PD644 - E-HEALTH IN SARCOPENIC OBESITY: A SCOPING REVIEW

PD644

E-HEALTH IN SARCOPENIC OBESITY: A SCOPING REVIEW

V. Karagianni^1,*, R. Bereczky², M. Nørtoft^3,4, G. O. Iheme^5,6, S. Graungaard⁷, L. Ellegaard^8,9, A.-M. Boström^10,11

¹Medical R&D, Blodtrycksdoktorn AB, Kalmar, ²Yazen Health AB, Lund, Sweden, ³Department of Nursing, VIA University College, ⁴Hammel Neurorehabilitation and Research Clinic, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark, ⁵Department of Food Studies, Nutrition and Dietetics, Uppsala University, Uppsala, Sweden, ⁶Department of Human Nutrition and Dietetics, Michael Okpara University of Agriculture, Umudike, Nigeria, ⁷Aalborg Universitetshospital, Aalborg, Denmark, ⁸Department of Internal Medicine and Clinical Nutrition, University of Gothenburg, ⁹Institute of Medicine, Sahlgrenska University Hospital, Gothenburg, ¹⁰Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, ¹¹R&D Unit , Stockholms Sjukhem, Stockholm, Sweden

Rationale: Sarcopenic obesity (SO) is a critical phenotype of the double burden of malnutrition, where excess adiposity masks underlying skeletal muscle depletion and functional impairment, exacerbating metabolic risks. However, the characteristics of e-health interventions within this population remain fragmented. This scoping review maps e-health practices and implementation factors in sarcopenic obesity management.

Methods: Following Joanna Briggs Institute methodology and PRISMA-ScR guidelines, a systematic search of PubMed, Embase, and CINAHL was conducted to identify interventions focusing on adults with SO, utilizing e-health (telemedicine smartphones, wearables and remote monitoring) for treatment.

Results: Of 260 records screened, 10 interventions (duration 12–26 weeks) were identified, with diverse e-health modalities: virtual real-time sessions (n=5), telephone-based coaching (n=5), and wearables (n=4). Interventions targeted community-dwelling (n=5) and rural older adults (n=1), as well as disease-specific populations (n=4). E-health-supported lifestyle interventions incorporating resistance training (n=7) and dietary advice (n=4) consistently seemed to improve muscle strength (handgrip), physical performance (gait speed, sit-to-stand), and body composition. Facilitators included real-time feedback and remote access. Reported barriers included digital literacy challenges. Limitations included small samples, inconsistent definitions and variable outcomes.

Conclusion: Existing e-health interventions for SO are an emerging research field and promising intervention for improving physical function and body composition. However, the evidence remains limited and methodologically diverse. The next essential step is to systematically evaluate study quality using standardized diagnostic criteria to determine the true effect size of these digital tools.

Disclosure of Interest: None declared