Gender Differences in Anaerobic and Aerobic Responses to a Full Season of NCAA Division 1 Ice Hockey

PURPOSE: To examine training-induced changes in aerobic fitness and anaerobic power in a sample of division I, female college basketball players. METHODS: Aerobic fitness and anaerobic power were measured in a sample of female college basketball players before and after preseason training. Aerobic fitness was measured using a VO2 max test, and anaerobic power was measured using a Wingate test. Preseason training lasted one month and consisted of 8 hours per week of a combination of weight training, high-intensity interval sprint training, and skill workouts. Paired-sample t-tests were used to examine change pre- and post-intervention. Pearson correlations were conducted to examine potential associations among variables. RESULTS: A total of 13 female athletes completed this study. Maximal aerobic fitness significantly (p = .013) increased after preseason training, from 47.9 to 49.9 kg/ml/min. Relative peak power and relative mean power significantly increased after preseason training from 8.3 to 9.1 W/kg (p = .025) and from 6.7 to 7.6 W/kg (p < .001), respectively. Fatigue index did not significantly change as a result of preseason training. Despite these positive results, individual responses varied widely. Change in maximal aerobic fitness ranged from +0.2 to +6.1 ml/kg/min. Change in relative peak anaerobic power ranged from -1.0 to +3.0 W/kg, and change in relative mean anaerobic power ranged from +0.9 to +1.5 W/kg. Interestingly, change in maximal oxygen uptake and change in measures of anaerobic power were not significantly correlated with baseline levels of either of these variables. There were also no significant correlations between these changes in performance and age, year in school, or position played. There was, however, a significant, positive correlation (r = .77, p = .002) between change in relative peak anaerobic power and relative mean anaerobic power. CONCLUSIONS: Preseason training can have a positive effect on aerobic endurance and anaerobic power. These changes varied widely between athletes. However, this variation was not related to baseline fitness levels, age, year in school, or position played. This information may be useful for strength and conditioning coaches to design individualized training programs to maximize effects.

Low levels of physical activity and aerobic fitness are consistently associated with an increased risk of cardiovascular disease (CVD). Numerous studies have also shown that obesity indicators (BMI, waist circumference, waist-to-hip ratio, and waist-to-height ratio) are associated with CVD risk factors. However, it is uncertain whether change in physical activity is associated with CVD risk factors and whether this association is independent of change in aerobic fitness and body fatness. PURPOSE: To examine the associations between change in physical activity energy expenditure (PAEE), aerobic fitness and body fatness with CVD risk factors. METHODS: In a population-based sample of 393 men (n = 176) and women followed prospectively for 5.6 years, we measured PAEE by individually calibrated heart rate monitoring, maximal aerobic fitness (VO2max estimated from a graded exercise test), waist circumference, total body fat (by bio impedance) and eight established CVD risk factors (total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides, insulin, 2-h glucose, systolic and diastolic blood pressure) at baseline and follow-up. RESULTS: Change in PAEE was significantly and inversely associated with fasting triglycerides (B = −0.69; P = 0.028), insulin (B = − 1.14; P = 0.015) and 2-h glucose (B = −0.57; P = 0.027) at follow-up, after adjusting for sex, age, smoking status, baseline phenotype, aerobic fitness and body fatness (waist circumference or total body fat). These associations were materially unchanged after adjustment for change in aerobic fitness and body fatness (P <0.05). However, change in body fatness was consistently associated with change in all CVD risk factors, except for HDL-cholesterol, independently of change in PAEE and aerobic fitness (P <0.02). CONCLUSIONS: Change in physical activity level is inversely associated with insulin resistance, glucose intolerance and hyperlipidemia, independent of change in aerobic fitness and body fatness. This may have implications for cardiovascular risk reduction as increasing levels of physical activity may have protective effects without improvements in aerobic fitness, and reduced body fat mass. However body fatness was more strongly related to CVD risk factors than physical activity. Therefore, the combination of increasing levels of physical activity and avoidance of unhealthy weight gain is likely to be the most successful approach for the prevention of cardiovascular disease.

