PREPARING A RAPID NUTRITIONAL ASSESSMENT DURING EMERGENCY

JENIS DARURAT

• Bencana alam terisolir (akses sulit) e.g. Banjir mentawai

  PREPARING A RAPID NUTRITIONAL

• •

  Bencana alam tidak tidak terisolir e.g. Banjir jakarta

  ASSESSMENT DURING • Kerawanan pangan, e.g. EMERGENCY

• KLB gizi buruk

  Nia Novita Wirawan Department of Nutrition Faculty of Medicine University of Brawijaya

  STEPS IN RAPID ASSESSMENT DURING EMERGENCIES

• Warming up 2 (Group 2): Define objective
• Nutritional survey in emergency situation Target population
• Alternative sampling desain for emergency situation Define geographical area
• Survey Methodology Planning a survey
>Planning
• Gather information as many as possible from all possible resources
>Survey protocol
• training & supervision during survey
• data analysis & interpretation
• interpreting result & report fin
• Design data collection protocol

NECESSARY DATA

• the total number of displaced persons
• Census and/or registration:
• In the case of displaced persons, it may be possible to carry out a systematic registration of persons as they arrive at the new site.
>total affected population, and of average household size  useful when planning an intervention, and when calculating needed quantities of food, water,
• Exhaustive counting of habitats (or households)
• Habitats in the target area are counted one by one. The average

• Population figures are also needed to provide the

  denominators for indicators (such as mortality rates)

  Source of Information

  This may be coupled with other aid activities, such as distribution of food cards, detection of malnutrition, measles immunization, etc.

  number of persons per household is obtained from a sample of households, selected at random or through systematic sampling.

• Age and sex distribution of the population  programmed interventions can target specific groups, such as children under 5 or pregnant and lactating mothers
• The total population is then obtained by multiplying the total number of habitats by the average number of persons per household.

  Source of Information

  Source of Information

• Immunization coverage or programme activity data
• Suppose the immunization coverage rate age 6-59 months was 80% and that 10,000 children in this age group were immunized.
• The total children in this age group is therefore 10,000/0.80 = 12,500.

• •

  “Guesstimates”
• Key informants’ estimates, i.e. estimates by people and community leaders from the area,
• Children in this age group ± 16 percent of the total population  estimate total population at about 12,500/0.16, or about 78,000 persons
• In these situations it is important to select more than one informant and to triangulate the information provided by each to determine its reliability.
• Area sampling
• Delineate the boundaries of the target area in which people are living.
• Walk or drive along the boundary to identify key landmarks. Note their location, preferably using GPS.
• Draw a map, and calculate the total surface area.
• Draw a grid on the map, using squares of 25m x 25m or 100m x 100m, depending on the scale of the map.
• Randomly select a number of squares or GPS points, say 15.
• Count the number of people living in habitats within each square.
• Estimate the population by extrapolating the average number of persons per square, to the total number of squares counted for the full surface area.

• •

  the sampling frame has a known and non-zero chance of being selected into the survey sample.

  “Probability sampling means that every single individual in

• Non-probability methods of sampling such as quota

  or convenience sampling and random walk, may introduce bias into the survey, will throw findings into question, and are not accepted by WHO (their

  emphasis).” Source: WHO (undated)

HOW TO CALCULATE SAMPLE SIZE

  2

  2 Define the objective N = t x (p x q)/d • •

• Measurement unit vs Respondents (from whom we obtain

  N = sample size

  the data)

  t= risk errors 1,96 atau 5%

• May be the same, may be different

  p = expected prevalence of malnutrition as fraction of 1

• In case of the same  measurement unit is HH

  q= 1-p expected non prevalence

• Different  if measurement unit is children U5, but respondents is

  d= level of precision

  the mother to obtain information of the child Simple random or systematic _{2 2} N=1,96 x (0.15 x 0.85) / (0,03) cluster sample

  X design effect of 2

OTHER APPROACH OF SAMPLING DESIGN

  CAUTION

• If sample size is calculated for the number of e.g Children

  30X30 DESIGN (widely used) U5  HH to be contacted can be more

• •

  Alternative - LQAS:

  Depends on estimate proportion of selected target grup

  33X6

  67X3 DESIGN

  Number of family member/HH Sequential design

• Sequential design PRECISION

  a “look” at the data can be made after collection of each cluster

• •

  •

  When population-based surveys are used to obtain point

• If the data indicate a clear decision about the threshold level of

  estimates for indicators, it is important to consider the interest (outcomes 1 or 2, above), data collection can stop. If a clear precision and accuracy of the estimates derived from the decision about the threshold level of acute malnutrition cannot be data. made, data collection continues.

