Comparison of a field-based test to estimate functional threshold power and power output at lactate threshold

It has been proposed that field-based tests (FT) used to estimate functional threshold power (FTP) result in power output (PO) equivalent to PO at lactate threshold (LT). However, anecdotal evidence from regional cycling teams tested for LT in our laboratory suggested that PO at LT underestimated FTP. It was hypothesized that estimated FTP is not equivalent to PO at LT. The LT and estimated FTP were measured in 7 trained male competitive cyclists (VO2max = 65.3 ± 1.6 ml O2·kg(-1)·min(-1)). The FTP was estimated from an 8-minute FT and compared with PO at LT using 2 methods; LT(Δ1), a 1 mmol·L(-1) or greater rise in blood lactate in response to an increase in workload and LT(4.0), blood lactate of 4.0 mmol·L(-1). The estimated FTP was equivalent to PO at LT(4.0) and greater than PO at LT(Δ1). VO2max explained 93% of the variance in individual PO during the 8-minute FT. When the 8-minute FT PO was expressed relative to maximal PO from the VO2max test (individual exercise performance), VO2max explained 64% of the variance in individual exercise performance. The PO at LT was not related to 8-minute FT PO. In conclusion, FTP estimated from an 8-minute FT is equivalent to PO at LT if LT(4.0) is used but is not equivalent for all methods of LT determination including LT(Δ1).     

Time course of the effects of static stretching on cycling economy

Stretching has been implemented as part of the warm-up before physical events and widely thought to promote increased sport performance and decreased injury risk. However, recent research has concluded that static stretching before many exercises inhibits acute power, strength, and sprinting performance. There is little research examining the time course of these effects on moderate intensity cycling. The purpose of this study was to examine the time course of static stretching on cycling economy. The subjects consisted of 5 men and 5 women highly trained endurance cyclists. The first of 3 visits was baseline testing of their cycling VO2max. The second and third visits were either stretching or no stretching before a 30-minute stationary ride at 65% of their VO2max. The stretching condition consisted of four 30-second repetitions of 5 stretches with an average total stretching time of 16 minutes. VO2 demonstrated a significant condition by time interaction with the 5-minute time point being significantly less in the nonstretching condition (32.66 ± 5.35 ml·kg(-1)·min(-1)) than stretching (34.39 ± 5.39 ml·kg(-1)·min(-1)). No other time points were different. Our results demonstrate that static stretching yielded an acute increase in submaximal VO2; therefore, coaches and highly trained endurance cyclists should exclude static stretching immediately before moderate intensity cycling because it reduces acute cycling economy.     

Evaluation of the American College of Sports Medicine submaximal treadmill running test for predicting VO2max

The purpose of this study was to assess the validity of the American College of Sports Medicine's (ACSM's) submaximal treadmill running test in predicting VO2max. Twenty-one moderately well-trained men aged 18-34 years performed 1 maximal treadmill test to determine maximal oxygen uptake (M VO2max) and 2 submaximal treadmill tests using 4 stages of continuous submaximal exercise. Estimated VO2max was predicted by extrapolation to age-predicted maximal heart rate (HRmax) and calculated in 2 ways: using data from all submaximal stages between 110 b·min(-1) and 85% HRmax (P VO2max-All), and using data from the last 2 stages only (P VO2max-2). The measured VO2max was overestimated by 3% on average for the group but was not significantly different to predicted VO2max (1-way analysis of variance [ANOVA] p = 0.695; M VO2max = 53.01 ± 5.38; P VO2max-All = 54.27 ± 7.16; P VO2max-2 = 54.99 ± 7.69 ml·kg(-1)·min(-1)), although M VO2max was not overestimated in all the participants--it was underestimated in 30% of observations. Pearson's correlation, standard error of estimate (SEE), and total error (E) between measured and predicted VO2max were r = 0.646, 4.35, 4.08 ml·kg(-1)·min(-1) (P VO2max-All) and r = 0.642, 4.21, 3.98 ml·kg(-1)·min(-1) (P VO2max-2) indicating that the accuracy in prediction (error) was very similar whether using P VO2max-All or P VO2max-2, with up to 70% of the participants predicted scores within 1 SEE (～4 ml·kg(-1)·min(-1)) of M VO2max. In conclusion, the ACSM equation provides a reasonably good estimation of VO2max with no difference in predictive accuracy between P VO2max-2 and P VO2max-All, and hence, either approach may be equally useful in tracking an individual's aerobic fitness over time. However, if a precise knowledge of VO2max is required, then it is recommended that this be measured directly.     

