smart survey report, idleb governorate, syria

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.

.

Table 1: Summary of key indicators

Prevalence of acute malnutrition based on weight-height

z-scores1

(n) % CI

Prevalence of global acute malnutrition

(WFH <-2 z-score and/or edema) 12 2.2 1.2- 4.2 95% C.I.

Prevalence of moderate acute malnutrition

(WFH <-2 z-score and >=-3 z-score, no edema) 10 1.7 0.8 – 3.6 95% C.I.

Prevalence of severe acute malnutrition

(WFH <-3 z-score and/or edema) 3 0.5 0.2 – 1.6 95% C.I.

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

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

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

(WFA <-2 z-score and >=-3 z-score) 26 4.5 2.7 – 7.4 95% C.I.

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

(HFA <-2 z-score and >=-3 z-score) 54 9.4 6.6 – 13.1 95% C.I.

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

n = 578

Boys

n = 296

Girls

n = 282

Normal

(HGB > 12 mg/dl)

(374)

64.71 %

(184)

62.16 %

(190)

67.37 %

moderate anaemia

(HGB < 12 and > 7 mg/dl)

(204)

35.29 %

(112)

37.84 %

(92)

32.63 %

severe anaemia

(HGB < 7 mg/dl)

(0)

0 %

(0)

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

Assumptions based on context

(footnote any references used)

Value Parameters for Anthropometry

Assumption Idleb Parameters

The last SMART survey In Idleb

2014 Showed GAM rate 1.13 % (0.3

– 2.0 CI 95%) and due to the Waves

of new IDPs from Besieged area

came to the area we expect a higher

Prevalence

4 % Estimated Prevalence of GAM (%)

Based on SMART recommendations

for the estimated GAM prevalence (±

3% for estimated prevalence <10%).

3 % ± Desired precision

The design effect chosen for this

survey (1.5) was chosen to reflect

potential differences between rural,

urban and camp/informal settlements

in conflict-affected districts.

1.5 Design Effect (if applicable)

Children to be included in the

survey

268

There is no available data about the

HH size in this area and We used 5. 5

Average HH Size

This rate had been used in 2014

SMART survey and we used the

same.

15 % % Children under-5

The Non-response rate in the last 5 % % Non-response Households

Survey in the area was about 3% and

we expect a slightly higher rate.

Households to be included in the

survey

417

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

of

children

6-59

months

planned

Number

of

children

6-59

months

included

% 6-59 month

children

included/planned

Number of

eligible 6-59

month

children

Number of

eligible 6-59

month

children

included

% of eligible

6-59 month

children

included

267 578 216 % 586 578 98.6%

Table 2.4: Percent of household non-response

Number of HH

planned*

Number of HH

surveyed

% HH Non-Response

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 n = 578

Boys n = 296

Girls n = 282

Prevalence of global malnutrition

(<-2 z-score and/or oedema)

(13) 2.2 % (1.2 - 4.2 95%

C.I.)

(4) 1.4 % (0.5 - 3.5 95%

C.I.)

(9) 3.2 % (1.6 - 6.1 95%

C.I.)


(<-2 z-score and >=-3 z-score, no

oedema)

(10) 1.7 % (0.8 - 3.6 95%

C.I.)

(3) 1.0 % (0.3 - 3.1 95%

C.I.)

(7) 2.5 % (1.1 - 5.5 95%

C.I.)

Prevalence of severe malnutrition


(3) 0.5 % (0.2 - 1.6 95%

C.I.)

(1) 0.3 % (0.0 - 2.6 95%

C.I.)

(2) 0.7 % (0.2 - 2.9 95%

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

(<-3 z-score)

Moderate

wasting

(>= -3 and <-2

z-score )

Normal

(> = -2 z score)

Oedema

Age

(mo)

Total

no.

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

6-17 173 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

No. 0

(0.0 %)

Kwashiorkor

No. 0

(0.0 %)

Oedema absent Marasmic

No. 3

(0.5 %)

Not severely malnourished

No. 575

(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

n = 578

Boys

n = 296

Girls

n = 282

Prevalence of global malnutrition

(< 125 mm and/or oedema)

(11) 1.9 %

(0.8 - 4.6 95%

C.I.)

(6) 2.0 %

(0.6 - 6.8 95%

C.I.)

(5) 1.8 %

(0.6 - 4.9 95%

C.I.)


(< 125 mm and >= 115 mm, no

oedema)

(9) 1.6 %

(0.6 - 3.8 95%

C.I.)

(6) 2.0 %

(0.6 - 6.8 95%

C.I.)

(3) 1.1 %

(0.3 - 3.3 95%

C.I.)

