Digital Solutions for the Control of Lifestyle Parameters in Individuals With High Cardiometabolic Risk: a Scoping Review

Clinical Snapshot

Key Findings

• P Value: Not reported at review level

• Effect Size: Not quantified due to scoping review methodology

• Primary Outcome: Significant improvements in weight reduction, BMI, and waist circumference with digital interventions

• Nnt Or Sensitivity: High reliability of AI-based image analysis tools compared with DXA for body composition assessment

• Confidence Interval: Not applicable for scoping review

Clinical Application

Promising as complementary tool to clinician-guided care, but requires structured integration into clinical pathways Relevant to Australian digital health initiatives and chronic disease management programs; aligns with TGA digital therapeutics framework development Adults with overweight, obesity, or metabolic complications seeking lifestyle interventions

Abstract

BACKGROUND: Digital technologies are increasingly used to promote healthier behaviors and prevent noncommunicable diseases (NCDs). Diet and physical activity are key determinants of cardiometabolic health, where digital tools can support self-monitoring and behavior change. OBJECTIVE: This scoping review aimed to evaluate the effectiveness of digital health technologies in improving diet quality and adherence, assessing body composition, and promoting physical activity among adults at cardiometabolic risk. METHOD: A systematic search was performed in Web of Science and PubMed (2000-2025) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) guidelines and the PICo framework. Inclusion criteria focused on digital solutions for diet and exercise in adults with overweight, obesity, or metabolic complications. RESULTS: 15 studies were included (8 randomized controlled trials, 2 pilot studies, and 5 validation studies). Most intervention studies reported significant improvements in weight reduction, body mass index, or waist circumference, especially when mobile applications or wearable devices were combined with personalized feedback. Validation studies confirmed a high reliability of AI-based image analysis tools for estimating body composition compared with DXA. Improvements in dietary adherence and physical activity levels were also observed in several studies. However, heterogeneity in study design, short follow-up duration, and variability in outcome measures limited comparability across studies. Major gaps included limited long-term evidence, scarce use of AI-driven personalized interventions, insufficient reporting of measurement validity, and underrepresentation of vulnerable populations. CONCLUSION: Digital health technologies, including mobile apps, wearables, and AI-based systems, show promising potential as a complementary tool to clinician-guided care. They can enhance dietary adherence, promote self-monitoring, and support healthier lifestyles, although their long-term effectiveness remains to be confirmed. Future research should prioritize long-term randomized trials, standardized outcomes measures, validation of AI-based tools in diverse populations, and structured integration of digital interventions into clinical pathways.

References

1. 1.Mayol, D., Tecce, N., Amatrudo, F., Russo, G., Aprano, S., De Luca, V., Iaccarino, G., Illario, M., Colao, A., Moscatelli, F., & Vetrani, C. (2026). Digital solutions for the control of lifestyle parameters in individuals with high cardiometabolic risk: A scoping review. Current Nutrition Reports. https://doi.org/10.3389/fmed.2023.1123863