Askow, Andrew T

The purpose of the study was to examine differences in body fat percentage (BF%) across groups stratified by resting metabolic rate (RMR) when normalized to body weight. National Collegiate Athletic Association Division III athletes (n = 190; Age: 19.8 ± 1.4 year; Body Mass: 79.3 ± 20.2 kg; Height: 175.0 ± 9.3 cm, Body Mass Index: 25.6 ± 4.9 kg/m2) participated in this cross-sectional mixed cohort study. Body composition was assessed using air displacement plethysmography. RMR was assessed using indirect calorimetry. For each sex, tertiles were determined and used to create low, moderate, and high relative RMR groups as follows: low (M: <26 kcal/kg; F: <24 kcal/kg), moderate (M: 26.1–29.0 kcal/kg; F: 24.1–27.0 kcal/kg), and high (M: >29.1 kcal/kg; F: >27.1 kcal/kg). The mean ± standard deviation RMR for male and female athletes was 27.9 ± 3.2 and 25.9 ± 2.8 kcals/kg when expressed relative to body weight. When stratified by sex, males in the low RMR group had significantly higher BF% values than those in the moderate (mean difference, [95% confidence intervals]) (7.2, [2.4, 12.0] kcal/kg; p < 0.01) and high RMR groups (7.7, [2.9, 12.5] kcal/kg; p < 0.001). Female athletes in the moderate RMR group had higher body fat percentages than those in the high RMR group (mean difference, [95% confidence intervals]) (5.8, [2.4, 9.2] kcal/kg; p < 0.01). Female athletes in the moderate relative RMR group had higher BF% values than those in the higher relative RMR group (3.3, [−0.1, 6.7] kcal/kg; p = 0.049). Both male and female athletes with a low relative RMR had a higher BF%.

Abstract Floersch, S, Vidden, C, Askow, AT, Jones, MT, Fields, JB, and Jagim, AR. Seasonal changes in match demands and workload distribution in collegiate soccer across two seasons. J Strength Cond Res 38(8): 1440–1446, 2024—The purpose of this study was to examine seasonal changes in match demands in a collegiate women's soccer team. Forty-eight NCAA Division III women soccer athletes (age: 19.5 ± 1.2 years; height: 1.67 ± 0.05 m; body mass: 64.8 ± 7.4 kg; fat-free mass: 50.0 ± 4.5 kg; body fat %: 22.6 ± 6.0) were equipped with wearable global positioning systems with inertial sensors and heart rate (HR) monitors during matches throughout the 2019 ( n = 22) and 2021 seasons ( n = 26). Players were classified by position: flank player (FP; n = 28), center midfielder (CM; n = 11), and center back fielder (CB; n = 9) and as starters (S, n = 17) or reserves (R, n = 31). Variables included HR, training load, total distance, high-speed distance, distance per minute, and weighted distance. Differences in match and practice session demands were analyzed using linear mixed-effects models with season (2 levels; 2019 and 2021) as a fixed factor, with alpha set to p = 0.05. Data across all matches and training sessions were collapsed and presented as mean ± SD for descriptive purposes and then grouped by session type (i.e., match or training) and position. Athletes traveled more distance at high speeds during match play in the 2021 season compared with 2019 (mean difference, 95% confidence intervals [CI]) (200, 95% CI: 104, 304 km; p < 0.05) but had a lower training load in 2021 compared with 2019 (−50, 95% CI: −63, −36; p < 0.05) during match play. For training sessions, mean HR (4, 95% CI: 2, 5 bpm), total distance (0.5, 95% CI: 0.4, 0.7), distance per minute (5.6, 95% CI: 4.5, 6.7 m·min −1 ), high-speed distance (43, 95% CI: 43, 18, 67 m), high accelerations (8.6, 95% CI: 5.4, 11.8 n ), and high accelerations per minute (0.1, 95% CI: 0.1, 0.1 n ·min −1 ) were all higher in 2021 compared with 2019 ( p < 0.05). As a team, several differences in measures of external workload were found between seasons in both session types (training and matches). Variations in positional demands of match play appear to fluctuate by year.

