Model nutrition assessment report (based on the … · Web view2017/01/02 · Eastern Ghouta is part of Rural Damascus governorate, and it is besieged area for about 5 years, the

nutrition assessment report

Report of SMART Nutrition Survey Eastern Ghouta – Rural Damascus of (Syria) during (5/1/2017 to 14/1/2017).

(?? Feb 2017)

Implemented by: Syrian Development International

Technical support: Physicians Across continents –Turkey & CDC/Atalanta

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Table of ContentsAcknowledgement..............................................................................................................................................4List of Acronyms................................................................................................................................................5Executive summary............................................................................................................................................61. Introduction....................................................................................................................................................7

1.1 Geographic description of survey area.....................................................................................................71.2 Survey Objectives....................................................................................................................................7

2. Methodology..................................................................................................................................................92.1 Sample size...............................................................................................................................................92.2 Sampling procedure: selecting clusters..................................................................................................102.3 Sampling procedure: selecting households and children.......................................................................112.4 Case definitions and inclusion criteria...................................................................................................112.5 Questionnaire, training and supervision.................................................................................................11

Questionnaire...........................................................................................................................................11Survey teams and supervision..................................................................................................................11Training....................................................................................................................................................12

2.6 Data analysis..........................................................................................................................................122.7 Characteristic of the sample...................................................................................................................12

3. Results..........................................................................................................................................................153.1 Prevalence of acute malnutrition based on weight-for-height z-scores.................................................153.2: Prevalence of underweight based on weight-for-age z-score (WAZ)...................................................163.3: Prevalence of stunting based on height-for-age z-score (HAZ)............................................................173.4: Prevalence of overweight based on weight for height z-score (HAZ)..................................................18

4. Discussion....................................................................................................................................................204.1 Nutritional status....................................................................................................................................204.2 Causes of malnutrition...........................................................................................................................20

5. Conclusions..................................................................................................................................................206. Recommendations and priorities..................................................................................................................207. References....................................................................................................................................................208. Acknowledgements......................................................................................................................................209. Annex...........................................................................................................................................................22

Annex 1 Plausibility Report.....................................................................................................................22Annex 2 Assignment of Clusters............................................................................................................33Annex 3 Standardization test : Evaluation of Enumerators..............................................................34Annex 4 Result Tables for NCHS growth reference 1977................................................................36Annex 5 maps of surveyed area.............................................................................................................40Annex 6 Questionnaire........................................................................................................................43Annex 7 cluster control form................................................................................................................44Annex 8: calendar events.............................................................................................................................45Annex 9: referral form...............................................................................................................................46Annex 10: training agenda.......................................................................................................................47

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Acknowledgement

This survey would not have been possible without the financial support of Nutrition Cluster members for the Northern Syria operations based in Gaziantep and Hatay, in Southern Turkey. The technical support for the survey was provided by Action Against Hunger Canada funded by OFDA-USAID and the Centers for Disease Control and Prevention (CDC). A profound thank you also to the survey teams for their dedication and attention to detail as well as all village leaders, local council and guides for their willingness to assist where needed. Involvement of the mothers and caregivers, particularly for giving their time to answer interview questions is extremely appreciated, without whom the collection of required data would have been impossible.

In addition to those mentioned above, special appreciation goes to the Syrian NGOs implementing interventions inside Syria, who led the survey field work. In particular Physicians Across Continents (PAC) led the entire field level coordination, co-facilitated the survey training, contributed to the survey protocol preparation, field level data collection including field supervision and drafting of the report. Syrian American Medical Society (SAMS) contributed to the survey protocol preparation and field level data collection. The survey team is also grateful to the EPI task force for Northern Syria for providing April 2015 polio campaign results in Aleppo, which assisted in the sampling design.

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List of Acronyms

CDC Centers for Disease Control and Prevention CI Confidence Interval ENA Emergency Nutrition Assessment GAM Global Acute Malnutrition HAZ Height-for-Age Z-Scores HFA Height-for-Age IYCF Infant and Young Child Feeding IYCF-E Infant and Young Child Feeding in Emergencies MAM Moderate Acute Malnutrition MUAC Mid-Upper Arm CircumferenceNGO Non-Governmental Organization PAC Physicians Across Continents (NGO)PPS Probability Proportional to Size PSU Primary Sampling Unit RC Reserve Cluster SAM Severe Acute Malnutrition SD Standard DeviationSDI Syrian Development International (NGO)SMART Standardized Monitoring and Assessment of Relief and TransitionsSRP Strategic Response PlanUNICEF United Nations Children’s Fund WAZ Weight-for-Age Z-Scores WFA Weight-for-Age WFH Weight-for-Height WHO World Health Organization WHZ Weight-for-Height Z-Scores

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Executive summary 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) 13 2.1 % ( 1.2- 3.5 95% CI)

Prevalence of moderate acute malnutrition(WFH <-2 z-score and >=-3 z-score, no edema) 11 1.8 % ( 0.9- 3.2 95% CI)

Prevalence of severe acute malnutrition(WFH <-3 z-score and/or edema) 2 0.3 % ( 0.1- 1.3 95% CI)

Prevalence of underweight based on weight-for-age z-scores1

Prevalence of underweight(WFA <-2 z-score) 60 9.6 % ( 7.4-12.3 95% CI)

Prevalence of moderate underweight(WFA <-2 z-score and >=-3 z-score) 52 8.3 % ( 6.2-11.1 95% CI)

Prevalence of severe underweight(WFA <-3 z-score) 8 1.3 % ( 0.7- 2.4 95% CI)

Prevalence of stunting based on height-for-age z-scores1

Prevalence of stunting( HFA <-2 z-score) 191 30.5 % (25.7-35.8 95% CI)

Prevalence of moderate stunting(HFA <-2 z-score and >=-3 z-score) 140 22.4 % (18.3-27.0 95% CI)

Prevalence of severe stunting(HFA <-3 z-score) 51 8.1 % ( 5.9-11.1 95% CI)

Prevalence of overweight based on weight for height cut-offs1

Prevalence of overweight (WHZ > 2) 18 2.9 % (1.6 - 5.2 95% C.I.)

Prevalence of severe overweight (WHZ > 3) 3 0.5 % (0.1 - 2.1 95% C.I.)

· geographic area surveyed and population type · dates of survey· methodology used (sampling, sample size, main indicators)· main anthropometric results (prevalence of global and severe acute

malnutrition in terms of z-scores and/or oedema and 95% confidence intervals)

· brief interpretation of the results· recommendations.

