Introduction
Successful running performance in long duration events is directly influenced by maximal oxygen uptake (o2max), fractional use of o2max (End), and the energy cost of running (Cr) (10). Although we have been aware of its importance since the 1970s, the state of knowledge about Cr is low compared to our understanding of o2max or End (10,13). Cr is the O2 equivalent of the energy required to run through a given distance at a submaximal speed (32). It is particularly relevant to predict performance in individuals with similar o2max (9) and has been acknowledged as one of the multiple determinants of East African runners' domination in international competitions (21). Cr depends on a complex interplay of factors including training, environment, physiology, biomechanics, anthropometry, and training (32). Recent research suggests that strength training is one of the most powerful interventions for improving Cr (17,28,34,36,37) However, because muscular hypertrophy has been shown to interfere with some peripheral aerobic adaptations, (5,23) it has been suggested that implementations should use strength training methods that emphasize on neural adaptations (11).
Plyometric and dynamic weight training (PT and DWT) fulfill this requirement (14,20,40). Plyometric training involves an eccentric contraction immediately followed by a concentric contraction to allow the muscle to store and recoil elastic energy (6,24,38). Jumps and rebounds are typically used to induce this muscle strech shortening cycle. Dynamic weight training involves concentric contractions leading to the maximal power output (40). It generally consists in moving relatively light loads (between 30 and 50% of 1 repetition maximum) as fast as possible (40).
The effectiveness of plyometric and DWT (either alone or in combination) to decrease Cr has been highlighted in several convergent reports (28,35,37). In a recent study (35), 8 moderately trained endurance runners improved Cr after they completed a 6-week program of high volume-low intensity plyometric training in concomitance with their usual endurance training. In another study (37) in which the authors implemented a comparable plyometric training program, they also found a moderate decrease in Cr. Other authors (28) replaced 32% of the usual endurance training volume of 12 elite crosscountry runners by an explosive strength training program involving both plyometric and DWT. They reported a large decrease in Cr, thus confirming the effectiveness of these methods to improve running efficiency. However, to the best of our knowledge, no attempt has been made to determine whether 1 of these 2 methods was more appropriate in improving Cr. Physiological and practical applications of this issue are important. They could provide evidence-based data to the coach that may help in the optimization of the strength training of endurance athletes and experimental data to the scientist that may contribute to our understanding of the mechanisms underpinning improvement in Cr.
Therefore, the purpose of this study was to compare the effectiveness of 2 strength training methods matched for volume and intensity to improve Cr in male endurance athletes. Because it allows the use of series and parallel elastic components and has therefore the potential for improving the ability of the muscle tendon unit to store and recoil elastic energy, we hypothesized that plyometric training would result in a greater decrease in Cr than DWT.
Methods
Experimental Approach to the Problem
After a thorough briefing and medical screening, all participants signed a written statement of informed consent. Once included, they first completed a maximal continuous graded exercise test (session 1), followed by a force-velocity test (session 2), a countermovement jump test, and a performance test (session 3). All tests were separated by at least 48 hours and were performed in a 7-day period, before and after an 8-week training period. To avoid any residual fatigue induced by recent training, participants were asked to refrain from strenuous exercise the day before the tests. They were also asked to arrive fully hydrated to the laboratory, at least 3 hours after their last meal. No attempt was made to control the content of this meal. After initial testing, participants were randomly assigned to the DWT group, PT group, and the control group (C). The groups were matched for age and peak oxygen consumption. There were no initial differences in other dependent variables between groups.
Subjects
Thirty-five moderately to well-trained male endurance runners with no history of strength training participated in this study. They were competing at a provincial-standard level (3-7 training sessions per week) at distances between 5,000 and 42,195 m. Their age, stature, body mass, body mass index, and sum of skin folds (triceps, biceps, subscapular, and suprailiac) are reported in Table 1. The protocol was reviewed and approved by the Research Ethics Board in Health Sciences of the University of Montreal, Canada.
