Study review- Running Economy: Neuromuscular and Joint-Stiffness Contributions in Trained Runners[i]
By Iris Saar
Running economy is a rather broad concept, pertaining to the physiological (metabolic) demands on the cardiovascular system- namely, the maximal oxygen consumption, or the ability to sustain a high oxygen consumption, during a given run velocity[ii]. The relationship between the efficiency of the runner and the energy expenditure can be described as reversed, defining the term “Economy” (lower energy cost=higher efficiency in the distance ran). The term pertains also to the biomechanical aspect of the skeletal system; it is assumed that a cluster of biomechanical factors, or variables, affect running economy or the submaximal oxygen consumption[iii] during a run. As humanity gets closer to breaking two hours in the marathon running distance of 26.2 miles, the question of how, if at all, biomechanical, neurological and spatiotemporal changes affects running economy is becoming more prominent. The article reviewed here[iv] addressed that question by assessing kinematics, kinetics and muscles coactivation among a group of sub-45 min. 10K runners, performing various running trials.
Biomehcnical changes are mostly musculatures coactivation and spatiotemporal changes can be stride frequency (cadence) and / or time spent contacting with the ground.
Among of the more studied biomechanical variables in the literature are[v]-
· Ground contact time: time from toe-touch to toe-off the ground.
· Swing time: toe-off to consecutive land of the same foot.
· Stride length: distance measured from toe off to land of second foot.
· Stride frequency: number of ground contact events per minute.
· Stride angle: ROM⁰ of hip extension during the stride.
· Initial contact, mid stance and propulsion: distribution of those during ground contact.
An additional concept studied in relation to running economy is joint mobility or the relative stiffness of the articulation. This is being hypothesized to be beneficial for running- the article reviewed here researched the contribution of joint stiffness to the rate of running efficiency among trained runners, together with spatiotemporal (time and space) changes.
Thirty (30) trained runners were selected for this study. The standard to determine level of training was a time result of sub-45 minutes 10K (=6.2 miles) run. For explanatory reasons, note that the age graded performance of runners in their mid-twenties (mean age of sample) is fifty-two (52) minutes[vi]. Therefor the sample presented higher than average level of training. The researchers do mention this later on as a potential conflicting factor in the spatiotemporal changes. They were asked to run at a speed equivalent to a fifty (50) minutes 10K for six consecutive minutes on a treadmill set to 1% elevation, which based on their usual training provided a relatively easy level of exertion, again as mentioned by the researches. This was deliberately done to enable a steady state of oxygen consumption which was measured as sub-max (VO2). Following the treadmill runs, the runners completed several trails of 60-meters track runs, during which trajectory markers were placed. This was done to determine the biomechanical factors affecting their running economy. Different settings were used to quantify oxygen cost and biomechanical changes (treadmill fr VO2 vs. running track or “overground” running for muscle coactivation).
Since the gait cycle consists of about six phases (Figure 1), it is important to establish a graphic understating of the cycle and its phases before further reviewing the method used to assess the relationship between the variables, which were studied during the stance phase. The gait cycle, with minimal differences between walking and running (mostly in torque) can be described as the first phase being the initial contact with ground. During this phase, Newton’s 3rd law comes into play and facilitates the respective force / load, creating propulsion of the body into the midstance phase. This phase is terminated and is instantly followed by the pre swing- an “introduction” to the swing phase itself. The swing is divided to a pre, mid and terminal swing phases. In this article, the researchers identified the peak phase to determine the angle, and moment, of maximal knee flexion; it has been set at the mid-stance phase.
Figure 1: components of the gait cycle[vii]
Seven key muscles which preoccupy running were classified as dependent variables, as listed below:
1. GM: Gluteus medius (posterior, proximal)
2. RF: Rectus femoris (anterior, proximal)
3. BF: Bicep femoris (posterior, proximal)
4. PL: Peroneus longus (anterior, distal)
5. TA: Tibialis anterior (anterior, distal)
6. LG: Gastrocnemius lateralis (posterior, distal)
7. MG: Gastrocnemius medius (posterior, distal)
Three of the muscles are located anteriorly at the lower limbs and four are posterior. This, by itself, is an interesting classification, as the motion of running is a forward movement however the majority of the propulsion is created thanks to our posterior musculature. Sub-classification made by the researchers (although not detailed in the article) was proximal vs. distal, with more distal regions (identical number of anterior/posterior locations). Although there are three anterior muscles listed, it was found that only the Rectus femoris was related to running economy. The only “collaboration” found between anterior and posterior muscles in the coactivation was between the Rectus femoris and the Gastrocnemius medius in the ground phase; since those muscles differ in location, perhaps preactivation creates a more stable environment for the entire lower limb, especially since this occurs prior to the swing phase. This question remains unanswered in the current study. Preactivation is another broad concept in running and in this scope can be applied as pre-workout drills such as bounding and strides.
Additional observation is the mono vs. biarticular muscles; the Rectus femoris and the Gastrocnemius operate on both hip and knee joints[viii] and therefor claimed to have a higher degree of efficiency in comparison to monoarticluar muscles such as the Gluteus medius, for example. The article mentions efficiency also in their ability to transfer elastic energy; this might be in fact due the fascia surrounding those muscles rather than the strength of the muscle fibers, as fascia is known to be an energy-saver elastic tissue[ix].
