The oxygen uptake (o2) at a submaximal running speed (running economy) has been strongly correlated with distance running performance when maximal oxygen uptake (o2max) values are comparable (5,8). Previous work has acknowledged age, sex, body mass, body temperature, muscle fiber composition, biomechanical factors, fatigue, and training as interindividual characteristics that may contribute to the variability in running economy (1,7,15,16). Flexibility has been controversially suggested as one of the trainable, biomechanical factors that may affect running economy (6,10,13). Researchers have identified a significant inverse relationship between flexibility and running economy; that is, lower flexibility scores have been related to a greater economy (6,10,13). These results suggest that the inflexibility seen in the hip and leg musculature allows for greater elastic energy storage and use in the muscles and tendons during the running gait (6,10,13). Specifically, it was suggested that the distance runners with tighter musculotendinous structures demanded less work from the muscles (i.e., a lower o2) at a submaximal velocity because they used more elastic energy while running (6,10,13). The importance of this mechanism to running is substantial because the use of elastic energy has been calculated as contributing to 40-50% of the energy demanded during distance running (4).
Other research fails to support the existence of an inverse relationship between flexibility and running economy, countering that flexibility is an essential component in reaching peak running performance (2,11,17). These conflicting results, as well as the lack of experimental research, prevent drawing a firm conclusion on the flexibility-economy relationship. Additional research is clearly warranted to further investigate the proposed association and its significance to the distance running population.
While taking into account the potential inverse relationship between flexibility and running economy, it is also interesting to consider the sex differences among these 2 variables. In a study of elite distance runners, Daniels and Daniels (8) found that men were 6-7% more economical than women at a fixed velocity. Similarly, Bransford and Howley (3) observed a sex difference in running economy among trained and untrained subjects, and they suggest that mechanical and training differences are key contributors to the variation. Although running economy is multifactorial, if its inverse relationship with flexibility is valid, it would not be surprising that men have consistently demonstrated less flexibility than women (10,14,19).
Contrary to other similar correlational studies, the current investigation collected data from both sexes to examine the cross-gender relationship between flexibility and running economy. The purpose of the current study was to determine the magnitude of the relationship between running economy and sit-and-reach flexibility among men and women collegiate distance runners. It was hypothesized that there would be a significant inverse relationship between sit-and-reach flexibility and running economy. That is, an inflexible runner will demonstrate a greater economy than his or her flexible counterpart through the use of more stored elastic energy, thereby demanding less work from the muscles while running. Furthermore, we hypothesized that women would display greater sit-and-reach flexibility than men and that men would exhibit a more efficient running economy at a submaximal velocity.
Experimental Approach to the Problem
A correlational study was designed to determine the magnitude of the relationship between sit-and-reach flexibility and running economy. Evaluating a group of well-trained distance runners, flexibility was quantified using the standard sit-and-reach test (9). The sit-and-reach scores were correlated to the subjects' running economies at both absolute and relative (10-km pace) velocities. Running economy (ml·kg−1·m−1) was calculated by dividing the velocity (m·min−1) into the o2 (ml·kg−1·min−1) consumed at the submaximal velocity (2,10). This was done to allow comparison of the economies at a relative velocity. Finally, the means of each sex were compared to examine differences in sit-and-reach flexibility and running economy.
Eight distance runners (4 men and 4 women) from the Nebraska Wesleyan University track and field team participated in this study. The pool was limited to distance runners to acquire well-trained endurance athletes with comparable aerobic capacities. Descriptive characteristics of the subjects are presented in Table 1 (mean ± SD). At the time of the study, the distance runners were training for their outdoor track season, where they competed in races ranging from 1500 m to 10 km. At the time of the study, their training involved running 50 ± 10 miles each week.
To measure running economy in distance runners, data were collected at an absolute velocity and at a relative velocity near 10-km race pace (8). Therefore, each subject's reported 10-km pace was used to predetermine the progression of the maximal treadmill test and to establish the relative speed at which running economy was recorded. This protocol was also used to ensure that fatigue was comparatively equal among the subjects throughout the treadmill test. If the subjects had not participated in a 10-km race within the previous year, Riegel's (18) formula estimated a 10-km pace from a different race distance that had been completed the previous year. For example, if 5-km performance was reported, Riegel's formula (which estimates that pace will decrease by 6.89% when distance doubles) was used to determine the subject's 10-km pace. Before the testing session, all subjects gave written informed consent to participate in this study. This study was approved by the health and human performance faculty of Nebraska Wesleyan University. To minimize the effects of fatigue, the treadmill test served as the workout on the testing day for all subjects.
