1 Rapid SMART Assessment Report Qala-e-Naw IDP Camps, Badghis province Date: 4-11 April 2019 Lead by: Dr: Shafiullah Samim, Dr. M. Khalid Zakir and Dr. Nazir Sajid Author: Beka Teshome and Dr. Sayed Rahim Rastkar Funded by: AHF-OCHA Action Contre la Faim AAH is a non-governmental, non-political and non-religious organization AFGHANISTAN
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Rapid SMART Assessment Report Qala-e-Naw IDP Camps, Badghis province
Date: 4-11 April 2019
Lead by: Dr: Shafiullah Samim, Dr. M. Khalid Zakir and Dr. Nazir Sajid
Author: Beka Teshome and Dr. Sayed Rahim Rastkar
Funded by: AHF-OCHA
Action Contre la Faim
AAH is a non-governmental, non-political and non-religious organization
2.1. General objective ............................................................................................................................. 10
2.2. Specific objectives ....................................................................................................................... 10
5.3.1. Distribution by sex and age ................................................................................................. 17
5.3.2. Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema)
and by sex ........................................................................................................................................... 18
5.3.3. Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or
oedema 19
5.3.4. Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) .................. 20
5.3.5. Prevalence of underweight based on weight-for-age z-scores .......................................... 21
5.3.6. Prevalence of stunting based on height-for-age z-scores and by sex ................................. 22
The overall objective of the rapid SMART assessments was to estimate the current prevalence of acute
malnutrition among children 6-59 months of age and PLW in Qala-e-Naw city IDP camps, Badghis province
2.2. Specific objectives
The specific objectives included the following:
To estimate the prevalence of global and severe acute malnutrition in children aged 6-59 months.
To estimate the prevalence of acute malnutrition among PLW using MUAC.
To estimate the prevalence of diarrhea among children 6-59 months in the last two weeks prior
to the survey dates.
To estimate prevalence of chronic malnutrition and underweight among children aged 6-59
months.
3. METHODOLOGY
3.1. Geographic target area and population group
The two Rapid SMART assessments were carried out in in segment A (Kharistan, Jar Khoshk, Jar Haji Sakhi,
Chakaran) and segment B (Zaimati, Sanjidak, Baghlar, Shamal Darya) of Qala-e-Naw IDP Camps. The IDP
arrived to Qala-e-Naw IDP Camps from all districts of Badghis province. The IDP has multi ethnics origin
such us Tjik, Pashtoon, Aimaq, and Uzbek. Dari was more spoken than Pashto in the IDP population. All
the 115 Chief/Malik2 (62 in segment A & 53 in segment B) were included in the sampling frame. The study
population was children from the age of 6 to 59 months and PLW.
2Chief/Malik are the community elders, which are acting as leader of a group of families or a single village at whole.
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Qala-e-Naw IDP Camps location, Badghis province
3.2. Survey period
A four-days training was organized between 31 March to 3rd April 2019 and data collection took place
from 4th to 11th of April, 2019, in two phases. The first phase data collection was conducted in segment
A between 4-7 April) while the second phase data collection was conducted in segment B between 8-11
April 2019.
3.3. Survey design
The two rapid nutrition assessmenst (Segment A & Segment B) in Qala-e-Naw IDP Camps were cross-
sectional with two-stage cluster samplings based on the SMART methodology.
3.4. Sample size
A pre-determined sample size of 25 clusters with 10 households (250 households) was chosen for the each
rapid assessment and was expected to be enough to ensure representativeness with acceptable
precision3. To reach required sample, the rapid SMART methodology4 proposes to use a simplified rule to
convert children into households:
3As per the rapid SMART guideline, a sample size of minimum 200 children would be enough to estimate GAM prevalence for cluster random sampling. 4GUIDELINES. Rapid SMART surveys for Emergencies. Developed by ACF – International, SMART Initiative at ACF – Canada and CDC Atlanta. Version 1, September 2014
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A. When the percentage of children under age of 5 is below 15%, 25 clusters of 12 households would
be enough to estimate GAM prevalence.
B. When the percentage of children under age of 5 is above 15%, 25 clusters of 10 households would
be enough to estimate GAM prevalence.
As the reference percentage of under-5 population for Afghanistan is 17.3% (Afghanistan Updated
Population CSO 2018-19), the option B was applied. 25 Cluster of 10 households were selected randomly
using PPS by ENA software (2015 updated version) out of the total list of population living in the IDP camps
near to Qala-e-Naw city in the different camps.
3.5. Sampling procedures
The surveys applied a two-stage cluster sampling method referring to the SMART methodology based on
probability proportional to population size (PPS). Stage one sampling involved the sampling of the clusters
to be included in the survey while the second stage sampling involved the selection of the households
from the sampled clusters. The smallest geographical unit in Qala-e-Naw IDP Camps i.e. a Chief/Malik
defined a cluster.
