Citations

Aerobic exercise and thermal stress instigate robust challenges to the immune system. Various attempts to modify or supplement the diet have been proposed to bolster the immune system responses. The purpose of this study was to identify the impact of yeast beta-glucan (Saccharomyces cerevisiae) supplementation on exercise-induced muscle damage and inflammation. Healthy, active men (29.6 ± 6.7 years, 178.1 ± 7.2 cm, 83.2 ± 11.2 kg, 49.6 ± 5.1 mL/kg/min, n = 16) and women (30.1 ± 8.9 years, 165.6 ± 4.1 cm, 66.7 ± 10.0 kg, 38.7 ± 5.8 mL/kg/min, n = 15) were randomly assigned in a double-blind and cross-over fashion to supplement for 13 days with either 250 mg/day of yeast beta-glucan (YBG) or a maltodextrin placebo (PLA). Participants arrived fasted and completed a bout of treadmill exercise at 55% peak aerobic capacity (VO2Peak) in a hot (37.2 ± 1.8 °C) and humid (45.2 ± 8.8%) environment. Prior to and 0, 2, and 72 h after completing exercise, changes in white blood cell counts, pro- and anti-inflammatory cytokines, markers of muscle damage, markers of muscle function, soreness, and profile of mood states (POMS) were assessed. In response to exercise and heat, both groups experienced significant increases in white blood cell counts, plasma creatine kinase and myoglobin, and soreness along with reductions in peak torque and total work with no between-group differences. Concentrations of serum pro-inflammatory cytokines in YBG were lower than PLA for macrophage inflammatory protein 1β (MIP-1β) (p = 0.044) and tended to be lower for interleukin 8 (IL-8) (p = 0.079), monocyte chemoattractment protein 1 (MCP-1) (p = 0.095), and tumor necrosis factor α (TNF-α) (p = 0.085). Paired samples t-tests using delta values between baseline and 72 h post-exercise revealed significant differences between groups for IL-8 (p = 0.044, 95% Confidence Interval (CI): (0.013, 0.938, d = −0.34), MCP-1 (p = 0.038, 95% CI: 0.087, 2.942, d = −0.33), and MIP-1β (p = 0.010, 95% CI: 0.13, 0.85, d = −0.33). POMS outcomes changed across time with anger scores in PLA exhibiting a sharper decline than YBG (p = 0.04). Vigor scores (p = 0.04) in YBG remained stable while scores in PLA were significantly reduced 72 h after exercise. In conclusion, a 13-day prophylactic period of supplementation with 250 mg of yeast-derived beta-glucans invoked favorable changes in cytokine markers of inflammation after completing a prolonged bout of heated treadmill exercise.

Abstract Harty, PS, Zabriskie, HA, Stecker, RA, Currier, BS, Moon, JM, Richmond, SR, Jagim, AR, and Kerksick, CM. Position-specific body composition values in female collegiate rugby union athletes. J Strength Cond Res 35(11): 3158–3163, 2021—Rugby union is a full-contact, intermittent team sport. Anthropometric characteristics of rugby union athletes have been shown to influence suitability for a given position and affect performance. However, little anthropometric data exist in female rugby union athletes. Thus, the purpose of this study was to report position-specific anthropometric, body composition, and bone density values in female collegiate rugby union athletes and to identify between-position differences in these variables. This investigation was a cross-sectional study involving 101 female collegiate rugby union athletes, categorized as forwards and backs as well as by position (props, hookers, locks, flankers, number 8 forwards, halfback, fly-half, centers, wings, and fullbacks). Anthropometric characteristics of all athletes were measured, and body composition was assessed via dual-energy x-ray absorptiometry. Outcome variables included age, height, body mass, BMI, body fat percentage, fat mass (FM), FM index, fat-free mass (FFM), FFM index, lean soft tissue, bone mineral content, bone mineral area, and bone mineral density. Anthropometric and body composition differences between forwards and backs were identified via independent t -tests and Mann-Whitney U tests, depending on normality of the variable. Between-position differences were assessed using one-way analysis of variances (ANOVAs) with Tukey post-hoc comparisons or Welch's ANOVA with Dunnett's T3 post-hoc test. Significant differences ( p < 0.014) were identified between forwards and backs for every anthropometric variable, with forwards displaying greater height (167.7 ± 7.2 cm), body mass (81.5 ± 15.1 kg), and body fat percentage (28.2 ± 6.1%) relative to backs (164.5 ± 5.1 cm; 64.5 ± 7.7 kg; 21.9 ± 3.7%). Likewise, significant differences were identified for every anthropometric variable between several positions ( p < 0.01). Significant ( p < 0.05) interposition differences were identified within the subgroup of forwards, but not within the subgroup of backs. The present investigation is the first to report position-specific anthropometric and body composition data in female collegiate rugby union athletes. The results of this study can be used by rugby union coaches for recruiting and personnel decisions, to determine a player's suitability for a given position, and to further inform training and nutritional interventions in this population.

