,000 new members joining the sport each year ( Parish et al., 2010 ). Female physique (FP) athletes have aspirations of achieving a lean and muscular body composition for competitive success ( Halliday et al., 2016 ). Preparing for a natural physique competition provides a myriad of health benefits
Nura Alwan, Samantha L. Moss, Kirsty J. Elliott-Sale, Ian G. Davies and Kevin Enright
Kathryn H. Myburgh, Claire Berman, Illana Novick, Timothy D. Noakes and Estelle V. Lambert
We studied 21 ballet dancers aged 19.4 ± 1.4 years, hypothesizing that undernu-trition was a major factor in menstrual irregularity in this population. Menstrual history was determined by questionnaire. Eight dancers had always been regular (R). Thirteen subjects had a history of menstrual irregularity (HI). Of these, 2 were currently regularly menstruating, 3 had short cycles, 6 were oligomenorrheic, and 2 were amenorrheic. Subjects completed a weighed dietary record and an Eating Attitudes Test (EAT). The following physiological parameters were measured: body composition by anthropometry, resting metabolic rate (RMR) by open-circuit indirect calorimetry, and serum thyroid hormone concentrations by radioimmunoassay. R subjects had significantly higher RMR than HI subjects. Also, HI subjects had lower RMR than predicted by fat-free mass, compared to the R subjects. Neitherreported energy intake nor serum thyroid hormone concentrations were different between R and HI subjects. EAT scores varied and were not different between groups. We concluded that in ballet dancers, low RMR is more strongly associated with menstrual irregularity than is currentreported energy intake or serum thyroid hormone concentrations.
Matteo Levi Micheli, Luca Pagani, Mario Marella, Massimo Gulisano, Antonio Piccoli, Fabrizio Angelini, Martin Burtscher and Hannes Gatterer
Bioelectrical-impedance standards (resistance, reactance, and phase angle) are well established for the normal population or in the clinical setting and are considered indicators for cell mass, cell function, and hydration status. However, such standards do not exist for the male soccer population. Therefore, the goal of the current investigation was to provide a set of bioelectrical-impedance data of a large sample of soccer players with different performance levels.
A sample of 893 players, registered in all Italian soccer divisions, was divided into 5 groups according to their performance level. Whole-body impedance measurements were performed during the first half of the competitive period. Besides estimation of body composition, bioelectrical-impedance vector analysis (BIVA) was performed. BIVA does not depend on equations and displays differences in hydration and body-cell mass (BCM). Individual vectors can be classified by using the 50%, 75%, and 95% tolerance ellipse.
In comparison with the other divisions and the normal population, the mean vector of the elite level showed a shift to the left (P < .001). Compared with the elite level, players of a lower performance level had lower phase angles, BCM, and fat-free mass.
In conclusion, soccer players belong to a specific population. Muscle mass and function, as indicated by BCM and phase angle, increase with increasing performance level. The soccer-specific tolerance ellipses might be used for classifying individual vectors and to define target regions for low-level players.
Sarah J. Woodruff and Renee D. Meloche
Female athletes should aim to achieve energy balance to maintain health and have a high performance output. The purpose of this study was to investigate energy availability (EA) among members of a medium-size Canadian Interuniversity Sport women’s volleyball team and to describe exercise energy expenditure (ExEE) during practices, game warm-ups, and games. Total daily energy expenditure was assessed over 7 d using the Bodymedia Sensewear Mini armband, while energy intake (EI) was measured with dietary food logs. Body composition was assessed using air-displacement plethysmography (Bod Pod). Energy availability was calculated using the equation EA = (EIkcal – ExEEkcal)/kg fat-free mass (FFM). Participants consumed 3,435 (± 1,172) kcal/day and expended 3479 (± 604) kcal/day. Mean EA was 42.5 kcal · kg FFM-1 · d-1 across all 7 d, and 2 participants fell below the 30-kcal · kg FFM-1 · d-1 threshold. Furthermore, participants expended 511 (± 216), 402 (± 50), and 848 (± 155) kcal during practices, game warm-ups, and games, respectively. Overall, the participants were relatively weight stable and should be encouraged to continue fueling their exercise and high ExEE needs with appropriate nutritional strategies.