3.5.1. First stage sampling: selection of clusters
List of Chief/Malik with their respective population was obtained from the national NGO AYSO and
community leaders. Chief/Malik in the IPD camps were considered as clusters and the sampled clusters
were selected with probability proportional to population size (PPS). All the 115 villages of Qala-e-Naw
IDP Camps (62 in segment A & 53 in segment B) along with their respective populations were entered into
ENA software and clusters were selected automatically to be included in the survey (annex 3 & 4). There
was no inaccessible clusters for both rapid assessments. In Chief/Malik where more than one cluster was
assigned, segmentation was done and the required number of clusters selected randomly. Segmentation
was done in chief/malik 34 of segment B. Upon arrival to the cluster, the teams mapped the area and used
water tankers, static mobile health sites and hills as landmarks.
3.5.2. Second stage sampling: selection of households
Household definition: Group of people living under same roof and sharing food from the same pot. In
households with multiple wives, those living and eating in different houses were considered as separate
Households (HHs). Wives living in different houses and eating from same pot were considered as one HH.
The second stage of sampling was the selection of households within the selected clusters (Chief/Malik)
using a systematic random method as described below.
On arrival at the Chief/Malik:
The survey team introduced themselves and the objective of the survey to the Chief/Malik leader.
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In collaboration with the Chief/Malik leader, the team prepared a list of all households in the
Chief/Malik. Abandoned households were not listed.
The required number of households were selected using systematic random sampling.
The sampling interval was determined by:
Sampling interval = Total number of sampling units in the population
Number of sampling units in the sample (10)
Selection of the first sampling unit: A number between 1 and the sampling interval was randomly
chosen.
Selection of the following sampling units: Number of the 1st sampling unit + sampling interval;
etc.
In cases where there was no eligible child but having PLW, a household was still considered part of the
sample, where only anthropometric data of PLW was collected. If a respondent was absent during the
time of household visit, the teams left a message and re-visited later to collect data, with no substitution
of households.
Each team was assisted by a Chief/Malik guide (Chief/Malik leader) to lead and guide the survey team
within the Chief/Malik and locating the selected households.
3.6. Organization of the Survey
3.6.1. Survey Coordination
With the lead of Action Against Hunger Afghanistan, communication was done of survey objectives to all
the relevant administrative authorities, community leaders as well as stakeholders such as MoPH, PND,
PPHD and other partners.
3.6.2. Survey Teams
Eight teams each comprising two enumerators (1 male & 1 female) were deployed to collect data in all
the selected clusters from 4th to 11th April 2019. Four supervisors were assigned to supervise the survey
teams (1 supervisor per 2 survey teams).
3.6.3. Training of the Survey Teams
Training was carried out by AAH’s survey manager and was conducted in the local language5. Four
supervisors (1 supervisor per 2 teams), were responsible for ensuring the recording of all data collected
as well as ensuring accuracy of measurements taken, methodology and any other technical issues raised
while in the field. Candidates with prior experience in nutrition survey were given preference. Training
5ACF surveillance team members had been trained on anthropometric measurement, survey methodology, interview skill and other practical aspects in addition to their extensive experience in carrying out surveys in Afghanistan.
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was conducted for four days from 31st March to 3rd April 2019, and training covered survey objectives,
basic malnutrition, concept of sampling and SMART survey methodology followed by anthropometric
measurements, recognition of the signs and symptoms of malnutrition including nutritional bi-lateral
oedema and interview techniques.
As a mean to verify anthropometric skills of enumerators and to detect differences among measurers a
standardization test was conducted during the fourth day of the training. Ten children were measured
once by the survey supervisor and then each of the 16 enumerators were allowed to measure the
children’s weight, height and MUAC twice with a time interval between individual measures. Observations
of errors in the performance of each team with regards to undertaking measurements and completing
the questionnaires were identified, discussed and corrected with all team members by the team
supervisors and the survey manager.
3.7. Data collection and field work
3.7.1. Children anthropometric survey
Structured questionnaires (annex 5) were used to collect anthropometric and morbidity data from all
children within the eligible age range (6-59 months) using anthropometric questionnaire. Once measured,
visible small mark on the left upper arm or on the fingernails of the child was made in order to avoid
measuring the same child several times. The collected data were:
Age: The age of children was estimated based on using birth certificate record, vaccination card or parent
records of exact birth dates or ages in completed months. In case the above-mentioned documents were
not available, local event calendar was used (annex 6). The calendar of local events was jointly developed
with the survey assistants and camp leaders. All the birth dates were collected in accordance with Hijri
Calendar – Afghanistan Official Calendar and were converted to Georgian format using date converter.
Sex: Male or female
Weight: Children’s weights were taken without clothes using SECA scales (100g precision).
Height/length: Children were measured using wooden UNICEF measuring boards (precision of 0.1cm).
