Changes in hormonal profiles during competition preparation in physique athletes.

PURPOSE: Physique athletes engage in rigorous competition preparation involving intense energy restriction and physical training to enhance muscle definition. This study investigates hormonal changes and their physiological and performance impacts during such preparation. METHODS: Participants included female (10 competing (COMP) and 10 non-dieting controls (CTRL)) and male (13 COMP and 10 CTRL) physique athletes. COMP participants were tested 23 weeks before (PRE), one week before (MID), and 23 weeks after the competition (POST). Non-dieting CTRL participants were tested at similar intervals. Measurements included body composition (DXA), muscle cross-sectional area (ultrasound), energy availability (EA) derived by subtracting exercise energy expenditure (EEE) from energy intake (EI) and dividing by fat-free mass (FFM), muscle strength, and various serum hormone concentrations (ACTH, cortisol, estradiol, FSH, IGF-1, IGFBP-3, insulin, and free and total testosterone and SHBG). RESULTS: During the diet, EA (p < 0.001), IGF-1 (p < 0.001), IGFBP-3 (p < 0.01), and absolute muscle strength (p < 0.01-0.001) decreased significantly in both sexes in COMP. Decreases in IGF-1 were also associated with higher loss in FFM. In males, testosterone (p < 0.01) and free testosterone (p < 0.05) decreased, while SHBG (p < 0.001) and cortisol (p < 0.05) increased. Insulin decreased significantly only in males (p < 0.001). Mood disturbances, particularly increased fatigue in males (p < 0.05), highlighted the psychological strain of competition preparation. All these changes were restored by increased EA during the post-competition recovery period. CONCLUSION: Significant reductions in IGF-1 and IGFBP-3 during competition preparation may serve as biomarkers for monitoring physiological stress. This study offers valuable insights into hormonal changes, muscle strength, and mood state during energy-restricted intense training.

A Survey of Resistance Training Practices Among Physique Competitors During Peak Week.

ABSTRACT: Homer, KA, Cross, MR, and Helms, ER. A survey of resistance training practices among physique competitors during peak week. J Strength Cond Res XX(X): 000-000, 2024-Physique athletes are ranked by their on-stage presentation of muscle size, proportionality, and leanness. To acutely maximize muscle size, competitors manipulate resistance training (RT) variables in the days before the contest, commonly referred to as peak week (PW). Resistance training manipulations during PW may act synergistically with nutrition strategies such as carbohydrate loading. However, because little information exists on changes made to RT during PW, the purpose of this research was to determine the current practices of physique athletes and whether competitor characteristics were predictive of the RT variables manipulated. A total of 104 responses to the RT section of a survey on PW nutrition and training were analyzed through a series of multiple logistic regression models to examine the relationship between RT manipulations and competitor characteristics. Furthermore, to determine the magnitude of differences between PW and the week before PW (WBPW) for these variables, a McNemar-Bowker test, paired t-tests, and Wilcoxon signed-rank tests were conducted for nominal, continuous, and discrete outcomes, respectively. For all statistical analyses, p <0.05 was deemed significant. Competitors generally adjusted RT in a variety of ways, where proximity-to-failure was the most frequently manipulated and training frequency was the least; however, no competitor characteristic predicted any of the RT variables manipulated. Within those who manipulated RT variables during PW, frequency, volume, and intensity decreased while repetition ranges of compound exercises increased, empirically confirming that competitors seek to reduce training stress during PW. Such findings can be incorporated in future experimental designs examining the efficacy of peaking strategies to enhance the generalizability of results.

The effect of a bodybuilding carbohydrate-loading protocol on anthropometry: Preliminary findings from a randomized crossover trial.

To acutely enhance muscle size and definition, carbohydrate (CHO)-loading protocols are commonly implemented by bodybuilders in the week before competition. This study sought to evaluate the effects of a bodybuilding CHO-loading protocol on anthropometry. Four dieting males engaging in resistance training (RT) with very low body fat participated in this randomized crossover trial. Each experimental period consisted of data collection on days one, four, and five corresponding to baseline, postdepletion, and postloading phases, respectively. During depletion, a standardized RT regimen and diet was followed. This diet was maintained on day 4 with the addition of placebo (PLA) or CHO drinks which contained 9 g/kg BM CHO for postloading data collection on day 5. Body mass (BM), skinfold thickness (SF), and ultrasound muscle thickness (MT) were obtained with descriptive data at both group and individual level calculated. From baseline, BM, SF, and MT mostly decreased in both conditions following depletion. All outcomes then increased from postdepletion following CHO-loading (BM: +0.8%, SF: +1.1%, MT: +2.9%) but not with PLA. Comparing to baseline, postloading changes were greater with CHO (BM: +0.3%, SF: -2.3%, MT: +2.1%) than PLA (BM: -0.9%, SF: -0.5%, MT: -0.8%). Individual differences in response to each phase were also observed. Group level changes seemingly favor CHO-loading; however, it is difficult to judge whether these changes are practically meaningful as they may not be large enough to exceed measurement error and daily biological fluctuations. Before implementation, coaches and competitors should consider individualizing protocols through precompetition testing and visually assessing changes in physique.

