891 resultados para aerobic fitness
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Purpose: The aim of this study was to verify the influence of aerobic fitness (VO(2)max) on internal training loads, as measured by the session rating of perceived exertion (session-RPE) method. Methods: Nine male professional outfield futsal players were monitored for 4 wk of the in-season period with regards to the weekly accumulated session-RPE, while participating in the same training sessions. Single-session-RPE was obtained from the product of a 10-point RPE scale and the duration of exercise. Maximal oxygen consumption was determined during an incremental treadmill test. Results: The average training load throughout the 4 wk period varied between 2,876 and 5,035 arbitrary units. Technical-tactical sessions were the predominant source of loading. There was a significant correlation between VO(2)max (59.6 +/- 2.5 mL.kg(-1).min(-1)) and overall training load accumulated over the total period (r = -0.75). Conclusions: The VO(2)max plays a key role in determining the magnitude of an individual's perceived exertion during futsal training sessions.
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Adiposity, low aerobic fitness and low levels of activity are all associated with clustered cardiovascular disease risk in children and their high prevalence represents a major public health concern. The aim of this study is to investigate the relationship of objectively measured physical activity (PA) with motor skills (agility and balance), aerobic fitness and %body fat in young children. This study is a cross-sectional and longitudinal analyses using mixed linear models. Longitudinal data were adjusted for baseline outcome parameters. In all, 217 healthy preschool children (age 4-6 years, 48% boys) participated in this study. PA (accelerometers), agility (obstacle course), dynamic balance (balance beam), aerobic fitness (20-m shuttle run) and %body fat (bioelectric impedance) at baseline and 9 months later. PA was positively associated with both motor skills and aerobic fitness at baseline as well as with their longitudinal changes. Specifically, only vigorous, but not total or moderate PA, was related to changes in aerobic fitness. Higher PA was associated with less %body fat at baseline, but not with its change. Conversely, baseline motor skills, aerobic fitness or %body fat were not related to changes in PA. In young children, baseline PA was associated with improvements in motor skills and in aerobic fitness, an important determinant of cardiovascular risk.
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BACKGROUND: The debate about a possible relationship between aerobic fitness and motor skills with cognitive development in children has recently re-emerged, because of the decrease in children's aerobic fitness and the concomitant pressure of schools to enhance cognitive performance. As the literature in young children is scarce, we examined the cross-sectional and longitudinal relationship of aerobic fitness and motor skills with spatial working memory and attention in preschool children. METHODS: Data from 245 ethnically diverse preschool children (mean age: 5.2 (0.6) years, girls: 49.4%) analyzed at baseline and 9 months later. Assessments included aerobic fitness (20 m shuttle run) and motor skills with agility (obstacle course) and dynamic balance (balance beam). Cognitive parameters included spatial working memory (IDS) and attention (KHV-VK). All analyses were adjusted for age, sex, BMI, migration status, parental education, native language and linguistic region. Longitudinal analyses were additionally adjusted for the respective baseline value. RESULTS: In the cross-sectional analysis, aerobic fitness was associated with better attention (r=0.16, p=0.03). A shorter time in the agility test was independently associated with a better performance both in working memory (r=-0.17, p=0.01) and in attention (r=-0.20, p=0.01). In the longitudinal analyses, baseline aerobic fitness was independently related to improvements in attention (r=0.16, p=0.03), while baseline dynamic balance was associated with improvements in working memory (r=0.15, p=0.04). CONCLUSIONS: In young children, higher baseline aerobic fitness and motor skills were related to a better spatial working memory and/or attention at baseline, and to some extent also to their future improvements over the following 9 months. TRIAL REGISTRATION: clinicaltrials.gov NCT00674544.
