Publications

BACKGROUND: In large supplementary feeding programs for children, it is challenging to create and sustain contextual, acceptable, nutritionally complete,  and diverse supplemental foods. For example, the Indian Supplementary Nutrition  Program (SNP) supplements the dietary intake of children, pregnant and lactating  women, and severely acutely malnourished (SAM) children by offering dry take home  rations (THRs) or hot cooked meals (HCMs) across India, but an optimization tool  is necessary to create local contextual recipes for acceptable and nutritionally  adequate products. OBJECTIVES: This study aimed to create a linear programming  (LP) model to optimize diverse food provisions for a SNP to meet its program  guidelines, using locally available foods, within budgetary allocations. METHODS:  A LP algorithm with appropriate constraints was used to generate an optimal THR  based on raw foods, or an optimal weekly HCM menu comprised of a lunch meal with  mid-morning snacks, based on user choices of foods and recipes. The database of  foods used was created by a prospective survey conducted across all states of  India for this purpose, such that the recipe and food optimization was diverse  and specific to the guidelines for each beneficiary group. RESULTS: An  interactive web-based app, which can optimize feeding programs at any population  level, was developed for use by program implementers and is hosted at  https://www.datatools.sjri.res.in/SNP/. In the Indian example analyzed here, the  recommended optimized diets met the guidelines for diversified and nutritionally  complete SNP provision but at a cost that was almost 25% higher than the present  Indian budget allocation. CONCLUSIONS: The optimization model developed  demonstrates that contextual SNP diets can be created to meet macronutrient and  most essential micronutrient needs of large-scale feeding programs, but  appropriate diversification entails additional costs.