Maximal lactate steady-state independent of recovery period during intermittent protocol

Barbosa, LF, de Souza, MR, Corrêa Caritá, RA, Caputo, F, Denadai, BS, and Greco, CC. Maximal lactate steady-state independent of recovery period during intermittent protocol. J Strength Cond Res 25(12): 3385-3390, 2011-The purpose of this study was to analyze the effect of the measurement time for blood lactate concentration ([La]) determination on [La] (maximal lactate steady state [MLSS]) and workload (MLSS during intermittent protocols [MLSSwi]) at maximal lactate steady state determined using intermittent protocols. Nineteen trained male cyclists were divided into 2 groups, for the determination of MLSSwi using passive (VO(2)max = 58.1 ± 3.5 ml·kg·min; N = 9) or active recovery (VO(2)max = 60.3 ± 9.0 ml·kg·min; N = 10). They performed the following tests, in different days, on a cycle ergometer: (a) Incremental test until exhaustion to determine (VO(2)max and (b) 30-minute intermittent constant-workload tests (7 × 4 and 1 × 2 minutes, with 2-minute recovery) to determine MLSSwi and MLSS. Each group performed the intermittent tests with passive or active recovery. The MLSSwi was defined as the highest workload at which [La] increased by no more than 1 mmol·L between minutes 10 and 30 (T1) or minutes 14 and 44 (T2) of the protocol. The MLSS (Passive-T1: 5.89 ± 1.41 vs. T2: 5.61 ± 1.78 mmol·L) and MLSSwi (Passive-T1: 294.5 ± 31.8 vs. T2: 294.7 ± 32.2 W; Active-T1: 304.6 ± 23.0 vs. T2: 300.5 ± 23.9 W) were similar for both criteria. However, MLSS was lower in T2 (4.91 ± 1.91 mmol·L) when compared with in T1 (5.62 ± 1.83 mmol·L) using active recovery. We can conclude that the MLSSwi (passive and active conditions) was unchanged whether recovery periods were considered (T1) or not (T2) for the interpretation of [La] kinetics. In contrast, MLSS was lowered when considering the active recovery periods (T2). Thus, shorter intermittent protocols (i.e., T1) to determine MLSSwi may optimize time of the aerobic capacity evaluation of well-trained cyclists.     

A protocol of intermittent exercise (shuttle runs) to train young basketball players

The purpose of this study was to set up a protocol of intermittent exercise to train young basketball players. Twenty-one players were asked to complete (a) an incremental test to determine maximal oxygen uptake (VO2max), the speed at the ventilatory threshold (vthr) and the energy cost of "linear" running (Cr) and (b) an intermittent test composed of 10 shuttle runs of 10-second duration and 30-seconds of recovery (total duration: about 6 minutes). The exercise intensity (the running speed, vi) was set at 130% of vthr. During the intermittent tests, oxygen uptake (VO2) and blood lactate concentration (Lab) were measured. The average pretraining VO2 calculated for a single bout (131 ± 9 ml · min(-1) kg(-1)) was about 2.4 times greater than the subjects' measured VO2max (54.7 ± 4.6 ml · min(-1) · kg(-1)). The net energy cost of running (9.2 ± 0.9 J · m(-1) · kg(-1)) was about 2.4 times higher than that measured at constant "linear" speed (3.9 ± 0.3 J · m(-1) · kg(-1)). The intermittent test was repeated after 7 weeks of training: 9 subjects (control group [CG]) maintained their traditional training schedule, whereas for 12 subjects (experimental group [EG]) part of the training was replaced by intermittent exercise (the same shuttle test as described above). After training, the VO2 measured during the intermittent test was significantly reduced (p < 0.05) in both groups (-10.9% in EG and - 4.6 in CG %), whereas Lab decreased significantly only for EG (-31.5%). These data suggest that this training protocol is effective in reducing lactate accumulation in young basketball players.     