An examination of the associations between nutritional peaking strategies in physique sport and competitor characteristics.

BACKGROUND: Physique athletes are subjectively judged on their on-stage esthetic per their competition division criteria. To succeed, competitors look to acutely enhance their appearance by manipulating nutritional variables in the days leading up to competition, commonly referred to as peak week (PW). Despite their documented wide adoption, PW strategies lack experimental evidence. Further, the relationship between the specific strategies and the characteristics of the competitors who implement them are unknown. The aim of this research was to examine the effect of competitor characteristics on the specific nutritional peaking strategies implemented, the length of these strategies, and the range of daily carbohydrate (CHO) intakes during these strategies. METHODS: A 58-item survey was developed to gather information on peak week nutrition and training practices of physique athletes. A total of 160 respondents above the age of 18 who had competed in the last 5 years completed the nutrition section. The topics analyzed for this paper included competitor demographics, peaking strategies utilized, and PW CHO intakes. Competitor demographics are presented with the use of descriptive statistics. Associations between competitor demographics and peaking strategies implemented, peaking strategy length, and daily CHO intake ranges were assessed using multiple logistic regression, multiple ordinal logistic regression, and linear mixed models, respectively. RESULTS: From the sampled population, ages 24-39 years (71.2%), male (68.8%), natural (65%), and amateur (90%) were the most common characteristics from their respective categories, while mean competition preparation length was 20.35 ± 8.03 weeks (Males: 19.77 ± 7.56 weeks, Females: 21.62 ± 8.93 weeks), competition preparation body mass loss was 11.5 ± 5.56 kg (M: 12.7 ± 5.76 kg, F: 7.16 ± 3.99 kg), and competition body mass was 72.09 ± 15.74 kg (M: 80.15 ± 11.33 kg, F: 54.34 ± 7.16 kg). For males, the highest and lowest daily CHO intake during PW were 489.63 ± 224.03 g (6.22 ± 2.93 g/kg body mass) and 148.64 ± 152.01 g (1.94 ± 2.17 g/kg), respectively, while for females these values were 266.73 ± 131.23 g (5.06 ± 2.67 g/kg) and 94.42 ± 80.72 g (1.81 ± 1.57 g/kg), respectively. CHO back loading (45%) and water loading (40.6%) were the most popular peaking strategies, while the most prevalent peaking strategy length was 7 days (27.2%). None of the competitor characteristics predicted the use of CHO-based peaking strategies nor peaking strategy length. For non-CHO-based strategies, drug-enhanced competitors were more likely to restrict water than non-drug enhanced, while males and professional competitors had greater odds of loading sodium than females and amateurs, respectively. Finally, when comparing the disparity in highest and lowest CHO intakes during peak week, sex was the only significant factor. CONCLUSIONS: The results of this survey provide further information on the nutritional peaking strategies implemented by competitors. Certain characteristics were identified as predictors of sodium loading and water restriction, and the range of daily PW CHO intake. Contrastingly, no associations were found for CHO-based peaking strategies or peaking strategy length. While our analyses may be underpowered, and thus results should be interpreted with caution, it appears the nutritional peaking strategies implemented by physique competitors are seemingly complex and highly individual.

Menstrual cycle patterns and their relationship with measures of well-being and perceived performance metrics in competitive and recreational resistance-trained athletes.

