30 research outputs found

    Anaerobic performance in masters athletes

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    Evaluation of a 2-Load Prediction Equation to Predict 1RM Bench Press in Football Players

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    Jerry L. Mayhew1, William F. Brechue2, Bryan Mann3, J. Jay Dawes4 1Truman State University, Kirksville, Missouri, 2Physiology Department, A. T. Still University of Health Sciences, Kirksville, Missouri, 3University of Miami, Miami, FL, 4Oklahoma State University, Stillwater, OK Repetitions-to-fatigue (RTF) equations are popular for estimating one-repetition maximum (1RM) bench press performance. Most of these equations have used a single submaximal load in the 70-90% range to predict 1RM. However, the efficacy of using a 2-load approach, as suggested by Brzycki, has received little attention. This technique extrapolates the slope of the 2-load-to-repetition relationship to estimate 1RM. The 2-load approach has not been compared to single-load equations to determine its accuracy for estimating 1RM in athletes. PURPOSE: To compare the accuracy of 1-load and 2-load equations to predict 1RM bench press in college football players. METHODS: NCAA Division-II players from 3 schools (n = 157) volunteered to participate during off-season resistance training. Players were grouped as linemen (n = 80; age = 19.5 ± 1.2 yrs, height = 184.7 ± 6.3 cm, weight = 107.8 ± 18.5 kg) and backs (n = 77; age = 19.6 ± 1.4 yrs, height = 182.1 ± 6.6 cm, weight = 92.3 ± 16.6 kg). Each player performed RTF in the 3-5RM and 7-10RM ranges on two separate days within the same week. The week following RTF performances, each player performed a 1RM using the standard touch-and-go method. 1RM predictions were constructed using several 1-load equations, the original 2-load 1repetition reduction equation, and a newly developed 2-load no-repetition reduction approach. RESULTS: The %1RM in the 3-5RM range was not significantly different between backs (90.2 ± 2.5%) and linemen (89.8 ± 2.4%). Likewise, %1RM in the 7-10RM range was not significantly different between backs (80.0 ± 4.0%) and linemen (79.9 ± 3.8%). The original 1load prediction for both 3-5RM loads (133.2 ± 24.0 kg) and 7-10RM loads (134.6 ± 23.8 kg) significantly underpredicted 1RM (136.5 ± 24.8 kg). The 2-load equation with a 1-repetition reduction (133.0 ± 24.4 kg) also significantly underpredicted 1RM. A new no-repetition reduction approach accurately predicted 1RM (136.5 ± 25.2 kg) to within ±5.0% in 79% of the players. The new no-reduction equation had no bias and an acceptable 95% LoA (-12.0 to 12.0 kg). CONCLUSION: A modified version of a two-load RTF prediction equation without a repetition reduction appears to offer a more accurate estimate of 1RM bench press in football athletes than previous 1-load equations or a 2-load 1-repetiton reduction equation

    Comparisons of Lean Mass Proportionalities between Male and Female College Athletes

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    Allison Oligschlaeger1, Monica L. Hunter1, Jana L. Arabas1, Jerry L. Mayhew1, and William F. Brechue2 1Truman State University, Kirksville, MO; 2A. T. Still University, Kirksville, MO Few studies have assessed regional lean mass proportionalities (LM%) between men and women competing in similar sports. Assessing LM% may identify performance differences between sexes in different sports. PURPOSE: To compare absolute and relative LM among men and women in comparable sports. METHODS: NCAA Division-II athletes (M = 106, age = 20.4 ± 1.2 yrs, height = 182.4 ± 8.6 cm, weight = 79.4 ± 12.2 kg; W = 90, age = 20.5 ± 1.2 yrs, height = 168.1 ± 7.6 cm, weight = 63.3 ± 9.1 kg) from 5 compatible sports (cross-country, soccer, basketball, swimming, and baseball/softball) were measured using dual-energy X-ray absorptiometry (DXA). Arms, legs, and trunk relative LM were expressed relative to total LM. RESULTS: A sex x sport multivariate ANOVA revealed that men had significantly greater LM in arms (8.5 ± 1.5 kg), legs (22.5 ± 3.5 kg), and trunk (30.3 ± 3.7 kg) than women (4.7 ± 0.7, 15.8 ± 1.9, 21.6 ± 2.2kg, respectively). Among sports, cross-country had the lowest LM for arms (5.3 ± 1.8 kg), legs (16.2 ± 3.2 kg), and trunk (23.0 ± 4.0 kg), while basketball had the highest (7.5 ± 2.4, 21.7 ± 4.7, and 28.4 ± 5.5 kg, respectively). There was no significant difference among soccer (6.2 ± 2.0, 18.6 ± 3.3, 25.0 ± 4.4 kg, respectively), swimming (6.7 ± 2.0, 17.9 ± 3.7, 25.8 ± 4.9 kg, respectively), and baseball/softball (7.1 ± 2.3, 20.1 ± 4.6, 26.7 ± 6.0 kg, respectively). Arm LM% for men (13.1 ± 1.1%) was significantly higher than for women (10.5 ± 0.9%) while trunk %LM was significantly higher in women (48.0 ± 1.5%) than in men (46.9 ± 1.6%). Leg LM% was not significantly different between men (34.7 ± 1.7%) and women (35.0 ± 1.6%). Cross-country (11.0 ± 1.9%) and soccer (11.5 ± 1.8%) had significantly lower arm LM% than basketball (12.1 ± 1.5 %), baseball/softball (12.1 ± 1.5%), and swimming (12.2 ± 1.5%), which did not differ significantly. Swimming (33.4 ± 1.2%) and cross-country (34.2 ± 1.5%) had significantly lower leg LM% than baseball/softball (35.1 ± 1.5%), soccer (35.1 ± 1.4%), and basketball (35.5 ± 1.6%), which did not differ significantly. Basketball (46.7 ± 1.6%) and baseball/softball (46.9 ± 1.4%) had significantly lower trunk LM% than soccer (47.2 ± 1.4%), swimming (48.3 ± 1.3%), and cross-country (48.6 ± 1.8%), which did not differ significantly. CONCLUSION: Although significant, LM variability across comparable sports appears to be small in magnitude

