The purpose of this study was to validate an equation that has been used to predict peak oxygen uptake (VO2peak) and, if invalid, to develop a new equation predicting VO2peak from performance on a cycle ergometer test. Forty-five 9- and 15-year-old children underwent a VO2peak test and were randomized into developmental (DEV) and cross-validation (C-V) groups. The equation under validation, which requires knowledge of resting energy expenditure (REE), underestimated VO2peak (p < .05), but once adjusted with a new parameter calculated in DEV, it cross-validated well (r YY′ = .98, SE = .18 L · min−1). The accuracy of a new prediction equation built in DEV, not using REE, was confirmed in C-V (r YY′ = .98, SE = .17 L · min−1) and the slope and intercept were not different from the line of identity (p < .05). VO2peak in schoolchildren can be predicted with good accuracy from an equation based on the whole sample [VO2peak′ = −1.5986 + 0.0115 · (maximal power output) + 0.0109 · (mass) + 0.1313 · (gender) + 0.0085 · (maximal heart rate)].
Sigurbjörn Árni Arngrímsson, Torarinn Sveinsson and Erlingur Jóhannsson
Ryan D. Burns, James C. Hannon, Timothy A. Brusseau, Patricia A. Eisenman, Pedro F. Saint-Maurice, Greg J. Welk and Matthew T. Mahar
Cardiorespiratory endurance is a component of health-related fitness. FITNESSGRAM recommends the Progressive Aerobic Cardiovascular Endurance Run (PACER) or One mile Run/Walk (1MRW) to assess cardiorespiratory endurance by estimating VO2 Peak. No research has cross-validated prediction models from both PACER and 1MRW, including the New PACER Model and PACER-Mile Equivalent (PACER-MEQ) using current standards. The purpose of this study was to cross-validate prediction models from PACER and 1MRW against measured VO2 Peak in adolescents. Cardiorespiratory endurance data were collected on 90 adolescents aged 13–16 years (Mean = 14.7 ± 1.3 years; 32 girls, 52 boys) who completed the PACER and 1MRW in addition to a laboratory maximal treadmill test to measure VO2 Peak. Multiple correlations among various models with measured VO2 Peak were considered moderately strong (R = .74–0.78), and prediction error (RMSE) ranged from 5.95 ml·kg-1, min-1 to 8.27 ml·kg-1.min-1. Criterion-referenced agreement into FITNESSGRAM’s Healthy Fitness Zones was considered fair-to-good among models (Kappa = 0.31–0.62; Agreement = 75.5–89.9%; F = 0.08–0.65). In conclusion, prediction models demonstrated moderately strong linear relationships with measured VO2 Peak, fair prediction error, and fair-to-good criterion referenced agreement with measured VO2 Peak into FITNESSGRAM’s Healthy Fitness Zones.
Yagesh N. Bhambhani, Robert S. Burnham, Gary D. Wheeler, Peter Eriksson, Leona J. Holland and Robert D. Steadward
In this study we compared the ventilatory threshold (VT) between 8 untrained and 8 endurance-trained males with quadriplegia during simulated wheelchair exercise. Each subject completed an incremental velocity test in his personal wheelchair mounted on a customized roller system designed to provide velocity and distance feedback. VT was identified by two trained evaluators using established respiratory gas exchange criteria. A significant interevaluator reliability coefficient of .90 (p < .01) was observed for the detection of VT. Relative oxygen uptake (V̇O2, ml · kg-1 · min-1) at VT and peak V̇O2 were significantly (p < .05) higher in the endurance-trained compared to untrained subjects. However, no significant difference (p > .05) was observed between the two groups when VT was expressed as a percentage of peak V̇O2. Significant correlations of .86 and .81 (p < .01) were observed between VT and peak V̇O2 in the untrained and trained groups, respectively. It was concluded that endurance training improves both VT and peak V̇O2 during wheelchair exercise in male subjects with quadriplegia but does not improve VT when it is expressed relative to peak V̇O2.
