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Background: Despite advances in medical and cardiac resynchronization therapy (CRT), individuals with chronic congestive heart failure (CHF) have persistent symptoms, including exercise intolerance. Optimizing cardio-locomotor coupling may increase stroke volume and skeletal muscle perfusion as previously shown in healthy runners. Therefore, we tested the hypothesis that exercise stroke volume and cardiac output would be higher during fixed-paced walking when steps were synchronized with the diastolic compared with systolic portion of the cardiac cycle in patients with CHF and CRT., Methods: Ten participants (58±17 years of age; 40% female) with CHF and previously implanted CRT pacemakers completed 5-minute bouts of walking on a treadmill (range, 1.5-3 mph). Participants were randomly assigned to first walking to an auditory tone to synchronize their foot strike to either the systolic (0% or 100±15% of the R-R interval) or diastolic phase (45±15% of the R-R interval) of their cardiac cycle and underwent assessments of oxygen uptake (V̇o 2 ; indirect calorimetry) and cardiac output (acetylene rebreathing). Data were compared through paired-samples t tests., Results: V̇o 2 was similar between conditions (diastolic 1.02±0.44 versus systolic 1.05±0.42 L/min; P =0.299). Compared with systolic walking, stroke volume (diastolic 80±28 versus systolic 74±26 mL; P =0.003) and cardiac output (8.3±3.5 versus 7.9±3.4 L/min; P =0.004) were higher during diastolic walking; heart rate (paced) was not different between conditions. Mean arterial pressure was significantly lower during diastolic walking (85±12 versus 98±20 mm Hg; P =0.007)., Conclusions: In patients with CHF who have received CRT, diastolic stepping increases stroke volume and oxygen delivery and decreases afterload. We speculate that, if added to pacemakers, this cardio-locomotor coupling technology may maximize CRT efficiency and increase exercise participation and quality of life in patients with CHF., Competing Interests: Disclosures None.

Human, but not canine or equine running performance, is significantly stratified by sex. The degree of stratification has obvious implications for classification and regulation in athletics. However, whether the widely cited sex difference of 10%-12% applies equally to sprint and endurance running events is unknown. Here, different determining factors for sprint (ground force/body mass) versus endurance performance (energy supply and demand) and existing trends, led us to hypothesize that sex performance differences for sprint running would increase with distance and be relatively small. We quantified sex performance differences using: 1 ) the race times of the world's fastest males and females ( n = 40 each) over a 15-year period (2003-2018) at nine standard racing distances (60-10,000 m), and 2 ) the 10-m segment times of male ( n = 14) and female ( n = 12) athletes in World Championship 100-m finals. Between-sex performance time differences increased with sprint event distance (60 m-8.6%, 100 m-9.6%, 200 m-11.0%, 400 m-11.7%) and were smaller than the relatively constant mean (12.4 ± 0.3%) observed across the five longer events from 800 to 10,000 m. Between-sex time differences for the 10-m segments within the 100-m dash event increased throughout spanning 5.6%-14.2% from the first to last segment. We conclude that sex differences in sprint running performance increase with race and running distance. NEW & NOTEWORTHY Sex performance differences for sprint running bursts are small (<6%), but widen as the distance sprinted increases (range: 5.6%-14.2%). The distance dependency identified here for sprinting differs from the prevailing literature view of between-sex performance differences for the human running of 10%-12% regardless of distance. The variable sprint margins observed reflect the relative performance benefits shorter females have for brief, acceleration-dependent efforts versus those taller males have for longer steadier-speed sprint efforts.

This comment addresses the incomplete presentation and incorrect conclusion offered in the recent manuscript of Beck et al . ( R. Soc. Open Sci. 9 , 211799 (doi:10.1098/rsos.211799)). The manuscript introduces biomechanical and performance data on the fastest-ever, bilateral amputee 400 m runner. Using an advantage standard of not faster than the fastest non-amputee runner ever (i.e. performance superior to that of the intact-limb world record-holder), the Beck et al . manuscript concludes that sprint running performance on bilateral, lower-limb prostheses is not unequivocally advantageous compared to the biological limb condition. The manuscript acknowledges the long-standing support of the authors for the numerous eligibility applications of the bilateral-amputee athlete. However, it does not acknowledge that the athlete's anatomically disproportionate prosthetic limb lengths (+15 cm versus the World Para Athletics maximum) are ineligible in both Olympic and Paralympic track competition due to their performance-enhancing properties. Also not acknowledged are the slower sprint performances of the bilateral-amputee athlete on limbs of shorter length that directly refute their manuscript's primary conclusion. Our contribution here provides essential background information and data not included in the Beck et al. manuscript that make the correct empirical conclusion clear: artificially long legs artificially enhance long sprint running performance., (© 2022 The Authors.)

Background: Synchronized arm and leg motion are characteristic of human running. Leg motion is an obvious gait requirement, but arm motion is not, and its functional contribution to running performance is not known. Because arm-leg coupling serves to reduce rotation about the body's vertical axis, arm motion may be necessary to achieve the body positions that optimize ground force application and performance., Research Question: Does restricting arm motion compromise performance in short sprints?, Methods: Sprint performance was measured in 17 athletes during normal and restricted arm motion conditions. Restriction was self-imposed via arm folding across the chest with each hand on the opposite shoulder. Track and field (TF, n = 7) and team sport (TS, n = 10) athletes completed habituation and performance test sessions that included six counterbalanced 30 m sprints: three each in normal and restricted arm conditions. TS participants performed standing starts in both conditions. TF participants performed block starts with extended arms for the normal condition and elevated platform support of the elbows for the crossed-arm, restricted condition. Instantaneous velocity was measured throughout each trial using a radar device. Average sprint performance times were compared using a Repeated Measures ANOVA with Tukey post-hoc tests for the entire group and for the TF and TS subgroups., Results: The 30 m times were faster for normal vs. restricted arm conditions, but the between-condition difference was only 1.6% overall and < 0.10 s for the entire group (4.82 ± 0.46 s vs. 4.90 ± 0.46 s, respectively; p < 0.001) and both TF (4.55 ± 0.34 vs. 4.63 ± 0.32 s; p < 0.001) and TS subgroups (5.01 ± 0.46 vs. 5.08 ± 0.47 s; p < 0.001)., Significance: Our findings suggest that when arm motion is restricted, compensatory upper body motions can provide the rotational forces needed to offset the lower body angular momentum generated by the swinging legs. We conclude that restricting arm motion compromised short sprint running performance, but only marginally., (Copyright © 2022 Elsevier B.V. All rights reserved.)