;)
Table 1: Physical characteristics of the participants during the experimental protocol.*†
Procedures
Exercise Testing
Maximal continuous graded exercise test: This test was performed on a motorized treadmill (Quinton, Bothell, WA, USA), which was calibrated at 8 and 16 km·h−1 (gradient = 0) before each session with an “in-house” system using an optical sensor connected to an acquisition card. Initial speed was set at 12 km·h−1 for 6 minutes, to determine the energy cost of running, and increased by 0.5 km·h−1 every minute until exhaustion. The grade was set at zero throughout the test. The speed of the last completed stage was considered as the peak treadmill speed (PTS). Oxygen uptake (o2) was determined continuously on a 15-second basis using an automated cardiopulmonary exercise system (Moxus, AEI Technologies, Naperville, IL, USA). Gas analyzers (S3A and CD3A, AEI Technologies, Naperville, IL, USA) were calibrated before each test, using a gas mixture of known concentration (15% O2 and 5% CO2) and ambient air. Their accuracy was ±0.003% for oxygen and ±0.02% for carbon dioxide (data provided by the manufacturer). The turbine was calibrated before each test using a motorized syringe (Vacu-Med, Ventura, CA, USA) with an accuracy of ±1%.(18) The tidal volume was set at 3l and the stroke rate at 40 cycles per minute. Mean o2 over the last 2 minutes of the initial 6-minute bout was divided by speed to calculate the energy cost of running (Cr, in ml·kg−1·km−1). The highest o2 over a 15-second period during the test was considered as peak oxygen consumption (o2peak, in ml·kg−1·min−1).
Force-velocity test: This test was performed on a guided squat rack allowing only vertical movements (Atlantis, Laval, Quebec, Canada). When cued, the participant moved from the standing position into a semisquat position (90° knee flexion) and had to stay motionless for 4 seconds (39) before moving the load as fast as possible. Two consecutive trials were performed per load, with the best reading recorded for further analyses. Three minutes of passive recovery was given between each load. Maximal average velocity and power were recorded by linking a shuttle to the end part of the bar locked to an infrared sensor (Musclelab, Ergotest, Norway). The accuracy of this electronic device reached the 10-microsecond time resolution with an optical transducer interruption each 3 mm of displacement (2). Average velocity and power were calculated through the whole range of motion used to perform a complete repetition (from 90° knee flexion to the full extension). Power-load curve was plotted during the test. The initial load was 10 kg and was increased by 10 kg until the flattening of the Power-Load curve and by increments of 5 kg afterward. The test was completed when power decreased during at least 2 consecutive loads. The highest power was considered as peak power (Ppeak, in W).
Countermovement jump test: This test was performed in the laboratory. When cued, the participant made a countermovement before jumping as high as possible. The hands had to be placed on the hips throughout the entire jump. No specific instruction was given regarding the depth or speed of the countermovement. Three trials separated by 1 minute of passive recovery were performed. The best one was recorded for further analyses. Vertical jump height was calculated from flight time using basic kinematic equations (22). Flight time was recorded with an optical system consisting of 2 bars placed opposite to each other and connected to a PC via the serial port (Optojump, Microgate, Bozano, Italy). This system transmits an infrared light 1-2 mm above the floor. When the light is interrupted by the feet, the units trigger a timer with a precision of 1 microsecond. The highest height was considered as peak vertical jump height (VJHpeak, in cm).
Performance test: This test was performed on a 200-m indoor track and consisted in an individual 3,000-m run. Participants were instructed to cover the distance as fast as possible and encouraged to maintain an even pace throughout the run in order to produce the best performance. Time was measured to the nearest second and considered as the performance criterion (Perf3,000, in seconds). Mean velocity over the 3,000 m was calculated and divided by PTS to estimate aerobic endurance (End, in % PTS) (3).
Training Interventions
Endurance Training
All participants (DWT, PT, and C) followed the same basic endurance-training program that was typical to what they were already doing. It involved 2 high-intensity interval training sessions and 1 low-intensity continuous training session per week. The content of these training sessions is described in Table 2.
Table 2: Basic endurance training program.*
Strength Training
Participants of the control group did not train for strength, whereas participants of DWT and PT groups performed 1 strength training session per week. The strength training program was designed to improve maximal power, defined as the ability to produce a high amount of force over a very short period of time (30). Training details relative to the number of sets and repetitions are given in Table 3. Rapid improvements were expected because participants had no experience in this kind of training. Therefore, the fourth training session was dedicated to the adjustment of training intensities by the mean of specific tests.
