AI-Powered Personalized Nutrition Plans for the Elderly in Thailand: A Systematic Literature Review on Implementation Strategies and Feasibility

Authors

  • Kanruthay Ruktaengam Triam Udom Suksa School, Bangkok, Thailand

Keywords:

Artificial Intelligence,, Personalized Nutrition, , Elderly, , Public Health,, Thailand

Abstract

Introduction: The global aging population is rapidly increasing, bringing growing concerns about nutrition-related challenges among the elderly. AI-driven personalized nutrition plans have brought an innovative solution, especially tailored-made approaches relating to individual health information for improving dietary adherence, controlling chronic conditions, and enhancing the quality of life and wellbeing of the elderly.

        Objective: This study aims to (1) identify strategies for implementing AI-powered personalized nutrition plans for older adults in Thailand, (2) assess their feasibility, and (3) evaluate their impact on the health and well-being of elderly individuals in Thailand.

        Method: This study employs a systematic literature review (SLR) approach to analyze existing research on the implementation and feasibility of AI-powered personalized nutrition plans for the elderly in Thailand.

Result: This systematic review discusses contemporary applications, effectiveness, and challenges of artificial intelligence-based nutrition systems among the elderly. Cutting-edge technologies (e.g., real-time data analytics, machine learning) have made precision nutrition more dynamic, integrating additional data sources (e.g., genomics, microbiomes). These capabilities hold enormous promise for combating obesity, diabetes, and malnourishment and for facilitating healthy aging.

Conclusion: The review emphasizes the importance of cross-disciplinary collaboration among healthcare providers, policymakers, and technologists to integrate AI-powered personalized nutrition into public health systems. Addressing ethical concerns, accessibility, and equity is essential, and future research should focus on improving algorithms, scalability, and long-term impact to promote global health equity.

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Published

2025-06-27

How to Cite

Ruktaengam, K. (2025). AI-Powered Personalized Nutrition Plans for the Elderly in Thailand: A Systematic Literature Review on Implementation Strategies and Feasibility. VCHPK Health and Public Health Sciences Journal, 5(1), 1–30. retrieved from https://he03.tci-thaijo.org/index.php/VCHPK/article/view/4278

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Research Article