We addressed a practical question that remains largely unanswered after more than a century of active investigation: can equations developed in the laboratory accurately predict the energy expended under free-walking conditions in the field? Seven subjects walked a field course of 6,415 m that varied in gradient (-3.0 to +5.0%) and terrain (asphalt, grass) under unloaded (body weight only, W b ) and balanced, torso-loaded (1.30 × W b ) conditions at self-selected speeds while wearing portable calorimeter and GPS units. Portable calorimeter measures were corrected for a consistent measurement-range offset (+13.8 ± 1.8%, means ± SD) versus a well-validated laboratory system (Parvomedics TrueOne). Predicted energy expenditure totals (mL O 2 /kg) from four literature equations: ACSM, Looney, Minimum Mechanics, and Pandolf, were generated using the speeds and gradients measured throughout each trial in conjunction with empirically determined terrain/treadmill factors (asphalt = 1.0, grass = 1.08). The mean energy expenditure total measured for the unloaded field trials (981 ± 91 mL O 2 /kg) was overpredicted by +4%, +13%, +17%, and +20% by the Minimum Mechanics, ACSM, Pandolf, and Looney equations, respectively (corresponding predicted totals: 1,018 ± 19, 1,108 ± 26, 1,145 ± 37, and 1,176 ± 24 mL O 2 /kg). The measured loaded-trial total (1,310 ± 153 mL O 2 /kg) was slightly underpredicted by the Minimum Mechanics equation (-2%, 1,289 ± 22 mL O 2 /kg) and overpredicted by the Pandolf equation (+13%, 1,463 ± 32 mL O 2 /kg). Computational comparisons for hypothetical trials at different constant speeds (range: 0.6-1.8 m/s) on variable-gradient loop courses revealed between-equation prediction differences from 0% to 37%. We conclude that treadmill-based predictions of free-walking field energy expenditure are equation-dependent but can be highly accurate with rigorous implementation. NEW & NOTEWORTHY Here, we investigated the accuracy with which four laboratory-based equations can predict field-walking energy expenditure at freely selected speeds across varying gradients and terrain. Empirical tests involving 6,415-m trials under two load conditions indicated that predictions are significantly equation dependent but can be highly accurate (i.e., ±4%). Computations inputting identical weight, speed, and gradient values for different theoretical constant-speed trials (0.6-1.8 m/s) identified between-equation prediction differences as large as 37%.

Although running shoes alter foot-ground reaction forces, particularly during impact, how they do so is incompletely understood. Here, we hypothesized that footwear effects on running ground reaction force-time patterns can be accurately predicted from the motion of two components of the body's mass (m b ): the contacting lower-limb (m 1  = 0.08m b ) and the remainder (m 2  = 0.92m b ). Simultaneous motion and vertical ground reaction force-time data were acquired at 1,000 Hz from eight uninstructed subjects running on a force-instrumented treadmill at 4.0 and 7.0 m / s under four footwear conditions: barefoot, minimal sole, thin sole, and thick sole. Vertical ground reaction force-time patterns were generated from the two-mass model using body mass and footfall-specific measures of contact time, aerial time, and lower-limb impact deceleration. Model force-time patterns generated using the empirical inputs acquired for each footfall matched the measured patterns closely across the four footwear conditions at both protocol speeds ( r 2  = 0.96 ± 0.004; root mean squared error  = 0.17 ± 0.01 body-weight units; n = 275 total footfalls). Foot landing angles (θ F ) were inversely related to footwear thickness; more positive or plantar-flexed landing angles coincided with longer-impact durations and force-time patterns lacking distinct rising-edge force peaks. Our results support three conclusions: 1 ) running ground reaction force-time patterns across footwear conditions can be accurately predicted using our two-mass, two-impulse model, 2 ) impact forces, regardless of foot strike mechanics, can be accurately quantified from lower-limb motion and a fixed anatomical mass (0.08m b ), and 3 ) runners maintain similar loading rates (ΔF vertical /Δtime) across footwear conditions by altering foot strike angle to regulate the duration of impact. NEW & NOTEWORTHY Here, we validate a two-mass, two-impulse model of running vertical ground reaction forces across four footwear thickness conditions (barefoot, minimal, thin, thick). Our model allows the impact portion of the impulse to be extracted from measured total ground reaction force-time patterns using motion data from the ankle. The gait adjustments observed across footwear conditions revealed that runners maintained similar loading rates across footwear conditions by altering foot strike angles to regulate the duration of impact.

The metabolic energy that human walking requires can vary by more than 10-fold, depending on the speed, surface gradient, and load carried. Although the mechanical factors determining economy are generally considered to be numerous and complex, we tested a minimum mechanics hypothesis that only three variables are needed for broad, accurate prediction: speed, surface grade, and total gravitational load. We first measured steady-state rates of oxygen uptake in 20 healthy adult subjects during unloaded treadmill trials from 0.4 to 1.6 m/s on six gradients: -6, -3, 0, 3, 6, and 9°. Next, we tested a second set of 20 subjects under three torso-loading conditions (no-load, +18, and +31% body weight) at speeds from 0.6 to 1.4 m/s on the same six gradients. Metabolic rates spanned a 14-fold range from supine rest to the greatest single-trial walking mean (3.1 ± 0.1 to 43.3 ± 0.5 ml O 2 ·kg -body -1 ·min -1 , respectively). As theorized, the walking portion (V̇o 2-walk  =  V̇o 2-gross - V̇o 2-supine-rest ) of the body's gross metabolic rate increased in direct proportion to load and largely in accordance with support force requirements across both speed and grade. Consequently, a single minimum-mechanics equation was derived from the data of 10 unloaded-condition subjects to predict the pooled mass-specific economy (V̇o 2-gross , ml O 2 ·kg -body + load -1 ·min -1 ) of all the remaining loaded and unloaded trials combined ( n = 1,412 trials from 90 speed/grade/load conditions). The accuracy of prediction achieved ( r 2  = 0.99, SEE = 1.06 ml O 2 ·kg -1 ·min -1 ) leads us to conclude that human walking economy is predictably determined by the minimum mechanical requirements present across a broad range of conditions. NEW & NOTEWORTHY Introduced is a "minimum mechanics" model that predicts human walking economy across a broad range of conditions from only three variables: speed, surface grade, and body-plus-load mass. The derivation/validation data set includes steady-state loaded and unloaded walking trials ( n = 3,414) that span a fourfold range of walking speeds on each of six different surface gradients (-6 to +9°). The accuracy of our minimum mechanics model ( r 2  = 0.99; SEE = 1.06 ml O 2 ·kg -1 ·min -1 ) appreciably exceeds that of currently used standards., (Copyright © 2017 the American Physiological Society.)