Mathieu L. Maltais, Karine Perreault, Alexandre Courchesne-Loyer, Jean-Christophe Lagacé, Razieh Barsalani and Isabelle J. Dionne
The decrease in resting energy expenditure (REE) and fat oxidation with aging is associated with an increase in fat mass (FM), and both could be prevented by exercise such as resistance training. Dairy consumption has also been shown to promote FM loss in different subpopulations and to be positively associated with fat oxidation. Therefore, we sought to determine whether resistance exercise combined with dairy supplementation could have an additive impact on FM and energy metabolism, especially in individuals with a deficit in muscle mass. Twenty-six older overweight sarcopenic men (65 ± 5 years old) were recruited for the study. They participated in 4 months of resistance exercise and were randomized into three groups for postexercise shakes (control, dairy, and nondairy isocaloric and isoprotein supplement with 375 ml and ~280 calories per shake). Body composition was measured by dual X-ray absorptiometry and REE by indirect calorimetry. Fasting glucose, insulin, leptin, inflammatory profile, and blood lipid profile were also measured. Significant decreases were observed with FM only in the dairy supplement group; no changes were observed for any other variables. To conclude, FM may decrease without changes in metabolic parameters during resistance training and dairy supplementation with no caloric restriction without having any impact on metabolic properties. More studies are warranted to explain this significant decrease in FM.
Laureen H. Smith, Devin Laurent, Erica Baumker and Rick L. Petosa
between these different components. 26 However, studies have found a strong link between BMI and percentage of body fat. 26 , 27 In research, BMI remains the most commonly used measure to assess general body composition. 26 Using the Tanita DC-430U Body Composition Analyzer (Arlington Heights, IL), BMI
Patrick Delisle-Houde, Nathan A. Chiarlitti, Ryan E.R. Reid and Ross E. Andersen
laboratory-based assessments (ie, isokinetic leg pull test, body composition assessment, V ˙ O 2 max ), and (3) on-ice testing (ie, 30 m forward, 30 m backward, on-ice pro-agility). It should be noted that the V ˙ O 2 max is part of the common laboratory/field tests, but it was performed in the second
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.
Eric R. Helms, Caryn Zinn, David S. Rowlands and Scott R. Brown
Caloric restriction occurs when athletes attempt to reduce body fat or make weight. There is evidence that protein needs increase when athletes restrict calories or have low body fat.
The aims of this review were to evaluate the effects of dietary protein on body composition in energy-restricted resistance-trained athletes and to provide protein recommendations for these athletes.
Database searches were performed from earliest record to July 2013 using the terms protein, and intake, or diet, and weight, or train, or restrict, or energy, or strength, and athlete. Studies (N = 6) needed to use adult (≥ 18 yrs), energy-restricted, resistance-trained (> 6 months) humans of lower body fat (males ≤ 23% and females ≤ 35%) performing resistance training. Protein intake, fat free mass (FFM) and body fat had to be reported.
Body fat percentage decreased (0.5–6.6%) in all study groups (N = 13) and FFM decreased (0.3–2.7kg) in nine of 13. Six groups gained, did not lose, or lost nonsignificant amounts of FFM. Five out of these six groups were among the highest in body fat, lowest in caloric restriction, or underwent novel resistance training stimuli. However, the one group that was not high in body fat that underwent substantial caloric restriction, without novel training stimuli, consumed the highest protein intake out of all the groups in this review (2.5–2.6g/kg).
Protein needs for energy-restricted resistance-trained athletes are likely 2.3–3.1g/kg of FFM scaled upwards with severity of caloric restriction and leanness.