To determine the relationship between change in physical activity level and change in directly measured maximal aerobic fitness in severely obese subjects participating in a 1-year lifestyle intervention, and to determine whether change in 6-min walk test (6 MWT) could be used as an indicator of change in aerobic fitness. Complete data on aerobic fitness (maximal oxygen consumption (VO2max) and time to exhaustion on the VO2max test), 6 MWT, and physical activity (Actigraph GT1M accelerometer) were obtained for 21 subjects (mean age 42.6 years (standard deviation (SD) 11.0 years); mean body mass index 39.6 (SD 4.5) kg/m(2)). Multiple linear regression (controlling for change in body mass index) was used to analyse the relationships for: (i) changes in physical activity vs aerobic fitness and change in 6 MWT; and (ii) changes in aerobic fitness vs 6 MWT. Change in physical activity level was related to VO2max and time to exhaustion (partial r > 0.63, p < 0.003). No significant relationships were found between changes in aerobic fitness and 6 MWT (partial r < 0.22, p > 0.351) or between changes in physical activity level and 6 MWT (partial r = 0.15, p = 0.531). Increased physical activity level over 1 year resulted in increased aerobic fitness in severely obese subjects. Although the sample size was small, these results suggest that change in 6 MWT might not be a good indicator of maximal change in aerobic fitness in this population.

The aim of this study was to determine the longitudinal associations among fitness components and between fitness and mobility capacity in children with cerebral palsy (CP). Forty-six children (26 males, 20 females; mean age 9y 7mo [SD 1y 8mo]) with a bilateral (n=24) or a unilateral spastic CP (n=22) participated in aerobic and anaerobic fitness measurements on a cycle ergometer and isometric muscle strength tests (Gross Motor Function Classification System [GMFCS] level I [n=26], level II [n=12], level III [n=8]). Mobility capacity was assessed with the gross motor function measure (GMFM) and a walking capacity test. Associations over longitudinal measurements (three or four measurements over 1y) were determined since longitudinal data allow a more accurate estimation. The associations were determined using a mixed model with fixed effects (mobility capacity as dependent variables and fitness components as independent variables) and a random intercept. In children with bilateral CP, changes in aerobic fitness were associated with changes in anaerobic fitness (p<0.001), and changes in aerobic fitness showed an association with changes in muscle strength (p<0.05). Anaerobic fitness was not associated with muscle strength. No associations between fitness components were found in unilateral CP. Anaerobic fitness and muscle strength were significant determinants for GMFM and walking capacity in bilateral but not in unilateral CP. The longitudinal associations between aerobic and anaerobic fitness and mobility indicate that increasing either aerobic or anaerobic fitness is associated with improvements in mobility in children with bilateral CP. While increasing anaerobic fitness might be beneficial for mobility capacity in children with bilateral CP, this is less likely for children with unilateral CP.

Changes in blood lipids consequent to aerobic exercise training related to changes in body fatness and aerobic fitness

Effects of exercise on emerging and traditional cardiovascular risk factors

To compare the dose-response relationship between traditional arbitrary speed thresholds versus an individualized approach, with changes in aerobic fitness in professional youth soccer players. A total of 14 youth soccer players completed a 1500-m time trial to estimate maximal aerobic speed (MAS, km·h-1) at the start and at the end of a 6-week period. Training load was monitored on a daily basis during this study. External load measures were total distance covered and total acceleration and deceleration distance >2m·s-2. Arbitrary high-speed running measures were meters covered and time spent at >17km·h-1 (m > high-speed distance, t > high-speed distance) and 21km·h-1 (m > very-high-speed distance, t > very-high-speed distance). Individualized high-speed running measures were meters covered and time spent at >MAS km·h-1 (m > MAS, t > MAS) and 30% anaerobic speed reserve (m > 30ASR, t > 30ASR). In addition, internal load measures were also collected: heart rate exertion and rating of perceived exertion. Linear regression analysis was used to establish the dose-response relationship between mean weekly training load and changes in aerobic fitness. Very large associations were found between t > MAS and changes in aerobic fitness (R2 = .59). Large associations were found for t > 30ASR (R2 = .38) and m > MAS (R2 = .25). Unclear associations were found for all other variables. An individualized approach to monitoring training load, in particular t > MAS, may be a more appropriate method than using traditional arbitrary speed thresholds when monitoring the dose-response relationship between training load and changes in aerobic fitness.