BACKGROUND: There is mixed evidence on how the menstrual cycle (MC) affects sports performance, with many studies showing variations in performance during different phases of the MC, while other evidence shows that the MC's effects on performance may be trivial. Therefore, this exploratory longitudinal monitoring study was designed to investigate MC characteristics and symptoms in a resistance-trained (RT) population to look for associations between measures of well-being and perceived performance metrics across the MC. METHODS: RT females reported their workout habits, perceived performance metrics, and measures of well-being while tracking their MC with detailed methods via daily check-ins in an app. RESULTS: Most MC characteristics and symptoms in the present RT population aligned with previous research on the general population. However, the frequency of irregular cycles was higher than in previous research on the general population. The amount of individual variation and within-subject cycle-to-cycle variation in MC characteristics and MC symptoms was also high. All measures of well-being were significantly associated with specific days of the MC, demonstrating a change in well-being based on the timing of the MC. Several perceived performance metrics were significantly associated with changes across the MC, while others were not. CONCLUSIONS: Overall, with the current evidence as it stands, a highly individualized approach should be taken for any training or performance considerations surrounding the MC due to the high levels of individual variation.

N of 1: Optimizing Methodology for the Detection of Individual Response Variation in Resistance Training.

Most resistance training research focuses on inference from average intervention effects from observed group-level change scores (i.e., mean change of group A vs group B). However, many practitioners are more interested in training responses (i.e., causal effects of an intervention) on the individual level (i.e., causal effect of intervention A vs intervention B for individual X). To properly examine individual response variation, multiple confounding sources of variation (e.g., random sampling variability, measurement error, biological variability) must be addressed. Novel study designs where participants complete both interventions and at least one intervention twice can be leveraged to account for these sources of variation (i.e., n of 1 trials). Specifically, the appropriate statistical methods can separate variability into the signal (i.e., participant-by-training interaction) versus the noise (i.e., within-participant variance). This distinction can allow researchers to detect evidence of individual response variation. If evidence of individual response variation exists, researchers can explore predictors of the more favorable intervention, potentially improving exercise prescription. This review outlines the methodology necessary to explore individual response variation to resistance training, predict favorable interventions, and the limitations thereof.

The Importance of Recovery in Resistance Training Microcycle Construction.

Systemic resistance training aims to enhance performance by balancing stress, fatigue and recovery. While fatigue is expected, insufficient recovery may temporarily impair performance. The aim of this review was to examine evidence regarding manipulation of resistance training variables on subsequent effects on recovery and performance. PubMed, Medline, SPORTDiscus, Scopus and CINAHL were searched. Only studies that investigated recovery between resistance training sessions were selected, with a total of 24 articles included for review. Training to failure may lengthen recovery times, potentially impairing performance; however, it may be suitable if implemented strategically ensuring adequate recovery between sessions of similar exercises or muscle groups. Higher volumes may increase recovery demands, especially when paired with training to failure, however, with wide variation in individual responses, it is suggested to start with lower volume, monitor recovery, and gradually increase training volume if appropriate. Exercises emphasising the lower body, multi-joint movements, greater muscle recruitment, eccentric contractions, and/or the lengthened position may require longer recovery times. Adjusting volume and frequency of these exercises can affect recovery demands depending on the goals and training logistics. Daily undulating programming may maximise performance on priority sessions while maintaining purposeful and productive easy days. For example, active recovery in the form of training opposing muscle groups, light aerobic cardio, or low-volume power-type training may improve recovery and potentially elicit a post activation potentiation priming effect compared to passive recovery. However, it is possible that training cessation may be adequate for allowing sufficient recovery prior to sessions of importance.

Dietary supplementation habits in international natural bodybuilders during pre-competition.

Bodybuilding is characterized by high-rates of sport supplementation. This is the first study to compare the supplementation patterns of winners (WB) and non-winners (NWB) among international natural bodybuilders during contest preparation. Fifty-six natural bodybuilders (5 women) (age = 28.85 ± 8.03 years; final body mass = 71.50 ± 10.28 kg), 19 WB (athletes who had achieved victory in an official natural bodybuilding championship at least once) and 37 NWB (athletes who never achieved victory), from 18 countries (55.36% from Spain) responded to this cross-sectional online survey related to their nutritional habits, strategies and supplementation practices. WB were significantly older (p = 0.024), completed more competitive seasons (p = 0.027) and participated in more competitions in the last contest year (p = 0.011). There were no significant differences between WB and NWB for years training for bodybuilding (p = 0.055), weeks of dieting for competition (p = 0.392), and body weight at the start (p = 0.553) and end (p = 0.330) of the season. Beverage and supplement consumption, purchasing patterns, and information sources did not differ between groups (p > 0.05). In conclusion, natural bodybuilding WB tended to be older and had more competitive experience, but shared similar supplementation protocols to NWB. Athletes' supplementation patterns were influenced by different sources of information. However, these natural bodybuilders mainly purchased their supplements through the internet without guidance from a coach or dietitian.

