Running economy (RE) a complex, multifactorial concept that represents the sum of metabolic, cardiorespiratory, biomechanical and neuromuscular efficiency during running.[1]: 33 [2][3] Oxygen consumption (VO2) is the most commonly used method for measuring running economy, as the exchange of gases in the body, specifically oxygen and carbon dioxide, closely reflects energy metabolism. Those who are able to consume less oxygen while running at a given velocity are said to have a better running economy. However, straightforward oxygen usage does not account for whether the body is metabolising lipids or carbohydrates, which produce different amounts of energy per unit of oxygen; as such, accurate measurements of running economy must use O2 and CO2 data to estimate the calorific content of the substrate that the oxygen is being used to respire.[4]
In distance running, an athlete may attempt to improve performance through training designed to improve running economy. Running economy has been found to be a good predictor of race performance; it has been found to be a stronger correlate of performance than maximal oxygen uptake (VO2 max) in trained runners with the same values.[5]
The idea of running economy is increasingly used to understand performance, as new technology can drastically lower running times over marathon distances, independently of physiology or even training. Factors affecting running economy include a runner’s biology, training regimens, equipment, and environment.
Measurement and values
editMeasurement
editRunning Economy is calculated by measuring VO₂ while running on a treadmill at various constant speeds for anywhere between three and fifteen minutes. VO₂ is the amount of oxygen consumed in milliliters over one minute and normalized by kilogram of body weight. To compare running economies between individuals, VO₂ is interpolated to common running velocities while also quantifying how much oxygen is needed to run one kilometer relative to body mass.[6] A lower value of running economy demonstrates better running efficiency and provides a good predictor for race performance.[7] A new method for measuring such concepts can be found with the help of the use of wireless foot-worn inertial sensors together with dedicated signal processing algorithms.[8][9]
Values of running economy
edit| Male mean (range) | Female mean (range) | ||||
| Runner classification | Speed (km/h) | Running economy (ml/kg/min) | VO 2 max (ml/kg/min) | Running economy (ml/kg/min) | VO 2 max (ml/kg/min) |
| Recreational | 14 | 47.4 (46.0–49.5) | 54.2 (51.0–57.8) | 47.3 (40.1–51.9) | 49.7 (45.2–54.1) |
| Moderately Trained | 14 | 46.8 (42.0–55.5) | 62.2 (56.6–69.1) | 47.9 (41.3–53.5) | 55.8 (50.5–59.4) |
| Highly Trained | 14 | 45.0 (32.4–56.5) | 70.8 (65.3–80.2) | 48.3 (39.0–56.7) | 61.7 (56.2–72.3) |
| Elite | 14 | 39.9 (36.1–44.5) | 75.4 (68.2–84.1) | 41.9 (38.7–46.9) | 66.6 (61.1–74.2) |
Factors affecting running economy
editIn The Lore of Running, Tim Noakes, a professor of exercise and sports science at the University of Cape Town, and also recreational runner, describes a number of variables that may affect running economy: vertical motion while running, the ability of the muscles to absorb energy during the shock of landing and transfer it to push-off, biomechanical factors, technique and type of activity, fitness and training, age, fatigue, gender, race, weight of clothing and shoes, and environmental conditions.[10]
Various studies have shown marathon runners to be more economical than middle distance runners and sprinters at speeds of 6–12 miles per hour (10–19 kilometers per hour).[11] At those speeds, film analysis has shown that sprinters and middle distance have more vertical motion than marathoners.[11]
Anthropometry
editRunning economy also depends on many innate characteristics with some body characteristics naturally giving runners an advantage. Some of these include height, limb length, and body mass distribution in certain areas of the body.
