Purpose: To examine rest redistribution (RR) effects on back squat kinetics and kinematics in resistance-trained women. Methods: Twelve women from strength and college sports (5.0 [2.2] y training history) participated in the randomized crossover design study with 72 hours between sessions (3 total). Participants completed 4 sets of 10 repetitions using traditional sets (120-s interset rest) and RR (30-s intraset rest in the middle of each set; 90-s interset rest) with 70% of their 1-repetition maximum. Kinetics and kinematics were sampled via force plate and 4 linear position transducers. The greatest value of repetitions 1 to 3 (peak repetition) was used to calculate percentage loss, [(repetition 10–peak repetition)/(peak repetition) × 100], and maintenance, {100–[(set mean–peak repetition)/(peak repetition)] × 100}, of velocity and power for each set. Repeated-measures analysis of variance was used for analyses (P < .05). Results: Mean and peak force did not differ between conditions. A condition × repetition interaction existed for peak power (P = .049) but not for peak velocity (P = .110). Peak power was greater in repetitions 7 to 9 (P < .05; d = 1.12–1.27) during RR. The percentage loss of velocity (95% confidence interval, –0.22% to –7.22%; P = .039) and power (95% confidence interval, –1.53% to –7.87%; P = .008) were reduced in RR. Mean velocity maintenance of sets 3 (P = .036; d = 1.90) and 4 (P = .015; d = 2.30) and mean power maintenance of set 4 (P = .006; d = 2.65) were greater in RR. Conclusion: By redistributing a portion of long interset rest into the middle of a set, velocity and power were better maintained. Therefore, redistributing rest may be beneficial for reducing fatigue in resistance-trained women.

The purpose of this study was to assess the body composition of male and female basketball athletes (n = 323) across season, year, and sport-position using air displacement plethysmography. An independent sample t-test assessed sport-position differences. An analysis of variance was used to assess within-subjects across season (pre-season, in-season, and off-season), and academic year (freshman, sophomore, and junior). For both men and women basketball (MBB, WBB) athletes, guards had the lowest body fat, fat mass, fat free mass, and body mass. No seasonal differences were observed in MBB, but following in-season play for WBB, a reduction of (p = 0.03) in fat free mass (FFM) was observed. Across years, MBB showed an increase in FFM from freshman to sophomore year, yet remained unchanged through junior year. For WBB across years, no differences occurred for body mass (BM), body fat (BF%), and fat mass (FM), yet FFM increased from sophomore to junior year (p = 0.009). Sport-position differences exist in MBB and WBB: Guards were found to be smaller and leaner than forwards. Due to the importance of body composition (BC) on athletic performance, along with seasonal and longitudinal shifts in BC, strength and conditioning practitioners should periodically assess athletes BC to ensure preservation of FFM. Training and nutrition programming can then be adjusted in response to changes in BC.

Merrigan, JJ, Tufano, JJ, Fields, JB, Oliver, JM, and Jones, MT. Rest redistribution does not alter hormone responses in resistance-trained women. J Strength Cond Res 34(7): 1867–1874, 2020—The purpose was to examine acute effects of rest redistribution (RR) on perceptual, metabolic, and hormonal responses during back squats. Twelve resistance-trained women (training age 5 ± 2 years; one repetition maximum [1-RM] per body mass, 1.6 ± 0.2) performed traditional (TS, 4 sets of 10 repetitions with 120 seconds interset rest) and RR sets (4 sets of two 5 repetition clusters with 30-second intraset rest and 90-second interset rest) in counterbalanced order, separated by 72 hours. Both conditions were performed at 70% 1RM with 360 seconds of total rest. Ratings of perceived exertion (RPE) were taken after each set. Blood was sampled at baseline, after each set, and at 5, 15, 30, and 60 minutes, as well as 24 and 48 hours after training. Alpha level was p ≤ 0.05. The RPE progressively increased throughout both conditions (p = 0.002) with a greater overall mean for TS (5.81 ± 0.14) than RR (4.71 ± 0.14; p = 0.003). Lactate increased above baseline and remained elevated through 15 minutes post in both conditions (4.00 ± 0.76; p = 0.001), with greater lactate levels for TS (6.33 ± 0.47) than RR (4.71 ± 0.53; p < 0.001). Total testosterone was elevated after set 2 (0.125 ± 0.02; p = 0.011), but no other time point, while free testosterone remained unchanged. Growth hormone continually rose from baseline to set 3 and returned to baseline by 60 minutes post (20.58 ± 3.19). Cortisol and creatine kinase did not change over time. No condition × time interactions existed for any hormone (p > 0.05). Use of rest redistribution resulted in lower perceived effort and lactate responses. Yet, hormone responses during rest redistribution were no different from TS.