• •

  The precision of an estimate is a statistical quantifica
• The sequential design thus allows for sampling to stop early

  of the reproducability of the measurement. It is usually

• Provided that the empirical data give a clear indication as to whether

  the prevalence of acute malnutrition is above or below the threshold reported as a 95% confidence interval (CI) and interpreted level before data from the full 67 clusters have been collected. as follows:

• However, the drawback of the design is that it does not allow for p
• Precision is different from accuracy. Whereas precision is

  estimates of child- and household-level indicators unless the full a statistical quantification of the certainty of the sample size of 67 clusters, 3 observations per cluster (n=201) is measurement, accuracy is the veracity of a measurement. collected

HOW TO SELECT SUBJECTS

  Lot quality assurance sampling (LQAS) TWO STAGE cluster sampling

• The analysis approach is relevant for health programs
>

•

since it is often useful to know whether a certain condition First step: (e.g., the prevalence of a particular disease) in a g
• Select the cluster or primary sampling units (PSUs) by

  population exceeds a critical threshold level or if a Probability Proportionate to Size (PPS). program (e.g., immunization mop-up operation) has

• With PPS, the probability of selecting a PSU for reached a certain target.

  sampling is proportionate to the population size of the

• LQAS analysis is also useful in emergency settings,

  PSU where government and humanitarian agencies often need

• to know whether the prevalence of acute malnutrition has

  A more populous PSU (cluster) therefore has a greater exceeded a certain threshold level or not. The threshold chance of being selected for sampling . levels of 10%, 15%, and 20% acute malnutrition prevalence are often used to determine the severity of a situation

STAGE 1: STEPS 1-4 STAGE 1: STEPS 5-6

• A random number is then selected between 1 and 3,742.

• •

  Complete list of the PSUs (cluster) in the survey area

  along with the respective population size of each PSU.

• The PSU corresponding to where the random number falls is the

  Generally, a random ordering of PSUs or ordering of the first cluster selected for sampling. PSUs according to region is preferred (columns titled

• Assume the random number 1,820 is selected

  “Village” and “Total Population”) Dabi is the first of the 33 clusters selected for sampling. This is

• Starting at the top of the list, calculate the cumulative

  because the number 1,820 falls between the corresponding population size and continue this process for the entire cumulative population range of 1,409 and 2,758 in the “Range” column.

  PSU list (“Cumulative Population” and “Range” column

• Compute the Sampling Interval (SI) by dividing the total The procedure for selecting the remaining 32 clusters to

  cumulative population by the total number of clusters to be sampled is shown below. Notice the decimals are kept be sampled for cumulative addition, but not for cluster selection.

• For the 33x6 design, divide the total population of Wobelleno,
• Cluster 1 = 1,820.00 123,498, by the 33 clusters: 123,498 / 33 = 3,742.36.
• Cluster 2 = 1,820.00 + 3,742.46 = 5,562.46

  Cluster selected for sampling with PPS CAUTION

• It may be the case that some of the clusters selected for

  sampling are later found to be inaccessible due to travel difficulties or security concerns.

• Should be avoided as much as possible as the inability to

  collect data from any of the original clusters selected for sampling can bias the results obtained.

• If it is known in advance that there are PSUs in the

  assessment area that will not be able to be sampled due to the security situation or travel difficulties  should not be included in the sampling frame used for the PPS cluster selection. STAGE 2: SELECTION OF SAMPLE WITHIN SELECTED CLUSTER

SIMPLE RANDOM SAMPLING

• Random walk;
• still widely adopted and accepted as an appropriate method to

  select observations within a cluster in emergency settings

• Compact segment sampling;
>Simple random samp
• The method is rarely used in an emergency setting, however, as it

  requires a complete listing (or enumeration) of all the observations (children or households) residing in the clusters selected for sampling

SYSTEMATIC SAMPLING

• Suppose a village consists of 100 households, and we

  want to interview 20 of them. We would do the following:

• A listing of these 100 households, or a map showing the

  location of these 100 households, would constitute a sample frame (Sample size is 20, and the sampling fraction is 1 in 5)

• To select a simple random sample (SRS), give each

  household a different number at @ paper • shake the paper well, and draw out 20 pieces of paper.

