Measure Of Anaerobic Capacity Research Articles

Climbing-Specific Exercise Tests: Energy System Contributions and Relationships With Sport Performance.

PurposeThe aim of the study was to evaluate distinct performance indicators and energy system contributions in 3 different, new sport-specific finger flexor muscle exercise tests.MethodsThe tests included the maximal strength test, the all-out test (30 s) as well as the continuous and intermittent muscle endurance test at an intensity equaling 60% of maximal force, which were performed until target force could not be maintained. Gas exchange and blood lactate were measured in 13 experienced climbers during, as well as pre and post the test. The energy contribution (anaerobic alactic, anaerobic lactic, and aerobic) was determined for each test.ResultsThe contribution of aerobic metabolism was highest during the intermittent test (59.9 ± 12.0%). During continuous exercise, this was 28.1 ± 15.6%, and in the all-out test, this was 19.4 ± 8.1%. The contribution of anaerobic alactic energy was 27.2 ± 10.0% (intermittent), 54.2 ± 18.3% (continuous), and 62.4 ± 11.3% (all-out), while anaerobic lactic contribution equaled 12.9 ± 6.4, 17.7 ± 8.9, and 18.2 ± 9.9%, respectively.ConclusionThe combined analysis of performance predictors and metabolic profiles of the climbing test battery indicated that not only maximal grip force, but also all-out isometric contractions are equally decisive physical performance indices of climbing performance. Maximal grip force reflects maximal anaerobic power, while all-out average force and force time integral of constant isometric contraction at 60% of maximal force are functional measures of anaerobic capacity. Aerobic energy demand for the intermittent exercise is dominated aerobic re-phosphorylation of high-energy phosphates. The force-time integral from the intermittent test was not decisive for climbing performance.

Reliability and Validity of a Modified Anaerobic Treadmill Test to Determine Anaerobic Capacity in Male NCAA Division II Soccer Players in USA

The purpose of this study was to develop a sports-specific anaerobic capacity test for soccer players that could be administered on commercial treadmills found in most exercise facilities. The Anaerobic Speed Test (AST) is an anaerobic capacity test on a treadmill, however the testing protocol (20% incline, 214 meter/min) cannot be completed on commercial treadmills because they have a maximum incline setting of 15%. This study newly developed the modified Anaerobic Speed Test (mAST) protocol (15% incline, 244 meter/min) through the use of an ACSM metabolic equation to predict energy expenditure equivalent to that of the AST. Fifteen NCAA Division II male soccer players (mean ± SD, age = 20 ± 1.9 yr; height = 181.3 ± 7.9 cm; weight = 74.8 ± 5.2 kg) participated in this study. Subjects participated in three testing days, one AST trial and two mAST trials all done on separate days, and total run time in seconds was recorded for each trial. Mean AST run times (60.5 ± 10.6) had a significantly positive correlation (p<0.001) with mean trial 1 mAST run times (71.9 ± 9.5). Mean trial 1 mAST run times (71.9 ± 9.5) had a significantly strong, positive correlation (p<0.001) with mean trial 2 mAST run times (75.7±10.2). These findings suggest that the mAST is a valid and reliable measure of anaerobic capacity that is sports-specific to running-type athletes and can be administered on commercial treadmills.

Peak power output during a 15m wheelchair overground sprint can be a measure of anaerobic capacity

Peak power output during a 15m wheelchair overground sprint can be a measure of anaerobic capacity

Effect of plasma donation and blood donation on aerobic and anaerobic responses in exhaustive, severe-intensity exercise

The purpose of this study was to investigate the immediate and delayed effects of plasma donation and blood donation on responses in exhaustive, severe-intensity exercise. Nineteen young men and women performed exhaustive cycle ergometer tests at ∼3.3 W·kg(-1) before and then 2 h, 2 days, and 7 days after withdrawal of either 8-10 mL·kg(-1) (∼700 mL) of plasma (n = 10) or 1 unit (450 mL) of whole blood (n = 9). Time to exhaustion was significantly (p < 0.05) decreased after the removal of plasma (-11% after 2 h) and after the removal of blood (-19% after 2 h and -7% after 2 days). Maximal oxygen uptake (.VO(2max)) was not affected by plasma donation, but .VO(2max) was reduced following blood withdrawal (-15% after 2 h, -10% after 2 days, and -7% after 7 days) presumably because of effects on blood volume, total haemoglobin content, and haemoglobin concentration. The kinetics of the oxygen uptake (.VO2) response was not affected by either intervention. Two measures of anaerobic capacity, postexercise blood lactate concentration, and maximal accumulated oxygen deficit were reduced (-14%, -15%, respectively) 2 h after plasma donation, but neither was affected by blood donation. Removal of plasma and removal of blood have different effects on blood constituency, on the .VO2 response, and on performance. Plasma donation appears to affect exercise performance because of reduced anaerobic capacity, whereas blood donation affects performance because of lowered .VO(2max).