Limbs are a greater distance from a person’s center of mass, so they have greater rotational inertia compared to the rest of the body. As a result, limbs require more energy to move, so their morphology plays a role in running economy. In the legs, an increased weight in the feet relates to running economy since they are located most distally from the hips, slightly smaller than average feet are ideal for optimizing running economy.[6][5] This is also why shoe choice affects running economy. Weight carried in the thighs also plays a role with weight distributed closer to the hip joint, but does affect running economy as much as foot morphology. In one study, weights were added to the runners’ feet and thighs and they found that VO₂ consumption increased twice as much in trials with weights on feet compared to thighs. While the distribution of mass in limbs has been correlated to running economy, there is no consensus on whether or not limb length is a factor.[6]
An ideal body for optimal running economy would include height slightly smaller than average for males and slightly greater for females, low body fat percentage, leg mass distributed closer to the hip joint, and a narrow pelvis with smaller than average feet.[5] It has also been shown that there might be an inverse relationship between body weight and running economy. However this relationship is small, as the energy used in running is similar among people of different sizes. It’s also possible that this relation has nothing to do with body mass and could be caused by inter-individual differences in physique.[6]
Physiology
editThere are many physiological conditions that can affect running economy including maximal oxygen uptake, metabolic factors, tendon length, and ventilation. Running economy has also been observed to decrease towards the end of races while core temperature, heart rate, ventilation, and lactic acid increase. Therefore, training to decrease those factors could improve running economy.[5]
Metabolic energy is the amount of energy (ATP) that the body can produce from oxygen intake and nutrients available in the body. Factors that affect metabolism would be important for improved running economy so as to efficiently utilize the body’s resources. Because oxygen is necessary for aerobic respiration, the higher VO₂ max a runner has, the longer they will be able to run without going into anaerobic respiration and accumulate lactic acid buildup.[5] It is also preferable that a runner’s body can burn fat as an energy source under intense work loads, in addition to carbohydrates. Fat takes more steps to metabolize than carbohydrates, so using them as an energy source is more expensive, but they contain more energy per molecule.[6]
When running, the Achilles tendon becomes stretched by flexion of the foot and stores some of that energy as elastic energy. Studies have shown that utilization of this elastic energy has a medium to large impact on reducing running energy. Energy stored in the tendon depends on how much the tendon is stretched and its internal properties. A shorter Achilles tendon moment arm length (the length between the tendon and force stretching it) will produce more energy, similar to how tightness in muscles stores and releases elastic energy.[6]
Training
editRunning economy is often used as a measure of an endurance runners performance, so there have been many different methods of improving it studied. One drawback of these studies is that participants are typically not elite athletes, who have difficulty improving running economy significantly. Other criticisms of these studies include small sample size, too few measurements to account for intra-individual fluctuations, and other factors that affect running economy.[5] Regardless, studies have been published examining how methods such as plyometrics, strength, or endurance training affect participants. There have also been studies into how environmental factors such as altitude training and heat training affect runners.
Plyometric training has been observed to increase the amount of force that muscles can generate in a short interval of time. In one study, plyometric training led to faster ten kilometer race times, despite decreasing the total amount of distance run in training.[12] Because this type of training does not improve VO₂ max its success has been attributed to an increased tension in the muscles and tendons. An increased stiffness in those areas allows for greater efficiency in using elastic energy stored when they become stretched, allowing for a shorter impact time with the ground.[13][5]
One of the most common approaches to training for improving running economy is strength training. One study compared endurance training and a mix of endurance and strength training and found that while the mixed group had a considerably lower VO₂ their running economies actually increased.[2] The two main reasons attributed to this increase are adaptations in the nervous system and a change in the type of muscle fibers. Heavy-load strength training has been shown to increase the amount of motor neurons activated when a muscle is contracted, producing a greater force. This reason is most commonly attributed because strength training is often associated with hypertrophy, causing an increase in muscle size, which would be disadvantageous for running economy.[13] Strength training also causes muscles to undergo a change from fast twitch fibers to slow twitch fibers, which are more immune to fatigue.[13]