The relationship between gait mechanics and running ground reaction forces is widely regarded as complex. This viewpoint has evolved primarily via efforts to explain the rising edge of vertical force-time waveforms observed during slow human running. Existing theoretical models do provide good rising-edge fits, but require more than a dozen input variables to sum the force contributions of four or more vague components of the body's total mass (m b ). Here, we hypothesized that the force contributions of two discrete body mass components are sufficient to account for vertical ground reaction force-time waveform patterns in full (stance foot and shank, m 1 =0.08m b ; remaining mass, m 2 =0.92m b ). We tested this hypothesis directly by acquiring simultaneous limb motion and ground reaction force data across a broad range of running speeds (3.0-11.1 m s -1 ) from 42 subjects who differed in body mass (range: 43-105 kg) and foot-strike mechanics. Predicted waveforms were generated from our two-mass model using body mass and three stride-specific measures: contact time, aerial time and lower limb vertical acceleration during impact. Measured waveforms (N=500) differed in shape and varied by more than twofold in amplitude and duration. Nonetheless, the overall agreement between the 500 measured waveforms and those generated independently by the model approached unity (R 2 =0.95±0.04, mean±s.d.), with minimal variation across the slow, medium and fast running speeds tested (ΔR 2 ≤0.04), and between rear-foot (R 2 =0.94±0.04, N=177) versus fore-foot (R 2 =0.95±0.04, N=323) strike mechanics. We conclude that the motion of two anatomically discrete components of the body's mass is sufficient to explain the vertical ground reaction force-time waveform patterns observed during human running., (© 2017. Published by The Company of Biologists Ltd.)

Accurate prediction of the metabolic energy that walking requires can inform numerous health, bodily status, and fitness outcomes. We adopted a two-step approach to identifying a concise, generalized equation for predicting level human walking metabolism. Using literature-aggregated values we compared 1) the predictive accuracy of three literature equations: American College of Sports Medicine (ACSM), Pandolf et al., and Height-Weight-Speed (HWS); and 2) the goodness-of-fit possible from one- vs. two-component descriptions of walking metabolism. Literature metabolic rate values (n = 127; speed range = 0.4 to 1.9 m/s) were aggregated from 25 subject populations (n = 5-42) whose means spanned a 1.8-fold range of heights and a 4.2-fold range of weights. Population-specific resting metabolic rates (V̇o2 rest) were determined using standardized equations. Our first finding was that the ACSM and Pandolf et al. equations underpredicted nearly all 127 literature-aggregated values. Consequently, their standard errors of estimate (SEE) were nearly four times greater than those of the HWS equation (4.51 and 4.39 vs. 1.13 ml O2·kg(-1)·min(-1), respectively). For our second comparison, empirical best-fit relationships for walking metabolism were derived from the data set in one- and two-component forms for three V̇o2-speed model types: linear (∝V(1.0)), exponential (∝V(2.0)), and exponential/height (∝V(2.0)/Ht). We found that the proportion of variance (R(2)) accounted for, when averaged across the three model types, was substantially lower for one- vs. two-component versions (0.63 ± 0.1 vs. 0.90 ± 0.03) and the predictive errors were nearly twice as great (SEE = 2.22 vs. 1.21 ml O2·kg(-1)·min(-1)). Our final analysis identified the following concise, generalized equation for predicting level human walking metabolism: V̇o2 total = V̇o2 rest + 3.85 + 5.97·V(2)/Ht (where V is measured in m/s, Ht in meters, and V̇o2 in ml O2·kg(-1)·min(-1))., (Copyright © 2016 the American Physiological Society.)

Are the fastest running speeds achieved using the simple-spring stance mechanics predicted by the classic spring-mass model? We hypothesized that a passive, linear-spring model would not account for the running mechanics that maximize ground force application and speed. We tested this hypothesis by comparing patterns of ground force application across athletic specialization (competitive sprinters vs. athlete nonsprinters, n = 7 each) and running speed (top speeds vs. slower ones). Vertical ground reaction forces at 5.0 and 7.0 m/s, and individual top speeds (n = 797 total footfalls) were acquired while subjects ran on a custom, high-speed force treadmill. The goodness of fit between measured vertical force vs. time waveform patterns and the patterns predicted by the spring-mass model were assessed using the R(2) statistic (where an R(2) of 1.00 = perfect fit). As hypothesized, the force application patterns of the competitive sprinters deviated significantly more from the simple-spring pattern than those of the athlete, nonsprinters across the three test speeds (R(2) <0.85 vs. R(2) ≥ 0.91, respectively), and deviated most at top speed (R(2) = 0.78 ± 0.02). Sprinters attained faster top speeds than nonsprinters (10.4 ± 0.3 vs. 8.7 ± 0.3 m/s) by applying greater vertical forces during the first half (2.65 ± 0.05 vs. 2.21 ± 0.05 body wt), but not the second half (1.71 ± 0.04 vs. 1.73 ± 0.04 body wt) of the stance phase. We conclude that a passive, simple-spring model has limited application to sprint running performance because the swiftest runners use an asymmetrical pattern of force application to maximize ground reaction forces and attain faster speeds., (Copyright © 2014 the American Physiological Society.)

Running performance, energy requirements and musculoskeletal stresses are directly related to the action-reaction forces between the limb and the ground. For human runners, the force-time patterns from individual footfalls can vary considerably across speed, foot-strike and footwear conditions. Here, we used four human footfalls with distinctly different vertical force-time waveform patterns to evaluate whether a basic mechanical model might explain all of them. Our model partitions the body's total mass (1.0 Mb) into two invariant mass fractions (lower limb=0.08, remaining body mass=0.92) and allows the instantaneous collisional velocities of the former to vary. The best fits achieved (R(2) range=0.95-0.98, mean=0.97 ± 0.01) indicate that the model is capable of accounting for nearly all of the variability observed in the four waveform types tested: barefoot jog, rear-foot strike run, fore-foot strike run and fore-foot strike sprint. We conclude that different running ground reaction force-time patterns may have the same mechanical basis., (© 2014. Published by The Company of Biologists Ltd.)

We formulated a "one-size-fits-all" model that predicts the energy requirements of level human walking from height, weight, and walking speed. Our three-component model theorizes that the energy expended per kilogram per stride is independent of stature at mechanically equivalent walking speeds. We measured steady-state rates of oxygen uptake of 78 subjects who spanned a nearly twofold range of statures (1.07-2.11 m) and sevenfold range of body masses (16-112 kg) at treadmill speeds from 0.4 to 1.9 m/s. We tested the size independence of the model by deriving best-fit equations in the form of the model on four stature groups (n ≥ 15): short, moderately short, moderately tall, and tall. The mean walking metabolic rates predicted by these four independently derived equations for the same set of reference subjects (n = 16; stature range: 1.30-1.90 m) agreed with one another to within an average of 5.2 ± 3.7% at the four intermediate speeds in our protocol. We next evaluated the model's gross predictive accuracy by dividing our 78 subjects into 39 stature-matched pairs of experimental and validation group subjects. The model best-fit equation derived on the experimental group subjects predicted the walking metabolic rates of the validation group subjects to within an average of 8.1 ± 6.7% (R(2) = 0.90; standard error of estimate = 1.34 ml O2·kg(-1)·min(-1)). The predictive error of the American College of Sports Medicine equation (18.0 ± 13.1%), which does not include stature as a predictor, was more than twice as large for the same subject group. We conclude that the energy cost of level human walking can be accurately predicted from height, weight, and walking speed.