1 Based on WHO Child Growth Standards (2006)

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1. Introduction

The conflict in the Syrian Arab Republic, which began in March 2011, has now entered its fifth year with violence increasing in scale and intensity. Security risks and deteriorating socio-economic conditions have resulted in an estimated 6.5 million internally displaced people (IDPs) within Syria and 10.8 million Syrians in need of humanitarian assistance (Syria SRP, 2015).The estimated number of people in need 13.5% and 6.5 M IDPs (SRP 2016) , People in need nutrition services 3.94 M (SRP 2016) These include acutely malnourished children, children at risk of under-nutrition, and pregnant and lactating women.

Poor nutritional status was present prior to the current crisis, with reported 23% of children under-five being stunted, 9.3% being wasted and 10.3% underweight (Syria Family Health Survey, MoH, 2009). Sub-optimal IYCF and micronutrient deficiencies (vitamin A, iron and iodine) also existed. A series of Rapid Nutrition Assessments conducted by UNICEF in collaboration with Syria MOH and Central Bureau of Statistics in 13 governorates between March and July 2014 indicated 7.2% Global Acute Malnutrition (GAM) and 2.3% Severe Acute Malnutrition (SAM). A SMART survey conducted in Idleb governorate in June 2014 showed a prevalence of GAM to be 1.2% (0.6-2.3%). A SMART survey in Aleppo and Hama in June 2015 showed a prevalence of GAM to be 1.3 % and 2.4 % respectively. A Rapid MUAC assessment in the Ghouta in 2016 showed a prevalence of GAM to be 6.4 %, and rapid MUAC assessment in rural Damascus in January 2016 showed prevalence of GAM 6.4 %

Population groups considered most vulnerable to malnutrition include IDPs, children, pregnant women, and lactating mothers. IDP families have resorted to negative coping mechanisms such as borrowing money, selling assets and property, and sending children to work in order to meet their basic food needs. The ability of host communities to sustain support to the IDPs is fast diminishing.

1.1 Geographic description of survey areaEastern Ghouta is part of Rural Damascus governorate, and it is besieged area for about 5 years, the survey had been conducted in the accessible area an it was five sub-district:(Kafr Batna\ بطنا \Duma , عربين\Arbin , كفر دوما \Nashabiyeh , حرستا\Harasta , مركز(.النشابيةThe total area is about 96 Km2, Annex 5 shows google maps photo of the area.The total population of the area is about 306,000 people, about 97,000 of them are IDPs, most of them are Muslim Sunni.All these areas are rural area, and they are agriculture areas, most of the people depend on agriculture, and some of them depend on the NGOs support. Because of the besiegement there are some NGOs who work in this area, most of them working in Health, nutrition, Food security sectors, there are an acceptable access to health and nutrition facilities. there are some foods cross into to the area through the tunnels, and these foods are sold at expensive prices.

1.2 Survey ObjectivesThe ongoing conflict has aggravated pre-existing nutritional concerns in Syria, as food security and water, sanitation, and health care services have deteriorated, and inappropriate IYCF practices have increased. These factors are potentially predisposing the population to risk of diarrhoea, insufficient micronutrient intake, and under-nutrition. Given the above context, the need to better understand the nutrition situation and to closely monitor the situation was identified as one of the priority undertakings within the 2015 Syria strategic response plan. The whole of Syria nutrition sector advocates implementation of the nutrition assessments in all the 14 governorates either through

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cross-line or cross-border operations. The successful SMART survey completed in one governorate (Idleb) in 2014 indicates that with proper training and logistics, high quality SMART surveys are feasible inside Syria. The 2014 successful implementation of SMART and the increasing demand for updated nutrition situation to base response on are the key motivation to conduct nutrition surveys in Aleppo and Hama.This standard protocol for nutrition survey will be adopted in the implementation of other nutrition assessment inside Syria in the future, as an effort to standardizing data quality in Syria and facilitate comparison of dataThe purpose of this survey is to:

Provide updated information on the nutritional situation of children 6-59 months in the besieged area in the Eastern Ghouta.

To measure the prevalence of acute malnutrition in children aged 6-59 months. To measure the prevalence of stunting in children aged 6-59 months.

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2. Methodology

2.1 Sample size Because there are many communities in the area and they are all about the same

conditions we used the Cluster sampling in this survey To calculate the sample size The following assumptions (table 2.1) based on the

given context were made to obtain the number of children to survey:Table 2.1 : Number of children / calculation parameters

Parameters Ghouta Assumptions

Estimated Prevalence of GAM 6.4 % In the Rapid MUAC assessment in the eastern Ghouta in

2016 the GAM rate was 6.4 %

Desired precision ±3%The desired precision for this survey (± 3%) was chosen based on SMART recommendations for the estimated GAM prevalence (± 3% for estimated prevalence <10%).

Design Effect 1.5The 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.

Children to be included 418 Based on the above three parameters, using ENA

software.

The SMART Methodology recommends converting the number of children into number of households (fixed household method) for the numerous reasons: it is easier to create lists of households than lists of children in the field; sample sizes calculated in number of children can encourage teams to skip households without any children (thus introducing a bias for household-level indicators); and households can provide a common metric for comparing sample size of many indicators. In order to do the conversion of number of children to sample into number of households, the following assumptions were made (table 2.2):

Table 2.2 : Number of household calculation parameters

Parameters Ghouta Assumptions

Average HH Size 5 The calculated household size for MUAC assessment in Ghouta was 5 and the same was used.

% Children under-5 16%

The proportion of under-five based on the Nutrition Cluster data for the 2017 response. The concentration of U5 in some locations are higher as noted in the earlier surveys. Nevertheless, 16 % is used for this survey.

% Non-response Households 8 %

A non-response rate of 8.2 % was observed during the MUAC assessment in Ghouta in 2016. The same rate is expected and used in this survey

Households to be included 630

Based on the above three parameters, using ENA software.

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The number of households to be completed per day will be 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 4.30 pm.2. Average travel time to reach each cluster (one-way): 30 min.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: 10 min.6. Breaks: One lunch break of 45 min.

The above gives on average 5:15 h (315 min) of working time in each cluster. If on average teams will spend 10 min in each HH and 5 min traveling from one HH to another, each team can comfortably reach 21 HH per day. Each team is to be composed of two persons (with at least one female enumerator)

The total number of households in the sample was then divided by the number of households to be completed in one day to get the number of clusters to be included in the survey. The number of clusters was based on visiting 21 HH per day. If we assume one day in each area (cluster):

630 HH/ 21 HH per day = 30 clusters

What sampling methodology (e.g., systematic random sampling, cluster sampling, etc.) did you chose? Why?

How did you calculate the sample size for anthropometry? (show the sample size calculation, including assumptions for expected prevalence, expected DEFF [if cluster sampling], required precision); if number of children was converted into the number of households, describe how this was done

How did you calculate the sample size for mortality? (show the sample size calculation, including assumptions for expected CMR, expected DEFF [if cluster sampling], required precision)

Describe whether sample sizes were adjusted for non-response, and if yes, justify the predicted non-response rate

If both mortality and anthropometry was measured, how did you reconcile sample sizes?