Studies have also been conducted to observe how environmental factors affect training. At high altitudes, metabolic erythropoietin increases the production of red blood cells to compensate for the lack of oxygen.[14] Altitude exposure also demonstrates measurable differences in metabolic activity in muscles.[2] Studies have shown that running economy improves considerably when training/sleeping at high altitudes and competing near sea level. Heat training has also proved to be effective, with an increased core temperature improving working efficiency of muscles. While an increased core temperature is beneficial to the muscles, a lower core temperature is preferred. When moving back to a normal temperature after training at higher temperatures, runners display a lower core temperature as well as heart rate.[2]
Biomechanics
editStride length, body kinematics, kinetics, and elastic energy are biomechanical factors associated with improved running economy.[2] The natural stride length of a trained athlete is related to a better running economy rather than any specific adjustments. Body kinematics encompass a variety of movement parameters associated with a better running economy.[13]
A runner with a better running economy has a relatively low amplitude of their center of mass, increased swing of the lower legs during a stride (decreased angle of the back of their knee), and increased angular velocity of plantar flexion during push-off, but has a reduced range of movement during plantar flexion.[2]
Other biomechanical factors associated with better running economy includes faster rotation of the shoulders, limiting of arm motion to moderate motion, a greater angular movement of the hips and shoulders with respect to the transverse plane of the runner, and lower peak levels of force on the ground.[2]
Flexibility of lower limb and torso in trained athletes improves running economy at all speeds through increased range of movement in the hips. Conversely, some studies have found that reduced flexibility in the calf and hip regions improve running economy by reducing the need for further muscle stabilization. Similar to a more tightly wound spring, less flexible muscles have increased energy storage and return of elastic energy.[2]
Shoes
editLightweight running shoes (<440g per pair) have been shown to have a statistical improvement upon running economy.[15] However, between barefoot running and lightweight shoes, there is no demonstrable differences.[15][16][13]
Cushioning has also been shown to reduce oxygen uptake and therefore running economy by providing an elastic energy storage of the downward force.[2] The shoe cushion itself needs to be of an optimal ‘spring rate’ in order to beneficially complement the muscle movements and forces.
Recent research has shown that the addition of a carbon-fiber plate in the midsole of a shoe coupled with a springy foam benefits running economy by reducing negative work done by the metatarsophalangeal joint.[17]
Environmental conditions
editTraining in warm temperatures increases core temperature which has been shown to improve running economy by improving the working efficiency of muscles. This creates a lasting effect when running at lower temperatures in which a relatively lower core temperatures can be achieved. A lower core temperature is associated with reduced increases in breathing, sweating and circulation at aerobic intensity, thereby increasing overall energy efficiency and improving running economy.[2][clarification needed]
Running economy in the media
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Breaking2 Project
editThe Breaking2 project was an event put on by Nike to break the marathon sub two hour barrier. The event utilized running economy in order to identify and improve factors that would aid in accomplishing the feat. The three runners included Lelisa Desisa, Eliud Kipchoge, and Zersenay Tadese. Eliud Kipchoge won the race with a time of 2:00:25, but ultimately failed to run the marathon in under two hours.[18]
Many runners were screened for the event, and ultimately Lelisa Desisa, Eliud Kipchoge, and Zersenay Tadese were chosen based on their potential. Physiological data was acquired from each runner along with their training regiments and personal records to estimate runner projections. To acquire data from each contestant, the Nike science team gave each runner GPS watches and heart rate monitors. Additionally, they visited each runner in their hometown to analyze hydration and nutrition strategies while monitoring skin temperature and sweat rates.[19][dead link]
The Breaking2 project team determined that the most critical parameter was the difference in skin temperature and internal body temperature, also known as temperature gradient.[19] Temperature gradient describes how rapidly temperature changes in relation to spatial location. In terms of running economy, a high difference between skin temperature and internal body temperature correlates with an improved running economy. In order to optimize this measurement for the athletes, the Breaking2 project was set to run over a three day window. This allowed for optimal weather conditions regarding temperature, wind, and cloud cover.[19] Moreover, the race took place in Northern Italy because of its wooded climate and racing routes with gradual curves. The Breaking2 project team also decided to focus on hydration and nutrition. In order to measure water loss, the runners were weighed before and after their training sessions, and muscle imaging was used to analyze the amount of sugar in the athlete's muscles. To combat the loss of water and sugar, the Nike team crafted sugar-water mixtures for each athlete. Slight modifications to the athletes diets were also tested, such as having Eliud Kipchoge eat beetroot bars instead of drinking beet juice.[19]
Ineos159 Challenge
editThe Ineos159 challenge took place in Vienna, Austria, and was run by Eliud Kipchoge in an attempt to run a marathon in under two hours. Eliud Kipchoge ran the race in 1:59:40[20] which translates to just under 2:50 min/km or 21.98 kmph.
