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Johann C. Bilsborough, Kate Greenway, Steuart Livingston, Justin Cordy and Aaron J. Coutts

The purpose of this study was to examine the seasonal changes in body composition, nutrition, and upper-body (UB) strength in professional Australian Football (AF) players. The prospective longitudinal study examined changes in anthropometry (body mass, fat-free soft-tissue mass [FFSTM], and fat mass) via dual-energy X-ray absorptiometry 5 times during an AF season (start preseason, midpreseason, start season, midseason, end season) in 45 professional AF players. Dietary intakes and strength (bench press and bench pull) were also assessed at these time points. Players were categorized as experienced (>4 y experience, n = 23) or inexperienced (<4 y experience, n = 22). Fat mass decreased during the preseason but was stable through the in-season for both groups. %FFSTM was increased during the preseason and remained constant thereafter. UB strength increased during the preseason and was maintained during the in-season. Changes in UB FFSTM were related to changes in UB-strength performance (r = .37−.40). Total energy and carbohydrate intakes were similar between the experienced and inexperienced players during the season, but there was a greater ratio of dietary fat intake at the start-preseason point and an increased alcohol, reduced protein, and increased total energy intake at the end of the season. The inexperienced players consumed more fat at the start of season and less total protein during the season than the experienced players. Coaches should also be aware that it can take >1 y to develop the appropriate levels of FFSTM in young players and take a long-term view when developing the physical and performance abilities of inexperienced players.

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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.

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Gabriel Lozano-Berges, Ángel Matute-Llorente, Alejandro Gómez-Bruton, Alejandro González-Agüero, Germán Vicente-Rodríguez and José A. Casajús

The assessment of percentage of body fat (%BF) is often performed in sport clubs to monitor body composition changes in the athletes during the season due to its relationship with physical fitness and performance ( Avlonitou et al., 1997 ). Anthropometry, bioelectrical impedance analysis, dual

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J. Paul Fawcett, Stephen J. Farquhar, Robert J. Walker, Thearoth Thou, Graham Lowe and Ailsa Goulding

The effects of oral vanadyl sulfáte (VOSO4) (0.5 mg/kg/day) on anthropometry, body composition, and Performance were investigated in a 12-week, double-blind, placebo-controlled trial involving weight-training volunteers. Performance was assessed in the treatment (VS) and placebo (P) groups using 1 and 10 repetitions maximum (RM) for the bench press and leg extension. Thirty-one subjects completed the trial, with 2 VS subjects withdrawing because of apparent side effects. There were no significant treatment effects for anthropo-metric parameters and body composition during the trial. Both groups had significant improvements in performance but the only significant effect of treatment was a Treatment × Time interaction in the 1 RM leg extension (p=.002), which could have arisen because the VS group had a lower performance at baseline in this test. It was concluded that oral vanadyl sulfáte was ineffective in changing body composition in weight-training athletes, and any modest performance-enhancing effect requires further investigation.

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Vivian H. Heyward

This paper provides an overview of practical methods for assessing body composition of children, adults, and older adults. Three methods commonly used in field and clinical settings are skinfolds, bioelectrical impedance analysis, and anthropometry. For each method, standardized testing procedures, sources of measurement error, recommendations for technicians, and selected prediction equations for each age category are presented. The skinfold method is appropriate for estimating body fat of children (6–17 years) and body density of adults (18–60 years) from diverse ethnic groups. Likewise, bioimpedance is well suited tor estimating the fat-free mass of children (10-19 years) as well as American Indian, black, Hispanic, and white adults. Anthropometric prediction equations that use a combination of circumferences and bony diameters are recommended for older adults (up to 79 years of age), as well as obese men and women.

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Robert MacKenzie, Linda Monaghan, Robert A. Masson, Alice K. Werner, Tansinee S. Caprez, Lynsey Johnston and Ole J. Kemi

ID: 7474988 7474988 5. Laffaye G , Levernier G , Collin JM . Determinant factors in climbing ability: influence of strength, anthropometry, and neuromuscular fatigue . Scand J Med Sci Sports . 2016 ; 26 : 1151 – 1159 . PubMed ID: 26453999 doi: 10.1111/sms.12558 26453999 6. Laffaye G

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Francesco Campa, Alessandro Piras, Milena Raffi and Stefania Toselli

. Anthropometry and functional movement patterns in elite male volleyball players of different competitive levels . J Strength Cond Res . 2018 ; 32 ( 9 ): 2601 – 2611 . doi:10.1519/JSC.0000000000002368 30137032 10.1519/JSC.0000000000002368 14. Lohman TG , Roche AF , Martorell R . Anthropometric

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Disa J. Smee, Anthony Walker, Ben Rattray, Julie A. Cooke, Ben G. Serpell and Kate L. Pumpa

, predicted sums of squares, and Pearson’s correlations are presented in Table  3 . While the magnitude of the mean bias percentage varied, BIA overestimated the amount of fat and underestimated the amount of lean mass. Conversely, all anthropometry-based body fat estimates underestimated fat and

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Danielle L. Gyemi, Charles Kahelin, Nicole C. George and David M. Andrews

, Altena TS , Swan PD . Comparison of anthropometry to DXA: a new prediction equation for men . Eur J Clin Nutr. 2004 ; 58 ( 11 ): 1525 – 1531 . PubMed doi:10.1038/sj.ejcn.1602003 10.1038/sj.ejcn.1602003 15162135 9. Bilsborough JC , Greenway K , Opar

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Rodrigo Rodrigues Gomes Costa, Rodrigo Luiz Carregaro and Frederico Ribeiro Neto

 al . Total body water and percentage fat mass measurements using bioelectrical impedance analysis and anthropometry in spinal cord-injured patients . Clin Nutr . 2000 ; 19 ( 3 ): 185 – 190 . PubMed ID: 10895109 doi: 10.1054/clnu.1999.0122 10895109 23. Abadie Ben R , Altorfer GL , Schuler PB