If cluster sampling, how did you decide how many clusters and how many households per cluster?

2.2 Sampling procedure: selecting clusters

Due to the large size of the population of interest, the large communities divided to a small segment, then these population data used to select the clusters, Clusters will be selected using the PPS (Probability Proportional to size) method.

A complete sampling frame was built using population data collected by a 3-logistics person who collected these data. All settlement locations included in the sampling frame were determined to be accessible for the teams. In building the sampling frame, all villages with less than 30 children were combined with the nearest village to avoid random selection of a cluster too few children to complete the cluster. In addition, all large communities divided to small segments with about 250 HH in each segment. The sampling frame was transferred to ENA for SMART software to randomly select 30 clusters and 4 reserve clusters. Clusters have been selected using the PPS (Probability Proportional to size)

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method. The sampling frames for the survey including the selected samples are provided in the Annex 2

2.3 Sampling procedure: selecting households and children

We used the simple random sampling method to select the HH in all clusters, we get an updated lists of all HH in the clusters and then used the ENA software to select randomly 21 HH from each list

If the HH was absent, the teams revisited the HH at the end of the day and complete the questionnaire or noted in the cluster control form that the HH is absent after re vested and this HH was not replaced with another HH.

2.4 Case definitions and inclusion criteria

For this survey, we used this definition of HH: All members who live under the same roof and eat from the same spot.

All children aged from 6 to 59 month included in the measurement, we used the accurate birthdate of the children (ID cards, birth reports, immunization cards), and we used the Calendar events (Annex 8 ) to determine the age of the children if the birthday is not known.

We used the measurement of weight, length or height and oedema to determine the nutrition statues of the children

We measured the length (laying down) for all children 6 -23 month , and measured height (standing up) for all children 24 – 59 month.

All children with oedema or Z-score for weight for height under -2 should be referred using the referral form (Annex 9) to the nearest nutrition or health facility to get the treatment.

All cases of oedema should be re checked by the supervisor and should be documented (no cases of bilateral oedema was founded)

We used the WHO 2006 standards to calculate the z-scores at the field and decide to refer the child.

2.5 Questionnaire, training and supervision

Questionnaire the questionnaire of this survey was in Arabic and all interviews in the field were in

Arabic. The data Anthropometric data collected was Length or Height and weight, no

other data had been collected, Annex 6 shows the questionnaire used in this survey

A cluster control form had been used to manage the HH visits and collect the require data about the HH, Annex 7 shows the Cluster control form used in the survey.

Survey teams and supervision One supervisor and three teams had been chosen for this survey, most of them

work as a community health works with the local NGOs and most of them had a background about malnutrition.

Each team was consisted of 3 members (one team leader and two enumerator) each team consist of one male and two female members.

Each team completed one cluster per day, the supervisor accompanied one team each day

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Training The training was conducted online (webinar training) through webex.com, the

trainers from PAC staff were based in Gaziantep – Turkey 17 enumerator attended the training (14 female and 3 male) and one supervisor. The training was in one training centre The training was ?? days, 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, determine the age of the children) the training agenda in the Annex 10.

An anthropometry standardization test was conducted, ten children two of them under 2 years was measured twice from all trainees, the supervisor measurement was use to compare the measurements, (we tried to do a standardization test in the first day but we could not finish it due to security reasons and the children had been gone to their homes, so we repeated the standardization test next day with new 10 children)

After the standardization test the three teams had been chosen according to their results in the standardization test, Annex 3 shows the result of the Standardization test

2.6 Data analysis

One data entry in the field entered the data to the ENA 2011 software (July 2015) in a daily basis, and the data were sending in a daily basis to PAC staff the data were being reviewed in a daily basis and if there is comment it was sending to the field every day

a second data entry in Gaziantep re-entered the data into the ENA 2011 software (the questionnaire was scanned and sent to the second data entry)

a double data entry check had been done and the mistakes corrected. The data had been analysed using the WHO 2006 standards and using the ENA

software, the analysis was conducted in PAC Gaziantep office with the support of CDC/ Atalanta

No exclusion had been applied for Z-score (one cases was excluded because z-score not available)

2.7 Characteristic of the sample A total of 627 children, 297 boys and 330 girls, aged 6-59 months from 608 households in 30 clusters in Eastern Ghouta – Rural Damascus were included in the survey and assessed for their anthropometric status. 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%. Of the 627 children, 626 (297 boys and 329 girls) were included in the analysis (1 missing weight and height). The household non-response was 22 HH (17 absent and 5 refuse) indicating that 3.5 % of households 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). 30 clusters (630 HH) were originally planned and all clusters had been visited. A 549 HH from the 625 surveyed HH were a 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 distribution of the assessed children sex shows boys and girls were equally represented (p=0.617) with the overall sex ratio of 1.0 as expected (Table 6). The age ratio of 6-29 months to 30-59 months (1.32) (The value should be around 0.85): p-value = 0.000 (significant difference)

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https://www.webex.com/

You can see the Statistical evaluation of sex and age ratios (using Chi squared statistic) in the ENA Plausibility Report (Annex 1 )

The total number of 6-59 month children included (observed) in the survey, 626, exceeded the planned requirement of 418 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. For example, a randomly selected household may contain two 6-59 month children but only one was included in the survey because the second child was away visiting their grandparents. A total of 98.9% of eligible 6-59 month children were included in the survey.

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

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

418 627 150 % 634 627 98.9 %

Table 2.4: Percent of household non-response

Number of HH planned*

Number of HH surveyed

% HH Non-Response

630 608 3.5 %

Table 2.5 : Distribution of age and sex of sample

Boys Girls Total Ratio

AGE (mo) no. % no. % no. % Boy:girl

6-17 90 45.5 108 54.5 198 31.6 0.8

18-29 77 48.4 82 51.6 159 25.4 0.9

30-41 50 49.5 51 50.5 101 16.1 1.0

42-53 51 49.5 52 50.5 103 16.4 1.0

54-59 29 43.9 37 56.1 66 10.5 0.8

Total 297 47.4 330 52.6 627 100.0 0.9

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Figure 2.1: Population age and sex pyramid

the age distribution shows a higher number of younger children than the old children, The age ratio of 6-29 months to 30-59 months (1.32), this also found in most of SMART survey in Syria (

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3. Results

The overall quality of the survey as evaluated by the ENA software is reported as good, with plausibility score of 14 as shown in the ENA Plausibility Report (Annex 1)

Anthropometric results (based on WHO standards 2006) No Exclusion of Z- score had been appliedfor anthropometric results based on NCHS growth reference 1977 see Annex 4

3.1 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, in Eastern Ghouta was ‐ 2.1% (1.2- 3.5 95% CI), and the prevalence of severe acute malnutrition (SAM), defined as WHZ < 3 and/or edema, was ‐ 0.3% (0.1- 1.3 95% CI), with no cases of edema found (Table 3.1).

