There are numerous factors, both genetic and adaptive, that can affect an athlete’s efficiency. When a non-athlete first begins a training program, there are significant neuromuscular adaptations that must occur to their most basic coordination patterns in order to lay the foundation for biomechanical efficiency. This efficiency, also known as “running economy,” is usually measured by the consumption of oxygen per kilometer run, per kilogram body weight. In other words, better running economy equates to a more efficient utilization and recycling of oxygen during a workout. There is a direct parallel between running economy and performance, in that the greater the running economy, the more efficient the runner, and the better the performance.
Running economy has been found to be a better predictor of performance than VO2max. In fact, when comparing runners with a similar VO2max, running economy can differ by as much as 30%, and substantially demarcates elite from trained recreational and untrained individuals. The intrinsic and extrinsic factors that may be modifiable will be discussed individually in order to gain a better understanding of the variables at play in an athlete’s running economy.
Intrinsic Factors
Intrinsic factors consist of fundamental anatomical movement patterns and their corresponding physics in application, which collectively produce a specific performance outcome. Typically, they are trainable up to the athlete’s genetically predisposed limits of athleticism, through experience and careful program design.
Spatiotemporal Factors: The Gait Cycle
Running velocity can be thought of as the product of stride frequency (cadence) and stride length. Increasing either one of these can lead to improvements in speed. Runners will adopt an innate frequency and stride length based on anthropomorphic factors such as height and weight, in a process called self-optimization; this subconscious tuning leads to near optimal efficiency for a given runner. This self-optimized frequency and stride length often differs from mathematical optimums by 3% in each category, leading researchers to believe that there is a range of optimum in which a runner can perform without compromising running economy. For example, the optimal range for stride length would be from the runner’s preferred stride length to minus 3% of the preferred. This range applies to well-trained runners, but be cautious of generalizing this to a novice athlete, as self-optimization seems to occur mainly with experience.
Experienced runners seem to self-optimize their stride frequency and length for optimal efficiency. Share on XVertical oscillation is another spatiotemporal factor that can be altered to improve efficiency. This parameter is a measure of the vertical displacement, or “bounce,” that occurs within a runner’s stride. Vertical oscillation tends to increase with fatigue and decrease when an athlete is running barefoot or with improved running economy. Theoretically, reducing vertical displacement improves running economy by attenuating the metabolic cost related to the supported body weight and reducing work against gravity. The higher the bounce in a runner’s stride, the more impact that needs to be absorbed with each landing foot. This can be costly over the long run, resulting in unnecessary fatigue. Therefore, encourage your runners to minimize vertical oscillation in their strides.
Ground contact time is a final factor in this category, and is highly debated in the field. Some studies say that short ground contacts are metabolically costly due to the high force production and requisite recruitment of expensive fast-twitch muscle fibers. Other studies have said the opposite: that long contact times are more metabolically expensive due to the lengthened “braking,” or deceleration, phase. What is true is that decreasing speed during the contact phase is not desirable. Therefore, regardless of contact time, deceleration is the least economical factor in this discussion.
Individuals with a rearfoot strike often exhibit longer ground contact times. More importantly, they decelerate with each stance phase, which can greatly affect running economy. The biggest determinant of metabolic cost is the distance ahead of the hip that the foot lands when initial contact with the ground is made. Ideally, the foot contacts the ground directly under the hip, and not out in front, for the most economical return of energy.
Kinematics: Movement Patterns
Many kinematic factors have been studied as potentially limiting factors in a runner’s overall economy. Cross comparison studies have found the following to be beneficial in improving kinematic efficiency:
- Greater plantarflexion velocity
- Greater horizontal heel velocity at initial contact
- Greater maximal thigh extension angle with the vertical
- Greater knee flexion during stance
- Reduced knee range of motion during stance
- Reduced peak hip flexion during braking
- Slower knee flexion velocity during swing
- Greater dorsiflexion during stance
- Slower dorsiflexion velocity during stance
- Greater shank angle at initial contact
We can examine leg-extension at toe-off, stride angle, and foot strike patterns more closely because they’re the parameters with the most supporting evidence. Reducing leg extension at toe-off can be accomplished by either one or a combination of reducing plantarflexion and decreasing knee extension as the runner pushes off the ground. This error can be seen most often in runners that exhibit an exaggerated reach behind the body with each stride. The leg extensor muscles can function closer to optimal when some tension remains in the slight flexion of the hip and knee joint at the end of this phase. This partial flexion also means that less energy will be required to move the leg into the swing phase of full flexion by lowering the moment of inertia.
Stride angle is a relatively new research topic, defined as the angle of the parable tangent of the center of mass at toe-off. Larger stride angles have been shown to lower VO2 at a given velocity, by decreasing stride length or increasing swing time, which makes for more efficient recycling of oxygen at a given pace. The trade-off of increasing swing time is often an increased vertical displacement, so it’s important to consider multiple factors when assessing an athlete for these inefficiencies.
Finally, according to empirical evidence, the effect of foot strike on running economy may be negligible with the following exception. Evidence surrounding optimal foot strike patterns shows that habitual forefoot strikers lose no efficiency when switching to a rearfoot strike; however, habitual rearfoot strikers show significantly worse economy when adopting a forefoot strike at slow (<3m/s) and medium (3.1-3.9m/s) speeds. A runner’s primary foot strike pattern should remain consistent, especially in the case of heel strikers, in order to maintain optimal efficiency.
Kinetics: The Forces That Cause Motion
The kinetic force that results in movement is the summation of multiple component forces such as deceleration (braking) plus acceleration (propulsion). Ground reactive force (GRF) is measured in three planes of motion: anterior-posterior, medial-lateral, and vertical. It is most ideal to have a high anterior-posterior propulsive force, low anterior-posterior braking force, and low medial-lateral and vertical forces in order to be most economical. In addition, changing the kinematic joint angles has been shown to reduce muscular strain during force generation, thereby improving economy.