    Comparisons of Lean Mass Proportionalities Among College Football Players

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    Spencer Newell1, Brenden Kelly1, Monica L. Hunter1, Allison Oligschlaeger1, Jana L. Arabas1, Jerry L. Mayhew1, and William F. Brechue2 1Truman State University, Kirksville, MO; 2A. T. Still University, Kirksville, MO Large athletes dominate college football. Significant amounts of training are devoted to developing muscle mass in these players. Advanced technology allows measurement of lean mass (LM) in selected regions of the body. However, no studies have evaluated differences in regional LM proportionalities amount players of different sizes in football. PURPOSE: To compare regional LM proportionalities (LM%) among college football players of different body weights. METHODS: NCAA Division-II players (n = 196) volunteered to be measured using dual-energy X-ray absorptiometry (DXA) to determine LM% for arms, legs, and trunk after offseason resistance training. For size comparison, players were divided into 4 body weight categories (Gr 1: \u3c91 kg, n = 100, Gr 2: 91-113 kg, n = 64, Gr 3: 114-135 kg, n = 19, Gr 4: \u3e135 kg, n = 13). Regional proportionalities (LM%) were determine by dividing regional LM by total LM. RESULTS: Absolute arm LM was not significantly different between Gr 4 (8.1 ± 2.4 kg) and Gr 1 (9.1 ± 1.2 kg) or between Gr 2 (10.1 ± 1.1 kg) and Gr 3 (10.4 ± 1.5 kg), but the first pair was significantly lower than the second pair. Gr 1 (24.0 ± 2.3 kg) had a significantly lower absolute leg LM than Gr 2 (27.5 ± 2.2 kg), which was significantly lower than Gr 3 (31.4 ± 2.0 kg) and Gr 4 (31.8 ± 5.5 kg). Gr 3 and Gr 4 did not differ significantly in leg LM. Absolute trunk LM was significantly different across Gr 1 (30.6 ± 2.4 kg), Gr 2 (34.4 ± 2.5 kg), Gr 3 (36.7 ± 5.1 kg), and Gr 4 (41.2 ± 5.7 kg). Arm LM% was not significantly different between Gr 1 (13.4 ± 1.4%) and Gr 2 (13.4 ± 0.9%) or between Gr 2 and Gr 3 (12.5 ± 1.7%); Gr 4 (9.4 ± 2.8%) was significantly lower than all groups. Leg LM% was not significantly different among Gr 1 (35.8 ± 2.5%), Gr 2 (36.4 ± 1.7%) and Gr 4 (36.8 ± 3.1%); Gr 3 (37.7 ± 2.2%) was significantly higher than all other groups. Trunk LM% was significantly lower for Gr 3 (44.0 ± 5.6%) than for Gr 4 (47.4 ± 6.2%), but there were no significant difference among Gr 1 (45.5 ± 1.8%), Gr 2 (45.4 ± 1.6%, and Gr 4 (47.7 ± 6.2%). CONCLUSION: This study revealed significant but small differences in regional lean mass proportionalities among college football players at the Division-II level. Further investigation should be performed on players from Division-I schools to determine if the pattern of regional proportionalities are similar across weight classifications
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