Table 3: Strength training program.*
Participants of the DWT group were required to perform purely concentric semisquats on a guided squat rack allowing only vertical movements (Atlantis, Laval, Quebec, Canada) and to move the load as fast as possible. This load was determined individually; it corresponded to the load allowing the attainment of Ppeak during the force-velocity test. Average power through the whole range of motion was measured with an infrared sensor (Musclelab, Ergotest, Norway; see Force-velocity test for a more complete description). A trial was counted only if power was at least 95% of Ppeak measured during the force-velocity test; otherwise it had to be recommenced. Feedback about power and validity of the trial was given at after each repetition.
Participants of the PT group were required to perform drop jumps from 20, 40, or 60-cm jump boxes. Briefly, a drop jump consists in stepping down from a given height and bouncing as high as possible. The hands have to be placed on the hips throughout the entire jump. In our study, no specific instruction was given regarding the depth or speed of the countermovement. The height of the jump box was determined individually; it corresponded to the height that allowed the participant to reach the highest vertical jump height (supposedly the highest power). Vertical jump height was measured with an optical system (Optojump, Microgate; see Countermovement Jump Test for a more complete description). A trial was counted only if the vertical jump height was at least 95% of the maximal vertical jump height reached during the first or the fourth training session; otherwise, it had to be recommenced. Feedback about vertical jump height and validity of the trial was given after each repetition.
Statistical Analyses
Standard statistical methods were used for the calculation of means and SDs. Normal Gaussian distribution of the data was verified by the Shapiro-Wilk test and homoscedascticity by a modified Levene Test. All variables met these underlying hypotheses. A 2-way analysis of variance (ANOVA) (Time × Group) with repeated measures on the Time factor was performed. Multiple comparisons were made with the Bonferroni post hoc test. The magnitude of the difference was assessed by the effect size (ES), calculated according to the following equation:
where ES is the effect size, M1 and M2 are the mean of the first and the second trial and SDpooled is the pooled SD, calculated as follows:
where S12 and S22 are the variance of the first and the second trials, and n is the number of participants. The magnitude of the difference was considered either small (0.2 < ES ≤ 0.5), moderate (0.5 < ES ≤ 0.8), or large (ES > 0.8) (8). Pearson product moment correlation was used to evaluate the association between relevant parameters. The significance level was set at p ≤ 0.05. All calculations were made with Statistica 6.0 (Statsoft, Tulsa, USA).
Results
Seven participants did not complete the 8-week training program and were withdrawn from the study. The main reasons were illness (n = 1), lack of motivation (n = 2), or injury (n = 4). It is worth noting that none of the injuries occurred during a strength training session. We deplored an ankle sprain during hiking (n = 1) and minor muscular tears during a graded exercise test (n = 1) or during a recreational activity (n = 2). Final sample sizes were n = 12 in DWT, n = 11 in PT, and n = 5 in C. These participants completed 97% (DWT), 99% (PT), and 100% (C) of the scheduled sessions, which reflects a very high training compliance.
There were no initial differences in dependent variables between groups. Body mass, body mass index, and the sum of skin folds did not change after the 8-week training intervention (Table 1), nor did o2peak or End (Table 4). The 2-way ANOVA revealed an interaction between time and group (p < 0.05) and an effect of time for Cr (p < 0.01, Table 4), whatever the power attributed to body mass (kg−1 or kg−0.75). Post hoc analysis allowed us to identify a moderate decrease in DWT (ES = 0.62, p < 0.01) and a large decrease in PT (ES = 1.01, p < 0.01). There was no improvement in C (ES = 0.00, NS). Individual results are shown in Figure 1. We also found an interaction between time and group (p < 0.05) and an effect of time (p < 0.01) for Ppeak (Table 4). The addition of a weekly strength training session induced a large increase of Ppeak in DWT (ES = 0.98, p < 0.01) and a small increase in PT (ES = 0.24, p < 0.01). No differences were found in C (ES = 0.04, NS). We found an effect of time for VJHpeak (p < 0.01). Both experimental groups improved VJHpeak (PT: ES = 0.52, p < 0.01 − DWT: ES = 0.25, p < 0.01). No differences were found for C (ES = 0.26, NS). Perf3000 increased moderately in PT (ES = 0.46, p < 0.05) and in DWT (ES = 0.37, p < 0.05). Improvements in Perf3000 were small for C (ES = 0.20, p < 0.05). No correlations were found, by the exception of an association between initial Cr and the percent change after the training intervention in experimental groups (r = − 0.57, p < 0.05; Figure 2).
