Low-carbohydrate and very-low-carbohydrate diets are often used as weight-loss strategies by exercising individuals and athletes. Very-low-carbohydrate diets can lead to a state of ketosis, in which the concentration of blood ketones (acetoacetate, 3-β-hydroxybutyrate, and acetone) increases as a result of increased fatty acid breakdown and activity of ketogenic enzymes. A potential concern of these ketogenic diets, as with other weight-loss diets, is the potential loss of fat-free mass (e.g., skeletal muscle). On examination of the literature, the majority of studies report decreases in fat-free mass in individuals following a ketogenic diet. However, some confounding factors exist, such as the use of aggressive weight-loss diets and potential concerns with fat-free mass measurement. A limited number of studies have examined combining resistance training with ketogenic diets, and further research is needed to determine whether resistance training can effectively slow or stop the loss of fat-free mass typically seen in individuals following a ketogenic diet. Mechanisms underlying the effects of a ketogenic diet on fat-free mass and the results of implementing exercise interventions in combination with this diet should also be examined.
Grant M. Tinsley and Darryn S. Willoughby
Erik Sesbreno, Gary Slater, Margo Mountjoy, and Stuart D.R. Galloway
simple calculation, absolute FM, and fat-free mass (FFM; overall mass excluding FM). Some practitioners apply this approach of estimating FFM in athletes in the daily training environment. However, few, if any of these skinfold equations have been validated to quantify body composition change ( Cisar et
Patricia W. Bauer, James M. Pivarnik, Willa C. Fornetti, Jennifer J. Jallo, and Lawrence Nassar
The purpose of this investigation was to evaluate three bioelectrical impedance analysis (BIA) prediction models for fat-free mass (FFM) using the U.S. National Women’s Gymnastics team (N = 48; age = 15.8 ± 1.8 years). One model had been developed recently using dual-energy x-ray absorptiometry (DEXA) as the criterion measure, whereas the other two used hydrodensitometry. In this investigation, FFM predictions were compared with measures obtained via DEXA. FFM measured by DEXA averaged 40.5 ± 7.4 kg (± SD), whereas values generated using the three BIA models were within 0.8 kg of this actual measure. Validity coefficients for all models were high (Rxy = .95-98). FFM prediction error was lowest with the model using DEXA as the criterion measure (1.3 kg) compared with the other two (1.9 and 2.4 kg). All BIA models underpredicted FFM in the heaviest girls, and the Lohman and Van Loan et al. models overpredicted FFM in the lightest girls. Whereas prediction error was significantly correlated to the girls’ bone mineral density in all BIA models, this relationship was strongest in the two that were developed using hydrodensitometry.
Adam J. Zemski, Shelley E. Keating, Elizabeth M. Broad, and Gary J. Slater
), distinct differences in body composition exist. Forwards have consistently been shown to be heavier, taller, and possess more fat-free mass (FFM) and fat mass (FM), whereas backs display proportionally lower body fat ( Lees et al., 2017 ; Zemski et al., 2015 ). Optimal body composition assists athletes in
Ava Farley, Gary J. Slater, and Karen Hind
quantify fat-free mass (FFM) and fat mass (FM) ( Ackland et al., 2012 ; Kerr et al., 2017 ). Depending on time and resources, the four most popular methods used on athletic populations are air displacement plethysmography (BOD POD), dual-energy X-ray absorptiometry (DXA), bioelectrical impedance
Beatriz Rael, Nuria Romero-Parra, Víctor M. Alfaro-Magallanes, Laura Barba-Moreno, Rocío Cupeiro, Xanne Janse de Jonge, Ana B. Peinado, and on Behalf of the IronFEMME Study Group
research in this area remain unclear, with some reporting little or no effects of the MC on BC, 9 , 10 whereas others found higher weight and fat-free mass (FFM) during the luteal phase. 11 , 12 Some of these conflicting findings may be related to methodological issues. Most studies in the literature
Neil Armstrong and Jo Welsman
single best indicator of youth aerobic fitness, but its interpretation in relation to sex, age, body mass, fat-free mass (FFM), and maturity status is controversial ( 4 ). The vast majority of published data are cross-sectional and, on balance, show that boys’ absolute peak V ˙ O 2 (ie, in L·min −1
