A Comparison of Anaerobic Power Tests using Cycle Ergometry and Non-motorized Treadmill Ergometry at Optimized Loads

International Journal of Exercise Science 16(4): 1293-1305, 2023. The purpose of this study was to compare performance markers derived from a 30-second maximal bout on a cycle ergometer (CE) and non-motorized treadmill (NMT) under optimized loads. Recreationally active participants (n = 40) volunteered for the study. Force-velocity tests on the CE and NMT were used to determine optimal resistance for peak power (PP) production. The remaining visits were randomized and counterbalanced, with a single 30-second maximal test on CE or NMT to assess PP, mean power (MP), fatigue index (FI), over the course of the 30-second test, and maximum heart rate (HRmax) and blood lactate (BLa-) taken 1-minute post. Results were that PP and MP were higher (P\u3c0.05) on CE compared to NMT for both sexes. FI did not differ among males (P=0.201) whereas females showed higher FI (P=0.002) on the CE. HRmax and BLa- were higher (P\u3c0.05) after NMT for both sexes. There was no difference for optimal braking force on NMT between males (16.65±4.49%BW) and females (14.30±3.10%BW) (P=0.061). CE optimal torque factor was higher for males (0.78±0.16 Nm/kg) compared to females (0.62±0.14 Nm/kg) (P=0.001). Overall, CE produced higher power output using optimized loads in recreationally active males and females, while NMT test resulted in a higher HRmax andBLa- concentration. These tests for anaerobic power, when performed with optimized loads, produced different results for several variables, therefore these modalities should not be considered interchangeable. Practitioners should consider which modality best mimics the activities of the person being tested when selecting a protocol

The influence of sex-division, experience, and pacing strategy on performance in the 2020 CrossFit® Open

To observe workout pacing strategies and determine which best predicted performance, this retrospective study analyzed recorded efforts from a random selection of 160 high-ranking (top 10,000) men and women (n = 80 each) in the 2020 CrossFit® Open (CFO). Video recordings submitted to the official competition leaderboard for all five tests were analyzed to quantify overall test completion rates (and tie-break time for test 5 only) and within-test repetition completion rate (repetitions × sec−1) for each exercise, as well as the quantity of failed repetitions, break strategy (count and duration), and transition times. Each variable was aggregated into first-half, last-half, and total-test averages, slopes, and coefficient of variation; except on test 5 (total-test only). Spearman's rank correlation coefficients were calculated between test completion rates, each test's respective pacing variables, competitor demographics (height and body mass) and CFO experience (i.e., past participation, consecutive competitions, and ranks). Stepwise regression using significantly (p < 0.05) correlated variables produced two prediction models for test performance (best predictor only and best overall model within 8 variables) in a validation group (50% of valid efforts) and then cross-validated against remaining athletes. When no between-group differences were seen, data were combined and used to create the final prediction models for test 1 (r2adj = 0.64–0.96, SEE = 0.4–1.2 repetitions × sec−1), test 2 (r2adj = 0.28–0.85, SEE = 2.0–4.5 repetitions × sec−1), test 3 (r2adj = 0.49–0.81, SEE = 1.1–1.7 repetitions × sec−1), test 4 (r2adj = 0.63–0.78, SEE = 0.6–0.9 repetitions × sec−1), and test 5 (rate: r2adj = 0.71–0.84, SEE = 1.2–1.6 repetitions × sec−1; tie-break time: r2adj = 0.06–0.62, SEE = 1.4–2.3 min). Across the five 2020 CFO tests, the data suggested that repetition pace, breaking strategy, and/or consistency in completing calisthenic-gymnastics components (when prescribed) was most predictive of performance. However, their influence was affected by the complexity of prescribed resistance training exercises and their relative loads. Athletes should prioritize calisthenic-gymnastics components but divert attention to more complex resistance training exercises when prescribed at higher relative intensity loads. Neither previous competition experience nor sex-division altered the hierarchal importance of these considerations

Effects of Heat Exposure on Body Water Assessed using Single-Frequency Bioelectrical Impedance Analysis and Bioimpedance Spectroscopy

