while performing a dance routine. While the mechanics of vertical jumps in the turnout position have been explored previously, a further understanding of differences in landing stiffness characteristics is warranted. Additionally, no evidence exists examining the influence of lower-extremity lean mass
Chris J. Alfiero, Ann F. Brown, Youngmin Chun, Alexandra Holmes, and Joshua P. Bailey
Ammar Nebigh, Mohamed Elfethi Abed, Rihab Borji, Sonia Sahli, Slaheddine Sellami, Zouhair Tabka, and Haithem Rebai
resulting in increased bone mass and architecture ( 3 ). Contracting skeletal muscle also produces hormonal and nervous stimuli that contribute to the muscle–bone interaction ( 11 ). According to many studies, higher rather than lower impact sports promote greater bone mineralization that enhances lean mass
Todd Miller, Stephanie Mull, Alan Albert Aragon, James Krieger, and Brad Jon Schoenfeld
.2 ± 4.7 43.8 ± 4.6 42.9 ± 4.9 43.3 ± 4.5 Fat mass (kg)* Control 37.5 ± 10.5 38.1 ± 12.1 Diet** 36.4 ± 7.9 35.2 ± 7.4 34.7 ± 7.0 34.1 ± 7.0 33.9 ± 6.8 Training 38.6 ± 11.0 37.8 ± 10.7 37.4 ± 10.5 37.3 ± 11.0 38.6 ± 11.7 Training + Diet** 41.3 ± 5.1 39.9 ± 5.0 39.2 ± 5.1 38.2 ± 5.2 38.0 ± 4.4 Lean mass
Kristen L. MacKenzie-Shalders, Neil A. King, Nuala M. Byrne, and Gary J. Slater
Increasing the frequency of protein consumption is recommended to stimulate muscle hypertrophy with resistance exercise. This study manipulated dietary protein distribution to assess the effect on gains in lean mass during a rugby preseason. Twenty-four developing elite rugby athletes (age 20.1 ± 1.4 years, mass 101.6 ± 12.0 kg; M ± SD) were instructed to consume high biological value (HBV) protein at their main meals and immediately after resistance exercise while limiting protein intake between meals. To manipulate protein intake frequency, the athletes consumed 3 HBV liquid protein supplements (22 g protein) either with main meals (bolus condition) or between meals (frequent condition) for 6 weeks in a 2 × 2 crossover design. Dietary intake and change in lean mass values were compared between conditions by analysis of covariance and correlational analysis. The dietary manipulation successfully altered the protein distribution score (average number of eating occasions containing > 20 g of protein) to 4.0 ± 0.8 and 5.9 ± 0.7 (p < .01) for the bolus and frequent conditions, respectively. There was no difference in gains in lean mass between the bolus (1.4 ± 1.5 kg) and frequent (1.5 ± 1.4 kg) conditions (p = .91). There was no clear effect of increasing protein distribution from approximately 4–6 eating occasions on changes in lean mass during a rugby preseason. However, other dietary factors may have augmented adaptation.
David B. Pyne, Megan E. Anderson, and Will G. Hopkins
To characterize within-subject changes in anthropometric characteristics of elite swimmers within and between seasons.
The subjects were 77 elite swimmers (31 females, 46 males, age 15 to 30 years) monitored over 0.4 to 9.2 years. One anthropometrist recorded their body mass (M) and sum of 7 skin-fold thicknesses (S) on 2042 occasions over 14 years from phase to phase within a season and over consecutive seasons. We estimated change in lean mass using a newly derived index (LMI) that tracked changes in M controlled for changes in S.
The LMI is M/Sx, where x = 0.16 ± 0.04 for females and 0.15 ± 0.05 for males (mean ± SD). The LMI of males increased 1.1% (95% confidence limits ± 0.2%) between preseason and taper phases, almost twice as much as that of females (0.6% ± 0.3%). During the same period, M and S fell by ~1% and ~11%, respectively. From season to season LMI increased by 0.9% (0.8% to 1.0%) for males and 0.5% (0.3% to 0.7%) for females. All these within-subject effects on LMI were well defined (±~0.3%). The typical variation (SD) of an individual’s LMI was 1.2% for assessments within a season and 1.9% between seasons, with a short-term technical error of measurement of ~0.5%.
Coaches and conditioners should typically expect a twofold greater increase in lean mass in male swimmers within and between seasons than in females. An LMI of the form M/Sx should be useful for monitoring individual swimmers and athletes in other sports in which body composition affects performance.
Magnus Carlsson, Tomas Carlsson, Daniel Hammarström, Christer Malm, and Michail Tonkonogi
To investigate the relationship between race performance and lean mass (LM) variables, as well as to examine sex differences in body composition in elite-standard cross-country skiers.
Thirty-four elite cross-country skiers (18 men and 16 women) underwent a dual-emission X-ray-absorptiometry body-composition test to determine LM, fat mass, and bone mineral content. For both sexes, performance data were collected from a sprint prologue and a distance race.