Prevailing physiological paradigms explain both sprint and endurance exercise performance in terms of the availability of metabolic energy. However, for all-out efforts of 60 s or less, the prevailing view is no longer viable. Contemporary evidence indicates that sprinting performance is determined by musculoskeletal force application, with a duration dependency explained by the intrinsically rapid rates at which skeletal muscle fatigues in vivo.

The metabolic and mechanical requirements of walking are considered to be of fundamental importance to the health, physiological function and even the evolution of modern humans. Although walking energy expenditure and gait mechanics are clearly linked, a direct quantitative relationship has not emerged in more than a century of formal investigation. Here, on the basis of previous observations that children and smaller adult walkers expend more energy on a per kilogram basis than larger ones do, and the theory of dynamic similarity, we hypothesized that body length (or stature, L(b)) explains the apparent body-size dependency of human walking economy. We measured metabolic rates and gait mechanics at six speeds from 0.4 to 1.9 m s(-1) in 48 human subjects who varied by a factor of 1.5 in stature and approximately six in both age and body mass. In accordance with theoretical expectation, we found the most economical walking speeds measured (J kg(-1) m(-1)) to be dynamically equivalent (i.e. similar U, where U=velocity(2)/gravity · leg length) among smaller and larger individuals. At these speeds, stride lengths were directly proportional to stature whereas the metabolic cost per stride was largely invariant (2.74±0.12 J kg(-1) stride(-1)). The tight coupling of stature, gait mechanics and metabolic energy expenditure resulted in an inverse relationship between mass-specific transport costs and stature (E(trans)/M(b)∝L(b)(-0.95), J kg(-1) m(-1)). We conclude that humans spanning a broad range of ages, statures and masses incur the same mass-specific metabolic cost to walk a horizontal distance equal to their stature.

Running speed is limited by a mechanical interaction between the stance and swing phases of the stride. Here, we tested whether stance phase limitations are imposed by ground force maximums or foot-ground contact time minimums. We selected one-legged hopping and backward running as experimental contrasts to forward running and had seven athletic subjects complete progressive discontinuous treadmill tests to failure to determine their top speeds in each of the three gaits. Vertical ground reaction forces [in body weights (W(b))] and periods of ground force application (T(c); s) were measured using a custom, high-speed force treadmill. At top speed, we found that both the stance-averaged (F(avg)) and peak (F(peak)) vertical forces applied to the treadmill surface during one-legged hopping exceeded those applied during forward running by more than one-half of the body's weight (F(avg) = 2.71 +/- 0.15 vs. 2.08 +/- 0.07 W(b); F(peak) = 4.20 +/- 0.24 vs. 3.62 +/- 0.24 W(b); means +/- SE) and that hopping periods of force application were significantly longer (T(c) = 0.160 +/- 0.006 vs. 0.108 +/- 0.004 s). Next, we found that the periods of ground force application at top backward and forward running speeds were nearly identical, agreeing to within an average of 0.006 s (T(c) = 0.116 +/- 0.004 vs. 0.110 +/- 0.005 s). We conclude that the stance phase limit to running speed is imposed not by the maximum forces that the limbs can apply to the ground but rather by the minimum time needed to apply the large, mass-specific forces necessary.

The recent competitive successes of a bilateral, transtibial amputee sprint runner who races with modern running prostheses has triggered an international controversy regarding the relative function provided by his artificial limbs. Here, we conducted three tests of functional similarity between this amputee sprinter and competitive male runners with intact limbs: the metabolic cost of running, sprinting endurance, and running mechanics. Metabolic and mechanical data, respectively, were acquired via indirect calorimetry and ground reaction force measurements during constant-speed, level treadmill running. First, we found that the mean gross metabolic cost of transport of our amputee sprint subject (174.9 ml O(2)*kg(-1)*km(-1); speeds: 2.5-4.1 m/s) was only 3.8% lower than mean values for intact-limb elite distance runners and 6.7% lower than for subelite distance runners but 17% lower than for intact-limb 400-m specialists [210.6 (SD 13.2) ml O(2)*kg(-1)*km(-1)]. Second, the speeds that our amputee sprinter maintained for six all-out, constant-speed trials to failure (speeds: 6.6-10.8 m/s; durations: 2-90 s) were within 2.2 (SD 0.6)% of those predicted for intact-limb sprinters. Third, at sprinting speeds of 8.0, 9.0, and 10.0 m/s, our amputee subject had longer foot-ground contact times [+14.7 (SD 4.2)%], shorter aerial [-26.4 (SD 9.9)%] and swing times [-15.2 (SD 6.9)%], and lower stance-averaged vertical forces [-19.3 (SD 3.1)%] than intact-limb sprinters [top speeds = 10.8 vs. 10.8 (SD 0.6) m/s]. We conclude that running on modern, lower-limb sprinting prostheses appears to be physiologically similar but mechanically different from running with intact limbs.

Partitioning locomotor metabolic rates into resting and locomotor components is a common practice that has both basic and applied value. Here, we evaluated the quantitative influence of the specific baseline value subtracted (quiet standing vs. resting metabolic rates) from the gross metabolic rates measured during walking. We quantified resting, standing and gross metabolic rates during horizontal treadmill walking at six speeds from 0.2 through 1.9 m*s(-1) in 6 healthy, adult subjects. We found that standing metabolic rates were significantly greater than resting values (1.25 +/- 0.03 vs. 1.08 +/- 0.02 W*kg(-1)) and that both constituted large fractions of the gross metabolic rate while walking at all speeds examined (range 16-58%). Differences in the respective net metabolic rates obtained by subtracting standing vs. resting values differed most at the slowest speed measured (16.0% at 0.2 m*s(-1)) and least at the fastest one (2.9% at 1.9 m*s(-1)). Standing metabolic rates, like walking metabolic rates, include the metabolic cost of muscular activation for balance and maintaining an upright posture. Therefore, the net metabolic rates determined by subtracting standing from gross rates underestimate the total muscular costs that walking requires. We suggest that the net walking metabolic rates obtained by subtracting resting metabolic rate values are more representative of the total metabolic energy that walking requires.

