2. Food Consumption Score - Nutrition

2. Food Consumption Score - Nutrition

VERSION

V5.0 - 2026.03 — Existing

INDICATOR CODE

2

TECHNICAL OWNER

PRG-S (Nutrition)

INDICATOR TYPE

Country Level Outcome Indicator

INDICATOR CLASSIFICATION

Complementary

INDICATOR SCOPE

Programme specific

APPLICABILITY

The selection of this indicator is recommended against the following sub-activities in CSPs logframes. Selection of the below sub-activities will NOT trigger in COMET the mandatory selection of this indicator:

1. General Distribution (GD);

2. Prevention of micronutrient deficiencies (PMD)

3. Prevention of stunting (STUN)

4. Prevention of acute malnutrition (PREV)

5. HIV Care and Treatment (HIV/TB_C&T)

6. School Meals Programme Take Home Incentives (SF_THI)

7. Food assistance for assets (FFA);

8. Food assistance for training (FFT)

9. Forecast-based anticipatory actions (FBA)

10. Other Climate Adaptation and Risk Management Activities (CAR)

11. Climate adapted assets and agricultural practices (CAP)

12. Smallholder Agricultural Market Support (SMS)

This indicator is associated with the nutrition sensitive marker selected at the sub-activity level.

UNIT OF MEASUREMENT & ANALYSIS

• Percentage of households that never consumed Vitamin A rich foods

• Percentage of households that never consumed Protein rich foods

• Percentage of households that never consumed Hem Iron rich foods

DEFINITION

The Food Consumption Score – Nutritional Quality indicator (FCS‑N) assesses the nutritional quality of household diets by examining the consumption of foods rich in three key nutrients (vitamin A, protein, and hem iron) using a seven-day recall tool. It provides deeper insight into the micronutrient adequacy of diets by analyzing the nutrient‑dense food groups that households consume.

RATIONALE

The data collected through the FCS‑N module supports analysis of household nutritional status by strengthening the link between food access, consumption patterns, and nutrition outcomes. FCS‑N builds on the Food Consumption Score (FCS) by examining the consumption of foods rich in protein, hem iron, and vitamin A. This provides additional insight into the micronutrient adequacy of household diets and helps identify potential nutrient gaps that are not captured by the standard FCS alone.

The selection of the three nutrient-rich groups of interest is supported by research and focuses on:

• Protein-rich foods: protein plays a key role in the growth and is crucial for the prevention of wasting as well as stunting which take place largely within the first 1,000 days.

• Hem Iron: Iron deficiency, one of the main causes of anaemia, affects approximately 25 percent of the world’s population, mainly pre-school children and women. The Lancet series (2008 and 2013) has documented long-term impacts on productivity and quality of life.

• Vitamin A: Vitamin A deficiency, if tackled before the age of five, can reduce mortality and infectious diseases such as measles, diarrhoea, and malaria by up to a third.

Building on the information provided by the standard FCS, the FCS‑N offers several added advantages:

• Identifies potential nutrient inadequacies at the household level

• Allows monitoring of trends in nutrient inadequacy over time

• Serves as a valuable indicator for tracking nutrient‑sensitive programme outcomes

• When combined with other indicators and process‑related tools, it supports decision‑making on the most appropriate food assistance modalities (food, cash, or vouchers).

DATA COLLECTION TOOL

Data Source

Household surveys embedded in Post‑Distribution Monitoring (PDM) and Food Security Outcome Monitoring (FSOM) questionnaires, where the FCS‑N module is routinely administered. These are primarily conducted via face‑to‑face interviews or remote modalities such as mVAM.

Data Collection Tool

The same module used to calculate FCS is applied for FCS-N , however, the expanded module must be applied. Some of the food groups are split into sub-groups to facilitate differentiation of the consumption of nutrient-rich foods from other less nutrient-rich items belonging to the same general food group:

• The vegetables group is sub-divided into dark green leafy vegetables (iron-rich) and deep yellow/orange vegetables (Vitamin-A rich) and less nutrient rich vegetables such as onions, white cabbage, etc.

• For the fruits group, it is important to distinguish between fruits rich in vitamin A – the deep yellow/orange ones – and less nutrient rich fruits such as apples, lemons, and oranges.

• It is important to distinguish the consumption of different types of flesh meats, rich in protein and iron, or organ meats that are also rich in Vitamin A from those that are less nutrient rich.

• Fortified foods (including CSB and Super Cereal) are of specific interest for FCS-N analysis and supplementary questions should be asked about consumption of these specific food groups as part of the food consumption module.