Modeling the repetitions-in-reserve-velocity relationship: a valid method for resistance training monitoring and prescription, and fatigue management.

Establishing a relationship between repetitions left in reserve and the mean absolute velocity (RIR-velocity relationship) during resistance training (RT) could allow for objective monitoring, prescription, and real-time adjustment of the training load and set-volume. Therefore, we examined the goodness of fit and prediction accuracy of general and individual RIR-velocity relationships in the free-weight back squat exercise. The effects of sex, training status and history, as well as personality traits, on the goodness of fit and the accuracy of these relationships were also investigated. Forty-six resistance-trained people (15 females and 31 males) performed a one-repetition maximum (1RM) test, and two repetitions to failure (RTF) tests 72 h apart. We found greater goodness of fit of individual RIR-velocity relationships compared to general RIR-velocity relationships. Individual, but not general RIR-velocity relationships established in the first testing session yielded acceptable prediction accuracy of RIR (mean error <2 repetitions) in the subsequent testing session, regardless of the load used. Similar results were obtained when both general and individual RIR-velocity relationships were averaged across the loads, suggesting that a single RIR-velocity relationship covering a range of loads can be used instead of traditional RT methods, potentially allowing for better fatigue management and more efficient adaptation.

Similar muscle hypertrophy following eight weeks of resistance training to momentary muscular failure or with repetitions-in-reserve in resistance-trained individuals.

This study examined the influence of resistance training (RT) proximity-to-failure, determined by repetitions-in-reserve (RIR), on quadriceps hypertrophy and neuromuscular fatigue. Resistance-trained males (n = 12) and females (n = 6) completed an 8-week intervention involving two RT sessions per week. Lower limbs were randomised to perform the leg press and leg extension exercises either to i) momentary muscular failure (FAIL), or ii) a perceived 2-RIR and 1-RIR, respectively (RIR). Muscle thickness of the quadriceps [rectus femoris (RF) and vastus lateralis (VL)] and acute neuromuscular fatigue (i.e., repetition and lifting velocity loss) were assessed. Data was analysed with Bayesian linear mixed-effect models. Increases in quadriceps thickness (average of RF and VL) from pre- to post-intervention were similar for FAIL [0.181 cm (HDI: 0.119 to 0.243)] and RIR [0.182 cm (HDI: 0.115 to 0.247)]. Between-protocol differences in RF thickness slightly favoured RIR [-0.036 cm (HDI: -0.113 to 0.047)], but VL thickness slightly favoured FAIL [0.033 cm (HDI: -0.046 to 0.116)]. Mean volume was similar across the RT intervention between FAIL and RIR. Lifting velocity and repetition loss were consistently greater for FAIL versus RIR, with the magnitude of difference influenced by the exercise and the stage of the RT intervention.

Terminating RT sets with a close proximity-to-failure (e.g., 1- to 2-RIR) can be sufficient to promote similar hypertrophy of the quadriceps as reaching momentary muscular failure in resistance-trained individuals over eight weeks, but the overall influence of proximity-to-failure on muscle-specific hypertrophy may also depend on other factors (e.g., exercise selection, order, and subsequent musculature targeted).Due to high repetition loss (from the first to final set) when sets are terminated at momentary muscular failure, performing RT with 1- to 2-RIR allows for similar volume load and repetition volume accumulation as reaching momentary muscular failure across eight weeks, possibly influencing the overall RT stimulus achieved.Performing RT to momentary muscular failure consistently induces higher levels of acute neuromuscular fatigue versus RT performed with 1- to 2-RIR; however, improved fatigue resistance overtime may attenuate acute neuromuscular fatigue and subsequent repetition loss (but may depend on the exercise performed).

Peak Week Carbohydrate Manipulation Practices in Physique Athletes: A Narrative Review.