Jaak Jürimäe, Kaja Haljaste, Antonio Cicchella, Evelin Lätt, Priit Purge, Aire Leppik and Toivo Jürimäe
The purpose of this study was to examine the influence of the energy cost of swimming, body composition, and technical parameters on swimming performance in young swimmers. Twenty-nine swimmers, 15 prepubertal (11.9 ± 0.3 years; Tanner Stages 1−2) and 14 pubertal (14.3 ± 1.4 years; Tanner Stages 3−4) boys participated in the study. The energy cost of swimming (Cs) and stroking parameters were assessed over maximal 400-m front-crawl swimming in a 25m swimming pool. The backward extrapolation technique was used to evaluate peak oxygen consumption (VO2peak). A stroke index (SI; m2 · s−1 · cycles−1) was calculated by multiplying the swimming speed by the stroke length. VO2peak results were compared with VO2peak test in the laboratory (bicycle, 2.86 ± 0.74 L/min, vs. in water, 2.53 ± 0.50 L/min; R2 = .713; p = .0001). Stepwise-regression analyses revealed that SI (R2 = .898), in-water VO2peak (R2 = .358), and arm span (R2 = .454) were the best predictors of swimming performance. The backward-extrapolation method could be used to assess VO2peak in young swimmers. SI, arm span, and VO2peak appear to be the major determinants of front-crawl swimming performance in young swimmers.
Christopher D. Black and Patrick J. O’Connor
Ginger has known hypoalgesic and anti-inflammatory properties. The effects of an oral dose of ginger on quadriceps muscle pain, rating of perceived exertion (RPE), and recovery of oxygen consumption were examined during and after moderateintensity cycling exercise. Twenty-five college-age participants ingested a 2-g dose of ginger or placebo in a double-blind, crossover design and 30 min later completed 30 min of cycling at 60% of VO2peak. Quadriceps muscle pain, RPE, work rate, heart rate (HR), and oxygen uptake (VO2) were recorded every 5 min during exercise, and HR and VO2 were recorded for 20 min after exercise. Compared with placebo, ginger had no clinically meaningful or statistically significant effect on perceptions of muscle pain, RPE, work rate, HR, or VO2 during exercise. Recovery of VO2 and HR after the 30-min exercise bout followed a similar time course in the ginger and placebo conditions. The results were consistent with related findings showing that ingesting a large dose of aspirin does not acutely alter quadriceps muscle pain during cycling, and this suggests that prostaglandins do not play a large role in this type of exercise-induced skeletal-muscle pain. Ginger consumption has also been shown to improve VO2 recovery in an equine exercise model, but these results show that this is not the case in humans.
Louisa Beale, Neil S Maxwell, Oliver R Gibson, Rosemary Twomey, Becky Taylor and Andrew Church
The purpose of this study was to characterize the physiological demands of a riding session comprising different types of recreational horse riding in females.
Sixteen female recreational riders (aged 17 to 54 years) completed an incremental cycle ergometer exercise test to determine peak oxygen consumption (VO2peak) and a 45-minute riding session based upon a British Horse Society Stage 2 riding lesson (including walking, trotting, cantering and work without stirrups). Oxygen consumption (VO2), from which metabolic equivalent (MET) and energy expenditure values were derived, was measured throughout.
The mean VO2 requirement for trotting/cantering (18.4 ± 5.1 ml·kg-1·min-1; 52 ± 12% VO2peak; 5.3 ± 1.1 METs) was similar to walking/trotting (17.4 ± 5.1 ml·kg-1·min-1; 48 ± 13% VO2peak; 5.0 ± 1.5 METs) and significantly higher than for work without stirrups (14.2 ± 2.9 ml·kg-1·min-1; 41 ± 12% VO2peak; 4.2 ± 0.8 METs) (P = .001).
The oxygen cost of different activities typically performed in a recreational horse riding session meets the criteria for moderate intensity exercise (3-6 METs) in females, and trotting combined with cantering imposes the highest metabolic demand. Regular riding could contribute to the achievement of the public health recommendations for physical activity in this population.
Lieselot Decroix, Kevin De Pauw, Carl Foster and Romain Meeusen
To review current cycling-related sport-science literature to formulate guidelines to classify female subject groups and to compare this classification system for female subject groups with the classification system for male subject groups.
A database of 82 papers that described female subject groups containing information on preexperimental maximal cycle-protocol designs, terminology, biometrical and physiological parameters, and cycling experience was analyzed. Subject groups were divided into performance levels (PLs), according to the nomenclature. Body mass, body-mass index, maximal oxygen consumption (VO2max), peak power output (PPO), and training status were compared between PLs and between female and male PLs.
Five female PLs were defined, representing untrained, active, trained, well-trained, and professional female subjects. VO2max and PPO significantly increased with PL, except for PL3 and PL4 (P < .01). For each PL, significant differences were observed in absolute and relative VO2max and PPO between male and female subject groups. Relative VO2max is the most cited parameter for female subject groups and is proposed as the principal parameter to classify the groups.