• Alternatively use a random number generator

STRATIFIED SAMPLING

• A numbered listing of all the 100 households is created,

  and an appropriate sampling interval (100/20=5) is worked out.

• An initial household is selected at random within the first

  sampling interval (let us suppose we selected the fourth household), and then the sampling interval is added to identify the remaining households: 4, 9, 14, 19, etc.

• good to have the list running in a logical geographic order,

  from one end of the village to the other

• Weakness: once we have made the first selection, the

  rest of the selections are predetermined, while those not selected had no chance of being picked.

STRATIFIED SAMPLING CLUSTER SAMPLING

  An approach in which each member of the population is

• systematic sampling is combined with other methods of

  assigned to a group (cluster) sampling

• Clusters are randomly selected
• E.g. Households close to a main road vs far from the
• All members of selected clusters are included in the sample.

  Steps:

• Appropriate for situations in which there is no readily
• Creating two sampling strata (one containing the houses

  available sampling frame (such as a camp census list) but in a predefined distance from the road and the other with for which it is easy to obtain lists of subgroups or clusters the households that are further away) of individuals, e.g. compounds or buildings or tents

  Important design consideration is sample size sample

• •

  • Selecting the samples separately within each stratum (2
• two key elements to this decision:

  sampling fraction: ratio sample size to total number how many clusters to take

• population)

  how many households to interview within each cluster

Multistage sampling:
• Binkin et al (2007) considers appropriate sample size for a nutrition
• clusters are selected but this time sample members are

  survey in a situation of famine 30 clusters of 30 children should provide reasonably valid estimates of the prevalence of malnutrition selected within the cluster using simple random or with at least 95 percent confidence that the estimated prevalence systematic sampling, rather than taking the whole cluster. differs from the true value by no more than 5 percent.

• The 30 x 30 approach has been used most frequently in emergencies

  and is known to provide reliable population estimates, however it is also time and resource intensive. Fanta-2, 2009 looks at alternative sampling designs which can

• provide reli
• estimates on the prevalence of acute malnutrition
• 33 clusters with 6 observations in each
• 67 clusters with 3 observations in each a sequential design.
• Results:

  ’67 x 3' design provides estimates that are almost as precise as those provided by the ’30 x 30' design, but requires only one-third to one-half of the field time to collect the data.

  Kabupaten

COMPLEX SAMPLE DESIGN

  Kecamatan 1 (region)

• Sampling frame consisting of e.g. all the villages, Interest in selecting a sample of households across these villages.
• Village B, dst

  But rather than go to every village which would be very expensive, we might prefer to select a sample of villages, and then interview a cluster of households within the selected villages

• Village A PSU

  Daftar Daftar

  STEPS:

  rumah rumah

• The villages might be grouped into strata according to their region

  tangga tangga MOS

• These villages form the primary sampling units (PSUs), and can be

  (household (household

  placed in a logical geographic order, which would provide an element 1-150

  1-67 of implicit stratification.

• A common approach is to begin by listing the villages along with some measure of size (MOS) (e.g. number of households in them).

  Village is selected systematically with probability proportional to this MOS, e.g: Village A with 150 HH, with total population in Kabupaten

  Within a region, a certain number of villages are then selected

• 2500 HH and calculated minimal sample size is 1000. PPS is

  systematically with probability proportional to this MOS, and within the

  150/2500 x 1000 = X selected HH number in village A selected villages a fixed number of households are selected. SAMPLING DURING IMMEDIATE SAMPLING DURING IMMEDIATE RESPONSE PHASE RESPONSE PHASE

• May not be possible to carry out a strict probability sample CONSIDERATION:

  survey: access/mobility issues, time/resource factors

• •

  Coverage: cover as wide a cross-section of the relevant

  and/or because the absence of good population data to population and geographical area as possible. Do not only create a suitable sample frame include easy-to-reach elements.

