Comparison of Techniques for Tracking Body Composition Changes across a Season in College Women Basketball Players.

Body composition assessment has become an integral part of athletes' training schedules. Questions remain concerning the accuracy of various methods to track body composition changes over a competitive year cycle. The purpose of this study was to compare various methods of tracking body composition across a college women's basketball season. Fourteen Division II women (age = 20.1 ± 1.2 y) were measured prior to the season (T1), after pre-season conditioning (T2), at mid-season (T3), and at the end of the season (T4) using skinfolds (SKF), two bioelectric impedance analysis (BIA) devices, and dual-energy x-ray absorptiometry (DXA). BIA devices were hand-to-hand (H-BIA) and foot-to-foot (F-BIA) single-frequency models. SKF were used to estimate %fat using four prediction equations. A method × trial factorial ANOVA on %fat with repeated measures over the second factor indicated that all methods except the Durnin-Womersley SKF equation were significantly lower than DXA. Across trials, DXA %fat at T1 (25.3 ± 4.7%) was significantly higher than at T2 (24.3 ± 4.6%), T3 (24.6 ± 4.6%), and T4 (24.4 ± 5.1%). Agreement between DXA and the other methods were moderate (r = 0.48 - 0.86). Rank-order correlations of DXA with the other methods to compare team order indicated H-BIA (rho = 0.67 - 0.78) and F-BIA (rho = 0.62 - 0.77) provided comparable agreement, with SKF methods having lower agreement for team order (rho = 0.46 - 0.73). Compared to the DXA standard, a foot-to-foot BIA device may provide adequate but significantly lower relative tracking of %fat across a women's basketball season.

Validity of Arm-to-Arm BIA Devices Compared to DXA for Estimating % Fat in College Men and Women.

Bioelectric impedance analysis (BIA) devices are commonly used to estimate percent body fat (%fat), although validation of their accuracy varies widely. The purpose of this study was to assess the validity of four commonly used BIA devices compared to dual-energy X-ray absorptiometry (DXA). College-aged men (n = 29, age = 19.7 ± 1.2 y, weight = 76.9 ± 12.5 kg) and women (n = 31, age = 20.5 ± 0.8 y, weight = 61.5 ± 9.2 kg) were evaluated for %fat using four single-frequency (50 mHz) BIA devices and DXA. A gender × device repeated measures ANOVA indicated some less expensive BIA devices produced %fat values that were not significantly different from DXA. A thumb-to-thumb BIA device produced the closest values in men (21.9 ± 6.6%) and women (32.1 ± 5.3%) compared to DXA (20.6 ± 6.1% and 30.3 ± 5.4%, respectively). The two more expensive BIA devices significantly underestimated in men (14.7 ± 5.8% and 17.0 ± 5.6%) and women (23.3 ± 4.2% and 23.3 ± 4.2%) compared to DXA. Interclass correlation coefficients with DXA were higher for the more expensive devices in men (ICC = 0.899 and 0.958) than the less expensive devices (ICC = 0.681 and 0.730). In women, all BIA devices showed moderate correlations with DXA (ICC = 0.537 to 0.658). Despite the convenience of simple BIA devices, their use in estimating body composition in young men and women might be questionable due to large variations in the differences between DXA and each device in this study.

Inter-Investigator Reliability of Anthropometric Prediction of 1RM Bench Press in College Football Players.

The purpose of this study was to determine the effect of inter-investigator differences in anthropometric assessments on the prediction of one-repetition maximum (1RM) bench press in college football players. Division-II players (n = 34, age = 20.4 ± 1.2 y, 182.3 ± 6.6 cm, 99.1 ± 18.4 kg) were measured for selected anthropometric variables and 1RM bench press at the conclusion of a heavy resistance training program. Triceps, subscapular, and abdominal skinfolds were measured in triplicate by three investigators and used to estimate %fat. Arm circumference was measured around a flexed biceps muscle and was corrected for triceps skinfold to estimate muscle cross-sectional area (CSA). Chest circumference was measured at mid-expiration. Significant differences among the testers were evident in six of the nine anthropometric variables, with the least experienced tester being significantly different from the other testers on seven variables, although average differences among investigators ranged from 1-2% for circumferences to 4-9% for skinfolds. The two more experienced testers were significantly different on only one variable. Overall agreement among testers was high (ICC>0.895) for each variable, with low coefficients of variation (CV<10.7%). Predicted 1RMs for testers (126.9 ± 20.6, 123.4 ± 22.0, and 132.1 ± 28.4 kg, respectively) were not significantly different from actual 1RM (129.2 ± 20.6 kg). Individuals with varying levels of experience appear to have an acceptable level of ability to estimate 1RM bench press using a non-performance anthropometric equation. Minimal experience in anthropometry may not impede strength and conditioning specialists from accurately estimating 1RM bench press.

Upper-body strength gains from different modes of resistance training in women who are underweight and women who are obese.

The purpose of this study was to determine the degree of upper-body strength gained by college women who are underweight and those who are obese using different modes of resistance training. Women who were underweight (UWW, n = 93, weight = 49.3 ± 4.5 kg) and women who were obese (OBW, n = 73, weight = 94.0 ± 15.1 kg) were selected from a larger cohort based on body mass index (UWW ≤ 18.5 kg·m⁻²; OBW ≥ 30 kg·m⁻²). Subjects elected to train with either free weights (FW, n = 38), supine vertical bench press machine (n = 52) or seated horizontal bench press machine (n = 76) using similar linear periodization resistance training programs 3× per week for 12 weeks. Each participant was assessed for upper-body strength using FWs (general) and machine weight (specific) 1 repetition maximum bench press before and after training. Increases in general and mode-specific strength were significantly greater for OBW (5.2 ± 5.1 and 9.6 ± 5.1 kg, respectively) than for UWW (3.5 ± 4.1 and 7.2 ± 5.2 kg, respectively). General strength gains were not significantly different among the training modes. Mode-specific gains were significantly greater (p < 0.05) than general strength gains for all groups. In conclusion, various resistance training modes may produce comparable increases in general strength but will register greater gains if measured using the specific mode employed for training, regardless of the weight category of the individual.