Citations

Background/Objectives: Adherence to sports-specific nutritional guidelines can help optimize athlete performance and health. However, adolescent athletes may not have adequate nutrition knowledge and understanding of specific nutritional requirements. The objective of the current study was to examine the nutrition knowledge and perceived dietary requirements of adolescent athletes. Methods: Male (n = 29, age: 15.7 ± 1.3 yrs.; height: 178.9 ± 8.3 cm; body mass: 74.7 ± 17.2 kg; body fat %: 13.9 ± 7.9%) and female (n = 15, age: 16.5 ± 1.4 yrs.; height: 169.9 ± 6.5 cm; body mass: 63.3 ± 4.5 kg; body fat %: 23.7 ± 3.8%) secondary school student-athletes completed body composition testing (hydrostatic weighing) and electronic surveys (Abridged Sports Nutrition Knowledge Questionnaire (ASNKQ); self-perception of dietary energy and macronutrient requirements). Results: Athletes demonstrated poor sports nutrition knowledge, with no differences observed between sexes for the number of questions answered correctly (males: 45.1 ± 9.8% vs. females: 43.1 ± 12.7%; p = 0.57). No relationships were observed between ASNKQ scores and body composition parameters or between ASNKQ scores and self-reported perception of dietary energy and macronutrient requirements (p > 0.05). Athletes self-reported a lower perceived energy (−560 ± 1272 kcal/d; p = 0.014) and carbohydrate intake (−73 ± 376 g/d; p = 0.014) requirement compared to calculated nutritional recommendations. Athletes self-reported a higher perceived protein intake (263 ± 586 g/d; p = 0.026) requirement compared to calculated nutritional requirements. Conclusions: The current sample of adolescent athletes from the secondary school level appears to have a poor level of sports nutrition knowledge and understanding of energy and macronutrient requirements.

External (EL) and internal (IL) load are commonly used methods used to quantify training load in team sports. Playing time and playing position may influence the training loads for specific athletes throughout a season. The purpose of the current study was to evaluate the effect of athlete playing status and individual in-season practices on EL and IL across a collegiate women’s basketball season. Female basketball athletes were classified as high-minute (HMA; ≥15 min/game) or low-minute (LMA; <15 min/game) and wore microsensors during 53 practices for a total of 583 data points. EL was obtained via an inertial measurement unit (IMU) device that contained a triaxial accelerometer to obtain three-dimensional positioning data. IL and strength training (ST) load were determined via session rating of perceived exertion (sRPE) to create a daily summated value. Descriptive statistics indicate that athletes experienced individual differences in EL, ST, and IL throughout the season. A growth model showed that HMAs experienced higher EL than LMAs at the start of the season for practices (90.21 AU). Across all athletes, IL increased across the season (40.11 AU) and for each 1 unit of change in EL, IL increased by 1.04 AU. Repeated measures correlations identified a large relationship between IL and EL (r = 0.51, p < 0.001). A location-scale model indicated that the within-person variability of IL across all athletes was 3.29 AU but was not due to athlete playing status. It is recommended to base in-season training on individual loads and game demands to promote athlete readiness and improved sport performance.

Blood flow restriction (BFR) is a popular resistance exercise technique purported to increase metabolic stress and augment training adaptations over time. However, short-term use may lead to acute neuromuscular fatigue and higher exertion ratings. Objective: The purpose of the current study was to examine acute physiological responses to low-load resistance exercise utilizing BFR compared to higher-load, non-BFR resistance exercise. Methods: Recreationally trained males (n = 6) and females (n = 7) (mean ± standard deviation, age: 20 ± 1 yrs.; height: 172 ± 8 cm; weight: 73 ± 11 kg; BMI: 24.4 ± 2.2 kg·m−2; training experience: 4 ± 2 yrs.) had limb occlusion pressure determined (50%; right leg: 118 ± 11 mmHg; left leg: 121 ± 13 mmHg) using an automated, self-inflating cuff system during baseline testing. In subsequent sessions, using a randomized, cross-over design, participants completed one of two experimental conditions: (1) Low-load + BFR and (2) High load + non-BFR. In both conditions, participants completed one set of back squats at either 30% (BFR) or 60% (non-BFR) of an estimated 1RM for a max of 30 repetitions, followed by three additional sets with the same loads and a target of 15 repetitions per set. Blood lactate and countermovement jump (CMJ) height were measured pre- and post-back squat. Ratings of perceived exertion (RPE) were assessed following each set. Results: When collapsed across all sets, participants completed significantly more total repetitions in the BFR condition compared to non-BFR (75.0 ± 0.0 vs. 68.23 ± 9.27 reps; p = 0.015; ES: 1.03), but a lower training load volume (2380 ± 728 vs. 4756 ± 1538 kg; p < 0.001; ES: 1.97). There was a significant time-by-condition interaction (p < 0.001), with a greater increase in blood lactate occurring from baseline to post-back squat in the non-BFR condition (11.61 mmol/L, 95%CI: 9.93, 13.28 mmol/L) compared to BFR (5.98 mmol/L, 95%CI: 4.30, 7.65 mmol/L). There was another significant time-by-condition interaction (p = 0.043), with a greater reduction in CMJ occurring in the non-BFR condition (−6.01, 95%CI: −9.14, −2.88 cm; p < 0.001) compared to BFR (−1.50, 95%CI: −1.50, 4.51 cm; p = 0.312). Conclusions: Utilizing a low-load BFR protocol may allow for a higher training volume, yet lower metabolic stress and reduce neuromuscular fatigue compared to lifting at a higher load without the use of BFR.