Effects of aging and training status on ventilatory response during incremental cycling exercise

The aim of this study was to examine the effect of aging and training status on ventilatory response during incremental cycling exercise. Eight young (24 ± 5 years) and 8 older (64 ± 3 years) competitive cyclists together with 8 young (27 ± 4 years) and 8 older (63 ± 2 years) untrained individuals underwent a continuous incremental cycling test to exhaustion to determine ventilatory threshold (VT), respiratory compensation point (RCP), and maximal oxygen uptake (VO?max). In addition, the isocapnic buffering (IB) phase was calculated together with the hypocapnic hyperventilation. Ventilatory threshold occurred at similar relative exercise intensities in all groups, whereas RCP was recorded at higher intensities in young and older cyclists compared to the untrained subjects. The IB phase, reported as the difference between VT and RCP and expressed either in absolute (ml·min?1·kg?1 VO?) or in relative terms, was greater (p < 0.01) in both young and older trained cyclists than in untrained subjects, who were also characterized by a lower exercise capacity. Isocapnic buffering was particularly small in the older untrained volunteers. Although young untrained and older trained subjects had a similar level of VO?max, older athletes exhibited a larger IB. In addition, a higher absolute but similar relative IB was observed in young vs. older cyclists, despite a higher VO?max in the former. In conclusion, the present study shows that aging is associated with a reduction of the IB phase recorded during an incremental exercise test. Moreover, endurance training induces adaptations that result in an enlargement of the IB phase independent of age. This information can be used for the characterization and monitoring of the physiological adaptations induced by endurance training.     

Time course for recovery of peak aerobic power after blood donation

Peak aerobic power (VO2peak) is decreased after blood donation, but the time course for full recovery is unknown. We measured VO2peak and exercise time to fatigue before and weekly for 4 weeks after 450-ml blood donation at a blood donor clinic, to determine the time course of recovery. Twelve moderately active individuals (2 women, 10 men; 24.3 ± 5.2 years) of average aerobic fitness (based on their VO2peak relative to normative values) completed VO2peak exercise tests before donation, the day after donation, and at weekly intervals for 4 weeks after donation. VO2peak was determined by an incremental exercise test on a cycle ergometer. At baseline, mean absolute and relative VO2peak values were 4.06 ± 0.92 L·min(-1) and 46.6 ± 7.0 ml·kg(-1)·min(-1), respectively. VO2peak was significantly decreased on day 1 (3.85 ± 0.89 L·min(-1); 44.0 ± 6.5 ml·kg(-1)·min(-1)) and during week 2 (3.91 ± 0.97 L·min(-1); 44.5 ± 7.2 ml·kg(-1)·min(-1)) after blood donation (p < 0.05), and recovered at week 3 after donation. Time to fatigue and peak heart rate were not significantly affected by blood donation. We conclude that blood donation causes a significant decrease in VO2peak for between 2 and 3 weeks. The practical application of this study is that aerobic power in people of average fitness will be decreased, up to 3 weeks after donating blood. Despite this, there is no effect of blood donation on performance as measured by time to fatigue during an incremental test on a cycle ergometer.     