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Background: The debate about a possible relationship between aerobic fitness and motor skills with cognitive development in children has recently re-emerged, because of the decrease in children's aerobic fitness and the concomitant pressure of schools to enhance cognitive performance. As the literature in young children is scarce, we examined the cross-sectional and longitudinal relationship of aerobic fitness and motor skills with spatial working memory and attention in preschool children.Methods: Data from 245 ethnically diverse preschool children (mean age: 5.2 (0.6) years, girls: 49.4%) analyzed at baseline and 9 months later. Assessments included aerobic fitness (20 m shuttle run) and motor skills with agility (obstacle course) and dynamic balance (balance beam). Cognitive parameters included spatial working memory (IDS) and attention (KHV-VK). All analyses were adjusted for age, sex, BMI, migration status, parental education, native language and linguistic region. Longitudinal analyses were additionally adjusted for the respective baseline value.Results: In the cross-sectional analysis, aerobic fitness was associated with better attention (r = 0.16, p = 0.03). A shorter time in the agility test was independently associated with a better performance both in working memory (r = -0.17, p = 0.01) and in attention (r = -0.20, p = 0.01). In the longitudinal analyses, baseline aerobic fitness was independently related to improvements in attention (r = 0.16, p = 0.03), while baseline dynamic balance was associated with improvements in working memory (r = 0.15, p = 0.04).Conclusions: In young children, higher baseline aerobic fitness and motor skills were related to a better spatial working memory and/or attention at baseline, and to some extent also to their future improvements over the following 9 months.
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This study aimed to characterise both the [Formula: see text] kinetics within constant heavy-intensity swimming exercise, and to assess the relationships between [Formula: see text] kinetics and other parameters of aerobic fitness, in well-trained swimmers. On separate days, 21 male swimmers completed: (1) an incremental swimming test to determine their maximal oxygen uptake [Formula: see text], first ventilatory threshold (VT), and the velocity associated with [Formula: see text] [Formula: see text] and (2) two square-wave transitions from rest to heavy-intensity exercise, to determine their [Formula: see text] kinetics. All the tests involved breath-by-breath analysis of freestyle swimming using a swimming snorkel. [Formula: see text] kinetics was modelled with two exponential functions. The mean values for the incremental test were 56.0 ± 6.0 ml min(-1) kg(-1), 1.45 ± 0.08 m s(-1); and 42.1 ± 5.7 ml min(-1) kg(-1) for [Formula: see text], [Formula: see text] and VT, respectively. For the square-wave transition, the time constant of the primary phase (τ(p)) averaged 17.3 ± 5.4 s and the relevant slow component (A'(sc)) averaged 4.8 ± 2.9 ml min(-1) kg(-1) [representing 8.9% of the end-exercise [Formula: see text] (%A'(sc))]. τ(p) was correlated with [Formula: see text] (r = -0.55, P = 0.01), but not with either [Formula: see text] (r = 0.05, ns) or VT (r = 0.14, ns). The %A'(sc) did not correlate with either [Formula: see text] (r = -0.14, ns) or [Formula: see text] (r = 0.06, ns), but was inversely related with VT (r = -0.61, P < 0.01). This study was the first to describe the [Formula: see text] kinetics in heavy-intensity swimming using specific swimming exercise and appropriate methods. As has been demonstrated in cycling, faster [Formula: see text] kinetics allow higher aerobic power outputs to be attained. The slow component seems to be reduced in swimmers with higher ventilatory thresholds.
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This study aimed to compare two different maximal incremental tests with different time durations [a maximal incremental ramp test with a short time duration (8-12 min) (STest) and a maximal incremental test with a longer time duration (20-25 min) (LTest)] to investigate whether an LTest accurately assesses aerobic fitness in class II and III obese men. Twenty obese men (BMI≥35 kg.m-2) without secondary pathologies (mean±SE; 36.7±1.9 yr; 41.8±0.7 kg*m-2) completed an STest (warm-up: 40 W; increment: 20 W*min-1) and an LTest [warm-up: 20% of the peak power output (PPO) reached during the STest; increment: 10% PPO every 5 min until 70% PPO was reached or until the respiratory exchange ratio reached 1.0, followed by 15 W.min-1 until exhaustion] on a cycle-ergometer to assess the peak oxygen uptake [Formula: see text] and peak heart rate (HRpeak) of each test. There were no significant differences in [Formula: see text] (STest: 3.1±0.1 L*min-1; LTest: 3.0±0.1 L*min-1) and HRpeak (STest: 174±4 bpm; LTest: 173±4 bpm) between the two tests. Bland-Altman plot analyses showed good agreement and Pearson product-moment and intra-class correlation coefficients showed a strong correlation between [Formula: see text] (r=0.81 for both; p≤0.001) and HRpeak (r=0.95 for both; p≤0.001) during both tests. [Formula: see text] and HRpeak assessments were not compromised by test duration in class II and III obese men. Therefore, we suggest that the LTest is a feasible test that accurately assesses aerobic fitness and may allow for the exercise intensity prescription and individualization that will lead to improved therapeutic approaches in treating obesity and severe obesity.