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 Women experience a higher rate of anterior cruciate ligament (ACL) injuries than men. Muscle imbalance, in particular hamstring-to-quadriceps (H:Q) strength ratio, is considered a risk factor for ACL injury. The purpose of this systematic review was to identify isokinetic H:Q strength ratios in women team sport athletes and determine whether cutoff values, determined from research with predominantly males, of >0.6 for conventional ratio (Hamstring concentric :Quadriceps concentric [CR]) and >1.0 for functional ratio (Hamstring eccentric :Quadriceps concentric [FR]) were met. The CR (0.6) was not met for team ([mean ± SD: 0.56 ± 0.08]), field (0.57 ± 0.08), and court (0.56 ± 0.08) sports. Handball presented the highest (0.58 ± 0.07), and softball presented the lowest CRs (0.47 ± 0.06). The FR (1.0) was not met for team (0.69 ± 0.14), field (0.85 ± 0.14), and court (0.65 ± 0.14) sports. Soccer presented the highest (0.85 ± 0.14) and handball the lowest (0.66 ± 0.13) FRs. When assessing hamstring and quadriceps strength balance, women team sport athletes did not meet CR or FR values, which may contribute to increased ACL injury risk. H:Q ratios below cutoff values may indicate compromised hamstring strength. It is recommended practitioners implement strength exercises aimed to improve H:Q ratios.

Abstract Jagim, AR, Harty, PS, Jones, MT, Fields, JB, Magee, M, Smith-Ryan, AE, Luedke, J, and Kerksick, CM. Fat-free mass index in sport: normative profiles and applications for collegiate athletes. J Strength Cond Res 38(9): 1687–1693, 2024—Recent concerns have been raised regarding the ethical considerations of conducting body composition assessments in sports. Specific apprehensions pertain to the inappropriate use of percent body fat and the limited application of the results to performance and recovery. Fat-free mass index (FFMI), a height-adjusted assessment of FFM, can serve as an alternative body composition metric to focus on in sports. Fat-free mass index provides valuable context regarding an optimal amount of FFM, accounting for skeletal frame and height while helping to qualify an athlete's FFM as low, moderate, or high. This review posits that shifting the focus of body composition measures to FFM can support more ideal targets across athletic seasons, careers, and the return to play after injury. In addition, a FFM focus may help change the perception of body composition assessment and how athletes perceive their current body because of the increased focus on the FFM compartment and the goal of maximizing tissue accrual, rather than focusing on fat loss. Fat-free mass index is calculated by dividing FFM (kg) by height (m 2 ) and can serve to normalize FFM, relative to height, and enable comparisons across athletes, sport types, and sex. Previous research has identified differences in FFMI across sex and among sport categories. Still, there is a need for more published data to develop optimal ranges for FFMI across sex, sports, and positions. As more data become available, FFMI has the potential to provide normative guidelines for optimal FFM development, performance, and injury risk reduction. The purpose of the current review was to summarize FFMI values across collegiate sport categories and competitive status to provide normative profiles, according to sex and sport type.

Abstract Jagim, AR, Luedke, J, Erickson, JL, Fields, JB, and Jones, MT. Validation of bioelectrical impedance devices for the determination of body fat percentage in firefighters. J Strength Cond Res 38(8): e448–e453, 2024—To cross-validate bioelectrical impedance devices for the determination of body fat percentage (BF%) in firefighters. Twenty-eight structural firefighters were evaluated (female, n = 2; male, n = 26 [mean ± SD ] age: 38.2 ± 8.3 years; height: 180.2 ± 7.5 cm; body mass: 86.7 ± 20.8 kg; body mass index: 25.8 ± 7.8 kg·m −2 ) using multifrequency bioelectrical impedance analysis (MFBIA) hand-to-foot device, and single-frequency BIA foot scale (F2FBIA), and a single-frequency handheld BIA device (HHBIA). Dual X-ray absorptiometry served as the criterion. Validity metrics were examined to establish each method's performance. Body fat % values produced by MFBIA ( r = 0.913), F2FBIA ( r = 0.695), and HHBIA ( r = 0.876) were strongly associated ( p < 0.001) with criterion BF% measures. However, MFBIA, F2FBIA, and HHBIA all significantly ( p < 0.001) underestimated BF% when compared with the criterion measure. Constant error ranged between 4.0 and 5.5% across all BIA devices. Despite strong associations between the BIA devices included in the current study and the criterion measure, all BIA devices underestimated BF%, which resulted in an overestimation of fat-free mass. In addition, proportional bias was observed in which BF% was overestimated at lower values and underestimated at higher values.