SMART Survey Report, Idleb Governorate, Syria

Physicians Across Continents-Turkey

August 2017

Contents List of Acronyms ...... 3 Acknowledgements ...... 4 Executive summary ...... 5 1. Introduction ...... 8 2. Survey Objective ...... 8 3. Methodology ...... 9 3.1 Sample size ...... 9 3.2 Sampling procedure: selecting clusters ...... 10 3.3 Sampling procedure: selecting households and children ...... 11 3.4 Case definitions and inclusion criteria ...... 12 3.5 Questionnaire, training and supervision ...... 13 3.6 Data entry and analysis ...... 14 3.7 Characteristic of the sample ...... 14 4. Results ...... 16 4.1 Anthropometric results (based on WHO standards 2006): ...... 16 4.1.1 Prevalence of acute malnutrition based on weight-for-height z-scores ...... 16 4.1.2 Prevalence of acute malnutrition based on MUAC cut offs (and / or edema): .. 18 4.1.3: Prevalence of underweight based on weight-for-age z-score (WAZ) ...... 19 4.1.4: Prevalence of stunting based on height-for-age z-score (HAZ) ...... 20 4.1.5: Prevalence of overweight based on weight for height z-score (HAZ) ...... 21 4.2 Anaemia results: ...... 23 4.3 Separated children result: ...... 23 5. Discussion ...... 24 6. Recommendations and priorities ...... 25 7. Appendices ...... 26

List of Acronyms

CDC Centers for Disease Control and Prevention CCCM Camp Coordination and Camp Management CI Confidence Interval ENA Emergency Nutrition Assessment GAM Global Acute Malnutrition HAZ Height-for-Age Z-Scores HFA Height-for-Age IDP Internally Displaced People IYCF Infant and Young Child Feeding IYCF-E Infant and Young Child Feeding in Emergencies MAM Moderate Acute Malnutrition MUAC Mid-Upper Arm Circumference NGO Non-Governmental Organization NPM Need and Population Monitoring PAC Physicians Across Continents PPS Probability Proportional to Size PSU Primary Sampling Unit RC Reserve Cluster SAM Severe Acute Malnutrition SD Standard Deviation SMART Standardized Monitoring and Assessment of Relief and Transitions WAZ Weight-for-Age Z-Scores WFA Weight-for-Age WFH Weight-for-Height WHO World Health Organization WHZ Weight-for-Height Z-Scores

Acknowledgements

We thank the United Nations Children's Fund (UNICEF) for support and funding for this survey and Physicians Across Continents – Turkey (PAC-Turkey for their planning and implementation

Executive summary

After six years of war and deterioration of Health and nutrition services in Syria, there was a need to determine the nutrition situation. Physicians Across Continents (PAC) in coordination with Nutrition cluster conduct a Standardized Monitoring and Assessment of Relief and Transitions (SMART) survey in Idleb governorate in June 2014. However, after the Survey there were major changes in the situation. There were new accessible areas. These areas had been accessible from Turkey after being under the opposition’s control. There were a huge number of Internally Displaced People (IDPs) coming from other besieged areas (Aleppo, Madaiya, Dariya) and due to these changes, we planned to conduct a new SMART survey in Idleb governorate to determine the current nutrition status.

Idleb governorate is located in north of Syria and contains Host community and IDPs, most of them are Muslim, This survey was conducted between 10 to14 July 2017. Thirty clusters from Idleb governorate had been surveyed. These clusters has been selected randomly to represent all Idleb communities. Need and Population Monitoring (NPM) and CCCM data was used to estimate the population size. After we selected the clusters we used Simple or Systematic random sampling methods to select the Households in each cluster.

The main objective of the survey was to determine the Global Acute Malnutrition (GAM) prevalence in Idleb governorate.578 children 6 – 59 month from 411 Household (HH) were included in the survey. All selected clusters had been visited and no reserved cluster had been used. Table 1 below summarizes Major nutrition related findings.

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Table 1: Summary of key indicators

Prevalence of acute malnutrition based on weight-height (n) % CI z-scores1 Prevalence of global acute malnutrition 12 2.2 1.2- 4.2 95% C.I. (WFH <-2 z-score and/or edema) Prevalence of moderate acute malnutrition 10 1.7 0.8 – 3.6 95% C.I. (WFH <-2 z-score and >=-3 z-score, no edema) Prevalence of severe acute malnutrition 3 0.5 0.2 – 1.6 95% C.I. (WFH <-3 z-score and/or edema) Prevalence of acute malnutrition based on MUAC

Prevalence of global malnutrition (< 125 mm and/or oedema) 11 1.9 0.8 – 4.6 95% C.I.

Prevalence of moderate malnutrition 9 1.6 0.6 – 3.8 95% C.I. (< 125 mm and >= 115 mm, no oedema)

Prevalence of severe malnutrition (< 115 mm and/or oedema) 2 0.3 0.1 – 1.5 95% C.I.

Prevalence of underweight based on weight-for-age z- scores1 Prevalence of underweight (WFA <-2 z-score) 38 6.6 3.9 – 10.9 95% C.I. Prevalence of moderate underweight 26 4.5 2.7 – 7.4 95% C.I. (WFA <-2 z-score and >=-3 z-score) Prevalence of severe underweight (WFA <-3 z-score) 12 2.1 0.9 – 4.8 95% C.I. Prevalence of stunting based on height-for-age z-scores1

Prevalence of stunting (HFA <-2 z-score) 82 14.2 10.2 – 19.5 95% C.I.

Prevalence of moderate stunting 54 9.4 6.6 – 13.1 95% C.I. (HFA <-2 z-score and >=-3 z-score) Prevalence of severe stunting (HFA <-3 z-score) 28 4.9 2.6 – 8.9 95% C.I. Prevalence of overweight based on weight for height cut- offs1

Prevalence of overweight (WHZ > 2) 9 1.6 0.8 – 2.9 95% C.I.

Prevalence of severe overweight (WHZ > 3) 3 0.5 0.2 – 1.6 95% C.I.

1 Based on WHO Child Growth Standards (2006)

The prevalence of anaemia was 35.29 %, all of them were moderate cases with no cases of severe anaemia (table 3.14)

Table 4.14: HGB level of surveyed children Indicator All Boys Girls n = 578 n = 296 n = 282 Normal (374) (184) (190) (HGB > 12 mg/dl) 64.71 % 62.16 % 67.37 % moderate anaemia (204) (112) (92) (HGB < 12 and > 7 mg/dl) 35.29 % 37.84 % 32.63 % severe anaemia (0) (0) (0) (HGB < 7 mg/dl) 0 % 0 % 0 %

1. Introduction

The survey had been conducted in Idleb governorate in Syria. Idleb Governorate has 5 Districts which is further divided in to 25 sub Districts. Idleb has a total population of 1,895,676. IDPS leave in a mixed settlement with the host community. The majority of the population are Muslim Sunni. The population of Idleb are mainly dependant on agriculture with some pastoralist community. The survey was conducted in all communities of Idleb governorate. With the exception of Kafariya and Foaa Communities. These two communities were not accessible). A total of 739 Communities and camps were included in the sampling frame. The communities were mix of urban, rural and camps. Humanitarian assistance: All Communities in Idleb Governorate are accessible. A number of Humanitarian organizations operate in the area. Rural Eastern part of the Governorate has relatively less accessible than the other parts. Health and nutrition services coverage is not uniform with some rural communities having poor access. Access to food and market is good. However, there is some rise in price of food items. (Inflation)

2. Survey Objective

The Overall objective of the SMART assessment was to estimate the current prevalence of acute malnutrition among children 6-59 months of age in Idleb Governorate.

Specific Objectives

• Assess the prevalence of GAM in children 6- 59 months of age in Idleb governorate. • Assess the prevalence of stunting in children 6 – 59 months of age in Idleb governorate. • Assess the prevalence of anaemia in children 6 – 59 months of age in Idleb governorate. • Compare the prevalence of GAM using MUAC and using Weight / Height Z-score to see the sensitivity of MUAC.

3. Methodology

This survey used standard two-stage cluster sampling based on probability proportion to size (PPS). The assessment was conducted following the Standardised Monitoring and Assessment of Relief and Transitions (SMART) methodology, a fast, standardized and simplified method meant to ensure household/everyone in a target population has the same chance of being chosen.

3.1 Sample size

The following assumptions (based on the given context) were used to calculate the sample size. ENA for SMART software July 9th, 2015 version was used for sample size calculation

Parameters for Anthropometry Value Assumptions based on context (footnote any references used) Parameters Idleb Assumption The last SMART survey In Idleb 2014 Showed GAM rate 1.13 % (0.3 Estimated Prevalence of GAM (%) – 2.0 CI 95%) and due to the Waves 4 % of new IDPs from Besieged area came to the area we expect a higher Prevalence Based on SMART recommendations ± Desired precision 3 % for the estimated GAM prevalence (± 3% for estimated prevalence <10%). The design effect chosen for this survey (1.5) was chosen to reflect Design Effect (if applicable) 1.5 potential differences between rural, urban and camp/informal settlements in conflict-affected districts. 268 Children to be included in the survey Average HH Size There is no available data about the 5 HH size in this area and We used 5. This rate had been used in 2014 % Children under-5 15 % SMART survey and we used the same. % Non-response Households 5 % The Non-response rate in the last

Survey in the area was about 3% and we expect a slightly higher rate. 417 Households to be included in the survey

The number of households to be completed per day was determined according to the time the team could spend on the field excluding transportation, other procedures and break times. The details below are taken into consideration when performing this calculation based on the given context 1. Departure from office at 8 am and back at 5pm. 2. Average travel time to reach each cluster (one-way): 1 h. 3. Duration for initial introduction and selection of households: 1.5h. 4. Time spent to move from one household to the next: 5 min. 5. Average time in the household: 15 min. 6. Breaks: One lunch break of 45 min.

The above gives an average of 285 minutes of working time in each cluster. If on average teams will spend 15 minutes in each HH and 5 minutes traveling from one HH to another, each team can comfortably reach 14 HH per day (285/20). One day in each area (cluster) was assumed.

The sample size according to the above calculation was 417 households. To determine the number of clusters to be included in the survey the total number of households in the sample was divided by the number of households to be completed in one day.

Number of cluster=sample size (households)/number of HHs to be completed in a cluster. Number of cluster= 417 HH/ 14 HH per day = 30 clusters

Based on the above calculation, 30 clusters were included in the survey.

3.2 Sampling procedure: selecting clusters

To have a representative sample of whole Idleb governorate we collect all population data of every community in the governorate, all this communities were accessible except two. These community data was secured from Need and Population Monitoring (NPM) which was compiled by International Office of Migration (IOM) and the Camps data from Camp Coordination and Camp Management (CCCM).

The result is representative of the whole governorate Districts (five districts) and whole sub district (25 sub-district), only to communities were inaccessible (Kafariya and Foah)

The population data was put it in on list to generate the sampling frame then transferred to ENA software for SMART and randomly selected 30 clusters and 4 reserve clusters. Clusters have been selected using the PPS (Probability Proportional to size) method. Appendix 2 Shows the sampling frame and the selected clusters.

3.3 Sampling procedure: selecting households and children

Some of the communities selected had bigger population hence have two clusters selected in each (clusters 1, 2) (clusters 16, 17) (clusters 27, 28). Additional information was collected about these big Communities. Segmentation was done using ENA software for SMART. Two segments were selected in this community, which the team l visited. This stage had been done before the fieldwork.

To select Households in each cluster we used Systematic random sampling methods according to cluster size and the availability of HH list or the ability to build a HH list, in some clusters the teams used the segmentation,

Systematic random sampling was used in big clusters, the team count all the HH in the cluster then they calculated the sampling interval and then by using the Random number table selected randomly the first HH to be visited then we selected the following HH by adding the sample interval.

All abandoned HH had been excluded before starting to select the HH, all absent HH had been revisited at the end of the day and if it is still absent the team only put a notice on the cluster control form and they did not replace it.

Also, if there is a child absent in the selected HH, the team revisited the HH at the end of the day and if the child had return they measure the child, if not returned they put a notice on the Cluster control form.

