ANTHROPOMETRY AND MORTALITY SURVEY

AWEIL WEST COUNTY, NORTHERN BAHR EL GHAZAL STATE

SOUTH SUDAN

APRIL 2014

Concern Worldwide Nutrition Department, South Sudan Programme

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ACKNOWLEDGEMENTS

Concern’s South Sudan team wishes to express sincere thanks to all the survey teams

composed of Team Leaders, Enumerators, Data entry operators and Drivers for their

energy and commitment shown throughout the fieldwork; it would not be possible if

they had not dedicated their time and effort to doing this job non-stop (even on

weekends).

Thanks also to RRC (Relief and Rehabilitation Commission) for their support in

conducting this survey.

Last but not least, we appreciate the time and paramount hospitality of the

community and the households who allowed us to conduct interviews and take

anthropometric measurements of their children.

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LIST OF ABBREVIATION

ARI Acute Respiratory Infection

CHD County Health Department

CI Confidence Interval

CMR Crude Mortality Rate

CMAM Community Based Management of Acute Malnutrition

ENA Emergency Nutrition Assessment

EPI Expanded Programme on Immunization

GAM Global Acute Malnutrition

HH Household

MAM Moderate Acute Malnutrition

MUAC Mid Upper Arm Circumference

N Number

OTP Outpatient Therapeutic Program

PHCC Primary Health Care Center

PHCU Primary Health Care Unit

PPS Probability Proportional to Size

SAM Severe Acute Malnutrition

SFP Supplementary Feeding Program

SMART Standardized Monitoring and Assessment of Relief and Transition

SMOH State Ministry of Health

SSRRC South Sudan Relief and Rehabilitation Commission

U5MR Under Five Mortality Rate

UNICEF United Nations Children’s Fund

WFH Weight for Height

WFP World Food Programme

WHO World Health Organization

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Table of Contents EXECUTIVE SUMMERY ................................................................................................................................6

1. INTRODUCTION ........................................................................................................................9

2. SURVEY OBJECTIVES ........................................................................................................... 10

3. METHODOLOGY .................................................................................................................... 11

3.1 Sampling Methodology ......................................................................................................... 11

3.2 Case definition and inclusion criteria ............................................................................. 13

3.3 Ethical Consideration ............................................................................................................ 14

3.4 Questionnaire, training and supervision ....................................................................... 14

3.5 Data Analysis ............................................................................................................................ 15

4. RESULTS .................................................................................................................................... 16

4.1 Anthropometric results (based on WHO Standards 2006) ................................... 16

4.1.1 Distribution by Age and Sex ................................................................................ 16

4.1.2 Prevalence of Acute Malnutrition by WFH Z-Scores ................................. 16

4.1.3 Prevalence of Acute Malnutrition based on MUAC .................................... 18

4.1.4 Prevalence of Underweight by WFA Z-Scores ............................................ 19

4.1.5Prevalence of Stunting by WFH Z-Scores ......................................................... 20

4.2 Mortality .................................................................................................................................... 21

4.3 Child morbidity....................................................................................................................... 22

4.4 Child Immunization, Vitamin A supplementation and Deworming ................... 23

4.5 Infant and Young Child Feeding Practices ................................................................... 23

4.6 Water and Sanitation ........................................................................................................... 25

4.7 Food Security........................................................................................................................... 26

5. DISCUSSION ............................................................................................................................. 29

6. RECOMMENDATIONS ......................................................................................................... 31

ANNEXES ...............................................................................................................................................

Annex 1: Plausibility Check ........................................................................................................ 32

Annex 2: Cluster Assignment .................................................................................................... 44

Annex 3: Standardization test result ...................................................................................... 52

Annex 4: Result Tables for NCHS Growth Reference 1977 ........................................... 55

Annex 5: Questionnaire ............................................................................................................... 59

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List of Tables

Table 1: Results Summery ....................................................................................................................7

Table 2: Distribution of sampled population by age and sex ............................................... 16

Table 3: Prevalence of acute malnutrition based on WFH Z-Score ................................... 17

Table 4: Prevalence of acute malnutrition by age, based on WFH Z-Score .................... 17

Table 5: Distribution of acute malnutrition & oedema based on WFH Z-Score ........... 18

Table 6: Prevalence of acute malnutrition based on MUAC ................................................. 19

Table 7: Prevalence of acute malnutrition by age, based on MUAC .................................. 19

Table 8: Prevalence of Underweight ............................................................................................. 20

Table 9: Prevalence of Underweight by age ............................................................................... 20

Table 10: Prevalence of Stunting .................................................................................................... 21

Table 11: Prevalence of Stunting by age ...................................................................................... 21

Table 12: Mean z-scores, Design Effects and excluded subjects ......................................... 21

Table 13: Mortality rates .................................................................................................................... 22

Table 14: Illness reported in last 2 weeks ................................................................................... 22

Table 15: Health seeking behavior ................................................................................................. 22

Table 16: Infant and young child feeding practices ................................................................. 24

Table 17: Minimum Meal Frequency ............................................................................................. 24

Table 18: Water, sanitation and hygiene practices .................................................................. 26

Table 19: Main source of HH income in the past 30 days ..................................................... 26

Table 20: Main source of food .......................................................................................................... 28

Table 21: Main shocks experience by the HH ............................................................................ 28

Table 22: Household Coping Strategies ....................................................................................... 29

List of Figures

Figure 1: Weight-for-Height distribution curve ........................................................................ 18

Figure 2: Measles vaccination, vitamin A supplementation and deworming ................ 23

Figure 3: Diversity of food consumed by children ................................................................... 25

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EXECUTIVE SUMMERY

The report presents the results of a nutrition and mortality survey conducted by

Concern Worldwide in Aweil West in Northern Bahr El Ghazal (NBeG) State in South

Sudan in April 2014. The main objective of the survey was to determine the level of

acute malnutrition among children aged 6-59 months and analyse possible factors

contributing to malnutrition.

Standardized Monitoring and Assessment of Relief and Transition (SMART)

methodology was employed to undertake the survey. A two-stage cluster sampling

was used with 44 clusters of 14 households. The assessment targeted the caregivers

of households and children aged 6-59 months for the anthropometric measurements.

Information was also sought from the principal caregivers on Infant and Child

Feeding Practices (children aged 0-23 months), health, food security, water,

sanitation and hygiene. Data collection took place between 7 –16 April 2014. A

retrospective mortality survey over the past 90 days was undertaken alongside the

anthropometric survey using SMART methodology.

The survey findings show that critical Global Acute Malnutrition (GAM) rates of

17.0% and Severe Acute Malnutrition (SAM) rates of 1.8%. These rates are typical of

the area. Compared to the pre-harvest survey done in 2013, the rates from this

survey are lower, as the GAM rate in 2013 was 17.8% and SAM was 3.6% based on

WHZ. Prevalence of GAM based on MUAC is 6.9% and SAM is 1.6%.

The Crude Mortality Rate (CMR) was 0.51 deaths per 10,000 people per day and the

Under Five-Mortality Rate (U5MR) was 1.01 deaths in children under five per 10,000

children under five per day. These rates are not above emergency thresholds and are

typical of the area.

Morbidity was also very high among children under five in the surveyed area. Nearly

half of children were reported to have one or more symptoms of illnesses in the two

weeks prior the survey.

The survey also highlights sub-optimal IYCF practices, poor hygiene, sanitation, and

underutilization of health care services, which might be the possible cause of this

high level of malnutrition.

The main results of the survey are presented in the table below.

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Table 1: Results Summery

INDICATOR RESULTS

Nutritional Status of Children 6-59 months (WHO 2006)

Prevalence of Global Acute Malnutrition <-2 Z-scores 17.0 % (14.0 - 20.6 95% C.I.)

Prevalence of Severe Acute Malnutrition<-3 Z-scores 1.8 % (0.9 - 3.5 95% C.I.)

Prevalence of Underweight <-2 Z-scores 25.9 % (21.9 - 30.5 95% C.I.)

Prevalence of Stunting/Chronic Malnutrition <-2 Z-

scores

25.0 % (20.5 - 30.2 95% C.I.)

Nutritional status using MUAC

Prevalence of Global Acute malnutrition MUAC < 125

mm or oedema

6.9 % (4.6 - 10.2 95% C.I.)

Mortality rate

Crude Mortality Rate 0.51 /10,000/day

Under-five Mortality Rate 1.01 /10,000/day

Child Morbidity

Proportion of children being sick 2 weeks prior to the

survey

(327) 56.4%

Type of Illness

Fever/malaria (N=327) (219) 67.0%

Cough/ARI (N=327) (110) 33.6%

Diarrhoea (N=327) (110) 33.6%

Skin Infection (N=327) (15) 4.6%

Measles, vitamin A supplementation and deworming coverage

Measles-by card (N=473) (70) 14.8%

Measles-by recall (N=473) (214) 45.2%

Vitamin A in last 6 months (N=509) (138) 27.1%

Deworming (6-59 months) (N=509) (37) 7.3%

Water Sanitation and Hygiene (N=569)

Source of drinking water:

Borehole

Surface water

Open well

(302) 53.1%

(58) 10.2%

(15) 2.6%

Defecation in undesignated open area (272) 81.9%

Hand washing Practice

Before cooking Before eating Before feeding a child After defecating

After cleaning the child

(252) 75.9%

(245) 73.8%

(95) 28.6%

(87) 26.2% (72) 21.7%

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Infant and Young Child Feeding Practices

Timely initiation of breastfeeding (6-23 month)

(N=163)

Less than an hour

1-24 hours

Longer than 3 days

(122) 74.8%

(31) 19.0%

(4) 2.5%

Maintenance of breastfeeding

0-23 months (163)

6-11 months (63)

12-17 months (43)

18-23 months (57)

(134) 82.2%

(60) 95.2%

(40) 93.0%

(34) 59.7%

Ever breastfeed (N=172) (163) 94.8%

Timely introduction of complementary feeding-6-8

months (36)

(14) 38.9%

Household Food Security (N=569)

Main Income Source of the household (past 30 days)

Sale of natural resources

Brewing

Salaried work Sale of crops

(112) 19.7%

(58) 10.2%

(49) 8.6% (47) 8.3%

Main source of food

Own production Market/Shop purchase

Work for food

(173) 30.4%

(167) 29.4%

(30) 5.3%

Did not have enough food in the past 30 days (262) 46.1%

Coping strategies

Borrowing/kinship support Sell Animal

Rely on less preferred food Limit portion size

Reduce number of meals

(108) 41.2%

(95) 36.2%

(93) 35.5%

(58) 22.1%

(45) 17.1%

Main shocks experienced by the HH

Expensive food

Human sickness

Lack of water

Delay of rains

Insecurity

(351) 61.7%

(302) 53.0%

(92) 16.2%

(66) 11.6%

(32) 5.6%

Based on the information above, and in the rest of this report, the nutrition situation

in Aweil West is categorized as critical and can be associated with inappropriate IYCF

practices, high disease incidence, poor hygiene and sanitation, low measles/vitamin

A and deworming coverage, and limited access to safe water.

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1. INTRODUCTION

Aweil West in Northern Bahr El Ghazal (NBeG) State in South Sudan remains

amongst the highest risk states for child malnutrition and mortality in 2014. Concern

Worldwide (CWW) conducted SMART survey in 2013 and found that Global Acute

Malnutrition (GAM) rates (using WFH method) was above the acceptable WHO

emergency thresholds of 15%. Good nutrition, especially in the ‘window of

opportunity’—from conception to 24 months— is essential to capitalize full physical

and intellectual capacity, educational performance, and productivity. Against this

elevated baseline level, the malnutrition rate tends to peak once in the year between

the months of April and September. In Aweil West the pre-harvest GAM prevalence in

2013 was 17.8% and Severe Acute Malnutrition (SAM) was 3.6%.

Due to its proximity to the almost three decade long civil conflict with Sudan,

Northern Bahr el Ghazal State has suffered chronic under development with its

infrastructure, human resources and community and household in a dilapidated

state. It is the poorest state in South Sudan with minimal capacity to provide even

the most basic of services and is also the most food insecure state with 62% of the

population moderately food insecure and 10% severely insecure1 which is also

attributed to poor agronomic practices.

Factors such as sub-optimal young child feeding practices, food insecurity, illness,

conflict, and displacement exacerbate the critical nutrition situation.2 Within the

Ministry of Health (MoH), nutrition has a low priority and receives an insufficient

allocation of staff and resources to support sustainable nutrition programme

implementation and delivery.

According to FAO/WFP Crop and Food Security Assessment Mission Report (CFSAM)

2001-2012, NBeG has the lowest average yield for all cereals. The CFSAM of January,

2011 also revealed that, 7% and 36% of the population are respectively severely and

moderately food insecure in NBeG state. The chronic nature of GAM suggests the root

of the problem lies with chronic food insecurity as well as unsuitable child care

practices which is further exacerbated by high disease burden. Analyses from the

surveys completed so far have shown that children subsist on a diet that is generally

insufficient to meet their nutrient needs; with no diet diversification. Surveys during

the lean months reveal that households’ food stocks are depleted and there is acute

shortage of staple food. This is why there is a need for hunger blanket supplementary

feeding to reduce the rising malnutrition rates.

1 Annual Needs and Livelihoods Analysis Report, February 2012 2 Situation Analysis of Nutrition in Southern Sudan. GoSS/MoH/DN (2009)

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CWW, an active member of the Nutrition Cluster has implemented nutrition

programmes in NBEG since 2000. The proposed activities are integrated in CWW’s

overall health, nutrition and food security programmes addressing the underlying

causes of malnutrition.[1] Without CWW’s assistance, malnutrition rates are expected

to worsen due to 1) seasonal floods affecting food production while concurrently

increasing the disease burden; 2) border insecurity, 3) number of IDPs present. The

CHD has limited capacity and lack of resources to implement nutrition interventions

without support from CWW. CWW partners with UNICEF & WFP for nutrition

supplies and has funding for BPHS provision (excluding nutrition) from Crown

Agents (HPF).

With CWW support (Irish Aid, ECHO, and UNCHF funding), 22 health facilities in

Aweil West are now providing nutrition services reaching 50.7% of the population [2].