Children less than 87 cm were measured lying down, while those greater than or equal to 87 cm were
measured standing up.
Mid-upper arm circumference: MUAC measurements were taken at the mid-point of the left upper arm
using child tapes (precision of 0.1cm).
Bilateral pitting oedema: Assessed by the application of normal thumb pressure on both feet for 3
seconds. Occurrence of pitting oedema on both feet upon release of the fingers indicated nutritional
oedema classified as severely malnourished.
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3.7.2. Maternal nutritional status
The nutritional status of pregnant and lactating women was assessed based on MUAC measurements.
MUAC measurements were taken at the mid-point of the left upper arm using adult tapes.
3.7.3. Child Morbidity
Two-weeks retrospective morbidity data was collected from mothers/caregivers of all children (6-59
months) included in the anthropometric measurement. The mother/caregiver was asked whether or not
the child had diarrhea in the two weeks preceding the survey.
3.8. Data quality assurance
Assurance of data quality was insured through conducting high quality training for survey teams coupled
with standardization test, practical field exercise (pre - test survey) and close supervision of survey teams
during data collection. The survey supervisors were in charge of the data quality control as they ensured
that HH selection was done correctly, interviews were done correctly and consistently from one
household to the other and anthropometric measurements were correctly taken. All the filled
questionnaires were reviewed in the field by the survey supervisors for accuracy and completeness before
the teams left the given clusters. The survey supervisors reported daily and submitted all the verified
completed forms to the survey manager for review and feedback given every evening. Field visits were
also done by the survey manager during the survey period to ensure quality during data collection. Daily
data entry and regular plausibility checks were done and feedback given to survey team.
4. DATA MANAGEMENT AND ANALYSIS
The anthropometric data were analyzed using ENA software 2011 version (updated 9 July 2015). The
indices were compared to the World health Organization (WHO) Standards 2006 to determine the levels
of wasting, underweight and stunting. SMART flags: WHZ -3 to 3; HAZ -3 to 3; WAZ -3 to 3 were used in
final analysis to exclude zscores with extreme values from observed mean. Morbidity and PLW data were
analyzed on excel.
5. RESULTS
5.1. Mean z-scores, Design Effects and excluded subjects
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Table 5-1 and 5-2 shows the distribution of the sample statistics for the surveys. The standard deviations
(SD) for WHZ, WAZ & HAZ were within the acceptable range of 0.8-1.2. However, with design effect of
2.32, for HAZ in segment B, the sample population showed some degree of heterogeneity for chronic
malnutrition.
The overall data quality was scored as excellent (score of 5% for segment A, score of 8% for segement B).
For more information, see the plausibility check in Annex 1 & 2.
Table 5-1: Mean z-scores, design effect and excluded subjects, Qala-e-Naw city IDP camp (Segment A)
Indicator N Mean z-scores ± SD
Design Effect (z-score < -2)
z-scores not available*
z-scores out of range
Weight-for-Height 411 -0.33±1.09 1.00 0 7
Weight-for-Age 412 -1.16±1.05 1.03 0 6
Height-for-Age 410 -1.75±1.17 1.00 0 8
* contains for WHZ and WAZ the children with edema.
Table 5-2: Mean z-scores, design effect and excluded subjects, Qala-e-Naw city IDP camp (Segment B) Indicator N Mean z-scores
± SD Design Effect (z-
score < -2) z-scores not available*
z-scores out of range
Weight-for-Height 444 -0.53±1.04 1.20 0 4
Weight-for-Age 447 -1.46±0.93 1.13 0 1
Height-for-Age 444 -1.93±1.05 2.32 0 4
* contains for WHZ and WAZ the children with edema
5.2. General characteristics of study population and households
5.2.1. Households and children 6-59 months
In segment A, out of 250 households planned, data was collected from a total of 234 households (94%)
and in segment B, all the 250 planned households were surveyed (100%). In Segment A, 16 households
were recorded as non-response households. Further, about 216.5% of the sample size of children 6-59
months of age was met without resulting to visit the 4 reserve clusters (RCs). A total of 866 children aged
6-59 months (418 children from segment A and 448 children from segment B) were assessed for their
nutritional status using anthropometric measurements.
Table 5-3: Summary of households and children 6-59 months planned and those surveyed
Number of HH planned
Qala-e-Naw city IDP camp Segment A
250
Qala-e-Naw city IDP camp Segment B
250
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5.2.2. Pregnant and Lactating Women
In these assessments, a total of 556 pregnant & lactating women (275 in segment A, 281 in segment B)
were screened for malnutrition by MUAC.
5.3. Anthropometric results
5.3.1. Distribution by sex and age
The age and sex distribution of the sample population in the two surveys are illustrated in Table 5-4 and
5-5. Among the surveyed children, 453 (52.3%) were boys while 413 (47.7%) were girls. The overall sex
ratio of the surveyed children in both segments was 1.1 indicating that both sexes were equally
represented within the sample. Similarly, the distribution of the sample children age groups did not also
vary from the normal accepted percentage, which also shows that the sample was unbiased.