3.4 Case definitions and inclusion criteria

For this survey, all members who live under the same roof and eat from the same spot were considered as a household

All children 6 – 59 month lives in the selected HH were included in the anthropometry survey, all children had a known age and we did not use any other inclusion criteria.

For measuring the length and height, all children under 2 years (6 – 23 month) had been measured laying down (Length) and all children more than 2 years (24 – 59 month) had been measured standing up (Height).

WHO 2006 standards was used to analyze and report the anthropometry data.

Data collected to assess anemia in children 6 – 59 months age. All children 6 – 59 months of age who lives in the selected HH were measured for Hemoglobin (HGB) using Easy life

HB model: ET-123 used to measure the haemoglobin.

The following cut-off is used to assess anemia:

• HGB > 12 mg/dl normal and there is no anemia • HGB between 7 – 11.99 mg/dl there is a moderate anemia, • HGB < 7 mg/dl there is a severe anemia.

Data about separated children was also collected, children who are separated from their father and mother. Question was asked whether the child is living with his father or mother or any other (questionnaire in Appendix 6).

3.5 Questionnaire, training and supervision

Questionnaire:

The questionnaire was prepared in Arabic language and all the interviews were conducted in Arabic language all teams members were Arabic speaker. We did not need to do a translation and back-translation for the questionnaire. The questionnaire had three module, one for anthropometric measurement, one for HGB, and the other one for separated children (Appendix 6)

Survey teams and supervision:

Twenty-seven participants attended enumerators training. Only 18 of them were selected for data collection. Two supervisors were used to ensure data quality. A total of six team were involved in the data collection. Each team consisted of 3 members, one team leader, one measurer and one assistant. All enumerators were community health workers who had nutrition background. Two supervisors were employed to supervise the data collection. Each supervisor was responsible for three teams, and each day of field work the supervisor would make sure that the data collected is of good quality.

Training:

A face to face training of the enumerators was conducted at the PAC training center in Qah-Idleb for 6 days. 27 trainees attended the training. (5 male and 22 female)

The training covered the following topics:

• General survey objectives, • overview of survey design, • Household selection procedures, • Anthropometric measurements, • Signs and symptoms of malnutrition, • Data collection and interview skills, • How to fill the questionnaire and other format, • Determining age of a child, • Measuring HGB)

On the last day of the training, a standardization test was conducted. The supervisors measured 10 different children between 6 – 59 month twice for Weight, Length or Height and MUAC. Then each team also measured the 10 children twice. The measurements were entered to the ENA software and analysed. Field test (pilot test) was done before starting the actual data collection. The pilot test was done in a camp near to Qah, Idleb.

3.6 Data entry and analysis

The collected data had been entered in daily basis, the data had been scanned every day and this scanned files sent to data entry every day. Two data encoders entered the data separately on daily basis. The data has been entered to the ENA software for SMART (Ver of 9 July 2015).The data had been reviewed every day and if there is any feedback in general or for a specific team the survey manger sent these feedbacks before the staring of the next day

To ensure high quality of data entry, at the end of data entry double entry check had been applied correction of any data entry error is corrected accordingly. Data analysis was done after appropriate cleaning of data entry errors. To analyse the data some outliers (extremely Z-scores) had been excluded, we used the WHO flag exclusion criteria.

3.7 Characteristic of the sample

A total of 578 children, 296 boys and 282 girls, aged 6-59 months from 608 households in 30 clusters in Idleb governorate were included in the survey, this total number of children included in the survey exceeded the planned requirement of 418 children (150 %) - Table 2.3. The exact age of 90% of children aged 6-59 months was determined using family card, and an event calendar was used to determine the remaining 10%.

626 (297 boys and 329 girls) were included in the analysis (1 missing weight and height and 1 excluded using WHO flags).

2.1 % of households (N=9) were absent on a first and second visit or refused to collaborate with the survey teams on the day of data collection (table 2.4). . 549 out of 625 surveyed HH were host community (87.84 %) and 4.48 % were IDPs from less than one years and 7.68% were IDPs from more than one year. The total number of 6-59 month children included (observed) in the survey was 578 exceeded the planned requirement of 268 children. The percent of eligible children included in the survey refers to the total number of eligible children (6-59months) that live in the randomly selected households compared to the number of eligible children that were measured total of 98.6% of eligible 6-59 month children were included in the survey.

Table 2.3: Number of planned, included, eligible 6-59 month children

Number Number Number of of of Number of % of eligible % 6-59 month eligible 6-59 children children eligible 6-59 6-59 month children month 6-59 6-59 month children included/planned children months months children included included planned included

267 578 216 % 586 578 98.6%

Table 2.4: Percent of household non-response

Number of HH Number of HH % HH Non-Response planned* surveyed

420 411 2.1 %

4. Results

4.1 Anthropometric results (based on WHO standards 2006):

Anthropometric results (based on WHO standards 2006) Boys and girls were equally represented. The sample sex ratio was 1.0. According to WHO reference population children 6 to 17 month are 23.9% of 6 to 59-month children. Likewise, 18 to 29 are 25.5%, 30 to 41 are 22.4%, 42 to 53 are 19.2% and 54 to 59 are 9%. In the sampled population, the distribution is more or less similar compared to WHO reference. However, the younger age group (6-17 months) is over represented compared to the WHO reference.

Table 4.1: Distribution of age and sex of sample

Boys Girls Total Ratio AGE (mo) no. % no. % no. % Boy: girl 6-17 82 47.4 91 52.6 173 29.9 0.9 18-29 73 51.0 70 49.0 143 24.7 1.0 30-41 63 51.2 60 48.8 123 21.3 1.0 42-53 62 60.2 41 39.8 103 17.8 1.5 54-59 16 44.4 20 55.6 36 6.2 0.8 Total 296 51.2 282 48.8 578 100.0 1.0

4.1.1 Prevalence of acute malnutrition based on weight-for-height z-scores

The prevalence of Global Acute Malnutrition (GAM), defined as Weight-for-height Z scores (WHZ) <‐2 and/or edema was 2.2 % (1.2 - 4.2 95% C.I.) and the prevalence of severe acute malnutrition (SAM), defined as WHZ <‐3 and/or edema, was 0.5 % (0.2 - 1.6 95% C.I.), with no cases of edema found (Table 3.2). There were no statistically difference between the GAM in Boys (1.4 %) and Girls (2.8%) (P=0.348)

The prevalence of acute malnutrition (WHZ<-2 and/or edema) was highest among younger age group (6 – 17 month) (Table 3.2)

Table 4.2: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex

All Boys Girls n = 578 n = 296 n = 282

Prevalence of global malnutrition (13) 2.2 % (4) 1.4 % (9) 3.2 % (1.2 - 4.2 95% (0.5 - 3.5 95% (1.6 - 6.1 95% (<-2 z-score and/or oedema) C.I.) C.I.) C.I.)

Prevalence of moderate malnutrition (10) 1.7 % (3) 1.0 % (7) 2.5 % (0.8 - 3.6 95% (0.3 - 3.1 95% (1.1 - 5.5 95% (<-2 z-score and >=-3 z-score, no C.I.) C.I.) C.I.) oedema)

Prevalence of severe malnutrition (3) 0.5 % (1) 0.3 % (2) 0.7 % (0.2 - 1.6 95% (0.0 - 2.6 95% (0.2 - 2.9 95% (<-3 z-score and/or oedema) C.I.) C.I.) C.I.)

The prevalence of oedema is 0.0 % (No cases had been detected)

Table 4.3: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema

Severe wasting Moderate Normal Oedema (<-3 z-score) wasting (> = -2 z score) (>= -3 and <-2 z-score ) Age Total No. % No. % No. % No. % (mo) no. 6-17 173 1 0.6 5 2.9 167 96.5 0 0.0 18-29 143 0 0.0 0 0.0 143 100.0 0 0.0 30-41 123 1 0.8 2 1.6 120 97.6 0 0.0 42-53 103 0 0.0 1 1.0 102 99.0 0 0.0 54-59 36 1 2.8 2 5.6 33 91.7 0 0.0 Total 578 3 0.5 10 1.7 565 97.8 0 0.0

Table 4.4: Distribution of acute malnutrition and oedema based on weight-for-height z- scores

<-3 z-score >=-3 z-score Oedema present Marasmic kwashiorkor Kwashiorkor No. 0 No. 0 (0.0 %) (0.0 %) Oedema absent Marasmic Not severely malnourished No. 3 No. 575 (0.5 %) (99.5 %)

4.1.2 Prevalence of acute malnutrition based on MUAC cut offs (and / or edema):

The prevalence of global acute malnutrition (GAM) in children 6 – 59 month, defined as MUAC <125 mm was 1.9% (0.8 – 4.6 95% C.I), and the prevalence of severe acute malnutrition (SAM), defined as MUAC < 115 mm was 0.3 % (0.1 – 1.5 95% C.I), No cases of oedema has been found.

Table 4.5: Prevalence of acute malnutrition based on MUAC cut offs (and/or oedema) and by sex

All Boys Girls n = 578 n = 296 n = 282 Prevalence of global malnutrition (11) 1.9 % (6) 2.0 % (5) 1.8 % (< 125 mm and/or oedema) (0.8 - 4.6 95% (0.6 - 6.8 95% (0.6 - 4.9 95% C.I.) C.I.) C.I.) Prevalence of moderate malnutrition (9) 1.6 % (6) 2.0 % (3) 1.1 % (< 125 mm and >= 115 mm, no (0.6 - 3.8 95% (0.6 - 6.8 95% (0.3 - 3.3 95% oedema) C.I.) C.I.) C.I.)

Prevalence of severe malnutrition (2) 0.3 % (0) 0.0 % (2) 0.7 % (< 115 mm and/or oedema) (0.1 - 1.5 95% (0.0 - 0.0 95% (0.2 - 3.0 95% C.I.) C.I.) C.I.)

Table 4.6: Prevalence of acute malnutrition by age, based on MUAC cut off's and/or oedema Severe wasting Moderate Normal Oedema (< 115 mm) wasting (> = 125 mm ) (>= 115 mm and < 125 mm) Age Total No. % No. % No. % No. % (mo) no. 6-17 173 2 1.2 8 4.6 163 94.2 0 0.0 18-29 143 0 0.0 1 0.7 142 99.3 0 0.0 30-41 123 0 0.0 0 0.0 123 100.0 0 0.0 42-53 103 0 0.0 0 0.0 103 100.0 0 0.0 54-59 36 0 0.0 0 0.0 36 100.0 0 0.0 Total 578 2 0.3 9 1.6 567 98.1 0 0.0

4.1.3: Prevalence of underweight based on weight-for-age z-score (WAZ)

The prevalence of underweight in children 6-59 months, defined as weight- for-age Z scores (WAZ) <‐2 was 6.6 % (3.9 – 10.9 95% C.I.) with 2.1 % (0.9 - 4.8 95% C.I.) severely underweight, defined as Weight-for-Age Z scores (WAZ) <‐3 (Table 3.7). A higher prevalence of underweight by age group was observed among the age group (30 -41 months) (9.9%) (Table 3.8).

Table 4.7: Prevalence of underweight based on weight-for-age z-scores by sex

All Boys Girls n = 577 n = 296 n = 281 Prevalence of underweight (38) 6.6 % (19) 6.4 % (19) 6.8 % (<-2 z-score) (3.9 - 10.9 95% (3.4 - 11.8 95% (3.7 - 12.0 95% C.I.) C.I.) C.I.) Prevalence of moderate (26) 4.5 % (14) 4.7 % (12) 4.3 % underweight (2.7 - 7.4 95% (2.3 - 9.4 95% (2.4 - 7.5 95% (<-2 z-score and >=-3 z-score) C.I.) C.I.) C.I.) Prevalence of severe (12) 2.1 % (5) 1.7 % (7) 2.5 % underweight (0.9 - 4.8 95% (0.6 - 4.7 95% (1.0 - 5.9 95% (<-3 z-score) C.I.) C.I.) C.I.)

