Cemil Ertürk1, Mehmet Akif Altay2, Cemil Sert3, Ali Levent2, Metin Yaptı2, Kemal Yüce2. 1. Department of Orthopaedic Surgery, Harran University Faculty of Medicine, Yenisehir, 63100, Sanliurfa, Turkey. erturkc@yahoo.com. 2. Department of Orthopaedic Surgery, Harran University Faculty of Medicine, Yenisehir, 63100, Sanliurfa, Turkey. 3. Department of Biophysics, Harran University Faculty of Medicine, Sanliurfa, Turkey.
Abstract
BACKGROUND AND AIMS: We investigated body composition in knee osteoarthritis (OA) patients and evaluated its relationship with clinical parameters and radiographic severity. METHODS: Sixty-four patients with knee OA (52 females and 12 males with a mean age of 57.7 ± 8.6 years) and thirty healthy volunteers (20 females and 10 males with a mean age of 56.3 ± 9.5 years) were evaluated. Controls were selected among similar to demographic and hematologic characteristics of patients. Body compositions were assessed via bioelectrical impedance analysis (BIA). Each patient was clinically evaluated by the Western Ontario and McMaster University Osteoarthritis Index (WOMAC). In addition, radiographic severity was classified according to Kellgren-Lawrence's criteria. RESULTS: Phase angle, body capacitance, resistance, reactance, lean body mass, and intracellular water values of the patients with knee OA were found to be significantly lower than those of the controls (p < 0.05). Furthermore, fat mass and extracellular water levels were significantly higher in the patients compared to the controls (p < 0.05). Lean body mass was inversely correlated with WOMAC score (r = -0.716, p < 0.001), whereas fat mass was moderately correlated with WOMAC score (r = 0.281, p < 0.05) in bivariate analysis. However, with respect to the body composition, there was no significant difference between early grades and late grades in the knee OA with patients (p > 0.05). CONCLUSION: Body composition assessed using BIA might be associated with knee OA, and be a noninvasive tool for diagnosis of knee OA. However, body composition may not be predictive of the progression of knee OA.
BACKGROUND AND AIMS: We investigated body composition in knee osteoarthritis (OA) patients and evaluated its relationship with clinical parameters and radiographic severity. METHODS: Sixty-four patients with knee OA (52 females and 12 males with a mean age of 57.7 ± 8.6 years) and thirty healthy volunteers (20 females and 10 males with a mean age of 56.3 ± 9.5 years) were evaluated. Controls were selected among similar to demographic and hematologic characteristics of patients. Body compositions were assessed via bioelectrical impedance analysis (BIA). Each patient was clinically evaluated by the Western Ontario and McMaster University Osteoarthritis Index (WOMAC). In addition, radiographic severity was classified according to Kellgren-Lawrence's criteria. RESULTS: Phase angle, body capacitance, resistance, reactance, lean body mass, and intracellular water values of the patients with knee OA were found to be significantly lower than those of the controls (p < 0.05). Furthermore, fat mass and extracellular water levels were significantly higher in the patients compared to the controls (p < 0.05). Lean body mass was inversely correlated with WOMAC score (r = -0.716, p < 0.001), whereas fat mass was moderately correlated with WOMAC score (r = 0.281, p < 0.05) in bivariate analysis. However, with respect to the body composition, there was no significant difference between early grades and late grades in the knee OA with patients (p > 0.05). CONCLUSION: Body composition assessed using BIA might be associated with knee OA, and be a noninvasive tool for diagnosis of knee OA. However, body composition may not be predictive of the progression of knee OA.
Authors: Mehmet Akif Altay; Cemil Ertürk; Nuray Altay; Ahmet Şükrü Mercan; Serkan Sipahioğlu; Ali Murat Kalender; Uğur Erdem Işıkan Journal: Int Orthop Date: 2015-07-21 Impact factor: 3.075
Authors: Camille Parsons; Nicholas R Fuggle; Mark H Edwards; Lyndsey Goulston; Anna E Litwic; Darshan Jagannath; Suzan van der Pas; Cyrus Cooper; Elaine M Dennison Journal: Aging Clin Exp Res Date: 2017-11-03 Impact factor: 3.636
Authors: Juan José López-Gómez; Olatz Izaola-Jauregui; David Primo-Martín; Beatriz Torres-Torres; Emilia Gómez-Hoyos; Ana Ortolá-Buigues; Miguel A Martín-Ferrero; Daniel A De Luis-Román Journal: Nutrients Date: 2020-04-01 Impact factor: 5.717