For both different individuals and modes of locomotion, the external forces determining all-out sprinting performances fall predictably with effort duration from the burst maximums attained for 3 s to those that can be supported aerobically as trial durations extend to roughly 300 s. The common time course of this relationship suggests a metabolic basis for the decrements in the force applied to the environment. However, the mechanical and neuromuscular responses to impaired force production (i.e., muscle fatigue) are generally considered in relation to fractions of the maximum force available, or the maximum voluntary contraction (MVC). We hypothesized that these duration-dependent decrements in external force application result from a reliance on anaerobic metabolism for force production rather than the absolute force produced. We tested this idea by examining neuromuscular activity during two modes of sprint cycling with similar external force requirements but differing aerobic and anaerobic contributions to force production: one- and two-legged cycling. In agreement with previous studies, we found greater peak per leg aerobic metabolic rates [59% (+/-6 SD)] and pedal forces at VO2 peak [30% (+/-9)] during one- vs. two-legged cycling. We also determined downstroke pedal forces and neuromuscular activity by surface electromyography during 15 to 19 all-out constant load sprints lasting from 12 to 400 s for both modes of cycling. In support of our hypothesis, we found that the greater reliance on anaerobic metabolism for force production induced compensatory muscle recruitment at lower pedal forces during two- vs. one-legged sprint cycling. We conclude that impaired muscle force production and compensatory neuromuscular activity during sprinting are triggered by a reliance on anaerobic metabolism for force production.

We hypothesized that the maximum mechanical power outputs that can be maintained during all-out sprint cycling efforts lasting from a few seconds to several minutes can be accurately estimated from a single exponential time constant (k(cycle)) and two measurements on individual cyclists: the peak 3-s power output (P(mech max)) and the maximum mechanical power output that can be supported aerobically (P(aer)). Tests were conducted on seven subjects, four males and three females, on a stationary cycle ergometer at a pedal frequency of 100 rpm. Peak mechanical power output (P(mech max)) was the highest mean power output attained during a 3-s burst; the maximum power output supported aerobically (P(aer)) was determined from rates of oxygen uptake measured during a progressive, discontinuous cycling test to failure. Individual power output-duration relationships were determined from 13 to 16 all-out constant load sprints lasting from 5 to 350 s. In accordance with the above hypothesis, the power outputs measured during all-out sprinting efforts were estimated to within an average of 34 W or 6.6% from P(mech max), P(aer), and a single exponential constant (k(cycle) = 0.026 s(-1)) across a sixfold range of power outputs and a 70-fold range of sprint trial durations (R2 = 0.96 vs. identity, n = 105; range: 180 to 1,136 W). Duration-dependent decrements in sprint cycling power outputs were two times greater than those previously identified for sprint running speed (k(run) = 0.013 s(-1)). When related to the respective times of pedal and ground force application rather than total sprint time, decrements in sprint cycling and running performance followed the same time course (k = 0.054 s(-1)). We conclude that the duration-dependent decrements in sprinting performance are set by the fractional duration of the relevant muscular contractions.

The body sizes of highly adapted human and other mammalian runners vary in accordance with specific performance needs. Sprint specialists are relatively massive and muscular while endurance specialists are conspicuously limited both in body and in muscle mass. We hypothesized that the greater body masses of faster specialists are directly related to the greater ground support forces required to attain faster running speeds. Using human runners as a test case, we obtained mean values for body mass, stature and racing speed for the world's fastest 45 male and female specialists, respectively, over the past 14 years (1990-2003) at each of eight standard track racing distances from 100 to 10,000 m. Mass-specific ground support force requirements were estimated from racing speeds using generalized support force-speed relationships derived from 18 athletic subjects. We find a single relationship between mass, stature and event-specific ground support force requirements that spans the entire continuum of specializations and applies both to male and to female runners [body mass (kg) = mass-specific support force x stature2 (m) x a constant; N = 16 group means, R2 = 0.97; where the ideal mass constant, D = 10 kg m(-2)]. We conclude that running performance has a common structural basis.

We hypothesized that the anaerobic power and aerobic power outputs during all-out runs of any common duration between 10 and 150 s would be proportional to the maximum anaerobic (E(an-max)) and aerobic powers (E(aer-max)) available to the individual runner. Seventeen runners who differed in E(an-max) and E(aer-max) (5 sprinters, 5 middle-distance runners, and 7 long distance runners) were tested during treadmill running on a 4.6 degrees incline. E(an-max) was estimated from the fastest treadmill speed subjects could attain for eight steps. E(aer-max) was determined from a progressive, discontinuous, treadmill test to failure. Oxygen deficits and rates of uptake were measured to assess the respective anaerobic and aerobic power outputs during 11-16 all-out treadmill runs that elicited failure between 10 and 220 s. We found that, during all-out runs of any common duration, the relative anaerobic and aerobic powers utilized were largely the same for sprint, middle-distance, and long-distance subjects. The similar fractional utilization of the E(an-max) and E(aer-max) available during high-speed running 1) provides empirical values that modify and advance classic theory, 2) allows rates of anaerobic and aerobic energy release to be quantified from individual maxima and run durations, and 3) explains why the high-speed running performances of different event specialists can be accurately predicted (R(2) = 0.97; n = 254) from two direct measurements and the same exponential time constant.

Routine walking and running, by increasing daily total energy expenditure (TEE), can play a significant role in reducing the likelihood of obesity. The objective of this field study was to compare TEE estimated using foot-ground contact time (Tc)-pedometry (TEE(PEDO)) with that measured by the criterion doubly labeled water (DLW) method. Eight male U.S. Marine test volunteers [27 +/- 4 years of age (mean +/- SD); weight = 83.2 +/- 10.7 kg; height = 182.2 +/- 4.5 cm; body fat = 17.0 +/- 2.9%] engaged in a field training exercise were studied over 2 days. TEE(PEDO) was defined as (calculated resting energy expenditure + estimated thermic effect of food + metabolic cost of physical activity), where physical activity was estimated by Tc-pedometry. Tc-pedometry was used to differentiate inactivity, activity other than exercise (i.e., non-exercise activity thermogenesis, or NEAT), and the metabolic cost of locomotion (M(LOCO)), where M(LOCO) was derived from total weight (body weight + load weight) and accelerometric measurements of Tc. TEE(PEDO) data were compared with TEEs measured by the DLW (2H2(18)O) method (TEE(DLW)): TEE(DLW) = 15.27 +/- 1.65 MJ/day and TEE(PEDO) = 15.29 +/- 0.83 MJ/day. Mean bias (i.e., TEE(PEDO) - TEE(DLW)) was 0.02 MJ, and mean error (SD of individual differences between TEE(PEDO) and TEE(DLW)) was 1.83 MJ. The Tc-pedometry method provided a valid estimate of the average TEE of a small group of physically active subjects where walking was the dominant activity.