Table 4.8: Prevalence of underweight by age, based on weight-for-age z-scores

Severe Moderate Normal Oedema underweight underweight (> = -2 z score) (<-3 z-score) (>= -3 and <-2 z-score ) Age Total No. % No. % No. % No. % (mo) no. 6-17 172 2 1.2 8 4.7 162 94.2 0 0.0 18-29 143 1 0.7 9 6.3 133 93.0 0 0.0 30-41 123 5 4.1 6 4.9 112 91.1 0 0.0 42-53 103 2 1.9 3 2.9 98 95.1 0 0.0 54-59 36 2 5.6 0 0.0 34 94.4 0 0.0 Total 577 12 2.1 26 4.5 539 93.4 0 0.0

4.1.4: Prevalence of stunting based on height-for-age z-score (HAZ)

The prevalence of stunting, defined as Height-for-age Z scores (HAZ) <‐2 in children 6-59 months was 14.2 % (10.2 – 19.5 95% C.I.). Meanwhile 4.9 % (2.6 – 8.9 95% C.I.) children severely stunted, defined as height-for-age Z scores (HAZ) <‐3 (Table 4.9).The difference between boys (13.6%) and girls (14.9%) was not statistically significant (p=0.720).Stunting peaked amongst the age group of 30-41 months (22.8%) (Table 4.10).

Table 4.9: Prevalence of stunting based on height-for-age z-scores and by sex

All Boys Girls n = 576 n = 295 n = 281 Prevalence of stunting (82) 14.2 % (40) 13.6 % (42) 14.9 % (<-2 z-score) (10.2 - 19.5 95% (9.5 - 19.0 95% (10.1 - 21.6 C.I.) C.I.) 95% C.I.) Prevalence of moderate (54) 9.4 % (28) 9.5 % (26) 9.3 % stunting (6.6 - 13.1 95% (6.3 - 14.1 95% (5.6 - 14.9 95% (<-2 z-score and >=-3 z-score) C.I.) C.I.) C.I.) Prevalence of severe stunting (28) 4.9 % (12) 4.1 % (16) 5.7 % (<-3 z-score) (2.6 - 8.9 95% (1.9 - 8.4 95% (3.1 - 10.3 95% C.I.) C.I.) C.I.)

Table 4.10: Prevalence of stunting by age based on height-for-age z-scores

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

Age Total No. % No. % No. % (mo) no. 6-17 171 4 2.3 10 5.8 157 91.8 18-29 143 9 6.3 14 9.8 120 83.9 30-41 123 9 7.3 19 15.4 95 77.2 42-53 103 5 4.9 10 9.7 88 85.4 54-59 36 1 2.8 1 2.8 34 94.4 Total 576 28 4.9 54 9.4 494 85.8

4.1.5: Prevalence of overweight based on weight for height z-score (HAZ)

The prevalence of overweight, defined as weight-for-height Z scores (WHZ) > 2 in children 6-59 months was 1.6 % (0.8 – 2.9 95% C.I.), with 0.5 % (0.2 – 1.6 95% C.I.) of a severely overweight, defined as weight-for-height Z scores (WHZ) > 3 (Table 4.11). Prevalence of overweight by age group (Table 4.12).

Table 4.11: Prevalence of overweight based on weight for height cut off's and by sex (no oedema)

All Boys Girls n = 578 n = 296 n = 282 Prevalence of overweight (WHZ > (9) 1.6 % (4) 1.4 % (5) 1.8 % 2) (0.8 - 2.9 95% (0.5 - 3.4 95% (0.8 - 4.0 95% C.I.) C.I.) C.I.) Prevalence of severe overweight (3) 0.5 % (2) 0.7 % (1) 0.4 % (WHZ > 3) (0.2 - 1.6 95% (0.2 - 2.7 95% (0.0 - 2.7 95% C.I.) C.I.) C.I.)

Table 4.12: Prevalence of overweight by age, based on weight for height (no oedema)

Overweight Severe Overweight (WHZ (WHZ > 2) > 3)

Age (mo) Total no. No. % No. %

6-17 173 5 2.9 2 1.2

18-29 143 4 2.8 1 0.7

30-41 123 0 0.0 0 0.0

42-53 103 0 0.0 0 0.0

54-59 36 0 0.0 0 0.0

Total 578 9 1.6 3 0.5

Table 4.13: Mean z-scores, Design Effects and excluded subjects2

Indicator n Mean z- Design Effect z-scores not z-scores out scores ± SD (z-score < -2) available* of range

Weight-for-Height 578 0.02±0.97 1.26 0 0

Weight-for-Age 577 -0.48±1.03 2.55 0 1

Height-for-Age 576 -0.93±1.16 2.44 0 2 * contains for WHZ and WAZ the children with oedema.

2 WHO flags used

4.2 Anaemia results:

The HGB of children 6 to 59 months old children had been measured using (Easy life HB model: ET-123), the following case definition is used: HGB > 12 mg/dl  Normal HGB < 12 and > 7 mg/dl  moderate anaemia HGB < 7 mg/dl  severe anaemia

4.3 Separated children result:

Data about children were collected to assess if children are living separated from their parents. Questions were asked about all the children if they are living with their mother or father. If the response is no, a follow up question was asked about the relation between the HH head and the child. 552 child of 570 (96.84%) are living with their parents, and 3.16 % are separated from their parents, 2.63% live with their grandfathers, 0.53% live with their uncles.

5. Discussion

Age ratio of 6-29 months to 30-59 months: 1.21, which means that There were more young children than older children, this finding was observed in most surveys done in Syria (Hama 2015 =1.1 , Eastern Ghouta 2016 = 1.32).

The prevalence of GAM compared to last SMART survey done in Idleb 2014 shows that the prevalence still at low level and there is no big difference between the two results. The prevalence of acute malnutrition is still low in Idleb after 6 year of conflict. This might be an indicative of good food security status of the community. The highest prevalence of global acute malnutrition was among younger children, which might indicate poor IYCF-E practices, especially exclusive breastfeeding and complementary feeding.

The GAM rate using the WHZ and using the MUAC showed a proximately the same rate, which means that the sensitivity of MUAC can be high and can be used alone to determine the GAM rate in emergencies if the data collected is of good quality.

The stunting prevalence was 14.2 %, this result shows some improvement in the stunting rate compared to the result found in Idleb 2014 survey which was 22.9%. The high prevalence of anemia (35.3%) indicates that there is a high level of micronutrient deficiency.

6. Recommendations and priorities

• There is need for close follow up of the nutrition status of children 6 to 59 months of age.

• Even though the stunting has reduced since 2014, projects focusing on prevention of stunting should be strengthened. This includes infant and young child feeding projects.

• The prevalence of anaemia is very high. Micro nutrient supplement and awareness creation about prevention of anaemia should be focus of projects implemented in the area.

• Child protection projects focusing on family tracing and reunification should be considered.

• In emergency context in the area MUAC can be used as a sensitive indicator of acute malnutrition

7. Appendices

Appendix 1

Plausibility Report Plausibility check for: Final Data Idleb.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

Flagged data Incl % 0-2.5 >2.5-5.0 >5.0-7.5 >7.5 (% of out of range subjects) 0 5 10 20 0 (1.0 %)

Overall Sex ratio Incl p >0.1 >0.05 >0.001 <=0.001 (Significant chi square) 0 2 4 10 0 (p=0.560)

Age ratio(6-29 vs 30-59) Incl p >0.1 >0.05 >0.001 <=0.001 (Significant chi square) 0 2 4 10 10 (p=0.000)

Dig pref score - weight Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (7)

Dig pref score - height Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (7)

Dig pref score - MUAC Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (7)

Standard Dev WHZ Excl SD <1.1 <1.15 <1.20 >=1.20 . and and and or . Excl SD >0.9 >0.85 >0.80 <=0.80 0 5 10 20 5 (0.89)

Skewness WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 1 (-0.27)

Kurtosis WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 3 (0.51)

Poisson dist WHZ-2 Excl p >0.05 >0.01 >0.001 <=0.001 0 1 3 5 0 (p=0.122)

OVERALL SCORE WHZ = 0-9 10-14 15-24 >25 19 %

The overall score of this survey is 19 %, this is acceptable.

There were no duplicate entries detected.

Percentage of children with no exact birthday: 39 %

Anthropometric Indices likely to be in error (-3 to 3 for WHZ, -3 to 3 for HAZ, -3 to 3 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=8/ID=8: WHZ (-4.744), WAZ (-3.596), Weight may be incorrect Line=18/ID=18: WHZ (3.034), Weight may be incorrect Line=23/ID=23: HAZ (3.172), Age may be incorrect Line=51/ID=2: HAZ (-5.919), WAZ (-4.029), Age may be incorrect Line=54/ID=5: HAZ (-4.671), Age may be incorrect Line=57/ID=8: HAZ (-4.449), WAZ (-3.668), Age may be incorrect Line=58/ID=9: HAZ (-4.554), Age may be incorrect Line=91/ID=1: WAZ (2.635), Weight may be incorrect Line=127/ID=14: HAZ (2.336), Age may be incorrect Line=142/ID=9: WHZ (3.117), Weight may be incorrect Line=209/ID=9: HAZ (-4.222), Age may be incorrect Line=211/ID=11: HAZ (-4.279), Age may be incorrect Line=216/ID=16: HAZ (-4.691), Age may be incorrect Line=217/ID=17: WHZ (-4.086), HAZ (-5.887), WAZ (-5.508) Line=279/ID=9: HAZ (-4.392), Age may be incorrect Line=281/ID=11: HAZ (8.491), WAZ (4.104), Age may be incorrect Line=293/ID=6: WAZ (-3.583), Weight may be incorrect Line=333/ID=16: HAZ (4.327), Age may be incorrect Line=371/ID=5: WHZ (4.435), WAZ (3.112), Weight may be incorrect Line=463/ID=7: HAZ (2.539), Age may be incorrect Line=479/ID=9: HAZ (3.733), Age may be incorrect Line=577/ID=18: WHZ (-3.113), HAZ (-6.983), WAZ (-6.264)

Percentage of values flagged with SMART flags:WHZ: 1.0 %, HAZ: 2.8 %, WAZ: 1.6 %

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 : ################ 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 : ###### Month 60 : #

Age ratio of 6-29 months to 30-59 months: 1.21 (The value should be around 0.85).: p-value = 0.000 (significant difference)

Statistical evaluation of sex and age ratios (using Chi squared statistic):

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 82/68.7 (1.2) 91/65.4 (1.4) 173/134.1 (1.3) 0.90 18 to 29 12 73/67.0 (1.1) 70/63.8 (1.1) 143/130.8 (1.1) 1.04 30 to 41 12 63/64.9 (1.0) 60/61.8 (1.0) 123/126.7 (1.0) 1.05 42 to 53 12 62/63.9 (1.0) 41/60.8 (0.7) 103/124.7 (0.8) 1.51 54 to 59 6 16/31.6 (0.5) 20/30.1 (0.7) 36/61.7 (0.6) 0.80 ------6 to 59 54 296/289.0 (1.0) 282/289.0 (1.0) 1.05

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.560 (boys and girls equally represented) Overall age distribution: p-value = 0.000 (significant difference) Overall age distribution for boys: p-value = 0.027 (significant difference) Overall age distribution for girls: p-value = 0.000 (significant difference) 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: 7 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.001 (significant difference)

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: 7 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.007 (significant difference) 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: 7 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.001 (significant difference)

Evaluation of Standard deviation, Normal distribution, Skewness and Kurtosis using the 3 exclusion (Flag) procedures

. no exclusion exclusion from exclusion from . reference mean observed mean . (WHO flags) (SMART flags) WHZ Standard Deviation SD: 0.97 0.97 0.89 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: calculated with current SD: calculated with a SD of 1:

HAZ Standard Deviation SD: 1.25 1.16 0.99 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 14.4% 14.2% calculated with current SD: 19.6% 18.0% calculated with a SD of 1: 14.2% 14.3%

WAZ Standard Deviation SD: 1.05 1.03 0.94 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 6.7% 6.6% calculated with current SD: 7.7% 7.0% calculated with a SD of 1: 6.6% 6.5%

Results for Shapiro-Wilk test for normally (Gaussian) distributed data: WHZ p= 0.000 p= 0.000 p= 0.007 HAZ p= 0.000 p= 0.000 p= 0.000 WAZ p= 0.000 p= 0.000 p= 0.000 (If p < 0.05 then the data are not normally distributed. If p > 0.05 you can consider the data normally distributed)