The effect of pedalling cadence on maximal accumulated oxygen deficit

Pedalling cadence influences the oxygen demand and the tolerable duration of severe intensity cycle ergometer exercise. Both of these variables are factors in the calculation of maximal accumulated oxygen deficit (MAOD), which is a widely accepted measure of anaerobic capacity. We were therefore interested in determining whether pedalling cadence affected the value of MAOD. Eighteen university students performed square wave cycling tests, using cadences of 60, 80, and 100 rev min(-1), at work rates selected to cause exhaustion in ~5 min. The oxygen demands for the tests were estimated by extrapolation from the steady-state oxygen uptake in two 4-min moderate intensity bouts performed using each cadence, and were greater at higher cadences. Times to exhaustion were shorter at higher cadences (368 ± 168 s at 60 rev min(-1) > 299 ± 118 s at 80 rev min(-1) > 220 ± 85 s at 100 rev min(-1)). These factors conflated to produce values for MAOD that were not affected by cadence (52 ± 5 ml kg(-1) = 52 ± 5 ml kg(-1) = 52 ± 5 ml kg(-1)). Similarly, the blood lactate concentrations measured 5 min post-exercise were not affected by the pedalling cadence (10.5 ± 2.1 mM = 10.8 ± 1.0 mM = 10.7 ± 2.0 mM). Although muscle contraction frequency influences many exercise responses, we conclude that the expression of anaerobic capacity is not affected by the choice of pedalling cadence.

Maximal accumulated oxygen deficit in running and cycling

The purpose of this study was to compare values of maximal accumulated oxygen deficit (MAOD; a measure of anaerobic capacity) in running and cycling. Twenty-seven women and 25 men performed exhaustive treadmill and cycle ergometer tests of ∼3 min, ∼5 min, and ∼7 min duration. Oxygen demands were estimated assuming a linear relationship between demand and intensity and also using upwardly curvilinear relationships. When oxygen demand was estimated using speed (with exponent 1.05), values for MAOD for the three running tests were virtually identical; the mean of the three values was 78 ± 7 mL·kg⁻¹. Use of an oxygen demand that was estimated using work rate (with exponent 1.00) generated the most similar values for MAOD from the three cycling tests (mean of 59 ± 6 mL·kg⁻¹). Consistent with the higher (p < 0.05) MAOD in running, peak post-exercise blood lactate concentrations were also higher (p < 0.05) in running (13.9 ± 2.2 mmol·L⁻¹) than in cycling (12.6 ± 2.4 mmol·L⁻¹). The results suggest that the relationship between oxygen demand and running speed is upwardly curvilinear for the speeds used to measure MAOD; the relationship between demand and cycle ergometer work rate is linear; MAOD is greater in running than in cycling.

The Maximal Accumulated Oxygen Deficit Method

The maximal accumulated oxygen deficit (MAOD) method has been extensively, but unfortunately not very methodically, used; the procedure used to determine the MAOD varies considerably. Therefore, this review evaluates the effect of different numbers and durations of submaximal exercise bouts on the linear power output (PO)-oxygen uptake ((.)VO2) relationship and thus the MAOD. Changing the number and duration of the submaximal exercise bouts substantially influences the calculated MAOD when relatively long submaximal exercise bouts are used and no fixed value of the y-intercept is forced into the linear regression line. This is most likely due to non-linearity of the PO-(.)VO2 relationship for exercise intensities above the lactate threshold (LT). Non-linearity of the PO-(.)VO2 relationship is probably caused by the development of a slow component in (.)VO2 during submaximal exercise at intensities above the LT. Thus, it is important to standardize the number, duration and intensity of submaximal exercise bouts necessary to establish the PO-(.)VO2 relationship. Beyond changing the number and duration of the submaximal exercise bouts, the effect of different supramaximal exercise bouts on the calculated MAOD has been investigated. While it has become clear that different exercise protocols result in relatively similar values of the MAOD, a closer look at individual data suggests that it may be important to choose an exercise protocol that is representative of the athlete's event. The validity of the MAOD method was studied by different authors comparing the MAOD with metabolic measurements of anaerobic adenosine triphosphate (ATP) production. The main limitation with the metabolic measurements of anaerobic ATP production from muscle biopsy data is that the active muscle mass is unknown, which makes it hard to accurately study the validity of the MAOD method. From the studies that evaluated the reliability of the MAOD method it is clear that the MAOD method may not be a reliable measure of anaerobic capacity. From these findings it can be concluded that the MAOD method may have limitations as a valid and reliable measure of anaerobic capacity and needs to be further improved. We suggest the use of 10 x 4 minute submaximal exercise bouts and a fixed value of the y-intercept for the construction of the linear PO-(.)VO2 relationship, after which the MAOD can be determined during a supramaximal exercise protocol specific for the athlete's event. This method will lead to a more robust PO-(.)VO2 relationship and will therefore result in more valid and reliable results.

