Acute physiological outcomes of high-intensity functional training: a scoping review.

Background: Systematic reviews and meta-analyses related to high-intensity functional training (HIFT) have been conducted. However, due to a restricted pool of available research, these investigations are often limited in scope. As such, a scoping review investigating the present literature surrounding the acute physiological response to HIFT-based exercise was chosen as a more appropriate structured review. Methodology: A scoping review was conducted following Arksey and O'Malley's framework. Three large scale databases were searched to reveal any article pertaining to HIFT and related exercise terminology. Results: A total of 2,241 articles were found during the initial search. Following this, titles, then abstracts, and full-texts were reviewed to determine inclusion eligibility. A total of 60 articles which investigated a combined total of 35 unique HIFT workouts were included within this review. Conclusions: A variety of physiological parameters and HIFT workouts have been examined. Markers of intensity (e.g., blood lactate concentrations, heart rate) have been most consistently assessed across all studies, and these support the idea that HIFT workouts are typically performed at high-intensity. In contrast, the inclusion of most other measures (e.g., hormonal, markers of inflammation and damage, energy expenditure, performance) has been inconsistent and has thus, limited the possibility for making generalized conclusions. Differences in study methodologies have further impacted conclusions, as different studies have varied in sample population characteristics, workouts assessed, and time points. Though it may be impossible to comprehensively research all possible HIFT workouts, consistent adoption of population definitions and workload quantification may overcome this challenge and assist with future comparisons.

Relationships Between Body Composition and Performance in the High-Intensity Functional Training Workout "Fran" are Modulated by Competition Class and Percentile Rank.

This study examined relationships between body composition and high-intensity functional training (HIFT) workout performance. Fifty-seven men (31.4 ± 6.9 years, 177.2 ± 7.5 cm, 84.7 ± 8.5 kg) and thirty-eight women (29.2 ± 6.4 years, 166.6 ± 6.1 cm, 66.5 ± 7.7 kg) with HIFT experience (≥6 months) reported completing "Fran" (21-15-9 repetitions of barbell thrusters and pull-ups) in 4.78 ± 2.22 min and 6.05 ± 2.84 min, respectively, and volunteered to complete dual-energy X-ray absorptiometry assessments. Participants were grouped by competition class (men, women, master's men, master's women) and percentile rank in "Fran" (≤25th percentile, 25-75th percentiles, ≥75th percentile). Two-way analyses of variance revealed expected differences (p < 0.001) between men and women in non-bone lean mass (NBLM), fat-free mass index, and fat mass, and more NBLM (10.6-10.8 kg) and less fat mass (2.7-5.2 kg) in >75th percentile compared to other percentiles. Most body composition measures were significantly (p < 0.05) related to performance in men and women but limited in master's men; no relationships were seen in master's women. "Fran" time was negatively correlated to NBLM and fat-free mass index in all percentile groups (ρ = -0.37 to -0.64) and bone mineral characteristics for >25th percentile (ρ = -0.41 to -0.63), and positively correlated to fat mass in 25-75th percentiles (ρ = 0.33-0.60). No other relationships were seen in ≤25th percentile. The influence of body composition on "Fran" time appears to vary by both competition class and percentile rank. Though training to increase lean mass always seems relevant, reducing body fat only appears relevant in mid-skilled trainees and when it is outside healthy parameters.

CrossFit® open performance is affected by the nature of past competition experiences.

