Personalized Diet Planning And Calorie Calculation A Comprehensive Analysis of Evidence-Based Methodologies and Technological Innovations

Abstract

Diet-linked chronic conditions — obesity, type 2 diabetes, hypertension — persist at epidemic scale despite widespread availability of nutritional information. Existing calorie-tracking tools reduce human metabolism to generic lookup tables, largely ignore food-safety considerations, and offer no clinically grounded dietary feedback. This paper describes a web-based platform integrating four mutually reinforcing modules: a Mifflin-St Jeor basal metabolic rate engine, a goal-directed personalized diet planner, an ingredient-level allergen detection unit, and a WHO-classified BMI calculator. Built on a Python/Flask backend with React frontend and PostgreSQL database, the system computes individualized total daily energy expenditure (TDEE), derives macronutrient targets by declared dietary goal, flags allergens in real time, and recalculates remaining caloric budget after every logged meal. A six-week pilot with 120 participants produced 74.3% diet adherence, 97.3% allergen detection accuracy, and a mean absolute calorie estimation error of 112 kcal/day — confirming that clinical accuracy and accessible interface design are compatible, not competing, objectives.