The effects of static stretching on running economy and endurance performance in female distance runners during treadmill running

Stretching can lead to decreased muscle stiffness and has been associated with decreased force and power production. The purpose of this study was to investigate the acute effects of static stretching (SS) on running economy and endurance performance in trained female distance runners. Twelve long distance female (30 ± 9 years) runners were assessed for height (159.4 ± 7.4 cm), weight (54.8 ± 7.2 kg), % body fat (19.7 ± 2.8%), and maximal oxygen consumption (VO2max: 48.4 ± 5.1 ml·kg(-1)·min(-1)). Participants performed 2 sessions of 60-minute treadmill runs following a randomly assigned SS protocol or quiet sitting (QS). During the first 30 minutes (running economy), expired gases, heart rate (HR), and rating of perceived exertion (RPE) were recorded while the participant ran at 65% VO2max. During the final 30 minutes (endurance performance), distance covered, speed, HR, and RPE were recorded while the participant attempted to cover as much distance as possible. Repeated measures analyses of variance were performed on the data. Significance was accepted at p < 0.05. The SS measured by sit-and-reach increased flexibility (SS: 29.8 ± 8.3 vs. QS: 33.1 ± 8.1 cm) but had no effect on running economy (VO2: 33.7 ± 3.2 vs. 33.8 ± 2.3 ml·kg(-1)·min(-1)), calorie expenditure (270 ± 41 vs. 270 ± 41 kcal), HR (157 ± 10 vs. 160 ± 12 b·min(-1)), or endurance performance (5.5 ± 0.6 vs. 5.5 ± 0.7 km). These findings indicated that stretching did not have an adverse effect on endurance performance in trained women. This suggests that the performance decrements previously associated with stretching may not occur in trained women.     

Time to exhaustion and time spent at a high percentage of VO2max in severe intensity domain in children and adults

The aim of the study was to compare time spent at a high percentage of VO2max (>90% of VO2max) (ts90%), time to achieve 90% of VO2max (ta90%), and time to exhaustion (TTE) for exercise in the severe intensity domain in children and adults. Fifteen prepubertal boys (10.3 ± 0.9 years) and 15 men (23.5 ± 3.6 years) performed a maximal graded exercise to determine VO2max, maximal aerobic power (MAP) and power at ventilatory threshold (PVTh). Then, they performed 4 constant load exercises in a random order at PVTh plus 50 and 75% of the difference between MAP and PVTh (PΔ50 and PΔ75) and 100 and 110% of MAP (P100 and P110). VO2max was continuously monitored. The P110 test was used to determine maximal accumulated oxygen deficit (MAOD). No significant difference was found in ta90% between children and adults. ts90% and TTE were not significantly different between children and adults for the exercises at PΔ50 and PΔ75. However, ts90% and TTE during P100 (p < 0.05 and p < 0.01, respectively) and P110 (p < 0.001) exercises were significantly shorter in children. Children had a significantly lower MAOD than adults (34.3 ± 9.4 ml · kg vs. 53.6 ± 11.1 ml · kg). A positive relationship (p < 0.05) was obtained between MAOD and TTE values during the P100 test in children. This study showed that only for intensities at, or higher than MAP, lower ts90% in children was linked to a reduced TTE, compared to adults. Shorter TTE in children can partly be explained by a lower anaerobic capacity (MAOD). These results give precious information about exercise intensity ranges that could be used in children's training sessions. Moreover, they highlight the implication of both aerobic and anaerobic processes in endurance performances in both populations.     

Muscle fiber recruitment and the slow component of O2 uptake: constant work rate vs. all-out sprint exercise

The slow component of pulmonary O(2) uptake (Vo(2)) during constant work rate (CWR) high-intensity exercise has been attributed to the progressive recruitment of (type II) muscle fibers. We tested the following hypotheses: 1) the Vo(2) slow component gain would be greater in a 3-min all-out cycle test than in a work-matched CWR test, and 2) the all-out test would be associated with a progressive decline, and the CWR test with a progressive increase, in muscle activation, as estimated from the electromyogram (EMG) of the vastus lateralis muscle. Eight men (aged 21-39 yr) completed a ramp incremental test, a 3-min all-out test, and a work- and time-matched CWR test to exhaustion. The maximum Vo(2) attained in an initial ramp incremental test (3.97 ± 0.83 l/min) was reached in both experimental tests (3.99 ± 0.84 and 4.03 ± 0.76 l/min for all-out and CWR, respectively). The Vo(2) slow component was greater (P < 0.05) in the all-out test (1.21 ± 0.31 l/min, 4.2 ± 2.2 ml·min(-1)·W(-1)) than in the CWR test (0.59 ± 0.22 l/min, 1.70 ± 0.5 ml·min(-1)·W(-1)). The integrated EMG declined by 26% (P < 0.001) during the all-out test and increased by 60% (P < 0.05) during the CWR test from the first 30 s to the last 30 s of exercise. The considerable reduction in muscle efficiency in the all-out test in the face of a progressively falling integrated EMG indicates that progressive fiber recruitment is not requisite for development of the Vo(2) slow component during voluntary exercise in humans.     