2. SURVEY OBJECTIVES

The main objective of the survey was to determine the level of acute malnutrition

among children aged 6-59 months and analyse possible factors contributing to

malnutrition. It will also contribute to effective planning and implementation of

further nutrition interventions in the areas.

The specific objectives of the survey were:

1. To estimate the prevalence of acute and chronic malnutrition among children

aged 6-59 months.

2. To retrospectively estimate the levels of crude mortality rates and under five

mortality rates.

3. To estimate the coverage of health interventions e.g. measles vaccinations

among children aged 9-59 months, vitamin A supplementation and de-

worming among children aged 6-59 months.

4. To assess the prevalence of perceived morbidities in under five children.

5. To assess contextual factors associated with malnutrition in the county, such

as health, hygiene and sanitation, and food security and livelihoods.

6. To understand key Infant and Young Child Feeding (IYCF) indicators in the

survey area for children aged 0-23 months.

[1] As identified by UNICEF’s conceptual framework for malnutrition. http://www.unicef.org/sowc98/silent4.htm

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3. METHODOLOGY

The survey was designed as a cross-sectional household survey using a two-stage

cluster sampling method. SMART methodology was applied in the training, planning,

collection and analysis of both anthropometric and mortality data to ensure validity

and reliability of data. The assessment targeted the caregivers of households and

children aged 6-59 months for the anthropometric measurements, childcare

practices (immunization, vitamin A supplementation, deworming), morbidity, and

health seeking behaviour. Information was also gathered to establish the infant and

young child feeding practices (IYCF) among children aged 6 to 23 months as well as

the nutritional status of women of reproductive age (15-49 years). Additionally

information was sought from the principal caregivers on food security, water,

sanitation and hygiene. Data collection took place between 7 and 16 April 2014.

3.1 Sampling Methodology

3.1.1 Sample size

Two-stage cluster sampling was chosen because simple random sampling was not

feasible given the large geographic area and lack of a complete and recent list of

households in the county.

The sample size was calculated using ENA for SMART Nov 8th 2011 version software.

An estimated prevalence of 18.0% GAM was used based on the results of the April

2013 pre-harvest SMART survey. A desired precision of 5.0% was used as this will

allow the estimate to be precise enough to compare results to the previous year and

to make decisions regarding programme interventions. A design effect (DEFF) of 1.6

was used to take into account heterogeneity of population. An average household

size of 6 people and 20% of children under the age of 5 years were used based on

results of the previous year survey. A 5% non-response rate was included to account

for any households which were absent or refused to be included in the sample. Thus,

a sample size of 395 children and 385 households were needed for inclusion in the

cross sectional anthropometric survey.

The sample size for mortality was based upon an estimated death rate of 0.3 deaths

per 10,000 per day. This was based on the results of the 2013 pre-harvest SMART

survey. A desired precision of 0.5/10,000/day was used as this will allow the

estimate to be precise enough to compare results to the previous years. A design

effect (DEFF) of 1.6 was used to take into account heterogeneity of population. A

recall period of 90 days was used with the beginning of the recall period

corresponding with Christmas holiday. An average household size of 6 was used an a

5% non-response rate was included to account for any households which were

absent or refused to be included in the sample. Thus, a sample size of 157 households

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was needed for inclusion in the retrospective mortality survey.

As the sample size needed for anthropometry was larger than that for mortality, it

was decided to administer the mortality questionnaire in every household.

It was decided that 1 team can visit 14 households per day taking into consideration

travel time and population density. This meant that 44 clusters needed to be

selected.

Indicator Estimated

prevalence Desired Precision

DEFF Avg HH size

Children under 5

Non- response rate

Required sample size Persons HHs

GAM 18.0% 5% 1.6 6 20% 5% 395 385 CMR 0.3 0.5 1.6 6 - 5% 892 157

3.1.2 Sampling procedure: selecting clusters Data for the sampling frame came from village level population data used during the

2013 pre-harvest survey conducted by Concern Worldwide. The village list with

population sizes was updated by the County Health Department (CHD) and the Relief

and Rehabilitation Commission.

All villages were able to be selected for inclusion in the survey and 44 clusters were

randomly selected by assigning probability proportional to population size (PPS).

Five reserve clusters were also selected in the same manner.

3.1.3 Sampling procedure: selecting households and children

Households were selected using simple random sampling (SRS). Segmentation was

first used if villages had more than 100 households, with a segment chosen based by

assigning probability proportional to population size. Households were then selected

from the chosen segment using SRS.

On arrival in the selected villages, the survey teams first estimated the number of

households in village with the village leader. If the total number of households were

less than or equal to 100, all households in the village were listed and 14 households

were randomly selected from the list. When a village was larger than 100

households, the village was segmented using natural boundaries or Gols

(administrative unit smaller than a village, also referred to as a sub-village). The

estimated population of the segments were recorded and a segment was chosen

using PPS. All households in the selected segment were then listed and the required

households were randomly selected using SRS.

The procedure for simple random sampling was to first make an exhaustive list of all

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households in the village, with each household only recorded once. This was done

with the village leader. Each household was numbered. Next, one slip of paper for

each household in the list with the household number was folded and put into a

container. Then, the village leader was asked to select the required 14 households

from the container and these households were recorded on the form as selected.

Empty households and households with absent children were revisited in the

afternoon by the team before departing the village. Empty and non-responding

households were not replaced as a 5% non-response rate was built into the sample

size. If more than 50% of households in village were absent, the village would be

revisited at a later date to find the selected households, but this did not happen

during the survey.

As the basic sampling unit was the household, children were not selected

independently of the household. All children 6-59 months in the selected households

were included in the anthropometric survey. Respondents were mothers or

caretakers of the children in the household.

3.2 Case definitions and inclusion criteria

The definition of a household was a group of people living under same roof and

sharing food from the same pot for a period of at least 6 months. In home compounds

with multiple wives, those living and eating in different houses were considered as

separate households. Wives living in different houses and eating from same pot were

considered as one household. During the household listing mainly the woman’s name

was recorded to indicate each household.

Children aged between 6 and 59 months were eligible for the anthropometric survey.

Age was assessed using multiple methods as it is often difficult to determine. First

the mother or caretaker would be asked to show any card indicating the age of the

child, such as the child health card or a mother’s antenatal care card. If no document

was available, age was estimated using a local events calendar or by assessment of

physical characteristics or developmental milestones. If age was unknown, the height

range of 65 cm to 110 cm could be used for inclusion in the survey.

To determine if a child’s height or length should be taken, a cut-off of two years was

used with height taken for children above two years and length taken for children

below two years. Enumerators were informed to take time to determine accurate age

for children. Enumerators were informed of the cut-off of 87 cm that can be used

when age was unknown, but this was not recommended for use so that all would

follow one criteria.

Weight was taken using a 25 kg salter scale and recorded to the nearest 0.1 kg.

Height/length was measured using a wooden height board and recorded to the

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nearest 0.1 cm. Measurement of mid upper arm circumference (MUAC) was taken

using a coloured tape and recorded to the nearest 0.1 cm. The presence of bilateral

pitting (nutritional) oedema was determined by pressing with the thumbs on both

feet for three seconds. If a shallow pit remained in both feet after removal of thumbs,

it was recorded as oedematous and a photo was taken.

The case definition of Global Acute Malnutrition (GAM) was any child 6-59 months

with a z-score <-2 SD or MUAC <12.5 cm. The case definition of Severe Acute

Malnutrition (SAM) was any child with a z-score <-3 SD or MUAC <11.5 cm. WHO

Standards 2006 were used to report anthropometry results.

The length of the recall period was 90 days for the mortality survey. Christmas

holiday was the well-known event used to explain to survey responders the date of

the start of the recall period. The mortality questionnaire was conducted in all

selected households, even in those households with no eligible children for

anthropometry.

Other indicators were included in additional questionnaire: 1) components of food

security and livelihoods asked to households with children 6-59 months, 2) water

and sanitation questions asked to households with children 0-59 months, 3) Infant

and Young Child Feeding (IYCF) questions asked to households with children 0-23

months-- given to the youngest child, and 4) the health questions asked to

households with children 0-59 months. Immunization, vitamin A, and deworming

status were assessed by either verification of immunization cards or mother’s recall.

Retrospective morbidity was also assessed in this manner.

3.3 Ethical consideration

Verbal consent for all caregivers of the sampled children was sought before

administration of the questionnaire. All information collected during the survey were

treated as confidential and used for the survey and programming purposes only.

Children who were found as severely malnourished or with any other medical

condition during the survey were referred to the nearest health facility for medical

attention and appropriate treatment.

3.4 Questionnaire, training and supervision

The questionnaire was administered using the local language, Dinka. Responses were

recorded in English in Digital Data Gathering devices (Samsung Galaxy Tablets). The

translation of the questionnaire was agreed during the training, focusing on concepts

difficult to translate and concepts which might have more than one translation.

The questionnaire was pilot tested for one day before the beginning of the survey.

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Some small changes were necessary, which were made before beginning the survey.

The pilot test was also used as an opportunity to observe and improve

anthropometry measurement. Feedback was given at the end of the exercise.

There were five survey teams each comprising of one team leader and two

enumerators. Most had previously conducted a SMART survey before. The teams

were trained for 5 days by Concern Worldwide staff on survey objectives,

anthropometric measurement, survey methodology, household selection procedures,

interview skills, and other aspects. Overall supervision was done by several Concern

Worldwide staff. A standardization test was conducted to evaluate the capacity of

enumerators. During the test, 10 children were measured by the survey team

members. Members who performed poorly on the standardization test underwent

more training to improve their skills.

3.5 Data analysis

Data was entered and analysed using ENA for SMART software Nov 2011, and Epi

Info 3.5.3. Data was automatically uploaded from the Digital Data Gathering devices

to an online database which was exported to excel.

A p-value of <0.05 was considered to be statistically significant. Anthropometric data

was checked for outliers which were defined as records falling +/- 3 SD of WHZ from

the observed mean. SMART flags were excluded from the analysis.

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4. RESULTS

4.1 Anthropometric results (based on WHO Standards 2006):

The definition of Global Acute Malnutrition is defined as <-2 z scores weight-for-

height and/or oedema or MUAC < 12.5 cm. Severe Acute Malnutrition is defined as <-

3 z scores weight-for-height and/or oedema or MUAC < 11.5 cm. Exclusion of z-

scores from observed mean was made using the following SMART flags: WHZ -3 to 3;

HAZ -3 to 3; WAZ -3 to 3.

4.1.1 Distribution by age and sex

The age and sex distribution of the sampled children aged 6-59 months is illustrated

in Table 2. The age distribution shows a slight under-representation in the 54-59

month age group. This could be due to difficulties in establishing accurate ages for

children where ages are not routinely documented. The sex-ratio (males/females) is

well balanced except for this same age group.

Table 2: Distribution of age and sex of sample

Boys Girls Total Ratio AGE (mo) no. % no. % no. % Boy:girl 6-17 45 41.7 63 58.3 108 21.2 0.7 18-29 64 44.8 79 55.2 143 28.1 0.8 30-41 65 48.5 69 51.5 134 26.3 0.9 42-53 42 45.7 50 54.3 92 18.1 0.8 54-59 19 59.4 13 40.6 32 6.3 1.5 Total 235 46.2 274 53.8 509 100.0 0.9

4.1.2 Prevalence of Global Acute Malnutrition by WFH Z-scores (WHO

Standards 2006)

Wasting represents the failure to receive adequate nutrition in the period

immediately preceding the survey and may be the result of inadequate food intake or

a recent episode of illness causing loss of weight and the onset of malnutrition. It is

also referred to as acute malnutrition, which is reflected by low Weight-for-Height

(WFH).

Table 3 shows that the prevalence of Global Acute Malnutrition (GAM) among all

children was 17.0% (14.0 - 20.6 95% C.I.), indicative of a critical situation requiring

17

nutritional intervention based on the WHO Standards3. The prevalence of Severe

Acute Malnutrition (SAM) was found to be 1.8 % (0.9 - 3.5 95% C.I.).

Table 3: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex

All n = 499

Boys n = 229

Girls n = 270

Prevalence of global malnutrition (<-2 z-score and/or oedema)

(85) 17.0 % (14.0 - 20.6 95% C.I.)

(46) 20.1 % (15.1 - 26.2 95% C.I.)

(39) 14.4 % (10.7 - 19.2 95% C.I.)

Prevalence of moderate malnutrition (<-2 z-score and >=-3 z-score, no oedema)

(76) 15.2 % (12.5 - 18.5 95% C.I.)

(41) 17.9 % (13.4 - 23.4 95% C.I.)

(35) 13.0 % (9.3 - 17.8 95% C.I.)

Prevalence of severe malnutrition (<-3 z-score and/or oedema)

(9) 1.8 % (0.9 - 3.5 95% C.I.)

(5) 2.2 % (0.9 - 5.0 95% C.I.)

(4) 1.5 % (0.6 - 3.8 95% C.I.)

The prevalence of oedema was 0.2 %. Table 4 demonstrates the prevalence of wasting by child age group. The prevalence

of SAM was highest (2.9%) among children aged 18-29 months, indicating that this

age group is mainly affected by serious recent malnutrition situation.

Table 4: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema

Severe wasting

(<-3 z-score)

Moderate wasting

(>= -3 and <-2 z-score )

Normal (> = -2 z score)

Oedema

Age (mo)

Total no.

No. % No. % No. % No. %

6-17 108 1 0.9 11 10.2 96 88.9 0 0.0

18-29 139 4 2.9 25 18.0 110 79.1 0 0.0

30-41 132 2 1.5 25 18.9 104 78.8 1 0.8

42-53 90 1 1.1 11 12.2 78 86.7 0 0.0

54-59 30 0 0.0 4 13.3 26 86.7 0 0.0

Total 499 8 1.6 76 15.2 414 83.0 1 0.2

3 WHO cut off points for wasting using Z scores (<-2 Z scores in populations: <5% acceptable; 5-9% poor; 10

14% serious; >15% critical).

18

Table 5: Distribution of acute malnutrition and oedema based on weight-for-height z-scores

<-3 z-score >=-3 z-score Oedema present Marasmic kwashiorkor

No. 0 (0.0 %)

Kwashiorkor No. 1 (0.2 %)

Oedema absent Marasmic No. 8 (1.6 %)

Not severely malnourished No. 490 (98.2 %)

The Weight-for-Height distribution curve of anthropometric survey, shown below in

Figure 1, displays the results of the surveyed population compared to WHO

Standards. As illustrated by the shift of the curve to the left from the ‘normal’

population, it shows poor nutrition status of the population compared to the WHO

Standards.