Table 4: Physiological and neuromuscular results in the experimental and control groups.*†
Figure 1: Individual changes in C r from pre to posttraining for the 3 different experimental conditions. A) dynamic weight training (n = 12); B) plyometric training (n = 11); and C) control group (n = 5). The thick line represents group average.
Figure 2: Correlation between the initial level in C r and the percentage of changes from pre to posttraining for the subjects from the experimental groups (n = 23).
Discussion
The aim of this study was to compare the effectiveness of 2 strength training methods matched for volume and intensity to improve Cr in male endurance athletes. We hypothesized that plyometric training would result in a greater decrease in Cr because of an improved storage-recoil capacity of elastic energy. Our results partly confirmed this hypothesis. Participants of PT displayed a greater decrease in Cr than their DWT's counterparts (7% vs. 4%). It has to be mentioned that results from a recent article show that changes in Cr greater than 2.4% can be attributable to a training intervention rather than a testing error or day-to day variations (33). However, we failed to find any relationship with the capacity to store and recoil elastic energy as no correlations were found between changes in VJHpeak and changes in Cr.
It has been shown that o2 does not increase in proportion to body mass during both submaximal and maximal intensity running (1). To avoid misinterpretations when comparing individuals with different body masses, such as children and normal or overweight adults, it is often recommended to express o2 relative to the body mass raised to the power of 0.75 (1,16). In addition to improve the validity of comparisons, this allometric scaling has been reported to decrease interindividual variability (16), thus increasing statistical power. We made a sensitivity analysis between Cr expressed in ml·kg−0.75·m−1 or in ml·kg−1·m−1 and found no reason to use one approach instead of the other one. Because body mass was homogeneous (as measured by a modified Levenne Test) and not different between DWT, PT, and C, we finally opted for the classical approach (i.e., body mass raised to the power of 1).
A recent research (35) examined the effect of plyometric training on Cr. Eight moderately to well-trained male endurance runners added 2 sessions of high volume-low intensity plyometric training per week during 6 weeks to their usual endurance training. The authors found a moderate decrease in Cr (p < 0.05, ES = 0.46), whereas both End (as measured by lactate threshold) and o2peak remained unchanged. Other authors (34,37) reported similar amplitudes of improvement after a 6- to 9-week high volume-low intensity plyometric training period in moderately to well-trained endurance athletes (p < 0.05, ES = 0.28-0.30). In contrast to these reports, participants of the present study performed a low volume-high intensity plyometric training. Our results confirm the positive effect of such training on Cr but with a much greater amplitude of improvement (p < 0.01, ES = 1.01). It should be noted that these gains were obtained with only 1 session per week. It is far less than current recommendations (30,31) or practices (34,35,37). A recent meta-analysis examining the effectiveness of plyometric training for improving vertical jump height reported an overall ES of 0.84 (38). The ES of the PT group, which was 1.01, underscore the undoubted efficiency of the method we used in this study that relied more on training intensity than training volume.
We were not able to find a concurrent strength and endurance training study that used the same weight training protocol than ours. In a recent study (26), 7 well- to highly trained triathletes added 2 sessions of low-volume, low-velocity, and high-intensity strength training per week during 14 weeks to their usual endurance training. They reported a large decrease in Cr (p < 0.05, ES = 1.10), whereas End (as measured by the second ventilator threshold) and o2peak remained the same. These results were confirmed very recently (36). The authors found a large decrease in Cr (p < 0.05, ES = 1.03) in 8 moderately to well-trained endurance athletes after a high intensity, low velocity, and low volume strength training program 3 d·wk−1 during an 8-week period. In our study, participants of DWT performed a low-volume, high-velocity, and moderate-intensity strength training that allowed reaching at least 95% of maximal power. This intervention resulted in a moderate decrease in Cr (p < 0.01, ES = 0.63). This amplitude of improvement was less than results previously published (26,36). Several factors may have contributed to this difference. Current guidelines recommend 2-3 sessions per week to improve maximal strength (30,31). In this study, participants of experimental groups added only 1 session per week to their endurance training. It is possible that the overall training load was not sufficient to stress adequately adaptation processes in DWT. However, the large increase in Ppeak (p < 0.01, ES = 0.98) we observed in this group, which was comparable with the gains reported in strength alone training studies (p < 0.01, ES = 1.03) (40), does not support this contention. Another possible explanation is that concentric maximal power per se is not a major determinant of Cr. If such an association existed, the corollary for the higher increase of Ppeak we found in DWT should have been a higher decrease in Cr. The inverse was true, because we observed an interaction that favors PT and found no association between changes in Ppeak and changes in Cr.