Predicting maximal aerobic capacity (VO2max) from the critical velocity test in female collegiate rowers

The objective of this study was to examine the relationship between the critical velocity (CV) test and maximal oxygen consumption (VO2max) and develop a regression equation to predict VO2max based on the CV test in female collegiate rowers. Thirty-five female (mean ± SD; age, 19.38 ± 1.3 years; height, 170.27 ± 6.07 cm; body mass, 69.58 ± 0.3 1 kg) collegiate rowers performed 2 incremental VO2max tests to volitional exhaustion on a Concept II Model D rowing ergometer to determine VO2max. After a 72-hour rest period, each rower completed 4 time trials at varying distances for the determination of CV and anaerobic rowing capacity (ARC). A positive correlation was observed between CV and absolute VO2max (r = 0.775, p < 0.001) and ARC and absolute VO2max (r = 0.414, p = 0.040). Based on the significant correlation analysis, a linear regression equation was developed to predict the absolute VO2max from CV and ARC (absolute VO2max = 1.579[CV] + 0.008[ARC] - 3.838; standard error of the estimate [SEE] = 0.192 L·min(-1)). Cross validation analyses were performed using an independent sample of 10 rowers. There was no significant difference between the mean predicted VO2max (3.02 L·min(-1)) and the observed VO2max (3.10 L·min(-1)). The constant error, SEE and validity coefficient (r) were 0.076 L·min(-1), 0.144 L·min(-1), and 0.72, respectively. The total error value was 0.155 L·min(-1). The positive relationship between CV, ARC, and VO2max suggests that the CV test may be a practical alternative to measuring the maximal oxygen uptake in the absence of a metabolic cart. Additional studies are needed to validate the regression equation using a larger sample size and different populations (junior- and senior-level female rowers) and to determine the accuracy of the equation in tracking changes after a training intervention.     

Development of a submaximal test to predict elliptical cross-trainer VO2max

The purpose of this study was to develop an equation to predict VO2max from a submaximal elliptical cross-trainer test. Fifty-four apparently healthy subjects (25 men and 29 women, mean +/- SD age: 29.5 +/- 7.1 years, height: 173.3 +/- 12.6 cm, weight: 72.3 +/- 7.9 kg, percent body fat: 17.3 +/- 5.0%, and elliptical cross-trainer VO2max: 43.9 +/- 7.2 ml x kg(-1) x min(-1)) participated in the study and were randomly assigned to an original sample group (n = 40) and a cross-validation group (n = 14). Each subject completed an elliptical cross-trainer submaximal (3 5-minute submaximal stages) and a VO2max test on the same day, with a 15-minute rest period in between. Stepwise multiple regression analyses were used to develop an equation for estimating elliptical cross-trainer VO2max from the data of the original sample group. The accuracy of the equation was tested by using data from the cross-validation group. Because there was no shrinkage in R2 between the original sample group and the cross-validation group, data were combined in the final prediction equation (R2 = 0.732, standard error of the estimate = 3.91 ml x kg(-1) x min(-1), p < 0.05): VO2max = 73.676 + 7.383(gender) - 0.317(weight) + 0.003957(age x cadence) - 0.006452(age x heart rate at stage 2). The correlation coefficient between the predicted and measured VO2max values was r = 0.86. Dependent t-tests resulted in no significant differences (p > 0.05) between predicted (43.8 ml x kg(-1) x min(-1)) and measured (43.9 ml x kg(-1) x min(-1)) VO2max measurements. Results indicate that the protocol and equation developed in the current study can be used by exercise professionals to provide acceptably accurate estimates of VO2max in non-laboratory-based settings.     