We hypothesized that all-out running speeds for efforts lasting from a few seconds to several minutes could be accurately predicted from two measurements: the maximum respective speeds supported by the anaerobic and aerobic powers of the runner. To evaluate our hypothesis, we recruited seven competitive runners of different event specialties and tested them during treadmill and overground running on level surfaces. The maximum speed supported by anaerobic power was determined from the fastest speed that subjects could attain for a burst of eight steps (approximately 3 s or less). The maximum speed supported by aerobic power, or the velocity at maximal oxygen uptake, was determined from a progressive, discontinuous treadmill test to failure. All-out running speeds for trials of 3-240 s were measured during 10-13 constant-speed treadmill runs to failure and 4 track runs at specified distances. Measured values of the maximum speeds supported by anaerobic and aerobic power, in conjunction with an exponential constant, allowed us to predict the speeds of all-out treadmill trials to within an average of 2.5% (R2 = 0.94; n = 84) and track trials to within 3.4% (R2 = 0.86; n = 28). An algorithm using this exponent and only two of the all-out treadmill runs to predict the remaining treadmill trials was nearly as accurate (average = 3.7%; R2 = 0.93; n = 77). We conclude that our technique 1) provides accurate predictions of high-speed running performance in trained runners and 2) offers a performance assessment alternative to existing tests of anaerobic power and capacity.

Mammals use the elastic components in their legs (principally tendons, ligaments, and muscles) to run economically, while maintaining consistent support mechanics across various surfaces. To examine how leg stiffness and metabolic cost are affected by changes in substrate stiffness, we built experimental platforms with adjustable stiffness to fit on a force-plate-fitted treadmill. Eight male subjects [mean body mass: 74.4 +/- 7.1 (SD) kg; leg length: 0.96 +/- 0.05 m] ran at 3.7 m/s over five different surface stiffnesses (75.4, 97.5, 216.8, 454.2, and 945.7 kN/m). Metabolic, ground-reaction force, and kinematic data were collected. The 12.5-fold decrease in surface stiffness resulted in a 12% decrease in the runner's metabolic rate and a 29% increase in their leg stiffness. The runner's support mechanics remained essentially unchanged. These results indicate that surface stiffness affects running economy without affecting running support mechanics. We postulate that an increased energy rebound from the compliant surfaces studied contributes to the enhanced running economy.

Seeking to develop a simple ambulatory test of maximal aerobic power (VO(2 max)), we hypothesized that the ratio of inverse foot-ground contact time (1/t(c)) to heart rate (HR) during steady-speed running would accurately predict VO(2 max). Given the direct relationship between 1/t(c) and mass-specific O(2) uptake during running, the ratio 1/t(c). HR should reflect mass-specific O(2) pulse and, in turn, aerobic power. We divided 36 volunteers into matched experimental and validation groups. VO(2 max) was determined by a treadmill test to volitional fatigue. Ambulatory monitors on the shoe and chest recorded foot-ground contact time (t(c)) and steady-state HR, respectively, at a series of submaximal running speeds. In the experimental group, aerobic fitness index (1/t(c). HR) was nearly constant across running speed and correlated with VO(2 max) (r = 0.90). The regression equation derived from data from the experimental group predicted VO(2 max) from the 1/t(c). HR values in the validation group within 8.3% and 4.7 ml O(2) x kg(-1) x min(-1) (r = 0.84) of measured values. We conclude that simultaneous measurements of foot-ground constant times and heart rates during level running at a freely chosen constant speed can provide accurate estimates of maximal aerobic power.

We compared backward with forward running to test the idea that the application of ground force to support the weight of the body determines the energetic cost of running. We hypothesized that higher metabolic rates during backward versus forward running would be directly related to greater rates of ground force application and the volume of muscle activated to apply support forces to the ground. Four trained males ran backward and forward under steady-state conditions at eight treadmill speeds from 1.75 to 3.50 m x s(-1). Rates of oxygen uptake were measured to determine metabolic rates, and inverse periods of foot-ground contact (1/tc) were measured to estimate rates of ground force application. As expected, at all eight speeds, both metabolic rates and estimated rates of ground force application were greater for backward than for forward running. At the five slowest speeds, the differences in rates of ground force application were directly proportional to the differences in metabolic rates between modes (paired t-test, P<0.05), but at the three highest speeds, small but significant differences in proportionality were present in this relationship. At one of these three higher speeds (3.0 m x s(-1)), additional measurements to estimate muscle volumes were made using a non-invasive force plate/video technique. These measurements indicated that the volume of muscle active per unit of force applied to the ground was 10+/-3% greater when running backward than forward at this speed. The product of rates of ground force application and estimated muscle volumes predicted a difference in metabolic rate that was indistinguishable from the difference we measured (34+/-6% versus 35+/-6%; means +/- s.e.m., N=4). We conclude that metabolic rates during running are determined by rates of ground force application and the volume of muscle activated to apply support forces to the ground.

We twice tested the hypothesis that top running speeds are determined by the amount of force applied to the ground rather than how rapidly limbs are repositioned in the air. First, we compared the mechanics of 33 subjects of different sprinting abilities running at their top speeds on a level treadmill. Second, we compared the mechanics of declined (-6 degrees ) and inclined (+9 degrees ) top-speed treadmill running in five subjects. For both tests, we used a treadmill-mounted force plate to measure the time between stance periods of the same foot (swing time, t(sw)) and the force applied to the running surface at top speed. To obtain the force relevant for speed, the force applied normal to the ground was divided by the weight of the body (W(b)) and averaged over the period of foot-ground contact (F(avge)/W(b)). The top speeds of the 33 subjects who completed the level treadmill protocol spanned a 1.8-fold range from 6.2 to 11.1 m/s. Among these subjects, the regression of F(avge)/W(b) on top speed indicated that this force was 1.26 times greater for a runner with a top speed of 11.1 vs. 6.2 m/s. In contrast, the time taken to swing the limb into position for the next step (t(sw)) did not vary (P = 0.18). Declined and inclined top speeds differed by 1.4-fold (9.96+/-0.3 vs. 7.10+/-0.3 m/s, respectively), with the faster declined top speeds being achieved with mass-specific support forces that were 1.3 times greater (2.30+/- 0.06 vs. 1.76+/-0.04 F(avge)/ W(b)) and minimum t(sw) that were similar (+8%). We conclude that human runners reach faster top speeds not by repositioning their limbs more rapidly in the air, but by applying greater support forces to the ground.