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Objective: This study assesses differences in adiposity, aerobic fitness, and lifestyle characteristics in preschoolers according to their weight status and sports club (SC) participation. Method: As part of the Ballabeina study, 600 randomly selected preschoolers (mean age 5.1 ± 0.6 years; 50.2% girls) were analyzed. Body composition was measured by bioelectrical impedance, aerobic fitness by the 20-meter shuttle run test, and physical activity by accelerometers. Eating habits, media use, and SC participation were assessed by questionnaires. Results: Overweight children (Swiss national percentiles) and children not participating in SC had both lower aerobic fitness and higher % body fat compared to their respective counterparts (all p ≤ 0.028). In addition, children not participating in SC were less physically active, had more media use, and ate less healthy compared to children participating in SC (all p ≤ 0.023). Controlling for parental sociocultural determinants attenuated differences in % body fat, in physical activity, and in eating habits. Conclusion: Aerobic fitness differs both according to weight status and SC participation in preschoolers. Furthermore, in view of the many differences in lifestyle behaviors, SC participation at this age could represent a more discriminatory indicator of healthy lifestyle characteristics than weight status.
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Objective: to assess the diagnostic accuracy of different anthropometric markers in defining low aerobic fitness among adolescents. Methods: cross-sectional study on 2,331 boys and 2,366 girls aged 10 - 18 years. Body mass index (BMI) was measured using standardized methods; body fat (BF) was assessed by bioelectrical impedance. Low aerobic fitness was assessed by the 20-meter shuttle run using the FITNESSGRAMR criteria. Waist was measured in a subsample of 1,933 boys and 1,897 girls. Overweight, obesity and excess fat were defined according to the International Obesity Task Force (IOTF) or FITNESSGRAMR criteria. Results: 38.5% of boys and 46.5% of girls were considered as unfit according to the FITNESSGRAMR criteria. In boys, the area under the ROC curve (AUC) and 95% confidence interval were 66.7 (64.1 - 69.3), 67.1 (64.5 - 69.6) and 64.6 (61.9 - 67.2) for BMI, BF and waist, respectively (P<0.02). In girls, the values were 68.3 (65.9 - 70.8), 63.8 (61.3 - 66.3) and 65.9 (63.4 - 68.4), respectively (P<0.001). In boys, the sensitivity and specificity to diagnose low fitness were 13% and 99% for obesity (IOTF); 38% and 86% for overweight + obesity (IOTF); 28% and 94% for obesity (FITNESSGRAMR) and 42% and 81% for excess fat (FITNESSGRAMR). For girls, the values were 9% and 99% for obesity (IOTF); 33% and 82% for overweight + obesity (IOTF); 22% and 94% for obesity (FITNESSGRAMR) and 26% and 90% for excess fat (FITNESSGRAMR). Conclusions: BMI, not body fat or waist, should be used to define low aerobic fitness. The IOTF BMI cut-points to define obesity have a very low screening capacity and should not be used.
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The aims of this study were: (1) to verify the validity of previous proposed models to estimate the lowest exercise duration (T (LOW)) and the highest intensity (I (HIGH)) at which VO(2)max is reached (2) to test the hypothesis that parameters involved in these models, and hence the validity of these models are affected by aerobic training status. Thirteen cyclists (EC), eleven runners (ER) and ten untrained (U) subjects performed several cycle-ergometer exercise tests to fatigue in order to determine and estimate T (LOW) (ET (LOW)) and I (HIGH) (EI (HIGH)). The relationship between the time to achieved VO(2)max and time to exhaustion (T (lim)) was used to estimate ET (LOW). EI (HIGH) was estimated using the critical power model. I (HIGH) was assumed as the highest intensity at which VO2 was equal or higher than the average of VO(2)max values minus one typical error. T (LOW) was considered T (lim) associated with I (HIGH). No differences were found in T (LOW) between ER (170 +/- 31 s) and U (209 +/- 29 s), however, both showed higher values than EC (117 +/- 29 s). I (HIGH) was similar between U (269 +/- 73 W) and ER (319 +/- 50 W), and both were lower than EC (451 +/- 33 W). EI (HIGH) was similar and significantly correlated with I-HIGH only in U (r = 0.87) and ER (r = 0.62). ET (LOW) and T (LOW) were different only for U and not significantly correlated in all groups. These data suggest that the aerobic training status affects the validity of the proposed models for estimating I (HIGH).