Prevalence of severe malnutrition


(2) 0.3 %

(0.1 - 1.5 95%

C.I.)

(0) 0.0 %

(0.0 - 0.0 95%

C.I.)

(2) 0.7 %

(0.2 - 3.0 95%

C.I.)

Table 4.6: 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. %

6-17 173 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

n = 577

Boys

n = 296

Girls

n = 281

Prevalence of underweight

(<-2 z-score)

(38) 6.6 %

(3.9 - 10.9 95%

C.I.)

(19) 6.4 %

(3.4 - 11.8 95%

C.I.)

(19) 6.8 %

(3.7 - 12.0 95%

C.I.)

Prevalence of moderate

underweight

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

(26) 4.5 %

(2.7 - 7.4 95%

C.I.)

(14) 4.7 %

(2.3 - 9.4 95%

C.I.)

(12) 4.3 %

(2.4 - 7.5 95%

C.I.)

Prevalence of severe

underweight

(<-3 z-score)

(12) 2.1 %

(0.9 - 4.8 95%

C.I.)

(5) 1.7 %

(0.6 - 4.7 95%

C.I.)

(7) 2.5 %

(1.0 - 5.9 95%

C.I.)

Table 4.8: 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. %

6-17 172 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

n = 576

Boys

n = 295

Girls

n = 281

Prevalence of stunting

(<-2 z-score)

(82) 14.2 %

(10.2 - 19.5 95%

C.I.)

(40) 13.6 %

(9.5 - 19.0 95%

C.I.)

(42) 14.9 %

(10.1 - 21.6

95% C.I.)


stunting


(54) 9.4 %

(6.6 - 13.1 95%

C.I.)

(28) 9.5 %

(6.3 - 14.1 95%

C.I.)

(26) 9.3 %

(5.6 - 14.9 95%

C.I.)

Prevalence of severe stunting

(<-3 z-score)

(28) 4.9 %

(2.6 - 8.9 95%

C.I.)

(12) 4.1 %

(1.9 - 8.4 95%

C.I.)

(16) 5.7 %

(3.1 - 10.3 95%

C.I.)

Table 4.10: 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. %

6-17 171 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

n = 578

Boys

n = 296

Girls

n = 282

Prevalence of overweight (WHZ >

2)

(9) 1.6 %

(0.8 - 2.9 95%

C.I.)

(4) 1.4 %

(0.5 - 3.4 95%

C.I.)

(5) 1.8 %

(0.8 - 4.0 95%

C.I.)

Prevalence of severe overweight

(WHZ > 3)

(3) 0.5 %

(0.2 - 1.6 95%

C.I.)

(2) 0.7 %

(0.2 - 2.7 95%

C.I.)

(1) 0.4 %

(0.0 - 2.7 95%

C.I.)

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

Overweight

(WHZ > 2)

Severe Overweight (WHZ

> 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-

scores ± SD

Design Effect

(z-score < -2)

z-scores not

available*

z-scores out

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=91/ID=1: WAZ (2.635), Weight may be incorrect


Line=142/ID=9: WHZ (3.117), Weight may be incorrect




Line=217/ID=17: WHZ (-4.086), HAZ (-5.887), WAZ (-5.508)


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=371/ID=5: WHZ (4.435), WAZ (3.112), Weight 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 : ##############################


problematic)


Digit preference MUAC:

Digit .0 : ################

Digit .1 : ################################

Digit .2 : ##############################

Digit .3 : ##############################

Digit .4 : ######################################

Digit .5 : ####################

Digit .6 : ####################################

Digit .7 : ############################

Digit .8 : ##############################

Digit .9 : ###############################


problematic)


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



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



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 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


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



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)



-------------------------------------------------------------------------------------

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



Overall age distribution: p-value = 0.242 (as expected)


Overall age distribution for girls: p-value = 0.545 (as expected)

Overall sex/age distribution: p-value = 0.075 (as expected)


-------------------------------------------------------------------------------------

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








-------------------------------------------------------------------------------------

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








-------------------------------------------------------------------------------------

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








-------------------------------------------------------------------------------------

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







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)





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)





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





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)





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





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)




(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 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:



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

Superv.(H1+H2)]

Supervisor 0.32 5/4



Enumerator 3 0.17 OK 6.67 POOR 1/7 5/4








MUAC:



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

Superv.(MUAC1+MUAC2]

Supervisor 26.00 4/4











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

n = 575

Boys

n = 294

Girls

n = 281

Prevalence of global

malnutrition


(11) 1.9 %

(0.9 - 3.9

95% C.I.)

(6) 2.0 %

(1.0 - 4.3

95% C.I.)