Planning the long run

How the long distance runner plans to reach the finish line in the shortest possible time remains elusive as it is determined by complex interaction between psychological and physiological factors. Yet, the athlete is so accurate in expressing his capacity that A. V. Hill stated, ‘some of the most consistent physiological data are contained, not in books on physiology, not even on medicine, but in world's records for running different horizontal distances’ (Lloyd, 1966). A. V. Hill used these records to formulate a mathematical model with the energy required for running expressed as the sum of a store and a continuous provision. Physiological indices describe work capacity in terms of pulmonary oxygen uptake and accumulation of lactate in blood although the distributing volume and the elimination of lactate are not regularly evaluated. A quantitative measure of anaerobic capacity, albeit too large, is the part of the total energy demand that is not covered by the pulmonary oxygen uptake during exercise and expressed as the (maximal) oxygen deficit, while others find the workload that elicits a given blood lactate level (often 4 mm) to be a sensitive predictor of performance. Also the ability to excel over long distances relates to the muscle glycogen level and genetic variation comes into play, e.g. with the percentage of slow twitch muscle fibres being higher in the endurance athlete than in the general population (70–80%versus 50%). Furthermore, training enhances not only aerobic capacity but also the number of capillaries around each muscle fibre, and hence the oxygen diffusion into the cells is enhanced 2.5-fold. Such physiological descriptions of the athlete, however, provide little help in choosing the optimal race pace while the most obvious candidate for that purpose is the ventilatory response. Ventilation increases curvilinearly with work rate to impressive levels as it may approach 270 l min−1 during whole body exercise (Jensen et al. 2001). Several mathematical procedures have been used to define the work rate that elicits the progressive increase in ventilation, but for the athlete that work intensity simply manifests when he cannot talk without being dysphonic. The study by Amann et al. (2009) in this issue of The Journal of Physiology has taken up the challenge to evaluate whether neural influence from the exercising muscles is integrated in the central nervous system and contributes to the choice of work rate during a 5 km ergometer cycling time trial. The same group (Amann et al. 2008) found in a similar study increased motor output during exercise where the neural feedback from the working muscles was attenuated by epidural anaesthesia, but since the local anaesthetic also affected muscle strength, time trial performance was reduced. In contrast, intrathecal administration of the morphine analogue fentanyl did not affect muscle strength and performance was enhanced by 6% over the first half of the maximal effort but then decreased by 11% over the second half of the trial (Amann et al. 2009). Obviously, the athletes overestimated their work capacity at the beginning of the trial possibly because less information reached the central nervous system from the working muscles in response to the intrathecal administration of fentanyl. Yet, at least one other interpretation is relevant besides influence from, e.g. skin, body and notably brain temperature (Nybo et al. 2002). With the administration of fentanyl, the ventilatory response to the larger workload accomplished in the first half of the trial was reduced by almost 4%. Thus, if we accept that ventilation provides an important feedback for the choice of the work intensity, it may be that this attenuated signal indicated to the athlete that he could increase the pace. Before we concur with Amann et al. (2009) that afferent signals from the muscles are crucial for choosing the optimal work intensity, at least one more piece of information needs to be provided. It should be shown whether the same elevated initial work load is chosen while ventilation is maintained at the same level as in the control trial, e.g. by administration of doxapram. Yet, the unique work by Amann et al. (2009) opens an avenue for evaluating, in physiological terms, the experience of the athlete while previous studies describe performance in terms of the relative work load where heart rate, oxygen uptake and blood lactate are the most often used references.

