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James P. Veale, Alan J. Pearce, David Buttifant and John S. Carlson

Purpose:

Body structure and physical development must be addressed when preparing junior athletes for their first season in a senior competition. The aim of this preliminary study was to measure the extent of the assumption that final year junior Australian Football (AF) athletes are at a physical mismatch to their senior counterparts.

Methods:

Twenty-one male participants (17.71 ± 0.27 y) were recruited from one state based elite junior AF competition and forty-one male participants (22.80 ± 4.24 y) were recruited from one club competing in the senior elite Australian Football League (AFL), who were subsequently divided into two groups; professional rookies aged 18-20 y (19.44 ± 0.70 y; n = 18) and professional seniors aged 21+ y (25.43 ± 3.98 y; n = 23). Dual energy X-ray absorptiometry (DEXA) scans of all participants were completed.

Results:

Despite being an average 6.0% and 6.1% lighter in total weight and lean mass respectively, no significant difference was found between the elite junior athletes and their professional AFL rookie counterparts. However, significant differences were demonstrated in comparison with the professional AFL senior athletes (P < .01). Both professional AFL groups demonstrated greater than 0.3 kg total bone mineral content (BMC) than the elite junior athletes (P < .01) and significantly greater segmental BMC and bone mineral density (BMD) results (P < .05).

Conclusion:

While the results identify the differences in body composition of the elite junior athletes, development in a linear fashion is noted, providing useful information for the creation of age appropriate expectations and training programs.

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Alis Bonsignore, David Field, Rebecca Speare, Lianne Dolan, Paul Oh and Daniel Santa Mina

treatment, which include deleterious changes to body composition (eg, bone mineral density, muscular atrophy, increased body fat percentage), physical capacity, fatigue, metabolism (eg, increased blood triglycerides, cholesterol, and impaired glycemic control), psychological well-being, and health

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Simone A. Tomaz, Alessandra Prioreschi, Estelle D. Watson, Joanne A. McVeigh, Dale E. Rae, Rachel A. Jones and Catherine E. Draper

favorable measures of body composition, along with a range of positive psychosocial and health outcomes. 6 Research from high-income countries shows that complying with the PA and SB components of the guidelines is associated with better health and developmental outcomes. 6 – 10 Evidence supporting the

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Alessandra Madia Mantovani, Manoel Carlos Spiguel de Lima, Luis Alberto Gobbo, Enio Ricardo Vaz Ronque, Marcelo Romanzini, Bruna Camilo Turi-Lynch, Jamile Sanches Codogno and Rômulo Araújo Fernandes

not engaged (Table  2 ). Lean soft tissue was higher in women engaged in sports participation in early life compared with women not engaged ( P -value = .001), but not in men ( P -value = .07). Table 2 Comparison of Body Composition Variables Between Early Sports Participation in Childhood or

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Nathaniel S. Nye, Drew S. Kafer, Cara Olsen, David H. Carnahan and Paul F. Crawford

, fitness level, biomechanics, genetic factors, training progression strategies (or lack thereof), age, gender, tobacco use, footwear, previous history of injury, lumbopelvic core strength/stability, intrinsic foot muscle strength/stability, body composition], it is not surprising that the AUCs are somewhat

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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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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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D. Enette Larson-Meyer, Kathleen Woolf and Louise Burke

obtaining, verifying and interpreting data needed to identify nutrition-related problems, their causes and their significance” ( Academy of Nutrition and Dietetics, 2015 ). A complete assessment should ideally include dietary evaluation, anthropometry and body composition analysis, biochemical testing

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Rodrigo Antunes Lima, Lisbeth Runge Larsen, Anna Bugge and Lars Bo Andersen

in the association between physical fitness and academic performance. However, several recent studies have proposed plausible mechanisms for the association between academic performance and body composition, such as evidence showing that excess adiposity might impair cognitive function and thereby