The module must be designed carefully based on knowledge of local diets and typical food items consumed. The above list can help to group different food items correctly by sub-group. Extensive training of enumerators using visuals such as sample foods or pictures is essential. This XLSForm will help in designing forms in Excel which can be converted to a MoDA or ODK form data collection software. The form can also be self-generated by selecting the sub-module Combined (FCS/FCSN) in the module Food Consumption in WFP Survey Designer.

SAMPLING REQUIREMENTS

Sample size: The recommended sample size is 270 per stratum per round of data collection, with consideration given to the parameters below:

• Population size (beneficiaries per stratum): at least 20,000

• Desired level of confidence: 90%

• Acceptable margin of error: 5%

• Response distribution: 50%

• Simple random sample (design effect): 1

If cluster sample is employed, sample size should increase by at least 50% (at least 405 households).

If the prevalence is lower or higher than 50%, or the beneficiaries per stratum less than 20,000 then sample size could be lower than 270, use the sample size tool for calculation.

Mandatory stratification:

• Programme activity

• Transfer modality

Optional stratification:

• Beneficiaries/non-beneficiaries (when relevant)

Guidance on sampling is available here.

Sample size tool: Raosoft sample size calculator

INDICATOR CALCULATION FOR REPORTING

This indicator is calculated by using the following steps:

1. Aggregate the individual food groups into nutrient rich food groups:

   1. Vitamin A rich foods: Dairy, Organ meat, Eggs, Orange vegetables, Green vegetables and Orange fruits.

   2. Protein-rich foods: Pulses, Dairy, Flesh meat, Organ meat, Fish and Eggs.

   3. Hem iron-rich foods: Flesh meat, Organ meat, and Fish.

2. Sum up the frequency of consumption of each food group to calculate the aggregated frequency of consumption by nutrient-rich food groups

   Example of calculating the Vitamin A rich group:

   Vitamin-A rich foods	Frequency (days consumed 7 days before the interview)	Sum of frequencies
   Dairy	3	13
   Organ meat	4
   Eggs	1
   Orange veg.	3
   Green veg.	2
   Orange fruits	0

   Note: this same process should be repeated for Protein-rich foods & Hem iron-rich foods

3. Build categories of frequency of food consumption groups

   For analysis, the consumption frequencies of each nutrient-rich food group are recoded into three categories:

   1 = 0 times (Never consumed)

   2 = 1-6 times (Consumed sometimes)

   3 = 7 times or more (Consumed at least 7 times)

   Following the example above, the frequency of a household’s consumption of Vitamin-A rich foods is 13. Thus, the household falls under the third group: ‘7 times or more’.

4. Calculate the percentage of households by frequency of consumption category (‘never’, ‘sometimes’ and ‘at least 7 times’) for each one of the three nutrient-rich food

For more details and syntax, please refer to Food Consumption Score Nutritional Quality in the VAM resource center here . Scripts in R, STATA and SPSS and sample data are also available on github for calculating this indicator.

DATA ENTRY AND DISAGGREGATION IN CORPORATE SYSTEMS

Values are recorded in the logframe. Each value has a reporting combination which is created based on:

• Sub-activity

• Location

• Beneficiary Group

Recommended disaggregation (in COMET):

• Sex

The baseline, target & follow-up values are reported as one number overall for each category as follows:

For COMET reporting: If the sample size is not representative of the mandatory disaggregation groups, please include a note indicating that the results are indicative for that specific group in both the COMET and ACR note sections.

For regular reporting: Ensure that the reporting accurately reflects categories with a representative sample size.

BASELINE

Baselines are set only once, at one of the following points:

1. At the beginning of the CSP, or

2. When the indicator is selected for reporting after the commencement of the CSP, or

3. When there is a change in target, location and/or modality that triggers a new reporting combination (target, location and modality) for an existing indicator.

Baselines remain fixed for the entire CSP period and are not recalculated annually, unless applicable above.

Baseline values should be established within three months before and no later than three months from the start date of activity implementation. However, it is strongly recommended to collect baseline values within one month prior to the start of activity implementation. The baseline could also be determined from a relevant WFP assessment conducted within the three months prior to the start of programme activity.

Baseline values in COMET are presented and reported in the same format as the follow‑up value table.

TARGET SETTING

Annual targets:

End of CSP target:

• Reduced prevalence of beneficiaries never consuming protein-rich foods compared to the pre-assistance baseline value

• Reduced prevalence of beneficiaries never consuming Hem Iron foods compared to the pre-assistance baseline value

• Reduced prevalence of beneficiaries never consuming Vitamin A compared to the pre-assistance baseline value.