Nutrition is a key aspect of running economy, and it was crucial to Kipchoge's success. Prior to the race, Eliud Kipchoge increased his carbohydrate intake in order to supply his muscles with fuel. Without carbohydrates, the body breaks down fats in a process called lipid metabolism. However, most elite runners do not have a high body fat percentage. During the race, he was consuming about 60 to 100 grams of carbohydrates every hour.[21] He did this by consuming a 500 mL drink consisting of 80 grams of carbohydrates. This was a change from his previous attempt at the Breaking2 project where he drank 50 mL drinks every few kilometers. Larger drinks supply fuel to the muscles sooner, but they have an increased chance of causing intestinal discomfort.[22]
Location and weather were also heavily considered because of their impact on running economy. Vienna was picked for multiple reasons. Firstly, the city is very flat which requires less energy expenditure. Secondly, the city is relatively close to sea level resulting in a higher concentration of oxygen in the air. The high oxygen level allows athletes to better perform aerobic exercises. Lastly, the race was run on a morning with low humidity and temperature levels. During the Breaking2 project, where Eliud Kipchoge failed to run a marathon in under two hours, there was unexpected rain. The extra moisture can increase the weight of the runner and reduce road traction.[22]
See also
editReferences
edit- ^ Daniels, Jack (2013). "Aerobic and training profiles". In Hanlon, Tom; Marty, Claire; Wolpert, Tyler (eds.). Daniels' Running Formula (3rd ed.). Champaign, IL: Human Kinetics. pp. 33–38. ISBN 978-1450431835.
The measure of energy expended while running aerobically at some submax speeds is a measure of running economy.
- ^ a b c d e f g h i j Saunders, Philo U; Pyne, David B; Telford, Richard D; Hawley, John A (2004). "Factors Affecting Running Economy in Trained Distance Runners". Sports Medicine. 34 (7): 465–485. doi:10.2165/00007256-200434070-00005. ISSN 0112-1642. PMID 15233599. S2CID 2323239.
- ^ Crowther, Greg (2001). "Tips on maximizing your running economy". Greg Crowther professional website. Retrieved 20 August 2014.
Measuring someone's running economy is equivalent to asking the question, "How far can this person run using a given amount of energy?" Energy use is usually reported in terms of oxygen consumption; the farther the person can run per unit of oxygen consumed – or, stated another way, the less oxygen he/she consumes in running a given distance – the more economical he/she is.
- ^ Shaw, Andrew J.; Ingham, Stephen A.; Folland, Jonathan P. (2014). "The Valid Measurement of Running Economy in Runners". Medicine & Science in Sports & Exercise. 46 (10): 1968–1973. doi:10.1249/MSS.0000000000000311. PMID 24561819.
- ^ a b c d e f g Saunders, Philo; Pyne, David; Telford, Richard; Hawley, John (2004). "Factor affecting running economy in trained distance runners" (PDF). Sports Medicine. 34 (7): 465–485. doi:10.2165/00007256-200434070-00005. PMID 15233599. S2CID 2323239. Archived from the original (PDF) on 21 August 2014. Retrieved 18 August 2014.
Running economy (RE) is typically defined as the energy demand for a given velocity of submaximal running, and is determined by measuring the steady-state consumption of oxygen (VO2) and the respiratory exchange ratio.
- ^ a b c d e f g Barnes, Kyle R; Kilding, Andrew E (27 March 2015). "Running economy: measurement, norms, and determining factors". Sports Medicine – Open. 1 (1): 8. doi:10.1186/s40798-015-0007-y. ISSN 2199-1170. PMC 4555089. PMID 27747844.
- ^ Kipp, Shalaya; Kram, Rodger; Hoogkamer, Wouter (11 February 2019). "Extrapolating Metabolic Savings in Running: Implications for Performance Predictions". Frontiers in Physiology. 10: 79. doi:10.3389/fphys.2019.00079. ISSN 1664-042X. PMC 6378703. PMID 30804807.