Figure 1: Weight-for Height Distribution Curve

4.1.3 Prevalence of Child Acute Malnutrition based on MUAC

The MUAC is a useful tool for rapidly identifying children at a higher risk of mortality

at the community level. According to new international guidelines and

recommendations, MUAC was taken for children of 6 month to below five years

(Table 6). GAM rates were comparable for boys and girls. Children aged 18-29

months had the highest rates of SAM while 6-17 month olds had the highest rates of

MAM (Table 7).

19

Table 6: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) and by sex

All n = 505

Boys n = 234

Girls n = 271

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

(35) 6.9 % (4.6 - 10.2 95% C.I.)

(16) 6.8 % (4.1 - 11.2 95% C.I.)

(19) 7.0 % (4.4 - 11.1 95% C.I.)

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

(27) 5.3 % (3.5 - 8.0 95% C.I.)

(11) 4.7 % (2.7 - 8.1 95% C.I.)

(16) 5.9 % (3.6 - 9.5 95% C.I.)

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

(8) 1.6 % (0.6 - 4.1 95% C.I.)

(5) 2.1 % (0.8 - 5.9 95% C.I.)

(3) 1.1 % (0.4 - 3.4 95% C.I.)

Table 7: Prevalence of acute malnutrition by age, based on MUAC cut off's and/or oedema

Severe wasting

(< 115 mm)

Moderate wasting

(>= 115 mm and < 125

mm)

Normal (> = 125 mm )

Oedema

Age (mo)

Total no.

No. % No. % No. % No. %

6-17 106 2 1.9 13 12.3 91 85.8 0 0.0

18-29 142 5 3.5 11 7.7 126 88.7 0 0.0

30-41 134 0 0.0 2 1.5 132 98.5 1 0.7

42-53 91 0 0.0 1 1.1 90 98.9 0 0.0

54-59 32 0 0.0 0 0.0 32 100.0 0 0.0

Total 505 7 1.4 27 5.3 471 93.3 1 0.2

4.1.4 Prevalence of underweight based on weight-for-age z-scores

The Weight-for-Age (WFA) indices give a mixed reflection of both the current and

past nutritional experience of the community, therefore, does not differentiate

malnutrition due to current and past nutritional/health experience. As such, it is a

composite measure of both wasting and stunting, thus, a useful tool in individual

child growth monitoring. The findings (Table 8) indicated that 25.9 % (21.9 - 30.5

95% C.I.) of the children were underweight and 7.6 % (5.3 - 10.7 95% C.I.) severely

20

underweight. Children aged 18-29 months were the most severely underweight. The

prevalence of underweight between boys and girls was comparable.

Table 8: Prevalence of underweight based on weight-for-age z-scores by sex

All n = 501

Boys n = 231

Girls n = 270

Prevalence of underweight (<-2 z-score)

(130) 25.9 % (21.9 - 30.5

95% C.I.)

(65) 28.1 % (22.7 - 34.3

95% C.I.)

(65) 24.1 % (19.4 - 29.5

95% C.I.)

Prevalence of moderate underweight (<-2 z-score and >=-3 z-score)

(92) 18.4 % (15.0 - 22.3

95% C.I.)

(47) 20.3 % (16.0 - 25.5

95% C.I.)

(45) 16.7 % (12.5 - 21.9

95% C.I.)

Prevalence of severe underweight (<-3 z-score)

(38) 7.6 % (5.3 - 10.7 95% C.I.)

(18) 7.8 % (4.2 - 14.1 95% C.I.)

(20) 7.4 % (5.0 - 10.9 95% C.I.)

Table 9: Prevalence of underweight by age, based on weight-for-age z-scores

Severe underweight (<-3 z-score)

Moderate underweight

(>= -3 and <-2 z-score )

Normal (> = -2 z score)

Oedema

Age (mo)

Total no.

No. % No. % No. % No. %

6-17 107 3 2.8 10 9.3 94 87.9 0 0.0

18-29 140 19 13.6 26 18.6 95 67.9 0 0.0

30-41 133 13 9.8 30 22.6 90 67.7 1 0.8

42-53 91 3 3.3 21 23.1 67 73.6 0 0.0

54-59 30 0 0.0 5 16.7 25 83.3 0 0.0

Total 501 38 7.6 92 18.4 371 74.1 1 0.2

4.1.5 Prevalence of Stunting

Stunting (Height-for-Age or HFA) measures linear growth and is thus an indicator of

chronic malnutrition, which is reflective of cumulative effects of long-standing

nutritional inadequacy and/or recurrent chronic illness. Unlike wasting, it is not

affected by seasonality but is rather related to the effects of socio-economic

development, long-standing food security situation and child health status.

Chronic malnutrition, or stunting, affects 25.0 % (20.5 - 30.2 95% C.I.) of children

aged 6-59 months, 6.1 % (3.7 - 10.0 95% C.I.) of who are severely stunted in the

surveyed areas (Table 10). This prevalence indicates a serious nutrition context

according to WHO, which defines a stunting prevalence below 10 percent as

21

acceptable, between 10 and 20 percent as poor, between 20 and 40 percent as

serious, and above 40 percent as critical. Children aged 30-41 months were the most

severely stunted (Table 11).

Table 10: Prevalence of stunting based on height-for-age z-scores and by sex

All n = 488

Boys n = 228

Girls n = 260

Prevalence of stunting (<-2 z-score)

(122) 25.0 % (20.5 - 30.2

95% C.I.)

(64) 28.1 % (21.8 - 35.3

95% C.I.)

(58) 22.3 % (17.4 - 28.2

95% C.I.)

Prevalence of moderate stunting (<-2 z-score and >=-3 z-score)

(92) 18.9 % (15.7 - 22.5

95% C.I.)

(51) 22.4 % (17.2 - 28.6

95% C.I.)

(41) 15.8 % (12.1 - 20.4

95% C.I.)

Prevalence of severe stunting (<-3 z-score)

(30) 6.1 % (3.7 - 10.0 95% C.I.)

(13) 5.7 % (2.6 - 12.1 95% C.I.)

(17) 6.5 % (3.9 - 10.7 95% C.I.)

Table 11: Prevalence of stunting by age based on height-for-age z-scores

Severe stunting (<-3 z-score)

Moderate stunting (>= -3 and <-2 z-

score )

Normal (> = -2 z score)

Age (mo)

Total no.

No. % No. % No. %

6-17 104 2 1.9 9 8.7 93 89.4

18-29 134 9 6.7 33 24.6 92 68.7

30-41 129 13 10.1 26 20.2 90 69.8

42-53 89 5 5.6 18 20.2 66 74.2

54-59 32 1 3.1 6 18.8 25 78.1

Total 488 30 6.1 92 18.9 366 75.0

Table 12: Mean z-scores, Design Effects and excluded subjects

Indicator n Mean z-scores ± SD

Design Effect (z-score < -2)

z-scores not available*

z-scores out of range

Weight-for-Height 498 -1.05±0.98 1.00 8 3

Weight-for-Age 501 -1.34±1.09 1.18 7 1

Height-for-Age 488 -1.06±1.23 1.51 3 18

* contains for WHZ and WAZ the children with oedema.

4.2 Mortality results (retrospective over 90 days prior to interview)

Five hundred and sixty nine households were interviewed for retrospective mortality

information using a recall period of 90 days. A total of 67 births and 17 deaths had

22

occurred during the survey period. Five of these deaths were children under five

years of age. Table 13 below shows the Mortality Rates.

Table 13: Mortality Rates

CMR (total deaths/10,000 people / day): 0.51 (0.28-0.95) (95% CI)

U5MR (deaths in children under five/10,000 children under five / day): 1.01 (0.43-2.40) (95% CI)

4.3 Morbidity

More than half (56.4%) of the surveyed children reported to have been sick during

the two-week period preceding the survey. The three main causes of child illness

were fever/ malaria, cough and diarrhoea, affecting 67%, 33.6% and 33.6% of the

children, respectively (Table 14).

Table 14: Illness reported in the last 2 weeks

Type of Illness Number (N=327) %

Fever 219 67.0

Cough 110 33.6

Diarrhoea 110 33.6

Skin Infection 15 4.6

Eye infection 4 1.2

Malnutrition 3 0.9

Measles 2 0.3

The total proportion of caretakers seeking medical assistance in PHCC, PHCU and

hospitals was only 27.1% (Table 15). It is noteworthy that 42.5% of the childcare

givers reportedly sought no medical assistance the last time their children had been

ill.

Table 15: Health seeking behaviour

Number (N=327) %

None 139 42.5

PHCC 98 16.9

PHCU 50 8.6

Pharmacy 16 2.8

Hospital 9 1.6

Mobile/outreach clinic 4 0.7

CDD- Community Drug Distributor 3 0.5

Traditional practitioner 3 0.5

Shop 3 0.5

HHP – Home Health Promoter 1 0.2

23

4.4 Immunization, vitamin A supplementation and deworming

Immunization status was obtained by verifying immunization cards and from

caretaker recall. It should be noted that recall data is usually less reliable than

observational data documented on a health card. Only 14.8% of children surveyed

received measles immunization as shown by card and 45.2% received by recall.

Vitamin A supplementation coverage within the last six months prior to the survey

was 27.1%. Such low levels of immunization and vitamin A supplementation

coverage (Figure 2) means that children under five are increasingly vulnerable to

morbidities and mortalities related to childhood illnesses. The deworming coverage

for children aged 6 to 59 months with evidence of a card and mother‘s recall was also

very low at 7.3%.

Figure 2: Measles vaccination, vitamin A supplementation and deworming

coverage

4.5 Infant and Young Child Feeding practices

Breastfeeding appeared universal with 96.3% of caretakers reporting having

breastfed their children aged between 0 to two years, while 82.2% of that age

category was still being breastfed at the time of the interview. About 74.8% of

caretakers introduced breast milk within the first hour of birth (Table 16). This is

commendable as WHO recommends that children breastfeed for 2 years and longer.

The maintenance of breastfeeding was also investigated at various ages as per the

WHO 2007 guidelines4. Over 95.2% of children 6-11 months from all the survey sites

were still breastfeeding and over 88.9% of those 12-17 months old were also still

4 Indicators for Assessing Infant and Young Child Feeding Practices. Conclusions of a consensus meeting

held 6-8 November 2007 in Washington DC, USA.

7.3

14.8

45.2

27.1

0

10

20

30

40

50

60

70

80

90

100

Deworming(N=509)

Measles-by card(N=473)

Measles-by recall(N=473)

Vitamin A(N=509)

24

breastfeeding. The rate of breastfeeding significantly reduced for those children 18-

23 months (53.1%) in the survey sites.

The proportion of infants 6-8 months who received breast milk and a solid, semi-

solid or soft food (based on 24 hour dietary recall) is only 38.9% (n=36).

Table 16: Infant and Young Child Feeding Practices

Breastfeeding Practices Number %

Timely initiation of breastfeeding (6-23

month) (N=163)

Less than an hour 122 74.8

1-24 hours 31 19

2-3 days 6 3.7

Longer than 3 days 4 2.5

Maintenance of breastfeeding

0-23 months (163) 134 82.2

6-11 months (63) 60 95.2

12-17 months (43) 40 93.0

18-23 months (57) 34 59.7

Ever breastfeed (N=172)

0-23 months 163 94.8

Timely Introduction of Complementary Feeding

6-8 months (36) 14 38.9

The survey also revealed a low minimum meal frequency, with 19.4% of children 6-8

months of age being fed less than the recommended two meals per day and only

5.2% of children aged 9-23 month were fed the recommended minimum of 3 times

per day. Although on average, both subsets of children are not being fed with the

recommended frequency, the older children (9-23m) are in the most critical position.

Table 17: Minimum Meal Frequency

Meal frequency of children % n

Minimum Meal Frequency (6-8 month) (N=36) 19.4 7

Minimum Meal Frequency (9-23 month) (N=136) 5.2 7

The minimum dietary diversity for children 6-23 months is considered to be foods

fed from ≥ 4 food groups out of the 7 food groups. The understanding is that the

more diverse the diet the more likely a child is receiving adequate levels of a range of

25

nutrients. Only 9.5% of the children aged 6 to 23 months had a minimum dietary

diversity of consuming foods from 4 or more different food groups in the previous 24

hours.

The data also revealed that most children in the surveyed area had low intake from

animal sources with only 12.8% of children 6-23 months consuming meat, and fewer

children consuming eggs (4.1%) and only 18.6% consuming milk (Figure 3). Animal

source foods are good sources for both protein and critical micronutrients and

should be part of the diet.

Figure 3: Consumption of different food groups

4.6 Water and Sanitation

The main source of drinking water among 53.1% of the population was borehole,

followed by open surface water (10.2%), and then protected open well (2.6%).

Water collection time was reported to be less than 30 minutes (21.6%) to less than

an hour (22.1%) among the majority of the households.

Hand washing is done before cooking among 75.9% and before eating among 73.8%

of the respondents, but only 21.7% after cleaning a child and 26.2% after defecating.

In addition, only 57.5% use water and soap to wash their hands. The majority

(81.9%) use bush/undesignated open area for defecation (Table 18).

52.9

35.5

18.6 18.6 12.8

6.9 4.1 3.5 2.3 0

102030405060708090

100

Cereal Fish Pulses Milk Meat Vit-Arich

fruits &Veg

Eggs Otherfruits &

veg

Roots

26

Table 18: Water Sanitation and Hygiene Practices

Water Sanitation and Hygiene Number (N=569) %

Source of drinking water

Borehole 302 53.1

Surface water (river, stream) 58 10.2

Open well 15 2.6

Piped water/household connection/water tank

11 1.9

Protected well 1 0.2

Protected spring 1 0.2

Pond/dam 1 0.2

Places of Defecation

Undesignated open area 272 81.9

Designated open area 53 15.9

Pit latrine 34 10.2

Hand washing Practice

Before cooking 252 75.9

Before eating 245 73.8

Before feeding a child 95 28.6

After defecating 87 26.2

After Cleaning the child 72 21.7

4.7 Food Security

The main source of income in the past 30 days as reported by the interviewed

resident households was mainly sale of natural resources (19.7%) followed by

brewing (10.2%).