Target values in COMET are presented in the same format as the follow‑up value table.

FREQUENCY OF DATA COLLECTION

Minimum: twice/year

It is strongly recommended that data collection for one of the follow-ups happens in the same period to the baseline. In addition, all follow-ups are to be conducted within the same period/number of days after food distributions. The data collection must take place between 7 to 21 days after food/cash distributions take place.

For years when a baseline is conducted, only one follow up is required.

INTERPRETATION

FCS‑N results should be analysed and reported across geographic areas, over time, and among relevant sub‑groups (e.g., activity type, transfer modality). When food assistance programmes are designed and implemented in a nutrition‑sensitive manner through appropriate food composition, choice of modality, and effective nutrition messaging, an increase in the consumption of protein‑rich, heme‑iron‑rich, and vitamin‑A‑rich foods would reasonably be expected.

During interpretation, it is important to account for potential sources of bias. Some nutrient‑rich foods may be seasonally available (e.g., mangoes or certain leafy vegetables), which can influence consumption patterns independent of programme effects. In addition, within each nutrient group, analysts should assess the frequency of consumption of individual food items, as increases may be driven by programme‑specific transfers (e.g., high protein consumption resulting from pulses provided through in‑kind assistance).

Findings should be reviewed jointly with the nutrition team to ensure accurate interpretation and to contextualize results within broader nutrition‑sensitive programming efforts.

REPORTING EXAMPLE(S)

Example from Goma (DRC)

In Goma, WFP beneficiaries demonstrated a higher daily consumption of protein‑rich foods (19%) compared with non‑beneficiaries (5%). However, there was no observed improvement in the daily consumption of iron‑rich foods among beneficiaries (1%). Differences were also noted between male‑ and female‑headed households in their consumption of protein‑rich, iron‑rich, and vitamin‑A‑rich foods during the data collection period. The trends are summarized below.

INDICATORS COLLECTED & ANALYSED AT THE SAME TIME

The following indicators may be reported along with this indicator:

Household level indicators:

• 1. Food Consumption Score-Nutrition (FCS)

• 3. Reduced Coping Strategies Index (rCSI)

• 4. Livelihood Coping Strategies - Food Security (LCS-FS)

• 5. Livelihood Coping Strategies - Essential Needs (LCS-EN)

• 6. Economic Capacity to Meet Essential Needs (ECMEN)

Individual level indicators: 10. MAD, 11. MDD-W (if applicable).

COMPLEMENTARY QUALITATIVE RESEARCH

Focus group discussions can be conducted in addition to the household level data collected to triangulate the information about dietary habits and the regular consumption of (1) Vitamin A-rich foods, (2) Protein-rich foods and (3) Hem iron-rich foods.

Example questions for a focus group discussion:

• Can you describe the typical foods consumed by households in your community? What are the three main staple food commodities consumed in your community?

• From your own perspective, how would you define a nutritious diet?

• Are there any specific foods that you consider to be important for meeting the nutritional needs of households in your community? Why are these foods important?

• Are there any specific challenges or barriers people in your community face in accessing and consuming a diverse range of foods?

• Are there any cultural or traditional practices that influence the food consumption choices in your community? Can you provide examples?

• What is their general perception of the assistance people receiving in your community?

DECISIONS DATA CAN INFORM

The three indicators (Protein-rich food, Vitamin A-rich food, Hem Iron-rich food) calculated from the FCS-N questionnaire module are essential for assessing the effectiveness of a WFP's nutrition-sensitive interventions aimed at meeting the nutrient needs of assisted households. These indicators provide valuable insights into the nutritional quality of the assistance provided and can help identify any gaps or areas for improvement in the intervention design.

This analysis can help select the appropriate food transfer modalities (food, cash, or vouchers) and feed into decisions on nutrition-sensitive programming. Furthermore, it can provide information to stakeholders in the nutrition sphere for analysis regarding the population’s nutritional intakes.

VISUALIZATION

Example:

LIMITATIONS

FCS-N is a household-level indicator and does not provide information about individual level intake or the consumption of different nutritionally vulnerable groups within the household such as infants, young children, pregnant & breastfeeding women.

FURTHER INFORMATION

Refer to the FCS-N page on the VAM Resource Centre or contact the Needs Assessments and Targeting Unit in GHQ (PRG-F) at global.assessmentandtargeting@wfp.org and the Nutrition Unit in GHQ (PRG-S).