BACKGROUND: Physique athletes are ranked by a panel of judges against the judging criteria of the corresponding division. To enhance on-stage presentation and performance, competitors in certain categories (i.e. bodybuilding and classic physique) achieve extreme muscle size and definition aided by implementing acute "peaking protocols" in the days before competition. Such practices can involve manipulating nutrition and training variables to increase intramuscular glycogen and water while minimising the thickness of the subcutaneous layer. Carbohydrate manipulation is a prevalent strategy utilised to plausibly induce muscle glycogen supercompensation and subsequently increase muscle size. The relationship between carbohydrate intake and muscle glycogen saturation was first examined in endurance event performance and similar strategies have been adopted by physique athletes despite the distinct physiological dissimilarities and aims between the sports. OBJECTIVES: The aim of this narrative review is to (1) critically examine and appraise the existing scientific literature relating to carbohydrate manipulation practices in physique athletes prior to competition; (2) identify research gaps and provide direction for future studies; and (3) provide broad practical applications based on the findings and physiological reasoning for coaches and competitors. FINDINGS: The findings of this review indicate that carbohydrate manipulation practices are prevalent amongst physique athletes despite a paucity of experimental evidence demonstrating the efficacy of such strategies on physique performance. Competitors have also been observed to manipulate water and electrolytes in conjunction with carbohydrate predicated on speculative physiological mechanisms which may be detrimental for performance. CONCLUSIONS: Further experimental evidence which closely replicates the nutritional and training practices of physique athletes during peak week is required to make conclusions on the efficacy of carbohydrate manipulation strategies. Quasi-experimental designs may be a feasible alternative to randomised controlled trials to examine such strategies due to the difficulty in recruiting the population of interest. Finally, we recommend that coaches and competitors manipulate as few variables as possible, and experiment with different magnitudes of carbohydrate loads in advance of competition if implementing a peaking strategy.

Accuracy of Intraset Repetitions-in-Reserve Predictions During the Bench Press Exercise in Resistance-Trained Male and Female Subjects.

ABSTRACT: Refalo, MC, Remmert, JF, Pelland, JC, Robinson, ZP, Zourdos, MC, Hamilton, DL, Fyfe, JJ, and Helms, ER. Accuracy of intraset repetitions-in-reserve predictions during the bench press exercise in resistance-trained male and female subjects. J Strength Cond Res 38(3): e78-e85, 2024-This study assessed the accuracy of intraset repetitions-in-reserve (RIR) predictions to provide evidence for the efficacy of RIR prescription as a set termination method to inform proximity to failure during resistance training (RT). Twenty-four resistance trained male ( n = 12) and female ( n = 12) subjects completed 2 experimental sessions involving 2 sets performed to momentary muscular failure (barbell bench press exercise) with 75% of 1 repetition maximum (1RM), whereby subjects verbally indicated when they perceived to had reached either 1 RIR or 3 RIR. The difference between the predicted RIR and the actual RIR was defined as the "RIR accuracy" and was quantified as both raw (i.e., direction of error) and absolute (i.e., magnitude of error) values. High raw and absolute mean RIR accuracy (-0.17 ± 1.00 and 0.65 ± 0.78 repetitions, respectively) for 1-RIR and 3-RIR predictions were observed (including all sets and sessions completed). We identified statistical equivalence (equivalence range of ±1 repetition, thus no level of statistical significance was set) in raw and absolute RIR accuracy between (a) 1-RIR and 3-RIR predictions, (b) set 1 and set 2, and (c) session 1 and session 2. No evidence of a relationship was found between RIR accuracy and biological sex, years of RT experience, or relative bench press strength. Overall, resistance-trained individuals are capable of high absolute RIR accuracy when predicting 1 and 3 RIR on the barbell bench press exercise, with a minor tendency for underprediction. Thus, RIR prescriptions may be used in research and practice to inform the proximity to failure achieved upon set termination.

Effect of Small and Large Energy Surpluses on Strength, Muscle, and Skinfold Thickness in Resistance-Trained Individuals: A Parallel Groups Design.