The absolute expression of LM variables (whole-body [LMWB], upper body [LMUB], and lower body [LMLB]) was significantly correlated with finishing time in the sprint prologue independent of sex. Distance-race performance was significantly related to LMWB, LMUB, and LMLB in women; however, no correlation was found in men. Men had a significantly higher LM and lower fat mass, independent of expression (absolute or relative), for the whole body, arms, trunk, and legs, except for the absolute fat mass in the trunk.
The absolute expressions of LMWB, LMUB, and LMLB were significant predictors of sprint-prologue performance in both sexes, as well as of distance-race performance in women only. Compared with women, male skiers have a higher LM in the body segments that are major contributors to propelling forces. These results suggest that muscle mass in the lower and upper body is equally important for race performance; thus, more focus of elite skiers’ training should be directed to increasing whole-body muscle mass to improve their competitive performance capability.
Eric C. Haakonssen, David T. Martin, Louise M. Burke, and David G. Jenkins
Body composition in a female road cyclist was measured using dual-energy X-ray absorptiometry (5 occasions) and anthropometry (10 occasions) at the start of the season (Dec to Mar), during a period of chronic fatigue associated with poor weight management (Jun to Aug), and in the following months of recovery and retraining (Aug to Nov). Dietary manipulation involved a modest reduction in energy availability to 30–40 kcal · kg fat-free mass−1 · d−1 and an increased intake of high-quality protein, particularly after training (20 g). Through the retraining period, total body mass decreased (−2.82 kg), lean mass increased (+0.88 kg), and fat mass decreased (−3.47 kg). Hemoglobin mass increased by 58.7 g (8.4%). Maximal aerobic- and anaerobic-power outputs were returned to within 2% of preseason values. The presented case shows that through a subtle energy restriction associated with increased protein intake and sufficient energy intake during training, fat mass can be reduced with simultaneous increases in lean mass, performance gains, and improved health.
Christie L. Ward, Rudy J. Valentine, and Ellen M. Evans
Adiposity, lean mass, and physical activity (PA) are known to influence physical function in older adults, although the independent influences are not completely characterized. Older adults (N = 156, M age = 68.9 ± 6.7 yr, 85 men) were assessed for body composition via dual-energy X-ray absorptiometry, PA by accelerometer, and physical function via timed up-and-go (UP&GO), 30-s chair stand, 6-min walk (6-min WALK), and Star-Excursion Balance Test. In the absence of percentage-body-fat by PA interactions (p > .05), main effects existed such that a higher percentage body fat was associated with poorer performance in UP&GO, 30-s chair stand, and 6-min WALK (p < .05). No significant main effects were found for PA and functional performance. Adiposity explains 4.6–11.4% in physical functional variance (p < .05). Preventing increases in adiposity with age may help older adults maintain functional independence.
Adam J. Zemski, Shelley E. Keating, Elizabeth M. Broad, Damian J. Marsh, Karen Hind, and Gary J. Slater
in body composition, such as increases in lean mass (LM), are associated with favorable changes in a number of performance traits ( Bilsborough et al., 2016 ; Crewther et al., 2013 ). Therefore, being able to accurately quantify preseason physique changes is of value to sport science practitioners
David Travis Thomas, Laurie Wideman, and Cheryl A. Lovelady
To examine the effect of yogurt supplementation pre- and postexercise on changes in body composition in overweight women engaged in a resistance-training program.
Participants (age = 36.8 ± 4.8 yr) with a body-mass index of 29.1±2.1 kg/m2 were randomized to yogurt supplement (YOG; n = 15) or isoenergetic sucrose beverage (CONT; n = 14) consumed before and after exercise for 16 wk. Participants were also instructed to reduce energy intake daily (–1,046 kJ) during the study. Body composition was assessed by dual-energy X-ray absorptiometry, waist circumference, and sagittal diameter. Strength was measured with 1-repetition maximum. Dietary recalls were obtained by a multipass approach using Nutrition Data System software. Insulin-like growth factor-1 and insulin-like growth-factor-binding protein-3 were measured with ELISA.
Significant weight losses of 2.6 ± 4.5 kg (YOG) and 1.2 ± 2.5 kg (CONT) were observed. Total lean weight increased significantly over time in both YOG (0.8 ± 1.2 kg) and CONT (1.1 ± 0.9 kg). Significant reductions in total fat (YOG = 3.4 ± 4.1 kg vs. CONT = 2.3 ± 2.4 kg) were observed over time. Waist circumference, sagittal diameter, and trunk fat decreased significantly over time without group differences. Both groups significantly decreased energy intake while maintaining protein intake. Strength significantly increased over time in both groups. No changes over time or between groups were observed in hormone levels.
These data suggest that yogurt supplementation offered no added benefit for increasing lean mass when combined with resistance training and modest energy restriction.