Fields, JB, Merrigan, JJ, White, JB, and Jones, MT. Body composition variables by sport and sport-position in elite collegiate athletes. J Strength Cond Res 32(11): 3153–3159, 2018—To assess body composition measures by sport and sport-position. Elite collegiate athletes participated (n = 475): men's and women's soccer (MSOC, n = 67; WSOC, n = 110); men's and women's swimming (MSWIM, n = 26; WSWIM, n = 22); men's and women's track and field (MTF, n = 29; WTF, n = 24); women's lacrosse and volleyball (WLAX, n = 84; WVB, n = 73); and baseball (BASE, n = 40). One-way analysis of variances assessed differences across sport and sport-position. Post hoc analysis was Tukey honestly significant difference (p ≤ 0.05). For men, BASE and MSWIM had the highest body fat percentage (BF%) (BASE: 16.3 ± 5.2%; MSWIM: 14.2 ± 3.5%). MSOC (11.5 ± 5.3%, 0.13 ± 0.72 kg) and MTF (9.8 ± 5.1%, 0.11 ± 0.08 kg) had the lowest BF% and fat mass (FM)-to-fat-free mass (FFM) ratio (FM:FFM). Fat mass did not differ between MSOC (9.1 ± 4.9 kg), MTF (7.7 ± 5.9 kg), and MSWIM (11.1 ± 3.1 kg). Fat mass for MSOC and MTF was lower than BASE (14.1 ± 5.2). For women, WVB displayed the highest BF% (25.4 ± 5.1%), FM (18.5 ± 5.2 kg), FFM (53.3 ± 5.1 kg), and body mass (BM) (71.8 ± 8.4 kg), but did not differ from WSWIM in BF%, FM, FFM, and BM. WTF had the lowest BF% (12.9 ± 4.0%), FM (7.5 ± 2.5 kg), BM (58.2 ± 4.4 kg), and FM:FFM (0.15 ± 0.05 kg). VB had the highest FFM (53.3 ± 5.1 kg). Body composition differences were observed between sport-positions (p < 0.01). Body composition differed across sport and sport-position, which may be attributed to sport-specific physiological demands.

Sport nutrition knowledge has been shown to influence dietary habits of athletes. The purpose of the current study was to examine relationships between sport nutrition knowledge and body composition and examine potential predictors of body weight goals in collegiate athletes. Participants included National Collegiate Athletic Association Division III women (n = 42, height: 169.9 ± 6.9 cm; body mass: 67.1 ± 8.6 kg; fat-free mass: 51.3 ± 6.6 kg; body fat per cent: 24.2 ± 5.3%) and men (n = 25, height: 180.8 ± 7.2 cm; body mass: 89.2 ± 20.5 kg; fat-free mass: 75.9 ± 12.2 kg; body fat per cent: 13.5 ± 8.9%) athletes. Body composition was assessed via air displacement plethysmography. Athletes completed a validated questionnaire designed to assess sport nutrition knowledge and were asked questions about their perceived dietary energy and macronutrient requirements, as well as their body weight goal (i.e., lose, maintain, gain weight). Athletes answered 47.98 ± 11.29% of questions correctly on the nutrition questionnaire with no differences observed between sexes (men: 49.52 ± 11.76% vs. women: 47.03 ± 11.04%; p = 0.40). An inverse relationship between sport nutrition knowledge scores and body fat percentage (BF%) (r = –0.330; p = 0.008), and fat mass (r = –.268; p = 0.032) was observed for all athletes. Fat mass (β = 0.224), BF% (β = 0.217), and body mass index (BMI) (β = 0.421) were all significant (p < 0.05) predictors of body weight goal in women. All athletes significantly (p < 0.001) underestimated daily energy (–1,360 ± 610.2 kcal/day), carbohydrate (–301.6 ± 149.2 grams/day [g/day]), and fat (–41.4 ± 34.5 g/day) requirements. Division III collegiate athletes have a low level of sport nutrition knowledge, which was associated with a higher BF%. Women athletes with a higher body weight, BF% and BMI were more likely to select weight loss as a body weight goal. Athletes also significantly underestimated their energy and carbohydrate requirements based upon the demands of their sport, independent of sex.