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.     

Familial resemblance in maximal heart rate, blood lactate and aerobic power

There are considerable interindividual differences in maximal oxygen uptake per kilogram of body weight (VO2 max/kg), maximal heart rate (max HR) and maximal blood lactate (max blood La) measured during a progressive exercise test. The aim of the study was to quantify the familial relationships for these variables. Parents and children of 38 families of French-Canadian descent were submitted to a modified Balke treadmill test. VO2 max/kg and max HR were the highest values reached during the test for 1 min. Max blood La was obtained from a blood sample taken 2 min after the test. The effects of age and sex were significant for max blood La and VO2 max/kg in each generation. Scores were thus adjusted through multiple regression procedures (age + sex + age X sex + age2), yielding residuals which were submitted to further analysis. Intraclass correlations (ri) were significant in pairs of sibs for max blood La and max HR, i.e. 0.28 (p less than 0.01) and 0.43 (p less than 0.05), respectively. For VO2 max/kg, pairs of spouses and sibs were about similarly correlated (ri = 0.20 and 0.15; p less than 0.05). Data suggested that children were more related to their mother than to their father for VO2 max/kg, VO2 max/kg of fat-free weight, and particularly for max HR. It was concluded that familial resemblance and heritability estimates for maximal aerobic power, max HR and max blood La were quite low and generally nonsignificant. Correlations between biological sibs were, however, consistently significant for max HR and max blood La. The suggestion of a maternal effect in maximal aerobic power should be further investigated.     

Heart rate variability and body temperature during the sleep onset period

Heart rate variability (HRV) and body temperature during the sleep onset period was examined. The core body temperature and electrocardiogram were recorded continuously beginning 1 h before lights out (LO) until the end of the first rapid eye movement sleep (REM) in 14 young healthy subjects. HRV was calculated by the MemCalc method. The time course changes in body temperature and HRV was analyzed before and after sleep onset, and during the following eight consecutive phases: the 60 min before LO, the 30 min before LO, LO, first stage 2 (sleep onset), first slow wave sleep (SWS), stage 2 just before REM, start of REM, and end of REM. A clear decline was observed in the ratio of the low frequency (LF) to high frequency (HF) component of HRV (LF/HF), normalized LF (LF/(LF + HF)), and body temperature prior to sleep onset both in the time course of the sleep onset period and in the consecutive phases. The HF increased prior to sleep onset in the consecutive phases, while no clear increase was observed in the time course of sleep onset period. Changes in LF/(LF + HF) and LF/HF preceded SWS and REM. These results suggest the existence of a strong coupling between the cardiac autonomic nervous system and body temperature at the sleep onset period that may not be circadian effects. Furthermore, LF/(LF + HF) and LF/HF may possibly anticipate sleep and the onset of each sleep stage.

     

Cardiac parasympathetic regulation: respective associations with cardiorespiratory fitness and training load

The objective of this study was to establish the separate associations between parasympathetic modulations of the heart [evaluated through heart rate (HR) variability (HRV) indexes and postexercise HR recovery (HRR) indexes] with cardiorespiratory fitness and training load. We have measured cardiorespiratory fitness through peak oxygen consumption (Vo2 max) and estimated weekly training load with the Baecke sport score in 55 middle-aged individuals (30.8 +/- 1.8 yr, body mass index 24.5 +/- 0.4 kg/m2). HRV indexes were analyzed at rest under controlled breathing, and HRR was estimated from HR curve fitting after maximal exercise or from measurements of the number of beats recovered at 60 s after exercise. Multiple linear regressions were used to investigate the separate relationships between vagal-related HRV indexes and Vo2 max and Baecke scores. On the basis of their Vo2 max and Baecke scores, subjects were classified as fit or unfit and as low trained (LT) or moderately trained (MT), which yielded four groups: UnfitLT, UnfitMT, FitLT, and FitMT. Vagal-related HRV indexes were positively correlated with Vo2 max (P < 0.05) but not with Baecke scores. In contrast, HRR indexes were related to Baecke scores (P < 0.05) but not with Vo2 max. FitLT and FitMT had significantly higher (P < 0.05) normalized vagal-related HRV indexes than UnfitLT and UnfitMT, but HRR did not change. Moderate training was associated with significantly lower HRR indexes both in UnfitMT and FitMT compared with UnfitLT and FitLT, but there was no difference in vagal-related HRV indexes. These results indicate that vagal-related HRV indexes are related more to cardiorespiratory fitness, whereas HRR appears to be better associated with training load.     