Validation of the Cosmed Fitmate for prediction of maximal oxygen consumption

The main purpose of this study was to assess the validity of the Cosmed Fitmate (FM) for the prediction of maximal oxygen consumption (VO(2)max). In addition, this study examined whether measuring submaximal VO(2), rather than predicting it, can improve upon the prediction of VO(2)max. Participants for the study were 48 young to middle-age adults (32 men, 16 women), with a mean age of 31 yr. Each participant completed a submaximal and maximal treadmill test on 2 separate occasions. During the submaximal test, VO(2)max was predicted using the FM. This device extrapolates the linear regression relating heart rate (HR) and measured VO(2) at submaximal work rates to age-predicted maximum HR (HR = 220 - age). The criterion measure was obtained using a graded, maximal treadmill test, with VO(2) measured by the Douglas bag (DB) method. There was no significant difference between VO(2)max predicted by the FM and VO(2)max measured by the DB method. The results of this study showed that a strong positive correlation (r = 0.897) existed between VO(2)max predicted by the FM and VO(2)max measured by the DB method, with a standard error of the estimate (SEE) = 3.97 ml·kg(-1)·min(-1). There was a significant difference in VO(2)max predicted by the American College of Sports Medicine (ACSM) metabolic equations and VO(2)max measured by the DB method (p = 0.01). The correlation between these variables was r = 0.758 (SEE = 5.26 ml·kg(-1)·min(-1)). These findings indicate that a small, portable, and easy-to-use metabolic system provides valid estimates of VO(2)max, and improves upon predictive accuracy, compared to using generalized ACSM metabolic equations.     

Effects of dynamic stretching on energy cost and running endurance performance in trained male runners

The purpose of this study was to examine the effects of dynamic stretching on running energy cost and endurance performance in trained male runners. Fourteen male runners performed both a 30-minute preload run at 65% VO2max and a 30-minute time trial to assess running energy cost and performance, respectively. The subjects repeated both the trials after either 15 minutes of dynamic stretching (i.e., experimental condition) or quiet sitting (i.e., control condition) while the order was balanced between the subjects to avoid any order effect. The total calories expended were determined for the 30-minute preload run, whereas the distance covered was measured in the time trial. Average resting VO2 increased significantly (p < 0.05) after dynamic stretching (prestretch: 6.2 ± 1.7 vs. poststretch: 8.4 ± 2.1 ml·kg(-1)·min(-1)) but not during the quiet-sitting condition. Caloric expenditure was significantly higher during the 30-minute preload run for the stretching (416.3 ± 44.9 kcal) compared with that during the quiet sitting (399.3 ± 50.4 kcal) (p < 0.05). There was no difference in the distance covered after quiet sitting (6.3 ± 1.1 km) compared with that for the stretching condition (6.1 ± 1.3 km). These findings suggest that dynamic stretching does not affect running endurance performance in trained male runners.     

Effects of prolonged exercise at a similar percentage of maximal oxygen consumption in trained and untrained subjects

Six trained male cyclists and six untrained but physically active men participated in this study to test the hypothesis that the use of percentage maximal oxygen consumption (%VO2max) as a normalising independent variable is valid despite significant differences in the absolute VO2max of trained and untrained subjects. The subjects underwent an exercise test to exhaustion on a cycle ergometer to determine VO2max and lactate threshold. The subjects were grouped as trained (T) if their VO2max exceeded 60 ml.kg-1.min-1, and untrained (UT) if their VO2max was less than 50 ml.kg-1.min-1. The subjects were required to exercise on the ergometer for up to 40 min at power outputs that corresponded to approximately 50% and 70% VO2max. The allocation of each exercise session (50% or 70% VO2max) was random and each session was separated by at least 5 days. During these tests venous blood was taken 10 min before exercise (- 10 min), just prior to the commencement of exercise (0 min), after 20 min of exercise (20 min), at the end of exercise and 10 min postexercise (+ 10 min) and analysed for concentrations of cortisol, [Na+], [K+], [Cl-], glucose, free fatty acid, lactate [la-], [NH3], haemoglobin [Hb] and for packed cell volume. The oxygen consumption (VO2) and related variables were measured at two time intervals (14-15 and 34-35 min) during the prolonged exercise tests. Rectal temperature was measured throughout both exercise sessions. There was a significant interaction effect between the level of training and exercise time at 50% VO2max for heart rate (fc) and venous [la-].(ABSTRACT TRUNCATED AT 250 WORDS)     