Table 5-4: Distribution of age & sex of children 6-59 months, Qala-e-Naw city IDP camp (segment A)
Table 5-5: Distribution of age & sex of children 6-59 months, Qala-e-Naw city IDP camp (segment B)
Number of HH surveyed
Qala-e-Naw city IDP camp Segment A
234
Qala-e-Naw city IDP camp Segment B
250
Number of children 6-59 months planned
Qala-e-Naw city IDP camp Segment A
200
Qala-e-Naw city IDP camp Segment B
200
Number of children 6-59 months surveyed
Qala-e-Naw city IDP camp Segment A
418
Qala-e-Naw city IDP camp Segment B
448
Boys Girls Total Ratio
AGE (mo) no. % no. % no. % Boy: girl
6-17 47 50.0 47 50.0 94 22.5 1.0
18-29 43 42.2 59 57.8 102 24.4 0.7
30-41 52 52.0 48 48.0 100 23.9 1.1
42-53 41 53.9 35 46.1 76 18.2 1.2
54-59 32 69.6 14 30.4 46 11.0 2.3
Total 215 51.4 203 48.6 418 100.0 1.1
Boys Girls Total Ratio
AGE (mo) no. % no. % no. % Boy: girl
6-17 52 51.5 49 48.5 101 22.5 1.1
18-29 75 54.7 62 45.3 137 30.6 1.2
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5.3.2. Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by
sex
GAM WHZ is defined as <-2 z scores weight-for-height and/or oedema while severe acute malnutrition is
defined as <-3z scores weight-forheight and/or oedema.
The prevalence of GAM and SAM in the IDP camps are presented in Table 5-6 & 5-7. Prevalence of GAM
in segment A was 7.5% (5.6 - 10.0 95% C.I.), whereas SAM was 1.9% (1.0 - 3.9 95% C.I.). GAM among
households in segment B was 8.3% (5.8 - 11.8 95% C.I.), and SAM was found to be 1.6 % (0.6 - 4.1 95%
C.I.). No oedema case was observed during the assessment in both segments.
In the final analysis, 11 children (7 in segment A & 4 in segment B) were excluded due to out of range
values using SMART flags (-3 to 3 Z-score).
Table 5-6: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex, segment A
The prevalence of oedema is 0.0 %
Table 5-7: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex, segment B
30-41 48 52.2 44 47.8 92 20.5 1.1
42-53 40 51.9 37 48.1 77 17.2 1.1
54-59 23 56.1 18 43.9 41 9.2 1.3
Total 238 53.1 210 46.9 448 100.0 1.1
All
n = 411 Boys
n = 211 Girls
n = 200
Prevalence of global malnutrition (<-2 z-score and/or oedema)
(31) 7.5 % (5.6 - 10.0 95% C.I.)
(16) 7.6 % (5.1 - 11.1 95% C.I.)
(15) 7.5 % (4.6 - 11.9 95% C.I.)
Prevalence of moderate malnutrition (<-2 z-score and >=-3 z-score, no oedema)
(23) 5.6 % (4.0 - 7.8 95% C.I.)
(10) 4.7 % (2.5 - 8.7 95% C.I.)
(13) 6.5 % (4.1 - 10.1 95% C.I.)
Prevalence of severe malnutrition (<-3 z-score and/or oedema)
(8) 1.9 % (1.0 - 3.9 95% C.I.)
(6) 2.8 % (1.3 - 5.9 95% C.I.)
(2) 1.0 % (0.3 - 3.8 95% C.I.)
All
n = 444 Boys
n = 236 Girls
n = 208
Prevalence of global malnutrition (<-2 z-score and/or oedema)
(37) 8.3 % (5.8 - 11.8 95% C.I.)
(21) 8.9 % (5.8 - 13.5 95% C.I.)
(16) 7.7 % (4.8 - 12.1 95% C.I.)
Prevalence of moderate malnutrition (<-2 z-score and >=-3 z-score, no oedema)
(30) 6.8 % (4.4 - 10.2 95% C.I.)
(17) 7.2 % (4.2 - 12.0 95% C.I.)
(13) 6.3 % (3.7 - 10.3 95% C.I.)
Prevalence of severe malnutrition (<-3 z-score and/or oedema)
(7) 1.6 % (0.6 - 4.1 95% C.I.)
(4) 1.7 % (0.6 - 4.5 95% C.I.)
(3) 1.4 % (0.3 - 6.2 95% C.I.)
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The prevalence of oedema is 0.0 %
5.3.3. Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema
As shown in table 5-8 & 5-9, younger children 6-29 months were the most malnourished by WHZ than any
other age group .Table 5-10 shows the distribution of acute malnutrition based on WHZ and oedema. No
cases of kwashiorkor were observed in the sample. Malnutrition was presented as marasmas only.