Table 19: Main source of income in the past 30 days

Main income source Number (N=569) %

Sale of natural resources (firewood, grass)

112 19.7

Brewing 58 10.2

Sale of crops 47 8.3

Salaried work 49 8.6

Other petty trading 24 4.2

Family support 20 3.5

Sale of food aid 7 4.7

Casual labour 24 4.2

Small business 17 2.9

Skilled labour 14 2.4

Sale of livestock 9 1.6

Sale of fish 4 0.7

Sale of animal products 1 0.2

27

The main source of food in the household was own production at 30.4% followed by

market/shop purchase at 29.4%. Table 20 shows all the responses as given by the

households.

Table 20: Main Source of Food

Main Food Source Number (N=569) %

Own production 173 30.4

Market/shop purchase 167 29.4

Work for food 30 5.3

Gathering 8 1.4

Gifts 5 0.9

Borrowing/debt 4 0.7

The main shock experienced by most households at the time of the survey was

expensive food items (61.7%), followed by human sickness (53%), lack of water

(16.2%) and delay of rains (11.6%). About half of the households (46.1%) did not

have enough food in the past 30 days.

Table 21: Major Shocks experienced by the HH

Number (N=569) %

Expensive food 351 61.7

Human sickness 302 53.0

Lack of water 92 16.2

Delay of rains 66 11.6

Insecurity 32 5.6

Floods 30 5.3

Pest/crop disease 23 4.0

Livestock disease 22 3.9

No shocks 12 2.1

Despite the setbacks mentioned above, household has strived to ensure availability

of adequate food. Some of the coping strategies were borrowing/kinship support

(41.2%), selling livestock asset (36.2%), relying on less preferred food (35.5%), and

reducing portion size at meals (22.1%).

28

Table 22: Household Coping Strategies

Number (N=569) %

Borrowing/kinship support 108 41.2

Sell more animals than usual 95 36.2

Rely on less preferred/cheaper food

93 35.5

Reduce portion size at meals 58 22.1

Reduce number of meals adults eat

45 17.1

Consume seed stock 17 6.5

29

5. DISCUSSION

Boys and girls were equally represented in the survey showing no systematic bias.

The ratio of boys to girls was 0.9 with 46.2% boys (n=235) and 53.8% girls (n=274).

The age distribution indicates slight variation as compared to the normal WHO age

distribution. The age ratio of children 6-29 to 30-59 is 0.97 compared to the WHO

value of 0.85, indicating there are slightly more younger children in the sample than

expected. This could be due to a number of factors such as time of day, older children

in school, etc.

The survey findings indicate that the malnutrition situation in Aweil West County is

‘critical’ with Global Acute Malnutrition (GAM) of 17.0 % and Severe Acute

Malnutrition (SAM) rate of 1.8%. These rates are typical of the area. Prevalence of

GAM based on MUAC is 6.9% and SAM is 1.6%. Compared to the pre-harvest survey

done in 2013, the rates from this survey are lower, as the GAM rate in 2013 was

17.8% and SAM was 3.6% based on WHZ.

The crude mortality rate was 0.51 deaths per 10,000 people per day and the under

five-mortality rate was 1.01 deaths in children under five per 10,000 children under

five per day. These rates are not above emergency thresholds and are typical of the

area.

The prevalence of morbidity was very high among children under five in the

surveyed area. Fever (a proxy for malaria) was the main cause of illness (67.0%)

followed by cough and diarrhoea. All these conditions have the effects of reducing

food intake and nutrient absorption while at the same time increasing the body’s

demand for nutrients. This could have a significant bearing on the nutritional status

of these children, as well as other health implications. Health seeking practices as

reported by mothers with sick children was also not encouraging at all, with a high

proportion of mothers (42.5%) not seeking medical care for their children.

Measles and vitamin A supplementation coverage (27%) for under-fives was found

to be extremely low. De-worming coverage for children was also very low at 7.3%.

The results of this assessment clearly suggest that achieving acceptable levels of

immunization coverage remains a huge challenge in the surveyed area. The result

also indicates that the routine immunization program and other services for vitamin

A supplementation and deworming are performing poorly and attention should be

placed on strengthening to achieve a very high level of coverage.

The results from the IYCF practices are also alarming –especially in terms of

complementary feeding practices. The survey revealed a low meal frequency, with

19.4% of children 6-8 months of age being fed less than the recommended two meals

30

per day and only 5.2% of children aged 9-23 month were fed at least 3 times per day.

Although on average, while both subsets of children are not being fed with the

recommended frequency, the older children (9-23m) are in the most critical position.

The diet of young children in these communities also appears to lack diversity. Only

9.5% of children received foods from 4 or more food groups. Nutrient-rich foods like

animal source foods, dairy products and vitamin A rich fruits and vegetables are

rarely consumed.

The water and sanitation situation was also not any better. The biggest concern is

accessibility of water available to the households for consumption. Almost three

quarter of the surveyed household spent over the WHO recommended time of 30

minutes to fetch water. Very little was done to safeguard the safety and quality of

water at household level. This is exposing the community at risk of water borne

disease. Similarly, open defecation was common and practiced by almost all of the

households. The practice of hand washing using soap was also low. This could be

constrained partly, by the scarcity of water. The aforementioned factors predisposed

the community to infections thence the high diarrhoea incidences.

Overall, the malnutrition revealed in the county can be associated with poor hygiene

and sanitation, lack of adequate food, poor attendance to health services, low measles

coverage, poor feeding practices and lack of potable water.

31

6. RECOMMENDATIONS

Short-term

1. Continue Outpatient Therapeutic Programme, Stabilization Centre, and Targeted Supplementary Feeding Programme and scale up in areas of low coverage.

2. Continue and strengthen Blanket Supplementary Feeding Programme to help prevent the nutrition situation from deteriorating.

3. Implement and continue to strengthen regular community screening of malnutrition.

4. Implement a Social and Behaviour Change Communication (SBCC) strategy to promote appropriate Infant and Young Child Feeding practices, immunization and hygiene promotion activities.

5. Closely monitor the nutrition and food security situation and develop a contingency plan to provide prompt emergency response/relief as appropriate.

Medium/Long term

1. Investigate the functioning of the health centres and strengthen the existing health system to increase coverage of the health care services.

2. Increase safe water access at household level (through boreholes drilling, water pumps installation, rainwater collection, creation of dams, etc.).

3. Support the community in the construction of latrines and build local capacity in accessing the construction tools and skills.

4. Support income generation and small business development in order to increase the sustainability, diversity and size of household incomes.

32

Annex 1

Plausibility check for: RSS_0414_CWW_AweilWest.as Standard/Reference used for z-score calculation: WHO standards 2006 (If it is not mentioned, flagged data is included in the evaluation. Some parts of this plausibility report are more for advanced users and can be skipped for a standard evaluation) Overall data quality Criteria Flags* Unit Excel. Good Accept Problematic Score Missing/Flagged data Incl % 0-2.5 >2.5-5.0 >5.0-10 >10 (% of in-range subjects) 0 5 10 20 0 (0.6 %) Overall Sex ratio Incl p >0.1 >0.05 >0.001 <0.000 (Significant chi square) 0 2 4 10 2 (p=0.084) Overall Age distrib Incl p >0.1 >0.05 >0.001 <0.000 (Significant chi square) 0 2 4 10 10 (p=0.000) Dig pref score - weight Incl # 0-5 5-10 10-20 > 20 0 2 4 10 2 (10) Dig pref score - height Incl # 0-5 5-10 10-20 > 20 0 2 4 10 0 (5) Standard Dev WHZ Excl SD <1.1 <1.15 <1.20 >1.20 0 2 6 20 0 (0.98) Skewness WHZ Excl # <±1.0 <±2.0 <±3.0 >±3.0 0 1 3 5 0 (0.07) Kurtosis WHZ Excl # <±1.0 <±2.0 <±3.0 >±3.0 0 1 3 5 0 (-0.25) Poisson dist WHZ-2 Excl p >0.05 >0.01 >0.001 <0.000 0 1 3 5 0 (p=0.159) Timing Excl Not determined yet 0 1 3 5 OVERALL SCORE WHZ = 0-5 5-10 10-15 >15 14 % At the moment the overall score of this survey is 14 %, this is acceptable. There were no duplicate entries detected. Percentage of children with no exact birthday: 100 % Age/Height out of range for WHZ: HEIGHT: Line=115/ID=132: 12.10 cm Line=407/ID=461: -1E5 cm Line=432/ID=492: -1E5 cm Anthropometric Indices likely to be in error (-3 to 3 for WHZ, -3 to 3 for HAZ, -3 to 3

33

for WAZ, from observed mean - chosen in Options panel - these values will be flagged and should be excluded from analysis for a nutrition survey in emergencies. For other surveys this might not be the best procedure e.g. when the percentage of overweight children has to be calculated): Line=6/ID=13: HAZ (-4.478), Age may be incorrect Line=11/ID=18: HAZ (3.166), Height may be incorrect Line=18/ID=25: HAZ (2.220), Age may be incorrect Line=34/ID=41: HAZ (-4.328), Age may be incorrect Line=93/ID=110: WHZ (-4.432), Weight may be incorrect Line=103/ID=120: HAZ (2.728), Age may be incorrect Line=117/ID=134: HAZ (-4.653), Height may be incorrect Line=147/ID=171: WHZ (-5.358), Weight may be incorrect Line=152/ID=176: WHZ (-4.336), Weight may be incorrect Line=174/ID=206: WAZ (-4.348), Age may be incorrect Line=188/ID=220: HAZ (2.117), Age may be incorrect Line=326/ID=374: HAZ (-4.320), Age may be incorrect Line=338/ID=386: HAZ (-4.430), Age may be incorrect Line=346/ID=394: HAZ (-4.350), Age may be incorrect Line=372/ID=426: HAZ (-4.136), Age may be incorrect Line=378/ID=432: HAZ (-4.587), Age may be incorrect Line=385/ID=439: HAZ (-4.228), Height may be incorrect Line=388/ID=442: HAZ (-4.166), Age may be incorrect Line=444/ID=504: HAZ (2.243), Height may be incorrect Line=461/ID=532: HAZ (2.464), Age may be incorrect Line=466/ID=537: HAZ (2.286), Age may be incorrect Line=477/ID=548: HAZ (-4.574), Age may be incorrect Percentage of values flagged with SMART flags:WHZ: 0.6 %, HAZ: 3.6 %, WAZ: 0.2 % Age distribution: Month 6 : ######### Month 7 : ############ Month 8 : ############### Month 9 : ########### Month 10 : ######## Month 11 : ######## Month 12 : ######## Month 13 : ######## Month 14 : ######## Month 15 : #### Month 16 : ######### Month 17 : ######## Month 18 : ######## Month 19 : ########### Month 20 : ############ Month 21 : ########### Month 22 : ######## Month 23 : ############## Month 24 : ####################### Month 25 : ############ Month 26 : ###########

34

Month 27 : ########## Month 28 : ############## Month 29 : ######### Month 30 : ######## Month 31 : ########## Month 32 : ########### Month 33 : ############ Month 34 : ############ Month 35 : ########## Month 36 : ################## Month 37 : ######### Month 38 : ############ Month 39 : ########### Month 40 : ############ Month 41 : ######### Month 42 : ############## Month 43 : ##### Month 44 : ##### Month 45 : #### Month 46 : ###### Month 47 : ####### Month 48 : ######### Month 49 : ################# Month 50 : ### Month 51 : ######## Month 52 : ###### Month 53 : ######## Month 54 : ### Month 55 : ### Month 56 : ####### Month 57 : #### Month 58 : ###### Month 59 : ######### Age ratio of 6-29 months to 30-59 months: 0.97 (The value should be around 1.0). Statistical evaluation of sex and age ratios (using Chi squared statistic): Age cat. mo. boys girls total ratio boys/girls ------------------------------------------------------------------------------------- 6 to 17 12 45/54.5 (0.8) 63/63.6 (1.0) 108/118.1 (0.9) 0.71 18 to 29 12 64/53.2 (1.2) 79/62.0 (1.3) 143/115.1 (1.2) 0.81 30 to 41 12 65/51.5 (1.3) 69/60.1 (1.1) 134/111.6 (1.2) 0.94 42 to 53 12 42/50.7 (0.8) 50/59.1 (0.8) 92/109.8 (0.8) 0.84 54 to 59 6 19/25.1 (0.8) 13/29.2 (0.4) 32/54.3 (0.6) 1.46 ------------------------------------------------------------------------------------- 6 to 59 54 235/254.5 (0.9) 274/254.5 (1.1) 0.86 The data are expressed as observed number/expected number (ratio of obs/expect) Overall sex ratio: p-value = 0.084 (boys and girls equally represented) Overall age distribution: p-value = 0.000 (significant difference) Overall age distribution for boys: p-value = 0.035 (significant difference) Overall age distribution for girls: p-value = 0.002 (significant difference)

35

Overall sex/age distribution: p-value = 0.000 (significant difference) Digit preference Weight: Digit .0 : ################ Digit .1 : ########################## Digit .2 : ######################## Digit .3 : #################### Digit .4 : #################################### Digit .5 : #################### Digit .6 : ########################## Digit .7 : #################### Digit .8 : ########################## Digit .9 : ########################################## Digit Preference Score: 10 (0-5 excellent, 6-10 good, 11-20 acceptable and > 20 problematic) Digit preference Height: Digit .0 : ###################### Digit .1 : ########################## Digit .2 : ############################ Digit .3 : ############################## Digit .4 : ############################ Digit .5 : #################### Digit .6 : ########################## Digit .7 : #################### Digit .8 : ###################### Digit .9 : ################################# Digit Preference Score: 5 (0-5 excellent, 6-10 good, 11-20 acceptable and > 20 problematic) Digit preference MUAC: Digit .0 : ############## Digit .1 : ######################### Digit .2 : ########################## Digit .3 : ############################# Digit .4 : ######################## Digit .5 : ####################### Digit .6 : ################################# Digit .7 : ######################### Digit .8 : ########################## Digit .9 : ############################ Digit Preference Score: 6 (0-5 excellent, 6-10 good, 11-20 acceptable and > 20 problematic) Evaluation of Standard deviation, Normal distribution, Skewness and Kurtosis using the 3 exclusion (Flag) procedures