International Journal of Exercise Science 10(7): 1085-1093, 2017. The purpose of this study was to determine if heat exposure alters the measures of total body water (TBW), extracellular water (ECW), and intracellular water (ICW) in both single-frequency bioelectrical impedance analysis (BIA) and bioimpedance spectroscopy (BIS). Additionally, we sought to determine if any differences exist between the BIA and BIS techniques before and after brief exposure to heat. Body water was evaluated for twenty men (age=24±4 years) in a thermoneutral environment (22°C) before (PRE) and immediately after (POST) 15 min of passive heating (35°C) in an environmental chamber. The mean difference and 95% limits of agreement at PRE demonstrated that BIS yielded significantly higher body water values than BIA (all p0.05; 0.2±1.5kg). Additionally, the ES of the mean differences at POST were trivial to small and the r-values were high (r≥0.96). When analyzing the changes in body water before and after heat exposure, POST values for BIS were significantly higher than PRE (all

Is caffeine recommended before exercise? A systematic review to investigate its impact on cardiac autonomic control via heart rate and its variability

Evaluating different doses of caffeine (CAF) on heart rate (HR) variability (HRV) during and following exercise in order to assess its impact on autonomic control. We intended to evaluate the influence of CAF as a supplement before exercise on HRV through a systematic review. Manuscripts were selected based on electronic searches of MEDLINE, EMBASE and CINAHL databases from 2010 to 2019 and followed the protocol Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA). Blind randomized designs and controlled trials that reported the influence of CAF on HRV during exercise and during recovery from exercise, with strength of evidence assessed using the GRADE system; the search for the studies was organized using the PICOS strategy. A total of 1797 articles were recognized, following the screening and eligibility stages, 9 studies continued to the final sample. Six studies reported that the combination of CAF supplementation with physical exercise exhibited higher HR when compared to the placebo group during post-exercise recovery; additionally, prolonged activation of sympathetic cardiac control and delayed parasympathetic reactivation following exercise was observed. However, three studies demonstrated no CAF influence when using similar doses. This review observed equivocal results in HR and HRV recovery following exercise with the presence of CAF consumption. These findings cannot confirm the cardiac autonomic changes observed where entirely due to the influence of CAF, and further studies should be performed to better understand this relationship

Relative accuracy of anthropometric-based body fat equations in males and females with varying BMI classifications

Background: BMI based body fat equations developed from Womersley and Durnin (BMIWO), Jackson et al. (BMIJA), Deurenberg et al. (BMIDE), and Gallagher et al. (BMIGA) are commonly used to quantify body fat percentage (BF%). However, relative fat mass (RFM) is a new anthropometric-based method that has been proposed as an alternative. Aims: The purpose of this study was to examine the independent and interactive effects of sex and BMI classification on the relative accuracy of BMI-based body fat equations and RFM. Methods: Males (n = 75) and females (n = 75) were stratified and classified into three different groups; 1) normal weight (n = 50 [NW: 50% males]; BMI\u3c25.0 kg/m2); 2) overweight (n = 50 [OW: 50% males]; BMI≥25.0–29.9 kg/m2); 3) obese (n = 50 [OB: 50% males]; BMI≥30.0 kg/m2). A criterion three-compartment model (3C model) was determined with air displacement plethysmography for body volume and multi-frequency bioimpedance analysis for total body water. Data were stratified by sex and BMI classification. Difference scores were created by subtracting estimated BF% from 3C model BF%. Results: A significant SEX × BMI interaction was detected for all comparisons (all p \u3c 0.05). Post hoc analysis indicated the differences in BF% were statistically significant between OW females and males for all equations (BMIWO:-2.99 ± 4.79% vs. 4.71 ± 5.86%, p = 0.003; BMIJA:-1.77 ± 4.83% vs. 5.77 ± 5.85%, p \u3c 0.001; BMIDE:-3.09 ± 4.80% vs. 4.97 ± 5.98%, p \u3c 0.001; BMIGA:0.36 ± 4.51% vs. 4.56 ± 5.55%, p = 0.018; RFM:-2.17 ± 4.84% vs. 3.01 ± 5.34%, p = 0.004, respectively). In addition, there were significant differences between females and males classified as NW (BMIJA:-2.11 ± 4.15% vs. 2.61 ± 5.98%, p = 0.008) and OB (BMIGA:2.40 ± 3.36% vs. −1.09 ± 6.40%, p = 0.006). Conclusions: The current findings highlight that RFM does not appear to overcome error commonly associated with BMI-based body fat equations when stratifying by sex and BMI classification. Nonetheless, practitioners can use BMIWO, BMIDE, and RFM in males and females classified as NW or OB, but should employ caution prior to use in OW persons