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

Table 3.1: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex

Alln = 626

Boysn = 297

Girlsn = 329

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

(13) 2.1 %(1.2 - 3.5 95% C.I.)

(4) 1.3 %(0.5 - 3.5 95% C.I.)

(9) 2.7 %(1.6 - 4.8 95% C.I.)

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

(11) 1.8 %(0.9 - 3.2 95% C.I.)

(4) 1.3 %(0.5 - 3.5 95% C.I.)

(7) 2.1 %(1.1 - 4.1 95% C.I.)

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

(2) 0.3 %(0.1 - 1.3 95% C.I.)

(0) 0.0 %(0.0 - 0.0 95% C.I.)

(2) 0.6 %(0.1 - 2.5 95% C.I.)

The prevalence of oedema is 0.0 % (no cases of oedema had been identified)

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

Severe wasting(<-3 z-score)

Moderate wasting

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

Normal(> = -2 z score)

Oedema

Age (mo)

Total no.

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

6-17 198 1 0.5 6 3.0 191 96.5 0 0.018-29 159 0 0.0 3 1.9 156 98.1 0 0.030-41 100 0 0.0 1 1.0 99 99.0 0 0.042-53 103 0 0.0 0 0.0 103 100.0 0 0.054-59 66 1 1.5 1 1.5 64 97.0 0 0.0Total 626 2 0.3 11 1.8 613 97.9 0 0.0

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Table 3.3: Distribution of acute malnutrition and oedema based on weight-for-height z-scores

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

No. 0(0.0 %)

KwashiorkorNo. 0

(0.0 %)Oedema absent Marasmic

No. 2(0.3 %)

Not severely malnourishedNo. 624

(99.7 %)

3.2: 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 9.6 % (7.4 – 12.3 95% C.I.) with 1.3% (0.7 – 2.4 95% C.I.) severely underweight,‐ defined as Weight-for-Age Z scores (WAZ) < 3 (Table 3.4). a higher prevalence of underweight‐ between girls were reported boys (6.7%) and girls (12.2%). A similar prevalence of underweight by age group was observed with a bit higher prevalence among the age group (6 - 17 months) (11.1%) (Table 3.5).

Table 3.4: Prevalence of underweight based on weight-for-age z-scores by sex

Alln = 626

Boysn = 297

Girlsn = 329

Prevalence of underweight(<-2 z-score)

(60) 9.6 %(7.4 - 12.3 95% C.I.)

(20) 6.7 %(4.6 - 9.8 95% C.I.)

(40) 12.2 %(9.0 - 16.2 95% C.I.)

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

(52) 8.3 %(6.2 - 11.1 95% C.I.)

(18) 6.1 %(3.9 - 9.3 95% C.I.)

(34) 10.3 %(7.3 - 14.5 95% C.I.)

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

(8) 1.3 %(0.7 - 2.4 95% C.I.)

(2) 0.7 %(0.2 - 2.8 95% C.I.)

(6) 1.8 %(0.9 - 3.9 95% C.I.)

Table 3.5: Prevalence of underweight by age, based on weight-for-age z-scores

Severe underweight(<-3 z-score)

Moderate underweight(>= -3 and <-2

z-score )


Oedema

Age (mo)

Total no.

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

6-17 198 4 2.0 18 9.1 176 88.9 0 0.018-29 159 1 0.6 15 9.4 143 89.9 0 0.030-41 100 1 1.0 8 8.0 91 91.0 0 0.042-53 103 1 1.0 7 6.8 95 92.2 0 0.054-59 66 1 1.5 4 6.1 61 92.4 0 0.0Total 626 8 1.3 52 8.3 566 90.4 0 0.0

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3.3: 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 30.5 % (25.7 - 35.8 95% C.I.) with 8.1 % (5.9 - 11.1 95% C.I.) severely stunted, defined as height-for-age Z scores (HAZ) < 3 (Table 3.6). The difference between boys (28.3%) and girls ‐(32.5%) was not statistically significant (p= 0.74187). Stunting peaked amongst the age group of 30-41 months (45%) (Table 3.7).

Table 3.6: Prevalence of stunting based on height-for-age z-scores and by sex

Alln = 626

Boysn = 297

Girlsn = 329

Prevalence of stunting(<-2 z-score)

(191) 30.5 %(25.7 - 35.8 95% C.I.)

(84) 28.3 %(22.4 - 35.0 95% C.I.)

(107) 32.5 %(26.5 - 39.1 95% C.I.)

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

(140) 22.4 %(18.3 - 27.0 95% C.I.)

(62) 20.9 %(16.4 - 26.3 95% C.I.)

(78) 23.7 %(18.6 - 29.8 95% C.I.)

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

(51) 8.1 %(5.9 - 11.1 95% C.I.)

(22) 7.4 %(4.8 - 11.2 95% C.I.)

(29) 8.8 %(6.0 - 12.8 95% C.I.)

Figure 3.1: ???????

Table 3.7: Prevalence of stunting by age based on height-for-age z-scores

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Severe stunting(<-3 z-score)

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

score )Normal

(> = -2 z score)

Age (mo)

Total no. No. % No. % No. %

6-17 198 11 5.6 27 13.6 160 80.818-29 159 11 6.9 39 24.5 109 68.630-41 100 14 14.0 31 31.0 55 55.042-53 103 11 10.7 24 23.3 68 66.054-59 66 4 6.1 19 28.8 43 65.2Total 626 51 8.1 140 22.4 435 69.5

3.4: 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 2.9 % (1.6 - 5.2 95% C.I.). 0.5 % (0.1 - 2.1 95% C.I.) of a severely overweight (defined as weight-for-height Z scores (WHZ) > 3) (Table 3.8). The difference between girls (4.1%) and boys (3%) was not significant (p=0.474). Prevalence of overweight was highest amongst the age groups (30-53 months) (Table 3.9).

Table 3.8: Prevalence of overweight based on weight for height cut off's and by sex (no oedema)

Alln = 626

Boysn = 297

Girlsn = 329

Prevalence of overweight (WHZ > 2)

(18) 2.9 %(1.6 - 5.2 95% C.I.)

(7) 2.4 %(1.0 - 5.2 95% C.I.)

(11) 3.3 %(1.6 - 6.7 95% C.I.)

Prevalence of severe overweight (WHZ > 3)

(3) 0.5 %(0.1 - 2.1 95% C.I.)

(2) 0.7 %(0.2 - 2.8 95% C.I.)

(1) 0.3 %(0.0 - 2.2 95% C.I.)

