Aerobic capacity/sustainable aerobic metabolism, anaerobic capacity, and running economy are the primary physiological factors influencing endurance running performance. Although a complete understanding of factors that influence running economy is still lacking, an important contributor may be muscle fiber type. Oxidative type I myofibers are more metabolically efficient than type II myofibers during isometric contractions (16,32), cycling (9), and walking (16). However, type I myofibers have been shown to be related to running economy at slow speeds (6) but type II myofibers at faster speeds (23).
During running, potentiation of force and power occurs during the push-off phase because of elastic energy obtained during the stretch-shortening cycle (SSC). It is estimated that 35% to more than 50% of the energy absorbed during the negative phase of an SSC is used during the concentric contraction (1). Accordingly, it seems reasonable to hypothesize that the elastic energy gained from stretch-shortening cycle potentiation (SSCP) may reduce the energy required to run.
Increased preload seems to enhance SSCP (4,8). This prestretch allows the muscle to stiffen before the start of the concentric contraction. Thus, force potentiation during the concentric contractions is dependent on what happens during the prior eccentric contraction (5,7,8). Additionally, late-phase high force/power eccentric contractions (26) and length of time of the amortization phase (5) both may contribute to the development of SSCP.
It seems likely that a stronger muscle should be able to generate more force eccentrically and shorten the amortization time and thus increase running economy. Consistent with this hypothesis, several studies have shown that resistance training not only increases muscle strength but also increases locomotion economy (13,17,27). It also seems reasonable to assume that fast-twitch muscle fibers might be better able to develop high forces late in the SSC better than slow-twitch muscle fibers.
Several studies have shown that greater tendon compliance increases stretch and energy savings during the eccentric phase (10,22,28). Ultimately, this enables more force to be exerted during the concentric phase of an SSC, thereby lowering energy cost during the concentric phase. Based on differences in power output, it has been suggested that 50% of the difference between muscle efficiency (∼25%) and running efficiency at 4 m·s−1 (∼50%) is accounted for by obtaining SSCP from the Achilles tendon/foot complex (3). Indeed, the medial gastrocnemius contracts almost isometrically during the push-off phase of walking and vertical jumping (10,11,20,21). Along with the potentiation of force, the isometric contractions require about one-third as much energy as concentric contractions (30). This translates into longer Achilles tendons, which potentially have more potential for stretch, being related to increased walking (15,25) and running economy (14).
To our knowledge, no investigation has attempted to determine how muscle fiber type, late eccentric force development, SSCP, strength, tendon length, and running economy are interrelated. The purpose of this study was to develop a model for increasing our understanding of how these factors are related and thus may affect running economy. We hypothesized that leg strength and fiber type would be independently related to late eccentric force during a ballistic leg press, that eccentric force would be related to SSCP force, and SSCP velocity would be related to SSCP force and Achilles tendon length. Finally, we hypothesized that SSCP velocity would be related to running economy.
Experimental Approach to the Problem
Many factors are known to influence running economy, and as such, multiple in vivo approaches were used. Subjects were required to visit laboratories 3 times over a 10- to 14-day period (at least 2 days separated each laboratory visit): visit 1—after subject screening, body composition was first evaluated, followed by measurement of resting energy expenditure and running performance by indirect calorimetry to evaluate net oxygen uptake (i.e., economy) at 6 and 7 mph, then followed by a
test; visit 2—magnetic resonance imaging was used to measure Achilles tendon length and cross-sectional area, followed by strength and ballistic jumping used to understand late eccentric force and potentiation; visit 3—muscle biopsies were obtained, enabling the determination of muscle fiber type distribution. Collectively, these various strategies provided comprehensive insight into the factors affecting running economy, as all measures were used to develop a working model.
Twenty trained male recreational distance runners, aged 24–40 years, having completed at least one 10-km run or marathon within the last 6 months served as subjects (Table 1). None reported health problems on a health history questionnaire or were taking any medications that would affect body composition, energy expenditure, or endurance performance. Subjects were tested on 4 separate visits: (a) screening and body composition assessment, (b) magnetic resonance imaging and ballistic muscle function tests, (c) percutaneous needle muscle biopsy, and (d) walking/running economy and maximum oxygen uptake tests. The study was approved by the Institutional Review Board at the University of Alabama at Birmingham, and written informed consent was obtained from all subjects.
