Fuzzy Evaluation of Glycemic Load and Beta-Glucan Intake: Deriving a Type 2 Diabetes–Preventive Dietary Circle

Background/Objectives: Diabetes mellitus type 2 (T2D) is a global epidemic affecting over 500 million adults. Glycemic load (GL) and beta-glucan intake are modifiable dietary risk factors for T2D that are largely shaped by the choice of cereal-based foods. This study derives fuzzy sets for GL and beta-glucan to enable joint nutritional evaluation within a multidimensional framework and uses the framework to generate a T2D-preventive dietary circle. Methods: Fuzzy membership functions for GL and beta-glucan were constructed based on epidemiological dose–response data and established dietary reference values. These functions were integrated into the existing Nutritional Value Score (NVS II) system, which aggregates the evaluation of nutrient intake using a Schweizer–Sklar T-norm (p = 6). A fuzzy optimization algorithm was applied to an average representative German omnivore diet to derive a T2D-preventive dietary circle. Results: The GL fuzzy set reaches its optimum at ≤80 g/d and penalizes intakes ≥160 g/d; the beta-glucan fuzzy set reaches its optimum at ≥3 g/d. Fuzzy optimization shifted the diet markedly toward vegetables, legumes, fish, and tofu while strongly reducing cereals and milk products. The resulting dietary circle achieved an evaluation > 0.9 for the intake of every nutrient and an aggregate score of 0.894. Conclusions: Integrating GL and beta-glucan into the fuzzy evaluation framework yields a coherent, food-based T2D-preventive dietary circle that can serve as a practical reference for counseling, menu planning and intervention studies.