Abstract Currier, BS, Harty, PS, Zabriskie, HA, Stecker, RA, Moon, JM, Jagim, AR, and Kerksick, CM. Fat-free mass index in a diverse sample of male collegiate athletes. J Strength Cond Res 33(6): 1474–1479, 2019—Fat-free mass index (FFMI) is a body composition metric that has been used to assess relative muscularity in athletes. Fat-free mass index is calculated by dividing FFM by height squared, although further height corrections through linear regression may be needed in taller individuals. This study reported height-adjusted FFMI (FFMI Adj ) data in 209 male collegiate athletes from 10 sports (baseball, cross country, football, golf, ice hockey, weightlifting, rugby, swimming, track and field, and water polo) and the FFMI Adj natural upper limit for sports with sufficient sample size. The body composition of all subjects (mean ± SD ; age: 20.7 ± 1.9 years, height: 182.9 ± 6.7 cm, body mass: 90.8 ± 16.8 kg, and percent body fat: 15.6 ± 5.3) was measured using dual-energy x-ray absorptiometry. Linear regression was used to adjust for height, and the FFMI Adj natural upper limit was determined by calculating the 97.5th percentile of all values. One-way analyses of variance with Games-Howell post hoc comparisons were used to determine between-sport differences. A paired-samples t -test revealed a significant difference ( p < 0.001) between unadjusted and adjusted mean FFMI values. The overall mean FFMI Adj was 22.8 ± 2.8 kg·m −2 . Significant between-sport differences ( p < 0.001) in FFMI Adj were identified. Average FFMI Adj was highest in football athletes (24.28 ± 2.39 kg·m −2 ) and lowest in water polo athletes (20.68 ± 3.56 kg·m −2 ). The FFMI Adj upper limit was calculated for all athletes (28.32 kg·m −2 ), rugby (29.1 kg·m −2 ), and baseball (25.5 kg·m −2 ). This study reported FFMI Adj values in a diverse cohort of male collegiate athletes, providing data for the first time in several sports. These values can be used to guide nutritional and exercise interventions, predict athletic performance, and provide coaches with standardized information regarding the potential for further FFM accretion in male athletes.

Little data is available regarding the energy and nutritional status of female collegiate team sport athletes. Twenty female NCAA Division II lacrosse athletes (mean ± SD: 20.4 ± 1.8 years; 68.8 ± 8.9 kg; 168.4 ± 6.6 cm; 27.9 ± 3% body fat) recorded dietary intake and wore a physical activity monitor over four consecutive days at five different time points (20 days total) during one academic year. Body composition, bone health, and resting metabolic rate were assessed in conjunction with wearing the monitor during off-season, pre-season, and season-play. Body fat percentage decreased slightly during the course of this study (p = 0.037). Total daily energy expenditure (TDEE) (p < 0.001) and activity energy expenditure (AEE) (p = 0.001) energy were found to change significantly over the course of the year, with pre-season training resulting in the highest energy expenditures (TDEE: 2789 ± 391 kcal/day; AEE: 1001 ± 267 kcal/day). Caloric (2124 ± 448 kcal/day), carbohydrate (3.6 ± 1.1 g/kg), and protein (1.2 ± 0.3 g/kg) intake did not change over the course of the year (p > 0.05). Athletes self-reported a moderate negative energy balance (366–719 kcal/day) and low energy availability (22.9–30.4 kcal/kg FFM) at each measurement period throughout the study. Reported caloric and macronutrient intake was low given the recorded energy expenditure and macronutrient intake recommendations for athletes. Athletic support staff should provide athletes with appropriate fueling strategies, particularly during pre-season training, to adequately meet energy demands.

Abstract Jagim, AR, Camic, CL, Askow, A, Luedke, J, Erickson, J, Kerksick, CM, Jones, MT, and Oliver, JM. Sex differences in resting metabolic rate among athletes. J Strength Cond Res 33(11): 3008–3014, 2019—The purpose of this study was to compare differences in resting metabolic rate (RMR) between sexes in Division III National Collegiate Athletic Association (NCAA) collegiate athletes and to identify predictors of RMR. Sixty-eight male (M) (age: 20.1 ± 1.5 years; height: 181.8 ± 5.9 cm; body mass (BM): 93.7 ± 16.3 kg; and body fat%: 16.3 ± 8.6%) and 48 female (F) athletes (age: 19.4 ± 1.3 years; height: 166.5 ± 6.0 cm; BM: 63.4 ± 12.7 kg; and body fat%: 21.5 ± 6.3%) participated in a single day of testing, which included determination of RMR using indirect calorimetry and air displacement plethysmography to measure fat mass and fat-free mass (FFM). An independent-samples t -test was used to compare differences in body composition and RMR between sexes, and regression analysis was used to identify predictors of RMR. Men had a significantly higher absolute RMR (M: 2,481 ± 209 vs. F: 1,553 ± 193 kcals·d −1 ; p < 0.001), but when adjusted for BM (M: 25.6 ± 8.3 vs. F: 25.9 ± 2.5 kcals·kg −1 BM per day; p = 0.82) and FFM (M: 31.1 ± 10.6 vs. F: 33.6 ± 3.8 kcals·kg −1 FFM per day; p = 0.12), these differences became nonsignificant. Regression analysis indicated that BM in both men (β = 0.73) and women (β = 0.88) was the strongest predictor of RMR. The results of the current study indicate minimal differences in RMR between sexes among athletic populations when adjusted for BM and FFM. In the current group of athletes, BM seems to account for the largest variability in RMR.