Skewness WHZ -0.33 -0.33 -0.27 HAZ 0.35 -0.23 -0.15 WAZ -0.56 -0.33 -0.28 If the value is: -below minus 0.4 there is a relative excess of wasted/stunted/underweight subjects in the sample -between minus 0.4 and minus 0.2, there may be a relative excess of wasted/stunted/underweight subjects in the sample. -between minus 0.2 and plus 0.2, the distribution can be considered as symmetrical. -between 0.2 and 0.4, there may be an excess of obese/tall/overweight subjects in the sample. -above 0.4, there is an excess of obese/tall/overweight subjects in the sample

Kurtosis WHZ 2.40 2.40 0.51 HAZ 7.80 2.68 0.41

WAZ 3.31 2.29 0.67 Kurtosis characterizes the relative size of the body versus the tails of the distribution. Positive kurtosis indicates relatively large tails and small body. Negative kurtosis indicates relatively large body and small tails. If the absolute value is: -above 0.4 it indicates a problem. There might have been a problem with data collection or sampling. -between 0.2 and 0.4, the data may be affected with a problem. -less than an absolute value of 0.2 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=1.31 (p=0.122) GAM: ID=1.31 (p=0.122) HAZ < -2: ID=1.80 (p=0.005) HAZ < -3: ID=1.47 (p=0.050) WAZ < -2: ID=1.97 (p=0.001) WAZ < -3: ID=1.68 (p=0.012)

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: 1.07 (n=30, f=0) ########### 02: 0.85 (n=30, f=0) ## 03: 1.08 (n=30, f=0) ############ 04: 0.81 (n=30, f=0) 05: 1.28 (n=30, f=1) #################### 06: 1.04 (n=30, f=0) ########## 07: 0.84 (n=30, f=0) ## 08: 1.29 (n=30, f=1) ##################### 09: 1.01 (n=30, f=1) ######### 10: 0.82 (n=30, f=0) # 11: 0.91 (n=30, f=0) #### 12: 0.80 (n=29, f=0) 13: 0.98 (n=29, f=0) ######## 14: 0.92 (n=28, f=1) ##### 15: 0.81 (n=27, f=0) 16: 0.82 (n=25, f=0) # 17: 1.19 (n=22, f=1) ################# 18: 0.93 (n=17, f=1) ##### 19: 0.67 (n=15, f=0) 20: 0.79 (n=13, f=0) 21: 0.83 (n=11, f=0) O 22: 1.09 (n=11, f=0) OOOOOOOOOOOO 23: 1.04 (n=08, f=0) OOOOOOOOOO 24: 0.73 (n=04, f=0) 25: 0.79 (n=03, f=0) 26: 0.23 (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 3 6 7 8 9 n = 97 82 124 98 97 80 Percentage of values flagged with SMART flags: WHZ: 1.0 1.2 0.0 3.1 1.0 0.0 HAZ: 8.2 2.4 0.8 3.1 2.1 0.0 WAZ: 3.1 0.0 1.6 2.0 2.1 0.0 Age ratio of 6-29 months to 30-59 months: 1.37 1.22 1.21 1.04 1.20 1.22 Sex ratio (male/female): 0.87 1.34 1.14 1.13 0.90 1.00 Digit preference Weight (%): .0 : 5 1 9 6 3 10 .1 : 19 16 10 10 9 14 .2 : 7 13 14 10 12 13 .3 : 8 12 11 9 11 13 .4 : 15 11 10 10 15 9 .5 : 7 4 6 9 8 6 .6 : 11 13 9 8 10 11 .7 : 10 11 15 12 9 13 .8 : 8 9 9 9 10 6 .9 : 8 10 6 15 10 6 DPS: 13 14 9 8 10 9 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference Height (%): .0 : 2 0 19 8 6 11 .1 : 8 10 11 14 11 11 .2 : 20 13 16 8 10 14 .3 : 14 9 9 13 10 10 .4 : 11 12 10 15 13 11 .5 : 8 4 13 6 5 8 .6 : 11 13 5 11 8 11 .7 : 10 10 4 11 11 11 .8 : 3 15 6 3 11 4 .9 : 11 15 7 9 12 9 DPS: 16 15 16 12 8 9 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference MUAC (%): .0 : 1 2 13 5 3 5 .1 : 8 15 7 14 12 13 .2 : 8 12 9 8 18 8 .3 : 12 9 8 9 15 8 .4 : 19 16 14 8 7 15 .5 : 6 1 9 10 6 9 .6 : 19 12 8 13 8 15 .7 : 6 10 15 9 8 8

.8 : 8 10 10 12 12 9 .9 : 12 13 8 10 9 13 DPS: 18 15 8 9 14 11 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Standard deviation of WHZ: SD 1.01 0.93 0.97 0.95 0.76 1.02 Prevalence (< -2) observed: % 6.2 2.5 Prevalence (< -2) calculated with current SD: % 5.8 3.0 Prevalence (< -2) calculated with a SD of 1: % 5.7 2.7 Standard deviation of HAZ: SD 1.52 1.09 1.13 1.27 1.18 1.08 observed: % 32.0 7.3 16.1 14.3 4.1 10.0 calculated with current SD: % 38.1 11.1 16.2 18.5 16.3 11.4 calculated with a SD of 1: % 32.3 9.2 13.3 12.8 12.3 9.6

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 15/10.4 (1.4) 17/12.1 (1.4) 32/22.5 (1.4) 0.88 18 to 29 12 12/10.2 (1.2) 12/11.8 (1.0) 24/21.9 (1.1) 1.00 30 to 41 12 11/9.9 (1.1) 16/11.4 (1.4) 27/21.3 (1.3) 0.69 42 to 53 12 7/9.7 (0.7) 6/11.2 (0.5) 13/20.9 (0.6) 1.17 54 to 59 6 0/4.8 (0.0) 1/5.5 (0.2) 1/10.4 (0.1) 0.00 ------6 to 59 54 45/48.5 (0.9) 52/48.5 (1.1) 0.87

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.477 (boys and girls equally represented) Overall age distribution: p-value = 0.002 (significant difference) Overall age distribution for boys: p-value = 0.091 (as expected) Overall age distribution for girls: p-value = 0.040 (significant difference) Overall sex/age distribution: p-value = 0.001 (significant difference)

Team 2:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 12/10.9 (1.1) 11/8.1 (1.4) 23/19.0 (1.2) 1.09 18 to 29 12 14/10.6 (1.3) 8/7.9 (1.0) 22/18.5 (1.2) 1.75 30 to 41 12 8/10.3 (0.8) 8/7.7 (1.0) 16/18.0 (0.9) 1.00 42 to 53 12 11/10.1 (1.1) 7/7.6 (0.9) 18/17.7 (1.0) 1.57 54 to 59 6 2/5.0 (0.4) 1/3.7 (0.3) 3/8.8 (0.3) 2.00 ------6 to 59 54 47/41.0 (1.1) 35/41.0 (0.9) 1.34

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.185 (boys and girls equally represented) Overall age distribution: p-value = 0.242 (as expected) Overall age distribution for boys: p-value = 0.466 (as expected) Overall age distribution for girls: p-value = 0.545 (as expected) Overall sex/age distribution: p-value = 0.075 (as expected)

Team 3:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 20/15.3 (1.3) 18/13.5 (1.3) 38/28.8 (1.3) 1.11 18 to 29 12 15/14.9 (1.0) 15/13.1 (1.1) 30/28.1 (1.1) 1.00 30 to 41 12 14/14.5 (1.0) 8/12.7 (0.6) 22/27.2 (0.8) 1.75 42 to 53 12 13/14.2 (0.9) 11/12.5 (0.9) 24/26.8 (0.9) 1.18 54 to 59 6 4/7.0 (0.6) 6/6.2 (1.0) 10/13.2 (0.8) 0.67 ------6 to 59 54 66/62.0 (1.1) 58/62.0 (0.9) 1.14

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.473 (boys and girls equally represented) Overall age distribution: p-value = 0.271 (as expected) Overall age distribution for boys: p-value = 0.579 (as expected) Overall age distribution for girls: p-value = 0.442 (as expected) Overall sex/age distribution: p-value = 0.132 (as expected)

Team 4:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 13/12.1 (1.1) 17/10.7 (1.6) 30/22.7 (1.3) 0.76 18 to 29 12 9/11.8 (0.8) 11/10.4 (1.1) 20/22.2 (0.9) 0.82 30 to 41 12 13/11.4 (1.1) 10/10.1 (1.0) 23/21.5 (1.1) 1.30 42 to 53 12 16/11.2 (1.4) 4/9.9 (0.4) 20/21.1 (0.9) 4.00 54 to 59 6 1/5.5 (0.2) 4/4.9 (0.8) 5/10.5 (0.5) 0.25 ------6 to 59 54 52/49.0 (1.1) 46/49.0 (0.9) 1.13

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.544 (boys and girls equally represented) Overall age distribution: p-value = 0.235 (as expected) Overall age distribution for boys: p-value = 0.152 (as expected) Overall age distribution for girls: p-value = 0.112 (as expected) Overall sex/age distribution: p-value = 0.006 (significant difference)

Team 5:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 13/10.7 (1.2) 13/11.8 (1.1) 26/22.5 (1.2) 1.00 18 to 29 12 13/10.4 (1.2) 14/11.5 (1.2) 27/21.9 (1.2) 0.93 30 to 41 12 7/10.1 (0.7) 11/11.2 (1.0) 18/21.3 (0.8) 0.64 42 to 53 12 7/9.9 (0.7) 8/11.0 (0.7) 15/20.9 (0.7) 0.88 54 to 59 6 6/4.9 (1.2) 5/5.4 (0.9) 11/10.4 (1.1) 1.20 ------6 to 59 54 46/48.5 (0.9) 51/48.5 (1.1) 0.90

The data are expressed as observed number/expected number (ratio of obs/expect)

Overall sex ratio: p-value = 0.612 (boys and girls equally represented) Overall age distribution: p-value = 0.415 (as expected) Overall age distribution for boys: p-value = 0.524 (as expected) Overall age distribution for girls: p-value = 0.827 (as expected) Overall sex/age distribution: p-value = 0.301 (as expected)

Team 6:

Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 9/9.3 (1.0) 15/9.3 (1.6) 24/18.6 (1.3) 0.60 18 to 29 12 10/9.0 (1.1) 10/9.0 (1.1) 20/18.1 (1.1) 1.00 30 to 41 12 10/8.8 (1.1) 7/8.8 (0.8) 17/17.5 (1.0) 1.43 42 to 53 12 8/8.6 (0.9) 5/8.6 (0.6) 13/17.3 (0.8) 1.60 54 to 59 6 3/4.3 (0.7) 3/4.3 (0.7) 6/8.5 (0.7) 1.00 ------6 to 59 54 40/40.0 (1.0) 40/40.0 (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 = 0.460 (as expected) Overall age distribution for boys: p-value = 0.951 (as expected) Overall age distribution for girls: p-value = 0.208 (as expected) Overall sex/age distribution: p-value = 0.159 (as expected)

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: 1.17 (n=05, f=0) ############### 02: 0.93 (n=05, f=0) ###### 03: 0.88 (n=05, f=0) ### 04: 1.46 (n=05, f=0) ############################ 05: 1.27 (n=05, f=0) #################### 06: 0.97 (n=05, f=0) ####### 07: 1.54 (n=05, f=0) ############################### 08: 0.91 (n=05, f=0) ##### 09: 0.60 (n=05, f=0) 10: 0.86 (n=05, f=0) ### 11: 0.98 (n=05, f=0) ######## 12: 0.48 (n=05, f=0) 13: 1.03 (n=05, f=0) ########## 14: 0.85 (n=05, f=0) ## 15: 1.04 (n=05, f=0) ########## 16: 0.74 (n=05, f=0)

17: 1.42 (n=04, f=1) ########################## 18: 0.57 (n=03, f=0) 19: 1.20 (n=02, f=0) OOOOOOOOOOOOOOOOO 20: 0.12 (n=02, f=0) 21: 0.09 (n=02, f=0) 22: 0.90 (n=02, f=0) OOOO 23: 0.60 (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

