Bodybuilding is a competitive endeavor where a combination of muscle size, symmetry, “conditioning” (low body fat levels), and stage presentation are judged. Success in bodybuilding requires that competitors achieve their peak physique during the day of competition. To this end, competitors have been reported to employ various peaking interventions during the final days leading to competition. Commonly reported peaking strategies include altering exercise and nutritional regimens, including manipulation of macronutrient, water, and electrolyte intake, as well as consumption of various dietary supplements. The primary goals for these interventions are to maximize muscle glycogen content, minimize subcutaneous water, and reduce the risk abdominal bloating to bring about a more aesthetically pleasing physique. Unfortunately, there is a dearth of evidence to support the commonly reported practices employed by bodybuilders during peak week. Hence, the purpose of this article is to critically review the current literature as to the scientific support for pre-contest peaking protocols most commonly employed by bodybuilders and provide evidence-based recommendations as safe and effective strategies on the topic.

Progressive resistance training volume: effects on muscle thickness, mass, and strength adaptations in resistance-trained individuals. J Strength Cond Res 36(3): 600-607, 2022-This study investigated the effects of 12-SET, 18-SET, and 24-SET lowerbody weekly sets on muscle strength and mass accretion. Thirty-five resistance-trained individuals (one repetition maximum [1RM] squat: body mass ratio [1RM: BM] 5 2.09) were randomly divided into 12-SET: n 5 13, 18-SET: n 5 12, and 24-SET: n 5 10. Subjects underwent an 8-week resistance-training (RT) program consisting of 2 weekly sessions. Muscle strength (1RM), repetitions to failure (RTF) at 70% of 1RM, anterior thigh muscle thickness (MT), at the medial MT (MMT) and distal MT (DMT) points, as well as the sum of both sites (SMT), along with region of interest for fat-free mass (ROI-FFM) were measured at baseline and posttesting. For the 1RM, there was a main time effect (p # 0.0001). However, there was a strong trend toward significance (p 5 0.052) for group-by-time interaction, suggesting that 18-SET increased 1RM back squat to a greater extent compared with 24-SET (24-SET: 9.

The purpose of this investigation was to compare the effects of auto-regulatory exercise selection (AES) vs. fixed exercise selection (FES) on muscular adaptations in strength-trained individuals. Seventeen males (Mean ± SD; age = 24 ± 5.45 years; height = 180.3 ± 7.54cm, lean body mass [LBM] 66.44 ± 6.59kg; squat and bench press 1RM: body mass ratio 1.87, 1.38 respectively) were randomly assigned into either AES or FES. Both groups trained three times a week for 9 weeks. AES self-selected the exercises for each session, whereas FES was required to perform exercises in a fixed order. LBM was assessed via DEXA and maximum strength via 1RM testing, pre and post training intervention. Total volume load was significantly higher for AES than for FES (AES: 573,288kg ± 67,505, FES: 464,600 ± 95,595, p=0.0240). For LBM, there was a significant main time effect (p=0.009). However, confidence interval analysis (95%CIdiff) suggested that only AES significantly increased LBM (AES: 2.47%, ES: 0.35, 95% CIdiff [0.030kg: 3.197kg], FES: 1.37 %, ES: 0.21, 95% CIdiff [-0.500kg: 2.475kg]). There was a significant main time effect for maximum strength (p≤0.0001). However, 95% CIdiff suggested that only AES significantly improved Bench-press 1RM (AES: 6.48%, ES: 0.50, 95% CIdiff [0.312kg: 11.42kg; FES: 5.14%, ES: 0.43 95%CIdiff [-0.311kg: 11.42kg]. On the other hand for back squat 1RM similar responses were observed between groups, (AES: 9.55%, ES: 0.76 95% CIdiff [0.04kg: 28.37kg], FES: 11.54%, ES: 0.80, 95%CIdiff [1.8kg: 28.5kg]. Our findings, suggest AES may provide a small advantage in LBM and upper body maximal strength in strength-trained individuals.

This study investigated the effects of two different velocity-based training (VBT) regimens on muscular adaptations. Fifteen female college volleyball players were randomly assigned into either progressive velocity-based training (PVBT) or optimum training load (OTL). Both groups trained three times a week for seven weeks. PVBT performed a 4-week strength block (e.g., 0.55–0.70 m·s−1) followed by a 3-week power block (e.g., 0.85–1.0 m·s−1), whereas OTL performed training at ~0.85–0.9 m·s−1. 1RM and peak power output (PP) assessments on the back squat (BS), bench press (BP) and deadlift (DL) exercises were assessed pre and post training. There was a main time effect (p ≤ 0.05) for BS and BP 1RM, (PVBT: 19.6%, ES: 1.72; OTL: 18.3%, ES: 1.57) and (PVBT: 8.5%, ES: 0.58; OTL: 10.2%, ES: 0.72), respectively. OTL increased DL 1RM to a greater extent than PVBT (p ≤ 0.05), (OTL: 22.9%, ES: 1.49; PVBT: 10.9%, ES: 0.88). Lastly, there was a main time effect (p ≤ 0.05) for BS, BP and DL PP, (PVBT: 18.3%, ES: 0.86; OTL: 19.8%, ES: 0.79); (PVBT: 14.5%, ES: 0.81; OTL: 27.9%, ES: 1.68); (PVBT: 15.7%, ES: 1.32; OTL: 20.1%, ES: 1.77) respectively. Our data suggest that both VBT regimens are effective for improving muscular performance in college volleyball players during the offseason period.

Despite the lack of standardized terminology, building muscle and losing fat concomitantly has been referred to as body recomposition by practitioners. Although many suggest that this only occurs in untrained/novice and overweight/obese populations, there is a substantial amount of literature demonstrating this body recomposition phenomenon in resistance-trained individuals. Moreover, 2 key factors influencing these adaptations are progressive resistance training coupled with evidence-based nutritional strategies. This review examines some of the current literature demonstrating body recomposition in various trained populations, the aforementioned key factors, nontraining/nutrition variables (i.e., sleep, hormones), and potential limitations due to body composition assessments. In addition, this review points out the areas where more research is warranted.