The relationship between in-season changes in aerobic fitness and body composition in collegiate athletes is poorly defined. PURPOSE: To evaluate in-season changes in aerobic fitness among collegiate athletes, and how these are influenced by gender, sport and body composition. METHODS: 50 NCAA Division 1 athletes [23 female (11 hockey, 12 soccer), 27 male (11 hockey, 16 soccer)] completed testing immediately before and after their competitive seasons for determination of lean body mass (LBM) and percentage body fat (BF%) by dual-energy x-ray absorptiometry (DXA) and maximal treadmill testing for maximal aerobic capacity (VO2max), time to exhaustion (Tmax), and ventilatory threshold (VT). Pre- and post-season fitness and body composition values were compared using paired t-tests. Multivariable regression analysis was used to identify independent predictors of in-season change in body composition using gender and sport as covariates, as well as in-season changes in fitness measures using sport, gender and body composition as covariates. RESULTS: Compared to pre-season, post-season values for the entire group were lower for VO2max (4.30±0.88 v 4.08±0.86 L/min, p=0.002), and unchanged for Tmax (16.5±2.2 v 16.1±2.3 min, p=0.13), VT (3.05±0.77 v 3.15±0.66 L/min, p=0.18), BF% (19.1±6.8 v 19.4±6.5 %, p=0.39) and LBM (56.7±10.5 v 56.3±9.8 kg, p=0.48). (p>0.05 for all). LBM was a significant, independent predictor of in-season changes in VO2max (r2=0.33, p<0.001), Tmax (r2=0.19, p=0.003) and VT (r2=0.21, p=0.003). In-season change in BF% was not related to VO2max (r2=0.04, p=0.29) or VT (r2=0.03, p=0.51), but was a strong predictor of changes in Tmax (r2=0.32, p<0.001). Gender and sport were not related to in-season changes in body composition or fitness variables (p>0.05 for all). CONCLUSION: In collegiate intermittent sport athletes, in-season change in LBM explains a significant portion of changes in VO2max and VT, whereas in-season changes in Tmax are independently predicted by changes in both LBM and BF%. In-season changes in aerobic fitness and body composition do not differ across sport or gender. This suggests that efforts to influence body composition during the competitive season can significantly impact aerobic fitness in intermittent sport athletes.

PurposeTo challenge current conventions in paediatric sport science and use data from recent longitudinal studies to elucidate the development of aerobic and anaerobic fitness, with reference to youth athletes.Methods(1) To critically review the traditional practice of ratio scaling physiological variables with body mass and, (2) to use multiplicative allometric models of longitudinal data, founded on 1053 (550 from boys) determinations of 10–17-year-olds’ peak oxygen uptake ( {{text{V}}text{O}}_{2} ) and 763 (405 from boys) determinations of 11–17-year-olds’ peak power output (PP) and mean power output (MP), to investigate the development of aerobic and anaerobic fitness in youth.ResultsThe statistical assumptions underpinning ratio scaling of physiological variables in youth are seldom met. Multiplicative allometric modelling of longitudinal data has demonstrated that fat free mass (FFM) acting as a surrogate for active muscle mass, is the most powerful morphological influence on PP, MP, and peak {{text{V}}text{O}}_{2} . With FFM appropriately controlled for, age effects remain significant but additional, independent effects of maturity status on anaerobic and aerobic fitness are negated.ConclusionsRatio scaling of physiological variables with body mass is fallacious, confounds interpretation of the development of anaerobic and aerobic fitness, and misleads fitness comparisons within and across youth sports. Rigorous evaluation of the development of anaerobic and aerobic fitness in youth requires longitudinal analyses of sex-specific, concurrent changes in age- and maturation-driven morphological covariates. Age and maturation-driven changes in FFM are essential considerations when evaluating the physiological development of youth athletes.