Detraining increases body fat and weight and decreases VO2peak and metabolic rate

Competitive collegiate swimmers commonly take a month off from swim training after their last major competition. This abrupt cessation of intense physical training has not been well studied and may lead to physiopsychological decline. The purpose of this investigation was to examine the effects of swim detraining (DT) on body composition, aerobic fitness, resting metabolism, mood state, and blood lipids in collegiate swimmers. Eight healthy endurance-trained swimmers (V(O2)peak, 46.7 ± 10.8 ml · kg(-1) · min(-1)) performed 2 identical test days, 1 in the trained (TR) state and 1 in the detrained (~5 weeks) state (DT). Body composition and circumferences, maximal oxygen consumption (V(O2)peak), resting metabolism (RMR), blood lipids, and mood state were measured. After DT, body weight (TR, 68.9 ± 9.7 vs. DT, 69.8 ± 9.8 kg; p = 0.03), fat mass (TR, 14.7 ± 7.6 vs. DT, 16.5 ± 7.4 kg; p = 0.001), and waist circumference (TR, 72.7 ± 3.1 vs. DT, 73.8 ± 3.6 cm; p = 0.03) increased, whereas V(O2)peak (TR, 46.7 ± 10.8 vs. DT, 43.1 ± 10.3 ml · kg(-1) · min(-1); p = 0.02) and RMR (TR, 1.34 ± 0.2 vs. DT, 1.25 ± 0.17 kcal · min(-1); p = 0.008) decreased, and plasma triglycerides showed a trend to increase (p = 0.065). Our data suggest that DT after a competitive collegiate swim season adversely affects body composition, fitness, and metabolism. Athletes and coaches need to be aware of the negative consequences of detraining from swimming, and plan off-season training schedules accordingly to allow for adequate rest/recovery and prevent overuse injuries. It's equally important to mitigate the negative effects on body composition, aerobic fitness and metabolism so performance may continue to improve over the long term.     

Fit women are not able to use the whole aerobic capacity during aerobic dance

Edvardsen, E, Ingjer, F, and B?, K. Fit women are not able to use the whole aerobic capacity during aerobic dance. J Strength Cond Res 25(12): 3479-3485, 2011-This study compared the aerobic capacity during maximal aerobic dance and treadmill running in fit women. Thirteen well-trained female aerobic dance instructors aged 30 ± 8.17 years (mean ± SD) exercised to exhaustion by running on a treadmill for measurement of maximal oxygen uptake (VO(2)max) and peak heart rate (HRpeak). Additionally, all subjects performed aerobic dancing until exhaustion after a choreographed videotaped routine trying to reach the same HRpeak as during maximal running. The p value for statistical significance between running and aerobic dance was set to ≤0.05. The results (mean ± SD) showed a lower VO(2)max in aerobic dance (52.2 ± 4.02 ml·kg·min) compared with treadmill running (55.9 ± 5.03 ml·kg·min) (p = 0.0003). Further, the mean ± SD HRpeak was 182 ± 9.15 b·min in aerobic dance and 192 ± 9.62 b·min in treadmill running, giving no difference in oxygen pulse between the 2 exercise forms (p = 0.32). There was no difference in peak ventilation (aerobic dance: 108 ± 10.81 L·min vs. running: 113 ± 11.49 L·min). In conclusion, aerobic dance does not seem to be able to use the whole aerobic capacity as in running. For well endurance-trained women, this may result in a lower total workload at maximal intensities. Aerobic dance may therefore not be as suitable as running during maximal intensities in well-trained females.     

Ambulatory estimates of maximal aerobic power from foot -ground contact times and heart rates in running humans.