We tested the importance of aerobic metabolism to human running speed directly by altering inspired oxygen concentrations and comparing the maximal speeds attained at different rates of oxygen uptake. Under both normoxic (20.93% O2) and hypoxic (13.00% O2) conditions, four fit adult men completed 15 all-out sprints lasting from 15 to 180 s as well as progressive, discontinuous treadmill tests to determine maximal oxygen uptake and the metabolic cost of steady-state running. Maximal aerobic power was lower by 30% (1.00 +/- 0.15 vs. 0.77 +/- 0.12 ml O2. kg-1. s-1) and sprinting rates of oxygen uptake by 12-25% under hypoxic vs. normoxic conditions while the metabolic cost of submaximal running was the same. Despite reductions in the aerobic energy available for sprinting under hypoxic conditions, our subjects were able to run just as fast for sprints of up to 60 s and nearly as fast for sprints of up to 120 s. This was possible because rates of anaerobic energy release, estimated from oxygen deficits, increased by as much as 18%, and thus compensated for the reductions in aerobic power. We conclude that maximal metabolic power outputs during sprinting are not limited by rates of anaerobic metabolism and that human speed is largely independent of aerobic power during all-out runs of 60 s or less.

We tested whether the rate at which force is applied to the ground sets metabolic rates during classical-style roller skiing in four ways: 1) by increasing speed (from 2.5 to 4.5 m/s) during skiing with arms only, 2) by increasing speed (from 2.5 to 4.5 m/s) during skiing with legs only, 3) by changing stride rate (from 25 to 75 strides/min) at each of three speeds (3.0, 3.5, and 4.0 m/s) during skiing with legs only, and 4) by skiing with arms and legs together at three speeds (2.0-3.2 m/s, 1.5 degrees incline). We determined net metabolic rates from rates of O2 consumption (gross O2 consumption - standing O2 consumption) and rates of force application from the inverse period of pole-ground contact [1/tp(arms)] for the arms and the inverse period of propulsion [1/tp(legs)] for the legs. During arm-and-leg skiing at different speeds, metabolic rates changed in direct proportion to rates of force application, while the net ground force to counteract friction and gravity (F) was constant. Consequently, metabolic rates were described by a simple equation (metab = F . 1/tp . C, where metab is metabolic rates) with cost coefficients (C) of 8.2 and 0.16 J/N for arms and legs, respectively. Metabolic rates predicted from net ground forces and rates of force application during combined arm-and-leg skiing agreed with measured metabolic rates within +/-3. 5%. We conclude that rates of ground force application to support the weight of the body and overcome friction set the energetic cost of skiing and that the rate at which muscles expend metabolic energy during weight-bearing locomotion depends on the time course of their activation.

Similarly sized bipeds and quadrupeds use nearly the same amount of metabolic energy to run, despite dramatic differences in morphology and running mechanics. It has been shown that the rate of metabolic energy use in quadrupedal runners and bipedal hoppers can be predicted from just body weight and the time available to generate force as indicated by the duration of foot-ground contact. We tested whether this link between running mechanics and energetics also applies to running bipeds. We measured rates of energy consumption and times of foot contact for humans (mean body mass 78.88 kg) and five species of birds (mean body mass range 0.13-40.1 kg). We find that most (70-90%) of the increase in metabolic rate with speed in running bipeds can be explained by changes in the time available to generate force. The rate of force generation also explains differences in metabolic rate over the size range of birds measured. However, for a given rate of force generation, birds use on average 1.7 times more metabolic energy than quadrupeds. The rate of energy consumption for a given rate of force generation for humans is intermediate between that of birds and quadrupeds. These results support the idea that the cost of muscular force production determines the energy cost of running and suggest that bipedal runners use more energy for a given rate of force production because they require a greater volume of muscle to support their body weight.

During running, muscles and tendons must absorb and release mechanical work to maintain the cyclic movements of the body and limbs, while also providing enough force to support the weight of the body. Direct measurements of force and fiber length in the lateral gastrocnemius muscle of running turkeys revealed that the stretch and recoil of tendon and muscle springs supply mechanical work while active muscle fibers produce high forces. During level running, the active muscle shortens little and performs little work but provides the force necessary to support body weight economically. Running economy is improved by muscles that act as active struts rather than working machines.

The purpose of this study was to determine the value of the peak oxygen deficit (POD) as a predictor of sprint and middle-distance track performance. POD, peak blood lactate, VO2peak, lactate threshold, and running economy at 3.6 m.s-1 were measured during horizontal treadmill running in 22 male and 19 female competitive runners of different event specialties. Subjects also completed running performance trials at 100, 200, 400, 800, 1500, and 5000 m. Correlations of track performances with POD (ml.kg-1) (-0.66, -0.71, -0.71, -0.62, -0.52, and -0.40) were moderately strong at the sprint and middle distances, accounting for 44-50% of the performance variance at the three shortest distances. Correlations of track performances with peak blood lactate concentration were lower than with POD and accounted for approximately one-half as much of the performance variance (21-26%) at the three shortest distances. Multiple regression analyses indicated that the POD was the strongest metabolic predictor of 100-, 200- and 400-m performance, and that VO2peak was the strongest metabolic predictor of 800-, 1500-, and 5000-m performance. We conclude that the POD is a moderately strong predictor of sprint and middle-distance track performance.

To investigate the effects of varying levels of hypohydration on ratings of perceived exertion (RPE) during moderate and heavy submaximal exercise, and at the lactate threshold (LT) and ventilatory threshold (VT), 9 male subjects cycled under states of euhydration (EU), moderate hypohydration (MH), and severe hypohydration (SH). The desired level of hypohydration was achieved over a 36-hr period by having subjects cycle at 50% VO2max in a 38 degrees C environment on two occasions while controlling fluid intake and diet. During submaximal exercise, oxygen uptake, ventilation, heart rate, blood lactate, and RPE were not significantly different among treatments. Hypohydration did not significantly alter LT or VT, or perceptual responses at LT or VT. It is concluded that hypohydration of up to 5.6% caused by fluid manipulation and exercise in the heat over a 36-hr period does not alter RPE or the lactate or ventilatory threshold, nor RPE at the lactate and ventilatory thresholds measured during moderate and heavy submaximal cycling in a neutral (22 degrees C) environment.