BACKGROUND: Many perform resistance training (RT) to increase muscle mass and strength. Energy surpluses are advised to support such gains; however, if too large, could cause unnecessary fat gain. We randomized 21 trained lifters performing RT 3 d/wk for eight weeks into maintenance energy (MAIN), moderate (5% [MOD]), and high (15% [HIGH]) energy surplus groups to determine if skinfold thicknesses (ST), squat and bench one-repetition maximum (1-RM), or biceps brachii, triceps brachii, or quadriceps muscle thicknesses (MT) differed by group. COVID-19 reduced our sample, leaving 17 completers. Thus, in addition to Bayesian ANCOVA comparisons, we analyzed changes in body mass (BM) with ST, 1-RM, and MT changes via regression. We reported Bayes factors (BF10) indicating odds ratios of the relative likelihood of hypotheses (e.g., BF10 = 2 indicates the hypothesis is twice as likely as another) and coefficients of determination (R2) for regressions. RESULTS: ANCOVAs provided no evidence supporting the group model for MT or squat 1-RM. However, moderate (BF10 = 9.9) and strong evidence (BF10 = 14.5) indicated HIGH increased bench 1-RM more than MOD and MAIN, respectively. Further, there was moderate evidence (BF10 = 4.2) HIGH increased ST more than MAIN and weak evidence (BF10 = 2.4) MOD increased ST more than MAIN. Regression provided strong evidence that BM change predicts ST change (BF10 = 14.3, R2 = 0.49) and weak evidence predicting biceps brachii MT change (BF10 = 1.4, R2 = 0.24). CONCLUSIONS: While some group-based differences were found, our larger N regression provides the most generalizable evidence. Therefore, we conclude faster rates of BM gain (and by proxy larger surpluses) primarily increase rates of fat gain rather than augmenting 1-RM or MT. However, biceps brachii, the muscle which received the greatest stimulus in this study, may have been positively impacted by greater BM gain, albeit slightly. Our findings are limited to the confines of this study, where a group of lifters with mixed training experience performed moderate volumes 3 d/wk for 8 weeks. Thus, future work is needed to evaluate the relationship between BM gains, increases in ST and RT adaptations in other contexts.

One Velocity Loss Threshold Does Not Fit All: Consideration of Sex, Training Status, History, and Personality Traits When Monitoring and Controlling Fatigue During Resistance Training.

PURPOSE: This study aimed to quantify the potential variability in the volume of work completed after reaching different velocity loss (VL) thresholds and determine the effects of sex, training status and history, as well as psychological traits on the reliability and magnitude of the amount of work completed after reaching different VL thresholds using different loads in the back-squat exercise. METHODS: Forty-six resistance-trained people (15 females and 31 males; 18 to 40 years of age) with a wide range of strength levels, training experience, and different training practices were recruited and performed a one-repetition maximum (1RM) test, and two repetitions to failure (RTF) tests 72 h apart. RTF tests were performed with 70, 80, and 90% of 1RM with 10 min of rest between sets. The Bland-Altman analysis for multiple observations per participant and equivalence tests were used to quantify the variability in the volume of work completed after reaching different VL thresholds, whereas linear and generalised mixed-effects models were used to examine the effects of different moderators on the stability and magnitude of the amount of work completed after reaching different VL thresholds. RESULTS: The findings of the present study question the utility of using VL thresholds to prescribe resistance training (RT) volume as the agreement in the amount of work completed across two consecutive testing sessions was not acceptable. Regardless of the load used, females completed more repetitions than males across VL thresholds, while males performed repetitions at higher velocities. In addition, individuals with higher levels of emotional stability also tended to perform more repetitions across VL thresholds. Finally, sex, choice of load, strength levels and training practices, as well as emotional stability affected the linearity of the repetition-velocity relationship and when sets terminated. CONCLUSION: Using the same VL thresholds for all individuals, while assuming generalisability of the stimuli applied, would likely lead to variable acute physiological responses to RT and divergent neuromuscular adaptations over long term. Therefore, VL monitoring practices could be improved by considering sex, training status, history, and psychological traits of individuals due to their effects on the variability in responses to different VL thresholds.

Changes in Intraset Repetitions in Reserve Prediction Accuracy During Six Weeks of Bench Press Training in Trained Men.

In this study we investigated whether the accuracy of intraset repetitions in reserve (RIR) predictions changes over time. Nine trained men completed three bench press training sessions per week for 6 weeks (following a 1-week familiarization). The final set of each session was performed until momentary muscular failure, with participants verbally indicating their perceived 4RIR and 1RIR. RIR prediction errors were calculated as raw differences (RIRDIFF), with positive and negative values indicating directionality, and absolute RIRDIFF (absolute value of raw RIRDIFF) indicating error scores. We constructed mixed effect models with time (i.e., session) and proximity to failure as fixed effects, repetitions as a covariate, and random intercepts per participant to account for repeated measures, with statistical significance set at p ≤ .05. We observed a significant main effect for time on raw RIRDIFF (p < .001), with an estimated marginal slope of -.077 repetitions, indicating a slight decrease in raw RIRDIFF over time. Further, the estimated marginal slope of repetitions was -.404 repetitions, indicating a decrease in raw RIRDIFF as more repetitions were performed. There were no significant effects on absolute RIRDIFF. Thus, RIR rating accuracy did not significantly improve over time, though there was a greater tendency to underestimate RIR in later sessions and during higher repetition sets.