Muscle coactivation differed in the resulting cost of oxygen transfer. Previous study[x] recognized the Bicep femoris and Gastrocnemius leading as top contributors to higher energy costs. Those two muscles actually increased the energy costs during the propulsion and the initial ground contact (absorption of force, where it seems energy cot would be greater to begin with). In this article, however, no such relationship was based- perhaps to the more heterogeneous nature of the group and the different running speeds involved.
Coactivation may be detrimental; excessive activation in the joint might not respond appropriately to the load and the metabolic “price” might increase. This, in turn, can also increase the stiffness of the ankle which can negatively impact the runner’s economy (although, some degree of stiffness is actually necessary for the braking phase). According to the study, lower energy cost was found with a lesser coactivation rate of the Gastrocnemius lateralis and the Tibialis anterior So far, these factors are all biomechanics in character; spatiotemporal changes were only observed with higher cadence and shorter ground contact time as positively affecting the running economy. In another study[xi], it was found that “economical” running speed (a rather cautious term to describe optimal speed) is 70% of the runner’s lactate threshold; therefor, running economy can be practical and applied through specific pace designation.
In the question of what makes a runner more economical, shorter ground contact time and higher stride frequency have been found to be significant in positively affecting running economy. Looking back at the components of the gait cycle, it seems as the braking phase, in which most the absorption of force takes place, is shortened. The topic of stability vs. mobility concluded in the notion that greater knee stiffness is more economical, whereas mobility in the ankle joint negatively affects it (this correlates with the observation of higher energy costs in the more distal areas). Unsurprisingly, biarticular muscles activation shows to be more efficient, since they activate more than one joint at the same time. Generally, greater running economy was found to be related to better neuromuscular control, mostly during the ground contact phase.
Practical future applications
Since there are quite a few contributing factors to enhanced running economy, the applicable question would be how voluntary are they? Can we recruit neurological signals to preactivate the kinetic chain in a timely manner, especially during ground contact time?
Hereditary biomechanics might also pose a favorable distinction between levels of economy in trained runners; this topic has not been widely researched. It was found that genetics plays a role in biomehcanic regulations of some distal tendons[xii] and it might be useful to study the variables in relation to predisposed genetics in runners.
Applying this knowledge to pre / hab, or reducing risk of injuries as a result of more controlled spatiotemporal changes would be beneficial to virtually all populations of runners, from recreational to elite.
[i] Tam, N., Tucker, R., Santos-Concejero, J., Prins, D., & Lamberts, R. P. (2019). Running Economy: Neuromuscular and Joint-Stiffness Contributions in Trained Runners. International Journal of Sports Physiology & Performance, 14(1), 16–22
[ii] TEMPLE, C., LIND, E., VAN LANGEN, D., TRUE, L., HUPMAN, S., & HOKANSON, J. F. (2017). Run Economy on a Normal and Lower Body Positive Pressure Treadmill. International Journal of Exercise Science, 10(5), 774–781
[iii] Williams, K. R., & Cavanagh, P. R. (1987). Relationship between distance running mechanics, running economy, and performance. Journal of Applied Physiology, 63(3), 1236-1245.
[iv] Tam, N., Tucker, R., Santos-Concejero, J., Prins, D., & Lamberts, R. P. (2019). Running Economy: Neuromuscular and Joint-Stiffness Contributions in Trained Runners. International Journal of Sports Physiology & Performance, 14(1), 16–22
[v] Santos-Concejero, J., Granados, C., Irazusta, J., Bidaurrazaga-Letona, I., Zabala-Lili, J., Tam, N., & Gil, S. M. (2013). Differences in Ground Contact Time Explain the Less Efficient Running Economy in North African Runners. Biology of Sport, 30(3), 181–187
[vi] Average 10k Pace by Age Group and Sex, taken from http://www.pace-calculator.com/10k-pace-comparison.php access date April 11th, 2019
[vii] Dugan, S. A., & Bhat, K. P. (2005). Biomechanics and analysis of running gait. Physical Medicine and Rehabilitation Clinics, 16(3), 603-621.
[viii] Biel, Andrew. (1997) Trail guide to the body :how to locate muscles, bones and more Boulder, CO : Andrew Biel, p. 296-328
[ix] Masi, A. T., Nair, K., Evans, T., & Ghandour, Y. (2010). Clinical, biomechanical, and physiological translational interpretations of human resting myofascial tone or tension. International journal of therapeutic massage & bodywork, 3(4), 16.
[x] Kyröläinen, H., Belli, A., & Komi, P. V. (2001). Biomechanical factors affecting running economy. Medicine & Science in Sports & Exercise, 33(8), 1330-1337.
[xi] Black, M. I., Handsaker, J. C., Allen, S. J., Forrester, S. E., & Folland, J. P. (2018). Is There an Optimal Speed for Economical Running?. International journal of sports physiology and performance, 13(1), 75-81.
[xii] Wang, V. M., Banack, T. M., Tsai, C. W., Flatow, E. L., & Jepsen, K. J. (2006). Variability in tendon and knee joint biomechanics among inbred mouse strains. Journal of orthopaedic research, 24(6), 1200-1207.