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.

Pacing Strategies Differ by Sex and Rank in 2020 CrossFit® Open Tests.

This retrospective study collected video recordings of a random selection of eighty men and women (n = 160) completing all five tests of the 2020 CrossFit® Open. All competitors were ranked within the top 10,000 overall but were sub-divided based on whether they ranked within the top 10% of their respective divisions. To examine the effect of sex and rank on pacing strategy, video analysis quantified the overall repetition completion rate on each test, as well as per minute (or round) repetition completion rates for each test's individual exercises, quantity of failed repetitions, break times, and transition times. All per minute (or round) data were aggregated into first- and last-half or total test average, slopes, and coefficient of variation. Sex and rank analyses of variance were performed on averages, slopes, and coefficients of variation for each variable calculated over the first and last halves of each test, except test 5 (total only). The top 10% of men were 17.5% faster (p < 0.001) than everyone else in tests 1, 3, and 5. The top 10% of women and remaining men were ~9.5% faster than remaining women in tests 1 and 3. In test 5, the remaining men were faster than top 10% of women (~11.2%, p < 0.001), and both were faster than the remaining women. In tests 2 and 4, the top 10% of athletes were 9.7% faster (p < 0.001) than remaining athletes, and at the same time, men were 7.7% faster (p < 0.001) than women. Analysis of each test's components revealed the top 10% of competitors to be faster and more consistent in most areas, while men were generally faster than women in gymnastics components and more consistent with their pace for resistance training exercises. These data provide insight into the differential factors linked to success in the men's and women's CFO divisions.

A Comparison of Anaerobic Power Tests using Cycle Ergometry and Nonmotorized Treadmill Ergometry at Optimized Loads.

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<0.05) 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<0.05) 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 and BLa- 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.

Carbohydrate Rinse Fails to Enhance Cycling Performance or Alter Metabolic and Autonomic Recovery in Recreational Cyclists.

The purpose of the study was to examine the effects of carbohydrate (CHO) mouth rinsing on autonomic and metabolic recovery as well as cycling performance. Ten male recreational cyclists (age = 30 ± 6 years, VO2peak = 54.5 ± 8.1 mL·kg-1·min-1) completed a randomized, double-blind, placebo-controlled, crossover designed study. A CHO or a placebo (PLA) rinse was administered every 12.5% of a work to completion trial (75%Wmax). Heart rate variability (lnRMSSD), the respiratory exchange ratio, and plasma epinephrine, norepinephrine, insulin, glucose, free fatty acids (FFA), and lactate were measured pre- and post-exercise. The CHO rinse did not improve time to completion of the test trial (CHO: 4108 ± 307 s, PLA: 4176 ± 374 s, p = 0.545). Further, the CHO rinse did not impact autonomic recovery, as measured by lnRMSSD (p = 0.787) and epinephrine (p = 0.132). Metabolic biomarkers were also unaffected by the CHO rinse, with no differences observed in responses of FFA (p = 0.064), lactate (p = 0.302), glucose (p = 0.113) or insulin (p = 0.408). Therefore, the CHO mouth rinse does not reduce the acute sympathetic response following strenuous exercise and does not result in improvements in cycling time to completion.

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.

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<25.0 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 < 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 < 0.001; BMIDE:-3.09 ± 4.80% vs. 4.97 ± 5.98%, p < 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.

Agreement Between 2 Segmental Bioimpedance Devices, BOD POD, and DXA in Obese Adults.

This study examined the agreement between 2 segmental bioimpedance analysis (BIA) devices, air displacement plethysmography (BOD POD), and dual energy X-ray absorptiometry (DXA) for estimating body composition in obese adults. Fifty obese adults (25 men and 25 women; age = 34.20 ± 11.19 years; BMI = 36.14 ± 5.33 kg/m2) had their body fat percentage (BF%) and fat-free mass (FFM) evaluated with 2 segmental BIA devices (InBody 230 and InBody 720), BOD POD, and DXA (Lunar iDXA). Body composition via the BOD POD was determined using the Siri equation whereas manufacturer-based equations generated metrics (ie, BF% and FFM) for the InBody devices. The effect size of the mean differences for all BF% and FFM comparisons were trivial (Cohen's d < 0.20). The standard error of estimate (SEE), total error (TE), and 95% limits of agreement (LOAs) were low for both segmental BIA devices when compared to DXA (SEE < 2.26% and 2.35 kg; TE < 2.58% and 2.66 kg; 95% LOAs < ± 4.94% and 4.86kg). The error for BOD POD was also low when compared to DXA (SEE = 2.39% and 2.57 kg; TE = 2.34% and 2.56 kg; 95% LOAs = 4.63% and 5.06 kg). Validity statistics were slightly higher, but considered acceptable, when comparing the segmental BIA devices against BOD POD (SEE < 3.37% and 3.63 kg; TE < 3.44% and 3.79 kg; 95% LOAs < ± 6.62% and 7.19 kg). Lastly, the 2 segmental BIA devices produced nearly identical validity statistics when compared to each other. However, both BIA devices revealed proportional bias for BF% and FFM when compared to the BOD POD and DXA (all p < 0.05). The current study's findings indicate the InBody 230 is interchangeable with the InBody 720 in obese adults. Also, the trivial effect size, when compared against the BOD POD and DXA, suggest the InBody devices could be used for estimating group BF% and FFM. In contrast, the significant proportional bias demonstrates the BIA devices are not acceptable for individual estimates of body composition in an obese clinical population.