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The aim of this study was to address the question if the VO2 kinetics is further improved as the aerobic training status increases from trained to elite level athletes. Maximal oxygen uptake (VO(2)max), work-rate associated to VO(2)max (IVO(2)max) and VO2 kinetics of moderate (Mod) and maximal exercise (Max) were determined in fifty-five subjects. Then, they were assigned into three groups: low (LF), intermediate (IF) and high (HF) aerobic fitness level. In average, the VO(2)max of LF, IF and HF groups were, respectively, 36.0 +/- 3.1, 51.1 +/- 4.5 and 68.1 +/- 3.9 ml . kg . min(-1) (p <= 0.05 among each other). VO2 kinetics mean response time of both exercise intensities were significantly faster (p <= 0.05) in HF (Mod, 27.5 +/- 5.5 s; Max, 32.6 +/- 8.3 s) and IF (Mod, 25.0 +/- 3.1 s; Max, 42.6 +/- 10.4 s) when compared to LF (Mod, 35.7 +/- 7.9 s; Max: 57.8 +/- 17.8 s). We can conclude that VO2 kinetics is improved as the fitness level is increased from low to intermediate but not further improved as the aerobic fitness level increases from intermediate to high.
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Objective. The aim of this study was to verify the possibility of lactate minimum (LM) determination during a walking test and the validity of such LM protocol on predicting the maximal lactate steady-state (MLSS) intensity. Design. Eleven healthy subjects (24.2 ± 4.5 yr; 74.3 ± 7.7 kg; 176.9 ± 4.1 cm) performed LM tests on a treadmill, consisting of walking at 5.5 km h -1 and with 20-22% of inclination until voluntary exhaustion to induce metabolic acidosis. After 7 minutes of recovery the participants performed an incremental test starting at 7% incline with increments of 2% at each 3 minutes until exhaustion. A polynomial modeling approach (LMp) and a visual inspection (LMv) were used to identify the LM as the exercise intensity associated to the lowest [bLac] during the test. Participants also underwent to 24 constant intensity tests of 30 minutes to determine the MLSS intensity. Results. There were no differences among LMv (12.6 ± 1.7 %), LMp (13.1 ± 1.5 %), and MLSS (13.6 ± 2.1 %) and the Bland and Altman plots evidenced acceptable agreement between them. Conclusion. It was possible to identify the LM during walking tests with intensity imposed by treadmill inclination, and it seemed to be valid on identifying the exercise intensity associated to the MLSS. Copyright © 2012 Guilherme Morais Puga et al.
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The aim of this study was to analyze the influence of aerobic fitness on the effects of prior exercise on VO2response during subsequent moderate-intensity exercise. After determination of the lactate threshold (LT) and maximal VO2 (VO2max). 14 untrained subjects (UG) and 14 well-trained cyclists (TG) performed on different days and in random order, rest to moderate-intensity exercise transitions (6 minutes at 80% of LT), preceded by either no prior exercise or prior supramaximal exercise (PSE: two bouts of 1 minute at 120% of VO2max, with a 1-minute rest in between). Baseline VO2 was significantly increased (p<0.05) by PSE in both groups (UG: 0.39 ± 0.06 vs. 0.51 ± 0.15 L·min -1;TG: 0.37 ± 0.06 vs. 0.58 ± 0.14 L·min -1). In the TG group, the steady state VO2 was significantly increased by PSE (TG: 2.21 ± 0.38 vs. 2.07 ± 0.27 L·min-1, p<0.05; UG: 1.60 ± 0.27 vs. 1.60 ± 0.29 L· min-1, p>0.05). It can be concluded that aerobic fitness level influences the effects of PSE on VO2 response during moderate-intensity exercise. [J Exerc Sci Fit • Vol 7 • No 1 • 48-54 • 2009].
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Intramyocellular lipid (IMCL) variations in older men are poorly explored. In young adults, IMCL can be influenced by both diet and exercise interventions; this flexibility is related to aerobic fitness. We evaluated in active older adults the influence of maximal aerobic capacity on short-term diet and exercise-induced variations in IMCL stores.