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: 0.77 (n=05, f=0) 02: 1.02 (n=05, f=0) ######### 03: 0.66 (n=05, f=0) 04: 0.98 (n=05, f=0) ######## 05: 0.80 (n=05, f=0) 06: 0.73 (n=05, f=0) 07: 0.66 (n=05, f=0) 08: 1.78 (n=05, f=0) ######################################### 09: 1.90 (n=05, f=1) ############################################## 10: 1.13 (n=05, f=0) ############## 11: 0.28 (n=05, f=0) 12: 0.63 (n=04, f=0) 13: 0.42 (n=04, f=0) 14: 0.76 (n=04, f=0) 15: 1.04 (n=04, f=0) ########## 16: 0.65 (n=03, f=0) 17: 0.33 (n=03, f=0) 18: 0.11 (n=02, f=0) 19: 0.44 (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: 0.99 (n=05, f=0) ######## 02: 0.85 (n=05, f=0) ## 03: 1.28 (n=05, f=0) #################### 04: 0.64 (n=05, f=0) 05: 0.62 (n=05, f=0) 06: 1.70 (n=05, f=0) ###################################### 07: 0.53 (n=05, f=0) 08: 0.99 (n=05, f=0) ######## 09: 0.78 (n=05, f=0) 10: 0.84 (n=05, f=0) ## 11: 0.87 (n=05, f=0) ### 12: 0.97 (n=05, f=0) ####### 13: 1.28 (n=05, f=0) #################### 14: 0.49 (n=05, f=0) 15: 0.96 (n=05, f=0) ####### 16: 0.80 (n=05, f=0) 17: 1.09 (n=05, f=0) ############ 18: 0.68 (n=05, f=0) 19: 0.58 (n=05, f=0) 20: 1.10 (n=05, f=0) ############# 21: 1.19 (n=05, f=0) ################ 22: 1.45 (n=05, f=0) ########################### 23: 1.11 (n=04, f=0) ############# 24: 0.33 (n=03, f=0) 25: 0.93 (n=02, f=0) OOOOOO

(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: 1.08 (n=05, f=0) ############ 02: 0.81 (n=05, f=0) 03: 0.75 (n=05, f=0) 04: 0.68 (n=05, f=0) 05: 0.64 (n=05, f=0) 06: 0.73 (n=05, f=0) 07: 0.80 (n=05, f=0) 08: 2.11 (n=05, f=1) ####################################################### 09: 0.71 (n=05, f=0) 10: 0.34 (n=05, f=0) 11: 0.56 (n=05, f=0) 12: 0.57 (n=05, f=0) 13: 1.02 (n=05, f=0) ######### 14: 1.73 (n=05, f=1) ####################################### 15: 0.69 (n=05, f=0) 16: 0.86 (n=04, f=0) ### 17: 0.41 (n=04, f=0) 18: 2.06 (n=02, f=0) OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO 19: 0.29 (n=02, f=0) 20: 0.08 (n=02, f=0) 21: 0.65 (n=02, f=0) 22: 0.07 (n=02, f=0) 23: 0.30 (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: 0.24 (n=05, f=0) 02: 0.48 (n=05, f=0) 03: 1.56 (n=05, f=0) ################################ 04: 0.34 (n=05, f=0) 05: 2.02 (n=05, f=1) ################################################### 06: 0.72 (n=05, f=0) 07: 0.52 (n=05, f=0) 08: 0.67 (n=05, f=0) 09: 0.48 (n=05, f=0) 10: 0.39 (n=05, f=0) 11: 0.47 (n=05, f=0) 12: 0.34 (n=05, f=0) 13: 0.23 (n=05, f=0) 14: 0.32 (n=05, f=0) 15: 0.37 (n=05, f=0) 16: 0.78 (n=05, f=0) 17: 0.70 (n=04, f=0) 18: 0.50 (n=03, f=0) 19: 0.45 (n=03, f=0) 20: 0.69 (n=03, f=0) 21: 0.18 (n=02, f=0) 22: 0.92 (n=02, f=0) OOOOO

(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: 6

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=05, f=0) 02: 0.99 (n=05, f=0) ######## 03: 1.35 (n=05, f=0) ####################### 04: 0.52 (n=05, f=0) 05: 1.55 (n=05, f=0) ############################### 06: 0.75 (n=05, f=0) 07: 0.64 (n=05, f=0) 08: 0.51 (n=05, f=0) 09: 0.82 (n=05, f=0) # 10: 1.00 (n=05, f=0) ########

11: 1.43 (n=05, f=0) ########################## 12: 1.42 (n=05, f=0) ########################## 13: 1.11 (n=05, f=0) ############# 14: 1.08 (n=04, f=0) ############ 15: 0.78 (n=03, f=0) 16: 0.70 (n=03, f=0) 17: 0.78 (n=02, f=0) 18: 0.70 (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)

Appendix 2

Assignment of Clusters

Geographical unit Population size Assigned cluster

Aqrabat C3866 962 Nayrab C3867 5026 Ein Shib C3868 2436 Kreiz C3869 1929 Tab Issa - Eastern And Western C3870 672 Idlep City C3871 116390 1,2 Mastumeh C3872 4149 Sijer - Bqesemtoh C3873 3517 Northern Ora C3874 1414 Arshani C3875 1061 Qminas C3876 3423 Falyun C3877 6398 Martein C3878 2180 Kafruhin C3879 2958 Busra - Little Zafar C3880 440 Ballisa C3881 1821 Big Zafar C3882 640 Talkhatra C3883 1001 Barissa C3884 522 Tweim C3885 196 Harmala C3886 920 Jdidhe Abu Elthohur C3887 980 Taljineh C3888 749 Tawahineh C3889 634 Jallas C3890 1439 Abul Thohur C3891 7151 RC Tal Fukhar C3892 1127 Baragethi C3893 1806 Mustariha C3894 438

Rasm Abed C3895 2454 Tawil Elsheikh C3896 518 Hseiniyeh - Tal Kalba C3897 3168 Tal Sultan C3898 3088 Tal Silmo C3899 1278 Hmeimat Eldayer C3900 1457 Tal Elaghar C3901 907 Ras El Ein C3902 2797 Tal Tufan C3903 5404 Msheirfeh C6362 385 Sukariyeh C6623 179 Shkheir C6624 504 Debshieh C6625 644 Jdideh C6626 343 Wasita C6627 210 Rasm Nayyas C6628 200 Thahabiyeh C6629 343 Bennsh C3904 11201 Toum C3906 2713 Anqrati C3907 895 Tromba C3908 2763 Jobas C3909 3858 Dadikh C3910 3637 Bweiti C3911 1362 3 Bijfas C3912 975 Salamin C3913 2098 Abul Khos C3914 1886 San C3915 1759 Saraqab C3916 14559 Tal Karatine C3918 2743 Rayan C3919 3682 Afs C3920 10236 Ajez C3921 1572 Khuwara C3922 1897 Rasafa C3923 3161

Sheikh Idris C3924 6923 Khan Elsobol C3925 8865 4 Maharim C3926 2351 Kafr Battikh C3927 5641 Kafr Omeim C3928 7004 Lof C3929 2473 Mardikh C3930 5307 Maar Dibsi C3931 8895 Tal Tabariz C6634 368 Teftnaz C3932 7641 Talhiyeh C3933 3082 Shallakh C3934 3388 Maaret Elnaasan - Maaret Elhaski C3935 11697 5 Ketyan C3936 3175 Abu Kansa C6635 266 Jdarya C6636 616 Bhora C3937 686 Zardana Mashehad C3938 4102 Batenta C3939 2310 Taltuneh C3940 315 Ram Hamdan C3941 7469 Kafr - Kafrehmul C3942 5243 Haranbush C3943 7614 Hazano C3944 15389 Kafr Jales C3945 5824 6 Murin C3946 637 Ma'arrat Tamasrin C3947 31535 Kafr Nabi C3948 1617 Kelly C3949 7189 Maaret Elekhwan C3950 3080 Kaftin C3951 2499 Shekh Bahr C6631 315 Habat C6632 294 Beeret Kaftin C6633 749 Sarmin C3953 13335 7

Hatamiyeh C3954 316 Jarada C3955 1075 Kanayes C3956 1088 Hantutin C3957 2247 Tqana C3958 841 Tal Dibis C3959 2592 Hazzan C3960 648 Samkeh C3961 502 Eastern Deir C3962 5129 Ghadqa C3963 6896 Babilla C3964 3750 Dana C3965 2878 Halbeh C3966 1830 Thahrat Talamnas C3967 1865 Western Deir C3968 3108 Hraki C3969 2174 Harran C3970 681 Tal Kersyan C3971 1011 Sarman C3972 2460 Abu Makki C3973 3144 Telamnas C3974 15809 8 Barsa C3975 1475 Bsida C3976 119 Jarjnaz C3977 13344 Maar Shurin C3978 11438 Kweires C3979 240 Maasaran C3980 13182 Maar Shamsheh C3981 4425 9 Qaratli C3982 1043 Maar Shamarin C3983 7371 Kafruma C3984 10136 Ma'arrat An Nu'man C3985 30969 Hamdieh C6596 467 Western-Nuhiyeh C6597 600 Maarata C6598 341

Qasabiyeh C3986 831 Khan Shaykun C3987 11638 10 Um Zaytuna C3988 525 Hbit C3989 4877 Abdin C3990 2295 Nqeir C3991 3176 Baarbu C3992 1022 Kafr Ein C3993 3422 Little Khayrieyh C3994 549 Ghazileh C3995 976 Mreiheb C3996 1728 Tal Elojeh C3997 508 Rasm Elabed C3998 836 Jeb Elqasab C3999 224 Tellemara C4000 624 Tal Dam C4001 348 Halban C4002 687 Borj C4003 620 Dwadiyeh C4004 692 Maksar C4005 668 Ojeh C4006 1184 Ejaz C4007 1279 Thleijeh C4008 725 Khayriyeh C4009 462 Bashkum C4010 680 Shara - Sharat Elajayez C4011 1128 Um Sehrij C4012 1072 Um Tini C4013 688 Southern Um Mweilat C4014 588 Sheikh Barakeh C4015 1846 Jaberiyeh C4016 1086 Abu Sharji C4017 948 Tal Halawa C4018 722 Rabeeah Brennan C4019 753 Mutawaseta C4020 957

Saree C4021 688 Seraa C4022 2700 Jahman C4023 1348 Sanjar C4024 4956 11 Sqiah C4025 648 Sayadi C4026 1006 Abul Eleij C4027 1127 Dreibiyeh C4028 512 Heisa C4029 35 Hawa C4030 1172 Khyara C4031 1692 Khwein Elshaer C4032 220 Brennan C4033 660 Rabeeah Musa C4034 521 Karsanti C4035 276 Big Karatin C4036 1004 Fahil Jallas C4037 1099 Ferwan C4038 832 Magharet Merza C4039 1477 Little Karatin C4040 976 Mardagana Burtuqala C4041 532 Qasr Elabyad C4042 1196 Nibaz C4043 1027 Qatra C4044 3124 Kafraya Al Mara C4045 1000 Northern Lweibdeh C4046 769 Eastern Lweibdeh C4047 435 Mreijeb Elmashad C4048 827 Western Sarja C6306 1608 Eastern Sarja C6363 572 Nasriyeh C6599 76 Rasm Ward C6600 240 Abu Thijeh C6601 28 Mahatet Um Rejim C6602 292 Um Rjem C6603 300

Rasm Barjas C6604 616 Farja C6605 704 Northern Rasha C4049 552 Jbala C4050 3676 Tramla C4051 5384 Faqie C4052 2934 Shorlin C4053 1265 Sfuhen C4054 3716 Sheikh Mustafa C4055 3142 Hazarin C4056 5007 Big Dara C4057 1260 Has C4058 8995 12 Um Nir C4059 616 Milaja C4060 1535 Basqala C4061 5464 Kafr Oweid C4062 5076 Maar Tesin C4063 788 Qoqfin C4064 1814 Maar Tamater C4065 3683 Maarzita C4066 3773 Kafr Musa C4067 565 Kafr Nobol C4068 15698 Fleifel C4069 322 Ftireh C4070 5726 Maar Tahroma C4071 6935 13 Kawkabeh C4072 2194 Karsaa C4073 2572 Lweibdeh C4074 924 Al-Halubi C6594 388 Southern Rasha C6595 388 Sahal C4075 937 Tama C4076 1438 Skik C4077 1277 Raffa C4078 2492 Breiseh C4079 557