The fastest repetition in a set predicts the number of repetitions completed to failure during resistance training: The impact of individual characteristics.

The aim of this study was to examine the goodness of fit and prediction accuracy of general and individual relationships between the maximum number of repetitions completed in a set (XRM) and the fastest repetition in the set (XRM-velocity relationship) in the free-weight back squat exercise. The effects of sex, training status and history, as well as personality traits, on the goodness of fit and the accuracy of these relationships were also investigated. Forty-six resistance-trained people (15 females and 31 males) performed a one-repetition maximum (1RM) test, and two repetitions to failure (RTF) tests, 72 h apart. RTF tests were performed with 70, 80, and 90% of 1RM with 10 min of inter-set rest. A greater goodness of fit was found for individual XRM-velocity relationships (R2 = 0.98; residual standard error [RSE] = 1.01-1.15) compared to general XRM-velocity relationships (R2 = 0.45-0.49; RSE = 3.44-3.66). Individual, but not general XRM-velocity relationships established in the first testing session yielded acceptable prediction accuracy (mean error = 1.96 vs 2.81 repetitions) of XRM in the subsequent testing session. Sex, training status and history, and personality traits did not affect the goodness of fit of general and individual XRM-velocity relationships or their prediction accuracy, suggesting the potential generalisability of those findings among resistance-trained populations. Therefore, individual XRM-velocity relationships can be used to prescribe loads matching an intended XRM by recording only the fastest velocity of the set with a given load and predicting, with reasonable accuracy, the XRM for the individual.

Influence of Resistance Training Proximity-to-Failure, Determined by Repetitions-in-Reserve, on Neuromuscular Fatigue in Resistance-Trained Males and Females.

BACKGROUND: This study examined the influence of proximity-to-failure in resistance training (RT), using subjective repetitions-in-reserve (RIR) prediction, on neuromuscular fatigue and perceptual responses. METHODS: Twenty-four resistance-trained males (n = 12) and females (n = 12) completed three experimental trials in a randomised order, each involving six RT sets (barbell bench press) with 75% 1-RM performed to either momentary muscular failure (FAIL), 1-RIR, or 3-RIR. Changes in lifting velocity with a fixed load were assessed from pre-exercise to post-exercise with the aim of quantifying acute neuromuscular fatigue (4 min post-exercise) and the associated time course of recovery (24 and 48 h post-exercise), and from the first to final set performed. Perceptual responses to RT were assessed at multiple time points during and following RT. RESULTS: Decreases in lifting velocity at 4 min post-exercise were greater for FAIL ( - 25%) versus 1-RIR ( - 13%) and 3-RIR ( - 8%), with greater decreases for male ( - 29%) versus female ( - 21%) participants following FAIL. At 24 h post-exercise, decreases in lifting velocity were greater for FAIL ( - 3%) and 1-RIR ( - 3%) versus 3-RIR (+ 2%), with all between-protocol differences diminishing at 48 h post-exercise. Loss of lifting velocity from the first to final set was greater for FAIL ( - 22%) versus 1-RIR ( - 9%) and 3-RIR ( - 6%), with a greater lifting velocity loss from the first to final set for males ( - 15%) versus females ( - 9%). As proximity-to-failure neared, ratings of perceived discomfort, exertion, and muscle soreness increased, general feelings worsened, and perceived recovery decreased. CONCLUSION: These findings support a linear relationship between RT proximity-to-failure and both acute neuromuscular fatigue and negative perceptual responses, which may influence long-term physiological adaptations and adherence to RT.

Velocity loss is a flawed method for monitoring and prescribing resistance training volume with a free-weight back squat exercise.