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 < 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.

Pre-Anticipatory Anxiety and Autonomic Nervous System Response to Two Unique Fitness Competition Workouts.

To evaluate the feasibility of on-site collection of subjective anxiety, autonomic nervous system activity, and salivary catecholamines surrounding high-intensity functional training (HIFT) competition, ten experienced HIFT competitors completed baseline assessments of anxiety and heart rate variability (HRV). Then, in two consecutive weeks (Workout 1 and 2) within the competition, HRV was recorded and examined in 5-min segments prior to exercise (PRE) and across a 30-min period after competitors completed their choice of the prescribed or scaled each workout. Subjective anxiety ratings and saliva samples were collected at PRE and immediately-(IP), 30-min (30P), and 60-min post-exercise (60P). Saliva samples were analyzed for concentrations of epinephrine and norepinephrine. Generalized linear mixed models with repeated measures revealed significant (p < 0.05) differences between workouts for all measures. Compared to Workout 1, anxiety (~50%), epinephrine (173-340%), norepinephrine (29-234%) were greater in Workout 2 and various HRV-derived indices were more depressed. Additionally, some HRV-derived indices appeared to be modulated (p < 0.05) by competitive level and sex at PRE and throughout the 30-min recovery period. These data suggest that autonomic activity may differ between the competitive and laboratory settings, and that the response may be further modulated by the workout's design, the athlete's sex, and competitive level.

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<25.0kg/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<0.001) while 4C-DXA2 was significantly higher (CE = 4.8%; p<0.001). 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<0.05). 4C-DXA1 BF% was not significant in OWBMI (CE = -0.5%; p = 0.112) whereas 4C-DXA2 was higher (CE = 4.5%; p<0.001). 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<0.001). 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.

Influence of acute consumption of caffeine vs. placebo over Bia-derived measurements of body composition: a randomized, double-blind, crossover design.

BACKGROUND: Bioelectrical impedance analysis (BIA) is often used to estimate total body water (TBW), intracellular body water (ICW), extracellular body water (ECW), and body fat percentage (BF%). A common restriction for BIA analysis is abstinence from caffeine 12-h prior to testing. However, research has yet to determine whether the consumption of caffeine influences BIA testing results. The purpose of this study was to determine if the consumption of caffeine influences BIA-derived BF% and body water values in habitual caffeine users. METHODS: Twenty apparently healthy males (26.6 ± 4.1 years) identified as habitual caffeine consumers (≥ one 95 mg serving per day ≥ four days per week) participated in this study. Participants came to the lab on three occasions, the first visit serving as the control (CON) with no supplementation. The remaining two visits were performed in a randomized double-blind, cross-over fashion. Participants consumed 200 mg of dextrose (PLA) or caffeine (CAF) in capsule form. During each visit, seven multi-frequency BIA measurements were conducted before (PRE) and after (15-min, 30-min, 45-min, 60-min, 75-min, 90-min) consumption. RESULTS: Repeated measures ANOVA revealed BF% for CAF was lower than the CON and PLA conditions at PRE and 15-min (p < 0.001, p = 0.004), but not statistically significant for the remaining time points (i.e., 30-, 45-, 60-, 75-, and 90-min). However, the effect size (ES) of the BF% differences were trivial. The CON, PLA, and CAF conditions had higher PRE ICW values than their associated post time points (i.e., 15-, 30-, 45-, 60-, 75-, and 90-min). Similar to BF%, ES of the mean differences for ICW were trivial. No other differences were observed. CONCLUSION: Caffeine consumption in habitual users produced trivial changes in TBW, ECW, ICW, or BF%. Therefore, the pre-testing guidelines for caffeine consumption may not be necessary in habitual caffeine consumers.

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

Nickerson, BS, Esco, MR, Bishop, PA, Fedewa, MV, Snarr, RL, Kliszczewicz, BM, and Park, K-S. 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 < 0.001, CEs = 1.8-3.2%), whereas SF7JP was significantly lower (p < 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.