Aim. Elite level soccer players cover about 10 km during a 90-minute game. Although running is the predominant activity in soccer, explosive movements such as sprinting, jumping and kicking are important for successful performance. The aims of this study were to determine the technical skill ability, aerobic- and anaerobic fitness of elite male under-18 African soccer players; and to determine whether a relationship exists between the technical skill ability and aerobic and anaerobic fitness. Methods. One-hundred-and-sixty-nine (n=169) elite male under-18 soccer players from eleven African countries participated in the study. Technical skill ability (dribbling, crossing, shooting, passing) was assessed using four soccer-specific tests. Aerobic and anaerobic fitness was measured through a 20-metre multi-stage shuttle run test and a repeated sprint ability test respectively. Results. The results showed that VO2max level (47.71 ml·kg-1·min-1) was much lower than indicated in literature (60 ml·kg- 1·min-1). An average total distance of 704.36 m was recorded for the repeated sprint ability test. A positive correlation was found between dribbling and both aerobic and anaerobic fitness. Results indicated differences among various playing positions with forwards producing best performance in the passing and shooting skills test, forwards and defenders possessing the highest level of aerobic fitness and goalkeepers displaying the lowest level of aerobic and anaerobic fitness. Conclusion. Aerobic and anaerobic fitness influenced the players’ ability to dribble. The African soccer players generally have a lower level of both aerobic and anaerobic fitness. DOI: 10.5901/mjss.2014.v5n27p1704

PURPOSE: The purpose of this investigation was to examine the relationship between maximal oxygen uptake (V̇O2max) and anaerobic power in Special Weapons and Tactics (SWAT) team members of law enforcement. METHODS: Fourteen healthy men and one healthy woman (age: 33 ± 6 y, height: 179.6 ± 6.7 cm, body mass: 89.6 ± 10.4 kg) performed a graded exercise test to measure V̇O2max and a Wingate Anaerobic Test to measure anaerobic power on two separate occasions. V̇O2max was determined with a graded exercise test on a motorized treadmill using the Costill-Fox protocol. Anaerobic power was determined using the Wingate Anaerobic Test where participants cycled against a resistance of 9% of body mass (8 ± 1 kg) on a Wingate cycle ergometer. Pearson’s r correlations were conducted to analyze the relationship between absolute V̇O2max and absolute power as well as relative V̇O2max and relative power. RESULTS: Absolute V̇O2max was significantly positively correlated to absolute peak power (r = 0.60; p = 0.02) and absolute average power (r = 0.75; p < 0.01). Moreover, relative V̇O2max was significantly positively correlated to relative peak power (r = 0.56; p = 0.03) and relative average power (r = 0.64; p = 0.01). CONCLUSIONS: There are moderate-to-strong positive correlations between V̇O2max and anaerobic power. It is possible that adaptations that occur with high intensity anaerobic exertions might be related to changes in aerobic metabolism. Future research might consider examining the effectiveness of anaerobic power training on aerobic fitness among the tactical athlete populations.

An association between training load and changes in aerobic fitness has been established but the effect of training load on changes in strength/power remains controversial. Internal (Banister's TRIMP) and external (total distance, high-speed running and sprint distance) training load was collected from sixteen professional soccer players during and aerobic fitness and strength/power variables were measured before and after a 9-week pre-season. Banister's TRIMP had a moderate correlation with changes in maximal oxygen uptake (r=0.46, 90% CI: 0.04; 0.74). Total distance had a large and a moderate correlation with changes in velocity at 2M (r=0.60, 90% CI: 0.23; 0.82) and changes in velocity at 4M (r=0.42, 90% CI: -0.01; 0.72). High-speed running had moderate correlations with changes in maximal oxygen uptake (r=0.45, 90% CI: 0.03; 0.74), velocity at 2M (r=0.45, 90% CI: 0.03; 0.74) and velocity at 4M (r=0.39, 90% CI: -0.00; 0.70). Sprint distance had a large and a moderate correlation with changes in maximal oxygen uptake (r=0.58, 90% CI: 0.20; 0.81) and velocity at 4M (r=0.46, 90% CI: 0.00; 0.74 respectively). High versus low total distance was associated with lower changes in squat jump and countermovement jump (ES=-0.90, 90% CI: -1.57; -0.24 and ES=-1.06, 90% CI: -1.89; -0.24) respectively. High versus low high-speed running was associated with higher changes in maximal oxygen uptake (ES=0.36, 90% CI: 0.02; 0.70) but lower changes in squat jump (ES=-0.58, 90% CI: -1.32; 0.15). External rather internal training load had more pronounced correlations with changes in aerobic fitness. Higher compared with lower volumes of total distance and high-speed running were associated with lower gains in strength/power indices. Establishing a "dose-response" association between external/internal training load and endurance as well as strength adaptations, may maximize endurance gains with the least possible interference on strength/power gains, thus better informing soccer training practice.

