FCS

Food Consumption Score (FCS)

The concept of measuring food security is rather elusive with no single method for its measurement. Food consumption in kilocalories is the gold standard for quantifying consumption and is regarded as the entry point for measuring food security. While it is considered one of the gold standards for food security, the collection of detailed food intake data is difficult and time consuming.

Through the development of the Food Consumption Score (FCS) in Southern Africa in 1996, World Food Programme (WFP)’s goal was to create a standard food consumption data collection instrument and analysis approach that was flexible enough for different needs and contexts but equally standard enough to have equally applicable analysis techniques and equally interpretable results that could be implemented in the field in a reasonable data collection and analysis timeframe.

The Food Consumption Score is a composite score based on dietary diversity, food frequency and relative nutritional importance of different food groups. FCS aggregates household-level data on the diversity and frequency of food groups consumed over he previous seven days which is then weighted according to the relative nutritional value of the consumed food groups. The FCS is meant to approach an indicator of food consumption that can be used to make comparisons between different countries and situations.

The frequency weighted diet diversity score or “Food Consumption Score” is calculated using the frequency of consumption of different food groups by a household during the seven days before the survey. The calculation steps are as follows:

Group food items in the specified food groups (condiments not included)
Sum all the consumption frequencies of food items within the same group
- Note: if potatoes were eaten on three of they last seven days, they are given a frequency score of 3. Similarly, if potatoes were eaten on three of the last seven days, twice a day on each of those three days, they are still allocated a frequency score of 3.
- Any summed food group frequency over 7 is recorded as 7
Multiply the value of each food group by its weight (see table below)
Sum the weighted food groups scores to obtain FCS
Determine the household’s food consumption status based on the following thresholds:
- Poor: 0 – 21
- Borderline: 21.5 – 35
- Acceptable: > 35

The two standard FSC thresholds were identified to distinguish different food consumption levels with a score of 21 set as the bare minimum a household is expected to eat. A score below 21 means that the household is unable to eat at least staples and vegetables on a daily basis and thus, would be considered to have poor food consumption. The second threshold was set at 35. Consequently, households scoring between 21 and 35 have borderline levels of food consumption while households scoring above 35 are estimated as having acceptable food consumption levels.

When creating a composite scoring system for dietary diversity, the choice of assigning weights is obligatory and subjective. Weights, like those in the FSC methodology, are typically constant across analyses to give the tool a better degree of standardisation. The FSC good group weights were determined and interpreted by a team of analysts of ‘nutrient density’. Although subjective, this weighting attempts to give greater importance to foods which are usually considered to have greater ‘nutrient density’ (meat and fish for example) and lesser importance to foods like sugar.

It is important to note that although both oil and sugar are weighted 0.5, combined, this has the effect of giving households a base of FSC 7. Subsequently, if this base diet of oil and sugar is combined only with frequent consumption starch base for seven days, the FSC score already meets the minimum threshold of 21. This, however, can clearly not be considered a borderline diet. To deal with this possible situation an adjustment to the FSC calculation is made as follows:

If through cluster analysis, the population is found to homogeneously consume oil and sugar almost daily, the thresholds for the three consumption groups can be raised from 21 and 35 to 28 and 42. By adding 7 to each threshold, the methodology takes into account the daily consumption of oil and sugar which equates to 7 points on the FSC.
FSC thresholds in this scenario change as follows:
- Poor: 0 – 28
- Borderline: 28.5 – 42
- Acceptable: > 42
If the populations display a heterogenous pattern of oil and sugar consumption, the approach of changing thresholds does not work. In such situations, eliminating the consumption of oil and sugar in the FSC calculation while continuing to use 21 and 35 as the cut-offs, is the best approach. However, this strategy introduces a downward bias in the FSC score and disregards the importance of oil in the diet. Nevertheless, it allows for a smoother FSC comparison between these populations.

