AI-Driven Personalized Nutrition and Health Guidance: Enhancing Health Outcomes for Nigerian Families

D.A. Ighere, O.A. Obichere, A.T. Olufelo and J.O. Amao

Background and Objective: Personalized nutrition, powered by Artificial Intelligence (AI), offers a promising approach to addressing dietary and health challenges in diverse populations. This study explored the effectiveness of AI-driven personalized nutrition interventions tailored to dietary preferences, health needs and locally available foods among Nigerian families. Materials and Methods: A total of 200 participants were recruited and stratified into an intervention group (receiving AI-based personalized dietary recommendations) and a control group (following standard dietary guidelines). Evaluated parameters included dietary adherence, blood pressure, blood glucose and BMI. Results: Dietary adherence was significantly higher in the intervention group (73%) compared to the control group (44%). Participants in the intervention group also demonstrated notable improvements in health markers, with reductions in systolic blood pressure (average decrease 13 mmHg), fasting blood glucose (average decrease 18 mg/dL), monthly food cost reduced by 15/1% and BMI (average decrease 1.6 points). Qualitative feedback indicated high acceptance of the AI tool, although challenges such as limited access to technology and initial unfamiliarity with AI were reported. Conclusion: The AI-driven personalized nutrition can effectively improve dietary adherence and key health outcomes while offering culturally acceptable and affordable guidance for Nigerian families.

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