2017 ◽  
Vol 12 (3) ◽  
pp. 393-401 ◽  
Author(s):  
Shane Malone ◽  
Mark Roe ◽  
Dominic A. Doran ◽  
Tim J. Gabbett ◽  
Kieran D. Collins

Purpose:To examine the association between combined session rating of perceived exertion (RPE) workload measures and injury risk in elite Gaelic footballers.Methods:Thirty-seven elite Gaelic footballers (mean ± SD age 24.2 ± 2.9 y) from 1 elite squad were involved in a single-season study. Weekly workload (session RPE multiplied by duration) and all time-loss injuries (including subsequent-wk injuries) were recorded during the period. Rolling weekly sums and wk-to-wk changes in workload were measured, enabling the calculation of the acute:chronic workload ratio by dividing acute workload (ie, 1-weekly workload) by chronic workload (ie, rolling-average 4-weekly workload). Workload measures were then modeled against data for all injuries sustained using a logistic-regression model. Odds ratios (ORs) were reported against a reference group.Results:High 1-weekly workloads (≥2770 arbitrary units [AU], OR = 1.63–6.75) were associated with significantly higher risk of injury than in a low-training-load reference group (<1250 AU). When exposed to spikes in workload (acute:chronic workload ratio >1.5), players with 1 y experience had a higher risk of injury (OR = 2.22) and players with 2–3 (OR = 0.20) and 4–6 y (OR = 0.24) of experience had a lower risk of injury. Players with poorer aerobic fitness (estimated from a 1-km time trial) had a higher injury risk than those with higher aerobic fitness (OR = 1.50–2.50). An acute:chronic workload ratio of (≥2.0) demonstrated the greatest risk of injury.Conclusions:These findings highlight an increased risk of injury for elite Gaelic football players with high (>2.0) acute:chronic workload ratios and high weekly workloads. A high aerobic capacity and playing experience appears to offer injury protection against rapid changes in workload and high acute:chronic workload ratios. Moderate workloads, coupled with moderate to high changes in the acute:chronic workload ratio, appear to be protective for Gaelic football players.


2021 ◽  
pp. 194173812110584
Author(s):  
Barry P. Boden ◽  
Anwar E. Ahmed ◽  
Kenneth M. Fine ◽  
Michael J. Craven ◽  
Patricia A. Deuster

Background: Nontraumatic fatalities occur on a regular basis in high school (HS) and college football athletes, primarily in obese linemen performing high-intensity exercise. One contributing factor to these deaths may be a mismatch between baseline aerobic (cardiorespiratory) fitness and exercise regimens. Hypothesis: There is a wide range of aerobic fitness in HS and college football players. Body mass index (BMI) is a safe and simple method for estimating baseline aerobic fitness. Study Design: Retrospective cohort study. Level of Evidence: Level 3. Methods: A retrospective review was performed on 79 HS football athletes who had VO2Peak (mL·kg−1·min−1) measured during the offseason. Multivariate regression analysis was used to determine if BMI (obese, overweight, and normal; kg/m2), position played (linemen vs other), year in school (freshmen vs other), and/or race (African American vs White) were risk factors for poor aerobic fitness. A separate cohort of 135 (48 HS; 87 college) football athletes performed a 6-minute run test to determine speed (miles/min), extrapolate VO2Max, and calculate reference values for suggested upper threshold safe starting speeds (85% of maximum) for aerobic training based on BMI. The relationship between BMI and VO2Peak was assessed. The exercise regimens (speeds) of 2 collegiate football fatalities from the public domain were used to predict their VO2Max values. Results: Mean VO2Peak (mL·kg−1·min−1) was 38.5 ± 8.6 (range 19.1-60.6); when grouped by BMI, low scores (<40) were found in 87.5% of obese (32.4 ± 7.7), 47.8% of overweight (40.8 ± 7.6), and 45.2% of normal (41.4 ± 7.8) athletes. VO2Peak was significantly lower in linemen (32.8 ± 6.4; P = 0.007) compared with nonlineman (41.8 ± 7.9), and in obese players (by BMI; 32.4; P = 0.019) compared with nonobese players (41.4 ± 7.6), but did not differ by age, year in school, or race. Means for speed (min/mile) and extrapolated VO2Max (mL·kg−1·min−1) for the 6-minute run test by BMI groups were both significantly different ( P = 0.001) for normal (7.0 ± 0.6; 51.1 ± 2.6), overweight (7.6 ± 0.8; 46.5 ± 3.2), and obese (8.9 ± 1.5; 36.8 ± 5.9) athletes. There was a significant negative correlation ( r = −0.551; P = 0.001; R2 = 0.304) between VO2Peak and BMI. Safe starting speed recommendations for running 1 mile range from 7.3 to 12.1 min/mile for BMIs 20 to 40 kg/m2 for HS and college athletes. For the 2 fatalities (mean, BMI of 36.5 kg/m2) repetitive sprint speeds were 49 and 89% higher than our safe starting speeds for their BMI. Conclusion: A large spectrum of baseline aerobic fitness was noted in HS and college football players. Obese players and linemen had statistically lower baseline aerobic fitness, a major risk factor for possible heat illness. BMI is an acceptable surrogate for VO2Peak and can be employed to develop safe training regimens without the need for a maximum fitness test, which can place the athlete at risk for a medical event. Clinical Relevance: Knowledge of BMI provides an estimate of baseline aerobic fitness and a foundation for prescribing safe, individualized exercise regimens.


2016 ◽  
Vol 30 (3) ◽  
pp. 102-113 ◽  
Author(s):  
Chun-Hao Wang ◽  
Chun-Ming Shih ◽  
Chia-Liang Tsai

Abstract. This study aimed to assess whether brain potentials have significant influences on the relationship between aerobic fitness and cognition. Behavioral and electroencephalographic (EEG) data was collected from 48 young adults when performing a Posner task. Higher aerobic fitness is related to faster reaction times (RTs) along with greater P3 amplitude and shorter P3 latency in the valid trials, after controlling for age and body mass index. Moreover, RTs were selectively related to P3 amplitude rather than P3 latency. Specifically, the bootstrap-based mediation model indicates that P3 amplitude mediates the relationship between fitness level and attention performance. Possible explanations regarding the relationships among aerobic fitness, cognitive performance, and brain potentials are discussed.


1972 ◽  
Author(s):  
B. Paranov ◽  
Al. Takev ◽  
A. Sepetlieva
Keyword(s):  

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