GROWTH-SUPPORTING FOOD CONSUMPTION IN 6-23 MONTHS CHILDREN IN NORTHERN BENIN AND MINIMUM DIET DIVERSITY PREDICTION WITH SUPERVISED MACHINE LEARNING APPROACHES

Inadequate complementary feeding remains a major driver of child undernutrition in sub-Saharan Africa. Yet, the diet quality of infants and young children in northern Benin is poorly documented. This study monitored growth-supporting food consumption among children aged 6-23 months in the commune of Banikoara and assessed supervised machine learning (ML) approaches for predicting failure to achieve Minimum Dietary Diversity (MDD). A descriptive longitudinal study was conducted from November 2023 to July 2024 in five districts.Data were collected over five rounds using a non-quantitative 24-hour recall based on the infant and young child feeding diet quality questionnaire applied to 149 children. Multivariate Generalized Estimating Equations identified determinants of MDD, Egg and Flesh Food (EFF) and Fruit and Vegetable (FV) consumption.