PURPOSE: The aim of this study was to examine the goodness of fit, prediction accuracy, and stability of general and individual relationships between velocity loss and the percentage of completed repetitions out of maximum possible (VL-%repetitions) in the free-weight back squat exercise. The effects of sex, training status and history, as well as personality traits, on the goodness of fit and the accuracy of these relationships were also investigated. METHODS: Forty-six resistance-trained people (15 females and 31 males) performed a one-repetition maximum (1RM) test, and two repetitions to failure (RTF) tests, 72 h apart. RTF tests were performed with 70, 80, and 90% of 1RM with 10 min inter-set rest. RESULTS: The findings question the utility of using general and individual VL-%repetitions relationships to prescribe training volume with free-weight back squats as (1) the agreement in the %repetitions completed until reaching a given velocity loss threshold across two consecutive testing sessions was unacceptable, regardless of the load used; and (2) the ability of general and individual VL-%repetitions relationships to predict %repetitions in a subsequent testing session were poor (absolute errors > 10%). Sex, training status and history, and personality traits did not affect the goodness of fit of general and individual VL-%repetitions relationships or their prediction accuracy, suggesting potential generalisability of those findings among resistance-trained populations. CONCLUSIONS: VL-%repetitions relationships do not seem to provide any additional benefits compared to costless, traditional methods and hence should not be used for monitoring and prescribing resistance training with a free-weight back squat exercise.

Weight loss induces changes in adaptive thermogenesis in female and male physique athletes.

Physique athletes lose substantial weight preparing for competitions, potentially altering systemic metabolism. We investigated sex differences in body composition, resting energy expenditure (REE), and appetite-regulating and thyroid hormone changes during a competition preparation among drug-free physique athletes. The participants were female (10 competing (COMP) and 10 nondieting controls (CTRL)) and male (13 COMP and 10 CTRL) physique athletes. COMP were tested before they started their diet 23 weeks before competing (PRE), during their diet one week before competing (MID), and 23 weeks after competing (POST), whereas CTRL were tested at similar intervals but did not diet. Measurements included body composition by dual-energy X-ray absorptiometry, muscle size, and subcutaneous fat thickness (SFA) by ultrasound, REE by indirect calorimetry, circulating ghrelin, leptin T3, and T4 hormone analysis. Fat mass (FM) and SFA decreased in both sexes (p < 0.001), while males (p < 0.001) lost more lean mass (LM) than females (p < 0.05). Weight loss, decreased energy intake, and increased aerobic exercise (p < 0.05) led to decreased LM- and FM-adjusted REE (p < 0.05), reflecting metabolic adaptation. Absolute leptin levels decreased in both sexes (p < 0.001) but more among females (p < 0.001) due to higher baseline leptin levels. These changes occurred with similar decreases in T3 (p < 0.001) and resting heart rate (p < 0.01) in both sexes. CTRL, who were former or upcoming physique athletes, showed no systematic changes in any measured variables. In conclusion, while dieting, female and male physique athletes experience REE and hormonal changes leading to adaptive thermogenesis. However, responses seemed temporary as they returned toward baseline after the recovery phase. ClinicalTrials.gov (NCT04392752).

Influence of Resistance Training Proximity-to-Failure on Skeletal Muscle Hypertrophy: A Systematic Review with Meta-analysis.

BACKGROUND AND OBJECTIVE: This systematic review with meta-analysis investigated the influence of resistance training proximity-to-failure on muscle hypertrophy. METHODS: Literature searches in the PubMed, SCOPUS and SPORTDiscus databases identified a total of 15 studies that measured muscle hypertrophy (in healthy adults of any age and resistance training experience) and compared resistance training performed to: (A) momentary muscular failure versus non-failure; (B) set failure (defined as anything other than momentary muscular failure) versus non-failure; or (C) different velocity loss thresholds. RESULTS: There was a trivial advantage for resistance training performed to set failure versus non-failure for muscle hypertrophy in studies applying any definition of set failure [effect size=0.19 (95% confidence interval 0.00, 0.37), p=0.045], with no moderating effect of volume load (p=0.884) or relative load (p=0.525). Given the variability in set failure definitions applied across studies, sub-group analyses were conducted and found no advantage for either resistance training performed to momentary muscular failure versus non-failure for muscle hypertrophy [effect size=0.12 (95% confidence interval -0.13, 0.37), p=0.343], or for resistance training performed to high (>25%) versus moderate (20-25%) velocity loss thresholds [effect size=0.08 (95% confidence interval -0.16, 0.32), p=0.529]. CONCLUSION: Overall, our main findings suggest that (i) there is no evidence to support that resistance training performed to momentary muscular failure is superior to non-failure resistance training for muscle hypertrophy and (ii) higher velocity loss thresholds, and theoretically closer proximities-to-failure do not always elicit greater muscle hypertrophy. As such, these results provide evidence for a potential non-linear relationship between proximity-to-failure and muscle hypertrophy.