Table 5-8: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema, segment A
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 91 4 4.4 12 13.2 75 82.4 0 0.0
18-29 101 4 4.0 4 4.0 93 92.1 0 0.0
30-41 98 0 0.0 0 0.0 98 100.0 0 0.0
42-53 75 0 0.0 4 5.3 71 94.7 0 0.0
54-59 46 0 0.0 3 6.5 43 93.5 0 0.0
Total 411 8 1.9 23 5.6 380 92.5 0 0.0
Table 5-9: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema, segment B
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 97 4 4.1 12 12.4 81 83.5 0 0.0
18-29 137 3 2.2 8 5.8 126 92.0 0 0.0
30-41 92 0 0.0 7 7.6 85 92.4 0 0.0
42-53 77 0 0.0 1 1.3 76 98.7 0 0.0
54-59 41 0 0.0 2 4.9 39 95.1 0 0.0
Total 444 7 1.6 30 6.8 407 91.7 0 0.0
Table 5-10: Distribution of acute malnutrition and oedema based on weight-for-height z-scores
Qala-e-Naw city IDP camp
(Segment A) Qala-e-Naw city IDP camp (Segment B)
<-3 z-score >=-3 z-score <-3 z-score >=-3 z-score
Oedema present Marasmic kwashiorkor
No. 0 (0.0 %)
Kwashiorkor No. 0
(0.0 %)
Marasmic kwashiorkor No. 0
(0.0 %)
Kwashiorkor No. 0
(0.0 %)
Oedema absent Marasmic No. 12
Not severely malnourished
Marasmic No. 11
Not severely malnourished
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5.3.4. Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema)
The prevalence of global acute malnutrition based on MUAC (<125mm) and/or oedema in segment A was
8.1% (5.6 - 11.7 95% C.I.) and of severe acute malnutrition (MUAC <115mm and/or oedema) was 2.4%
(1.3 - 4.4 95% C.I.). In segement B, the prevalence of global acute malnutrition based on MUAC was 8.7%
(6.4 - 11.8 95% C.I.), and SAM was found to be 1.6% (0.7 - 3.5 95% C.I.). Detailed results are presented in
tables 5-11 & 5-12.
Table 5-11: Prevalence of acute malnutrition based on MUAC cut offs (and/or oedema) and by sex., segment A
Table 5-12: Prevalence of acute malnutrition based on MUAC cut offs (and/or oedema) and by sex., segment B
According to table 5-13 & 5-14, younger children 6-29 months were more malnourished by MUAC than
older children above 2 years of age. This is consistent with the known fact that MUAC tends to identify
younger children.
Table 5-13: Prevalence of acute malnutrition by age, based on MUAC cut off's and/or oedema, segment A
Severe wasting
(< 115 mm)
Moderate wasting
Normal (> = 125 mm )
Oedema
(2.9 %) No. 406 (97.1 %)
(2.5 %) No. 437 (97.5 %)
All
n = 418 Boys
n = 215 Girls
n = 203
Prevalence of global malnutrition (< 125 mm and/or oedema)
(34) 8.1% (5.6 - 11.7 95%
C.I.)
(13) 6.0% (3.4 - 10.6 95% C.I.)
(21) 10.3% (6.2 - 16.7 95%
C.I.)
Prevalence of moderate malnutrition (< 125 mm and >= 115 mm, no oedema)
(24) 5.7% (3.8 - 8.6 95% C.I.)
(8) 3.7% (1.9 - 7.3 95% C.I.)
(16) 7.9% (4.5 - 13.4 95%
C.I.)
Prevalence of severe malnutrition (< 115 mm and/or oedema)
(10) 2.4% (1.3 - 4.4 95% C.I.)
(5) 2.3% (0.8 - 6.7 95% C.I.)
(5) 2.5% (1.1 - 5.5 95% C.I.)
All
n = 448 Boys
n = 238 Girls
n = 210
Prevalence of global malnutrition (< 125 mm and/or oedema)
(39) 8.7% (6.4 - 11.8 95% C.I.)
(20) 8.4% (5.5 - 12.7 95%
C.I.)
(19) 9.0% (6.4 - 12.6 95%
C.I.)
Prevalence of moderate malnutrition (< 125 mm and >= 115 mm, no oedema)
(32) 7.1% (5.1 - 10.0 95% C.I.)
(16) 6.7% (4.3 - 10.4 95%
C.I.)
(16) 7.6% (4.9 - 11.6 95%
C.I.)
Prevalence of severe malnutrition (< 115 mm and/or oedema)
(7) 1.6% (0.7 - 3.5 95% C.I.)
(4) 1.7% (0.6 - 4.4 95% C.I.)