Following company instructions, dual-energy x-ray absorptiometry (GE Lunar Prodigy, Madison, WI, USA) was used to evaluate percent body fat. Subjects were instructed to remain still in a supine position during the analysis that took approximately 5 minutes. Adult software (version 1.33) was used to analyze the scans.
Seated resting and running oxygen uptake were measured using a MAX-II Cart metabolic system (Physio-Dyne Instrument Company, Quogue, NY, USA). Before each test, calibration was conducted with a 3-L calibration syringe and known standard gases. To assess resting oxygen uptake (
), subjects were required to remain seated for 10 minutes before data collection. Immediately, after this preliminary period, a further 10 minutes was used for data collection. Five minutes after the seated resting evaluation, subjects stretched as needed and then warmed up at self-selected speeds on the treadmill for 4–5 minutes. Immediately after the warm-up, subjects ran for 4–5 minutes at 6 mph (9.68 km·h−1). When steady state (no increase in heart rate or
over previous minute) was achieved at 6 mph (4–5 minutes in all cases), speed was increased to 7 mph (11.29 km·h−1). Subjects ran at 7 mph until steady state was reached (4–5 minutes). The subjects then rested 5–10 minutes before beginning the maximum oxygen uptake (
) test. Seated resting
was subtracted from running
to calculate net
for running at 6 and 7 mph. Using a protocol previously designed for trained runners (24,29), subjects ran for 1 minute at increasing intensities starting at 6 mph. Each minute the subject was offered the choice of increasing speed (0.5 mph) or grade (2.5%). Subjects ran until voluntary exhaustion was reached. To determine
, at least 2 of the following were criteria were met: (a) plateauing of
, (b) respiratory exchange ratio (RER) >1.2, or (c) heart rate within ±10 beats of age-predicted maximum.
Tendon Length/Cross-section Volume
Measurements of tendon length and area were determined using a 3-dimensional volumetric T1-weighted Turbo Field Echo imaging sequence (T1TFE) and T1-weighted Turbo Spin Echo imaging sequences (TSE) using a 1H transmit/receive torso phased-array coil on a 3-T Philips Achieva system. Overall, a series of scout images were collected followed by a set of separate coronal, sagittal, and axial scans from below the patient's foot to above the maximum cross-sectional area of the subject's thigh (i.e., slightly below the groin). The complete set of images was broken into 4 segments or regions corresponding to the various anatomical locations from the subject's foot up to their groin.
Region 1 was defined as slightly below the subject's foot to approximately midcalf. A set of 32 coronal images (T1TFE, flip angle = 8°, 32 contiguous slices, slice thickness = 2 mm, TR = 8.068 milliseconds, TE = 4.60 milliseconds, ETL = 160, acquisition matrix = 160 × 160, reconstructed matrix = 256 × 256, FOV = 250 × 250 mm), 32 sagittal images (T1TFE, flip angle = 8°, 32 contiguous slices, slice thickness = 2 mm, TR = 8.068 milliseconds, TE = 4.60 milliseconds, ETL = 160, acquisition matrix = 160 × 160, reconstructed matrix = 256 × 256, FOV = 250 × 250 mm) and 48 axial images (TSE, flip angle = 90°, 48 contiguous slices, slice thickness = 5 mm, TR = 800 milliseconds, TE = 15 milliseconds, ETL = 3, acquisition matrix = 153 × 192, reconstructed matrix = 256 × 256, FOV = 160 × 160 mm) were collected. The coronal and sagittal images were used for tendon length measurements through the subject's ankle and lower calf region. The axial images in this region were used for tendon and muscle cross-sectional area measurements.
Region 2 was defined as an area from midcalf through the patient's knee. A series of 54 axial images (TSE, flip angle = 90°, 54 contiguous slices, slice thickness = 5 mm, TR = 800 milliseconds, TE = 15 milliseconds, ETL = 3, acquisition matrix = 153 × 192, reconstructed matrix = 256 × 256, FOV = 160 × 160 mm) were collected. The axial images in this region were used for muscle cross-sectional area measurements and were combined with the axial images from region 1 to provide a contiguous cross-sectional view of the subject's lower leg (i.e., from below the foot to slightly above the knee).
