

Prevalence�of�moderate�malnutrition��(<Ͳ2�and�>=Ͳ3�zͲscore,�no�oedema)��

(63)�15.8�%�(12.8�Ͳ�19.4�)�

(47)�13.0�%�(9.5�Ͳ�17.4�)�

(110)�14.5�%�(11.9�Ͳ�17.5�)�

(60)�15.0%�(12.0�Ͳ�18.5)�

(55)�12.9�%�(10.1�Ͳ�16.4)�

(115)�13.9�%�(12.0�Ͳ�16.1�)�

(225)�14.2�%�(12.6�Ͳ�16.0)�

Prevalence�of�severe�malnutrition��(<Ͳ3�zͲscore�and/or�oedema)��

(35)�4.6�%�(3.1�Ͳ�6.7�)�

(23)�5.8�%�(3.6�Ͳ�9.0�)�

(35)�4.6�%�(3.1�Ͳ�6.7�)�

(27)�6.7�%�(4.6�Ͳ�9.7�)�

(22)�5.2�%�(3.6�Ͳ�7.4�)�

(49)�5.9�%�(4.4�Ͳ�7.9�)�

(84)�5.3�%�(4.2�Ͳ�6.7)�

NCHS�1977�

� Boys�n�=�401�

Girls�n�=�363�

All�n�=�764�

Boys�n�=�407�

Girls�n�=�434�

All�n�=�841�

All�n�=�1605�

Prevalence�of�global�malnutrition��(<Ͳ2�zͲscore�and/or�oedema)�

(82)�20.4�%�(16.6�Ͳ�25.0�)�

(55)�15.2�%�(11.6�Ͳ�19.6�)�

(137)�17.9�%�(15.2�Ͳ�21.0�)�

(76)�18.7�%�(14.9�Ͳ�23.2�)�

(90)�20.7%�(16.9�Ͳ�25.2)�

(166)�19.7�%(16.8�Ͳ�23.0)�

(303)�18.9�%�(16.8�Ͳ�21.1)�

Prevalence�of�moderate�malnutrition��(<Ͳ2�z�and�>=Ͳ3�zͲscore,�no�oedema)��

(76)�19.0%�(15.3�Ͳ�23.3)�

(52)�14.3%�(10.8�Ͳ�18.8)�

(128)�16.8�%�(14.1�Ͳ�19.8)�

(63)�15.5�%�(11.9�Ͳ�19.9�)�

(75)�17.3%�(13.6�Ͳ�21.7)�

(138)�16.4�%�(13.9�Ͳ�19.3)�

(266)�16.6�%�(14.6�Ͳ�18.7)�

Prevalence�of�severe�malnutrition��(<Ͳ3�zͲscore�and/or�oedema)��

(6)�1.5�%�(0.7�Ͳ�3.2)�

(3)�0.8�%�(0.3�Ͳ�2.5)�

(9)�1.2%�(0.7�Ͳ�2.1)�

(13)�3.2�%�(1.7�Ͳ�5.8)�

(15)�3.5%�(2.1�Ͳ�5.5)�

(28)�3.3�%�(2.3�Ͳ�4.7)�

(37)�2.3�%�(1.7�Ͳ�3.1)�

� �

.

8.7�Prevalence�of�acute�malnutrition�based�on�MUAC�segregated�by�gender.�

Indicator�KN�Shah� Mehar� Over�all��Boys�n�=�401�

Girls�n�=�364�

All�n�=�765�

Boys�n�=�407�

Girls�n�=�434�

All�n�=�841�

All�n�=�1606�

Prevalence�of�global�malnutrition��(<�125�mm�and/or�oedema)�

(77)�19.2�%�(14.4�Ͳ�25.2�)�

(74)�20.3�%�(16.5�Ͳ�24.7�)�

(151)�19.7�%�(16.0�Ͳ�24.1�)�

(93)�22.9�%�(17.3�Ͳ�29.6�)�

(121)�27.9�%�(22.7�Ͳ�33.7�)�

(214)�25.4�%�(20.6�Ͳ�31.0�)�

(365)�22.7%�(19.4�Ͳ�26.5)�

Prevalence�of�moderate�malnutrition��(<�125�mm�and�>=�115�mm,�no�oedema)��

(60)�15.0�%�(10.9�Ͳ�20.3�)�

(56)�15.4�%�(12.1�Ͳ�19.4�)�

(116)�15.2�%�(11.9�Ͳ�19.1�)�

(55)�13.5�%�(9.7�Ͳ�18.5�)�

(60)�13.8�%�(10.5�Ͳ�17.9�)�

(115)�13.7�%�(10.7�Ͳ�17.3�)�

(231)�14.4%�(11.9�Ͳ�17.3)�

Prevalence�of�severe�malnutrition��(<�115�mm�and/or�oedema)��

(17)�4.2�%�(2.6�Ͳ�6.7�)�

(18)�4.9�%�(3.1�Ͳ�7.9�)�

(35)�4.6�%�(3.1�Ͳ�6.6�)�

(38)�9.3�%�(6.4�Ͳ�13.4�)�

(61)�14.1�%�(10.3�Ͳ�18.8�)�

(99)�11.8�%�(9.0�Ͳ�15.3�)�

(134)�8.3%�(6.6�Ͳ�10.4)