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      Estimation of skeletal muscle mass by bioelectrical impedance analysis

      1 , 2 , 3 , 1
      Journal of Applied Physiology
      American Physiological Society

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          Abstract

          The purpose of this study was to develop and cross-validate predictive equations for estimating skeletal muscle (SM) mass using bioelectrical impedance analysis (BIA). Whole body SM mass, determined by magnetic resonance imaging, was compared with BIA measurements in a multiethnic sample of 388 men and women, aged 18-86 yr, at two different laboratories. Within each laboratory, equations for predicting SM mass from BIA measurements were derived using the data of the Caucasian subjects. These equations were then applied to the Caucasian subjects from the other laboratory to cross-validate the BIA method. Because the equations cross-validated (i.e., were not different), the data from both laboratories were pooled to generate the final regression equation SM mass (kg) = [(Ht<SUP>2</SUP>/ <IT>R</IT> x 0.401) + (gender x 3.825) + (age x -0. 071)] + 5.102 where Ht is height in centimeters; R is BIA resistance in ohms; for gender, men = 1 and women = 0; and age is in years. The r(2) and SE of estimate of the regression equation were 0.86 and 2.7 kg (9%), respectively. The Caucasian-derived equation was applicable to Hispanics and African-Americans, but it underestimated SM mass in Asians. These results suggest that the BIA equation provides valid estimates of SM mass in healthy adults varying in age and adiposity.

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          Most cited references11

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          Applied potential tomography

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            Influence of diet and exercise on skeletal muscle and visceral adipose tissue in men.

            The effects of diet only (DO) and diet combined with either aerobic (DA) or resistance (DR) exercise on subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), lean tissue (LT), and skeletal muscle (SM) tissue were evaluated in 33 obese men (DO, n = 11; DA, n = 11; DR, n = 11). All tissues were measured by using a whole body multislice magnetic resonance imaging (MRI) model. Within each group, significant reductions were observed for body weight, SAT, and VAT (P 0.05). For all treatments, the relative reduction in VAT was greater than in SAT (P 0.05). MRI-LT and MRI-SM decreased both in the upper and lower body regions for the DO group alone (P < 0.05). Peak O2 uptake (liters) was significantly improved (approximately 14%) in the DA group as was muscular strength (approximately 20%) in the DR group (P < 0.01). These findings indicate that DA and DR result in a greater preservation of MRI-SM, mobilization of SAT from the abdominal region, by comparison with the gluteal-femoral region, and improved functional capacity when compared with DO in obese men.
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              The impact of body build on the relationship between body mass index and percent body fat.

              The objective of the study was to test the hypothesis that differences in the relationship between percent body fat (%BF) and body mass index (BMI) between populations can be explained (in part) by differences in body build. Cross-sectional, comparative study. 120 age, gender and BMI matched Singapore Chinese, Beijing Chinese and Dutch (Wageningen) Caucasians. From body weight and body height, BMI was calculated. Relative sitting height (sitting height/height) was used as a measure of relative leg length. Body fat was determined using densitometry (underwater weighing) in Beijing and Wageningen and using a three-compartment model based on densitometry and hydrometry in Singapore. Wrist and knee widths were measured as indicators for frame size and skeletal mass was calculated based on height, wrist and knee width. In addition, a slenderness index (height/sum of wrist and knee width) was calculated. For the same BMI, Singapore Chinese had the highest %BF followed by Beijing Chinese and the Dutch Caucasians. Singaporean Chinese had a more slender frame than Beijing Chinese and Dutch Caucasians. Predicted %BF from BMI, using a Caucasian prediction formula, was not different from measured %BF in Wageningen and in Beijing, but in Singapore the formula underpredicted %BF by 4.0 +/- 0.8% (mean +/- s.e.m.) compared to Wageningen. The difference between measured and predicted %BF (bias) was related to the level of %BF and with measures of body build, especially slenderness. Correction for differences in %BF, slenderness and relative sitting height, decreased the differences between measured and predicted values compared to the Dutch group from 1.4 +/- 0.8 (not statistically significant, NS) to -0.2 +/- 0.5 (NS) in Beijing and from 4.0 +/- 0.8 (P < 0.05) to 0.3 +/- 0.5 (NS) in Singapore (all values mean +/- s.e.m.). The study results confirm the hypothesis that differences in body build are at least partly responsible for a different relationship between BMI and %BF among different (ethnic) groups.
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                Author and article information

                Journal
                Journal of Applied Physiology
                Journal of Applied Physiology
                American Physiological Society
                8750-7587
                1522-1601
                August 2000
                August 2000
                : 89
                : 2
                : 465-471
                Affiliations
                [1 ]School of Physical and Health Education, Queen's University, Kingston, Ontario, Canada K7L 3N6;
                [2 ]Obesity Research Center, St. Luke's/Roosevelt Hospital, Columbia University, College of Physicians and Surgeons, New York, New York 10025; and
                [3 ]Clinical Nutrition Program, University of New Mexico, School of Medicine, Albuquerque, New Mexico 87131
                Article
                10.1152/jappl.2000.89.2.465
                10926627
                fbf192c3-ab75-42d8-9df1-28beac403415
                © 2000
                History

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