Region 3 was defined as an area slightly below the subject's knee to approximately midthigh. A set of 32 sagittal images (T1TFE, flip angle = 8°, 32 contiguous slices, slice thickness = 2 mm, TR = 8.068 milliseconds, TE = 4.60 milliseconds, ETL = 160, acquisition matrix = 160 × 160, reconstructed matrix = 256 × 256, FOV = 250 × 250 mm) and 54 axial images (TSE, flip angle = 90°, 54 contiguous slices, slice thickness = 5 mm, TR = 800 milliseconds, TE = 15 milliseconds, ETL = 3, acquisition matrix = 153 × 192, reconstructed matrix = 256 × 256, FOV = 160 × 160 mm) were collected. The sagittal images were used for tendon length measurements through the knee and lower thigh regions. The axial images in this region were used for tendon and muscle cross-sectional area measurements.
All acquisition parameters were selected to optimize the signal-intensity contrast between muscle, fat, and tendon and to reduce the scan time as much as possible. All were analyzed by importing the resulting DICOM images into the ImageJ software package, and regions of interest and length measurements were manually drawn around the tendons and outlines of the muscles of interest. Achilles tendon length was measured from the distal attachment of the medial gastrocnemius on Achilles to the superior border of the calcaneus. Test-retest analysis of Achilles tendon length and thickness on 5 subjects yielded a coefficient of variation of 1.1 and 1.8%, respectively.
Potentiated Jump Height
After 3 to 6 practice jumps, air-borne time in the vertical jump was measured during 3 trials of each countermeasure jump, static jump, and drop jump. In all 3 kinds of jumps, subjects were instructed to jump only vertically and as high as they could with hands positioned on the hips. Air-borne time was measured using a pressure sensitive mat (custom signaling mats; Tapeswitch Corporation, London, Ontario, Canada). An electronic goniometer was worn on the knee so that the lowest knee-flexed position could be determined during the countermeasure jump and then duplicated in the static jump. Before initiation of the static jump, subjects held a flexed knee position for 3 seconds that was equal to the average lowest knee-flexed position obtained in the 3 countermeasure jumps. Subjects dropped from a 20.3-cm bench during the drop jump. Jump potentiation was calculated as the difference between the drop jump and static jump.
Ballistic Leg Press Measures
We have previously described these measures in detail (26). Briefly, all ballistic leg press measures were taken using a muscle performance system comprised a 35° (from horizontal) leg press machine (Nebula #6000-A, Versailles, OH, USA) and a cable extension linear position transducer (LPT) (model # PT5DC-125-V62-UP-MOPO-C25; Celesco Transducer Products, Inc., Chatsworth, CA, USA) interfaced with a National Instruments (Austin, TX, USA) data acquisition system. Data were sampled at 1 kHz and digitally filtered using a low-pass 4-pole Butterworth filter with a cutoff frequency of 50 Hz. The LPT was placed beside the leg press machine with a cable attached to the upper weight bar of the machine and the LPT aligned to the linear motion of the machine. To standardize hip position, the leg press back rest was set at a 38° relative to the floor. Feet were positioned 20 cm apart with the edge of the posterior heel aligned with the bottom edge of the leg press foot plate. For all ballistic throws, the lower limit of movement was set at 90° knee flexion. For SSC throws, the subject started with the knees in the fully extended position, and for concentric only (CO) throws, the subject started with the knees flexed at 90°.
Each subject performed ballistic leg presses with 150% of their body weight. Correcting for the 35° of the leg press, weight plates were added to the machine to bring the total load (weight of the empty leg press sled plus weight plates added) to 150% of each subject's body weight. Velocity and acceleration were calculated with the finite-difference technique (33). The acceleration was combined with the system corrected mass to calculate force output. Subjects performed 3 SSC followed by 3 CO ballistic leg press throws with 1-minute rest periods between throws. Criterion scores used for analysis of force, velocity, acceleration, and power were averages of the 2 trials with the highest peak power for SSC throws and for CO throws. As previously described (26), all ballistic leg press evaluations in our laboratory have high test-retest reliability with coefficients of variation for measures ranging from 1.7 to 4.3% and intraclass correlation coefficients ranging from 0.93 to 0.95.
