Background/Objectives:Bioelectrical impedance analysis (BIA) provides noninvasive measures of skeletal muscle mass (SMM) and visceral adipose tissue (VAT). This study (i) analyzes the impact of conventional wrist-ankle vs segmental technology and standing vs supine position on BIA equations and (ii) compares BIA validation against magnetic resonance imaging (MRI) and dual X-ray absorptiometry (DXA).Subjects/Methods:One hundred and thirty-six healthy Caucasian adults (70 men, 66 women; age 40±12 years) were measured by a phase-sensitive multifrequency BIA (seca medical body composition analyzers 515 and 525). Multiple stepwise regression analysis was used to generate prediction equations. Accuracy was tested vs MRI or DXA in an independent multiethnic population.Results:Variance explained by segmental BIA equations ranged between 97% for total SMMMRI, 91–94% for limb SMMMRI and 80–81% for VAT with no differences between supine and standing position. When compared with segmental measurements using conventional wrist-ankle technology. the relationship between measured and predicted SMM was slightly deteriorated (r=0.98 vs r=0.99, P<0.05). Although BIA results correctly identified ethnic differences in muscularity and visceral adiposity, the comparison of bias revealed some ethnical effects on the accuracy of BIA equations. The differences between LSTDXA and SMMMRI at the arms and legs were sizeable and increased with increasing body mass index.Conclusions:A high accuracy of phase-sensitive BIA was observed with no difference in goodness of fit between different positions but an improved prediction with segmental compared with conventional wrist-ankle measurement. A correction factor for certain ethnicities may be required. When compared with DXA MRI-based BIA equations are more accurate for predicting muscle mass.
Assessment of a low skeletal muscle mass (SM) is important for diagnosis of ageing and disease-associated sarcopenia and is hindered by heterogeneous methods and terminologies that lead to differences in diagnostic criteria among studies and even among consensus definitions. The aim of this review was to analyze and summarize previously published cut-offs for SM applied in clinical and research settings and to facilitate comparison of results between studies. Multiple published reference values for discrepant parameters of SM were identified from 64 studies and the underlying methodological assumptions and limitations are compared including different concepts for normalization of SM for body size and fat mass (FM). Single computed tomography or magnetic resonance imaging images and appendicular lean soft tissue by dual X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA) are taken as a valid substitute of total SM because they show a high correlation with results from whole body imaging in cross-sectional and longitudinal analyses. However, the random error of these methods limits the applicability of these substitutes in the assessment of individual cases and together with the systematic error limits the accurate detection of changes in SM. Adverse effects of obesity on muscle quality and function may lead to an underestimation of sarcopenia in obesity and may justify normalization of SM for FM. In conclusion, results for SM can only be compared with reference values using the same method, BIA- or DXA-device and an appropriate reference population. Limitations of proxies for total SM as well as normalization of SM for FM are important content-related issues that need to be considered in longitudinal studies, populations with obesity or older subjects.
According to the World Health Organization Expert Consultation, current body mass index (BMI) cut-offs should be retained as an international classification. However, there are ethnic differences in BMI-associated health risks that may be caused by differences in body fat or skeletal muscle mass and these may affect the interpretation of phase angle and bioelectrical impedance vector analysis (BIVA). Therefore, the aim of this study was to compare body composition measured by bioelectrical impedance analysis among 1048 German, 1026 Mexican, and 995 Japanese adults encompassing a wide range of ages and BMIs (18–78 years; BMI, 13.9–44.3 kg/m2). Regression analyses between body composition parameters and BMI were used to predict ethnic-specific reference values at the standard BMI cut-offs of 18.5, 25, and 30 kg/m2. German men and women had a higher fat-free mass per fat mass compared with Mexicans. Normal-weight Japanese were similar to Mexicans but approached the German phenotype with increasing BMI. The skeletal muscle index (SMI, kg/m2) was highest in Germans, whereas in BIVA, the Mexican group had the longest vector, and the Japanese group had the lowest phase angle and the highest extracellular/total body water ratio. Ethnic differences in regional partitioning of fat and muscle mass at the trunk and the extremities contribute to differences in BIVA and phase angle. In conclusion, not only the relationship between BMI and adiposity is ethnic specific; in addition, fat distribution, SMI, and muscle mass distribution vary at the same BMI. These results emphasize the need for ethnic-specific normal values in the diagnosis of obesity and sarcopenia.
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