(5) 1.8 %

(0.6 - 4.9

95% C.I.)


malnutrition

(<-2 z-score and >=-3 z-score, no

oedema)

(11) 1.9 %

(0.9 - 3.9

95% C.I.)

(6) 2.0 %

(1.0 - 4.3

95% C.I.)

(5) 1.8 %

(0.6 - 4.9

95% C.I.)


malnutrition


(0) 0.0 %

(0.0 - 0.0

95% C.I.)

(0) 0.0 %

(0.0 - 0.0

95% C.I.)

(0) 0.0 %

(0.0 - 0.0

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

(<-3 z-score)

Moderate

wasting

(>= -3 and <-2

z-score )

Normal

(> = -2 z score)

Oedema

Age

(mo)

Total

no.

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

6-17 171 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

No. 0

(0.0 %)

Kwashiorkor

No. 0

(0.0 %)

Oedema absent Marasmic

No. 0

(0.0 %)

Not severely malnourished

No. 578

(100.0 %)

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

and by sex

All

n = 578

Boys

n = 296

Girls

n = 282

Prevalence of global

malnutrition


(11) 1.9 %

(0.8 - 4.6

95% C.I.)

(6) 2.0 %

(0.6 - 6.8

95% C.I.)

(5) 1.8 %

(0.6 - 4.9

95% C.I.)


malnutrition

(< 125 mm and >= 115 mm, no

oedema)

(9) 1.6 %

(0.6 - 3.8

95% C.I.)

(6) 2.0 %

(0.6 - 6.8

95% C.I.)

(3) 1.1 %

(0.3 - 3.3

95% C.I.)


malnutrition


(2) 0.3 %

(0.1 - 1.5

95% C.I.)

(0) 0.0 %

(0.0 - 0.0

95% C.I.)

(2) 0.7 %

(0.2 - 3.0

95% C.I.)

Table 3.6: 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. %

6-17 173 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

malnutrition

(<80% and/or oedema)

(7) 1.2 %

(0.6 - 2.4 95%

C.I.)

Prevalence of moderate acute

malnutrition

(<80% and >= 70%, no oedema)

(7) 1.2 %

(0.6 - 2.4 95%

C.I.)

Prevalence of severe acute

malnutrition

(<70% and/or oedema)

(0) 0.0 %

(0.0 - 0.0 95%

C.I.)

Table 3.6: 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. %

6-17 171 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

n = 572

Boys

n = 291

Girls

n = 281

Prevalence of underweight

(<-2 z-score)

(48) 8.4 %

(5.1 - 13.6

95% C.I.)

(22) 7.6 %

(4.2 - 13.1

95% C.I.)

(26) 9.3 %

(5.3 - 15.7

95% C.I.)


underweight


(36) 6.3 %

(3.8 - 10.4

95% C.I.)

(16) 5.5 %

(3.0 - 9.9

95% C.I.)

(20) 7.1 %

(4.1 - 12.2

95% C.I.)


underweight

(<-3 z-score)

(12) 2.1 %

(1.0 - 4.4

95% C.I.)

(6) 2.1 %

(0.9 - 4.4

95% C.I.)

(6) 2.1 %

(0.8 - 5.7

95% C.I.)

Table 3.8: 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. %

6-17 170 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

n = 564

Boys

n = 289

Girls

n = 275

Prevalence of stunting

(<-2 z-score)

(52) 9.2 %

(6.3 - 13.2

95% C.I.)

(19) 6.6 %

(4.0 - 10.5

95% C.I.)

(33) 12.0 %

(8.0 - 17.6

95% C.I.)

Prevalence of moderate stunting


(40) 7.1 %

(4.8 - 10.5

95% C.I.)

(13) 4.5 %

(2.8 - 7.1

95% C.I.)

(27) 9.8 %

(6.1 - 15.4

95% C.I.)

Prevalence of severe stunting

(<-3 z-score)

(12) 2.1 %

(1.1 - 4.0

95% C.I.)

(6) 2.1 %

(0.9 - 4.6

95% C.I.)

(6) 2.2 %

(1.0 - 4.5

95% C.I.)

Table 3.10: 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. %

6-17 171 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

n = 575

Boys

n = 294

Girls

n = 281

Prevalence of overweight (WHZ

> 2)

(4) 0.7 %

(0.2 - 2.3

95% C.I.)

(2) 0.7 %

(0.2 - 2.7

95% C.I.)

(2) 0.7 %

(0.2 - 2.9

95% C.I.)

Prevalence of severe overweight

(WHZ > 3)

(0) 0.0 %

(0.0 - 0.0

95% C.I.)

(0) 0.0 %

(0.0 - 0.0

95% C.I.)

(0) 0.0 %

(0.0 - 0.0

95% C.I.)