Seeking to develop a simple ambulatory test of maximal aerobic power (VO(2 max)), we hypothesized that the ratio of inverse foot-ground contact time (1/t(c)) to heart rate (HR) during steady-speed running would accurately predict VO(2 max). Given the direct relationship between 1/t(c) and mass-specific O(2) uptake during running, the ratio 1/t(c). HR should reflect mass-specific O(2) pulse and, in turn, aerobic power. We divided 36 volunteers into matched experimental and validation groups. VO(2 max) was determined by a treadmill test to volitional fatigue. Ambulatory monitors on the shoe and chest recorded foot-ground contact time (t(c)) and steady-state HR, respectively, at a series of submaximal running speeds. In the experimental group, aerobic fitness index (1/t(c). HR) was nearly constant across running speed and correlated with VO(2 max) (r = 0.90). The regression equation derived from data from the experimental group predicted VO(2 max) from the 1/t(c). HR values in the validation group within 8.3% and 4.7 ml O(2) x kg(-1) x min(-1) (r = 0.84) of measured values. We conclude that simultaneous measurements of foot-ground constant times and heart rates during level running at a freely chosen constant speed can provide accurate estimates of maximal aerobic power.     

The influence of exercise intensity on the power spectrum of heart rate variability

The power spectral analysis of R-R interval variability (RRV) has been estimated by means of an autoregressive method in seven sedentary males at rest, during steady-state cycle exercise at 21 percent maximal oxygen uptake (%VO2max), SEM 2%, 49% VO2max, SEM 2% and 70% VO2max, SEM 2% and during recovery. The RRV, i.e. the absolute power of the spectrum, decreased 10, 100 and 500 times in the three exercise intensities, returning to resting value during recovery. In the RRV power spectrum three components have been identified: (1) high frequency peak (HF), central frequency about 0.24 Hz at rest and recovery, and 0.28 Hz, SEM 0.02, 0.37 Hz, SEM 0.03 and 0.48 Hz, SEM 0.06 during the three exercise intensities, respectively; (2) low frequency peak (LF), central frequency about 0.1 Hz independent of the metabolic state; (3) very low frequency component (VLF), less than 0.05 Hz, no peak observed. The HF peak power, as a percentage of the total power (HF%), averaged 16%, SEM 5% at rest and did not change during exercise, whereas during recovery it decreased to 5%-10%. The LF% and VLF% were about 50% and 35% at rest and during low exercise intensity, respectively. At higher intensities, LF% decreased to 16% and VLF% increased to 70%. During recovery a return to resting values occurred. The HF component may reflect the increased respiratory rate and the LF peak changes the resetting of the baroreceptor reflex with exercise. The hypothesis is made that VLF fluctuations in heart rate might be partially mediated by the sympathetic system.     

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.     

Aging and factors related to running economy

The purpose of this study was to investigate the relationship that age has on factors affecting running economy (RE) in competitive distance runners. Fifty-one male and female subelite distance runners (Young [Y]: 18-39 years [n = 18]; Master [M]: 40-59 years [n = 22]; and Older [O]: 60-older [n = 11]) were measured for RE, step rate, lactate threshold (LT), VO2max, muscle strength and endurance, flexibility, power, and body composition. An RE test was conducted at 4 different velocities (161, 188, 215, and 241 m·min(-1)), with subjects running for 5 minutes at each velocity. The steady-state VO2max during the last minute of each stage was recorded and plotted vs. speed, and a regression equation was formulated. A 1 × 3 analysis of variance revealed no differences in the slopes of the RE regression lines among age groups (y = 0.1827x - 0.2974; R2 = 0.9511 [Y]; y = 0.1988x - 1.0416; R2 = 0.9697 [M]; y = 0.1727x + 3.0252; R2 = 0.9618 [O]). The VO2max was significantly lower in the O group compared to in the Y and M groups (Y = 64.1 ± 3.2; M = 56.8 ± 2.7; O = 44.4 ± 1.7 mlO2·kg(-1)·min(-1)). The maximal heart rate and velocity @ LT were significantly different among all age groups (Y = 197 ± 4; M = 183 ± 2; O = 170 ± 6 b·min(-1) and Y = 289.7 ± 27.0; M = 251.5 ± 32.9; O = 212.3 ± 24.6 m·min(-1), respectively). The VO2max @ LT was significantly lower in the O group compared to in the Y and M groups (Y = 50.3 ± 2.0; M = 48.8 ± 2.9; O = 34.9 ± 3.2 mlO2·kg(-1)·min(-1)). The O group was significantly lower than in the Y and M groups in flexibility, power, and upper body strength. Multiple regression analyses showed that strength and power were significantly related to running velocity. The results from this cross-sectional analysis suggest that age-related declines in running performance are associated with declines in maximal and submaximal cardiorespiratory variables and declines in strength and power, not because of declines in running economy.     