• non-probabilistic sampling
• Sample frame: Establish clearly the sample frame is (list

  of people, villages or a map)

  Sampling methods: Use probability sampling if at all

• •

  possible and justify if use non-probability samp
• Sample size: Use as large a sample as fit in with

  resources. Better to visit more locations and interview less people in each, than vice versa.

  Secondary data: Make full use of secondary data

• •

  JUDGEMENT SAMPLING Purposive sampling

• •

  •

  Best choice of sampling in the immediate aftermath of an “experts” select the sample

  emergency when it is not possible to apply probability

• extension of convenience sampling sampling.
• E.g: the expert may decide to draw the entire sample
• Within this approach, selection of the sample is done according

  one to specified criteria to represent certain cases, e.g. the

• extremes or the norm includes many villages.

  “representative” village, even though the target population

• •

  stratify possible localities according to socio-economic or

  When using this method, the researcher must be demographic criteria and visit diverse areas e.g. urban and

• rural areas, and with both residents and non-residents

  confident that the chosen sample is truly representative of (displaced persons), higher/lower prevalence of chronic the entire population (extremely familiar with all villages to malnutrition, different ethnic groups, etc. have this confidence)

• Once sites, villages or households have been stratified by
• In reality, it is quite unlikely that the selected villages or

  some fixed criteria then a form of quota sampling can be households would be representative of all villages or applied households. The criteria for site selection (IASC, 2009)

RANDOM WALK METHOD

• Urgent need: First priority will be to assess areas in greatest need
• An approach which is often used in post-emergency

  (Consider vulnerability suc as population size, density and influx, surveys when complete data on the affected populations availability of water and food, reported epidemics or malnutrition. is still not available

  Accessibility: Where overall needs are urgent, widespread and unmet,

• it is justifiable to focus on accessible areas. However, w
• Ensuring that information is collected from households

  inaccessibility is a widespread problem or coincides with very urgent with different proximity to the village centre, roads, stream needs, the extreme rapid assessment – a two-hour visit – may be necessary to fill information gaps.

• Gaps in existing knowledge: Cover locations about which little is

  known or where key information is lacking, especially where no relief agencies are yet working.

• Worst-/best-case scenarios are often used to provide some reference for interpreting data.

  Notes: sites selected are those most urgently in need of assistance

RANDOM WALK METHOD RANDOM WALK METHOD

  Begin the sampling at some randomly defined

• geographical point, and then follow a specified systematic
• Greet Community Leader and Seek Permission to

  Conduct Survey path of travel in order to select the households to be

• Explain the Random Selection Process interviewed.
• It is recommended that the interview team requests t
• This might entail selecting every nth household, or else

  accompanied by the community leader or another respected screening each household along the path of travel to member of the community during data collection at the cluster site locate the presence of the special target population such

  The team should describe to the community leader/member the

• as children under 5.

  importance that a random procedure be used to select the • In the latter case, each qualifying household is households to be sampled. interviewed, until the quota is reached.

• Identify the Center of the Cluster Site

  References: (FANTA-2 Project, 2009) and (ICRC/IFRC, 2008).

RANDOM WALK METHOD RANDOM WALK METHOD

• Spin the Pen Map and Enumerate Households in Randomly Selected
• Note of the direction the ball of the pen is pointing Direction • • This is the direction that has been randomly selected for the walks from the center of the cluster site to the perimeter of the

  interview team to walk in order to identify the first random cluster site, in the direction indicated by the ball of the pen

• household to be sampled in the cluster.

  Households that lie approximately along the line extending from the center of the cluster site to the perimeter of the cluster site in the direction of the ball of the pen are mapped and enumerated.

• Even if walking in the indicated direction is difficult, this is the

  direction along which the households in the cluster need to be mapped and enumerated.

RANDOM WALK METHOD RANDOM WALK

• Select a Random Number to Identify the First Random

  Household to Sample in the Cluster

• The random number selected should fall between 1 and the total

  number of households enumerated during the walk to the perimeter of the village.

• If the random number selected is greater than the total number of

  households enumerated a new random number should be selected.