Tamanaah C4081 5229 Dajaj C4082 406 Niha C4083 2741 Hamadaniyeh C4084 1027 Um Elkhalayel C4085 4249 Abu Omar C4086 1026 Tal Maraq C4087 1476 Mashraf Rajmel Mashraf C4088 691 Farja C4089 2451 Shatib C4090 364 Big Khwein C4091 2148 Rweideh C4092 1468 Tal Khanzir C4094 954 Um Jalal C4095 2868 Qleiat Eltubiyeh C4096 1206 Northern Msheirfeh C4098 1374 Tal Shih C6606 792 Tah C4099 7433 14 Babuline C4100 5416 Amudiyeh C4101 811 Rakaya Sijneh C4102 1898 Tahtaya C4103 1199 Sahyan C4104 882 Heish C4105 10768 Armanaya C4106 884 Sheikh Dames C4107 1020 Abu Habbeh C4108 1135 Moqa C4109 4843 Kafrsajna C4110 10982 Kafr Basin C4111 1530 Maar Hattat C4112 1279 Maysruneh C4113 1080 Madaya C6593 1607 Ariba C4114 912 Harim C4115 19984 15

Besnaya - Bseineh C4116 3178 Kafr Hum C4117 1212 Mira Shaq C4118 68 Kafr Mu C4119 176 Hezreh - Hezri C4120 3175 Sarmada C4121 39501 RC Tal Elkaramej C4122 9943 Selwa C4123 8158 Tilaada C4124 7380 Termanin C4125 25690 Dana C4126 87452 16,17 Aqrabat C4127 3196 Burj Elnumra C4128 2160 Deir Hassan - Darhashan C4129 2359 Atma C4130 9859 Qah C4131 4139 Kafr Deryan C4132 10269 18 Bab El Hawa C6389 816 Abu Talha C4133 2124 Hamziyeh C4134 1057 Foziyeh C4135 100 Ein Elbikara C4136 1644 Tlul C4137 3840 Saidiyeh C4138 2779 Little Hir Jamus C4139 412 Salqin C4140 44626 19 Big Hir Jamus C4141 2086 Allani C4142 3612 Azmarin C4143 9292 Bozanti C4144 172 Eskat C4145 9624 Delbiya C4146 1387 Betiya C4147 399 Tellemar C4148 4176 Kafarna C4149 392

Kafrahlat Jallad C4150 440 Kafr Hind C4151 2090 Shyukh C6364 345 Sayed Khalil C6617 146 Jeser Maksour C6618 348 Faroukiyeh C6619 420 Msheirfeh C6620 713 Hamra C6621 324 Jakara C6622 521 Abarita C4152 394 Bshendlaya - Rashadiya C4153 249 Taltita C4154 493 Helleh C4155 502 Jadeen C4156 285 Kafr Takharim C4157 18492 20 Kafr Kila C4158 1353 Kafr Mars C4159 346 Kuku - Ein Eljaj C4160 676 Htan C4161 3661 Banabel C4162 1480 Barisha C4164 6185 Sardin C4165 4453 Boz Ghaz C4166 3372 Ras Elhisn C4167 5497 Rabeeta C4168 1321 Radwa C4169 2988 Torlaha C4170 2027 Meraf Elshalaf C4171 5361 Kafr Aruq C4172 5138 Qalb Lozeh C4173 2667 Qourqeena C4174 6526 21 Koknaya C6616 461 Ghafar C4175 2703 Armanaz C4176 15389 Quneitra C4177 1231

Hafasraja C4178 7534 Sheikh Yousef C4179 3471 Biret Armanaz C4180 2879 Baliya C4181 1201 Dweila C4182 626 Kuwaro - Um Elriyah C4183 1204 Milis C4184 4194 Kabta C4185 1652 Upper Sheikh Sindyan C4186 12 Msheirfeh C4187 384 Sali C4189 376 Maalaqa - Bishlamon C4190 2244 Balmis C4191 2360 Salhiyeh C4192 225 Bsheiriyeh - Bello C4193 2828 22 Um Rish C4194 2064 Bteibat C4195 172 Mintar C4196 512 Upper Shghur C4197 2586 Eshtabraq C4198 60 Jisr-Ash-Shugur C4199 10108 Bzeit C4200 1136 Bkafla C4201 607 Ein Elhamra C4202 1684 Ghassaniyeh C4203 464 Ein Elsoda C4204 1392 Kafir C4205 892 Qaysiyeh C4206 1004 Alyeh C4207 200 Jannet Elqora C4208 260 Ghanya C4209 12 Sokkariyeh C4210 1316 Sabileh C4211 312 Western Marj Akhdar C4212 4996 Um Elgar C4213 12

Dgali C4214 284 Eastern Marj Akhdar C4215 5152 Tal Awar C4217 440 Tal Hamki C4218 108 Frikeh C4219 416 Watba C4220 504 Marj Elzohur C4221 875 Kniset Nakhleh C4222 2082 Kastanah Fawqan C6640 568 Jeb Alsafa C6641 236 Qulaia C6642 208 Baksariya C4223 875 Badama C4226 2360 Armala C4227 1980 Hanbushiyeh C4228 1720 Ein El-Bayda C4229 2085 Kherbet Eljoz C4231 5090 Shaturiyeh C4232 1205 23 Najiyeh C4233 85 Ramliyeh C4234 590 Maraand C4235 90 Sawadiya - Nabhan C4236 1084 Turin C4237 352 Zarzur C4238 7160 Ghazala - Mgheidleh C4240 2832 Jamiliya C4241 1256 Ramadiyeh C4242 868 Mazuleh C4243 1728 Matleh - Batlaya C4244 808 Amud C4245 1200 Sadiyeh - Bsentiya C4246 1636 Thahr C4247 1952 Andnaniyeh - Farjein C4248 1548 Dorriyeh C4249 888 Zahraa - Kherbet Amud C4250 2160

Sheikh Issa Elashury C4251 1156 Darkosh C4252 15580 Zanbaqi C4253 952 Mreimin C4254 1084 Kharab Khalil C6637 408 Kharab Amer C6638 496 Kharab Sultan C6639 224 Janudiyeh C4255 9752 24 Yaqubiyeh C4256 2332 Hassaniyeh - Hatya C4257 2476 Qaderiyeh - Qayqun C4258 2452 Maland C4259 3324 Qanniyeh C4260 1592 Mudiah - Luxin C4261 484 Nasra C4262 772 Foz - Zuf C4263 1580 Tiba - Katrin C4264 100 Jdidet Eljisr C4265 1996 Athar C4266 664 Hamama - Kafr Debbin C4267 5468 Bazabur C4268 1880 Orm Eljoz C4269 6754 Abkally C4270 248 Bab Ellah C4271 1404 Thaheriya C4272 316 Sarja C4273 2892 Banin C4274 1364 Shinan C4275 3372 Berjhab C4276 752 Ebneh C4277 1105 Ariha C4278 33059 25 Maarzaf C4279 1696 Majdaliya C4280 1838 Mseibin C4281 2212 Kafraziba C4282 1724

Kafrlata C4283 4056 Nahleh C4284 2226 Maarbalit C4285 2168 Nahliya C4286 2130 Moataf C4287 3504 Korin C4288 3840 Kafr Shalaya C4289 2309 Motaram C4290 2324 Ruwaiha C6607 580 Kafr Najd C6608 1405 Badriyeh C6609 232 Kadoura C6610 176 Maalali C6611 244 Abdita C4291 2160 RC Ablin C4292 2921 Deir Sunbul C4293 1448 Rami C4294 4364 Ehsem C4295 5605 Balshun C4296 3319 Bsames C4297 3321 Mozra C4298 3981 Ein Laruz C4299 1393 Maghara C4300 2147 Arnaba C4301 2648 Balyun C4302 6443 Joseph C4303 3962 Bara C4304 9934 Farkya C4305 1809 Kafr Haya C4306 1459 26 Marata C4307 2213 Marayan C4308 3363 Kansafra C4309 4953 Baydar Shamsu C4310 1000 Shagurit C4311 743 Ora Qabli - Edwan C4312 3049

Kniseh C4313 2800 Bales C4314 500 Sararif C4315 1252 Northern Laj C4316 1736 Matleh Ariha C4317 204 Hmeimat C4319 812 Jadraya C4320 1247 Beftamun C4321 1333 Bsanqul C4322 1252 Anb C4323 1255 Baqlid C4324 396 Hlul C4326 825 Sahen C4327 2324 Hila C4328 1944 Kafrmid C4329 463 Mhambal C4330 3216 Marj C6365 1044 Sanghara C6612 228 Alyeh C6613 340 Ainata C6614 299 Qrsaya C6615 424 Abu Habbeh Camp52 662 Al Muaysruneh Camp53 211 Lhluoba Camp54 214 Abul Eleij Camp55 254 Bashkum Camp56 274 Khaldyiah Camp57 240 Eastern Ejaz Camp58 139 Western Ejaz Camp59 655 Fahil Jallas Camp60 117 Fakkah Camp61 148 Jeb Elqasab Camp62 101 Sawame' Camp63 185 Khayriyeh Camp64 130 Lower Maksar Camp65 117

Upper Maksar Camp66 208 Mreijeb Slejah Camp68 400 Mreijeb Elmashad Camp69 310 Lweibdeh Camp70 274 Ojeh Camp71 158 Qatra Camp72 159 Rasm Elabed Camp73 529 Ramleh Camp74 213 Re'a Alhawa Camp75 459 Tal Halawa Camp76 1274 Al Farja Al Gharbi Camp78 672 Al Raffa Al Janobi Camp80 222 Al Raffa Al Sharqi Camp82 371 Sahal Camp83 236 Tal Shih Camp84 460 Aqrabat (Ahl Al?Athar) Camp85 690 Al Dana Camp86 345 Municipality building Camp90 140 Atmeh Camp92 61828 27,28 Al Nahdha Camp93 414 Al Ummahat Camp94 330 Aycha Camp95 1063 Othman Bin Affan Camp96 138 Shahba'1 (Bab Al Hawa Lower/1) Camp97 1712 Shahba'2 Camp98 419 Taiba City Camp99 1793 Termanin Camp100 124 Ayidoun Camp101 2072 Kadimoon Camp102 1614 Samidoon Camp103 2072 Al Safsafa Camp105 2019 Al Taakhi Camp106 1340 Abu Obeida Ben Aljaraah Camp107 602 Al Rahmah Lahl Al Gab (Al Qaqaa) Camp108 1465 Ghetaa Al Rahma 1 Camp109 714

Nasaem Al Khayr Camp110 1807 Nour Al Houda Camp111 1143 Sons of Mehin Camp112 2472 Ahl Al Balad Camp113 557 Al Nahda Camp114 2119 Zamzam Camp115 561 Ebtieen Camp116 282 Al Mashhad Camp117 280 Reef Aleppo Camp118 145 Tal Al Karama Camp119 489 Al Wdhehee Camp120 279 Al Foqaraa (The Poor) Camp121 808 Al Alani school Camp122 119 Al Fath Camp123 137 Al Meshrefeiah school Camp124 122 Ahmad Hameesh Camp126 185 Al Banin school Camp128 120 Al Ezzawi school Camp129 182 Al Sakan Al Shababi Camp131 290 Al Thawra school Camp133 125 Act and Impact (Athar) Camp136 1138 Ahel Al Sham Camp137 709 Ahel Halep Camp138 712 Al Ahrar Camp139 1174 Al Amal Bil Awdah Camp140 442 Al Aqsa Camp141 688 Al Asil Camp142 853 Al Ataa Camp143 736 Al Ayade Al Baydaa Camp144 287 Al Fadal Camp145 559 Al Faraj Camp146 1044 Al Farouk Camp147 886 Al Ghab Al Mankoub Camp148 710 Al Haneen Camp149 400 Al Haq Camp150 545