Abstract Askow, AT, Jennings, W, Jagim, AR, Fields, JB, Beaudoin, RG, Sanchez, GM, Weeks, JE, Oliver, JM, and Jones, MT. Athlete external load measures across a competitive season in high school basketball. J Strength Cond Res 37(11): 2206–2212, 2023—The purpose of this retrospective analysis was to quantify in-season external load and to determine if relationships existed between load metrics and basketball performance. Eleven male high school varsity basketball athletes (n = 11; mass 80.5 ± 9.6 kg, height 190.2 ± 9.4 cm, age 17.6 ± 0.7 years) were monitored across a season. PlayerLoad (PL), PL per minute (PL·min −1 ), total jumps, and explosive movements (EMs) were quantified using a commercially available local positioning unit. Basketball-specific performance metrics, including points scored, points allowed, point differentials, and shooting percentages for each quarter and game, were compiled. Data were analyzed using repeated-measure analysis of variance to evaluate differences in load by starting status, session type, game outcome, and game type. Pearson's correlation coefficients were used to assess relationships between load metrics and basketball performance. Statistical significance was set at p < 0.05. The mean values across 23 games for PL, PL·min −1 , total jumps, and EMs were 457 ± 104 AU, 10.9 ± 1.6 AU, 42.6 ± 9.6, and 46.7 ± 7.2, respectively. Relationships were observed ( p < 0.05) between PL and points scored ( r = 0.38) and free throw percentage ( r = 0.21). Further relationships were observed between PL·min −1 and free throw shooting percentage ( r = −0.27), and between points scored and total jumps ( r = 0.28), and EMs ( r = 0.26). Notable differences in game demands were observed for playing status. Meaningful differences in measures of external load were observed between each quarter of play, with the highest measures evident in quarters 1 and 3. Guards and forwards experienced minimal differences in external load during gameplay, and game outcome did not result in differences. Higher point totals corresponded with higher PL, total jumps, and EM.

The purpose of this study was to examine sex differences in resting metabolic rate (RMR) and associations between measured RMR and body composition parameters in athletes. One-hundred and ninety collegiate men (n = 98; age: 20.1 ± 1.6 yr.; body mass: 92.7 ± 17.5 kg; height: 181.6 ± 6.2 cm, body mass index: 28.0 ± 4.7 kg/m2) and women (n = 92; age: 19.4 ± 1.1 yr.; body mass: 65.2 ± 11.0 kg; height: 168.0 ± 6.6 cm, body mass index: 23.0 ± 3.6 kg/m2) athletes volunteered to participate in this study. Athletes completed a body composition assessment using air displacement plethysmography and RMR using indirect calorimetry. Assessments were completed in a fasted state and after refraining from intense physical activity > 24 h prior to testing. Data were collected during the 2016–2019 seasons. Men had a higher RMR compared to women (2595 ± 433 vs. 1709 ± 308 kcals; p < 0.001); however, when adjusted for body mass (p = 0.064) and fat-free mass (p = 0.084), the observed differences were not significant. Height, body mass, body mass index, fat-free mass, and fat mass were positively associated with RMR in both men and women athletes (r = 0.4–0.8; p < 0.001). Body mass (men: β = 0.784; women: β = 0.832)) was the strongest predictor of RMR. Men athletes have a higher absolute RMR compared to their women counterparts, which is influenced by greater body mass and fat-free mass. Body mass is the strongest predictor of RMR in both men and women athletes.

