Prevalence of Underweight (WfA)
English: % of children aged 6 - 59 months with a weight for age < –2 Z scores
French: % d'enfants âgés de 6 à 59 mois avec un poids pour l'âge < -2 Z-scores
Czech: % dětí ve věku 6-59 měsíců s hmotnostně-věkovým poměrem < -2 Z-skóre
What is its purpose?
The indicator measures the prevalence of underweight. It assesses to what degree (so called "Z-score") a child's weight for age (WfA) deviates from the weight of a child of the same age and sex in the 2006 WHO Growth Standards. It is a composite indicator which combines chronic and acute growth faltering.
How to Collect and Analyse the Required Data
Children's weight and age are (alongside with other data) assessed by anthropometric surveys using SMART methodology (local events calendars are used to correctly determine child's age). SMART's website provides all the required guidance, forms, training modules as well as Emergency Nutrition Assessment (ENA) software used for data analysis and reporting.
According to WHO, the prevalence of underweight (< –2 SD) shall be interpreted as:
< 10%: low prevalence
10-19%: medium prevalence
20-29%: high prevalence
≥ 30%: very high prevalence
1) This indicator relies on accurate age assessment. Since people often do not remember the exact dates of their children’s birth, the data collectors should never rely only on the information provided by caregivers and always verify the child’s age. This can be done by reviewing the child’s birth certificate or other documents; however, since many caregivers do not have such documents, it is essential that your data collectors are able to determine the child’s age by using local events calendars. Read FAO’s Guidelines (see below) to learn how to prepare local events calendars and how to train data collectors in their correct use.
2) Always collect and report gender disaggregated data (such disaggregation is automatically produced by ENA software).
3) Compared to measuring weight for height (showing wasting) and height for age (showing stunting), this indicator provides less useful data (as it is less clear what problem it represents). It is a composite indicator which combines chronic and acute growth faltering.
4) Since the differences in the prevalence of underweight are often relatively small (e.g. from 23.5% to 21%), SMART surveys need to be implemented to a maximum quality and precision. Always use a small margin of error (2-2.5%). If your team does not have sufficient experience with conducting SMART surveys, contract an in-country or headquarters-based advisor to design methodology, train your team and supervise the survey quality.
Access Additional Guidance
- ACF (2014) Rapid SMART Surveys Guidelines (.pdf)
- ACF (2014) Guide: Enquêtes nutritionnelles SMART rapides (.pdf)
- PIN (2015) Practical Checklist for Conducting Nutrition Surveys (.pdf)
- SMART methodology
- WHO (2010) Interpretation Guide (.pdf)
- FAO (2008) Guidelines for Estimating the Month and Year of Birth of Young Children (.pdf)