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Minnetti, M.* ; Pierantozzi, G.* ; Aubertin-Leheudre, M.* ; Ballesteros-Pomar, M.D.* ; Batsis, J.A.* ; Boirie, Y.* ; Busetto, L.* ; Cederholm, T.* ; Cruz-Jentoft, A.J.* ; Genton, L.* ; Gonzalez, M.C.* ; Heymsfield, S.B.* ; Prado, C.M.* ; Siervo, M.* ; Weijs, P.J.* ; Poggiogalle, E.* ; Barazzoni, R.* ; Donini, L.M.* ; Bennett, J.* ; Breton, I.* ; Brunani, A.* ; Capodaglio, P.* ; Caprio, M.* ; Cardinali, L.* ; Cereda, E.* ; Coletti, D.* ; Defeudis, G.* ; Schueren, M.V.* ; Di Stefano, A.* ; Di Vincenzo, O.* ; Dulloo, A.* ; Eftekhariranjbar, S.* ; Eglseer, D.* ; Frigerio, F.* ; Giustina, A.* ; Guan, Z.* ; Guillet, C.* ; Ho-Seong, H.* ; Laviano, A.* ; Migliaccio, S.* ; Moro, T.* ; Muscaritoli, M.* ; Muzzioli, L.* ; Naitoh, T.* ; Noirez, P.* ; Oppert, J.M.* ; Paoli, A.* ; Perna, S.* ; Petroni, M.L.* ; Piciocchi, C.* ; Pintavalle, M.* ; Pistilli, G.* ; Pinto, A.* ; Rondanelli, M.* ; Salas-Salvadó, J.* ; Schoufour, J.* ; Seelander, M.* ; Semeraro, G.* ; Serlie, M.* ; Shi, H.P.* ; Swendsen, M.* ; Thorand, B. ; Topinkova, E.* ; Verlaan, S.* ; Vettor, R.* ; Visser, M.* ; Volkert, D.* ; Voortman, T.* ; Yumuk, V.*

Current application and future directions for the sarcopenic obesity Global Leadership Initiative (SOGLI) diagnostic algorithm.

Clin. Nutr. 62:106675 (2026)
Research data DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
BACKGROUND: Sarcopenic obesity (SO) is characterized by excess adiposity and reduced muscle mass and function. In 2022, the Sarcopenic Obesity Global Leadership Initiative (SOGLI) proposed a diagnostic algorithm to standardize SO identification by integrating screening, diagnostic assessment, and staging. AIM: This review evaluates the application of the SOGLI algorithm, identifying strengths, limitations, and potential areas for refinement. METHODS: A narrative review with systematic citation tracking was conducted (April 2022-August 2025). Literature searches in PubMed, Scopus, and Web of Science identified original studies in adults (≥18 years) explicitly using the SOGLI algorithm. Data on screening, diagnostic tools, staging, prevalence, and comorbidities were synthesized. RESULTS: Seventy-two studies applied the SOGLI algorithm, showing heterogeneous approaches across clinical settings. For obesity screening, about half used both body mass index and waist circumference, while sarcopenia screening tools were less frequently reported. For SO diagnosis, bioelectrical impedance analysis was the most common method for body composition assessment, while muscle function was predominantly assessed via hand-grip strength. SO staging was reported in 19% of studies, most often as Stage II. Application of the algorithm consistently confirmed associations between SO and chronic disease burden, functional decline, and increased mortality. CONCLUSIONS: The SOGLI algorithm represents a major advance, with 72 studies adopting it in two years. Some inconsistencies in screening and staging suggest opportunities for refinement. These findings support its validity, while further standardization and integration of novel biomarkers could enhance its clinical effectiveness.
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Publication type Article: Journal article
Document type Review
Keywords Espen/easo Algorithm ; Sogli ; Sarcopenic Obesity ; Sarcopenic Obesity Global Leadership Initiative
ISSN (print) / ISBN 0261-5614
e-ISSN 0261-5614
Journal Clinical Nutrition
Quellenangaben Volume: 62, Issue: , Pages: , Article Number: 106675 Supplement: ,
Publisher Elsevier
Reviewing status Peer reviewed
Institute(s) Institute of Epidemiology (EPI)