Al Hijaz Camp151 521 Al Ikhaa Camp152 1301 Al Ikhlas Camp153 683 Al Jabal Camp154 266 Aleman Billah Camp155 828 Al Karama Camp156 2988 Al Karim Al Awsat Camp157 425 Al Mahabbah Camp158 757 Al Manara Camp159 714 Al Mustakbal Camp160 897 Al Nahda Aleslamia Camp161 743 Al Nour Camp162 738 Al Resalah (extension of Doaa, Doaa & Saleh) Camp163 376 Al Safa wa Al Marwa Camp164 810 Al Shuhada Camp165 542 Atfal Alghad Camp166 578 Doaa Camp167 1168 Doaat Al Kwait (Al Khayrat) Camp168 703 RC Harameen Camp169 783 Kura Mankouba Camp170 576 Moatakalen Sahl Al Gab Camp171 1238 Nasret Al Mazloum Camp172 1516 Nour Al Mustafa Camp173 986 Nour Al Mustakbal Camp174 757 Nour Al Sham Camp175 542 Nour Hama Camp176 179 Qadisiya Camp177 790 Rajaa Camp178 862 Rawdah Camp179 536 Reef Hama Mankouba Camp180 751 Salah Eldin (including Al Islah) Camp181 1719 Sedik (Extension of Al Aqsa) Camp182 707 Shaheid Saleh Camp183 790 Shams Al Hurriya Camp184 1295 Shuhada Sahl Al Gab Camp185 608

Sons of Homs (Abna Homs) Camp186 635 Tabarak Al Rahman Camp187 688 Taibah Camp188 1272 Tajammu Camp189 149 Watasimu (including Tadamun and Sahl Al Ghab) Camp190 2418 Yasmeen Al Sham Camp191 1423 Zahret Al Madaen Camp192 754 Ain Jaloot Camp193 210 Al Aasy Camp194 799 Al Fateh Al Araby Camp195 444 Al Hurriya wa Adalah Camp196 1233 Al Ikhlas and Al Taqua Camp197 932 Al Nawaeer Camp198 1666 Al Shrouk Camp199 623 Bara`m Al Thawra Camp200 624 Children of Freedom Martyrs Camp201 360 Farajak Yarab Camp202 234 Fardoose Camp203 893 Fateh Aleslam Camp204 472 Korayish (Al Khair) Camp205 724 Lan Narka`llla Lilah Camp206 1464 Liyajlikum Camp207 1184 Qassioun Camp208 488 Toyor Al Janna (Heaven Bird's) Camp209 866 Abu Bakker Al Sidiq Camp210 732 Afamia Camp211 541 Ahbab Al Rasoul Camp212 833 Al Arbaeen Camp213 434 Al Bayan Camp214 559 Al Imam Camp215 841 Al Intisar Camp216 638 Al Magad Camp217 527 Al Motasem Camp218 393 Al Muhajreen Camp219 656 Al Radwan Camp220 241

Al Rahmah Camp221 735 Al Tawheed Camp222 269 Al Waleed Camp223 746 Alebaa Camp224 595 Ataa 2 (Hamad Al Ammar 1/Dar Al Riaya ? Orphans) Camp225 557 Ataa 3 (Al Ansar) Camp226 635 Ataa 4 (Al Reaya Al Islamiya) Camp227 929 Ataa 5 (Shabab Al Khayr) Camp228 935 Ataa 6 (Shabab Al Khayr 3) Camp229 1479 Ataa 7a (Ataa Almara Alkwaityeh 1) Camp230 992 Ataa 7b (Ataa Almara Alkwaityeh 2) Camp231 1190 Ataa 8 (Shabab Al Khayr 2) Camp232 1588 Ataa 9a (Hamad Al Ammar 2) Camp233 660 Ataa 9b (Nasaem Alkhair) Camp234 785 Bab Al Hawa Camp235 683 Bab Al Hawa extension (Al Mutahaboun Bellah) Camp236 1243 29 Bani Omiyet Camp237 341 Hibat Allah Camp238 751 Kafr Nabutha Alsmoud Camp239 309 Madenh Monarh (Hmamiat) Camp240 666 Nasret Al Rasoul Camp241 702 Qah Camp242 1296 Sarkhat Tifl Camp243 468 Sahl Al Ghab Alawal Camp244 460 Shuhadaa Abdeen Camp245 701 Abl Baydar Camp246 242 Al Ahd Billah Camp247 1234 Al Forkan Camp249 1334 Al Goroub Camp250 719 Al Jolan Camp251 1630 Al Khalij Camp252 482 Al Midan Camp253 1054 Al Nasser Camp254 1612 Al Madiq 1 Camp255 115 Al Madiq 2 Camp256 279

Al Salam Camp257 1797 Dar Al Riaya ? Disabled Camp258 1040 Dma'aet Nazeh Camp259 309 Kafr Nabutha Al Amal Camp260 282 Kafr Nabutha Alhora Camp261 312 Muhajreen Al Gab Camp262 514 Shams Al Izza Camp263 214 Shuhada Kafr Nabutha Camp264 701 Zahrat Al Jolan Camp265 496 Ariha Camp266 311 Al Faraj (Al Ghab) Camp267 741 Al Faroq Camp268 391 Al Fateh Camp269 312 Al Imdad Camp270 490 Al Khirba Al Muhasara Camp271 610 Al Nouri Camp272 970 Al Sadaka Camp273 503 Al Ummah Camp274 522 Khaled Bin Al Waleed Camp275 1178 Alhai Aljanouby school Camp276 152 Al Kaws school Camp278 140 Al Khorbeh school Camp279 155 Almjamaa Altarbawy Camp281 150 Alsiasieh Camp283 190 Alzeraah Camp284 300 Karm Abo Jaafar Camp286 600 Omahat Al Moumenien Camp287 251 Jabal Harim (Sabiroon) Camp288 777 Al Madenh Monarh (Harim) Camp289 139 Abna`a Al Ghab Camp290 864 Kafr Hum Camp291 956 Maaret Elekhwan Transit Centre Camp306 550 Othman Bin Affan Camp317 894 Ali Bin Abi Taleb Camp318 1435 Meriamen Camp320 108

Az?Zawf 1 (Sham) Camp321 2840 Az?Zawf 2 (Sadaka Tashi) Camp322 2493 Az?Zawf 3 (Al Ikhaa) Camp323 1242 Al Hamama Camp324 327 Al Kaderiyeh Camp325 129 Salah Alden (Kherbet Eljoz) Camp328 3229 Ataa Al Kheir Camp329 2482 Ein Al Bayda Camp330 4845 Omar Camp331 3184 Al Hanbushiyeh Camp332 1608 30

Geographical unit Population size Cluster Idlep City C3871 116390 1,2 Abul Thohur C3891 7151 RC Bweiti C3911 1362 3 Khan Elsobol C3925 8865 4 Maaret Elnaasan - Maaret Elhaski C3935 11697 5 Kafr Jales C3945 5824 6 Sarmin C3953 13335 7 Telamnas C3974 15809 8 Maar Shamsheh C3981 4425 9 Khan Shaykun C3987 11638 10 Sanjar C4024 4956 11 Has C4058 8995 12 Maar Tahroma C4071 6935 13 Tah C4099 7433 14 Harim C4115 19984 15 Sarmada C4121 39501 RC Dana C4126 87452 16,17 Kafr Deryan C4132 10269 18 Salqin C4140 44626 19 Kafr Takharim C4157 18492 20 Qourqeena C4174 6526 21 Bsheiriyeh - Bello C4193 2828 22 Shaturiyeh C4232 1205 23 Janudiyeh C4255 9752 24 Ariha C4278 33059 25 Abdita C4291 2160 RC Kafr Haya C4306 1459 26 Atmeh Camp92 61828 27,28 Doaat Al Kwait (Al Khayrat) Camp168 703 RC Bab Al Hawa extension (Al Mutahaboun Bellah) Camp236 1243 29 Al Hanbushiyeh Camp332 1608 30

Appendix 3

Evaluation of Enumerators

Weight:

Precision: Accuracy: No. +/- No. +/- Sum of Square Sum of Square Precision Accuracy [W1-W2] [Enum.(W1+W2)- (Superv.(W1+W2)]

Supervisor 1.03 3/7 Enumerator 1 1.10 OK 0.41 OK 1/7 3/5 Enumerator 2 0.91 OK 0.34 OK 0/7 4/5 Enumerator 3 0.19 OK 0.82 OK 1/9 4/5 Enumerator 4 4.67 POOR 5.94 POOR 3/6 5/5 Enumerator 5 77.32 POOR 77.33 POOR 1/8 6/3 Enumerator 6 1.66 OK 0.77 OK 1/6 6/3 Enumerator 7 0.42 OK 0.59 OK 0/7 3/7 Enumerator 8 0.76 OK 0.29 OK 2/7 4/4 Enumerator 9 0.51 OK 0.32 OK 2/7 4/4 Enumerator 10 0.35 OK 0.66 OK 1/3 5/4

Height:

Precision: Accuracy: No. +/- No. +/- Sum of Square Sum of Square Precision Accuracy [H1-H2] [Enum.(H1+H2)- Superv.(H1+H2)]

Supervisor 0.32 5/4 Enumerator 1 1.59 POOR 11.67 POOR 5/3 5/5 Enumerator 2 7.27 POOR 6.31 POOR 6/4 6/3 Enumerator 3 0.17 OK 6.67 POOR 1/7 5/4 Enumerator 4 59.50 POOR 69.04 POOR 4/4 3/7 Enumerator 5 561.61 POOR 568.87 POOR 7/2 3/7 Enumerator 6 1.82 POOR 14.30 POOR 3/4 1/7

Enumerator 7 0.22 OK 6.34 POOR 1/7 5/3 Enumerator 8 0.45 OK 1.83 POOR 1/5 4/6 Enumerator 9 5.26 POOR 21.48 POOR 3/6 3/7 Enumerator 10 10.87 POOR 25.27 POOR 1/4 1/8

MUAC:

Precision: Accuracy: No. +/- No. +/- Sum of Square Sum of Square Precision Accuracy [MUAC1-MUAC2] [Enum.(MUAC1+MUAC2)- Superv.(MUAC1+MUAC2]

Supervisor 26.00 4/4 Enumerator 1 27.00 OK 705.00 POOR 2/4 1/9 Enumerator 2 104.00 POOR 700.00 POOR 3/3 2/8 Enumerator 3 10.00 OK 422.00 POOR 4/3 3/6 Enumerator 4 14.00 OK 272.00 POOR 2/4 3/5 Enumerator 5 83.00 POOR 1097.00 POOR 2/4 2/8 Enumerator 6 134.00 POOR 440.00 POOR 3/5 4/6 Enumerator 7 9.00 OK 275.00 POOR 5/4 4/5 Enumerator 8 41.00 OK 271.00 POOR 4/4 4/6 Enumerator 9 46.00 OK 324.00 POOR 6/2 2/8 Enumerator 10 18.00 OK 714.00 POOR 2/7 3/7

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.

Appendix 4

Result Tables for NCHS growth reference 1977

Table 3.2: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex

All Boys Girls n = 575 n = 294 n = 281 Prevalence of global (11) 1.9 % (6) 2.0 % (5) 1.8 % malnutrition (0.9 - 3.9 (1.0 - 4.3 (0.6 - 4.9 (<-2 z-score and/or oedema) 95% C.I.) 95% C.I.) 95% C.I.) Prevalence of moderate (11) 1.9 % (6) 2.0 % (5) 1.8 % malnutrition (0.9 - 3.9 (1.0 - 4.3 (0.6 - 4.9 (<-2 z-score and >=-3 z-score, no 95% C.I.) 95% C.I.) 95% C.I.) oedema) Prevalence of severe (0) 0.0 % (0) 0.0 % (0) 0.0 % malnutrition (0.0 - 0.0 (0.0 - 0.0 (0.0 - 0.0 (<-3 z-score and/or oedema) 95% C.I.) 95% C.I.) 95% C.I.) The prevalence of oedema is 0.0 %

Table 3.3: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema

Severe wasting Moderate Normal Oedema (<-3 z-score) wasting (> = -2 z score) (>= -3 and <-2 z-score ) Age Total No. % No. % No. % No. % (mo) no. 6-17 171 0 0.0 5 2.9 166 97.1 0 0.0 18-29 142 0 0.0 0 0.0 142 100.0 0 0.0 30-41 123 0 0.0 3 2.4 120 97.6 0 0.0 42-53 103 0 0.0 1 1.0 102 99.0 0 0.0 54-59 36 0 0.0 2 5.6 34 94.4 0 0.0 Total 575 0 0.0 11 1.9 564 98.1 0 0.0

Table 3.4: Distribution of acute malnutrition and oedema based on weight-for-height z- scores

<-3 z-score >=-3 z-score Oedema present Marasmic kwashiorkor Kwashiorkor No. 0 No. 0 (0.0 %) (0.0 %) Oedema absent Marasmic Not severely malnourished No. 0 No. 578 (0.0 %) (100.0 %)

Table 3.5: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) and by sex

All Boys Girls n = 578 n = 296 n = 282 Prevalence of global (11) 1.9 % (6) 2.0 % (5) 1.8 % malnutrition (0.8 - 4.6 (0.6 - 6.8 (0.6 - 4.9 (< 125 mm and/or oedema) 95% C.I.) 95% C.I.) 95% C.I.) Prevalence of moderate (9) 1.6 % (6) 2.0 % (3) 1.1 % malnutrition (0.6 - 3.8 (0.6 - 6.8 (0.3 - 3.3 (< 125 mm and >= 115 mm, no 95% C.I.) 95% C.I.) 95% C.I.) oedema) Prevalence of severe (2) 0.3 % (0) 0.0 % (2) 0.7 % malnutrition (0.1 - 1.5 (0.0 - 0.0 (0.2 - 3.0 (< 115 mm and/or oedema) 95% C.I.) 95% C.I.) 95% C.I.)