(3) 1.4% (0.5 - 4.4 95% C.I.)
21
(>= 115 mm and < 125 mm)
Age (mo) Total no. No. % No. % No. % No. %
6-17 94 7 7.4 13 13.8 74 78.7 0 0.0
18-29 102 3 2.9 10 9.8 89 87.3 0 0.0
30-41 100 0 0.0 1 1.0 99 99.0 0 0.0
42-53 76 0 0.0 0 0.0 76 100.0 0 0.0
54-59 46 0 0.0 0 0.0 46 100.0 0 0.0
Total 418 10 2.4 24 5.7 384 91.9 0 0.0
Table 5-14: Prevalence of acute malnutrition by age, based on MUAC cut off's and/or oedema, segement B
Severe wasting
(< 115 mm)
Moderate wasting
(>= 115 mm and < 125 mm)
Normal (> = 125 mm )
Oedema
Age (mo) Total no. No. % No. % No. % No. %
6-17 101 6 5.9 21 20.8 74 73.3 0 0.0
18-29 137 1 0.7 11 8.0 125 91.2 0 0.0
30-41 92 0 0.0 0 0.0 92 100.0 0 0.0
42-53 77 0 0.0 0 0.0 77 100.0 0 0.0
54-59 41 0 0.0 0 0.0 41 100.0 0 0.0
Total 448 7 1.6 32 7.1 409 91.3 0 0.0
5.3.5. Prevalence of underweight based on weight-for-age z-scores
Weight for Age is a composite index that measures both stunting and wasting. The prevalence of
underweight in segment A and segment B of Qala-e-Naw city IDP camp was 21.6% (17.7 - 26.1 95% C.I.)
and 26.6% (22.3 - 31.4 95% C.I.), respectively as indicated in table 5-15 & 5-16.
Table 5-15: Prevalence of underweight based on weight-for-age z-scores by sex., segment A
Table 5-16: Prevalence of underweight based on weight-for-age z-scores by sex., segment B
All
n = 412 Boys
n = 212 Girls
n = 200
Prevalence of underweight (<-2 z-score)
(89) 21.6% (17.7 - 26.1 95% C.I.)
(44) 20.8% (15.0 - 27.9 95% C.I.)
(45) 22.5% (16.4 - 30.0 95% C.I.)
Prevalence of moderate underweight (<-2 z-score and >=-3 z-score)
(65) 15.8% (12.8 - 19.3 95% C.I.)
(31) 14.6% (9.9 - 21.1 95% C.I.)
(34) 17.0% (12.9 - 22.1 95% C.I.)
Prevalence of severe underweight (<-3 z-score)
(24) 5.8% (3.7 - 9.1 95% C.I.)
(13) 6.1% (3.4 - 10.9 95% C.I.)
(11) 5.5% (2.6 - 11.2 95% C.I.)
All
n = 447 Boys
n = 237 Girls
n = 210
Prevalence of underweight (<-2 z-score)
(119) 26.6% (22.3 - 31.4 95% C.I.)
(68) 28.7% (23.0 - 35.1 95%
C.I.)
(51) 24.3% (17.9 - 32.1 95%
C.I.)
Prevalence of moderate underweight (<-2 z-score and >=-3 z-score)
(92) 20.6% (17.3 - 24.3 95% C.I.)
(50) 21.1% (17.1 - 25.8 95%
C.I.)
(42) 20.0% (14.9 - 26.3 95%
C.I.)
22
5.3.6. Prevalence of stunting based on height-for-age z-scores and by sex
Stunting is indicated by low height/length for age compared to WHO standard 2006. From the survey
findings, the stunting rate for children aged 6-59 months in Qala-e-Naw city IDP camp was 40.0% (35.3 -
44.9 95% C.I.) in segment A and 47.5% (40.2 - 55.0 95% C.I.) in segment B as indicated in table 5-17 & 5-
18.
Table 5-17: Prevalence of stunting based on height-for-age z-scores and by sex., segment A
Table 5-18: Prevalence of stunting based on height-for-age z-scores and by sex., segment B
5.4. Child morbidity
High prevalence of diarrhoea was recorded in both segment A and B of Qala-e-Naw city IDP camp (Table
5-19). Nearly one-third of surveyed children reportedly suffered from diarrhoea in the two weeks prior to
the assessment (31.6% in segment A and 33.9% in B)
Prevalence of severe underweight (<-3 z-score)
(27) 6.0% (3.9 - 9.3 95% C.I.)
(18) 7.6% (4.5 - 12.5 95% C.I.)
(9) 4.3% (2.1 - 8.7 95% C.I.)
All
n = 410 Boys
n = 208 Girls
n = 202
Prevalence of stunting (<-2 z-score)
(164) 40.0% (35.3 - 44.9 95%
C.I.)
(83) 39.9% (33.6 - 46.6 95%
C.I.)