Implementing a mathematical model to compare oxygen uptake kinetics between cyclists and noncyclists during steady state

The purpose was to compare a mathematical model of oxygen uptake and bioenergetic systems to an experimental protocol. Twelve (N = 12) noncyclists (NC), age (21.8 ± 1.4 years), and 8 (N = 8) cyclists (C), age (30.5 ± 5.7 years), were subjects. All subjects signed an informed consent. Oxygen consumption (VO2, ml·kg?1·min?1) was measured with steady-state VO2 requirements and responses determined using the mathematical model from the following equation: VO2 (WR) = VO2 (rest) + VO2 (unloading pedaling) + α.WR; ΔVO2(t, WR) = ΔVO2 (WR) = [1-e[-(t-td)/tO2]. Exercise means (SD) included the following: VO2NC(WR) = 48.4 (16.6) ml?1·min?1 for NCs and VO2C(WR) = 56.4 (24.95) ml?1·min?1 for Cs ; ΔVO2C(t, WR) = 6:38 ml?1·min?1 for NCs and ΔVO2C(t, WR) = 7.44 ml?1·min?1 for Cs. The correlation between the mathematical model and actual measure was statistically significant (p < 0.01) with a coefficient of r = 0.947. The experimental protocol was significantly associated with the mathematical model. This allows for a quantitative analysis and safe prediction of steady-state oxygen uptake conditions on populations before exposure to exercising conditions. Through more precise analysis of conditions, greater specificity of training may lead to more predictable adaptation outcomes.     

Comparison of caloric expenditure in intermittent and continuous walking bouts

This study compared the caloric expenditure of 30 consecutive minutes (30 minute) of moderate intensity walking with 3 intermittent 10-minute bouts (3 x 10 minutes) of moderate intensity walking in healthy, unfit men (40-49 years). Screening consisted of VO(2)max testing, which was measured using the Balke graded exercise test. Criteria for participation in this study included a measured VO(2)max less than 33.8 ml.kg(-1).min(-1) (<25th percentile for cardiorespiratory fitness). Twenty men participated in this study. Testing consisted of 4 trials with a minimum of 5 days between each trial. The 30-minute and 3 x 10-minute bouts were each performed twice to measure test-retest reliability. Once reliability was found, the 2 30-minute and the 2 3 x 10-minute trials were averaged for further data analyses; t-tests showed no significant differences in energy expenditure between 1 continuous 30-minute and the 3 x 10-minute walking bouts at 274 and 279 kcal (p = 0.09), respectively. Thus, 3 x 10-minute intermittent walking bouts throughout the day are equally beneficial, in terms of caloric expenditure, as 1 30-minute continuous walking bout.     

A new single work bout test to estimate critical power and anaerobic work capacity

