Anaerobic power and achievement of VO2 plateau in pre-pubertal boys

An investigation into the associations between psychological skills, anaerobic fitness, and aerobic fitness in elite Iranian taekwondo athletes

This study investigated the relationship between psychological skills and fitness levels among elite taekwondo athletes. A total of ten Iranian male elite taekwondo athletes (mean age of 20.6±2 years, BMI 18.78±0.62 kg/m2, and fat percentage of 8.87±1.46%) participated in the study. The Sports Emotional Intelligence Questionnaire, Sports Success Scale, Sport Mental Toughness Questionnaire, and Mindfulness Inventory for Sport were used to assess psychological factors. The Wingate test was used to determine anaerobic power, and the Bruce test to determine aerobic fitness. Descriptive statistics and Spearman rank correlation coefficients were utilised to examine any relationships between subscales. Statistically significant correlations were recorded between the evaluation of feelings (EI scale) and VO2peak (ml/kg/min) (r = -0.70, p = 0.0235) and between social skills (EI scale) and relative peak power (W/kg) (r = 0.84, p = 0.0026). Also, between optimism (EI scale) and VO2peak (ml/kg/min) (r = -0.70, p = 0.0252) and between optimism (EI scale) and HR-MAX (r = -0.75, p = 0.0123); and, finally, between control (mental toughness scale) and relative peak power (W/kg) (r = 0.67, p = 0.0360). These findings demonstrate relationships between psychological factors and the advantages of good anaerobic and aerobic capabilities. Finally, the study also demonstrated that elite taekwondo athletes have high mental performance abilities that are interrelated with anaerobic and aerobic performance.

A Meta-Analysis of Sampled Maximal Aerobic Capacity Data for Boys Aged 11 Years Old or Less Obtained by Cycle Ergometry

The aim of this study was to develop distributions of VO_2max based on measured values that exist in the literature in prepubertal boys using cycle ergometry. PRISMA guidelines were followed in conducting this research. One database was searched for peak and maximal VO₂ values in healthy boys with mean age under 11 years old. Data were split into articles reporting absolute and relative VO_2max values and analyzed accordingly. Multilevel models grounded in Bayesian principles were used. We investigated associations between VO_2max and body mass, year of the study, and country of origin. Differences in "peak" and "maximal" VO₂ were assessed. Absolute VO_2max (Lmin^-1) increases with age (P ~100%) but mean relative VO_2max does not change (P ~100%). Absolute VO_2max is higher in more recent studies (P = 95.7 ± 0.3%) and mean relative VO_2max is lower (P = 99.6 ± 0.1%). Relative VO_2max in the USA is lower compared with boys from other countries (P = 98.8 ± 0.2%), but there are no differences in absolute values. Mean aerobic capacity estimates presented as "peak" values are higher than "maximal" values on an absolute basis (P = 97.5 ± 0.3%) but not on a relative basis (P = 99.6 ± 0.1%). Heavier boys have lower cardiorespiratory fitness (P ≈ 100%), and body mass seems to be increasing faster with age in the USA compared with other countries (P = 92.3 ± 0.3%). New reference values for cardiorespiratory fitness are presented for prepubertal boys obtained with cycle ergometry. This is new, as no reference values have been determined so far based on actual measured values in prepubertal boys. Aerobic capacity normalized to body weight does not change with age. Cardiorespiratory fitness in prepubertal boys is declining, which is associated with increasing body mass over the last few decades. Lastly, this study did not find any statistically significant difference in the sample's mean aerobic capacity estimates using the "peak" and "maximum" distinctions identified in the literature.

The Oxygen Uptake Plateau-A Critical Review of the Frequently Misunderstood Phenomenon

A flattening of the oxygen uptake–work rate relationship at severe exercise indicates the achievement of maximum oxygen uptake \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left({\text{VO}}_{2\max } \right)$$\end{document}VO2max. Unfortunately, a distinct plateau \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left( {{{\text{VO}}}_{2} {\text{pl}}} \right)$$\end{document}VO2pl at \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2\max }$$\end{document}VO2maxis not found in all participants. The aim of this investigation was to critically review the influence of research methods and physiological factors on the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2} {\text{pl}}$$\end{document}VO2pl incidence. It is shown that many studies used inappropriate definitions or methodical approaches to check for the occurrence of a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2} {\text{pl}}$$\end{document}VO2pl. In contrast to the widespread assumptions it is unclear whether there is higher \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2} {\text{pl}}$$\end{document}VO2pl incidence in (uphill) running compared to cycling exercise or in discontinuous compared to continuous incremental exercise tests. Furthermore, most studies that evaluated the validity of supramaximal verification phases, reported verification bout durations, which are too short to ensure that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2\max }$$\end{document}VO2max have been achieved by all participants. As a result, there is little evidence for a higher \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2} {\text{pl}}$$\end{document}VO2pl incidence and a corresponding advantage for the diagnoses of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2\max }$$\end{document}VO2max when incremental tests are supplemented by supramaximal verification bouts. Preliminary evidence suggests that the occurrence of a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2} {\text{pl}}$$\end{document}VO2pl in continuous incremental tests is determined by physiological factors like anaerobic capacity, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2}$$\end{document}VO2-kinetics and accumulation of metabolites in the submaximal intensity domain. Subsequent studies should take more attention to the use of valid \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2} {\text{pl}}$$\end{document}VO2pl definitions, which require a cut-off at ~ 50% of the submaximal \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2}$$\end{document}VO2 increase and rather large sampling intervals. Furthermore, if verification bouts are used to verify the achievement of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{{2{\text{peak}}}}$$\end{document}VO2peak/\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\text{VO}}}_{2\max }$$\end{document}VO2max, it should be ensured that they can be sustained for sufficient durations.