One Repetition Maximum Leg Press
Leg strength was evaluated using a 35° (from horizontal) leg press machine (Nebula #6000-A) as previously described (26). After a 5-minute warm-up on a cycle ergometer at 30–50 W, subjects did 5 leg press repetitions with a weight equal to their respective body weight and after a 2-minute rest 5 repetitions with a weight equal to 150% of their respective body weight. All succeeding trials consisted of 1 repetition followed by a 2-minute rest. Weight was increased by 40 kg increments at first but gradually decreased to 20 and then 10 kg as difficulty increased. The largest weight lifted was considered to be the 1 repetition maximum (1RM). Test-retest coefficient of variation for 1RM testing in our laboratory is less than 3%.
Myofiber Type Distribution
Muscle biopsy samples were obtained under local anesthesia (1% lidocaine) from the right vastus lateralis by percutaneous needle biopsy using a 5-mm Bergstrom biopsy needle under suction, as previously described (2). Samples were mounted oriented cross-sectionally using a dissecting microscope and quickly frozen in liquid nitrogen–cooled isopentane. All samples were stored at −80° C until analysis. The relative distributions of myofiber types I, IIa, and IIx were determined by myosin heavy chain immunohistochemistry using our well-established protocol (18,19).
Mean values and SDs were calculated for all study variables. Pearson's product correlations were determined for muscle fiber type, Achilles tendon length, SSCP variables of interest, and running economy. Based on previous research findings and Pearson's product correlations, a possible model was developed for explaining running economy. Multiple regression was used to determine independence of specific relationships between variables. Variable inflation factors were less than 2 in all cases. Significance was set at 0.05.
Mean values and SDs of study variables are presented in Table 1. Correlations between variables of interest in attempting to model running economy are presented in Table 2. Net
at 6 mph was positively related to type I myofiber percent and Achilles tendon length but negatively related to type IIa fiber percent and SSCP velocity. Net
at 6 mph was negatively correlated with SSCP velocity and potentiated jump height in the countermeasure jump. Based on previous findings, the following model was tested using the interrelationships observed in this study (Figure 1). Leg press strength (partial r = 0.66, p < 0.01) and type IIx myofiber percent (partial r = 0.52, p = 0.03) were independently related to late eccentric force (0–100 milliseconds before amortization). Late eccentric force was related to SSCP force (r = 0.73, p < 0.01). Stretch-shortening cycle potentiation force (partial r = 0.74, p < 0.01) and Achilles tendon length (partial r = 0.52, p = 0.03) were independently related to running economy (reduced net oxygen uptake). Potentiated vertical jump height (partial r = −0.45, p ≤ 0.05) and SSCP during the ballistic leg press (partial r = −0.63, p < 0.01) were independently related to 6 mph running net
Previous studies have shown that Achilles tendon length (14) and increased strength (by resistance training) (17,27) may have a positive effect on running economy, presumably in part by enhancing the potential for increased SSCP while running. In addition, late eccentric force production during SSC has been shown to be important for developing SSCP in ballistic muscle actions (5,7,8,26). For the first time, this study shows a series of interrelationships that link myofiber type percent and hip/knee extension strength to increased late eccentric force during a ballistic muscle action (ballistic leg press). This in turn is related to increased SSCP and a resultant improvement in running economy. These relationships highlight a multifaceted model of running economy, which includes high leg strength and high percent of type II muscle fibers to increase late eccentric force capabilities. Coupled with longer Achilles tendon, these characteristics result in greater SSCP that ultimately enhance running economy.
It is particularly interesting that fast-twitch myofiber percent is related to increased running economy in this study because it is probable that fast-twitch myofibers are less efficient at pumping Ca++ ions into the sarcoplasmic reticulum than slow-twitch myofibers (12). It has also been shown that fast-twitch myofiber percent is inversely related to exercise economy during isometric contractions (16,31,32), cycling (9), walking (16), and running at slow speeds (6). On the other hand, Kyrolainen et al. (23) found that type II myofiber percent was related to increased running economy at relatively fast running speeds. Fast-twitch muscle myofiber percentage was also related to late eccentric force development during the ballistic leg press. It is possible that individuals with a higher percentage of fast-twitch muscle fibers may have been able to delay the application of force during the eccentric phase of the SSC and allow development of greater late eccentric force before the concentric phase of the SSC. One possible explanation for the apparent conundrum of fast-twitch muscle fibers relating positively to running economy is that in activities such as rapid running in which there is a strong potential for SSCP, the rapid contraction capabilities of the fast-twitch myofibers increase late eccentric force, SSCP, and economy, which in turn compensates for the reduced biochemical efficiency of fast-twitch myofibers.