Measuring aerobic cycling power as an assessment of childhood fitness

The emergence of obesity, insulin resistance, and type 2 diabetes in children requires a rational, effective public health response. Physical activity remains an important component of prevention and treatment for obesity, type 2 diabetes, and insulin resistance. Studies in adults show cardiovascular fitness to be more important than obesity in predicting insulin resistance. We recently demonstrated that a school-based fitness intervention in children who are overweight could improve cardiovascular fitness, body composition, and insulin sensitivity, but it remains unclear whether accurate assessment of fitness could be performed at the school or outside of an exercise laboratory. To determine whether new methodology using measurement of cycling power could estimate cardiovascular aerobic fitness (as defined by VO2max) in middle school children who were overweight. Thirty-five middle school children (mean age 12 +/- 0.4 years) who were overweight underwent testing on a power sensor-equipped Cycle Ops indoor cycle (Saris Cycling Group, Fitchburg, WI) as well as body composition by dual x-ray absorptiometry and VO2max by treadmill determination. Insulin sensitivity was also estimated by fasting glucose and insulin. Maximal heart rate (MHR) was determined during VO2max testing, and power produced at 80%MHR was recorded. Spearman's rank correlation was performed to evaluate associations. Mean power determined on the indoor cycle at 80% of MHR was 129 +/- 77 watts, and average power at 80% MHR divided by total body weight was 1.5 +/- 0.5. A significant correlation between watts and total body weight was seen for VO2max (P = 0.03), and significant negative correlation was seen between watts/total body weight and fasting insulin (P < 0.05). Among middle school children who were overweight, there was a significant relationship between the power component of fitness and cardiovascular aerobic fitness (measured by VO2max). This more accessible and less intimidating field-based measure of power may prove useful in predicting changes in cardiovascular fitness. Thus, accurate assessment of childhood aerobic fitness may be achievable by measurement of power, possibly within the school environment, at substantially less cost and effort than laboratory-based measurements.     

Exercise and blood lymphocyte subset responses: intensity, duration, and subject fitness effects

This study examined the effect of exercise intensity and duration on the percent blood lymphocytes in men of low [LF; maximal O2 uptake (VO2max) less than 50 ml.kg-1.min-1 and sedentary], moderate (MF; VO2max = 50-60 ml.kg-1.min-1 and recreationally active), and high (HF; VO2max greater than 60 ml.kg-1.min-1 and recent training history) fitness. Thirty healthy adult men (aged 20-31 yr) participated in four randomly ordered cycle ergometer rides: ride 1 (65% VO2max, 30 min), ride 2 (30% VO2max, 60 min), ride 3 (75% VO2max, 60 min), and ride 4 (65% VO2max, 120 min). Blood samples were drawn at various times before and after the exercise sessions. Lymphocyte subsets were determined by flow cytometry using monoclonal antibodies for total T (CD3+), T-helper (CD4+), and T-suppressor (CD8+) lymphocytes and for a subset of cells expressing a natural killer (NK) cell antigen (Leu7+). Plasma catecholamines were assayed to determine exercise stress. There were sharp reductions (P less than 0.01) in the percentage of pan-T and T-helper lymphocytes immediately after exercise across all fitness levels; the magnitude of this reduction was greatest after the highest intensity (ride 3) or longest duration (ride 4) work. In contrast, the absolute number of T and T-helper cells tended to increase after exercise and significantly so in the HF subjects (P less than 0.005). There was no significant effect of exercise or subject fitness category on the percentage of T-suppressor lymphocytes, although the absolute numbers of this subset increased significantly after exercise in LF subjects. Marked increases (P less than 0.01) in the percentage of NK cells occurred immediately after exercise at all intensities and durations tested; numerical increases in total NK cells were significant in all fitness groups after the highest intensity work (ride 3; P less than 0.005). Irrespective of whether the changes were expressed as percentage or total numbers, recovery to base line occurred at 30 min after exercise. The results suggest that the exercise effect on blood lymphocyte subset percentages in men is transient and occurs across all fitness levels. Concomitant changes in plasma catecholamine concentrations are only weakly associated with these lymphocyte subset percentage responses to exercise. Furthermore, this study shows that the exercise-induced changes in lymphocyte percentages do not consistently reflect changes in the absolute numbers of cells.     

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.     

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.     