The objectives of this study were to determine the relationships of estimated active muscle mass and gender to anaerobic capacity, as measured by the peak oxygen deficit, and to compare these relationships with those for peak oxygen uptake (VO2peak). Fat-free leg volumes (FFLV), and one- and two-legged cycling peak oxygen deficit and VO2peak were determined in young, physically active men (N = 11) and women (N = 9). For men and women, mean (+/- SD) peak oxygen deficit for one-legged cycling (2.27 +/- 0.30 and 1.18 +/- 0.18 l) was 52% of that for two-legged cycling (4.40 +/- 0.62 and 2.25 +/- 0.28 l). For all subjects and both modes of exercise, there was a strong linear relation between peak oxygen deficit (1) and estimated active muscle mass (FFLV) (r = 0.94). This relation was the same in one- and two-legged cycling, but was different for men and women. For a given FFLV, the peak oxygen deficit was significantly higher (P < 0.05) in men than women by an average of 0.44 l. The relation of peak oxygen deficit to FFLV was significantly stronger than the relation of VO2peak to FFLV (r = 0.80). We conclude: (a) that the peak oxygen deficit is strongly related to the estimated active muscle mass during cycling; (b) that for a given estimated active muscle mass (FFLV), the peak oxygen deficit is higher in men than women; and (c) that the peak oxygen deficit is more strongly related than VO2peak to the estimated quantity of active muscle.

The effect of varying levels of hypohydration on hemodynamic, cardiorespiratory, and metabolic responses to progressive incremental submaximal cycling was examined in nine male subjects. Subjects cycled in a neutral (22 degrees C) environment under euhydration (EU), moderate hypohydration (MH), and severe hypohydration (SH). To achieve the desired level of hypohydration, subjects cycled at 50% VO2max for 1.5 h in a 38 degrees C environment on two separate occasions, 36 h prior to testing. Mean (+/- SE) percent losses in body weight from baseline during EU, MH, and SH were 0.6 +/- 0.3%, 3.3 +/- 0.1%, and 5.6 +/- 0.4%, respectively. Ventilation, O2 uptake, respiratory exchange ratio, heart rate, plasma free fatty acids, plasma glycerol, blood lactate, and hematocrit were not significantly altered by hypohydration. During EU, hemoglobin concentration was significantly lower than during both MH and SH, but no significant difference was observed for plasma volume loss. Plasma glucose was significantly higher during SH compared with EU and MH. These results suggest that hypohydration of up to 5.6% caused by exercise and fluid manipulation over 36 h does not alter cardiorespiratory or blood lactate responses during progressive incremental submaximal cycling in a neutral environment. However, hepatic metabolism may be altered during hypohydration as indicated by higher plasma glucose levels.

The purposes of this study were to validate the 12-min swim as a field test of VO2 peak in female recreational swimmers and to compare its validity with that of the 12-min run. The results are contrasted with those previously reported on a comparable group of male recreational swimmers. Thirty-four young women completed 12-min swim, 12-min run, tethered swimming VO2 peak, and treadmill running VO2 peak tests within 3 weeks. Mean (+/- SD) 12-min swim and run distances were 597 +/- 82 and 2,313 +/- 317 m, and mean tethered swim and treadmill run VO2 peak values were 39.2 +/- 4.9 and 45.4 +/- 6.3 ml.kg BW-1.min-1, respectively. Correlation coefficients and standard errors of estimate for predictions of swimming VO2 peak from the 12-min swim (.42 and 4.5 ml.kg BW-1.min-1) and run (.58 and 4.1 ml.kg BW-1.min-1) and for predictions of treadmill run VO2 peak from the 12-min swim (.34 and 6.0 ml.kg BW-1.min-1) and run (.87 and 3.2 ml.kg BW-1.min-1) indicated that the 12-min run was a more accurate predictor of tethered swim or treadmill run VO2 peak than the 12-min swim. These data are in close agreement with our previous study on young male recreational swimmers. We conclude that the 12-min swim has relatively low validity as a field test of peak aerobic power and that it is not an equally valid alternative to the 12-min run in young adult female recreational swimmers.(ABSTRACT TRUNCATED AT 250 WORDS)

The purposes of this study were to validate the 12-min swim as a field test of VO2max and to compare its validity with that of the 12-min run. Thirty-six young men completed 12-min swim, 12-min run, tethered swimming (TS) VO2peak, and treadmill running (TR) VO2peak tests within 3 wk. Mean (+/- SD) 12-min swim and run distances were 581 +/- 88 and 2797 +/- 290 m, and mean TS and TR VO2peak values were 50.3 +/- 6.2 and 57.2 +/- 5.5 ml.kg BW-1.min-1, respectively. Correlation coefficients and standard errors of estimate for predictions of TS VO2peak from the 12-min swim (0.40 and 5.7 ml.kg BW-1.min-1) and run (0.74 and 4.2 ml.kg BW-1.min-1) and for predictions of TR VO2peak from the 12-min swim (0.38 and 5.1 ml.kg BW-1.min-1) and run (0.88 and 2.6 ml.kg BW-1.min-1) indicated that the 12-min run was a more accurate predictor of TS or TR VO2peak than the 12-min swim. We conclude that the 12-min swim has relatively low validity as a field test of peak aerobic power and that it should not be considered an equally valid alternative to the 12-min run in young male recreational swimmers. However, the accuracy of predicting VO2peak from the 12-min swim is as good as some other commonly used methods, and, therefore, it may be adequate for fitness classification in situations in which a high level of accuracy is not needed.

The 1-mile run/walk test is the field test of choice for evaluating maximal aerobic power (VO2max) in school-aged children. The objective of this study was to determine the relative importance of selected metabolic determinants of mile run/walk performance in children 6-14 yr of age. Mile run/walk time (MRWT), VO2max, running economy (VO2 in ml.kg-1.min-1 at 8.05 km.h-1; VO2econ), and the percentage of VO2max utilized at the average mile run/walk speed (%VO2max) were measured in 59 children (33 boys and 26 girls); 27 6-8 yr olds (group 1), 17 9-11 yr olds (group 2), and 15 12-14 yr olds (group 3). Partial correlations between MRWT and VO2max, VO2econ, and %VO2max, holding constant the effects of age and sex, were as follows: group 1: -0.26, 0.03, and -0.82; group 2; -0.43, 0.09, and -0.88; and group 3, -0.60, 0.45, and -0.80. Multiple regression analysis indicated that the combination of the three metabolic measures accounted for 90%, 97%, and 90% of the variance in MRWT in the three age groups, respectively. Standardized regression coefficients for VO2max, VO2econ, and %VO2max in group 1 (-0.66, 0.19, and -0.83), group 2 (-0.45, 0.33, and -0.92), and group 3 (-0.76, 0.27, and -0.50) indicated that the %VO2max utilized at the average mile run/walk speed was the most important determinant of MRWT variance in children 6-11 yr old, whereas VO2max was the most important determinant for children 12-14 yr old. We conclude that the relative importance of the metabolic determinants of the 1-mile run/walk test, as typically administered in the schools, changes with age.