Because they used the same movement and were matched for training volume and intensity, the main difference between DWT and PT was the type of muscular contraction. Although DWT was purely concentric, PT allowed the use of series and parallel elastic components and therefore had the potential for improving the ability of the muscle-tendon unit to store and recoil elastic energy. However, we were not able to find any association between changes in VJHpeak and changes in Cr, nor any interaction between experimental groups regarding jump performance. Adaptations regarding the ability to use elastic energy and to develop more power probably differed between PT and DWT (38), but both contributed to the increased VJHpeak. Therefore, it appears that the countermovement jump test was not sensitive enough in itself to underline specific improvements in the ability to store and recoil elastic energy. Another possible explanation could be related to the important number of factors influencing Cr. It is possible that improvements in power and in the ability to use elastic energy are not the only determinants that contributed to a decrease in Cr. Indeed, some authors reported that changes in muscle stiffness and mechanical factors can influence Cr (15,25,27,32). A limit of this study is therefore the lack of a sensitive measure of these neuromuscular determinants.
The inverse relationship we found between initial Cr and percent change in Cr suggests that already efficient runners did not take the same advantage from a strength training program than less efficient ones. Either their adaptation capacity was at its maximum or more probably the training methods we used in this study were not adequate to stress it at a higher level. This issue has already been addressed (12). These authors assigned 12 novice and 14 varsity female rowers to either a low intensity-high repetition (H-rep) or a high intensity-low repetition (H-load) strength training group. Performance at a 2,000-m rowing ergometer test was recorded before and after an 8-week combined strength and endurance-training period. Interestingly, the authors reported that varsity rowers who performed H-load training demonstrated greater improvements in performance compared with those who performed H-rep training. Inversely, H-rep training was more effective than H-load training in novice participants. Our results and these results (12) concur with the hypothesis that the effectiveness of strength training to improve Cr or performance is dependent on both training status and the characteristics of strength training load.
The ultimate objective with athletic training is to improve performance. In this study, runners from the experimental groups and from the control group showed significant gains in Perf3,000. Although these results were expected for both PT and DWT, improvements for C are surprising considering that no performance determinants were modified. It should be kept in mind however that the variability of o2max END and Cr explains roughly 70% of the variability in marathon performance (10). This means that other factors are involved that were not measured in this study, such as psychological variables (29) and the use of other metabolic (anaerobic) pathways (4,28). Finally, although we found no interaction between groups, their respective ES (0.46, 0.37, and 0.20) suggests that the gains were higher in experimental groups and could have been significant with more statistical power.
Practical Applications
It has been shown that Cr can predict performance for middle and long distance runners with similar o2max values. Cr is influenced by a number of factors including strength training and neuromuscular adaptations. The purpose of this study was to compare the effectiveness of 2 strength training methods matched for volume and intensity to improve Cr in male endurance athletes. Our results confirm that athletes and coaches should include in their practices a precise assessment of Cr to plan an optimal training program. Although it is well known that strength training represents an important intervention to reduce the prevalence of injury (7,19), our results show that explosive strength training and more particularly PT is, moreover, a good intervention to improve Cr. Therefore, coaches should plan a strength training periodization that emphasizes on these 2 components. Athletes showing the initial highest Cr values will particularly benefit from explosive strength training. These positive adaptations can be expected after an 8-week intervention focusing on intensity rather than volume. For athletes with already low Cr, interventions should focus on increasing training volume and or intensity. As shown by the improvements in VJHpeak and in Ppeak, explosive strength training will benefit to runners by increasing their general athletic performance.
