Low glycemic index diets for subjects with diabetes by minimizing glycemic load of individual foods - Navarro Mentado, Maximino (My University, 2018)
In this work, the authors develop and analyze a linear programming model to obtain an ideal diet for individuals with diabetes by setting the glycemic load as the objective function. Additionally, a standardized system is used in order to facilitate the substitutability of foods present in a diet since those are classified according to their macronutrient content (proteins, lipids, and carbohydrates) and these values are, on average, very similar. Finally, the diet glycemic index is calculated with the model’s outcome to corroborate that it is indeed a diet with low glycemic index and that, at the same time, it complies with the nutrient restrictions, which proves that the model can be a useful tool both to generate low glycemic index diets and to restrict certain nutrients from the diet.
Este artículo es el resultado de un arduo trabajo de investigación, recolección de datos y modelado matemático. Los autores se basan en el problema de la dieta (un problema clásico de programación linear) y lo adaptan a las necesidades alimentarias de una persona con diabetes mellitus tomando como referencia una nueva clasificación fisiológica de los hidratos de carbono que surgen de los conceptos de índice glucémico y carga glucémica.
Keywords: Linear Programming; Diet Therapy; R Programming; Dietary control; Diet problem