Sakiho Miyauchi, Satomi Oshima, Meiko Asaka, Hiroshi Kawano, Suguru Torii, and Mitsuru Higuchi
The purpose of this study was to determine whether overfeeding and high-intensity physical training increase organ mass. We examined this question using cross-sectional and longitudinal studies in which we measured collegiate male American football players. Freshman (n = 10) and senior players in their second and third years of college (n = 17) participated in the cross-sectional study. The same measurements of the same freshman players (n = 10) were assessed after the one-year weight gain period in the longitudinal study. Fat-free mass (FFM), skeletal muscle, and adipose tissue mass were obtained using dual-energy X-ray absorptiometry. Liver, kidney, brain, and heart volumes were calculated using magnetic resonance imaging or echocardiography. Compared with the freshman players, the senior players had 10.8 kg more FFM, and 0.29 kg, 0.08 kg, and 0.09 kg greater liver, heart, and kidney mass, respectively. In the longitudinal study, FFM, liver, heart, and kidney mass of the freshman players increased by 5.2 kg, 0.2 kg, 0.04 kg, and 0.04 kg, respectively, after one year of overfeeding and physical training. On the other hand, the organ-tissue mass to FFM ratio did not change, except for the brain, in either the cross-sectional or longitudinal studies. Our results indicated that the organtissue masses increased with overfeeding and physical training in male collegiate American football players.
Linda B. Houtkooper
Body composition assessment techniques provide estimates of percent body fat (%BF), fat mass (FM), and fat-free mass (FFM) based on indirect assessment models and methods. Prediction equations for %BF developed using a two-component model based on adult body composition constants will overestimate %BF in youths, especially prepubescent youths. Body composition prediction equations that have been validated and cross-validated using multiple-component criterion models which include measurements of body density and the water and mineral components of FFM provide the most accurate means for assessment of body composition in youths. Use of appropriate prediction equations and proper measurement techniques, for either bioelectrical impedance or skinfolds, results in body composition estimates with standard errors of estimate (prediction errors) of 3 to 4% BF and 2.0 to 2.5 kg of FFM. Poor measurement technique and inappropriate prediction equations will result in much larger prediction errors.
Kenneth W. Kambis and Sarah K. Pizzedaz
Creatine monohydrate (CrH2O) supplementation has been demonstrated to increase skeletal muscle power output in men. However, its effect upon women is not as clearly defined. This study investigated the effect of oral creatine supplementation upon muscle function, thigh circumference, and body weight in women. Twenty-two consenting college-age women were assigned to 1 of 2 groups matched for dietary and exercise habits, phase of menstrual cycle, and fat-free mass (FFM). After familiarization with testing procedures, pretrial measures of muscle function (5 repetitions 60 deg · s−1 and 50 repetitions 180 deg · s−1) were conducted during maximal voluntary concentric contraction of the preferred quadriceps muscle using an isokinetic dynamometer. Subjects then ingested 0.5 g · kg−1 FFM of either CrH2O or placebo (one fourth dosage 4 times daily) in a double-blind design for 5 days. Resistance exercise was prohibited. After the ingestion phase was completed, all measures were repeated at the same time of day as during pretrials. Statistical analysis revealed time to peak torque in quadriceps extension decreased from pre-test values of 255 ± 11 ms (mean ± SEM) to post-test values of 223 ± 3 ms; average power in extension increased from 103 ± 7 W pre-test to 112 ± 7 W post-test; and, during flexion, average power increased from 59 ± 5 W pre-test to 65 ± 5 W post-test in the creatine group as compared to controls (p ≤ .05). FFM, percent body fat, mid-quadriceps circumference, skinfold thickness of the measured thigh, and total body weight did not change for both groups between trials. We conclude that CrH2O improves muscle performance in women without significant gains in muscle volume or body weight.