Table 3.9: 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. %

6-17 198 2 1.0 0 0.018-29 159 5 3.1 1 0.630-41 100 4 4.0 1 1.042-53 103 6 5.8 1 1.054-59 66 1 1.5 0 0.0

page 18 of 47

Total 626 18 2.9 3 0.5

Table 3.10: 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 626 0.21±1.02 1.00 1 0

Weight-for-Age 626 -0.63±1.03 1.00 1 0

Height-for-Age 626 -1.38±1.34 1.78 1 0* contains for WHZ and WAZ the children with edema.

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4. Discussion

4.1 Nutritional status

discuss sample sex ratio — any bias? If so, explain why you think there is bias prevalence of acute malnutrition if previous survey results are available, how do these results compare to before,

or to other areas nearby? how does the prevalence compare to national benchmarks of malnutrition? Is the prevalence of malnutrition typical or not?

4.2 Causes of malnutrition

What are the major acute causes of malnutrition and where possible the causes of mortality (taking into account causes already addressed by other interventions)? Consider immediate, underlying and basic causes.

What are the prospects for the coming months? Will the situation get better or worse (refer to seasonal changes etc)

Who is worst affected? What are the chronic causes of malnutrition? What does the community recommend? Does the story fit together? If not what are the unanswered questions A diagram to show the causal framework of malnutrition may be useful.

5. Conclusions

Overall conclusions on the severity of the situation and the urgency of the response required

6. Recommendations and priorities

Remember to prioritise recommendations and try to give a time when action would be appropriate (e.g, immediate, medium term or longer term).

Future nutrition monitoring Is it necessary to carry out another nutrition survey in this area in the near future?

Who should do it? Should there be any changes to the survey methodology? When should the survey take place?

Should there be food security indicator monitoring in this area? Who should do it?

7. References

List all secondary sources to which you have referred in the text.

8. Acknowledgements

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1. List all government departments, International agencies, International NGOs, National NGOs and other organisations that supported or participated in the survey. (All involved in planning the survey and those organisations or individuals who have provided staff, vehicles, equipment, logistics).2. List donors and other sources of funds3. List the individuals involved in the survey

Supervisor/Manager:Consultants/ Trainers/ Advisors/ analysists:Logistics/administration: Team members:Translators:Drivers:Others

4. (Optional) List those who gave permission/ authorisation and otherwise supported the survey in a non-participatory way.

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9. Annex

Annex 1 Plausibility ReportPlausibility check for: Eastern Ghouta.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 (0.8 %)

Overall Sex ratio Incl p >0.1 >0.05 >0.001 <=0.001 (Significant chi square) 0 2 4 10 0 (p=0.188)

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 2 (10)

Dig pref score - height Incl # 0-7 8-12 13-20 > 20 0 2 4 10 2 (9)

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

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 0 (0.93)

Skewness WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 0 (-0.08)

Kurtosis WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 0 (0.00)

Poisson dist WHZ-2 Excl p >0.05 >0.01 >0.001 <=0.001 0 1 3 5 0 (p=0.419)

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

The overall score of this survey is 14 %, this is good.

There were no duplicate entries detected.

Missing or wrong data:

WEIGHT: Line=533/ID=12HEIGHT: Line=533/ID=12

Percentage of children with no exact birthday: 10 %

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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=7/ID=7: HAZ (-4.819), WAZ (-3.696), Age may be incorrect Line=63/ID=2: WHZ (7.959), HAZ (-8.490), Height may be incorrect Line=90/ID=29: WHZ (4.052), HAZ (-4.777), Height may be incorrect Line=105/ID=13: HAZ (1.898), Age may be incorrect Line=157/ID=15: HAZ (2.042), Age may be incorrect Line=170/ID=4: HAZ (2.573), Age may be incorrect Line=230/ID=19: HAZ (-4.965), Age may be incorrect Line=319/ID=16: HAZ (2.293), Age may be incorrect Line=325/ID=1: HAZ (-4.506), WAZ (-3.920), Age may be incorrect Line=368/ID=1: HAZ (-4.941), Age may be incorrect Line=396/ID=14: HAZ (-4.656), Age may be incorrect Line=411/ID=2: HAZ (-4.387), Age may be incorrect Line=425/ID=16: WHZ (-3.040), WAZ (-4.363), Weight may be incorrect Line=434/ID=8: HAZ (-4.728), Age may be incorrect Line=443/ID=17: HAZ (3.507), Age may be incorrect Line=444/ID=18: HAZ (5.814), WAZ (3.580), Age may be incorrect Line=459/ID=15: HAZ (1.700), Age may be incorrect Line=465/ID=2: HAZ (3.225), Age may be incorrect Line=509/ID=11: HAZ (-5.739), Age may be incorrect Line=541/ID=1: WAZ (-4.280), Weight may be incorrect Line=556/ID=16: HAZ (1.820), Age may be incorrect Line=564/ID=24: HAZ (1.714), Age may be incorrect Line=581/ID=16: HAZ (2.401), Age may be incorrect Line=585/ID=20: HAZ (-4.758), Age may be incorrect Line=588/ID=1: HAZ (1.674), Age may be incorrect Line=593/ID=6: HAZ (-4.748), Age may be incorrect Line=620/ID=15: WHZ (-3.962), WAZ (-3.695), Weight may be incorrect Line=622/ID=17: WHZ (3.591), Weight may be incorrect

Percentage of values flagged with SMART flags:WHZ: 0.8 %, HAZ: 3.8 %, WAZ: 1.0 %

Age distribution:

Month 6 : #######Month 7 : #############Month 8 : #########################Month 9 : #####################Month 10 : ############Month 11 : #############Month 12 : ####################Month 13 : ################Month 14 : #################page 23 of 47

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: 1.32 (The value should be around 0.85).: p-value = 0.000 (significant difference)

Statistical evaluation of sex and age ratios (using Chi squared statistic): page 24 of 47

Age cat. mo. boys girls total ratio boys/girls ------------------------------------------------------------------------------------- 6 to 17 12 90/68.9 (1.3) 108/76.6 (1.4) 198/145.5 (1.4) 0.8318 to 29 12 77/67.2 (1.1) 82/74.7 (1.1) 159/141.8 (1.1) 0.9430 to 41 12 50/65.1 (0.8) 51/72.4 (0.7) 101/137.5 (0.7) 0.9842 to 53 12 51/64.1 (0.8) 52/71.2 (0.7) 103/135.3 (0.8) 0.9854 to 59 6 29/31.7 (0.9) 37/35.2 (1.1) 66/66.9 (1.0) 0.78------------------------------------------------------------------------------------- 6 to 59 54 297/313.5 (0.9) 330/313.5 (1.1) 0.90

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

Overall sex ratio: p-value = 0.188 (boys and girls equally represented)Overall age distribution: p-value = 0.000 (significant difference)Overall age distribution for boys: p-value = 0.006 (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: 10 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.000 (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: 9 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.000 (significant difference) page 25 of 47

