DOI: 10.3886/e108684v3
title: Assessment of nutritional status of children of pastoralists in a humanitarian setting: A Cross-sectional Standardized Monitoring and Assessment of Relief and Transitions Survey

description: The AVSI
Foundation in collaboration with the South Sudan Nutrition Cluster conducted a
SMART nutrition and mortality survey covering all the eight Payams of the
former Ikwoto County in the former Eastern Equitoria State. The main objective
of the survey was to assess the current prevalence of acute malnutrition and
retrospective mortality rates in the County. 

The Standardized
Methodology for Assessment in Relief and Transitions (SMART) which applies a
two-stage cluster sampling was used. A total of 623 children aged 6-59 months
from 532 households in 36 clusters were sampled for anthropometric
measurements. The mortality assessment was conducted concurrently in all 532
households. 

Additional information on Infant and Young Child
Feeding practices (IYCF) was collected in the 532 households visited to provide
more insight into possible risk factors associated with the high acute
malnutrition prevalence.  

The prevalence of Global Acute Malnutrition (GAM) defined
as Weight-for-Height 80%. Another 76.2% of children (0-23.9 months) were initiated
to breastfeeding within one hour after delivery. Introduction of solid,
semi-solid or soft foods among children aged 6 to 8.9 months was low (51.5%).
Findings indicated suboptimal IYCF practices.
description: Response Rates: Survey contains a total of 96% response rate on average on all questions
description: face-to-face interview~~
description: Children of pastoralists in South SudanSmallest Geographic Unit: Payam (Villages)
description: 1.1      Sampling methodology

<br>The survey applied a two-stage cluster sampling based on the
SMART methodology with clusters being selected using probability proportional
to population size (PPS).

<br><br>2.4.1 First stage
sampling <br>The first stage involved the assignment of the smallest
sampling unit called clusters which in this case were villages. A sampling
frame for clusters was prepared with assistance from the County Health
Department and the survey enumerators because they were familiar with the area.
All accessible villages along with their respective populations were entered
into the ENA for SMART software. Random selection of clusters from the total
number of villages in the County was done using the planning screen of ENA for
SMART software based on probability proportional to population size (PPS).
Clusters were defined as villages within Bomas in all the Payams of the County.
A total of 36 clusters were selected from the sampling frame generated from the
list of all villages in the County.

<br><br>2.4.2 Second stage
sampling

<br>Simple random sampling was used to select 15 households per
cluster to be surveyed. The household heads in the villages were listed with
the support of the village Chiefs. Once a complete list of household heads was
obtained, enumerators used ENA generated random numbers tables to select the
households from the sampling frame (household list). 2.4.3 Number of households
per cluster The number of households to be completed per day was determined
according to the time the team could spend in the field excluding
transportation, other procedures and break times. The details below were taken
into consideration when performing this calculation based on the given context:
1.     Departure from office at 8:00 am
and back at 6:00 pm. 2.     Average
travel time (to and from the field): 3 hours. 3.     Duration for initial introduction and
selection of households: 1 hour. 4.    
Breaks: 1 lunch break of 1hour. The above considerations gave an average
of 5 hours of working time in each cluster. 
If on average teams spent 10 minutes in each HH and 10 min traveling
from one HH to another, each team could comfortably reach 15 HH per day.  One day in each area (cluster) was assumed.
The total number of households in the sample was then divided by the number of
households to be completed in one day to determine the number of clusters to be
included in the survey.  528 HH/15 HH per
day = 35.2 clusters (when rounded up gives 36 clusters). Based on this
calculation 36 clusters were selected to be included in the survey. All the
selected clusters were surveyed and no replacements were done.