Our findings that hip and knee extension strength (leg press 1RM) were associated with eccentric force are not surprising, given that stronger muscles generate greater eccentric force production. Then, again, this is the first study to link eccentric force capacity to SSCP and running economy. Consistent with this observation, resistance training programs have increased economy in cross-country skiers (13) and runners (17,27). Taken together, it seems apparent that resistance training directed at improving hip and knee extensor strength is important for improving running economy. These results also suggest that leg strength and fiber type operate independently to affect late eccentric force, with strength affecting the magnitude of the eccentric contraction and fast-twitch myofibers affecting the ability to delay the application of large amounts of force until late in the eccentric phase of the SSC.
The strong significant correlation between late eccentric force development during the ballistic leg press and SSCP force (explaining over 50% of the variance in SSCP force) supports the premise that the eccentric phase of the SSC is very important for increasing potentiation of force. High forces late in the eccentric phase of an SSC are thought to increase stretch of the elastic components of the muscle/tendon complex. Our results are consistent with previous results reported by Bosco et al. (5) in which force generated during potentiated countermeasure jumps was associated with elevated late eccentric force during an SSC.
Achilles tendon length and SSCP force were independently related to SSCP velocity, suggesting that both high forces are required to stretch the elastic component of the muscle/tendon complex and that longer Achilles tendon increases the potential for stretch of the complex and potentiation of velocity. This observation is consistent with the relationship between walking (25) and running (14) economy previously reported, which further improves our understanding of how tendon length may affect locomotion economy.
It is interesting that ballistic leg press SSCP velocity and potentiated vertical jump height independently relate to running economy. This suggests that each is measuring a unique aspect of running economy. Potentially greater SSCP may occur in the hip musculature/tendons with the ballistic leg press and greater SSCP in the triceps surae/Achilles tendon with the vertical jump, which might account for independent relationships to running economy. Compared with the leg press, the vertical jump may induce substantially more stretch of, and load to, the Achilles tendon (greater ankle dorsiflexion) and thus more SSCP from stretch of the Achilles tendon. Also, in the leg press with the feet more anterior in relation to the trunk, relatively more force comes from the hips (gluteus maximus) (and substantially greater hip flexion) and less force from the knee extensors as compared with the feet in line with the trunk as in the vertical jump (less hip flexion with jump).
These results are all based on relationships found between the variables of interest in this study, and it should be emphasized that relationships do not necessarily indicate cause and effect. However, we believe that the interrelations found in this study are intriguing and suggestive of the proposed model. In conclusion, these results support the hypothesis that fast-twitch myofiber percent and hip and leg strength allow high late eccentric force during SSC. This late eccentric force during SSC contributes to increased SSCP force, and SSCP force along with longer Achilles tendons contributes to SSCP velocity. Finally, SSCP velocity contributes to increased running economy.
This study develops a potential model for helping to understand running economy. Confusion still exists concerning what role muscle fiber type may have in influencing locomotion economy, showing type I myofiber percent related to increased cycling and walking economy but type II myofiber percent related to increased running economy. This study suggests that improved running economy with type II myofiber percent may be caused by increased stretch-shortening potentiation because of increased ability to develop late eccentric force production. One practical message that can be obtained from this study is that resistance training, especially resistance training that includes eccentric contractions, may be beneficial for improving running economy. As late eccentric force development seems to be important in SSCP and thus running economy, exercise training strategies aimed at improving late eccentric force development may be beneficial for runners.
We thank David Bryan, Paul Zuckerman, William Ogard, and Jan A. Den Hollander for help in data acquisition. The study was supported by the UAB Department of Human Studies. No external funding was used, and there is no conflict of interest for any of the authors.
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