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: 0 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 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: 1.02 0.97 0.93 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 2.1% calculated with current SD: 1.5% calculated with a SD of 1: 1.4%

HAZ Standard Deviation SD: 1.34 1.31 1.11 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 30.5% 30.4% 29.7% calculated with current SD: 32.1% 31.4% 28.8% calculated with a SD of 1: 26.7% 26.3% 26.8%

WAZ Standard Deviation SD: 1.03 1.03 0.97 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 9.6% 9.6% calculated with current SD: 9.1% 9.1% calculated with a SD of 1: 8.5% 8.5%

Results for Shapiro-Wilk test for normally (Gaussian) distributed data: WHZ p= 0.000 p= 0.015 p= 0.823 HAZ p= 0.000 p= 0.000 p= 0.124 WAZ p= 0.013 p= 0.013 p= 0.663 (If p < 0.05 then the data are not normally distributed. If p > 0.05 you can consider the data normally distributed)

Skewness WHZ 0.60 -0.09 -0.08 HAZ 0.14 0.39 0.12 WAZ -0.15 -0.15 -0.03 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.

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-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 5.62 0.88 0.00 HAZ 2.82 1.94 -0.31 WAZ 0.74 0.74 -0.07 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=1.03 (p=0.419)GAM: ID=1.03 (p=0.419)HAZ < -2: ID=1.83 (p=0.004)HAZ < -3: ID=1.33 (p=0.108)WAZ < -2: ID=1.09 (p=0.332)WAZ < -3: ID=0.93 (p=0.572)

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: 1.03 (n=30, f=0) ########## 02: 1.71 (n=30, f=1) ###################################### 03: 0.84 (n=30, f=0) ## 04: 0.77 (n=30, f=0) 05: 0.88 (n=30, f=0) #### 06: 1.04 (n=30, f=0) ########## 07: 1.07 (n=30, f=0) ########### 08: 0.68 (n=30, f=0) 09: 0.84 (n=30, f=0) ## 10: 1.16 (n=30, f=0) ############### 11: 0.71 (n=30, f=0) 12: 0.87 (n=28, f=0) ### 13: 1.05 (n=28, f=0) ########### 14: 0.83 (n=27, f=0) # 15: 1.27 (n=27, f=1) #################### 16: 1.27 (n=26, f=1) ####################

page 27 of 47

17: 1.02 (n=26, f=1) ######### 18: 0.95 (n=23, f=0) ###### 19: 1.02 (n=20, f=0) ######### 20: 0.89 (n=18, f=0) #### 21: 0.82 (n=17, f=0) # 22: 0.74 (n=16, f=0) 23: 1.05 (n=12, f=0) OOOOOOOOOOO 24: 0.88 (n=10, f=0) OOO 25: 1.12 (n=08, f=0) ~~~~~~~~~~~~~~ 26: 0.93 (n=04, f=0) ~~~~~ 27: 0.17 (n=02, f=0)

(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)

Analysis by Team

Team 1 2 3 n = 205 233 189 Percentage of values flagged with SMART flags: WHZ: 2.0 0.9 0.0 HAZ: 4.4 4.3 3.2 WAZ: 2.0 0.9 0.5 Age ratio of 6-29 months to 30-59 months:

1.25 1.33 1.39 Sex ratio (male/female):

0.90 0.89 0.91 Digit preference Weight (%): .0 : 5 4 2 .1 : 10 19 13 .2 : 16 9 5 .3 : 7 7 13 .4 : 7 7 12 .5 : 8 12 10 .6 : 8 7 13 .7 : 8 9 10 .8 : 16 12 11 .9 : 14 14 12 DPS: 12 13 12 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference Height (%): .0 : 1 7 8 .1 : 21 14 11 .2 : 9 12 19 .3 : 9 11 16 .4 : 4 7 12 .5 : 11 17 5 .6 : 11 11 10 .7 : 10 6 10 .8 : 12 9 6 .9 : 13 6 3 DPS: 16 11 15 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic)

page 28 of 47

Digit preference MUAC (%): .0 : .1 : .2 : .3 : .4 : .5 : .6 : .7 : .8 : .9 : DPS: 0 0 0 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Standard deviation of WHZ: SD 1.02 1.10 0.91 Prevalence (< -2) observed: % 2.0 2.1 Prevalence (< -2) calculated with current SD: % 1.6 2.4 Prevalence (< -2) calculated with a SD of 1: % 1.4 1.5 Standard deviation of HAZ: SD 1.49 1.34 1.16 observed: % 35.3 28.8 27.5 calculated with current SD: % 34.5 30.9 30.3 calculated with a SD of 1: % 27.7 25.2 27.5

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

Team 1:



Overall sex ratio: p-value = 0.442 (boys and girls equally represented)Overall age distribution: p-value = 0.001 (significant difference)Overall age distribution for boys: p-value = 0.069 (as expected)Overall age distribution for girls: p-value = 0.011 (significant difference)Overall sex/age distribution: p-value = 0.000 (significant difference)

Team 2: page 29 of 47



Overall sex ratio: p-value = 0.394 (boys and girls equally represented)Overall age distribution: p-value = 0.013 (significant difference)Overall age distribution for boys: p-value = 0.228 (as expected)Overall age distribution for girls: p-value = 0.099 (as expected)Overall sex/age distribution: p-value = 0.006 (significant difference)

Team 3:



Overall sex ratio: p-value = 0.513 (boys and girls equally represented)Overall age distribution: p-value = 0.004 (significant difference)Overall age distribution for boys: p-value = 0.567 (as expected)Overall age distribution for girls: p-value = 0.003 (significant difference)Overall sex/age distribution: p-value = 0.000 (significant difference)

Evaluation of the SD for WHZ depending upon the order the cases are measured within each cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made).

Team: 1

Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.93 (n=10, f=0) ##### 02: 1.04 (n=10, f=0) ########## 03: 0.83 (n=10, f=0) # 04: 0.77 (n=10, f=0) 05: 1.07 (n=10, f=0) ########### 06: 1.28 (n=10, f=0) #################### 07: 1.39 (n=10, f=0) ######################### 08: 0.85 (n=10, f=0) ## 09: 0.64 (n=10, f=0) 10: 0.81 (n=10, f=0) # 11: 0.83 (n=10, f=0) # 12: 0.96 (n=09, f=0) ####### 13: 0.85 (n=09, f=0) ## 14: 0.43 (n=09, f=0) 15: 1.45 (n=09, f=1) ###########################

page 30 of 47

16: 1.52 (n=09, f=1) ############################## 17: 1.44 (n=09, f=1) ########################### 18: 0.71 (n=08, f=0) 19: 1.00 (n=07, f=0) ######### 20: 0.79 (n=06, f=0) 21: 0.60 (n=06, f=0) 22: 0.57 (n=05, f=0) 23: 0.84 (n=04, f=0) OO 24: 1.14 (n=03, f=0) ~~~~~~~~~~~~~~