Acknowledgments
The authors wish to thank Jerome Blais (B.Sc.) for the technical assistance. The authors have no conflict of interest and received no funding for this study. The authors have no professional relationships with companies or manufacturers that might benefit from the results of this study. The results of this study do not constitute endorsement of any product by the authors or the National Strength and Conditioning Association. No funds were received for this work from any organizations.
References
1. Bergh, U, Sjödin, B, Forsberg, A, and Svedenhag, J. The relationship between body mass and oxygen uptake duting running in humans.
Med Sci Sports Exerc 23: 205-211, 1991.
2. Bosco, C, Belli, A, Astrua, M, Tihanyi, J, Pozzo, R, Kellis, S, Tsarpela, O, Foti, C, Manno, R, and Tranquilli, C. A dynamometer for evaluation of dynamic muscle work.
Eur J Appl Physiol Occup Physiol 70: 379-386, 1995.
3. Bosquet, L, Leger, L, and Legros, P. Methods to determine aerobic endurance.
Sports Med 32: 675-700, 2002.
4. Bulbulian, R, Wilcox, AR, and Darabos, BL. Anaerobic contribution to distance running performance of trained cross-country athletes.
Med Sci Sports Exerc 18: 107-113, 1986.
5. Chilibeck, PD, Syrutuik, DG, and Bell, GJ. The effect of strength training on estimates of mitochondrial density and distribution throughout muscle fibres.
Eur J Appl Physiol 80: 604-609, 1999.
6. Chu, DA.
Jumping into Plyometrics. Champaign, IL, Human Kinetics, 1998.
7. Clement, DB and Taunton, JE. A guide to the prevention of running injuries.
Aust Fam Phys 10: 156-161, 163-164, 1981.
8. Cohen, J.
Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ, L. Erlbaum Associates, 1988.
9. Conley, DL and Krahenbuhl, GS. Running economy and distance running performance of highly trained athletes.
Med Sci Sports Exerc 12: 357-360, 1980.
10. di Prampero, PE, Atchou, G, Bruckner, JC, and Moia, C. The energetics of endurance running.
Eur J Appl Physiol Occup Physiol 55: 259-266, 1986.
11. Docherty, D and Sporer, B. A proposed model for examining the interference phenomenon between concurrent aerobic and strengh training.
Sports Med 30: 385-394, 2000.
12. Ebben, WP, Kindler, AG, Chirdon, KA, Jenkins, NC, Polichnowski, AJ, and Alexander, VN. The effect of high load vs high repetition training on endurance performance.
J Strength Cond Res 18: 513-517, 2004.
13. Foster, C and Lucia, A. Running economy: The forgotten factor in elite performance.
Sports Med 37: 316-319, 2007.
14. Häkkinen, K, Komi, PV, and Alen, M. Effect of explosive type strength training on isometric force- and relaxation-time, electromyographic and muscle fibre characteristics of leg extensor muscles.
Acta Physiol Scand 125: 587-600, 1985.
15. Heise, GD and Martin, PE. “Leg spring” characteristics and the aerobic demand of running.
Med Sci Sports Exerc 30: 750-754, 1998.
16. Helgerud, J. Maximal oxygen uptake, anaerobic threshold and running economy in women and men with similar performances level in marathons.
Eur J Appl Physiol 68: 155-161, 1994.
17. Hoff, J, Helgerud, J, and Wisloff, U. Maximal strength traiing improves work economy in trained female cross-country skiers.
Med Sci Sports Exer 31: 870-877, 1999.
18. Huszczuk, A, Whipp, BJ, and Wasserman, K. A respiratory gas exchange simulator for routine calibration in metabolic studies.
Eur Res J 3: 465-468, 1990.
19. Johnston, CA, Taunton, JE, Lloyd-Smith, DR, and McKenzie, DC. Preventing running injuries. Practical approach for family doctors.
Can Fam Phys 49: 1101-1109, 2003.
20. Kaneko, M, Fuchimoto, T, Toji, H, and Suei, K. Training effect of differing loads on the force-velocity relationship and mechanical power output in human muscle.