Flexibility was assessed using the standard sit-and-reach test, with the foot line at 23 cm. The sit-and-reach test has been used in similar previous research (2,6,13) and has been shown to be a valid measure of hamstring flexibility (14). Before warming up, and with their shoes off, each subject completed 3 attempts of the sit-and-reach test, pushing the slide as far forward on the sit-and-reach box as possible while keeping their legs straight. Each subject's best score of the 3 attempts was used in the statistical analyses.
After the sit-and-reach test, running economy and o2max were assessed during one incremental maximal treadmill test performed to volitional exhaustion. Gas exchange was collected via open-circuit calorimetry and was analyzed breath-by-breath using a metabolic cart (SensorMedics VMax 29, Yorba Linda, Calif). All subjects jogged approximately 330 m on an indoor track to warm up. A heart rate monitor (Polar FS1, Lake Success, NY) was used to observe heart rate throughout the treadmill test. To begin the treadmill test, the subjects walked for 3 minutes at 80.4-93.8 m·min−1, and then they proceeded to the first running stage. This first stage was predetermined for each sex as 33.3 m·min−1 less than the slowest individual's 10-km pace (men = 241.2 m·min−1; women = 198.32 m·min−1). The second stage was set at a speed halfway between the first and the third stages, with the third stage representing each subject's 10-km race pace. Thereafter, speed was increased by 16.67 m·min−1 until volitional exhaustion. Each stage was sustained for 3 minutes. The average o2 during the third minute of the first stage and the third minute of the third stage were recorded to calculate running economy (ml·kg−1·m−1) at absolute and relative velocities, respectively. Each subject's o2max (ml·kg−1·min−1) was recorded as the average o2 value measured during the final minute of the test, just before volitional exhaustion.
The data were analyzed using the Statistical Package for Social Sciences (Version 13.0, SPSS, Inc., Chicago, Ill), with the alpha level set at 0.05. The statistical analyses consisted of descriptive statistics, independent t-tests, and 1-tailed Pearson correlations. Descriptive statistics revealed mean and SD values for individual characteristics (age, height, weight, average miles run per week, and 10-km time) as well as the values obtained from the sit-and-reach assessment and the maximal treadmill test (o2max and running economy). The data were analyzed separately to examine sex differences, and they were analyzed together to evaluate trends. Independent t-tests assessed the differences between sexes in sit-and-reach flexibility and running economy. Omega squared was used to evaluate the magnitude of any differences. One-tailed Pearson correlations were used to assess the relationships between sit-and-reach flexibility and running economy and between running economy and 10-km time. The coefficient of determination quantified the variance in running economy that could be explained by sit-and-reach flexibility. Post hoc power calculations revealed a power of 0.93 for the Pearson r correlation between sit-and-reach flexibility and absolute running economy, and 0.50, 0.64, and 0.99 for the powers of the independent t-tests for relative running economy, absolute running economy, and sit-and-reach flexibility, respectively.
The results of this study are presented in Table 2 (mean ± SD). An independent t-test indicated a significant (p ≤ 0.05) difference between the sexes in sit-and-reach scores (Table 2). Statistically significant sex differences were not found in running economy data.
The correlational analysis revealed a significant relationship (r = 0.826, p = 0.006) between sit-and-reach scores and running economy among 8 collegiate distance runners at an absolute velocity (Figure 1). The coefficient of determination indicated that 68% of the variability seen in running economy at an absolute velocity can be explained by the variability in sit-and-reach scores. A similar relationship was observed between sit-and-reach scores and running economy at a relative velocity (Figure 1). However, the Pearson r was not statistically significant (r = 0.606, p = 0.056). Lastly, running economy at an absolute velocity was significantly correlated to 10-km running time (r = 0.686, p = 0.03).
The main finding of this study is that sit-and-reach flexibility is inversely related to running economy at an absolute velocity in men and women collegiate distance runners. As hypothesized, the runners with less sit-and-reach flexibility tended to be more economical at a submaximal velocity. These results support previous research that recognized an inverse relationship between flexibility and running economy among both distance runners and nonathletes (6,10,13). Although running economy at a relative velocity (10-km pace) was not significantly related to sit-and-reach flexibility (r = 0.606, p = 0.056), the parallel trend lines in Figure 1 are indicative of similar relationships. The present study has revealed a significant relationship across both men and women runners, suggesting that the inverse correlation is not gender specific.