36

. no exclusion exclusion from exclusion from

. reference mean observed mean

. (WHO flags) (SMART flags) WHZ Standard Deviation SD: 1.02 1.00 0.98 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 17.4% 17.2% calculated with current SD: 18.1% 17.5% calculated with a SD of 1: 17.7% 17.4% HAZ Standard Deviation SD: 1.37 1.37 1.23 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 26.3% 26.3% 25.0% calculated with current SD: 25.2% 25.2% 22.3% calculated with a SD of 1: 18.1% 18.1% 17.5% WAZ Standard Deviation SD: 1.09 1.09 1.09 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 26.1% 26.1% 25.9% calculated with current SD: 27.4% 27.4% 27.1% calculated with a SD of 1: 25.6% 25.6% 25.4% Results for Shapiro-Wilk test for normally (Gaussian) distributed data: WHZ p= 0.112 p= 0.815 p= 0.437 HAZ p= 0.768 p= 0.768 p= 0.083 WAZ p= 0.006 p= 0.006 p= 0.006 (If p < 0.05 then the data are not normally distributed. If p > 0.05 you can consider the data normally distributed) Skewness WHZ -0.16 -0.04 0.07 HAZ 0.01 0.01 0.04 WAZ -0.25 -0.25 -0.23 If the value is: -below minus 2 there is a relative excess of wasted/stunted/underweight subjects in the sample -between minus 2 and minus 1, there may be a relative excess of wasted/stunted/underweight subjects in the sample. -between minus 1 and plus 1, the distribution can be considered as symmetrical. -between 1 and 2, there may be an excess of obese/tall/overweight subjects in the sample. -above 2, there is an excess of obese/tall/overweight subjects in the sample Kurtosis WHZ 0.45 0.02 -0.25 HAZ 0.03 0.03 -0.46 WAZ -0.07 -0.07 -0.09 (Kurtosis characterizes the relative peakedness or flatness compared with the normal distribution, positive kurtosis indicates a relatively peaked distribution, negative kurtosis indicates a relatively flat distribution)

37

If the value is: -above 2 it indicates a problem. There might have been a problem with data collection or sampling. -between 1 and 2, the data may be affected with a problem. -less than an absolute value of 1 the distribution can be considered as normal. Test if cases are randomly distributed or aggregated over the clusters by calculation of the Index of Dispersion (ID) and comparison with the Poisson distribution for: WHZ < -2: ID=1.21 (p=0.159) WHZ < -3: ID=1.09 (p=0.312) Oedema: ID=1.00 (p=0.471) GAM: ID=1.21 (p=0.159) SAM: ID=1.04 (p=0.397) HAZ < -2: ID=1.57 (p=0.009) HAZ < -3: ID=2.03 (p=0.000) WAZ < -2: ID=1.29 (p=0.096) WAZ < -3: ID=1.38 (p=0.050) Subjects with SMART flags are excluded from this analysis. The Index of Dispersion (ID) indicates the degree to which the cases are aggregated into certain clusters (the degree to which there are "pockets"). If the ID is less than 1 and p > 0.95 it indicates that the cases are UNIFORMLY distributed among the clusters. If the p value is between 0.05 and 0.95 the cases appear to be randomly distributed among the clusters, if ID is higher than 1 and p is less than 0.05 the cases are aggregated into certain cluster (there appear to be pockets of cases). If this is the case for Oedema but not for WHZ then aggregation of GAM and SAM cases is likely due to inclusion of oedematous cases in GAM and SAM estimates. Are the data of the same quality at the beginning and the end of the clusters? Evaluation of the SD for WHZ depending upon the order the cases are measured within each cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made). Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.88 (n=43, f=0) ### 02: 0.99 (n=44, f=0) ######## 03: 1.39 (n=44, f=1) ######################### 04: 1.09 (n=43, f=0) ############ 05: 1.19 (n=42, f=1) ################# 06: 1.08 (n=40, f=1) ############ 07: 0.76 (n=42, f=0) 08: 0.81 (n=40, f=0) 09: 1.06 (n=37, f=0) ########### 10: 0.92 (n=32, f=0) ##### 11: 0.92 (n=24, f=0) ##### 12: 0.76 (n=18, f=0) 13: 1.19 (n=12, f=0) OOOOOOOOOOOOOOOO 14: 0.76 (n=09, f=0)

38

15: 0.78 (n=08, f=0) 16: 0.56 (n=05, f=0) 17: 0.67 (n=05, f=0) 18: 0.97 (n=02, f=0) ~~~~~~~ 19: 1.36 (n=02, f=0) ~~~~~~~~~~~~~~~~~~~~~~~~ 20: 0.94 (n=02, f=0) ~~~~~~ 21: 1.12 (n=02, f=0) ~~~~~~~~~~~~~ (when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points) Analysis by Team Team 1 2 3 4 5 n = 101 110 89 112 97 Percentage of values flagged with SMART flags: WHZ: 3.0 0.9 0.0 1.8 5.4 HAZ: 4.0 3.6 1.1 4.5 7.4 WAZ: 1.0 0.9 0.0 0.9 5.4 Age ratio of 6-29 months to 30-59 months: 0.77 1.29 1.07 0.81 1.02 Sex ratio (male/female): 0.63 0.90 0.98 1.00 0.83 Digit preference Weight (%): .0 : 8 7 4 5 6 .1 : 7 15 9 11 8 .2 : 13 9 8 8 8 .3 : 10 5 8 10 7 .4 : 16 13 15 13 14 .5 : 6 8 18 5 4 .6 : 8 9 9 16 7 .7 : 9 8 3 7 10 .8 : 6 11 13 11 11 .9 : 18 15 12 14 23 DPS: 13 10 14 11 17 Digit preference score (0-5 excellent, 5-10 good, 10-20 acceptable and > 20 problematic) Digit preference Height (%): .0 : 3 15 1 15 7 .1 : 7 14 10 12 9 .2 : 13 7 15 12 9 .3 : 11 10 20 10 8 .4 : 17 14 7 8 8 .5 : 8 8 9 5 10 .6 : 14 12 9 5 11 .7 : 5 8 7 11 8 .8 : 13 7 8 5 9 .9 : 10 5 15 17 19 DPS: 14 10 17 13 10 Digit preference score (0-5 excellent, 5-10 good, 10-20 acceptable and > 20 problematic) Digit preference MUAC (%): .0 : 1 11 4 6 4

39

.1 : 10 8 8 13 9

.2 : 9 12 9 13 7

.3 : 15 13 9 12 8

.4 : 8 12 10 7 9

.5 : 11 10 9 9 6

.6 : 16 11 16 8 16

.7 : 10 8 13 7 12

.8 : 12 7 12 8 13

.9 : 8 7 9 17 15 DPS: 13 6 10 11 12 Digit preference score (0-5 excellent, 5-10 good, 10-20 acceptable and > 20 problematic) Standard deviation of WHZ: SD 1.14 0.97 1.04 0.93 0.99 Prevalence (< -2) observed: % 16.0 18.0 Prevalence (< -2) calculated with current SD: % 19.4 15.8 Prevalence (< -2) calculated with a SD of 1: % 16.2 14.8 Standard deviation of HAZ: SD 1.36 1.33 1.34 1.30 1.45 observed: % 33.7 19.1 25.8 28.8 24.2 calculated with current SD: % 30.8 19.1 23.5 31.1 21.8 calculated with a SD of 1: % 24.8 12.2 16.7 26.0 13.0 Statistical evaluation of sex and age ratios (using Chi squared statistic) for: Team 1: Age cat. mo. boys girls total ratio boys/girls ------------------------------------------------------------------------------------- 6 to 17 12 8/9.0 (0.9) 13/14.4 (0.9) 21/23.4 (0.9) 0.62 18 to 29 12 6/8.8 (0.7) 17/14.0 (1.2) 23/22.8 (1.0) 0.35 30 to 41 12 15/8.6 (1.8) 15/13.6 (1.1) 30/22.1 (1.4) 1.00 42 to 53 12 8/8.4 (1.0) 14/13.4 (1.0) 22/21.8 (1.0) 0.57 54 to 59 6 2/4.2 (0.5) 3/6.6 (0.5) 5/10.8 (0.5) 0.67 ------------------------------------------------------------------------------------- 6 to 59 54 39/50.5 (0.8) 62/50.5 (1.2) 0.63 The data are expressed as observed number/expected number (ratio of obs/expect) Overall sex ratio: p-value = 0.022 (significant excess of girls) Overall age distribution: p-value = 0.189 (as expected) Overall age distribution for boys: p-value = 0.134 (as expected) Overall age distribution for girls: p-value = 0.572 (as expected) Overall sex/age distribution: p-value = 0.007 (significant difference) Team 2: Age cat. mo. boys girls total ratio boys/girls

40

------------------------------------------------------------------------------------- 6 to 17 12 9/12.1 (0.7) 18/13.5 (1.3) 27/25.5 (1.1) 0.50 18 to 29 12 20/11.8 (1.7) 15/13.1 (1.1) 35/24.9 (1.4) 1.33 30 to 41 12 9/11.4 (0.8) 12/12.7 (0.9) 21/24.1 (0.9) 0.75 42 to 53 12 9/11.2 (0.8) 12/12.5 (1.0) 21/23.7 (0.9) 0.75 54 to 59 6 5/5.5 (0.9) 1/6.2 (0.2) 6/11.7 (0.5) 5.00 ------------------------------------------------------------------------------------- 6 to 59 54 52/55.0 (0.9) 58/55.0 (1.1) 0.90 The data are expressed as observed number/expected number (ratio of obs/expect) Overall sex ratio: p-value = 0.567 (boys and girls equally represented) Overall age distribution: p-value = 0.102 (as expected) Overall age distribution for boys: p-value = 0.110 (as expected) Overall age distribution for girls: p-value = 0.184 (as expected) Overall sex/age distribution: p-value = 0.007 (significant difference) Team 3: Age cat. mo. boys girls total ratio boys/girls ------------------------------------------------------------------------------------- 6 to 17 12 10/10.2 (1.0) 13/10.4 (1.2) 23/20.6 (1.1) 0.77 18 to 29 12 13/10.0 (1.3) 10/10.2 (1.0) 23/20.1 (1.1) 1.30 30 to 41 12 14/9.6 (1.5) 14/9.9 (1.4) 28/19.5 (1.4) 1.00 42 to 53 12 6/9.5 (0.6) 7/9.7 (0.7) 13/19.2 (0.7) 0.86 54 to 59 6 1/4.7 (0.2) 1/4.8 (0.2) 2/9.5 (0.2) 1.00 ------------------------------------------------------------------------------------- 6 to 59 54 44/44.5 (1.0) 45/44.5 (1.0) 0.98 The data are expressed as observed number/expected number (ratio of obs/expect) Overall sex ratio: p-value = 0.916 (boys and girls equally represented) Overall age distribution: p-value = 0.015 (significant difference) Overall age distribution for boys: p-value = 0.131 (as expected) Overall age distribution for girls: p-value = 0.190 (as expected) Overall sex/age distribution: p-value = 0.010 (significant difference) Team 4: Age cat. mo. boys girls total ratio boys/girls ------------------------------------------------------------------------------------- 6 to 17 12 12/13.0 (0.9) 9/13.0 (0.7) 21/26.0 (0.8) 1.33 18 to 29 12 12/12.7 (0.9) 17/12.7 (1.3) 29/25.3 (1.1) 0.71 30 to 41 12 15/12.3 (1.2) 18/12.3 (1.5) 33/24.6 (1.3) 0.83 42 to 53 12 11/12.1 (0.9) 7/12.1 (0.6) 18/24.2 (0.7) 1.57 54 to 59 6 6/6.0 (1.0) 5/6.0 (0.8) 11/12.0 (0.9) 1.20 ------------------------------------------------------------------------------------- 6 to 59 54 56/56.0 (1.0) 56/56.0 (1.0) 1.00 The data are expressed as observed number/expected number (ratio of obs/expect) Overall sex ratio: p-value = 1.000 (boys and girls equally represented) Overall age distribution: p-value = 0.196 (as expected) Overall age distribution for boys: p-value = 0.937 (as expected)

41

Overall age distribution for girls: p-value = 0.104 (as expected) Overall sex/age distribution: p-value = 0.075 (as expected) Team 5: Age cat. mo. boys girls total ratio boys/girls ------------------------------------------------------------------------------------- 6 to 17 12 6/10.2 (0.6) 10/12.3 (0.8) 16/22.5 (0.7) 0.60 18 to 29 12 13/10.0 (1.3) 20/12.0 (1.7) 33/21.9 (1.5) 0.65 30 to 41 12 12/9.6 (1.2) 10/11.6 (0.9) 22/21.3 (1.0) 1.20 42 to 53 12 8/9.5 (0.8) 10/11.4 (0.9) 18/20.9 (0.9) 0.80 54 to 59 6 5/4.7 (1.1) 3/5.7 (0.5) 8/10.4 (0.8) 1.67 ------------------------------------------------------------------------------------- 6 to 59 54 44/48.5 (0.9) 53/48.5 (1.1) 0.83 The data are expressed as observed number/expected number (ratio of obs/expect) Overall sex ratio: p-value = 0.361 (boys and girls equally represented) Overall age distribution: p-value = 0.077 (as expected) Overall age distribution for boys: p-value = 0.478 (as expected) Overall age distribution for girls: p-value = 0.115 (as expected) Overall sex/age distribution: p-value = 0.016 (significant difference) Evaluation of the SD for WHZ depending upon the order the cases are measured within each cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made). Team: 1 Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.73 (n=09, f=0) 02: 1.30 (n=09, f=0) ##################### 03: 1.70 (n=09, f=1) ###################################### 04: 0.87 (n=09, f=0) ### 05: 1.35 (n=08, f=1) ####################### 06: 1.55 (n=07, f=0) ############################### 07: 0.62 (n=08, f=0) 08: 0.69 (n=08, f=0) 09: 1.33 (n=08, f=0) ###################### 10: 1.02 (n=08, f=0) ######### 11: 0.94 (n=04, f=0) OOOOOO 12: 0.87 (n=04, f=0) OOO 13: 1.66 (n=02, f=0) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 14: 0.05 (n=02, f=0) 15: 0.78 (n=02, f=0) 16: 0.90 (n=02, f=0) ~~~~ (when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points) Team: 2

