An Optimization Tool to Formulate Diets within a Supplementary Nutrition Program for Children.

Area of Science:

• Public Health Nutrition
• Food Science
• Operations Research

Background:

• Large-scale supplementary feeding programs face challenges in providing diverse, acceptable, and nutritionally complete foods.
• The Indian Supplementary Nutrition Program (SNP) offers dry take-home rations or hot cooked meals but requires optimization tools for local recipes.

Purpose of the Study:

• To develop a linear programming (LP) model for optimizing food provisions in supplementary feeding programs.
• To ensure diverse food options meet program guidelines and budget constraints using locally available ingredients.

Main Methods:

• An LP algorithm was employed to generate optimized dry take-home rations or weekly hot cooked meal menus.
• A comprehensive food database was created from a nationwide survey to ensure recipe diversity and adherence to beneficiary guidelines.

Main Results:

• An interactive web-based application was developed to optimize feeding programs at any population scale.
• Optimized diets met SNP guidelines for nutritional completeness and diversity, but costs were approximately 25% higher than current allocations.

Conclusions:

• The developed optimization model can create contextual supplementary feeding program diets meeting essential nutrient needs.
• Achieving appropriate food diversification within large-scale feeding programs necessitates increased budget allocations.