Relationships Between Blood Lactate and Measures of Anaerobic Capacity in Elite Women's Ice Hockey

Relationships Between Blood Lactate and Measures of Anaerobic Capacity in Elite Women's Ice Hockey

Anaerobic Running Capacity Determined from a 3-Parameter Systems Model: Relationship with other Anaerobic Indices and with Running Performance in the 800 m-Run

The purpose of this study was to compare anaerobic running capacity (ARC, i.e., the distance that can be run using only stored energy sources in the muscle) determined from a 3-parameter systems model with other anaerobic indices and with running performance in the 800 m. Seventeen trained male subjects (.VO(2max) = 66.54 +/- 7.29 ml . min (-1) . kg (-1)) performed an incremental test to exhaustion for the determination of .VO(2max) and peak treadmill velocity (PTV), five randomly ordered constant velocity tests at 95, 100, 105, 110, and 120 % of PTV to compute ARC and oxygen deficit (O(2)def, at 110 % of PTV), and a 800-m time trial to determine running performance (mean velocity over the distance, V (800 m)) and peak blood lactate concentration ([La (-)] (b, peak)). ARC (467 +/- 123 m) was positively correlated with O(2)def (56.35 +/- 18.47 ml . kg (-1); r = 0.57; p < 0.05), but not with [La (-)] (b, peak) (15.08 +/- 1.48 mmol . l (-1); r = - 0.16; p > 0.05). The O(2) equivalent of ARC (i.e., the product of ARC by the energy cost of running; 103.74 +/- 28.25 ml . kg (-1)), which is considered as an indirect estimation of O(2)def, was significantly higher than O(2)def (p < 0.01, effect size = 1.99). It was concluded that ARC is partially determined by anaerobic pathway, but that it probably does not provide an accurate measure of anaerobic capacity, if, however, O(2)def can be considered as a criterion measure for it.

Quantification of anaerobic capacity

Anaerobic capacity may be defined as the maximal amount of ATP formed by the anaerobic processes during a single bout of maximal exercise. While several methods have been presented to measure a person's anaerobic capacity, none have become universally accepted. The muscle biopsy technique provides information on the anaerobic energy release from direct measures of ATP and CP breakdown and muscle lactate concentrations. As a practical measure of anaerobic capacity, the method may be limited, as it is an invasive, skilled technique. Furthermore, it has the limitation of measuring relative changes in concentrations, not amounts, such that the anaerobic contribution is estimated from estimates of the active muscle mass involvement. Measurement of lactate in blood after exhaustive exercise has frequently been used, but several factors suggest that, while it provides an indication of the extent of anaerobic glycolysis, it cannot be used as a quantitative measure of the anaerobic energy yield. The mean power during an all‐out effort on a bicycle ergometer has also been assumed to be a measure of anaerobic capacity, yet it provides only an indication of the ability to maintain high power outputs. Concerns over the duration of the test, the protocol and type of ergometer used and the contribution of the aerobic energy system to the energy supply also limit its validity as a measure of anaerobic capacity. The oxygen debt, defined as the recovery oxygen uptake above resting metabolic rates, has been discredited as a valid and reliable measure of the anaerobic capacity, as it is generally acknowledged that mechanisms other than the metabolism of lactate also contribute to the post‐exercise oxygen uptake. The recent work of Medbø et al. in re‐examining the issue of oxygen deficit has created considerable interest in its use as a measure of anaerobic capacity. The measurement of oxygen deficit directly depends on the accurate assessment of the energy cost of the work completed. This is not difficult during submaximal exercise, as the steady‐state oxygen uptake represents the energy costs. During exhaustive supramaximal exercise, the validity of the maximal accumulated oxygen deficit as a measure of the anaerobic capacity has been questioned, as the energy cost is estimated and not measured, either by assuming a given mechanical efficiency or by extrapolating the submaximal relationship between work intensity and oxygen uptake to supramaximal levels. Despite these theoretical objections, the maximal accumuiated oxygen deficit method remains a promising measure of the anaerobic capacity, as it provides a non‐invasive means of quantifying the anaerobic energy release during exhaustive exercise.

The critical power concept. A review.