42

Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.93 (n=09, f=0) ###### 02: 0.63 (n=09, f=0) 03: 1.29 (n=09, f=0) ##################### 04: 1.16 (n=09, f=0) ############### 05: 1.05 (n=08, f=0) ########### 06: 0.62 (n=08, f=0) 07: 0.57 (n=08, f=0) 08: 0.78 (n=08, f=0) 09: 0.78 (n=07, f=0) 10: 0.97 (n=05, f=0) ####### 11: 0.87 (n=04, f=0) ### 12: 0.61 (n=04, f=0) 13: 1.38 (n=03, f=0) OOOOOOOOOOOOOOOOOOOOOOOO 14: 0.75 (n=03, f=0) 15: 1.16 (n=02, f=0) OOOOOOOOOOOOOOO 16: 0.54 (n=02, f=0) 17: 0.21 (n=02, f=0) (when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points) Team: 3 Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.84 (n=08, f=0) ## 02: 0.89 (n=08, f=0) #### 03: 1.50 (n=08, f=0) ############################# 04: 0.73 (n=08, f=0) 05: 1.55 (n=08, f=0) ################################ 06: 0.86 (n=08, f=0) ## 07: 1.11 (n=08, f=0) ############# 08: 0.68 (n=07, f=0) 09: 1.52 (n=07, f=0) ############################## 10: 0.72 (n=06, f=0) 11: 0.68 (n=06, f=0) 12: 1.08 (n=03, f=0) OOOOOOOOOOOO 13: 1.27 (n=02, f=0) ~~~~~~~~~~~~~~~~~~~~ (when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points) Team: 4 Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.79 (n=09, f=0) 02: 1.04 (n=09, f=0) ########## 03: 1.18 (n=09, f=0) ################

43

04: 1.18 (n=09, f=0) ################ 05: 0.87 (n=09, f=0) ### 06: 0.85 (n=09, f=0) ## 07: 0.89 (n=09, f=0) #### 08: 0.84 (n=09, f=0) # 09: 0.64 (n=08, f=0) 10: 0.74 (n=07, f=0) 11: 0.81 (n=05, f=0) 12: 0.50 (n=04, f=0) 13: 1.39 (n=03, f=0) OOOOOOOOOOOOOOOOOOOOOOOOO 14: 1.09 (n=02, f=0) ~~~~~~~~~~~~ 15: 0.52 (n=02, f=0) 17: 1.05 (n=02, f=0) ~~~~~~~~~~~ (when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points) Team: 5 Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.88 (n=08, f=0) ### 02: 0.87 (n=09, f=0) ### 03: 1.02 (n=09, f=0) ######### 04: 1.46 (n=08, f=0) ############################ 05: 1.06 (n=09, f=0) ########### 06: 1.56 (n=08, f=1) ################################ 07: 0.54 (n=09, f=0) 08: 0.99 (n=08, f=0) ######## 09: 0.85 (n=07, f=0) ## 10: 0.91 (n=06, f=0) ##### 11: 1.29 (n=05, f=0) ##################### 12: 0.76 (n=03, f=0) 13: 0.15 (n=02, f=0) (when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points) (for better comparison it can be helpful to copy/paste part of this report into Excel)

44

Annex 2

Assignment of Clusters

Geographical unit Population size Cluster

Aguat 269 Aguat Hong 433 Aguat Thong 528 Alang 119 Ayak Hong 259 Riangbar 359 1

Rolchol 266 Rum Deng Malou 295 Ulang 251 Warawar - Ubuokii 577 Warchuer 438 AWiel Pouou 579 Ayendit 418 Maduany 905 2

Maker Diing 541 Panthoi 264 Adanya 292 Adheima 332 Amothic 413 Ayongoi 229 Mabil Nhom 254 3

Malou Alel 510 Mareng Akuar 255 Marol Week 184 Mawella 616 Panrak 211 Riang Ajiing 464 Riangthon Cenguek 301 Rum Wetkor 205 Rummiirmed 159 Rumnyiel 469 4

Majak Piol 194 Maker Amuk 551 Maker Pan Aguer 720 Maker Wutic 616 Malek Alel 270 Marol Wol 367 5

Auchier 316 Awet 132

45

Majok Kuac 455 Majok Kuel 167 Marial Lual 301 Mayen 247 Riang Angon 577 Riang Malek Dut 184 War Alel 281 Wun Riang 335 Wun Uchanga 200 RC

Ben Ben 598 Hila Kamuja 468 Hongapat 486 Long Ariath 835 Lueth Abur 424 Machak Lang 438 RC

Majak Wut 614 Majok Ayuel Centre 341 Majok Nyok 169 Malek Alel 517 Malek Bin 291 Maper Yatthdit 402 Marial Wut 639 6

Muoch Atek 595 Nyikel 451 Pan Hong 406 Riang Diar 727 Riang Majok 895 7

Rum Lual Deng 96 Thok Ayuor 933 Titamata 485 Udhum 185 Udhum Centre 718 War Adhot 166 Liet Achol 272 8

Liethic 368 Akuak Ngap 1071 Ayak Hong 601 Ayakiit 886 9

Got Chok 1562 Got Nhom 1191 Hai Mathar 1050 10

Hong Buoi 537 Hong Chok 945 Hong Pakir 934 11

46

Macama 1341 Malma 528 Nyamlel 1459 12

Nyamlel Dit 1106 Pan Thoi 557 Pantit 489 Panyieth 575 13

Warawar 455 Wungueng 723 Aluel Achot 276 Aram Duang 285 Chumich 373 Ngok Rol 266 Noya 280 Piny Gaya 686 14

Riang Baar 377 Tekyi Nhom 421 Millitary Baracks 1069 New Life School 234 Nyamlel TB Hospital 145 Prison Department 176 Akot Awet 760 15

Amothic 759 Ating Thony 748 Ayath Kon 709 Ciwel 1367 16

Gok Thin 903 Got Chok 673 Kang Kuot 776 17

Mabior Rum 425 Magondit 804 Marol Akoon 595 Mathiang 617 Mathlith Thony 1553 18

Nyamlel Thii 1747 Nyin Mayen 676 19

War Alel 416 Abyei 702 Adotic 144 Akeu Pajiey 460 Akueic 558 Alel Thok 222 20

Angol 561 Langic 324

47

Lieth Nhom 396 Lil Thok 416 Mabok Kuot 264 Macharangom 353 Magar Nuol 604 Majak Lual 171 21

Majok 386 Maper Dit 368 Marol Atak 87 Marol Bol 370 Wakow 340 War Chuei 560 Yardit 294 Auchir 490 Aweet 482 22

Kuech Mathiang 356 Mabil 308 Machar Akot Athuol 399 Madhol 406 Maker 507 Malek Lol 798 23

Malith Buol 846 Nhom Lau A 882 Nhom Lau B 1626 RC

Pan Kocrac 255 Riang Viit 311 Ric Gom Juer 198 Rum Deng Malou 148 Rum Diar 296 Wat Nyang 267 Wet Weil 293 Wun Adot 205 Wut Akuak 335 Akuark Bak 595 RC

Gori 389 Machar Agany 381 Malou Goudo 201 Maper Pami 543 Uban 226 Acahana 168 Angicjo 117 Chumcok 227 Makul Gum 81 Panamada 196

48

Jorboich 741 24

Mangok Deng Dit 226 Kakou 689 Majok Deng Dit 934 Majok Gok 443 Makol Tit 657 25

Adhiam Kou 292 Akuak lang 543 Amudho 517 Amudho Alel Thok 644 Hong Wet Jok 503 Magok 185 26

Majok ngor Aleu 192 RiangAlei 263 Wanthkunyuk 297 Aciliet 221 Anyoupjang 586 Auceir 183 Hong wet wek 628 Panrup 214 Panthoi 254 Pantit 789 27

Lang Aken 228 Nyin Alel Majak 541 Akuer ngom 87 Mabok Akot 101 Makuac 368 Maper Gum 301 Marol boul 436 Ngor gap 67 Nyiret 603 28

Riang Achor 166 Riang kou 194 Topyep 129 Warkil 445 Warkot 128 Hong Thok 477 Majak Dut Ngong 342 Majok Adim 316 Malual Liet 355 Mayom Amum 194 29

Pan lang 285 Mading biel 410 Majok Alel 296

49

Maker Alel 637 Malek Ubur 295 Maluid 244 Pan Hong 647 Pan Hong chok 204 30

Agor 1007 Akek Rot 700 Alel Thok 735 Awada 1014 31

Langic 912 Machar Dau Yiel 604 Maker Ajieth 489 Mathar kou 687 32

Nyinken 647 Pan Riang 1092 Rumtit 532 War Alel 601 Gukger 321 33

Gukic 253 Lilthok 563 Maraial Baai 1131 Marail Adoot 857 Mour wel 206 34

Pan lang Agar 380 Makum 440 Malek Ubur 334 Marial Lual 380 Mayom 771 Ajok Celic 364 Akuangrel 393 RC

Akuangyok 814 Akuark Det 250 Akueng Adhot 163 Angon lek 209 Bariang 339 Gakrol 360 Hong Thon 259 Maper Tit 572 35

Mathiang Garang 330 Yal 550 Yal Akuak 126 Ajok Gout 576 Akek Rot 968 Dhiama 420 36

50

Gokic 660 Langic 946 Machar Akot Alich 481 Majaak Ajar 597 Majak Nhom 423 37

Maluil Athony 714 Abinkuel 324 Akotatap 146 Akoung 661 Akoung Atung 444 Akuanggueth 303 Akuark kar 646 38

Akuark kou 422 Dieng Ayen 195 Gum 374 Gumnhom 348 Karkou 558 Wungap 349 Wungiir 538 Akuark akuet 527 39

Akuarkroul 643 Hong Wol Wetjong 396 Kar-kar kou 400 Magok adeng 493 Malek mayar 567 Rumakouudok 758 40

Akuark Machar 423 Angon Awer 402 Angot Kil 246 Jouk kou 615 Lueth Jiel 333 Malou Diing 555 41

Mayom Bol 721 Moung Hol Met 626 Maker Miir 297 Makouc 1064 Nyinjong 1182 42

Paukou 771 akuark lang 647 Mabior Doung 529 machar ugauak 532 43

Maker 760 Mayom agep 297 Nyinbouli 1447

51

Nyipuga 386 44

Pon nyang 433 Umal 405

52

Annex 3

Evaluation of Enumerators

Weight:

Precision: Accuracy: No. +/- No. +/-

Sum of Square Sum of Square Precision Accuracy

[W2-W1] [Superv.(W1+W2)-

Enum.(W1+W2]

Supervisor 14.47 4/6

Enumerator 1 2.42 OK 21.37 OK 4/6 4/5

Enumerator 2 1.79 OK 22.32 OK 3/6 4/4

Enumerator 3 0.40 OK 16.37 OK 0/5 1/7

Enumerator 4 12.29 OK 23.44 OK 4/5 3/4

Enumerator 5 0.46 OK 15.31 OK 3/6 2/6

Enumerator 6 0.48 OK 15.29 OK 2/6 2/4

Enumerator 7 1.14 OK 17.77 OK 4/5 5/4

Enumerator 8 2.27 OK 15.50 OK 2/6 2/6

Enumerator 9 0.67 OK 13.88 OK 4/6 5/2

Enumerator 10 2.01 OK 15.20 OK 4/6 6/4

Enumerator 11 0.34 OK 16.75 OK 4/4 5/5

Enumerator 12 0.71 OK 15.30 OK 2/5 4/2

Enumerator 13 0.71 OK 16.22 OK 3/7 1/7

Enumerator 14 6513.59 POOR 5898.52 POOR 3/6 5/3

Enumerator 15 0.82 OK 15.83 OK 2/6 4/5

Enumerator 16 7.68 OK 33.93 OK 1/8 3/6

Enumerator 17 1.12 OK 13.29 OK 3/6 4/5

Enumerator 18 13.82 OK 23.55 OK 3/6 4/6

Enumerator 19 0.76 OK 15.05 OK 3/5 4/6

Enumerator 20 0.67 OK 15.42 OK 2/6 0/8

Height:

Precision: Accuracy: No. +/- No. +/-

Sum of Square Sum of Square Precision Accuracy

[H2-H1] [Superv.(H1+H2)-

Enum.(H1+H2]

Supervisor 77.83 6/4

Enumerator 1 10.81 OK 83.88 OK 5/5 6/4

53

Enumerator 2 11.65 OK 86.20 OK 4/4 6/4

Enumerator 3 58.27 OK 255.58 POOR 8/2 8/2

Enumerator 4 55.67 OK 259.48 POOR 6/4 7/3

Enumerator 5 3.72 OK 94.65 OK 6/4 7/3

Enumerator 6 7.14 OK 92.77 OK 7/3 7/3

Enumerator 7 7.80 OK 114.23 OK 5/5 10/0

Enumerator 8 4566.74 POOR 3803.19 POOR 4/5 7/3

Enumerator 9 6.72 OK 75.89 OK 5/5 5/5

Enumerator 10 10.53 OK 80.86 OK 9/1 8/2

Enumerator 11 7.41 OK 114.60 OK 6/4 6/3

Enumerator 12 6.65 OK 100.06 OK 5/5 7/3

Enumerator 13 9.34 OK 61.97 OK 6/4 6/3

Enumerator 14 6599.86 POOR 5704.91 POOR 5/4 4/6

Enumerator 15 2.98 OK 59.49 OK 7/3 6/4

Enumerator 16 470.15 POOR 226.62 OK 8/2 7/3

Enumerator 17 7.85 OK 100.04 OK 7/3 7/3

Enumerator 18 237.67 POOR 245.36 POOR 6/2 6/4

Enumerator 19 9554.94 POOR 8364.93 POOR 8/2 4/6

Enumerator 20 5.83 OK 72.96 OK 4/4 6/4

MUAC:

Precision: Accuracy: No. +/- No. +/-

Sum of Square Sum of Square Precision Accuracy

[MUAC2-MUAC1] [Superv.(MUAC1+MUAC2)-

Enum.(MUAC1+MUAC2]

Supervisor 29.35 9/0

Enumerator 1 Error Error 7/3 6/4

Enumerator 2 4.26 OK 33.75 OK 9/1 7/3

Enumerator 3 2.58 OK 18.27 OK 5/3 5/4

Enumerator 4 2.78 OK 26.01 OK 3/6 3/5

Enumerator 5 2.08 OK 20.99 OK 7/1 7/3

Enumerator 6 2.72 OK 26.33 OK 6/3 6/3

Enumerator 7 5.07 OK 32.86 OK 10/0 7/3

Enumerator 8 0.89 OK 32.86 OK 2/4 1/9

Enumerator 9 Error Error 7/2 3/7

Enumerator 10 2.24 OK 38.31 OK 6/2 2/8

Enumerator 11 4.37 OK 19.46 OK 2/7 6/4

Enumerator 12 1.67 OK 19.36 OK 1/7 8/2

Enumerator 13 0.26 OK 41.29 OK 5/2 0/10

Enumerator 14 12.48 OK 44.15 OK 7/3 1/8

54

Enumerator 15 11.02 OK 27.53 OK 5/4 3/7

Enumerator 16 20.69 OK 40.68 OK 7/3 4/6

Enumerator 17 3.62 OK 22.73 OK 7/3 2/7

Enumerator 18 2.96 OK 39.39 OK 8/2 2/6

Enumerator 19 9968.34 POOR 8897.51 POOR 9/0 3/7

Enumerator 20 1.49 OK 34.86 OK 6/2 1/9

For evaluating the enumerators the precision and the accuracy of their measurements is calculated.