To obtain accurate Food Consumption Scores, the questionnaire administered should properly account for food items that are consumed in very small quantities; defined in the FSC as condiments. For data collection purposes, the items known to be eaten as condiments should be identified during the questionnaire design and listed as separate food items. The enumerators should then be trained to clearly distinguish between condiments and the rest of the food groups. Weight cut-offs to differentiate between the use of food as a condiment or that of a main food are not to be used during data collection with respondents however, they may be appropriate when providing instructions to enumerators.

The guiding principle used to determine the FSC weights is the nutrient density of the food groups; the highest weights attached to foods with relatively high energy, good quality protein and a wide range of micro-nutrients that can easily be absorbed. The logic behind this weight assignment process is provided in the table below.

Advantages of the FCS methodology include:

A standardized and more transparent methodology
A repeatable data analysis within a dataset
A comparable analysis between datasets
The FCS is also able to capture both dietary diversity and food frequency

Drawbacks of this methodology include:

The assumption of the applicability of the analysis across time, context, location, population, etc.
The food group weight and food consumption group thresholds, although standardised, are based on certain inherently subjective choices
The analysis can mask important differing dietary patterns (for example, manioc consumers vs maize consumers) that have equal food consumption scores

The FCS has been validated and serves as a proxy for the quantity dimension or caloric sufficiency of food security and proves to be useful when it comes to categorizing and tracking households’ food security across time. The Food Consumption Score asks respondents to recall what they consumed over the past seven days and thus captures information about usual household diet. The FCS can be used for program monitoring and evaluations as well as population-level targeting. Since FCS is s standardized measure, it can also be used to compare households in different locations and can also be used to track cyclical changes in household diet if collected repeatedly across seasons or years.

The FSC methodology does not include information gathering of actual quantities of food eaten for the following reasons:

The inclusion of food groups in the list (vegetables, fruits, and so on) will prevent the accurate calculation of the caloric contribution of that group
The time and skill required to ask respondents questions on the actual amount of food consumed, while providing useful data, is too demanding on both time and enumerator capacity for most surveys
The bias respondents have when recalling the actual amounts eaten is generally accepted to be much greater than when they simply recall the number of days the food/food group was consumed

Generally, measures of food consumption diversity and frequency are correlated with caloric intake as well as micronutrient intake and results indicate the same is true for the FSC. However, in some contexts this addition of a separate module to measure quantities of food consumed may be of interest.

Additionally, since FCS is a continuous variable, standard statistics such as means and variance can be calculated while trends of means over time across categories can also be determined.

The choice to ulilise a seven-day recall period for the FSC is to ensure both good time coverage and “reliability” of a respondent’s memory. According to practical data collection experience by WFP, seven days seems to be the most appropriate recall period to capture information about a household’s usual diet while also taking into account the limits given by possible seasonal consumption.

Recall periods longer than seven days have proven to be problematic because their is an increase in respondents’ difficulty in remembering what meals they prepared. On the other hand, shorter recall period increase the likelihood of missing foods served habitually but infrequently in the household. This omission can, for example, happen on market days, Fridays (in Muslim areas) or Sundays (in Christian areas); alternatively, FCS would overestimate household consumption if the survey is done over these special days.

It is important to note that FCS and Household Dietary Diversity Score (HDDS) are highly correlated and therefore, can be used interchangeable as a measure of household-level diet diversity and as a validated proxy for energy sufficiency in most contexts. However, neither of these indicators can be used as a proxy for micronutrient adequacy as they have not been validated against gold standard measures of micronutrient adequacy.

In addition, when using both the FCS and HDDS, one faces the challenge of determining how to capture and whether to exclude small amounts of food. For both indicators, the accuracy to predict caloric adequacy increases by ensuring small items consumed in small amounts are excluded. Furthermore, both FCS and HDDS are not sensitive to intra-household inequities in food consumption and thus are not to be used in interventions targeting specific population groups such as nutritionally vulnerable women or children.

Since HDDS and FCS provide very similar information, the selection of one of the indicators over the other can often be driven by institutional preference (if an organisation or individual is interested in comparing their results to those of a WFP survey then FCS is preferable) or by the need for comparability with other surveys (if there is need to compare with other surveys that previously used HDDS then HDDS is preferable).