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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

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Catia Martins, Irina Kazakova, Marit Ludviksen, Ingar Mehus, Ulrik Wisloff, Bard Kulseng, Linda Morgan and Neil King

This study aimed to determine the effects of 12 weeks of isocaloric programs of high-intensity intermittent training (HIIT) or moderate-intensity continuous training (MICT) or a short-duration HIIT (1/2HIIT) inducing only half the energy deficit on a cycle ergometer, on body weight and composition, cardiovascular fitness, resting metabolism rate (RMR), respiratory exchange ratio (RER), nonexercise physical activity (PA) levels and fasting and postprandial insulin response in sedentary obese individuals. Forty-six sedentary obese individuals (30 women), with a mean BMI of 33.3 ± 2.9 kg/m2 and a mean age of 34.4 ± 8.8 years were randomly assigned to one of the three training groups: HIIT (n = 16), MICT (n = 14) or 1/2HIIT (n = 16) and exercise was performed 3 times/week for 12 weeks. Overall, there was a significant reduction in body weight, waist (p < .001) and hip (p < .01) circumference,, trunk and leg fat mass (FM; p < .01) and an increase in trunk and leg fat free mass (FFM; p < .01) and cardiovascular fitness (VO2max in ml/kg/min; p < .001) with exercise. However, no significant differences were observed between groups. There was no significant change in RMR, RER, nonexercise PA levels, fasting insulin or insulin sensitivity with exercise or between groups. There was a tendency for a reduction in AUC insulin with exercise (p = .069), but no differences between groups. These results indicate that isocaloric training protocols of HIIT or MICT (or 1/2HIIT inducing only half the energy deficit) exert similar metabolic and cardiovascular improvements in sedentary obese individuals.

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Mary O. Hearst, John R. Sirard, Leslie Lytle, Donald R. Dengel and David Berrigan

Background:

The association of physical activity (PA), measured 3 ways, and biomarkers were compared in a sample of adolescents.

Methods:

PA data were collected on 2 cohorts of adolescents (N = 700) in the Twin Cities, Minnesota, 2007–2008. PA was measured using 2 survey questions [Modified Activity Questionnaire (MAQ)], the 3-Day Physical Activity Recall (3DPAR), and accelerometers. Biomarkers included systolic (SBP) and diastolic blood pressure (DBP), lipids, percent body fat (%BF), and body mass index (BMI) percentile. Bivariate relationships among PA measures and biomarkers were examined followed by generalized estimating equations for multivariate analysis.

Results:

The 3 measures were significantly correlated with each other (r = .22–.36, P < .001). Controlling for study, puberty, age, and gender, all 3 PA measures were associated with %BF (MAQ = −1.93, P < .001; 3DPAR = −1.64, P < .001; accelerometer = −1.06, P = .001). The MAQ and accelerometers were negatively associated with BMI percentile. None of the 3 PA measures were significantly associated with SBP or lipids. The percentage of adolescents meeting the national PA recommendations varied by instrument.

Conclusions:

All 3 instruments demonstrated consistent findings when estimating associations with %BF, but were different for prevalence estimates. Researchers must carefully consider the intended use of PA data when choosing a measurement instrument.

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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.

Purpose:

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.

Methods:

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.

Results:

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).

Conclusions:

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.

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David B. Pyne, Megan E. Anderson and Will G. Hopkins

Purpose:

To characterize within-subject changes in anthropometric characteristics of elite swimmers within and between seasons.

Methods:

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.

Results:

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%.

Conclusion:

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.

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Andrew O. Agbaje, Eero A. Haapala, Niina Lintu, Anna Viitasalo, Juuso Väistö, Sohaib Khan, Aapo Veijalainen, Tuomo Tompuri, Tomi Laitinen and Timo A. Lakka

augment venous return from peripheral tissues to the heart by their contractions and therefore increases stroke volume and cardiac output ( 39 , 41 ). Moreover, using valid and reproducible measurement, we controlled for maturation and body composition in our statistical analyses ( 27 , 45 ). This study

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Marjan Mosalman Haghighi, Yorgi Mavros and Maria A. Fiatarone Singh

, there was no association between change in PA and change in HbA 1c in these 14 trials of behavioral programs, which reported both outcomes using meta-regression ( r  = −.46, P  = .64). This result was similar with the exclusion of the outlier 22 (data not shown). Body Composition Outcomes Data for

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Carina Bauer, Christine Graf, Anna M. Platschek, Heiko K. Strüder and Nina Ferrari

physical activity affects maternal body composition and metabolism. Women who were physically active during pregnancy had reduced risk of excessive weight gain 39 and offspring obesity. 40 Therefore, women should be encouraged to participate in regular physical activity. Consequently, knowledge about

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Ryan P. Durk, Esperanza Castillo, Leticia Márquez-Magaña, Gregory J. Grosicki, Nicole D. Bolter, C. Matthew Lee and James R. Bagley

gut microbiota composition (F/B) and VO 2 max, body composition, or dietary intake among healthy young adults in a free-living environment. Materials and Methods This study was conducted in accordance with the Declaration of Helsinki and approved by San Francisco State University’s Institutional