(81) 40.1% (32.3 - 48.4 95%
C.I.)
Prevalence of moderate stunting (<-2 z-score and >=-3 z-score)
(102) 24.9% (21.2 - 29.0 95%
C.I.)
(51) 24.5% (19.3 - 30.6 95%
C.I.)
(51) 25.2% (20.0 - 31.4 95%
C.I.)
Prevalence of severe stunting (<-3 z-score)
(62) 15.1% (11.8 - 19.1 95%
C.I.)
(32) 15.4% (11.7 - 20.0 95%
C.I.)
(30) 14.9% (10.3 - 20.9 95%
C.I.)
All
n = 444 Boys
n = 235 Girls
n = 209
Prevalence of stunting (<-2 z-score)
(211) 47.5% (40.2 - 55.0 95%
C.I.)
(123) 52.3% (44.4 - 60.1 95%
C.I.)
(88) 42.1% (31.4 - 53.6 95%
C.I.)
Prevalence of moderate stunting (<-2 z-score and >=-3 z-score)
(150) 33.8% (28.3 - 39.8 95%
C.I.)
(81) 34.5% (27.9 - 41.7 95%
C.I.)
(69) 33.0% (24.7 - 42.6 95%
C.I.)
Prevalence of severe stunting (<-3 z-score)
(61) 13.7% (10.4 - 18.0 95%
C.I.)
(42) 17.9% (13.5 - 23.2 95%
C.I.)
(19) 9.1% (5.6 - 14.5 95% C.I.)
23
Table 5-19: Morbidity among children 6-59 months, Qala-e-Naw city IDP camps, Badghis Province, April 2019
5.5. Maternal nutritional status
From the survey findings, 28.4% and 39.3% of women were found to be acutely malnourished in segment
A and B, respectively as indicated in table 5-20.
Table 5-20: Maternal nutritional status based on MUAC cut-off points for PLW, Qala-e-Naw city IDP camps, Badghis Province, April 2019
5.6. Prevalence of Combined Acute Malnutrtion based on WHZ and/or MUAC
The Combined GAM (cGAM) and Combined SAM (cSAM) among children 6-59 months based on WHZ and
or MUAC (mm) is shown in table 5-21.
Table 5-21 : Prevalence of Combined Acute Malnutrtion based on WHZ and/or MUAC for children 6-59 months old
5.7. Proportion of acutely malnourished children enrolled in & referred to a nutrition program
The number of children enrolled in the nearby therapeutic feeding program was only 11.8 % and 7.7% in
segment A and segment B, respectively. Overall, of children identified as acutely malnourished by the
survey teams only 20.6% in segment A and 12.8% in segment B were enrolled in a program at the time of
survey (Table 5-22). The low coverage of nutrition services is seen as a gap in response needs in the camps.
Qala-e-Naw city IDP camp
(Segment A) Qala-e-Naw city IDP camp
(Segment B)
n % n %
Diarrhea 6-59 months, two weeks recall
139 31.6 % 160 33.9 %
Qala-e-Naw city IDP camp
(Segment A) Qala-e-Naw city IDP camp
(Segment B)
n % n %
Global Acute Malnutrition (GAM) MUAC < 230 mm
58 28.4% 88 39.3%
Moderate Acute Malnutrition (MAM) MUAC < 230 -≥185 mm
56 27.5% 87 38.9%
Severe Acute Malnutrition (SAM) MUAC < 185 mm
2 0.9% 1 0.4%
24
All acutely malnourished children found during assessment were referred using referral forms to the
nearby health centre with OPD-SAM and OPD-MAM programme.
Table 5- 22: Proportion of Acutely Malnourished Children 6-59 Months Enrolled in a Treatment Programme
Sample Enrolled in
an OPD-SAM Enrolled in an
OPD-MAM
Enrolled in an IPD-SAM Not Enrolled
Acutely malnourished children 6-59 months by WHZ, MUAC, or oedema (N=45) in segment A
(4) 8.9 % (3) 6.7 % (0) 0.0 % (38) 84.4 %
Acutely malnourished children 6-59 months by WHZ, MUAC, or oedema (N=58) in segment B
(3) 5.2 % (2) 3.4 % (0) 0.0 % (53) 91.4 %
6. DISCUSSION
6.1. Nutritional status
The survey results in segment A and segment B revealed GAM rates of 7.5 % (5.6 - 10.0 95% C.I.) and 8.3%
(5.8-11.8 95% CI), respectively. The GAM prevalence based on weight-for-height <-2 z-scores was
classified as medium for both camps according to WHO-UNICEF thresholds for the level of severity of
malnutrition6. There was no significant difference in the level of acute malnutrition between the two
segments of Qala-e-Naw city IDP camp.
