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How to Measure Individual Nutrition Status

In my previous blog I explained how to measure impact on Food and Nutrition Security at household level. But how about the differences between household members? In this blog I will elaborate on measuring impact on individual level.

How to Measure Individual Nutrition Status

By measuring on an individual level we can more efficiently focus on the most vulnerable, like infants and young children, adolescent girls and women of reproductive age. You can assume that once the nutrition situation of these individuals has been improved it means that the nutritional status of all household members has improved.

Why is it important to focus on adolescent girls and women of reproductive age? The nutritional status of a woman before and during pregnancy has a direct impact on the development and nutritional status of her baby. Malnutrition before and during pregnancy increases the risk of low birth weight and under nutrition during infancy.

In addition women have their own right to adequate food and to be free from hunger, regardless of being pregnant or not. Furthermore women make up 43% of the overall agricultural workforce[1]. In many societies they have the main responsibility for production, processing and preparation of food for household consumption.

To define the nutritional status of an individual measurements, such as weight and height, are often used. The level of anemia, vitamin A and Iodine deficiency are also important indicators for the nutrition status of an individual. These indicators form part of National Demographic and Health Surveys[2], which are managed by the public sector.

The results of these surveys are publically available for almost every country, normally providing averages from national to district level. These surveys provide an important source of secondary data for problem and/or context analyses during the design and preparation phase of your project interventions. However possibilities to use these data for measurement of impact of specific project interventions is limited given the aggregation of the data as well as the limited frequency of the surveys and the usual delay in publication of the results.

In practice it’s not easy to measure weight and height, leave alone to take blood samples to define levels of vitamin A and hemoglobin (iron). Therefore I don’t recommend to include this type of indicators in the monitoring of your food and nutrition security projects. Rather, I suggest you make use of simple indicators, like the Dietary Diversity Scoredeveloped by FAO and the USAID supported FANTA-project.

For poor people low quality, monotonous diets are usually the norm. When people consume mainly starchy staple foods and there is a lack of vegetables, fruits, meat and fish, there is a high risk for micronutrient deficiencies. In such cases dietary diversity can tell us a lot on the quality of the diet.

How can you determine dietary diversity? You can do this by measuring the variety of foods consumed, based on a classification of available foods. In July 2014 an international expert meeting defined theMinimum Dietary Diversity for Women (MDD-W)[3], based on the following ten food groups.

The benchmark for assessing the quality of diets of adolescent girls and women of reproductive age has been set at five out of these ten pre-defined food groups. Persons consuming foods from five or more of the 10 food groups have a greater likelihood of meeting their micronutrient needs than those consuming foods from fewer food groups. Depending on the context and the character of the research one could amplify the number of food groups.

How to go about the actual collection of dietary diversity data? Experiences have demonstrated that one should take into account the following do’s and don’ts to collect reliable data for a dietary diversity score:

  • Apply a so-called 24-hour recall questionnaire during a face-2-face interview, asking the respondent what she consumed the day before. In general respondents are able to recall quite accurately what they consumed the day before.
  • Don’t go back further one or maximum two days, as it will reduce the reliability of the provided information.
  • Don’t plan a survey directly after an unusual day, e.g. a national Holiday as this will result in data which does not reflect the respondent’s usual diet.
  • Don’t ask whether the respondent consumed starchy staple foods yesterday; rather ask whether the respondent had breakfast yesterday. If confirmative ask what the respondent consumed for breakfast, registering the food groups included.
  • Do check the ingredients used for the dishes that are mentioned. For this the enumerator needs basic knowledge about nutrition and food preparation, as well as good interviewing skills. This is to prevent ‘false positive answers’ based on leading questions. Besides breakfast the enumerator should check whether the respondent had lunch, dinner and snacks between meals and/or after dinner. Only include foods when a minimum of 15 grams/millilitres or more has been consumed.

In case you want to measure impact through the dietary diversity score,  you should be aware of the timing of your baseline, mid-term and end-term measurement. I recommended to do all measurements in the lean period of the year, to find out whether your interventions have actually improved the nutrition situation in the most difficult part of the year.

Applying a Dietary Diversity Score is more time consuming than theHFIAS and requires a good level of food and nutrition knowledge among the interviewers. We have experienced that it is worth the investment as the combination of HFIAS and DDS provides a solid and valuable source of information for designing, monitoring as well as evaluating food and nutrition programs. Also for this indicator the AKVO FLOW tool can be used effectively.


[1] FAO, 2011. The state of food and agriculture 2010-11

[2] USAID. The Demographic and Healt Surveys Program,http://dhsprogram.com/

[3] http://www.fantaproject.org/monitoring-and-evaluation/minimum-dietary-diversity-women-indicator-mddw

Author Marijke de Graaf
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