For precision the sum of the square of the differences for the double measurements is calculated. This value should be less than two times the precision value of the supervisor.

For the accuracy the sum of the square of the differences between the enumerator values (weight1+weight2) and the supervisor values (weight1+weight2) is calculated. This value should be less than three times the precision value of the supervisor.

To check for systematic errors of the enumerators the number of positive and negative deviations can be used.

55

Annex 4

Result Tables for NCHS Growth Reference 1977

Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex

All n = 502

Boys n = 231

Girls n = 271

Prevalence of global malnutrition (<-2 z-score and/or oedema)

(92) 18.3 % (15.2 - 21.9 95% C.I.)

(47) 20.3 % (15.1 - 26.8 95% C.I.)

(45) 16.6 % (13.4 - 20.4 95% C.I.)

Prevalence of moderate malnutrition (<-2 z-score and >=-3 z-score, no oedema)

(85) 16.9 % (14.1 - 20.3 95% C.I.)

(42) 18.2 % (13.4 - 24.2 95% C.I.)

(43) 15.9 % (12.5 - 19.9 95% C.I.)

Prevalence of severe malnutrition (<-3 z-score and/or oedema)

(7) 1.4 % (0.5 - 4.1 95% C.I.)

(5) 2.2 % (0.6 - 7.8 95% C.I.)

(2) 0.7 % (0.2 - 3.0 95% C.I.)

The prevalence of oedema is 0.2 % Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema

Severe wasting (<-3 z-score)

Moderate wasting (>= -3 and <-2 z-score )

Normal (> = -2 z score)

Oedema

Age (mo)

Total no.

No. % No. % No. % No. %

6-17 108 0 0.0 13 12.0 95 88.0 0 0.0

18-29 140 4 2.9 31 22.1 105 75.0 0 0.0

30-41 134 2 1.5 28 20.9 103 76.9 1 0.7

42-53 90 0 0.0 10 11.1 80 88.9 0 0.0

54-59 30 0 0.0 3 10.0 27 90.0 0 0.0

Total 502 6 1.2 85 16.9 410 81.7 1 0.2

Distribution of acute malnutrition and oedema based on weight-for-height z-scores

<-3 z-score >=-3 z-score

Oedema present Marasmic kwashiorkor No. 0 (0.0 %)

Kwashiorkor No. 1 (0.2 %)

Oedema absent Marasmic No. 6 (1.2 %)

Not severely malnourished No. 495 (98.6 %)

56

Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) and by sex

All n = 505

Boys n = 234

Girls n = 271

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

(35) 6.9 % (4.6 - 10.2 95% C.I.)

(16) 6.8 % (4.1 - 11.2 95% C.I.)

(19) 7.0 % (4.4 - 11.1 95% C.I.)

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

(27) 5.3 % (3.5 - 8.0 95% C.I.)

(11) 4.7 % (2.7 - 8.1 95% C.I.)

(16) 5.9 % (3.6 - 9.5 95% C.I.)

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

(8) 1.6 % (0.6 - 4.1 95% C.I.)

(5) 2.1 % (0.8 - 5.9 95% C.I.)

(3) 1.1 % (0.4 - 3.4 95% C.I.)

Prevalence of acute malnutrition by age, based on MUAC cut off's and/or oedema

Severe wasting (< 115 mm)

Moderate wasting (>= 115 mm and < 125 mm)

Normal (> = 125 mm )

Oedema

Age (mo)

Total no.

No. % No. % No. % No. %

6-17 106 2 1.9 13 12.3 91 85.8 0 0.0

18-29 142 5 3.5 11 7.7 126 88.7 0 0.0

30-41 134 0 0.0 2 1.5 132 98.5 1 0.7

42-53 91 0 0.0 1 1.1 90 98.9 0 0.0

54-59 32 0 0.0 0 0.0 32 100.0 0 0.0

Total 505 7 1.4 27 5.3 471 93.3 1 0.2

Prevalence of acute malnutrition based on the percentage of the median and/or oedema

n = 502

Prevalence of global acute malnutrition (<80% and/or oedema)

(57) 11.4 % (8.5 - 15.0 95% C.I.)

Prevalence of moderate acute malnutrition (<80% and >= 70%, no oedema)

(53) 10.6 % (7.9 - 13.9 95% C.I.)

Prevalence of severe acute malnutrition (<70% and/or oedema)

(4) 0.8 % (0.2 - 2.7 95% C.I.)

57

Prevalence of malnutrition by age, based on weight-for-height percentage of the median and oedema

Severe wasting (<70% median)

Moderate wasting (>=70% and <80% median)

Normal (> =80% median)

Oedema

Age (mo)

Total no.

No. % No. % No. % No. %

6-17 108 0 0.0 6 5.6 102 94.4 0 0.0

18-29 140 1 0.7 24 17.1 115 82.1 0 0.0

30-41 134 2 1.5 14 10.4 117 87.3 1 0.7

42-53 90 0 0.0 8 8.9 82 91.1 0 0.0

54-59 30 0 0.0 1 3.3 29 96.7 0 0.0

Total 502 3 0.6 53 10.6 445 88.6 1 0.2

Prevalence of underweight based on weight-for-age z-scores by sex

All n = 502

Boys n = 231

Girls n = 271

Prevalence of underweight (<-2 z-score)

(161) 32.1 % (27.9 - 36.5 95% C.I.)

(76) 32.9 % (26.9 - 39.5 95% C.I.)

(85) 31.4 % (26.4 - 36.8 95% C.I.)

Prevalence of moderate underweight (<-2 z-score and >=-3 z-score)

(120) 23.9 % (20.6 - 27.5 95% C.I.)

(57) 24.7 % (19.6 - 30.5 95% C.I.)

(63) 23.2 % (18.6 - 28.6 95% C.I.)

Prevalence of severe underweight (<-3 z-score)

(41) 8.2 % (5.9 - 11.3 95% C.I.)

(19) 8.2 % (4.8 - 13.7 95% C.I.)

(22) 8.1 % (5.5 - 11.8 95% C.I.)

Prevalence of underweight by age, based on weight-for-age z-scores

Severe underweight (<-3 z-score)

Moderate underweight (>= -3 and <-2 z-score )

Normal (> = -2 z score)

Oedema

Age (mo)

Total no.

No. % No. % No. % No. %

6-17 108 4 3.7 17 15.7 87 80.6 0 0.0

18-29 140 21 15.0 37 26.4 82 58.6 0 0.0

30-41 133 13 9.8 37 27.8 83 62.4 1 0.8

42-53 91 3 3.3 22 24.2 66 72.5 0 0.0

54-59 30 0 0.0 7 23.3 23 76.7 0 0.0

Total 502 41 8.2 120 23.9 341 67.9 1 0.2

58

Prevalence of stunting based on height-for-age z-scores and by sex

All n = 492

Boys n = 229

Girls n = 263

Prevalence of stunting (<-2 z-score)

(92) 18.7 % (14.6 - 23.6 95% C.I.)

(43) 18.8 % (13.4 - 25.6 95% C.I.)

(49) 18.6 % (14.0 - 24.3 95% C.I.)

Prevalence of moderate stunting (<-2 z-score and >=-3 z-score)

(70) 14.2 % (11.4 - 17.6 95% C.I.)

(33) 14.4 % (10.6 - 19.2 95% C.I.)

(37) 14.1 % (10.5 - 18.6 95% C.I.)

Prevalence of severe stunting (<-3 z-score)

(22) 4.5 % (2.7 - 7.2 95% C.I.)

(10) 4.4 % (2.0 - 9.1 95% C.I.)

(12) 4.6 % (2.3 - 8.7 95% C.I.)

Prevalence of stunting by age based on height-for-age z-scores

Severe stunting (<-3 z-score)

Moderate stunting (>= -3 and <-2 z-score )

Normal (> = -2 z score)

Age (mo)

Total no.

No. % No. % No. %

6-17 106 3 2.8 3 2.8 100 94.3

18-29 136 6 4.4 27 19.9 103 75.7

30-41 129 7 5.4 22 17.1 100 77.5

42-53 89 5 5.6 13 14.6 71 79.8

54-59 32 1 3.1 5 15.6 26 81.3

Total 492 22 4.5 70 14.2 400 81.3

Mean z-scores, Design Effects and excluded subjects

Indicator n Mean z-scores ± SD

Design Effect (z-score < -2)

z-scores not available*

z-scores out of range

Weight-for-Height 501 -1.22±0.86 1.00 8 0

Weight-for-Age 502 -1.55±1.02 1.04 7 0

Height-for-Age 492 -0.91±1.21 1.58 3 14

* contains for WHZ and WAZ the children with edema.

59

Annex 5

Questionnaire SMART Survey, DDG – South Sudan, April 2014

No. Question Question type

Answer options Logic Validation

Section 1: Introduction and consent

1 This survey should be administered to the primary caregiver, usually the mother. Hello. My name is _________ and I work with Concern Worldwide. I am here today to conduct a household survey. The purpose of this survey is to obtain information on the health and nutrition practices of households in this village. We would also like to take some body measurements of young children to see how they are growing. This survey is voluntary and the information you give will be confidential and does not identify you or your household. The information will be used purely for project monitoring purposes and will not have any effect on services or assistance that you are receiving or should be receiving. Please answer all questions honestly. We are using this new machine to help us to collect information. It does not record your voice or take your photograph. It will store your information very safely and help us to make decisions about our work. Do you have any questions before we begin?

2 May I start now? Single choice 1. Yes If no, skip to the

60

2. No closing section of the survey.

Section 2: Mortality

3 How many people currently live in this household? (a household is defined as a group of people living under the same roof and sharing food from the same pot. In homes with multiple wives, those living and eating in different houses are considered as separate households. Wives living in different houses and eating from the same pot are considered as one household)

Number

4 How many children less than 5 years currently live in this household?

Number

5 Since Christmas Day, how many people in total have joined the household?

Number

6 Since Christmas Day, how many children less than 5 years have joined the household?

Number

7 Since Christmas Day, how many people in total have left the household?

Number

8 Since Christmas Day, how many children less than 5 years have left the household?

Number

9 Since Christmas Day, how many live births have occurred in this household? (any child born alive, even if only alive for few minutes)

Number

10 Since Christmas Day, how many people have died in the household?

Number

11 Since Christmas Day, how many children less than 5 years have died in this household?

Number If 0, skip to Q13

12 Reason for death among children less than 5 years? Multiple choice

1. Confirmed Malaria 2. Fever 3. Diarrhoea 4. Difficulty Breathing 5. Malnutrition 6. Measles 7. Accident 8. Violence

61

9. Other (specify) 10. Do not Know

Section 3: Anthropometrics and Infant/ Young Child Feeding practices

13 This survey should be administered to the primary caregiver, usually the mother, of children under 5 years only.

Information

14 Is there a child under 5 years in this household?

Single Choice 1. Yes 2. No

If no, skip to Q106

15 Take out your paper notepad and pen and write down the names of all the children aged 0 – 59 In this household. Start with the oldest child aged 0 – 59 months and write their name and age in months. Then the second oldest child – write their name and age in months (to determine age, ask mother to see immunization card or health cards or use the local events calendar to estimate age). Continue for all children. Once you have the names and ages of all children aged 0 – 59 months in the household, complete the following questions. Start with the oldest child (the first child on your list) and continue for all children in the household.

Information

16 Name of child Text

17 Sex of (name)

Single Choice 1. Male 2. Female

Insert name given in Q16

18 Date of Birth of (name) Date Insert name given in Q16

1 April 2009 to present only

19 Age of (name) in months Number Insert name given in Q16

0 – 59 only

20 Weight of (name) in kg (eg 12.4)

Number with one decimal place

Insert name given in Q16

Max of 50 One decimal

62

place

21 Height of (name) in cm (eg 78.1)

Number with one decimal place

Insert name given in Q16

Max of 130 One decimal place

Did you take the height or the length of the child? Single Choice 1. Height 2. Length

22 Does (name) have oedema ? (Test for bilateral pitting oedema, pressing thumbs for 3 seconds on both feet)

Single Choice 1. Yes 2. No

Insert name given in Q16 If yes, skip to Q24

Take photo of oedema test Photo

23 MUAC of (name) in cm (eg 12.3) Number with one decimal place

Insert name given in Q16

Max of 30.0 One decimal place

24 Did (name) receive a vitamin A capsule in last 6 months (since St. Daniel Comboni Day)? (Show sample of capsule)

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

25

Did (name) receive deworming medicine in the last 6 months (since St. Daniel Comboni Day)? (Show sample of tablet)

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

26 Has (name) been vaccinated against measles?

Single Choice 1. No 2. Yes, verified by card 3. Yes, mother’s recall 4. Do not know

Insert name given in Q16

27 Was (name) sick in the last 2 weeks ?

Single Choice 1. Yes 2. No

Insert name given in Q16 If no, skip to Q36

28 What illness did (name) suffer in the last 2 weeks? Multiple choice

1. Fever 2. Cough

Insert name given in Q16

63

3. Diarrhoea 4. Skin Infection 5. Eye infection 6. Measles 7. Malnutrition 6. Other (specify)

29a Did you take (name) for treatment when sick in the last 2 weeks?