• Select Subsequent Households to Sample in the Cluster

BEYOND IMMEDIATE RESPONSE

• Probability sampling, e.g. Cluster sampling • Two important outcomes.
>

•

30 Cluster with probability proportional to the most recent census estimate of size, 7 children aged 12-23 months in each cluster. Total 210 chil
• Possible to derive estimates from the survey, and to say that the sample is representative of the target population.
• Possible to calculate sampling errors, and thus get a good idea of the precision of the survey estimates.
• Selecting the children in each selected cluster by random
• Starts at a central point,
• Selects a random direction from that point (‘spinning the pen’),
• Choose a dwelling at random among those along the line from the centre to the edge of the community.
>All children in the household in the age range 12-23 months are selected and the mother or caregiver interviewed (In multi- household dwellings, all households are visit
• Starting from this household, the next nearest household is visited in turn until at least seven children have been found.
• Objectives, neccesary information and possible indicators

  1 There is some evidence that women’s dietary diversity also reflects household _{economic access to food. ** Those foods are not included because the respondent may not know which other household members purchase and eat outside the home.}

  9

  12

  Number of food groups included in the score

  All foods eaten by the individual of interest, consumed inside or outside the home, irrespective of where they were prepared.

  Purchased outside the home and consumed Outside**

  Included and excluded foods Prepared in the home and consumed in the home or outside the home; or Purchased or gathered outside and consumed in the home

  KEMAREN Wanita usia 15-49 tahun atau kelompok umur lain

  IDDS Respondent Orang yang bertanggung Jawab pada persiapan makanan untuk keluarga

  DIFFERENCES HDDS – IDDS HDDS

  for integrated rapid food and nutrition security assessments (link)

  ASSESSMENT OF FOOD SECURITY DURING EMERGENCY

  walk

  e.g. RAPID ASSESSMENT SURVEY FOR EXPANDED PROGRAMME ON IMMUNIZATION (EPI)

  If the region to be surveyed is very large or heterogeneous  split into strata and 30 clusters selected from each stratum

  E.g. Survey in a rural area, select 30 villages at random (preferably by sampling with probability proportional to size) from a list of all the villages in the affected area, and then pick a sample of households in those selected villages (e.g. By random walk).

NOT INCLUDES:

  Dietary Diversity Questionnaire Form 1 Sarapa n Snack Makan Siang Snack Makan malam Snack ^{Sebutkan semua makanan dan minuman (makan dan selingan) yang dimakan/diminum paling tidak oleh SALAH SATU anggota keluarga anda KEMAREN mulai pagi hingga malam hari baik di rumah maupun di luar rumah . Jika yagn dikonsumsi berupa} “mixed dishes”, tanyakan apa bahan-bahannya. _{Jika responden sudah selsai menyebutkan, tanyakan makanan/snack yang kemungkinan belum disebutkan} [Households: include foods eaten by any member of the household, and exclude _{Jika Sudah selsai isilah formulir 2 berdasarkan formulir 1. foods purchased and eaten outside the home] Jika ada kelompok makanan (food group) yang belum disebutkan, tanyakan kembali kepada respodnen.}

^Question

^{Number Food Group Examples Yes=1, No=0 1 Cereals Corn/maize, rice, wheat or any other grains/foods made from these (bread, noodles, mihun, bihun, porridge}

²

^{White Roots and tubers White potatos, white cassava, 'mbothe, talas, or other foods made from roots}

³

^{Vitamin A rich vegetables and tubers Pumpkin, carrot, squash, sweet potato, 'benthoel', 'red talas',}

⁴

^{Dark Green Leafy Vegetables Cassava leaves, spinach, 'daun singkong', daun kacang, kangkung, sawi, papaya leaves, etc 5 Other Vegetables Tomato, onion, eggplant, 6 Vitamin A rich fruit Ripe manggo, ripe papaya, and juice made from these 7 Other fruit Star fruit, banana, orange, rambutan, avocado, and juice made from these 8 Organ meat Liver, kidney, heart or other organ meats or blood-based food 9 Flesh Meat Beef, pork, lamb, goat, rabbit, chichen, duck, other birds, insects 10 Eggs Eggs from chicken, duck, or any other eggs 11 Fish and seafood Fresh or other dried fish or shellfish}

₁₂

^{Legumes, nuts and} _seeds ^{Dried beans, lentils, nuts, seeds or food made from these (sambal pecel,} _{tempe, tahu, etc)}

₁₃

_{Milk and Milk products Milk, cheese, yogurt or other milk products 14 Oils and fats Oil, fats, butter added to food or used for cooking 15 Sweets Sugar, honey, sweetened juice drinks, suggary foods such as chocolates,c andies, cookies and cakes}

₁₆

_{Spice, condiments, beverages Spices (black pepper, salt), condiments (soy sauce, tomato sauce, ketchup), cofee, tea, alcoholic bvereages}

  FORM 2 Aggregation of food groups from the questionnaire to create HDDS

  1 The vegetable food group is a combination of vitamin A rich vegetables and tubers, dark green leafy vegetables and other vegetables.

