{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T17:17:50Z","timestamp":1787505470801,"version":"build-2736575974"},"reference-count":33,"publisher":"S. Karger AG","issue":"1","license":[{"start":{"date-parts":[[2025,6,12]],"date-time":"2025-06-12T00:00:00Z","timestamp":1749686400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,6,12]],"date-time":"2025-06-12T00:00:00Z","timestamp":1749686400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Obes Facts"],"abstract":"<jats:p>&lt;p&gt;Introduction: Assessing the nutritional and morphofunctional status of patients with obesity (PwO) is essential for optimizing their management. Nutritional ultrasound (NU) is a noninvasive, portable technique that offers insights into muscle and adipose tissue status. Combining NU with bioelectrical impedance analysis (BIA) and handgrip strength (HGS) may improve the assessment of body composition and muscle functionality. This study aimed to evaluate the usefulness of NU as a primary tool for morphofunctional assessment in PwO while comparing and complementing it with BIA and HGS. Methods: A cross-sectional observational study was conducted including 178 PwO. Body composition was assessed using NU, single-frequency BIA, and HGS dynamometry. Correlations and multiple linear regression models were used to evaluate associations between NU, BIA, and HGS parameters. Results: Significant correlations were found between NU-measured quadriceps rectus femoris-cross-sectional area (RF-CSA) and BIA-derived fat-free mass markers, such as body cell mass (BCM) (r = 0.638, p &lt; 0.001) and appendicular skeletal muscle mass (r = 0.591, p &lt; 0.001). Additionally, leg subcutaneous adipose tissue measured by NU was highly correlated with BIA-calculated fat mass (r = 0.656, p &lt; 0.001). Linear regression analyses further confirmed the importance of RF-CSA as a strong predictor of BCM, along with HGS and body mass index, explaining 78.2% of the variability in BCM (R2 = 0.782, Akaike Information Criterion = 672). Conclusion: These findings suggest that NU, combined with BIA and HGS, provides a comprehensive, practical tool for assessing body composition and muscle function in obesity management, with the potential for routine application in clinical settings. &lt;\/p&gt;<\/jats:p>","DOI":"10.1159\/000546820","type":"journal-article","created":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T12:02:41Z","timestamp":1749816161000},"page":"12-21","source":"Crossref","is-referenced-by-count":2,"title":["Body Composition and Function in Patients with Obesity in Clinical Practice: Beyond the Body Mass Index"],"prefix":"10.1159","volume":"19","author":[{"given":"Mar\u00eda","family":"Garc\u00eda Olivares","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lara","family":"Dalla Rovere","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roc\u00edo","family":"Fern\u00e1ndez 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