PURPOSE: To examine the relationships between past competition performances and 2020 CrossFit® Open (CFO) performance. METHODS: A random selection from the top one thousand athletes (n = 220, 28.5 ± 4.4 years, 178 ± 7 cm, 87.5 ± 10.2 kg) were selected for this study. Overall and weekly performances (including ranks and scores) of the 2020 CFO, as well as overall ranks from all previous CFO, regional, and Games™ competitions in which they competed, were recorded from their publicly available online profile. The highest, lowest, average, and standard deviation (SD) of past rankings, as well as participation statistics (i.e., years since first appearance, total and consecutive appearances, and participation rate), were calculated for each competition stage. Relationships were then assessed between 2020 CFO performance and all past competition experience variables by calculating Kendall's tau (τ) correlation coefficients and Bayes factors (BF10). RESULTS: Overall and weekly ranking of the 2020 CFO was extremely favored (p < 0.001, BF10 > 100) to be related to the athlete's highest previous CFO rank (τ = 0.26-0.39) and individual regional appearances (τ = - 0.26 to - 0.34), as well as individual Games™ appearances (overall and for weeks 1, 3, and 4; τ = - 0.20 to - 0.22, p < 0.001, BF10 > 100). Evidence for all other significant relationships ranged from moderate to very strong (p < 0.05, BF10 = 3-100) and varied among specific 2020 CFO workouts. Few associations were noted for team competition experience, and these were generally limited to Games™ appearances (τ = - 0.12 to - 0.18, p < 0.05, BF10 = 3.3-100). CONCLUSIONS: Although specific relationships were found between 2020 CFO performance and individual appearances at regional and Games™ competitions, the most consistent relationships were seen with participation and ranking in past CFO competitions.

Workout Pacing Predictors of Crossfit® Open Performance: A Pilot Study.

To observe workout repetition and rest interval pacing strategies and determine which best predicted performance during the 2016 CrossFit® Open, five male (34.4 ± 3.8 years, 176 ± 5 cm, 80.3 ± 9.7 kg) and six female (35.2 ± 6.3 years, 158 ± 7 cm, 75.9 ± 19.3 kg) recreational competitors were recruited for this observational, pilot study. Exercise, round, and rest time were quantified via a stopwatch for all competitors on their first attempt of each of the five workouts. Subsequently, pacing was calculated as a repetition rate (repetitions·s-1) to determine the fastest, slowest, and average rate for each exercise, round, and rest interval, as well as how these changed (i.e., slope, Δ rate / round) across each workout. Spearman's rank correlation coefficients indicated that several pacing variables were significantly (p < 0.05) related to performance on each workout. However, stepwise regression analysis indicated that the average round rate best predicted (p < 0.001) performance on the first (R2 = 0.89), second (R2 = 0.99), and fifth (R2 = 0.94) workouts, while the competitors' rate on their slowest round best predicted workout three performance (R2 = 0.94, p < 0.001). The wall ball completion rate (R2 = 0.89, p = 0.002) was the best predictor of workout four performance, which was improved by 9.8% with the inclusion of the deadlift completion rate. These data suggest that when CrossFit® Open workouts consist of multiple rounds, competitors should employ a fast and sustainable pace to improve performance. Otherwise, focusing on one or two key exercises may be the best approach.

Predictors of CrossFit Open Performance.

The 2018 CrossFit Open (CFO) was the initial stage of an annual competition that consisted of five weekly workouts. Current evidence suggests that a variety of fitness parameters are important for progressing beyond this stage, but little is known about which are the most important. To examine relationships between CFO performance, experience, and physiological fitness, sixteen experienced (>2 years) athletes (30.7 ± 6.9 years, 171 ± 12 cm, 78.0 ± 16.2 kg) volunteered to provide information about their training and competitive history, and then complete a battery of physiological assessments prior to competing in the 2018 CFO. Athletes' resting energy expenditure, hormone concentrations, body composition, muscle morphology, cardiorespiratory fitness, and isometric strength were assessed on two separate occasions. Spearman correlations demonstrated significant (p < 0.05) relationships between most variables and performance on each workout. Stepwise regression revealed competition experience (R2 = 0.31-0.63), body composition (R2 = 0.55-0.80), vastus lateralis cross-sectional area (R2 = 0.29-0.89), respiratory compensation threshold (R2 = 0.54-0.75), and rate of force development (R2 = 0.30-0.76) to be the most common predictors. Of these, body composition was the most important. These fitness parameters are known targets with established training recommendations. Though preliminary, athletes may use these data to effectively train for CFO competition.