Oxygen uptake plateau: calculation artifact or physiological reality?

PURPOSE

To test whether the oxygen uptake ([Formula: see text]) plateau at [Formula: see text] is simply a calculation artifact caused by the variability of [Formula: see text] or a clearly identifiable physiological event.

METHODS

Forty-six male participants performed an incremental ramp and a [Formula: see text] verification test. Variability of the difference between adjacent sampling intervals (difference) and of the slope of the [Formula: see text]-workload relationship (slope) in the submaximal intensity domain were calculated. Workload defined sampling intervals used for the calculation of the difference and slope were systematically increased from 20 to 100 W until the expected risk of false plateau diagnoses based on the Gaussian distribution function was lower than 5%. Overall, more than 1500 differences and slopes were analyzed. Subsequently, frequencies of plateau diagnoses in the submaximal and maximal intensity domains were compared.

RESULTS

Variability of the difference and slope decreased with increasing sampling interval (p < 0.001). At a sampling interval of 50 W, the predefined acceptable risk of false plateau diagnoses (≤ 5%) was achieved. At this sampling interval, the actual frequency (1.4%) of false-positive plateau diagnoses did not differ from the expected frequency in the submaximal intensity domain (1.6%; p = 0.491). In contrast, the actual frequency at maximal intensity (35.7%) was significantly higher compared to the submaximal intensity domain (p < 0.001) and even higher than the expected frequency of false-positive diagnoses (p < 0.001).

CONCLUSION

The [Formula: see text] plateau at [Formula: see text] represents a physiological event and no calculation artifact caused by [Formula: see text] variability. However, detecting a [Formula: see text] plateau with sufficient certainty requires large sampling intervals.

Oxygen uptake plateau occurrence depends on oxygen kinetics and oxygen deficit accumulation

We tested the hypothesis that participants with an oxygen uptake ( V ˙ O 2 ) plateau during incremental exercise exhibit a lower VO₂ -deficit (VO_2DEF )-accumulation in the submaximal intensity domain due to faster ramp and square wave O₂ -kinetics. Twenty-six male participants performed a standard ramp test (increment: 30 W·min^-1 ), a ramp test with an individualized ramp slope and a two-step (moderate and severe) square wave exercise followed by a V ˙ O 2 m a x -verification bout. VO_2DEF was calculated by the difference between individualized ramp test V ˙ O₂ and V ˙ O₂ -demand estimated from steady-state V ˙ O₂ -kinetics. Twenty-four participants verified their V ˙ O_2max in the verification test. Ten of them showed a plateau in the individualized ramp test. VO_2DEF at the end of this ramp test (4.34 ± 0.60 vs 4.54 ± 0.43 L) was not different between the plateau and the non-plateau group (P > 0.05). The plateau group had a significantly (P < 0.05) lower VO_2DEF 2 minutes before termination of the individualized ramp test (2.24 ± 0.40 vs 2.78 ± 0.33 L). This coincided with a shorter mean response time (43 ± 9 vs 53 ± 7 seconds), a higher increase in V ˙ O₂ per W (10.1 ± 0.2 vs 9.2 ± 0.5 mL·min^-1 ·W^-1 ) at the individualized ramp test as well as shorter time constants of moderate (36 ± 6 vs 48 ± 7 seconds) and severe (62 ± 9 vs 86 ± 10 seconds) square wave kinetics (all P < 0.05). We conclude that the V ˙ O₂ -plateau occurrence requires a fast V ˙ O₂ -kinetics and a low VO_2DEF -accumulation at intensities below V ˙ O_2max .

Are Prepubertal Children Metabolically Comparable to Well-Trained Adult Endurance Athletes?

