Abidin Nurdiana Z, Mitra Soma R
School of Biosciences, Faculty of Science and Engineering, University of Nottingham Malaysia, 43500 Semenyih, Selangor, Malaysia.
Lifestyle Science Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, 13200 Bertam, Pulau Pinang, Malaysia.
Curr Gerontol Geriatr Res. 2021 Mar 18;2021:6634474. doi: 10.1155/2021/6634474. eCollection 2021.
Osteosarcopenic obesity (OSO) describes the concurrent presence of obesity, low bone mass, and low muscle mass in an individual. Currently, no established criteria exist to diagnose OSO. We hypothesized that obese individuals require different cut-points from standard cut-points to define low bone mass and low muscle mass due to their higher weight load. In this study, we determined cutoff values for the screening of osteosarcopenia (OS) in obese postmenopausal Malaysian women based on the measurements of quantitative ultrasound (QUS), bioelectrical impedance analysis (BIA), and functional performance test. Then, we compared the cutoff values derived by 3 different statistical modeling methods, (1) receiver operating characteristic (ROC) curve, (2) lowest quintile of the study population, and (3) 2 standard deviations (SD) below the mean value of a young reference group, and discussed the most suitable method to screen for the presence of OS in obese population. One hundred and forty-one ( = 141) postmenopausal Malaysian women participated in the study. Bone density was assessed using calcaneal quantitative ultrasound. Body composition was assessed using bioelectrical impedance analyzer. Handgrip strength was assessed using a handgrip dynamometer, and physical performance was assessed using a modified Short Physical Performance Battery test. ROC curve was determined to be the most suitable statistical modeling method to derive the cutoffs for the presence of OS in obese population. From the ROC curve method, the final model to estimate the probability of OS in obese postmenopausal women is comprised of five variables: handgrip strength (HGS, with area under the curve (AUC) = 0.698 and threshold ≤ 16.5 kg), skeletal muscle mass index (SMMI, AUC = 0.966 and threshold ≤ 8.2 kg/m), fat-free mass index (FFMI, AUC = 0.946 and threshold ≤ 15.2 kg/m), broadband ultrasonic attenuation (BUA, AUC = 0.987 and threshold ≤ 52.85 dB/MHz), and speed of sound (SOS, AUC = 0.991 and threshold ≤ 1492.15 m/s). Portable equipment may be used to screen for OS in obese women. Early identification of OS can help lower the risk of advanced functional impairment that can lead to physical disability in obese postmenopausal women.
骨肌少性肥胖（OSO）指个体同时存在肥胖、低骨量和低肌肉量的情况。目前，尚无既定的诊断OSO的标准。我们推测，由于肥胖个体体重负荷较高，因此在定义低骨量和低肌肉量时需要与标准切点不同的切点。在本研究中，我们基于定量超声（QUS）、生物电阻抗分析（BIA）和功能性能测试的测量结果，确定了马来西亚肥胖绝经后女性骨肌减少症（OS）筛查的临界值。然后，我们比较了通过三种不同统计建模方法得出的临界值，（1）受试者工作特征（ROC）曲线，（2）研究人群的最低五分位数，以及（3）低于年轻参照组平均值2个标准差（SD），并讨论了在肥胖人群中筛查OS存在的最合适方法。141名马来西亚绝经后女性参与了本研究。使用跟骨定量超声评估骨密度。使用生物电阻抗分析仪评估身体成分。使用握力计评估握力，并使用改良的简短身体性能电池测试评估身体性能。ROC曲线被确定为推导肥胖人群中OS存在临界值的最合适统计建模方法。从ROC曲线方法来看，用于估计肥胖绝经后女性OS概率的最终模型由五个变量组成：握力（HGS，曲线下面积（AUC）=0.698，阈值≤16.5kg）、骨骼肌质量指数（SMMI，AUC=0.966，阈值≤8.2kg/m）、去脂体重指数（FFMI，AUC=0.946，阈值≤15.2kg/m）、宽带超声衰减（BUA，AUC=0.987，阈值≤52.85dB/MHz）和声速（SOS，AUC=0.991，阈值≤1492.15m/s）。便携式设备可用于筛查肥胖女性的OS。早期识别OS有助于降低肥胖绝经后女性发生可能导致身体残疾的晚期功能障碍的风险。
