Related Experiment Video
Updated: Mar 28, 2026

A Complex Diving-For-Food Task to Investigate Social Organization and Interactions in Rats
Published on: May 8, 2021
Verifying Validity of the Household Dietary Diversity Score: An Application of Rasch Modeling
Wytse Vellema1, Sam Desiere2, Marijke D'Haese2
1Ghent University, Ghent, Belgium International Centre for Tropical Agriculture (CIAT), Cali, Colombia wytse.vellema@ugent.be.
Background:
The Household Dietary Diversity Score (HDDS) was developed to measure household food access, one of the levels of food security. Previous research has shown dietary diversity is related to food security. However, the validity of the HDDS in the form developed by the Food and Nutrition Technical Assistance (FANTA) project-12 food groups, 24-hour recall-and most frequently used by development organizations and nongovernmental organizations has never been verified.
Objective:
To verify the construct validity of the HDDS.
Methods:
A Rasch model was used to test the extent to which the HDDS meets the criteria required for interval scale measurement, using data from 1015 households in Colombia and Ecuador.
Results:
Different dietary patterns between Colombia and Ecuador and 2 cultural groups within Ecuador required data to be split into 3 subgroups. For each subgroup, the food groups meeting the criteria and their difficulty ranking were different. Refined indices, containing only those food groups meeting the criteria, contained 7 items in Colombia, 10 for Kichwa households in Ecuador, and 9 for migrant households.
Conclusion:
The indicator in its current form does not meet all criteria. Even when analyzing culturally homogenous subgroups within a small region, the components of the indicator do not form a reliable way of measuring household-level food access.
Related Concept Videos
Friedman Two-way Analysis of Variance by Ranks
Statistical Package for the Social Sciences (SPSS)
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
Two-Way ANOVA
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
One-Way ANOVA
One-Way ANOVA: Equal Sample Sizes
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
One-Way ANOVA: Unequal Sample Sizes