The cost of force production has been reevaluated many times within the research, but the synergistic task-by-task approach is the most accepted of late. This theory proposes that 80% of metabolic cost can be attributed to body weight support and forward propulsive forces, 7% to leg swing, 2% to lateral balance, and 11% to inexplicable costs such as braking forces, ventilation, and cardiac work. See Figure 1 for a graphic representation.
The magnitude of the GRF has a linear relationship with the vertical displacement of the runner. Using the spring-mass model, a spring’s stiffness can be calculated as the ratio of deformation (vertical displacement) to the vertical GRF; in the case of a runner, this number represents the stiffness of the entire musculoskeletal system. Leg stiffness is the ratio of maximal vertical force to maximal leg spring compression, and greater leg stiffness has been associated with a better running economy based on stretch-shortening principles on a cellular level.
Numerous extrinsic factors can affect leg stiffness. For example, exertional fatigue, increased surface compliance, and cushioned footwear all decrease stiffness and GRF, resulting in an attenuation of running economy. There are various methods to improve muscle tendon stiffness, with the most notable being plyometric training. Neuromuscular training and activation plays a pivotal role in stiffness as well.
Neuromuscular Activation and Recruitment
The creation of optimal muscle recruitment patterns is essential for developing the most efficient mechanics possible, thereby conserving the greatest amount of energy per stride. Well-trained advanced runners are known to have extremely refined muscle recruitment patterns as compared to novice athletes. Greater muscular activation in the lower limbs has been correlated to an increased VO2 at a given velocity, which consequently makes it detrimental to running economy. When more muscle fibers are recruited, there is a greater oxygen demand in those muscles, which increases the metabolic cost and lowers efficiency. Novice athletes have greater neuromuscular activation but, with experience, this process fine-tunes almost automatically to a more precise and ideal recruitment pattern.
Preactivation, also known as muscle tuning, is a prerequisite to ground contact with the potential to enhance GRFs via the stretch-shortening cycle. Simultaneous coactivation of agonist and antagonist muscle groups such as the quadriceps and hamstrings has been found to impair running economy. This is simply due to the fact that one muscle group cannot work as efficiently when the other is inhibiting its full activation with an opposing movement. A degree of relaxation is necessary, though some coactivation is also requisite to keep the leg from collapsing.
Extrinsic Factors
Running shoes and surface compliance are two of the main factors that affect running economy in the extrinsic category. There appears to be an optimal level of cushioning that is conducive to efficiency. Studies have shown that shoes with 10mm of cushioning tend to be more beneficial for running economy than either 0mm or 20mm of surface cushioning. Furthermore, running on grass is more economical than sand, based on the stifling of mechanical work on the latter surface.
Optimal level of cushioning in running shoes & surfaces is necessary for the best running economy. Share on XA firmer terrain enhances the ability to generate more energetic return, and a firm surface with some compliance such as grass can give an even greater return due to the elastic rebound properties it possesses. By the same token, softer shoes lose more energy during the stance phase than a stiffer, motion-controlled shoe. Shoes with more forefoot flexibility allow for greater propulsive forces to be generated, and reduce the strain on the gastrocnemius muscle during slow-speed running (<3m/s). The data shows that a shoe with a medium level of cushioning and flexibility may be ideal for maximizing return and efficiency. Trunk and upper limb biomechanics are less researched aspects of form, though unnatural or inconsistent movement patterns can clearly alter the balance of lower limb mechanics, thus reducing economy. In studies where the arm swing was suppressed, a decrease in peak vertical force and increase in knee and hip flexion angles were observed—both caused a slackening in muscle stiffness. Altering arm swing mechanics through training can prove to be more detrimental than simply allowing the natural balance to develop over time.
Developing Economy Through Training
Although no long-term studies have been conducted regarding the effect of training strategies on running economy, short-term interventions of 3-12 weeks are well supported. A study involving trained runners with poor economy found that spatiotemporal factors of running gait could be trained and improved after only three weeks of audio feedback. Four-week interventions utilizing minimalist footwear have shown promise in improving running economy, mostly by creating a more anterior footstrike and strengthening muscle-tendon stiffness.
When researched in the literature, popular acclaimed running techniques such as Pose, Chi, and midstance-to-midstance running have been shown to neither improve nor worsen efficiency. There is simply no evidentiary support for the claim that any of them improve running economy. Their implementation failure lies in the lack of specificity in targeting biomechanical factors, and/or targeting too many at the same time.
Anthropomorphic factors also play a role in how altering biomechanics may affect the individual. For example, asking an athlete with long legs to decrease their stride length results in increases in VO2 and decreases in economy; the same is true when asking an athlete with shorter legs to increase their stride length. More research is needed in this area to determine how best to customize the optimal stride range based on anthropomorphic qualities.
Future studies investigating the effects of longitudinal interventions will be helpful in drawing more reliable conclusions regarding the modifiable factors of running economy. What is clear is that many intrinsic spatiotemporal, kinetic, kinematic, and neuromuscular factors, as well as extrinsic factors, are at play collectively, and they all tie in to performance-related outcomes. Optimizing one or many factors can produce positive training effects in both trained and untrained athletes, and performance improvements will be quick to follow.
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References
- Bonacci, J., Chapman, A., Blanch, P., & Vicenzino, B. (2009). Neuromuscular adaptations to training injury and passive interventions. Sports Medicine, 39 (11), 903-921.
- Moore, I. S. (2016). Is there an economical running technique? A review of modifiable biomechanical factors affecting running economy. Sports Medicine, 46, 793-807.