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: 1.12 (n=10, f=0) ############# 02: 2.47 (n=10, f=1) ################################################################ 03: 0.90 (n=10, f=0) #### 04: 0.82 (n=10, f=0) # 05: 0.72 (n=10, f=0) 06: 0.70 (n=10, f=0) 07: 1.07 (n=10, f=0) ########### 08: 0.57 (n=10, f=0) 09: 0.90 (n=10, f=0) #### 10: 1.03 (n=10, f=0) ######### 11: 0.66 (n=10, f=0) 12: 0.73 (n=09, f=0) 13: 0.98 (n=09, f=0) ####### 14: 0.93 (n=09, f=0) ##### 15: 1.30 (n=09, f=0) ##################### 16: 1.46 (n=09, f=0) ############################ 17: 0.64 (n=09, f=0) 18: 0.70 (n=09, f=0) 19: 1.03 (n=08, f=0) ########## 20: 1.10 (n=08, f=0) ############ 21: 0.76 (n=08, f=0) 22: 0.88 (n=08, f=0) ### 23: 1.09 (n=07, f=0) ############ 24: 0.92 (n=06, f=0) OOOOO 25: 1.22 (n=06, f=0) OOOOOOOOOOOOOOOOO 26: 0.87 (n=03, f=0) ~~~ 27: 0.17 (n=02, f=0)


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: 0.92 (n=10, f=0) ##### 02: 1.05 (n=10, f=0) ########## 03: 0.86 (n=10, f=0) ### 04: 0.71 (n=10, f=0) 05: 0.72 (n=10, f=0) 06: 1.08 (n=10, f=0) ############ 07: 0.73 (n=10, f=0) 08: 0.58 (n=10, f=0) 09: 0.61 (n=10, f=0) 10: 1.27 (n=10, f=0) #################### 11: 0.70 (n=10, f=0) 12: 0.95 (n=10, f=0) ###### 13: 1.33 (n=10, f=0) ###################### 14: 1.03 (n=09, f=0) ########## 15: 0.56 (n=09, f=0) 16: 0.70 (n=08, f=0) 17: 0.76 (n=08, f=0) 18: 1.37 (n=06, f=0) ######################## 19: 0.25 (n=05, f=0) 20: 0.74 (n=04, f=0) 21: 0.99 (n=03, f=0) OOOOOOOO

page 31 of 47

22: 0.80 (n=03, f=0)


(for better comparison it can be helpful to copy/paste part of this report into Excel)

page 32 of 47

Annex 2 Assignment of Clusters

المدينة

المنطالقطاع الحيقة رمز

عددالعوائل

Cluster

الحجارية دومادوما GDD\1\34181حيالحجارية دومادوما GDD\1\73672حيالسيدين دومادوما GDD\2\24503حيالسنديانة دومادوما GDD\5\14424حيالرؤوف دومادوما عبد GDD\6\43985حيمساكن دومادوما GDD\9\1256RCحيمساكن دومادوما GDD\9\64216حيالمنفوش دومادوما GDD\10\4397RCحيGDD\11\52877الشمسدومادوماالقصارية دومادوما GDD\13\13978حيشرقية دومادوما GDD\14\23299حيGDD\15\1389RCساحةدومادوماالبغدادي دومادوما GDD\16\325910حيGDD\19\239011توحيددومادوماGDD\20\328912حميردومادوماوسطاني دومادوما GDD\22\143913ساحةGAA/1/232114قالشعربينعربينGAA/2/125015النورعربينعربينصغير عربينعربين GAA/10/1180RCحمامGAA/19/117016الخرابةعربينعربينالكبير زملكاعربين GAZ/28/113917جامعكفربطنا

عينGKA/1/111518-1المزرعة-ترما

كفربGKH/17/18019شعبانحزةطنا

كفربطنا

بيتالمدرسة سوا GKB/27/125020قطاع

كفربطنا

بيتب - -سوا 1GKB/37/120021قطاع

كفربطنا

ســـقبـGKS/47/125022الجوزةـا

كفربطنا

ســـقبـGKS/56/125023الجماجمـا

كفربbGKH/65/122024الفيالت حموريةطنا

كفربaGKH/76/125025الفيالت حموريةطنا

كفربطنا

ســـقبـالزيت ـا GKS/84/130226معصرة

page 33 of 47

حرستالعليتة حرستاا GHH/4/132127حي

حرستالقديم مسراباا GHM/10/126628الجامع

حرستالجندي مديرةا عالية GHM/18/132229صيدلية

حرستالتعلة حرستاا GHH/24/132130حي

page 34 of 47

Annex 3 Standardization test : 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 0.05 4/1 Enumerator 1 0.04 OK 0.09 OK 2/2 1/5 Enumerator 2 0.04 OK 0.09 OK 2/2 1/5 Enumerator 3 0.03 OK 0.06 OK 2/1 1/2 Enumerator 4 0.02 OK 0.07 OK 1/1 1/3 Enumerator 5 0.33 POOR 0.34 POOR 4/2 1/3 Enumerator 6 0.51 POOR 0.38 POOR 2/1 0/3 Enumerator 7 0.02 OK 0.09 OK 2/0 2/4 Enumerator 8 0.02 OK 0.09 OK 2/0 2/4 Enumerator 9 0.06 OK 0.03 OK 2/1 2/1 Enumerator 10 0.06 OK 0.03 OK 3/0 2/1 Enumerator 11 0.05 OK 0.08 OK 4/1 3/2 Enumerator 12 0.20 POOR 0.29 POOR 5/0 3/2 Enumerator 13 0.02 OK 0.05 OK 2/0 2/3 Enumerator 14 0.04 OK 0.07 OK 4/0 2/2 Enumerator 15 0.03 OK 0.04 OK 2/1 0/4 Enumerator 16 0.04 OK 0.03 OK 2/2 0/3 Enumerator 17 0.02 OK 0.07 OK 1/1 1/3

Height:


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

Supervisor 0.74 7/2 Enumerator 1 4.72 POOR 13.06 POOR 3/5 1/9 Enumerator 2 4.72 POOR 13.06 POOR 3/5 1/9 Enumerator 3 2.17 POOR 36.91 POOR 2/6 4/6 Enumerator 4 3.94 POOR 19.80 POOR 4/6 2/8 Enumerator 5 1.62 POOR 1.58 OK 6/3 4/4 Enumerator 6 1.22 OK 2.62 POOR 4/4 5/4 Enumerator 7 0.37 OK 1.07 OK 4/3 6/4 Enumerator 8 0.37 OK 1.07 OK 4/3 6/4 Enumerator 9 0.50 OK 4.80 POOR 4/3 2/7 Enumerator 10 0.84 OK 5.90 POOR 3/3 3/6 Enumerator 11 0.47 OK 0.89 OK 4/3 7/3 Enumerator 12 0.64 OK 0.74 OK 6/3 6/3 Enumerator 13 0.66 OK 0.72 OK 2/1 2/6 Enumerator 14 3.50 POOR 4.76 POOR 3/6 3/6 Enumerator 15 1.82 POOR 5.78 POOR 1/7 1/8 Enumerator 16 1.43 OK 2.99 POOR 1/7 1/5 Enumerator 17 3.94 POOR 19.80 POOR 4/6 2/8

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MUAC:


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

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.

page 36 of 47

Annex 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

Alln = 626

Boysn = 297

Girlsn = 329

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

(7) 1.1 %(0.6 - 2.2 95% C.I.)