Scand J Sport Sci 5: 50-55, 1983.
21. Larsen, HB. Kenyan dominance in distance running.
Comp Biochem Physiol A Mol Integr Physiol 136: 161-170, 2003.
22. Lehance, C, Croisier, JL, and Bury, T. Optojump system efficiency in the assessment of lower limbs explosive strength.
Sci Sports 20: 131-135, 2005.
23. MacDougall, JD, Sale, DG, Moroz, JR, Elder, GCB, Sutton, JR, and Howald, H. Mitochondrial volume density in human skeletal muscle following heavy resistance training.
Med Sci Sports Exerc 11: 164-166, 1979.
24. Malisoux, L, Francaux, M, Nielens, H, Renard, P, Lebacq, J, and Theisen, D. Calcium sensitivity of human single muscle fibers following plyometric training.
Med Sci Sports Exerc 38: 1901-1908, 2006.
25. McMahon, TA and Cheng, GC. The mechanics of running: How does stiffness couple with speed?
J Biomech 23: 65-78, 1990.
26. Millet, GP, Jaouen, B, Borrani, F, and Candau, R. Effects of concurrent endurance and strength training on running economy and o
2 kinetics.
Med Sci Sports Exerc 34: 1351-1359, 2002.
27. Morgan, DL, Proske, U, and Warren, D. Measurements of muscle stiffness and the mechanism of elastic storage of energy in hopping kangaroos.
J Physiol 282: 253-261, 1978.
28. Paavolainen, L, Häkkinen, K, Hamalainen, I, Nummela, A, and Rusko, H. Explosive-strength training improves 5-km running time by improving running economy and muscle power.
J Appl Physiol 86: 1527-1533, 1999.
29. Raglin, JS. The psychology of the marathoner: Of one mind and many.
Sports Med 37: 404-407, 2007.
30. Ratamess, NA, Alvar, BA, Evetoch, TK, Housh, TJ, Kibler, WB, Kraemer, WJ, and Triplett, NT. American College of Sports Medicine position stand. Progression models in resistance training for healthy adults.
Med Sci Sports Exerc 41: 687-708, 2009.
31. Rhea, MR, Alvar, BA, Burkett, LN, and Ball, SD. A meta analysis to determine the dose response for strength development.
Med Sci Sports Exerc 35: 456-464, 2003.
32. Saunders, PU, Pyne, DB, Telford, RD, and Hawley, JA. Factors affecting running economy in trained distance runners.
Sports Med 34: 465-485, 2004.
33. Saunders, PU, Pyne, DB, Telford, RD, and Hawley, JA. Reliability and variability of running economy in elite distance runners.
Med Sci Sports Exerc 36: 1972-1976, 2004.
34. Saunders, PU, Telford, RD, Pyne, DB, Peltola, EM, Cunningham, RB, Gore, CJ, and Hawley, JA. Short-term plyometric training improves running economy in highly trained middle and long distance runners.
J Strength Cond Res 20: 947-954, 2006.
35. Spurrs, RW, Murphy, AJ, and Watsford, ML. The effect of plyometric training on distance running performance.
Eur J Appl Physiol 89: 1-7, 2003.
36. Storen, O, Helgerud, J, Stoa, EM, and Hoff, J. Maximal strength training improves running economy in distance runners.
Med Sci Sports Exerc 40: 1087-1092, 2008.
37. Turner, AM, Owings, M, and Schwane, JA. Improvement in running economy after 6 weeks of plyometric training.
J Strength Cond Res 17: 60-67, 2003.
38. Villarreal, ES, Kellis, E, Kraemer, WJ, and Izquierdo, M. Determining variables of plyometric training for improving vertical jump height performance: A meta-analysis.
J Strength Cond Res 23: 495-506, 2009.
39. Wilson, GJ, Elliott, BC, and Wood, GA. The effect on performance of imposing a delay during a stretch-shorten cycle movement.
Med Sci Sports Exerc 23: 364-370, 1991.
40. Wilson, GJ, Newton, RU, Murphy, AJ, and Humphries, BJ. The optimal training load for the development of dynamic athletic performance.
Med Sci Sports Exerc 25: 1279-1286, 1993.