The prevalence of cGAM in segment A and segment B was 10.9% (8.4-14.0 95% C.I.) and 13.1% (10.7-15.8
95 % CI), respectively. This indicates a higher proportion of children under-five affected by acute
malnutrition in the camps when considering both WHZ and MUAC criteria instead of considering
separately those 2 indicators. Combined prevalence captures a greater proportion of acute malnourished
children 6-59 months, and may inform better the estimation of SAM and MAM caseloads in the camp,
ultimately, strengthening planning and programming7.
6According to WHO-UNICEF (2018) new prevalence thresholds for the level of severity of malnutrition, GAM rates less than 2.5% are very low, GAM rates between 2.5 - <5% are low, GAM rates between 5-<10% indicate the situation is medium, GAM rates between 10-<15% are high, while GAM rates of 15% and above are very high. https://www.who.int/nutrition/team/prevalence-thresholds-wasting-overweight-stunting-children-paper.pdf 7 The Afghanistan national Integrated Management of Acute Malnutrition (IMAM) guideline includes both WHZ and MUAC as independent admission criteria for SAM and MAM treatment centers
Stunting, identify as low height for age z-score, is caused by long-term insufficient nutrient intake and/or
frequent infections. The stunting rates in both segments are categorized as very high according to WHO-
UNICEF new thresholds of a prevalence8: 40.0% (35.3 - 44.9 95% CI) in segment A, and 47.5 % (40.2 - 55.0
95% CI) in segment B. Very high stunting levels are usually seen in contexts with very low access to health
services, low sanitation levels and low maternal nutritional status. The proportion of malnourished
pregnant and lactating women recorded in the two assessments was high with 28.4% of PLW in segment
A and 39.3% of PLW in segment B being found to have a MUAC of <23cm. Maternal undernutrition affects
a woman’s chances of surviving pregnancy as well as her child’s health. Nutritional status of pregnant and
lactating women are crucial for ensuring healthy fetal growth and development. There is need to design
programs to reverse the high prevalence of chronic malnutrition and maternal malnutrition with all
sectors involved.
The underweight prevalence is higher in segment B, 26.6% (22.3-31.4 95 % C.I) than segment A, 21.6%
(17.7 – 26.1 95% C.I) though not statistically significant. The prevalence of underweight is classified as high
in both camps, using the WHO classification9 for assessing severity of malnutrition by prevalence ranges
among children under 5 years of age
Although not significant, there was a slight decline in the rates of acute malnutrition (figure 2), where a
GAM rate of 10.0 (6.6 - 15.0; 95% CI) and SAM rate of 2.7% (1.2 - 6.0; 95% CI) was recorded in June 2018
in the selected hotspot locations of Badghis province. The reduction in acute malnutrition can be
8 According to WHO-UNICEF (2018) new prevalence thresholds for the level of severity of malnutrition, stunting rates less than 2.5% are very low, stunting rates between 2.5 - <10% are low, stunting rates between 10 - <20% are classified as medium, stunting rates between 20 - <30% are high, while stunting rates of 30% and above are very high. https://www.who.int/nutrition/team/prevalence-thresholds-wasting-overweight-stunting-children-paper.pdf 9 According to WHO (2000) Classification for assessing severity of malnutrition by prevalence, underweight rates less than 10% are low, underweight rates between 10 - 19% are medium, underweight rates between 20 - 29% are classified as high, underweight rates of 30% and above are very high.
Annex 5: Rapid SMART Assessment questionnaires for children and
pregnant and lactating women Date
(dd/mm/year) Cluster Name
Cluster Number Team Number HH Number
Child Questionnaire 0-59 months
Note only if length is measured for a child who is older than 2 years or height is measured for a child who is younger than 2 years, due to unavoidable circumstances in the field. Child Questionnaire
Child (6-59 months) ID Number
For any child that is identified as acutely malnourished (WHZ, MUAC, or edema)
Q1. Is the child currently receiving any malnutrition treatment services?
Probe, ask for enrollment card, and observe the treatment food (RUTF / RUSF) to
identify the type of treatment service
1=OPD SAM
2=OPD MAM
3=IPD SAM
4=No treatment
98=Don’t know
If the child is not enrolled in a treatment program, refer to nearest appropriate
treatment center
Q2. Did you refer the child?
1=yes
1 2 3 4 5 6 7 8 9 10
Child ID
Sex (f/m)
Birthday (dd/mm/yyyy)
Age (months)
Weight (00.0 kg)
Height or length
(00.0 cm)
Measure (l/h)*
Bilateral
edema Y/N
MUAC (000 mm)
Left arm
With clothes
(y/n)
1
2
3
4
5
6
7
8
33
0=no
Woman (15-49 years) age in years
Physiologic Status of woman
1=Pregnant
2=Lactating
3=Pregnant and lactating
4=None
MUAC measurement (mm)
Child (0-59 months) ID Number
Q3. In the past two weeks, has the child had diarrhea?
Diarrhea defined as the passage of three or more loose or liquid