The basis of the critical power concept is that there is a hyperbolic relationship between power output and the time that the power output can be sustained. The relationship can be described based on the results of a series of 3 to 7 or more timed all-out predicting trials. Theoretically, the power asymptote of the relationship, CP (critical power), can be sustained without fatigue; in fact, exhaustion occurs after about 30 to 60 minutes of exercise at CP. Nevertheless, CP is related to the fatigue threshold, the ventilatory and lactate thresholds, and maximum oxygen uptake (VO2max), and it provides a measure of aerobic fitness. The second parameter of the relationship, AWC (anaerobic work capacity), is related to work performed in a 30-second Wingate test, work in intermittent high-intensity exercise, and oxygen deficit, and it provides a measure of anaerobic capacity. The accuracy of the parameter estimates may be enhanced by careful selection of the power outputs for the predicting trials and by performing a greater number of trials. These parameters provide fitness measures which are mode-specific, combine energy production and mechanical efficiency in 1 variable, and do not require the use of expensive equipment or invasive procedures. However, the attractiveness of the critical power concept diminishes if too many predicting trials are required for generation of parameter estimates with a reasonable degree of accuracy.

Validity of Self-assessed Physical Fitness

This study compared self-ratings of components of physical fitness with objective measures of physical fitness. We made comparisons in two groups of male infantry soldiers (n = 96 and n = 276) and one group of older male military officers (n = 241). To obtain self-ratings of physical fitness, we asked subjects, "Compared to others of your age and sex, how would you rate your (a) endurance, (b) sprint speed, (c) strength, (d) flexibility?" Subjects responded to each of the four questions on a five-point scale. Self-ratings of endurance were systematically related to three measures of aerobic capacity, including VO2max, peak VO2, and two-mile run time (r = 0.29 to 0.53). Self-ratings of sprint speed showed only weak relationships to measures of anaerobic capacity assessed by the Wingate test, push-ups, and sit-ups (r = 0.10 to 0.17). Strength ratings were systematically related to measures of maximal strength (r = 0.28 to 0.53). Upper body strength measures were more closely associated with the self-ratings of strength than were measures of lower body strength. Responses to the flexibility question were systematically related to measures of hip/low back flexibility (r = 0.30 and 0.48) but not to other measures of flexibility. Apparently, physically active subjects can approximately classify their aerobic capacity, muscle strength, and some types of flexibility.

Skeletal muscle atrophy in response to 14 days of weightlessness: vastus medialis

The vastus medialis (VM) from rats after 14 days of microgravity on COSMOS 2044 (F) was compared with VM from tail-suspended hindlimb-unloaded rats (T) and ground controls, including vivarium (V), synchronous (S), and basal (B) animals. The VM is composed chiefly of fast-twitch fibers; however, it contains a deep portion closer to the bone with mixed slow- and fast-twitch fibers. In the mixed-fiber portion, type I and II fiber areas were significantly reduced in F animals. In the homogeneous portion with chiefly fast-twitch fibers, F rats also showed reductions in cross-sectional areas compared with T, V, and B but not S rats. Fiber densities (fibers/mm2) were greatest in VM from F rats. Capillary density changes paralleled fiber density changes. F animals have significantly greater density of capillaries in the mixed-fiber portion. Concentrations of protein, RNA, and DNA were highest in V controls, whereas F rats had the lowest level of total RNA. Lactate dehydrogenase activity, one measure of anaerobic capacity, was greater in F than in S rats. Citrate synthase activity, a measure of oxidative capacity, showed no significant differences between groups. Although triglyceride stores of VM were greater in F than in T rats, there were no significant differences from any of the control groups. It was concluded that VM wet weights may be a less sensitive measure of atrophy than the fiber area measurements. Fiber area decreases and fiber density increases in F animals were quantitatively comparable to those in soleus and extensor digitorum longus after 7 days of weightless flight in Spacelab 3. Our results suggest that VM shows measurable responses to weightlessness.

Physiological factors in infantry operations

Male infantry soldiers (n = 34) were studied before, during, and after a 5-day simulated combat exercise. During the exercise, subjects were rated on their field performance by senior infantry non-commissioned officers. Prior to the exercise, direct measures of body composition and maximal oxygen uptake were obtained. Before and after the exercise the Army Physical Fitness Test and various measures of anaerobic capacity (Wingate and Thorstensson tests) and muscular strength (isometric and isokinetic) were obtained. Results showed no significant decrement in field performance during the exercise. Upper-body anaerobic capacity and strength declined following the exercise, although the results for upper-body strength were not consistent on all measures. Field performance was significantly correlated with measures of upper-body anaerobic capacity and strength. Upper-body strength and anaerobic capacity appear to be important for infantry operations and subject to declines during combat operations.

Recovery O2 and blood lactic acid: longitudinal analysis in boys aged 11 to 15 years.

