Integration of Nutritional, physical Activity, and AI- based Interventions fro Personalized Weight Management

Paper ID : 1754-SPORTCONGRESS

Authors

فاطمه رضائی *1, رضا قراخانلو2, مهدیه ملانوری شمسی2 1دانشجو 2عضو هیئت علمی

Abstract

Abstract Introduction: Obesity represents a growing global health crisis, contributing substantially to morbidity, mortality, and healthcare costs. It arises from chronic energy imbalance regulated by intricate neuroendocrine and metabolic mechanisms. The modern lifestyle-marked by sedentary behavior and widespread consumption of calorie-dense, ultra-processed foods-has exacerbated obesity prevalence. While dietary and exercise interventions remain central to weight management, sustaining long-term adherence poses persistent challenges. The integration of digital health technologies and artificial intelligence (AI) has introduced transformative opportunities for adaptive, personalized, and scalable obesity management solutions. Methods: This review synthesizes current evidence on nutritional and physical activity interventions alongside digital and AI-based tools in weight management. Studies investigating low-carbohydrate, low-fat, and very-low-calorie diets were analyzed in relation to structured resistance and endurance training programs. Electronic health tools-including smartphone applications, wearable sensors, and AI-driven adaptive systems-were evaluated for their ability to enhance adherence, provide personalized feedback, and improve scalability. Findings from recent trials involving AI-generated diet plans and AI chatbots were incorporated to illustrate emerging directions in intelligent health coaching. Results: Traditional nutritional interventions effectively promote weight loss when maintaining a caloric deficit, while physical activity preserves lean mass and enhances metabolic flexibility. Digital interventions, including text-based programs, mobile applications, and wearable devices, demonstrate comparable efficacy to face-to-face approaches and improve accessibility at lower costs. Recent studies show that AI-supported coaching systems and AI-generated dietary plans enhance personalization and adherence, while AI chatbots promoting physical activity and healthy eating show promising results. Conclusion: Despite technological advancements, interindividual variability in metabolic, genetic, and behavioral responses remains a key barrier to universal success. AI-based analytics can integrate physiological and behavioral data to predict responses and optimize adherence in real time. The convergence of nutritional, physical, and AI-driven digital interventions represents a paradigm shift in obesity management toward personalized, data-driven, and sustainable health outcomes.

Keywords

Keywords: Obesity, Weight Loss, Artificial Intelligence, Digital Health, Exercise, Nutrition, Personalized Intervention

Status: Abstract Accepted (Poster Presentation)