A literature review on the effects of artificial intelligence-mediated nutrition counseling and exercise guidance on community-living sarcopenic obese elderly people

Coexisting with age-related muscle loss and excess adiposity, sarcopenic obesity poses serious risks for disability and mortality in community-living older adults. Traditional nutrition and exercise programs often suffer from poor adherence and limited personalization. This narrative review critically examines artificial intelligence (AI)-mediated nutrition counseling and exercise guidance for sarcopenic obese older individuals and proposes a conceptual framework for future practice and research. We conducted a narrative review of PubMed, Embase, Web of Science, and ScienceDirect (inception-April 2025), focusing on primary studies employing machine learning, natural language processing, or computer vision in nutrition or exercise interventions for adults ≥65 years with sarcopenic obesity. AI-driven nutrition tools achieved fat-mass reductions and muscle-mass gains, while AI-guided exercise programs delivered modest improvements in gait speed, balance, and strength. Few interventions intentionally incorporated behaviour change techniques (BCTs), and digital-literacy, usability, and ethical challenges. A conceptual model links AI algorithms, BCTs, user support, and ethical governance. AI-mediated interventions show preliminary promise for sarcopenic obesity management but are limited by small sample size, short follow-up time, and barriers to usability. Rigorous randomized trials, integrated BCTs, and robust ethical frameworks are needed to translate AI’s potential into scalable, equitable geriatric care.