Nineteen boys were tested annually from age 11 to 15 years. Recovery O2 (or O2 debt in l and ml X kg-1) and blood lactate ([La], mmol X l-1) were measured following supramaximal treadmill tests (20% grade) designed to stress the anaerobic energy systems maximally. The purpose was to describe the rate of development of anaerobic capacity (AnC) from pre-puberty to adolescence. AnC improved from age 11 to 15 years, as indicated by a tripling of recovery O2 (l), 80% increase in recovery O2 per kg and 45% in [La]. Changes were similar from year to year with average yearly increments in recovery O2 of 0.8 l or 9 ml X kg-1 and in [La] of 0.9 mmol X l-1. Individual data also were plotted in relation to age of peak height velocity (PHV, 12.9 +/- 1.2 years). Changes in the measures of AnC were not significantly different when related to biological rather than chronological age. Development of AnC did not show a growth function curve and was not closely correlated with size, nor was the development of AnC enhanced immediately following maturation. Thus, in this longitudinal study, recovery O2 and [La] as measures of AnC showed large increases from age 11 to 15 years, but the gains were similar year to year rather than related to size growth, per se, or hormonal influences at maturation postulated to induce qualitative changes in glycolytic potential of muscle.

Oxygen transport, tissue glycogen stores, and tissue pyruvate kinase activity in muskrats

Oxygen stores, respiratory properties of blood, tissue glycogen concentrations, and the rate-limiting enzyme for glycolysis, pyruvate kinase, were examined in muskrats (Ondatra zibethicus). Of the potential oxygen stores, lung volume (19.6 ± 0.68 mL/kg), and blood hemoglobin concentration (13.0 ± 0.34 g Hb/100 mL blood) were typical of terrestrial mammals, while concentrations of myoglobin in heart (7.4 ± 0.1 mg Mb/g tissue) and gastrocnemius muscle (13.3 ± 0.5 mg Mb/g tissue) were significantly higher than values from the same tissues in the laboratory rat. Blood P50 (oxygen half-saturation pressure) at pH 7.4, 24.4 ± 1.36 Torr (1 Torr = 133.322 Pa), and Bohr effect, −0.64 ± 0.04, also were significantly different, while the Hill coefficient and buffering capacity were comparable for both species. Of our measures of anaerobic capacity, glycogen concentrations and pyruvate kinase activities in heart, brain, and gastrocnemius muscle of O. zibethicus were all comparable to values obtained for terrestrial mammals. We conclude that muskrats tolerate submersion by adaptations associated with aerobic metabolism, although a review of the literature shows that these adaptations are fully developed only in animals freshly captured during winter.

Physical training under the influence of beta-blockade in rats. III. Effects on muscular metabolism.

Rats were trained by daily running exercises for 7 weeks. In addition, one group of rats was trained under the influence of propranolol, while another group received daily injections of propranolol only. None of the treatments used had influence on the activities of myocardial enzymes: 3-hydroxyacyl-CoA - dehydrogenase (HADH), succinate dehydrogenase (SDH), malate dehydrogenase (MDH), and citrate synthase (CS) which were assayed for estimating oxidative capacity, or lactate dehydrogenase (LDH) which was used as a measure of anaerobic capacity. Training without propranolol resulted in elevated activities of the oxidative enzymes in M. extensor digitorum and in M. soleus. The corresponding changes in the rat group trained with propranolol always were much smaller, despite an equal amount of training. Only the trend for lowered activity of LDH was observable in skeletal muscle of the rat groups trained both with and without propranolol. Long-term beta-blockade alone did not induce enzymatic changes. It is concluded that a functioning sympathetic nervous system is necessary for the adaptive responses of muscular metabolism to training. Blockade of the sympathetic influence during exercise periods also hampers the training-induced responses.

Morphological and Physiological Factors Related to Endurance Performance of 11- to 12-Year-Old Girls

Abstract This study examined the extent to which variance in endurance performance could be explained by various physiological and morphological factors in 11-to 12-year-old girls (N = 33). [Vdot]O2 max (ml/kg/minute), determined in a multistage treadmill test, was significantly related to run time (r = −.70). However, when percentage of fat as estimated from skinfolds and girths was held constant, the partial correlation was .09. The correlation between the sum of five skinfolds and run time was .92; the greater amounts of subcutaneous fat were associated with poorer performance. The second independent variable to be selected into a forward selection regression equation was the score on an all-out 1-minute steptest, an indirect measure of anaerobic capacity. The third variable selected was an index of maturity—whether or not the girls had achieved menarche; the more mature girls tended to do worse on the run. These three variables accounted for 90% of the variance in run time (R = .95). The dominance of ...