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

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 p<0.05; TBW=1.8kg; ECW=0.6±1.3kg; ICW=1.2±3.7kg). However, the effect size (ES) of the mean differences at PRE were small and the r-values were high (r≥0.97). TBW and ICW remained significantly higher at POST for BIS (both p<0.05; 1.4±3.2kg and 1.1±3.7kg, respectively) whereas ECW was not different (p>0.05; 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 p<0.001; TBW=0.6±0.8kg; ECW=0.4±0.3kg; ICW=0.3±0.6kg). Similarly, POST values for BIA were significantly higher than PRE (all p<0.001; TBW=1.0±0.6kg; ECW=0.7±0.4kg; ICW=0.4±0.4kg). BIA and BIS provide similar body water estimates. However, the increase in POST body water values indicate more research is needed before either method can be used for estimating body water after heat exposure.

Validity of Four-Compartment Model Body Fat In Physically Active Men And Women When Using DXA For Body Volume.

The purpose of this study was twofold: 1) compare body volume (BV) estimated from dual energy X-ray absorptiometry (DXA) to BV from a criterion underwater weighing (UWW) with simultaneous residual lung volume (RLV), and 2) compare four-compartment (4C) model body fat percentage (BF%) values when deriving BV via DXA (4CDXA) and UWW (4CUWW) in physically active men and women. One hundred twenty-two adults (62 men and 60 women) who self-reported physical activity levels of at least 1,000 MET·min·wk-1 volunteered to participate (age = 22 ± 5 years). DXA BV was determined with the recent equation from Smith-Ryan et al. while criterion BV was determined from UWW with simultaneous RLV. The mean BV values for DXA were not significant compared with UWW in women (p = .80; constant error [CE] = 0.0L), but were significantly higher in the entire sample and men (both p < .05; CE = 0.3 and 0.7L, respectively). The mean BF% values for 4CDXA were not significant for women (p = .56; CE = -0.3%), but were significantly higher in the entire sample and men (both p < .05; CE = 0.9 and 2.0%, respectively). The standard error of estimate (SEE) ranged from 0.6-1.2L and 3.9-4.2% for BV and BF%, respectively, while the 95% limits of agreement (LOA) ranged from ±1.8-2.5L for BV and ±7.9-8.2% for BF%. 4CDXA can be used for determining group mean BF% in physically active men and women. However, due to the SEEs and 95% LOAs, the current study recommends using UWW with simultaneous RLV for BV in a criterion 4C model when high individual accuracy is desired.

Comparison of Bioimpedance and Underwater Weighing Body Fat Percentage Before and Acutely After Exercise at Varying Intensities.

Nickerson, BS, Esco, MR, Kliszczewicz, BM, and Freeborn, TJ. Comparison of bioimpedance and underwater weighing body fat percentage before and acutely after exercise at varying intensities. J Strength Cond Res 31(5): 1395-1402, 2017-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 = -0.9 to 1.1% for 60% HRR; -0.3 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.

Autonomic Responses to an Acute Bout of High-Intensity Body Weight Resistance Exercise vs. Treadmill Running.

The aim of this study was to compare postexercise autonomic nervous system (ANS) recovery between a high-intensity training protocol (HITP) and high-intensity treadmill running (TM) in 10 physically fit males. For each trial, ANS activity was measured through the heart rate variability markers of log-transformed square root of the successive R-R differences (lnRMSSD) and high frequency power (lnHF). These markers were analyzed in 5-minute segments at 5-10 minutes of the pre-exercise period (PRE) and during the postexercise period at 15-20 minutes (POST15-20min), 20-25 minutes (POST20-25min), 25-30 minutes (POST25-30min), and 1 hour (POST60min). Plasma epinephrine (E) and norepinephrine (NE) were also examined at PRE, immediately post exercise (IPE), 1-hour post (1HP), and 2-hour post (2HP). The results of this study demonstrate a significant overall time-dependent decreases in lnRMSSD and lnHF (p = 0.003 and 0.001, respectively) in both trials. Trial-dependent differences were also observed in postexercise lnRMSSD and lnHF measures, HITP being significantly lower than TM (p = 0.002 and 0.000, respectively). lnRMSSD at POST60min-HITP remained significantly lower compared to PRE (p ≤ 0.05). lnHF returned to baseline in HIPT and TM (p = 0.081 and 0.065, respectively). A time-dependent increase in E and NE was observed in both trials at time point IPE when compared to PRE (p ≤ 0.05). E at 1HP and 2HP returned to near resting levels (p = 0.62, p = 0.26), whereas NE remained slightly elevated in both groups (p = 0.003, p = 0.021). A trial-dependent increase was observed with the HITP eliciting a greater E response (p = 0.025) and NE response (p = 0.03). The HITP causes a greater disruption of the ANS than intensity-matched TM exercise.