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Continuous Glucose Monitoring and Personalized Nutrition in Type 2 Diabetes - A Scoping Review
Bushra Hoque1, Asmaa Al-Mesaifri1, Sara Suleiman1
1College of Science and Engineering, Hamad Bin Khalifa University, Qatar.
Studies in Health Technology and Informatics
|July 3, 2026
Summary
Continuous Glucose Monitoring (CGM) offers promising personalized nutrition for Type 2 Diabetes (T2D). However, current research requires more diverse outcomes and AI integration for precision diabetes care.
Area of Science:
- Endocrinology
- Nutrition Science
- Medical Informatics
Background:
- Continuous Glucose Monitoring (CGM) is emerging in Type 2 Diabetes (T2D) management for personalized nutrition.
- Existing evidence on CGM-guided dietary interventions remains fragmented.
- Scoping reviews are essential for synthesizing scattered research in evolving fields.
Purpose of the Study:
- To systematically map and classify Continuous Glucose Monitoring-based nutrition interventions for Type 2 Diabetes.
- To summarize the outcomes and identify research gaps in this domain.
- To inform future research directions for precision nutrition in diabetes.
Main Methods:
- Adherence to JBI and PRISMA-ScR guidelines for scoping reviews.
- Comprehensive literature search across five databases and Google Scholar (2020-2025).
- Inclusion of 45 studies involving adults with T2D using CGM for dietary guidance, encompassing randomized trials, pilot, and observational designs.
Main Results:
- Interventions spanned CGM-guided nutrition, AI prediction, hybrid CGM-AI models, and telehealth coaching.
- Primary outcomes assessed were HbA1c, Time in Range, and weight.
- Behavioral, cardiovascular, and microbiome outcomes were infrequently reported.
Conclusions:
- CGM-enabled nutrition interventions show potential for Type 2 Diabetes management.
- Methodological inconsistencies and limited outcome diversity hinder current evidence.
- Further large-scale, long-term studies are crucial, particularly exploring advanced AI integration.
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