The question arises as to which mechanisms explain the inverse relationship observed between flexibility and running economy. Many authors suggest that the foremost explanation is the influence of the elastic energy storage and release mechanism of the muscles and tendons during the stretch-shortening cycle (6,10,13). Gleim et al. (10) have speculated on the potential energy-saving effects of this mechanism. They suggest that when a stiff muscle is stretched, it will generate greater tension from the elastic component than a more compliant muscle (10). Supporting research by Cavagna et al. (4) concludes that 40-50% of the energy demanded during distance running is provided by the use of elastic energy. This source of energy is most likely concentrated in the larger muscle groups of the legs, supplying the lower limbs with the most efficient means to maintain the running gait. Therefore, the current study adds further evidence that sit-and-reach flexibility is a good predictor of running economy and, thereby, of running performance in distance runners.
Although the findings of the current study lend support to the inverse relationship between sit-and-reach flexibility and running economy, it is important to note that they are inconsistent with some research. Beaudoin and Blum (2) recently have reported that many measures of lower-body flexibility were not significantly correlated to running economy in women distance runners. However, the authors acknowledge that their results conflict with previous research, and they attribute their contradictory findings to demographic and methodological differences (2). Further, in accordance with the current study's findings, one might suspect that running economy would worsen with an improvement in sit-and-reach flexibility. However, Nelson et al. (17) revealed opposing, yet promising, results in which a 10-week chronic stretching program improved flexibility by 9% but did not negatively influence running economy significantly. Considering these results, we speculate that with an increase in chronic flexibility, its relationship with running economy might simply shift to the right or increase the slope of the trend line (see Figure 1). Alternatively, a short-term study reports that 7 men college students actually improved their running economy by 4-7% immediately after a static stretching program that produced acute increases in flexibility (11). Although the subjects were not distance runners, these results support stretching before physical activity and corroborate the general belief that muscle flexibility and a greater joint range of motion enhance athletic performance (11).
The results of the current study indicate a significant correlation between 10-km time and running economy (r = 0.686, p = 0.03), supporting the suggestion that running economy is strongly related to distance running performance (5,8). This relationship also suggests that lab-based measurements of running economy are valid predictors of distance running performance. The significant sex difference observed in sit-and-reach scores confirms our hypothesis that men tend to be less flexible than women. These results are comparable with previous findings in which women were significantly more flexible than men in the sit-and-reach test (14,19). Statistically significant sex differences were not found in running economy at either velocity in this study. However, the omega squared value of 27% does indicate differences in running economy between the sexes, supporting previous suggestions that men are more economical runners than women (3,8). It is important to note that the limited number of subjects involved in this study probably resulted in difficulty detecting significant results. Therefore, the correlation trends should be considered in addition to the significant findings when interpreting the results.
Regarding the measurement and expression of running economy, it may be beneficial to arrive at an agreeable standard unit of economy (e.g., milliliters per kilogram per meter). Consistency in the reporting of this measurement will allow for comparison across studies and individuals in which running economy is assessed at different velocities and, eventually, will aid in collecting enough data to develop normative values for running economy. There is also a need for a standard protocol to measure running economy. Common protocols measure running economy by reporting o2 values at an inconsistent absolute speed ranging from 160.8 to 349.8 m·min−1 (2,6,8,13,17). However, in agreement with Beaudoin and Blum (2), it may be beneficial to assess running economy at a relative velocity as close as possible to a specific race pace, to best reflect an individual's running performance at that particular pace.
The findings of this study support the suggestion that distance runners with the least sit-and-reach flexibility tend to be more economical runners. These results add support to previous research findings of an inverse relationship between flexibility and running economy among distance runners. Because the current research analyzed both men and women, it uniquely indicates that the relationship continues across sex barriers. In support of previous theories, the relationship between flexibility and running economy can be explained with the function of the energy storage and release mechanism in the elastic components of the muscles and tendons. To establish the origin of the relationship between flexibility and running economy that was observed in this study, more experimental research is necessary. Future studies should investigate the acute and chronic effects of different stretching frequencies, intensities, durations, and modes of flexibility training (e.g., proprioceptive neuromuscular facilitation, dynamic stretching, static stretching, vibration training) on running economy and flexibility to determine the optimal range of motion and stretching program for distance runners.
Caution should be taken when drawing conclusions based on the proposed relationship, because it is correlational, not causal. Before assuming that inflexibility improves running economy, runners and coaches should also consider that inflexibility has been controversially associated with overuse running injuries (12). It also should be noted that optimal flexibility in a given joint motion may be sport specific, and although sit-and-reach inflexibility is associated with better running economy, the relationship may not transfer to other types of sports performance. Nonetheless, the results of the present study suggest that sit-and-reach flexibility is one of the many factors associated with running economy among collegiate distance runners.
The author thanks the members of the Nebraska Wesleyan University track and field team for contributing their time and talent to this study.
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