Firefighters often complete air management courses (AMC) to assess the ability to tolerate personal protective equipment, appropriately manage the breathing system and assess occupational performance. Little information is known relative to the physiological demands of AMCs, nor how to assess work efficiency in order to characterize occupational performance and evaluate progress. Purpose: To assess the physiological demands of an AMC and examine differences across BMI categories. A secondary aim was to develop an equation to assess work efficiency in firefighters. Methods: Fifty-seven firefighters (Women, n = 4; age: 37.2 ± 8.4 yr.; height: 182.0 ± 6.9 cm; body mass: 90.8 ± 13.1 kg; BMI: 27.8 ± 3.6 kg·m−2) completed an AMC per routine evaluation while wearing a department issued self-contained breathing apparatus and full protective gear. Course completion time, starting pounds per square inch (PSI) on the air cylinder, changes in PSI, and distance traveled were recorded. All firefighters were equipped with a wearable sensor integrated with a triaxial accelerometer and telemetry to assess movement kinematics, heart rate, energy expenditure, and training impulse. The AMC consisted of an initial section involving a hose line advance, rescue (body drag), stair climb, ladder raise, and forcible entry. This section was followed by a repeating loop, which consisted of a stair climb, search, hoist, and recovery walk. Firefighters repeated the course loop until the self-contained breathing apparatus air supply pressure reached 200 PSI, at which time they were instructed to lay down until the PSI reached zero. Results: Average completion time was 22.8 ± 1.4 min, with a mean distance of 1.4 ± 0.3 km and an average velocity of 2.4 ± 1.2 m·s−1. Throughout the AMC, the mean heart rate was 158.7 ± 11.5 bpm equating to 86.8 ± 6.3% of the age-predicted max heart rate and a training impulse of 55 ± 3 AU. Mean energy expenditure was 464 ± 86 kcals and work efficiency was 49.8 ± 14.9 km·PSI−1·s. Regression analysis determined that fat-free mass index (R2 = 0.315; β = −5.069), body fat percentage (R2 = 0.139; β = −0.853), fat-free mass (R2 = 0.176; β = −0.744), weight (R2 = 0.329; β = −0.681), and age (R2 = 0.096; β = −0.571) were significant predictors of work efficiency. Conclusions: The AMC is a highly aerobic task with near-maximal heart rates reached throughout the course. Smaller and leaner individuals achieved a higher degree of work efficiency during the AMC.

ABSTRACTPredictive resting metabolic rate (RMR) equations are widely used to determine total daily energy expenditure (TDEE). However, it remains unclear whether these predictive RMR equations accurately predict TDEE in the athletic populations. The purpose of this study was to examine the accuracy of 10 commonly used RMR prediction equations (Cunningham, De Lorenzo, Freire, Harris‐Benedict, Mifflin St. Jeor, Nelson, Owen, Tinsley, Watson, Schofield) in collegiate men and women athletes. One‐hundred eighty‐seven National Collegiate Athletic Association Division III men (n = 97) and women (n = 90) athletes were recruited to participate in one day of metabolic testing. RMR was measured using indirect calorimetry and body composition was analyzed using air displacement plethysmography. A repeated measures ANOVA with Bonferroni post hoc analyses was selected to determine mean differences between measured and predicted RMR. Linear regression analysis was used to assess the accuracy of each RMR prediction method (p<0.05). All prediction equations significantly underestimated RMR (p<0.001), although there was no difference between the De Lorenzo and Watson equations and measured RMR (p = 1.00) for women, only. In men, the Tinsley and Freire equations were the most agreeable formulas with the lowest root‐mean‐square prediction error value of 404 and 412 kcals, respectively. In women, the De Lorenzo and Watson equations were the most agreeable equations with the lowest root‐mean‐squared error value of 171 and 211 kcals, respectively. The results demonstrate that such RMR equations may underestimate actual energy requirements of athletes and thus, practitioners should interpret such values with caution.