- ^ Muniz-Pardos B, Sutehall S, Gellaerts J, et al. Integration of Wearable Sensors Into the Evaluation of Running Economy and Foot Mechanics in Elite Runners. Curr Sports Med Rep. 2018;17(12):480–488. doi:10.1249/JSR.0000000000000550.
- ^ Falbriard M, Meyer F, Mariani B, et al. "Accurate estimation of runningtemporal parameters using foot-worn inertial sensors". Front Physiol. 2018;9:610.
- ^ Noakes, Tim. 2003. The Lore of Running. (4th ed.) Oxford University Press ISBN 0-87322-959-2
- ^ a b Kenney, W. Larry; Wilmore, Jack H.; Costill, David L. (2011) [1994]. "Energy Expenditure and Fatigue". Physiology of Sport and Exercise (5th ed.). Champaign, Illinois: Human Kinetics. p. 111. ISBN 978-0-7360-9409-2. Retrieved 12 May 2012.
- ^ Lum, Danny; Tan, Frankie; Pang, Joel; Barbosa, Tiago M. (1 September 2019). "Effects of intermittent sprint and plyometric training on endurance running performance". Journal of Sport and Health Science. 8 (5): 471–477. doi:10.1016/j.jshs.2016.08.005. ISSN 2095-2546. PMC 6742614. PMID 31534822.
- ^ a b c d e Barnes, Kyle R.; Kilding, Andrew E. (8 August 2016). "Strategies to Improve Running Economy". Sports Medicine. 45 (1): 37–56. doi:10.1007/s40279-014-0246-y. ISSN 1179-2035. PMID 25164465. S2CID 207493323.
- ^ Płoszczyca, Kamila; Langfort, Józef; Czuba, Miłosz (2018). "The Effects of Altitude Training on Erythropoietic Response and Hematological Variables in Adult Athletes: A Narrative Review". Frontiers in Physiology. 9: 375. doi:10.3389/fphys.2018.00375. ISSN 1664-042X. PMC 5904371. PMID 29695978.
- ^ a b Fuller, Joel T.; Bellenger, Clint R.; Thewlis, Dominic; Tsiros, Margarita D.; Buckley, Jonathan D. (1 March 2015). "The Effect of Footwear on Running Performance and Running Economy in Distance Runners". Sports Medicine. 45 (3): 411–422. doi:10.1007/s40279-014-0283-6. ISSN 1179-2035. PMID 25404508. S2CID 24940517.
- ^ Cheung, R. T.; Ngai, S. P. (1 March 2016). "Effects of footwear on running economy in distance runners: A meta-analytical review". Journal of Science and Medicine in Sport. 19 (3): 260–266. doi:10.1016/j.jsams.2015.03.002. hdl:10397/26740. ISSN 1440-2440. PMID 25819704.
- ^ Hoogkamer, Wouter; Kipp, Shalaya; Kram, Rodger (1 January 2019). "The Biomechanics of Competitive Male Runners in Three Marathon Racing Shoes: A Randomized Crossover Study". Sports Medicine. 49 (1): 133–143. doi:10.1007/s40279-018-1024-z. ISSN 1179-2035. PMID 30460454. S2CID 53945282.
- ^ Breaking2 | 紀錄片特輯, retrieved 28 October 2019
- ^ a b c d "Ch 04 The Science". Nike.
- ^ INEOS. "Sub-Two Hour Marathon Challenge | INEOS 1:59 Challenge". www.ineos159challenge.com. Retrieved 8 November 2019.
- ^ King, A.J. (2018). "Carbohydrate dose influences liver and muscle glycogen oxidation and performance during prolonged exercise". Physiological Reports. 6 (1): e13555. doi:10.14814/phy2.13555. PMC 5789655. PMID 29333721.
- ^ a b Burgess, Matt (14 October 2019). "The incredible science behind Eliud Kipchoge's 1:59 marathon". Wired UK. ISSN 1357-0978. Retrieved 8 November 2019.