Single choice 1. Yes 2. No

Insert name given in Q16 If no, skip to Q31

29b Where did you take (name) for treatment when sick in the last 2 weeks?

Single choice 1. Hospital 2. PHCC 3. PHCU 4. Mobile/outreach clinic 5. CDD – Community Drug

Distributor 6. HHP – Home Health Promoter 7. Traditional practitioner/

traditional healer 8. Shop 9. Relative/friend 10. Pharmacy 11. Other

Insert name given in Q16

30 Who decided that (name) should be taken to (option)? Multiple Choice

1. Myself 2. Husband 3. My mother 4. My mother-in-law 5. Friend/neighbour 6. Other (Specify)

Insert name given in Q16 Insert option given in Q29b

31 Did (name) take any medicine since the fever started? Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16 Filter: only show this question if option 1 selected in Q28

32 What medicine did (name) take? (Ask to see treatment Multiple 1. Coartem (Artesunate/Amodiaquine) Insert name given in

64

care) (Show coartem tablet) Choice 2. Quinnine 3. Paracetamol 4. Other (Specify)

Q16 Filter: only show this question if option 1 selected in Q28

33 When (name) had diarrhoea, was anything given for treatment?

Multiple Choice

1. No 2. ORS sachet 3. Sugar salt solution 4. Thin porridge 5. Other (Specify) 6. Did not have diarrhoea

Insert name given in Q16 Filter: only show this question if option 3 selected in Q28

34 When (name) had diarrhoea, how much liquid was given to (name) as compared to when she or he is healthy?

Single Choice 1. Nothing given to drink 2. Much less than normal 3. Somwhat less than normal 4. About the same 5. More than normal 6. Do not know/remember

Insert name given in Q16 Filter: only show this question if option 3 selected in Q28

35 When (name) had diarrhoea, how much food was given to (name) as compared to when she or he is healthy?

Single Choice 1. No food given 2. Much less than normal 3. Somewhat less than normal 4. About the same 5. More than normal 6. Do not know/remember

Insert name given in Q16 Filter: only show this question if option 3 selected in Q28

36 Did (name) sleep under a mosquito net last night?

Single Choice 1. Yes 2. No

Insert name given in Q16

37 MUAC of mother in cm (eg 24.3) Number with one decimal place

Max of 40.0 One decimal place

38 Is the mother pregnant or breastfeeding? Single Choice 1. Yes, pregnant 2. Yes, breastfeeding 3. No

39 Is (name) aged 0 – 23 months? (Check your notepad)

Single Choice 1. Yes 2. No

Insert name given in Q16

65

If no, skip to Q68

40 Did you ever breastfeed (name)?

Single Choice 1. Yes 2. No

Insert name given in Q16 If no, skip to Q45

41 How long after birth did you first put (name) to the breast?

Single Choice 1. Immediately (less than 1 hour) 2. Between 1 – 24 hours 3. Between 2 – 3 days 4. Longer than 3 days 5. Do not know/ don’t remember

Insert name given in Q16

42 In the first 3 days after delivery, did you give any food or liquid other than breast milk to (name)?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16 If no, skip to Q44

43 What was (name) given in the first 3 days after delivery? Multiple Choice

1. Plain water 2. Sugar water or glucose water 3. Water with salt 4. Animal milk 5. Infant formula (eg Nan) 6. Other (Specify)

Insert name given in Q16

44 Was (name) breastfed yesterday during the day or at night?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

45 I would like to ask you about the types of liquids that (name) consumed yesterday during the day or at night.

Information Insert name given in Q16

46 Did (name) have plain water yesterday during the day or at night?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

47 Did (name) have infant formula (eg Nan) yesterday during the day or at night?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16 If no or do not know, skip to Q49

48 How many times did (name) have infant formula Number Insert name given in

66

yesterday during the day or at night? Q16

49 Did (name) have milk other than breast milk (tinned, powdered, fresh animal milk, sour milk) yesterday during the day or at night?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16 If no or do not know, skip to Q51

50 How many times did (name) have milk other than breast milk (tinned, powdered, fresh animal milk, sour milk) yesterday during the day or at night?

Number Insert name given in Q16

51 Did (name) have juice or juice drinks yesterday during the day or at night?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

52 Did (name) have any other liquids, including sugar water, clear broth, other water-based liquids, e.g. tea/ coffee yesterday during the day or at night?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

53 Did (name) have yogurt yesterday during the day or at night?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16 If no or do not know, skip to Q55

54 How many times did (name) have yogurt yesterday during the day or at night?

Number Insert name given in Q16

55 Did (name) have thin porridge yesterday during the day or at night?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

56 I would now like to ask you about all the foods (all meals and snacks) that (name) ate yesterday during the day or at night.

Information Insert name given in Q16

57 Yesterday during the day or at night, did (name) eat cereals/ staples (aseda, esh, ayup, porridge, bread, rice, macaroni, chappati, maize, sorghum, millet, ugali, CSB, CSB+, CSB++)?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

58 Yesterday during the day or at night, did (name) eat roots and tubers (white sweet potato , yam, cassava, irish

Single Choice 1. Yes 2. No

Insert name given in Q16

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potato)? 3. Do not know

59 Yesterday during the day or at night, did (name) eat beans and other pulses/pullen/legumes/nuts (groundnuts, simsim, yellow peas, g nut paste, simsim paste, lentils, haricot beans, cowpea, chickpeas)?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

60 Yesterday during the day or at night, did (name) eat milk or mik products (animal milk, yogurt, cheese, sour milk, fermented milk)?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

61 Yesterday during the day or at night, did (name) eat eggs?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

62 Yesterday during the day or at night, did (name) eat fish/seafood (fresh/ dried) ?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

63 Yesterday during the day or at night, did (name) eat meat (beef, goat, chicken, birds, mutton, duck, pork – including offals – liver, heart, kidney, intestines and insects/termites/ants)?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

64 Yesterday during the day or at night, did (name) eat yellow or orange coloured fruits or vegetables (mango, papaya, ripe jackfruit, carrot, pumpkin) or... green dark leafy vegetables (rigila, khudra, akuar,sukuma wiki, pumpkin leaves, cassava leaves, kale, spinach, cowpea leaves), orange squash, yellow-orange fleshed sweet potato?

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

65 Yesterday during the day or at night, did (name) eat other fruits or vegetables (tomato, onion, mango, watermelon, cabbage, lemon, coconut, palm fruit, date palm, lulu fruit, tamarin, lalok fruit, lalok leaves, okra, cucumber, eggplant, passion fruit, dum, banana, orange, lime, apple, cherries, courgette/zucchini) wild fruit and wild vegetable

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

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66 Yesterday during the day or at night, did (name) eat RUTF/plumpy’nut? (show common sachet)

Single Choice 1. Yes 2. No 3. Do not know

Insert name given in Q16

67 How many times did (name) eat solid, semi-solid or soft foods yesterday during the day or night ? (Enter 98 for Do not know)

Number Insert name given in Q16

68 Is there another child aged 0 – 59 months in this household? (Check your notepad)

Single Choice 1. Yes 2. No

If yes, return to Q16 If no, go to Q69

69 In your household, who makes the final decision of how your child should be fed (what should be given and when)?

Multiple choice

1. Myself 2. Husband 3. My mother 4. My mother-in-law 5. Friend/neighbour 6. Other (Specify)

Section 4: Food Security and Livelihoods

70 Is the head of household male or female? Single Choice 1. Male 1. Female

71 What was your households main source of income in the last 30 days?

Single Choice 1. Sale of crops 2. Sale of livestock 3. Sale of animal products 4. Brewing 5. Sale of fish 6. Sale of natural resources (firewood, grass) 7. Sale of food aid 8. Casual labour 9. Skilled labour 10. Salaried work 11. Other petty trading 12. Small business 13. Family support 14. Other (specify)

72 What was your households main source of food in the past Single Choice 1. Own production

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7 days? 2. Work for food 3. Gifts 4. Market/shop purchase 5. Borrowing/debt 6. Food aid 7. Gathering 8. Other (Specify)

73 Out of your household monthly expenditure, how much was allocated to food purchases?

Single Choice 1. 0% 2. 1-25% 3. 26-50% 4. >50% 5. Do not know

74 In the past 30 days, have there been times when you did not have enough food or money to buy food?

Single Choice 1. Yes 2. No

If no, skip to Q76

75 Which coping strategies did you use? (do not read out options) (record all options mentioned)

Multiple Choice

1. Rely on less preferred/cheaper food 2. Borrowing/kinship support 3. Reduce portion size at meals 4. Reduce number of meals adults eat 5. Reduce number of meals for family 6. Sell more animals than usual 7. Consume seed stock 8. Other (Specify)

76 What are the 3 main shocks currently faced by your household?

Multiple Choice

1. No schocks 2. Insecurity 3. Expensive food 4. Livestock disease 5. Floods 6. Human sickness 7. Delay of rains 8. Pest/crop disease 9. Lack of water 10. Other (Specify)

Max of 3 options to be selected

Section 5: Water, Sanitation and Hygiene

77 What is your household’s main source of drinking water currently?

Single Choice 1. Borehole 2. Protected well 3. Open well

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4. Protected spring 5. Unprotected spring 6. Surface water (river, stream) 7. Piped water/household connection/water tank 8. Pond/dam 9. Other (Specify)

78 What is your household’s main source of drinking water during the rainy season?

Single Choice 1. Borehole 2. Protected well 3. Open well 4. Protected spring 5. Unprotected spring 6. Surface water (river, stream) 7. Piped water/household connection/water tank 8. Pond/dam 9. Other (Specify)

79 How long does it take you to collect water for the household (including travel to and from and waiting time)?

Single Choice 1. Less than 30 minutes 2. 30 minutes to less than 1 hour 3. 1 hour to less than 2 hours 4. 2 hours to less than 4 hours 5. 4 hours and above

80 How many jerricans (20l) of water did the household use yesterday in total? (Consider balance of fetched water and left over amount)

Number

81 Is anything done to the water before drinking? Single Choice 1. Yes 2. No

In no, skip to Q83

82 What is done to the water before drinking? Multiple Choice

1. Boil 2. Filter with a cloth 3. Let it settle 4. Chlorination 5. Other (Specify)

83 Did you wash your hands yesterday? Single Choice 1. Yes 2. No

If no, skip to Q85

84 When did you wash your hands yesterday? (do not read Multiple 1. After defecation

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out options) (probe) (list all options mentioned) Choice 2. After cleaning a child who has defecated. 3. Before preparing food 4. Before eating 5. Before feeding a child 6. Other (Specify)

85 Do you use anything in addition to water to wash your hands?

Single Choice 1. Yes 2. No

If no, skip to Q87

86 What do you use to wash your hands? Single Choice 1. Water plus soap 2. Water plus ash 3. Other (Specify)

87 Do you currently have soap? Single Choice 1. Yes 2. No

If no, skip to Q89

88 Can I see the type of soap you have? Single Choice 1. No soap shown 2. Bar of soap 3. Liquid soap

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Where do members of your household usually defecate? (select more than one option if necessary)

Multiple Choice

1. Bush/undesignated open area 2. Designated open area 3. Hole 4. Pit latrine 5. VIP latrine 6. Other (Specify)

Section 6: Health

90 Is there a child aged 0 – 23 months in this household? (Check your notepad)

Single Choice 1. Yes 2. No

If no, skip to Q99

91 Where was your youngest child born? Single Choice 1. Home 2. Hospital 3. PHCC 4. PHCU 5. During travel 6. Other (Specify)

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92 Did you go anywhere for antenatal care during your last pregnancy?

Single Choice 1. Yes 2. No

If no, skip to Q95

93 Where did you go?

Single choice 1. Traditional Birth Attendant 2. Relative’s home 3. Hospital 4. PHCC 5. PHCU 6. Other (Specify)

94 How many times did you go to (option) for antenatal care during your last pregnancy?

Number Insert option given in Q93

95 During your last pregnancy were you given any iron tablets (show tablets)?

Single Choice 1. Yes 2. No 3. Do not know

If no, skip to Q96

For how long did you take the iron tablets? Single Choice 1. More than 3 months 2. Less than 3 months 3. Do not know

96 Has your youngest child recieved BCG vaccination? (ask to see immunization card if availble)

Single Choice 1. Yes by card 2. Yes by scar 3. No 4. Do not know

97 Has your youngest child recieved DPT 1? (DPT is an injection in the thigh sometimes given at the same time as mouth drops for polio)

Single Choice 1. Yes by card 2. Yes by recall 3. No 4. Do not know

98 Has your youngest child recieved DPT 3? (DPT is an injection in the thigh sometimes given at the same time as mouth drops for polio)

Single Choice 1. Yes by card 2. Yes by recall 3. No 4. Do not know

99 Are you currently using family planning? Single Choice 1. Yes, modern method (depo, implant, pills, condoms) 2. Yes, traditional method (breastfeeding, rhythm method) 3. No 4. Other (Specify)

100 Have you recieved healthcare free of cost during the last 1 Single Choice 1. Yes

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year? 2. No

101 Is any child in your household registered in a nutrition programme like OTP, TSFP, SC?

Single Choice 1. Yes 2. No

If no, skip to Q103

102 In what programme is your child registered? Multiple Choice

1. OTP/SC at health facility 2. Mobile OTP/ATFC 3. TSFP 4. Other (Specify)

103 Did anyone screen your children below 5 years this month?

Single Choice 1. Yes a HHP 2. Yes a CHW or health facility staff 3. No 4. Other (Specify)

104 Have you heard of HIV? Single Choice 1. Yes 2. No

In no, skip to Q106

105 How can you protect yourself from HIV? (record all answers mentioned)

Text

Section 7: Closing section of survey

106 Thank you for your time. [Enumerator - please step outside to finish the survey in order to capture a GPS location.]

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