Research quantifying the unique workload demands of starters and reserves in training and match settings throughout a season in collegiate soccer is limited. Purpose: The purpose of the current study is to compare accumulated workloads between starters and reserves in collegiate soccer. Methods: Twenty-two NCAA Division III female soccer athletes (height: 1.67 ± 0.05 m; body mass: 65.42 ± 6.33 kg; fat-free mass: 48.99 ± 3.81 kg; body fat %: 25.22 ± 4.78%) were equipped with wearable global positioning systems with on-board inertial sensors, which assessed a proprietary training load metric and distance covered for each practice and 22 matches throughout an entire season. Nine players were classified as starters (S), defined as those playing >50% of playing time throughout the entire season. The remaining 17 were reserves (R). Goalkeepers were excluded. A one-way ANOVA was used to determine the extent of differences in accumulated training load throughout the season by player status. Results: Accumulated training load and total distance covered for starters were greater than reserves ((S: 9431 ± 1471 vs. R: 6310 ± 2263 AU; p < 0.001) and (S: 401.7 ± 31.9 vs. R: 272.9 ± 51.4 km; p < 0.001), respectively) throughout the season. Conclusions: Starters covered a much greater distance throughout the season, resulting in almost double the training load compared to reserves. It is unknown if the high workloads experienced by starters or the low workloads of the reserves is more problematic. Managing player workloads in soccer may require attention to address potential imbalances that emerge between starters and reserves throughout a season.

Purpose: The purpose of this study was to determine whether session rating of perceived exertion-derived training load (sRPE-TL) correlates with GPS-derived measures of external load in National Collegiate Athletics Association (NCAA) Division I female soccer athletes. Methods: Twenty-one NCAA Division 1 collegiate women’s soccer athletes (11 starters, 10 non-starters; 65.1 ± 7.2 kg, 168.4 ± 7.9 cm, 20.3 ± 1.5 yrs) volunteered to take part in this study. Data for this study were collected over the course of 16 weeks during the 2018 NCAA women’s soccer season. External load and heart rate (HR) data were collected during each training session and match during the season. At least 30 min after the end of an activity (e.g., match or practice), athletes were prompted to complete a questionnaire reporting their perceived exertion for the session. sRPE-TL was calculated at the end of the season by multiplying perceived exertion by the respective session duration. Results: sRPE-TL was very strongly correlated with total distance, distance covered in velocity zones 1–3, the number of accelerations in zones 4 and 5, total PlayerLoad™, and PlayerLoad™. For internal load, sRPE-TL correlated very strongly (0.70 ≤ |r| < 0.90) with Edward’s and Bannister’s TRIMP and strongly (0.50 ≤ |r| < 0.70) with duration spent in in heart rate zones 5 and 6 (80–90% and 90–100% max HR, respectively) while correlations with maximum HR (bpm), mean HR (bpm), and mean HR (%) and sRPE-TL were moderate (0.30 ≤ |r| < 0.50). Conclusions: In NCAA Division I women soccer, sRPE-TL is strongly associated with external measures of workload. These relationships were stronger during match play, with acceleration load and total distance exhibiting the strongest relationship with sRPE-TL.

Objectives Concussions and mild traumatic brain injuries are important medical issues, particularly among youth as the long-term health consequences of these injuries can become increasingly problematic. The purpose of this study was to examine recent trends in diagnosed concussions among pediatric patients in a large health care system. Methods This was a retrospective, population-based epidemiology study design that queried all patient files (pediatrics included) using electronic medical health records and further stratified patients based on type of concussion, age, sex, and year from 2013 to 2018. Results Electronic health records from a cohort of 8 832 419 (n males = 4 246 492; n females = 4 585 931) patient visits were assessed for concussion diagnosis and filtered for those whose concussive event led to a loss of consciousness (LOC) or not (nLOC). Of these patients, 12 068 were diagnosed with a concussion (LOC = 3 699; nLOC = 8 369) with an overall incidence rate of 1.37 concussions per 1000 patients. Overall, the number of patients diagnosed with a concussion increased by 5063 (LOC = 1351; nLOC = 3712) from 2013 to 2018. Males and females presented with similar rates of concussions 5919 (49.05%) and 6149 concussions (50.95%), respectively. Of total diagnosed concussions, 4972 (LOC = 815; nLOC = 4157) were under the age of 18 and represented 41.2% of all diagnosed concussions with an incidence rate of 6.79 per 1000 patients. Conclusion The number of concussions diagnosed appear to be on the rise with the largest number of concussions being diagnosed in those under the age of 18. Future studies should seek to determine primary causality and the long-term health implications of concussions with or without LOC.