  2 The fruit group is a combination of vitamin A rich fruits and other fruits.

  3 The meat group is a combination of organ meat and flesh meat.

^Question

^{Number Food Group Examples Yes=1, No=0 1 Cereals Corn/maize, rice, wheat or any other grains/foods made from these (bread, noodles, mihun, bihun, porridge 2 White tubers Pumpkin, carrot, squash, sweet potato, 'benthoel', 'red talas',}

³

Vitamin A rich vegetables and tubers ^{White potatos, white cassava, 'mbothe, talas, or other foods made from roots}

₄

_{Dark green leafy vegetables Cassava leaves, spinach, 'daun singkong', daun kacang, kangkung, sawi, papaya leaves, etc}

₅

_{Other vegetables Tomato, onion, eggplant,}

₆

_{Vitamin A rich fruits Ripe manggo, ripe papaya, and juice made from these}

₇

_{Other fruits Star fruit, banana, orange, rambutan, avocado, jambu biji, and juice made from these 8 Organ meat (iron rich) Liver, kidney, heart or other organ meats or blood-based food 9 Flesh meat Beef, pork, lamb, goat, rabbit, chichen, duck, other birds, insects}

  

10

^{Eggs Eggs from chicken, duck, or any other eggs}

₁₁

_{Fish Fresh or other dried fish or shellfish}

₁₂

_{Legumes, nuts and seeds Dried beans, lentils, nuts, seeds or food made from these (sambal pecel, tempe, tahu, etc)}

₁₃

_{Milk and milk products Milk, cheese, yogurt or other milk products}

₁₄

_{Oils and fats (and red palm oil if applicable) Oil, fats, butter added to food or used for cooking 15 Sweets}

  

16

^{Spice, condiments, beverages} FORM 2

• •

  8 Food Groups in IDD for children, depending on the importance of certain foods in children’s d
• Score: 0-8

  7. Milk and milk products 8.

  4-5 medium

  < 3 low

  food habits)

  Sum HDDS Total no. of households ‘Cut off points’ in DDS?

  Sum will be between 0-12.

  HDDS Calculation

  Foods cooked in oil/fat

  6. Pulses/legumes/nuts

  Eggs

  4. Meat, poultry, fish, seafood 5.

  3. Other fruits or vegetables

  Vitamin A-rich plant foods

  1. Grains, roots or tubers 2.

  Specific food groups for IDD for children

  Aggregation of food groups from the questionnaire to create WDDS 1 The starchy staples food group is a combination of Cereals and White roots and tubers. _{2 The other vitamin A rich fruit and vegetable group is a combination of vitamin A rich vegetables and tubers and vitamin A rich fruit. 3 The other fruit and vegetable group is a combination of other fruit and other vegetables. 4 The meat group is a combination of meat and fish.}

• Cut off points depend on local circumstances (prevailing
• Step 1: Assign 1 if the food group/item consumed; 0 not consumed. Sum all the scores for various food groups.
• Rule of thumb:
• Step 2: The average IDDS for the sample population

  > 6 high

  sampling approaches can be adopted in integrated rapid food and nutrition security assessments

• When anthropometric measurements are taken, sampling

  is an important issue for the following reasons

• minimum sample size is needed for drawing conclusions about the

  population’s nutrition status that can be extrapolated to the larger population with a reasonable level of confidence.

• E.g. using a 30 x 30 cluster survey and a design effect of two

  needs 900 children under 5, confidence level of 95%, precision of 5%

• Large samples are usually needed to obtain precise

  estimates of malnutrition rates based on anthropometric measurements, while assessment of food availability and access, and information on the food security situation require smaller household samples.

  Source: WFP. 2009 Source: WFP. 2009 Source: WFP. 2009