Reliability and Agreement of Various InBody Body Composition Analyzers as Compared to Dual-Energy X-Ray Absorptiometry in Healthy Men and Women

Background: Bioelectrical impedance analysis has evolved over the years to include the use of multiple frequencies and impedance measurements to improve the accuracy and reliability of body composition estimates. The purpose of this investigation was to evaluate the reliability of the InBody230, InBody720, and InBody770 to measure body fat percent (BF%), fat mass (FM), and fat-free mass (FFM) in the general population and to compare results to dual-energy X-ray absorptiometry (DXA). Methods: A total of 31 males and 36 females participated in 2 d of testing separated by 24–72 h. Each visit consisted of a DXA scan, and analysis with the InBody230, InBody720, and InBody770. Results: All 3 bioelectrical impedance devices (InBody230, InBody720, and InBody770) were reliable in men and women as indicated by high intraclass correlation coefficients for BF% (≥0.98), FM (≥0.98), and FFM (≥0.99) and low standard error of measurement for BF% (0.77%–0.99%), FM (0.54–0.87 kg), and FFM (0.58–0.84 kg) and minimum difference for BF% (2.12%–2.73%), FM (1.49–2.39 kg), and FFM (1.60–2.32 kg), respectively. When examining the agreement between the 3 InBody analyzers with DXA, systematic bias (underestimation of BF% and FM and overestimation of FFM) was present for all comparisons (p \u3c 0.05) while proportional bias was present for FM in women and FFM in men. However, there was small individual error for all comparisons as indicated by the standard error of estimate and 95% limits of agreement. Conclusion: The InBody analyzers produce small individual error, which suggest these methods can be used as a surrogate when DXA is not available; however, practitioners should be aware of the systematic bias for all comparisons and proportional bias for FM in women and FFM in men. Furthermore, findings revealed that the research grade models, InBody720 and InBody770, added minimal benefit over the portable InBody230 when assessing BF%, FM, and FFM

Comparison of bioimpedance and underwater weighing body fat percentage before and acutely after exercise at varying intensities

The purpose of this study was to compare single-frequency bioelectrical impedance analysis (BIA) and bioimpedance spectroscopy (BIS) with underwater weighing (UWW) body fat percentage (BF%) before (PRE), immediately post (IP), and 60 minutes post (60P) an acute bout of moderate and vigorous aerobic exercise. Nine men (age = 24.6 ± 3.7 years) volunteered for this study. Subjects visited the laboratory on 3 separate occasions. Testing included two 30-minute exercise sessions at 60 and 80% heart rate reserve (HRR) and a 30-minute control (CON) trial. The constant error (CE) was significantly higher for BIA at each time point and exercise session (CE = 3.0-4.9% for 60% HRR; 2.5-4.7% for 80% HRR). Conversely, BIS yielded a nonsignificant CE at each time point and exercise session (CE = 20.9 to 1.1% for 60% HRR; 20.3 to 1.2% for 80% HRR). The standard error of estimate (SEE) for both exercise sessions ranged from 2.7 to 3.1% and 3.8-4.3% for BIA and BIS, respectively. The 95% limits of agreement were narrower for BIA (60% HRR = ±5.5 to 7.8%; 80% HRR = ±6.6 to 8.5%) than BIS (60%HRR = ±8.4 to 9.4%; 80% HRR = ±8.1 to 10.2%). Results indicate that BIS can be used for mean group BF% in men at PRE, IP, and 60P time periods. However, BIA yielded a lower SEE and 95% limits of agreement than BIS. Therefore, BIA provides better individual estimates of BF% in men, but the CE should be taken into consideration

Workout Pacing Predictors of Crossfit\u3csup\u3e®\u3c/sup\u3eOpen 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, Δrate / round) across each workout. Spearman\u27s rank correlation coefficients indicated that several pacing variables were significantly (p \u3c 0.05) related to performance on each workout. However, stepwise regression analysis indicated that the average round rate best predicted (p \u3c 0.001) performance on the first (R2 = 0.89), second (R2 = 0.99), and fifth (R2 = 0.94) workouts, while the competitors\u27 rate on their slowest round best predicted workout three performance (R2 = 0.94, p \u3c 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

Validity of DXA Body Volume Equations in a Four-compartment Model for Adults with Varying Body Mass Index and Waist Circumference Classifications

