Personalized nutrition represents a paradigm shift from standard one-size-fits-all dietetic advice to individually tailored intervention based on an individual's genetic profile, metabolic health, lifestyle, and environment. Advances in nutrigenomics and metabolomics have highlighted the role of genetic difference and molecular mechanisms in nutrient metabolism, food response, and disease risk for chronic conditions such as obesity, diabetes, and cardiovascular disease. At the same time, digital health technologies like mobile health applications, wearables, artificial intelligence–driven analytics, and continuous glucose monitoring are enabling real-time data capture and individualized feedback, thereby maximizing compliance and clinical impact of nutrition interventions. This review synthesizes evidence for the convergence of genomics and digital health into personalized nutrition, critically evaluating their common potential for better disease prevention and management. Emerging evidence shows that they can optimize dietary impacts, promote metabolic well-being, and facilitate precision-based preventive therapy but remain problems with respect to interpreting data, validating biomarkers, ethical considerations, access, and cost-effectiveness. By taking into account the current breakthroughs, challenges, and opportunities, this paper advocates for inter-disciplinary action among geneticists, clinicians, nutritionists, and digital health experts, and robust policy regulation to offer secure and equitable embracing of precision nutrition strategies. Future research involves further refining big data integration, optimizing predictive modeling, and translating results to scalable interventions that can be applied in both clinical and public health contexts around the globe, setting personalized nutrition as the basis for next-generation healthcare.
Ebadi et al. (2025) studied this question.