Seasonal aerobic performance variations in elite soccer players

The purpose of this study was to examine the seasonal changes in body composition and aerobic performance in elite soccer players. Twelve elite professional soccer players (aged 25 6 5 years, weight 75.7 6 5.3 kg, height 1.79 6 0.06 m) were measured for body fat (%), maximum oxygen consumption (VO2max), running velocity at VO2max (VO2max), running velocity at a fixed blood lactate concentration of 4 mmol · L21 (v-4 mM) at the start of the preseason period, at the beginning of the competitive period, and at midseason. VO2max, v-4 mM, and vVO2max increased significantly (p , 0.05) by 4.5, 10.5, and 7.8,respectively, after the preseason period. Thereafter, the aerobic performance parameters remained relatively constant, with no significant changes throughout the competitive period. The results of this study suggest that moderate improvements were observed in VO2max, and the %VO2max at 4 v-4 mM, whereas higher improvements were observed in VO2max and v-4 mmol · L21 after the preseason training period. On the other hand, during the competitive period, aerobic performance remained unchanged.In addition, this study suggests that heart rate, lactate, vVO2, and VO2max are useful and practical predictors that help monitor aerobic performance changes during a soccer season.     

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.     

Comparison of running performances and prevalence of overweight and obesity in Hungarian and Ukrainian adolescents

The 20-m shuttle run (20-mSRT) is a widely used field test to estimate peak oxygen consumption (VO2peak) and thus to assess aerobic fitness of adolescents (11). The purpose of this study was to analyse differences in basic anthropometric measurements (stature, body mass, percent body fat, BMI) and in aerobic fitness of Hungarian and Ukrainian adolescent boys and girls. We examined gender differences in maximal speed (km h-1), in peak VO2 (mL kg-1 min-1) and maximal heart rate (HRmax min-1). Two hundred ninety-two Ukrainian (mean age=16.5±0.5) and 374 (mean age=16.5±0.5) Hungarian adolescents volunteered to participate in this study. Differences were analysed using factorial analysis of the variance (ANOVA) and Student's t-test. Statistical significance was set at p<0.05. Hungarian boys and girls were significantly taller, heavier and had higher percent body fat than their Ukrainian counterparts. Altogether 10% of Hungarians and 7% of Ukrainians were classified overweight or obese according to Cole's BMI classification (4). VO2peak of Ukrainians (mean=49.44±5.29 mL kg-1 min-1) were significantly higher than that of Hungarians (mean=41.93±8.40 mL kg-1 min-1). Maximal heart rate also differed significantly (Ukrainians mean=201.12±8.43 min-1 vs. Hungarians mean=185.38±18.38 min-1).In conclusion, aerobic fitness of the Ukrainian adolescents was significantly higher than that of the Hungarians independently of BMI or gender.     

The genetic contribution to heart rate and heart rate variability in quiescent mice

Recent studies have suggested a genetic component to heart rate (HR) and HR variability (HRV). However, a systematic examination of the genetic contribution to the variation in HR and HRV has not been performed. This study investigated the genetic contribution to HR and HRV using a wide range of inbred and recombinant inbred (RI) mouse strains. Electrocardiogram data were recorded from 30 strains of inbred mice and 29 RI strains. Significant differences in mean HR and total power (TP) HRV were identified between inbred strains and RI strains. Multiple significant differences within the strain sets in mean low-frequency (LF) and high-frequency (HF) power were also found. No statistically significant concordance was found between strain distribution patterns for HR and HRV phenotypes. Genomewide interval mapping identified a significant quantitative trait locus (QTL) for HR [LOD (likelihood of the odds) score = 3.763] on chromosome 6 [peak at 53.69 megabases (Mb); designated HR 1 (Hr1)]. Suggestive QTLs for TP were found on chromosomes 2, 4, 5, 6, and 14. A suggestive QTL for LF was found on chromosome 16; for HF, we found one significant QTL on chromosome 5 (LOD score = 3.107) [peak at 53.56 Mb; designated HRV-high-frequency 1 (Hrvhf1)] and three suggestive QTLs on chromosomes 2, 11 and 15. In conclusion, the results demonstrate a strong genetic component in the regulation of resting HR and HRV evidenced by the significant differences between strains. A lack of correlation between HR and HRV phenotypes in some inbred strains suggests that different sets of genes control the phenotypes. Furthermore, QTLs were found that will provide important insight to the genetic regulation of HR and HRV at rest.