(2) 0.7 %(0.2 - 2.7 95% C.I.)

(5) 1.5 %(0.7 - 3.5 95% C.I.)

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

(6) 1.0 %(0.4 - 2.1 95% C.I.)

(2) 0.7 %(0.2 - 2.7 95% C.I.)

(4) 1.2 %(0.5 - 3.2 95% C.I.)

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

(1) 0.2 %(0.0 - 1.2 95% C.I.)

(0) 0.0 %(0.0 - 0.0 95% C.I.)

(1) 0.3 %(0.0 - 2.3 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 )


Oedema

Age (mo)

Total no.

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

6-17 198 0 0.0 3 1.5 195 98.5 0 0.018-29 159 0 0.0 3 1.9 156 98.1 0 0.030-41 100 0 0.0 0 0.0 100 100.0 0 0.042-53 103 0 0.0 0 0.0 103 100.0 0 0.054-59 66 1 1.5 0 0.0 65 98.5 0 0.0Total 626 1 0.2 6 1.0 619 98.9 0 0.0

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

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

No. 0(0.0 %)

KwashiorkorNo. 0

(0.0 %)Oedema absent Marasmic

No. 1(0.2 %)

Not severely malnourishedNo. 625(99.8 %)

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

Alln = 0

Boysn = 0

Girlsn = 0

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

(0) %( - 95% C.I.)

(0) %( - 95% C.I.)

(0) %( - 95% C.I.)

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

(0) %( - 95% C.I.)

(0) %( - 95% C.I.)

(0) %( - 95% C.I.)

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

(0) %( - 95% C.I.)

(0) %( - 95% C.I.)

(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. %

6-1718-2930-4142-5354-59Total

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

n = 626Prevalence of global acute malnutrition(<80% and/or oedema)

(5) 0.8 %(0.3 - 1.8 95%

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

(5) 0.8 %(0.3 - 1.8 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. %

6-17 198 0 0.0 1 0.5 197 99.5 0 0.0page 38 of 47

18-29 159 0 0.0 3 1.9 156 98.1 0 0.030-41 100 0 0.0 0 0.0 100 100.0 0 0.042-53 103 0 0.0 0 0.0 103 100.0 0 0.054-59 66 0 0.0 1 1.5 65 98.5 0 0.0Total 626 0 0.0 5 0.8 621 99.2 0 0.0

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

Alln = 626

Boysn = 297

Girlsn = 329

Prevalence of underweight(<-2 z-score)

(81) 12.9 %(10.3 - 16.1 95% C.I.)

(28) 9.4 %(7.1 - 12.4 95% C.I.)

(53) 16.1 %(12.1 - 21.2 95% C.I.)

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

(70) 11.2 %(8.4 - 14.7 95% C.I.)

(24) 8.1 %(5.9 - 10.9 95% C.I.)

(46) 14.0 %(9.9 - 19.4 95% C.I.)

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

(11) 1.8 %(1.1 - 2.8 95% C.I.)

(4) 1.3 %(0.5 - 3.5 95% C.I.)

(7) 2.1 %(1.1 - 4.2 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 )


Oedema

Age (mo)

Total no.

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

6-17 198 6 3.0 27 13.6 165 83.3 0 0.018-29 159 2 1.3 19 11.9 138 86.8 0 0.030-41 100 1 1.0 10 10.0 89 89.0 0 0.042-53 103 1 1.0 9 8.7 93 90.3 0 0.054-59 66 1 1.5 5 7.6 60 90.9 0 0.0Total 626 11 1.8 70 11.2 545 87.1 0 0.0

page 39 of 47

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

Alln = 626

Boysn = 297

Girlsn = 329

Prevalence of stunting(<-2 z-score)

(155) 24.8 %(20.6 - 29.4 95% C.I.)

(61) 20.5 %(15.1 - 27.3 95% C.I.)

(94) 28.6 %(23.5 - 34.2 95% C.I.)

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

(112) 17.9 %(14.5 - 21.9 95% C.I.)

(42) 14.1 %(10.1 - 19.4 95% C.I.)

(70) 21.3 %(16.4 - 27.1 95% C.I.)

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

(43) 6.9 %(4.7 - 9.9 95% C.I.)

(19) 6.4 %(4.1 - 9.9 95% C.I.)

(24) 7.3 %(4.5 - 11.5 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 )


Age (mo)

Total no.

No. % No. % No. %

6-17 198 10 5.1 22 11.1 166 83.818-29 159 9 5.7 29 18.2 121 76.130-41 100 10 10.0 20 20.0 70 70.042-53 103 10 9.7 23 22.3 70 68.054-59 66 4 6.1 18 27.3 44 66.7Total 626 43 6.9 112 17.9 471 75.2

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

Alln = 626

Boysn = 297

Girlsn = 329

Prevalence of overweight (WHZ > 2)

(9) 1.4 %(0.7 - 3.1 95% C.I.)

(2) 0.7 %(0.2 - 2.8 95% C.I.)

(7) 2.1 %(1.0 - 4.6 95% C.I.)

Prevalence of severe overweight (WHZ > 3)

(3) 0.5 %(0.1 - 2.1 95% C.I.)

(1) 0.3 %(0.0 - 2.5 95% C.I.)

(2) 0.6 %(0.2 - 2.4 95% C.I.)

page 40 of 47

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. %

6-17 198 1 0.5 0 0.018-29 159 3 1.9 1 0.630-41 100 1 1.0 1 1.042-53 103 3 2.9 1 1.054-59 66 1 1.5 0 0.0Total 626 9 1.4 3 0.5

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

626 -0.10±0.91 1.00 1 0

Weight-for-Age 626 -0.87±1.02 1.12 1 0Height-for-Age 626 -1.23±1.28 1.58 1 0* contains for WHZ and WAZ the children with edema.

Annex 5 maps of surveyed area

page 41 of 47

page 42 of 47

Annex 6 Questionnaire

page 43 of 47

Annex 7 cluster control form

page 44 of 47

Annex 8: calendar events

page 45 of 47

Annex 9: referral form

page 46 of 47

Annex 10: training agenda

page 47 of 47

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