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

Overweight

(WHZ > 2)

Severe

Overweight

(WHZ > 3)

Age

(mo)

Total

no.

No. % 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-

scores ±

SD

Design

Effect (z-

score < -2)

z-scores

not

available*

z-scores

out of

range

Weight-for-

Height

575 -0.26±0.83 1.43 0 3

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 (dd/mm/yyyy)تاريخ المقابلة

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

|___|___|

|___|

سنوات 5أشهر إلى أقل من 6فال من عمر األط (12/2016– 07/2012) 2016الى كانون األول 2012تموز بين شهر(، ولدوا6-59)

المنفصلينمسح األطفال

A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12

رقم

الطفلHH رقم

األسرة

الجنس

(f/m) تاريخ الميالد

(DD/MM/YYYY)

ملئت العموداذا A4 انتقل الى ,

A6العمود

العمر

(شهور)

فقط إذا لم

يوجد لدينا

تاريخ

الميالد

بشكل دقيق

الوزن(kg)

(00.0)

الطول(cm)

(000.0)

*: إذا تم

ياس ق

الطفل

بطريقة

مغايرة لما

اتفق عليه

الوذمة

ثنائية

الجانب(y/n)

MUAC

قياس

محيط

منتصف

العضد(mm)

(000)

الذراع

اليسرى

HGB رقم

الخضاب

(mg) (00.0)

أنت هل األب/األم

لهذا الحقيقي أو )نعم الطفل؟

ال(

01نعم =

02ال =

في حال اإلجابة

ب ال أجب عن

A12السؤال

ما هي العالقة بين رب

األسرة )أنت( والطفل

= حفيد 08= ابن أو 09

ابنة أخ/ أخت

=أخ أو 10

=ابن 11أخت 12أو ابنة عم

= ليسوا أقارب

1 / /

2 / /

3 / /

4 / /

5 / /

6 / /

7 / /

8 / /

9 / /

10 / /


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

|___|___|

|___|

سنوات 5أشهر إلى أقل من 6فال من عمر األطالى كانون األول 2012تموز بين شهر(، ولدوا6-59)

2016 (07/2012 –12/2016)

األطفال المنفصلينمسح

A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12

رقم

الطفلHH رقم

األسرة

الجن

س

(f/m)

تاريخ الميالد(DD/MM/YY

YY)


A6العمود

العمر

(شهور)

فقط إذا لم

يوجد لدينا

تاريخ

الميالد

بشكل دقيق

الوزن(kg)

(00.0)

الطول(cm)

(000.0)

*: إذا تم

ياس ق

الطفل

بطريقة

مغايرة

لما اتفق

عليه

الوذمة

ثنائية

الجانب(y/n)

MUAC

قياس محيط

منتصف العضد(mm)

(000)

الذراع اليسرى

HGB رقم

الخضاب

(mg) (00.0)


الحقيقي لهذا

الطفل؟ ال( أو )نعم

01نعم =

02ال =

في حال

اإلجابة ب

ال أجب عن

السؤال

التالي A12

ما هي العالقة بين رب

األسرة )أنت( والطفل



=أخ أو 10

=ابن 11أخت 12أو ابنة عم

= ليسوا أقارب

11 / /

12 / /

13 / /

14 / /

15 / /

16 / /

17 / /

18 / /

19 / /

20 / /


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

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سنوات 5أشهر إلى أقل من 6فال من عمر األط (12/2016– 07/2012) 2016الى كانون األول 2012تموز بين شهر(، ولدوا6-59)

مسح األطفال المنفصلين

A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12

HH رقم الطفل رقم

األسرة

الجنس

(f/m) تاريخ الميالد

(DD/MM/YYYY)


A6العمود

العمر

(شهور)

فقط إذا

لم يوجد

لدينا

تاريخ

الميالد

بشكل

دقيق

الوزن(kg)

(00.0)

الطول(cm)

(000.0)

*: إذا

ياس قتم

الطفل

بطريقة

مغايرة

لما اتفق

عليه

الوذمة

ثنائية

الجانب(y/n)

MUAC

قياس

محيط

منتصف

العضد(mm)

(000)

الذراع

اليسرى

HGB رقم

الخضاب

(mg) (00.0)


لهذا الحقيقي أو )نعم الطفل؟

ال(

01نعم =

02ال =

في حال اإلجابة

ب ال أجب عن

السؤال التالي A12

ما هي العالقة بين رب األسرة )أنت( والطفل



=أخ أو أخت 10=ابن أو ابنة 11= ليسوا 12عم

أقارب

21 / /

22 / /

23 / /

24 / /

25 / /

26 / /

27 / /

28 / /

29 / /

30 / /

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