The purpose of this investigation was to determine the validity of 4-compartment (4C) model body fat percent (BF%) estimates when using dual energy x-ray absorptiometry (DXA) derived body volume (BV) equations (4C-DXA1 and 4C-DXA2) in adults with varying body mass index (BMI) and waist circumference (WC) classifications. Each model was compared to a criterion 4C model with air-displacement plethysmography (ADP) generated BV (4C-ADP). Participants were categorized as normal weight (n = 40; NW = BMI\u3c25.0kg/m2); overweight (n = 40; OWBMI = BMI≥25.0 kg/m2); and overweight with at-risk WC (n = 35; OWBMI+WC = BMI≥25.0 kg/m2 and WC≥88.0cm for women and 102.0cm for men). 4C-DXA1 produced lower BF% than that derived using the 4C-ADP in NW (CE = -3.0%; p\u3c0.001) while 4C-DXA2 was significantly higher (CE = 4.8%; p\u3c0.001). The SEE and 95% limits of agreement (LOA) were lower for 4C-DXA2 (1.24% and ±2.5%, respectively) than 4C-DXA1 (2.59% and ±5.0%, respectively) and proportional bias was present for both (p\u3c0.05). 4C-DXA1 BF% was not significant in OWBMI (CE = -0.5%; p = 0.112) whereas 4C-DXA2 was higher (CE = 4.5%; p\u3c0.001). The SEE and 95% LOA were lower for 4C-DXA2 (1.20% and ±2.9%, respectively) than 4C-DXA1 (1.92% and ±3.9%, respectively) in OWBMI. Proportional bias was present for 4C-DXA1 (p = 0.007), but not 4C-DXA2 (p = 0.832). 4C-DXA1 and 4C-DXA2 produced significantly higher BF% in OWBMI+WC (CE = 2.2 and 2.3%, respectively; both p\u3c0.001). The SEE and 95% LOA remained lower for 4C-DXA2 (1.15% and ±2.5%, respectively) than 4C-DXA1 (1.84% and ±3.8%, respectively). There was proportional bias for 4C-DXA2 (p = 0.020), but not 4C-DXA1 (p = 0.183) in OWBMI+WC. Only one prediction model (i.e., 4C-DXA1 in OWBMI+WC) revealed valid estimates of BF%. Practitioners are encouraged to use criteria for both BMI and WC when utilizing DXA-derived BV in 4C-models for normal and overweight populations

Validity of BMI-Based Body Fat Equations in Men and Women: A 4-Compartment Model Comparison

Validity of BMI-based body fat equations in men and women: a 4-compartment model comparison. J Strength Cond Res 32(1): 121-129, 2018-The purpose of this study was to compare body mass index (BMI)-based body fat percentage (BF%) equations and skinfolds with a 4-compartment (4C) model in men and women. One hundred thirty adults (63 women and 67 men) volunteered to participate (age = 23 ± 5 years). BMI was calculated as weight (kg) divided by height squared (m). BF% was predicted with the BMI-based equations of Jackson et al. (BMIJA), Deurenberg et al. (BMIDE), Gallagher et al. (BMIGA), Zanovec et al. (BMIZA), Womersley and Durnin (BMIWO), and from 7-site skinfolds using the generalized skinfold equation of Jackson et al. (SF7JP). The 4C model BF% was the criterion and derived from underwater weighing for body volume, dual-energy X-ray absorptiometry for bone mineral content, and bioimpedance spectroscopy for total body water. The constant error (CE) was not significantly different for BMIZA compared with the 4C model (p = 0.74, CE = -0.2%). However, BMIJA, BMIDE, BMIGA, and BMIWO produced significantly higher mean values than the 4C model (all p \u3c 0.001, CEs = 1.8-3.2%), whereas SF7JP was significantly lower (p \u3c 0.001, CE = -4.8%). The standard error of estimate ranged from 3.4 (SF7JP) to 6.4% (BMIJA) while the total error varied from 6.0 (SF7JP) to 7.3% (BMIJA). The 95% limits of agreement were the smallest for SF7JP (±7.2%) and widest for BMIJA (±13.5%). Although the BMI-based equations produced similar group mean values as the 4C model, SF7JP produced the smallest individual errors. Therefore, SF7JP is recommended over the BMI-based equations, but practitioners should consider the associated CE