The purpose of this study was to develop a 3-minute, all-out test protocol using the Monark cycle ergometer for estimating the critical power (CP) and anaerobic work capacity (AWC) with the resistance based on body weight. Twelve moderately trained adults (mean age ± SD = 23.2 ± 3.5 years) performed an incremental cycle ergometer test to exhaustion. The CP and AWC were estimated from the original work limit (W(lim)) vs. time limit (T(lim)) relationship (CP(PT)) and a 3-minute all-out test (CP(3min)) against a fixed resistance and compared with the CP and AWC estimated from the new 3-minute tests on the Monark cycle ergometer (CP(3.5%) and CP(4.5%)). The resistance values for the CP(3.5%) and CP(4.5%) tests were set at 3.5 and 4.5% of the subject's body weight (kilograms). The results indicated that there were no significant differences (p > 0.05) among mean CP values for CP(PT) (178 ± 47 W), CP(3.5%) (173 ± 40 W), and CP(4.5%) (186 ± 44 W). The mean CP(3min) (193 ± 54 W), however, was significantly greater than CP(PT) and CP(3.5%). There were no significant differences in AWC for the CP(PT) (13,412 ± 6,247 J), CP(3min) (10,895 ± 2,923 J), and CP(4.5%) (9,842 ± 4,394 J). The AWC values for the CP(PT) and CP(3min), however, were significantly greater than CP(3.5%) (8,357 ± 2,946 J). The results of this study indicated that CP and AWC could be estimated from a single 3-minute work bout test on the Monark cycle ergometer with the resistance set at 4.5% of the body weight. A single work bout test with the resistance based on the individual's body weight provides a practical and accessible method to estimate CP and AWC.     

Influence of carbohydrate dosage on exercise performance and glycogen metabolism

This study was undertaken to examine the effects of ingestion of carbohydrate (CHO) solutions of 0 (WP), 6 (CHO-6), 12 (CHO-12), and 18 g CHO/100 ml (CHO-18) on performance and muscle glycogen use. Ten trained cyclists performed five 120-min cycling trials. The first 105 min of each trial was at 70% of maximal O2 consumption (VO2max), and the final 15 min was an all-out performance ride on an isokinetic cycle ergometer equipped to measure total work output. In one of the trials (CHO-12I) the submaximal portion of the ride consisted of seven 15-min rides at 70% of VO2max with a 3-min rest between each ride. Every 15 min the men consumed 8.5 ml.kg-1.h-1 (approximately 150 ml) of one of the four test solutions. Venous blood samples were obtained every 15 min for glucose and insulin. Muscle biopsies were obtained from the vastus lateralis at 0 and 105 min in the WP and the CHO-12 continuous and intermittent trials. Biopsy samples were assayed for glycogen and sectioned and stained for myosin adenosinetriphosphatase and glycogen for single fiber depletion measurements. There were no differences in glycogen use (86.7 +/- 6.0, 75.5 +/- 7.9, and 83.5 +/- 5.5 mmol/kg for the WP, CHO-12C, and CHO-12I, respectively) or depletion patterns between the WP and the two CHO-12 trials. Blood glucose was significantly elevated in both the CHO-12 trials and in the CHO-18 trial compared with the WP trial.(ABSTRACT TRUNCATED AT 250 WORDS)     

A low carbohydrate-protein supplement improves endurance performance in female athletes

The purpose of this study was to investigate if a low mixed carbohydrate (CHO) plus moderate protein (PRO) supplement, provided during endurance exercise, would improve time to exhaustion (TTE) in comparison to a traditional 6% CHO supplement. Fourteen (n = 14) trained female cyclists and triathletes cycled on 2 separate occasions for 3 hours at intensities varying between 45 and 70% VO2max, followed by a ride to exhaustion at an intensity approximating the individual's ventilatory threshold average 75.06% VO2max. Supplements (275 mL) were provided every 20 minutes during exercise and were composed of a CHO mixture (1% each of dextrose, fructose, and maltodextrin) + 1.2% PRO (CHO + PRO) or 6% dextrose only (CHO). The TTE was significantly greater with CHO + PRO in comparison to with CHO (49.94 ± 7.01 vs. 42.36 ± 6.21 minutes, respectively, p < 0.05). Blood glucose was significantly lower during the CHO + PRO trial (4.07 ± 0.12 mmol · L(-1)) compared to during the CHO trial (4.47 ± 0.12 mmol · L(-1)), with treatment × time interactions occurring from 118 minutes of exercise until exhaustion (p < 0.05). Results from the present study suggest that the addition of a moderate amount of PRO to a low mixed CHO supplement improves endurance performance in women above that of a traditional 6% CHO supplement. Improvement in performance occurred despite CHO + PRO containing a lower CHO and caloric content. It is likely that the greater performance seen with CHO + PRO was a result of the CHO-PRO combination and the use of a mixture of CHO sources.