It is well acknowledged that prepubertal children have smaller body dimensions and a poorer mechanical (movement) efficiency, and thus a lower work capacity than adults. However, the scientific evidence indicates that prepubertal children have a greater net contribution of energy derived from aerobic metabolism in exercising muscle and reduced susceptibility to muscular fatigue, which makes them metabolically comparable to well-trained adult endurance athletes. For example, the relative energy contribution from oxidative and non-oxidative (i.e. anaerobic) sources during moderate-to-intense exercise, the work output for a given anaerobic energy contribution and the rate of acceleration of aerobic metabolic machinery in response to submaximal exercise are similar between prepubertal children and well-trained adult endurance athletes. Similar conclusions can be drawn on the basis of experimental data derived from intra-muscular measurements such as type I fibre percentage, succinate dehydrogenase enzyme activity, mitochondrial volume density, post-exercise phosphocreatine re-synthesis rate and muscle by-product clearance rates (i.e. H⁺ ions). On a more practical level, prepubertal children also experience similar decrements in peak power output as well-trained adult endurance athletes during repeated maximal exercise bouts. Therefore, prepubertal children have a comparable relative oxidative contribution to well-trained adult endurance athletes, but a decrease in this relative contribution occurs from childhood through to early adulthood. In a clinical context, this understanding may prove central to the development of exercise-based strategies for the prevention and treatment of many metabolic diseases related to mitochondrial oxidative dysfunction (e.g. in obese, insulin-resistant and diabetic patients), which are often accompanied by muscular deconditioning during adolescence and adulthood.

Swimming Stroke Mechanical Efficiency and Physiological Responses of 100-m Backstroke with and without the use of paddles

The use of swimming aids during training contributes to greater swimming efficiency by the improvement of the swimming specific power of the athlete. The purpose of this study was to compare the swimming stroke technical characteristics and the physiological responses of swimming 100-m backstroke, with and without the use of paddles at maximum and sub-maximum intensities at the same swimming speed. Eight swimmers competing at the national level participated in this study. The measurements took place at 4 different sessions. At every session, each participant swam individually one 100-m backstroke swimming trial with or without paddles at the same speed and two levels of intensity (100% and 85% of maximum speed). The results revealed lower stroke length, greater stroke number and gliding length without the use of swimming paddles at both intensities. Blood lactate concentration (10.03±2.96 vs. 5.85±2.23 mmol/l) and Rating of Perceived Exertion (17.43±2.07 vs. 12±2.82) were greater without the use of swimming paddles only at 100% of maximum speed. Thus, swimming backstroke with paddles compared to unaided swimming, at a similar speed, showed a greater efficiency at maximal but not at sub-maximal intensity.

Evaluating the prediction of maximal heart rate in children and adolescents

In this study, we compared measured maximal heart rate (HRmax) to two different HRmax prediction equations [22 - age and 208 - 0.7(age)] in 52 children ages 7-17 years. We determined the relationship of chronological age, maturational age, and resting HR to measured HRmax and assessed seated resting HR and HRmax during a graded exercise test. Maturational age was calculated as the maturity offset in years from the estimated age at peak height velocity. Measured HRmax was 201 +/- 10 bpm, whereas predicted HRmax ranged from 199 to 208 bpm. Measured HRmax and the predicted value from the 208 - 0.7(age) prediction were similar but lower (p < .05) than the 220 - age prediction. Absolute differences between measured and predicted HRmax were 8 +/- 5 and 10 +/- 8 bpm for the 208 - 0.7 (age) and 220 - age equations, respectively, and were greater than zero (p < .05). Regression equations using resting HR and maturity offset or chronological age significantly predicted HRmax, although the R2 < .30 and the standard error of estimation (8.2-8.5) limits the accuracy. The 208 - 0.7(age) equation can closely predict mean HRmax in children, but individual variation is still apparent.

State of the Art Reviews: Development of Fitness in Children: The Influence of Gender and Physical Activity

The influences of gender and physical activity on the development of fitness are reviewed from early childhood to late adolescence. Changes in parameters of fitness prior to puberty are driven predominantly by neuroendocrine-mediated factors, although physical activity level may be influenced largely by sociocultural factors prior to and following puberty. Thus, it is still unclear to what extent environment versus genetics accounts for gender differences in fitness. Future studies need to account for all factors known to explain gender differences in fitness to better differentiate intrinsic versus environmental causes. Consequently, one must consider if and to what extent a gender comparison study actually reveals true, inherent gender differences compared with sociocultural and/or cultural influences. Nevertheless, differences in fitness between girls and boys that are influenced by sociocultural factors should be considered when devising programs to promote physical activity and enhance fitness in youth. Fundamentally, the role of parents and primary caregivers in modeling physical activity and influencing the fitness level of their child cannot be overestimated.