Advancing Precision Diagnosis of Sarcopenic Obesity Through Digital Technologies, Wearables and Omics Data

Sarcopenic obesity, the coexistence of excess adiposity with loss of muscle mass and function, is becoming increasingly prevalent. The condition is linked to higher morbidity and mortality but its diagnosis remains limited by reliance on body composition methods that are costly, inaccessible, and/or involve radiation exposure. Recent advances in bioinformatics, data analytics, and digital health technologies create opportunities for scalable, precise approaches to detection. This narrative review synthesizes current evidence from the published literature on online medical libraries (Pubmed, Medline, Scopus, Google Scholar) until September 2025 on multi-omics, digital phenotyping and eHealth research, highlighting how these tools can refine risk stratification and extend diagnostic reach beyond traditional methods. We describe the potential utility of wearable sensor technologies, and smartphone-based body composition methods, as well as genomics, proteomics, transcriptomics and metabolomics. Such approaches, alone or in combination, may enable earlier identification of sarcopenic obesity, including in individuals who are not routinely prioritized for screening. We conclude that integrating biological and digital data offers promise for advancing precision diagnostics in sarcopenic obesity, enabling more tailored prevention and intervention strategies while ultimately reducing healthcare burden. Further research is required to determine the feasibility, clinical utility and scalability of such innovations before their widespread implementation.