Table 3.6: Prevalence of acute malnutrition by age, based on MUAC cut off's and/or oedema

Severe wasting Moderate Normal Oedema (< 115 mm) wasting (> = 125 mm ) (>= 115 mm and < 125 mm) Age Total No. % No. % No. % No. % (mo) no. 6-17 173 2 1.2 8 4.6 163 94.2 0 0.0 18-29 143 0 0.0 1 0.7 142 99.3 0 0.0 30-41 123 0 0.0 0 0.0 123 100.0 0 0.0 42-53 103 0 0.0 0 0.0 103 100.0 0 0.0 54-59 36 0 0.0 0 0.0 36 100.0 0 0.0 Total 578 2 0.3 9 1.6 567 98.1 0 0.0

Table 3.5: Prevalence of acute malnutrition based on the percentage of the median and/or oedema

n = 575 Prevalence of global acute (7) 1.2 % malnutrition (0.6 - 2.4 95% (<80% and/or oedema) C.I.) Prevalence of moderate acute (7) 1.2 % malnutrition (0.6 - 2.4 95% (<80% and >= 70%, no oedema) C.I.) Prevalence of severe acute (0) 0.0 % malnutrition (0.0 - 0.0 95% (<70% and/or oedema) C.I.)

Table 3.6: Prevalence of malnutrition by age, based on weight-for-height percentage of the median and oedema

Severe Moderate Normal Oedema wasting wasting (> =80% (<70% median) (>=70% and median) <80% median) Age Total No. % No. % No. % No. % (mo) no. 6-17 171 0 0.0 4 2.3 167 97.7 0 0.0 18-29 142 0 0.0 0 0.0 142 100.0 0 0.0 30-41 123 0 0.0 1 0.8 122 99.2 0 0.0 42-53 103 0 0.0 0 0.0 103 100.0 0 0.0 54-59 36 0 0.0 2 5.6 34 94.4 0 0.0 Total 575 0 0.0 7 1.2 568 98.8 0 0.0

Table 3.7: Prevalence of underweight based on weight-for-age z-scores by sex

All Boys Girls n = 572 n = 291 n = 281 Prevalence of underweight (48) 8.4 % (22) 7.6 % (26) 9.3 % (<-2 z-score) (5.1 - 13.6 (4.2 - 13.1 (5.3 - 15.7 95% C.I.) 95% C.I.) 95% C.I.) Prevalence of moderate (36) 6.3 % (16) 5.5 % (20) 7.1 % underweight (3.8 - 10.4 (3.0 - 9.9 (4.1 - 12.2 (<-2 z-score and >=-3 z-score) 95% C.I.) 95% C.I.) 95% C.I.) Prevalence of severe (12) 2.1 % (6) 2.1 % (6) 2.1 % underweight (1.0 - 4.4 (0.9 - 4.4 (0.8 - 5.7 (<-3 z-score) 95% C.I.) 95% C.I.) 95% C.I.)

Table 3.8: Prevalence of underweight by age, based on weight-for-age z-scores

Severe Moderate Normal Oedema underweight underweight (> = -2 z score) (<-3 z-score) (>= -3 and <-2 z-score ) Age Total No. % No. % No. % No. % (mo) no. 6-17 170 3 1.8 11 6.5 156 91.8 0 0.0 18-29 141 2 1.4 11 7.8 128 90.8 0 0.0 30-41 122 4 3.3 9 7.4 109 89.3 0 0.0 42-53 103 2 1.9 5 4.9 96 93.2 0 0.0 54-59 36 1 2.8 0 0.0 35 97.2 0 0.0 Total 572 12 2.1 36 6.3 524 91.6 0 0.0

Table 3.9: Prevalence of stunting based on height-for-age z-scores and by sex

All Boys Girls n = 564 n = 289 n = 275 Prevalence of stunting (52) 9.2 % (19) 6.6 % (33) 12.0 % (<-2 z-score) (6.3 - 13.2 (4.0 - 10.5 (8.0 - 17.6 95% C.I.) 95% C.I.) 95% C.I.) Prevalence of moderate stunting (40) 7.1 % (13) 4.5 % (27) 9.8 % (<-2 z-score and >=-3 z-score) (4.8 - 10.5 (2.8 - 7.1 (6.1 - 15.4 95% C.I.) 95% C.I.) 95% C.I.) Prevalence of severe stunting (12) 2.1 % (6) 2.1 % (6) 2.2 % (<-3 z-score) (1.1 - 4.0 (0.9 - 4.6 (1.0 - 4.5 95% C.I.) 95% C.I.) 95% C.I.)

Table 3.10: Prevalence of stunting by age based on height-for-age z-scores

Severe Moderate Normal stunting stunting (> = -2 z score) (<-3 z-score) (>= -3 and <-2 z-score ) Age Total No. % No. % No. % (mo) no. 6-17 171 3 1.8 7 4.1 161 94.2 18-29 138 6 4.3 8 5.8 124 89.9 30-41 119 1 0.8 15 12.6 103 86.6 42-53 100 1 1.0 9 9.0 90 90.0 54-59 36 1 2.8 1 2.8 34 94.4 Total 564 12 2.1 40 7.1 512 90.8

Table 3.11: Prevalence of overweight based on weight for height cut off's and by sex (no oedema)

All Boys Girls n = 575 n = 294 n = 281 Prevalence of overweight (WHZ (4) 0.7 % (2) 0.7 % (2) 0.7 % > 2) (0.2 - 2.3 (0.2 - 2.7 (0.2 - 2.9 95% C.I.) 95% C.I.) 95% C.I.) Prevalence of severe overweight (0) 0.0 % (0) 0.0 % (0) 0.0 % (WHZ > 3) (0.0 - 0.0 (0.0 - 0.0 (0.0 - 0.0 95% C.I.) 95% C.I.) 95% C.I.)

Table 3.12: Prevalence of overweight by age, based on weight for height (no oedema)

Overweight Severe (WHZ > 2) Overweight (WHZ > 3) Age Total No. % No. % (mo) no. 6-17 171 2 1.2 0 0.0 18-29 142 2 1.4 0 0.0 30-41 123 0 0.0 0 0.0 42-53 103 0 0.0 0 0.0 54-59 36 0 0.0 0 0.0 Total 575 4 0.7 0 0.0

Table 3.13: Mean z-scores, Design Effects and excluded subjects

Indicator n Mean z- Design z-scores z-scores scores ± Effect (z- not out of SD score < -2) available* range Weight-for- 575 -0.26±0.83 1.43 0 3 Height Weight-for-Age 572 -0.73±0.95 3.07 0 6 Height-for-Age 564 -0.75±0.96 1.88 0 14 * contains for WHZ and WAZ the children with oedema.

Appendix 5

Maps of area

Appendix 6

Questionnaires

رقم الفريق رقم العنقود تاريخ المقابلة (dd/mm/yyyy)

|___|___|/|___|___|/ 2017 |___|___| |___|

األطفال من عمر 6 أشهر إلى أقل من 5 سنوات مسح األطفال المنفصلين )6-59شهر(، ولدوا بين تموز 2012 الى كانون األول 2016 )2012/07 –2016/12( A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 ما هي العالقة هل أنت MUAC HGB الوذمة الطول الوزن العمر تاريخ الميالد الجنس HH رقم بين رب األم/األب رقم قياس ثنائية (kg) (cm) )شهور( (f/m) (DD/MM/YYYY) رقم الطفل األسرة )أنت( الحقيقي لهذا الخضاب محيط الجانب (000.0) (00.0) األسرة والطفل الطفل؟ )نعم أو (mg) منتصف (y/n) فقط إذا لم اذا ملئت العمود *: إذا تم يوجد لدينا , انتقل الى ال( (00.0) العضد A4 08 = حفيد تاريخ العمود A6 نعم = mm) 01) قياس 09 = ابن أو الميالد ال = 02 (000) الطفل ابنة أخ/ بشكل دقيق الذراع بطريقة أخت في حال اإلجابة اليسرى مغايرة لما ب ال أجب عن اتفق عليه 10=أخ أو A12السؤال أخت 11=ابن أو ابنة عم 12 = ليسوا أقارب

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رقم الفريق رقم العنقود تاريخ المقابلة (dd/mm/yyyy)

|___|___|/|___|___|/ 2017 |___|___| |___|

األطفال من عمر 6 أشهر إلى أقل من 5 سنوات مسح األطفال المنفصلين )6-59شهر(، ولدوا بين تموز 2012 الى كانون األول )2016/12– 2012/07( 2016 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 ما هي العالقة هل أنت MUAC HGB الوذمة الطول الوزن العمر تاريخ الميالد الجن HH رقم بين رب األم/األب رقم قياس محيط ثنائية (kg) (cm) )شهور( DD/MM/YY) س رقم الطفل األسرة )أنت( الحقيقي الخضاب منتصف العضد الجانب (f/ YY) (00.0) (000.0) األسرة والطفل فقط إذا لم لهذا (m) (y/n) (mm) (mg يوجد لدينا الطفل؟ (000) *: إذا تم اذا ملئت العمود 08 = حفيد (00.0) تاريخ )نعم أو ال( الذراع اليسرى قياس A4, انتقل الى 09 = ابن أو الميالد نعم = 01 الطفل العمود A6 ابنة أخ/ بشكل دقيق ال = 02 بطريقة أخت مغايرة في حال لما اتفق 10=أخ أو اإلجابة ب أخت 11=ابن ال أجب عن عليه أو ابنة عم 12 السؤال = ليسوا التالي أقارب A12

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رقم الفريق رقم العنقود تاريخ المقابلة (dd/mm/yyyy)

|___|___|/|___|___|/ 2017 |___|___| |___|

األطفال من عمر 6 أشهر إلى أقل من 5 سنوات مسح األطفال المنفصلين )6-59شهر(، ولدوا بين تموز 2012 الى كانون األول 2016 )2012/07 –2016/12( A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 ما هي العالقة هل أنت MUAC HGB الوذمة الطول الوزن العمر تاريخ الميالد الجنس HH رقم الطفل بين رب األسرة األم/األب رقم قياس ثنائية (kg) (cm) )شهور( (f/m) (DD/MM/YYYY) رقم )أنت( والطفل الحقيقي لهذا الخضاب محيط الجانب (000.0) (00.0) األسرة الطفل؟ )نعم أو (mg) منتصف (y/n) فقط إذا اذا ملئت العمود 08 = حفيد *: إذا لم يوجد , انتقل الى ال( (00.0) العضد A4 09 = ابن أو تم قياس لدينا العمود A6 نعم = mm) 01) ابنة أخ/ الطفل تاريخ أخت ال = 02 (000) الميالد الذراع بطريقة في حال اإلجابة بشكل ب ال أجب عن اليسرى مغايرة 10=أخ أو أخت دقيق لما اتفق 11=ابن أو ابنة السؤال التالي عم 12 = ليسوا A12 عليه أقارب

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