This systematic review shows the large variety in the description of female subject groups in the existing literature. The authors propose a standardized preexperimental testing protocol and guidelines to classify female subject groups into 5 PLs based on relative VO2max, relative PPO, training status, absolute VO2max, and absolute PPO.
Linda S. Pescatello, Loretta DiPietro, Ann E. Fargo, Adrian M. Ostfeld and Ethan R. Nadel
The cross-sectional relationship between physical activity, physical fitness, and measures of resting hemodynamic function and adiposity was examined in 11 women and 14 men, all of whom were in good health (M age = 69.3 yrs). Resting diastolic blood pressure (DBP) differed significantly by quartiles of both weekly energy expenditure and estimated VO2max. Subjects whose energy expenditure was above the 50th percentile had significantly lower DBP than less active subjects, independent of age, gender, and VO2max, whereas those above the 75th percentile of VO2max had lower DBP and mean arterial pressure compared to less fit subjects, independent of age, gender, and weekly energy expenditure. There were no significant differences in the body mass index or percent body fat by quartile of weekly energy expenditure or estimated VO2max in the multivariable analysis. Mean waist-to-hip ratio (WHR) differed by level of weekly energy expenditure, independent of age, gender, and VO2max; individuals who reported a threshold of energy expenditure ≥6,099 kcal/wk had less relative abdominal fat than those reporting less activity. There were no significant independent differences in mean WHR or the central-to-peripheral skinfold ratio between quartiles of VO2max.
Philo U. Saunders, Amanda J. Cox, Will G. Hopkins and David B. Pyne
It is unclear whether physiological measures monitored in an incremental treadmill test during a training season provide useful diagnostic information about changes in distance running performance.
To quantify the relationship between changes in physiological measures and performance (peak running speed) over a training season.
Well-trained distance runners (34 males; VO2max 64 ± 6 mL⋅kg-1⋅min-1, mean ± SD) completed four incremental treadmill tests over 17 wk. The tests provided values of peak running speed, VO2max, running economy, and lactate threshold (as speed and %VO2max). The physiological measures were included in simple and multiple linear regression models to quantify the relationship between changes in these measures and changes in peak speed.
The typical within-subject variation in peak speed from test to test was 2.5%, whereas those for physiological measures were VO2max (mL⋅min-1⋅kg-1) 3.0%, economy (m⋅kg⋅mL–1) 3.6%, lactate threshold (%VO2max) 8.7%, and body mass 1.8%. In simple models these typical changes predicted the following changes in performance: VO2max 1.4%, economy 0.8%, lactate threshold –0.3%, and body mass –0.2% (90% confidence limits ~±0.7%); the corresponding correlations with performance were 0.57, 0.33, –0.05, and –0.13 respectively (~±0.20). In a multiple linear regression model, the contribution of each physiological variable to performance changed little after adjustment for the other variables.
Change in VO2max in an incremental test during a running season is a good predictor of change in peak running speed, change in running economy is a moderate predictor, and lactate threshold and body mass provide little additional information.
Nicolas Fabre, Laurent Mourot, Livio Zerbini, Barbara Pellegrini, Lorenzo Bortolan and Federico Schena
This study tested the hypothesis that the DMAX (for maximal distance) method could be applied to ratings of perceived exertion (RPE), to propose a novel method for individual detection of the lactate threshold (LT) using RPE alone during an incremental test to exhaustion. Twenty-one participants performed an incremental test on a cycle ergometer. At the end of each stage, lactate concentration was measured and the participants estimated RPE using the Borg CR100 scale. The intensity corresponding to the fixed lactate values of 2 or 4 mmol · L−1(2mM and 4mM), the ventilatory threshold (VT), the respiratory-compensation point (RCP), and the instant of equality of pulmonary gas exchange (RER=1.00) were determined. Lactate (DMAX La) and RPE (DMAX RPE) thresholds were determined using the DMAX method. Oxygen uptake (VO2), heart rate, and power output measured at DMAX RPE and at DMAX La were not statistically different. Bland-Altman plots showed small bias and good agreements when DMAX RPE was compared with the DMAX La and RER=1.00 methods (bias = −0.05% and −2% of VO2max, respectively). Conversely, VO2 from the DMAX RPE method was lower than VO2 at 4 mM and at RCP and was higher than VO2 at 2 mM and at VT. VO2 at DMAX RPE was strongly correlated with VO2 at DMAX La (r = .97), at RER=1.00 (r = .97), at 2 mM (r = .85), at 4 mM (r = .93), at VT (r = .95), and at RCP (r = .95). The combination of the DMAX method with the RPE responses permitted precise and individualized estimates of LT using the DMAX method.