Peak oxygen uptake (V.O2peak) is the ‘gold standard’ measure of youth aerobic fitness. There is no corresponding measure of anaerobic fitness and current understanding of the development of anaerobic fitness is principally founded on peak power output (PP) and mean power output (MP) during the Wingate anaerobic test. Multiplicative allometric modelling of large longitudinal data sets of V.O2peak, PP, and MP has demonstrated the powerful influence of fat-free mass (as a surrogate of active muscle mass) on the development of both aerobic and anaerobic fitness. In youth, anaerobic fitness increases at a greater rate than aerobic fitness and this can be largely explained by asynchronous developmental changes within active muscle. There is a progressive increase in potential for glycolytic flux with age and maturation so that from a metabolic perspective, children have a well-developed capacity for sports principally supported by oxidative metabolism but are likely to be disadvantaged in sports heavily reliant on anaerobic metabolism when compared to older and more mature youth. The ability to quickly attain high (or maximum) power output and retain much of it for a sustained period are important components of performance in many youth sports. This involves an interplay between aerobic and anaerobic metabolism which depends upon the mode, intensity, and duration of the exercise and the relative development of the youth athlete’s aerobic and anaerobic fitness.

National data suggest that aerobic fitness and adiposity are negatively correlated in children, but this relationship was established using submaximal exercise tests and skinfold measurements (NCHS Data Brief. 2014 May;(153):1‐8). This study extended previous investigations by evaluating the influence of adiposity on both aerobic and anaerobic fitness in N=458 male and N=304 female middle school aged students (mean±SD, age 13.3±0.6 y). BMI averaged 22.2±5.2 and 22.9±5.2 kg/m2 in boys and girls, respectively, with 37% of boys and 36% of girls classified as overweight or obese using CDC BMI‐for‐age growth charts. Adiposity was assessed using air‐displacement plethysmography (BOD POD, Cosmed, Rome, Italy), VO2max through a maximal, graded treadmill test (Bruce protocol) with continuous metabolic measurement (Cosmed Fitmate system, Rome, Italy), and aerobic fitness with the 30‐second Wingate test (Lode cycle ergometer, Groningen, The Netherlands). Average test scores for male and female students were as follows: body fat, 19.8±11.0 and 24.6±8.7 %, respectively; anaerobic capacity, 7.2±1.4 and 5.7±1.2 watts/kg; and VO2max, 45.1±10.8 and 33.9±8.1 ml.kg‐1.min‐1. Body fat % was negatively correlated with VO2max in boys (r=‐0.65) and girls (r=‐0.56), and with anaerobic capacity in boys (r=‐0.71) and girls (r=‐0.58) (all P&lt;0.001). Aerobic fitness was below adequate levels (boys 42 and girls 36 ml.kg‐1.min‐1) in 39% of boys and 60% of girls, with proportions increasing in direct proportion to adiposity (P&lt;0.001). These data indicate that over one‐third of the N=762 middle school‐aged boys and girls tested were classified as overweight/obese, and that body fat % was inversely related to aerobic and anaerobic fitness.Funding, Golden Leaf Foundation STEM Initiative

To identify the dose-response relationship between measures of training load (TL) and changes in aerobic fitness in academy rugby union players. Training data from 10 academy rugby union players were collected during a 6-wk in-season period. Participants completed a lactate-threshold test that was used to assess VO2max, velocity at VO2max, velocity at 2mmol/L (lactate threshold), and velocity at 4mmol/L (onset of lactate accumulation; vOBLA) as measures of aerobic fitness. Internal-TL measures calculated were Banister training impulse (bTRIMP), Edwards TRIMP, Lucia TRIMP, individualized TRIMP (iTRIMP), and session RPE (sRPE). External-TL measures calculated were total distance, PlayerLoad™, high-speed distance >15km/h, very-high-speed distance >18km/h, and individualized high-speed distance based on each player's vOBLA. A second-order-regression (quadratic) analysis found that bTRIMP (R2 = .78, P = .005) explained 78% of the variance and iTRIMP (R2 = .55, P = .063) explained 55% of the variance in changes in VO2max. All other HR-based internal-TL measures and sRPE explained less than 40% of variance with fitness changes. External TL explained less than 42% of variance with fitness changes. In rugby players, bTRIMP and iTRIMP display a curvilinear dose-response relationship with changes in maximal aerobic fitness.