LEADING ART ICLE
Sports Medicine 12 (4): 228-236, 1991 0112-1642/91/0010-0228/$04.50/0 © Adis International Limited. All rights reserved. SP010S1
Feasibility of Improving Running Economy Stephen P. Bailey and Russell R. Pate Department of Exercise Science, University of South Carolina, Columbia, South Carolina, USA
Running economy is defined as the rate of oxygen consumption (V02) at a given submaximal running velocity (Cavanagh & Williams 1982). Several investigators have demonstrated that running economy is correlated with endurance performance (Bransford & Howley 1988; Conley & Krahenbuhl 1980; Conley et al. 1981, 1984; Daniels 1985; Morgan et al. 1989), particularly within groups that are homogeneous in terms of maximal aerobic power (V02max). The factors that have been shown to be associated with running economy are numerous and include heart rate, ventilation, V02max, gender, age, temperature, fatigue, training status, body and segmental mass distribution, stride length and various other biomechanical variables (Daniels 1985; Morgan et al. 1989b; Pate et al. 1989). While various factors have been found to affect running economy, relatively little research exists in reference to the potential for improving running economy and endurance performance via manipulation of these factors. An evaluation of the practicality of improving running economy through the manipulation of these variables could assist the athlete and coach who hope to optimise endurance performance by improving running economy. The purposes of this review are to discuss, from a theoretical perspective, how running economy might be improved in a given athlete through the manipulation of pertinent variables and to examine the feasibility of such manipulation.
1. Factors Affecting Running Economy Oxygen cost for a given external workload is dependent on both the energy (A TP) needed to overcome the external resistance and the energy used when producing the former (Winter 1979). Throughout the following discussion, the energy needed to overcome external resistance will be referred to as 'external energy', and the energy used in the production of external energy will be referred to as 'internal energy'. Consequently oxygen cost at a given submaximal running velocity could be decreased by reducing the demand for external energy, internal energy or both. Of the factors that have been shown to affect running economy, stride length and segmental mass distribution are examples of factors that determine the demand for external energy, while ventilation and heart rate are factors that contribute to the demand for internal energy. Table I provides a categorical listing of the variables that have been shown to affect running economy. This categorisation of variables is used primarily for organisation. The authors recognise that not all variables fall neatly into a single category and that some researchers may not agree with the specifics of the categorisation.
2. Internal Energy Demand and Running Economy As described above, internal energy is that associated with oxygen delivery to the working muscles, thermoregulation and substrate metabol-
Improving Running Economy
ism. When attempting to improve the efficiency of these mechanisms, the overall goal is to minimise, the amount of ATP needed by the whole body to support production of a given amount of ATP in the working muscles. Following is a discussion of those variables that have been shown to affect the internal energy requirement of running. Emphasis is placed on the potential for improving running economy by manipulation of these variables. 2.1 Delivery of Oxygen to the Working Muscles The 2 variables that play an integral role in the delivery of oxygen to the working muscles and that have been shown to be significantly related to running economy are heart rate (beats/min) and ventilation (L/min) [Pate et al. 1989]. In both cases a significant and positive relationship has been shown to exist between the variable and oxygen cost while running at 160 m/min (6 mph) [Pate et al. 1989]. That is, as oxygen cost increased (or running economy decreased), heart rate and ventilation increased. The work of ventilation has been shown to constitute 7 to 8% of the total oxygen cost of exercise (Milic-Emili et al. 1962). Consequently, manipulation of the amount of ventilatory work necessary at a given running velocity could alter overall runTable I. Categorisation of the factors that affect running economy. External energy Age Segmental mass distribution Stride length Biomechanical variables Internal energy Heart rate Ventilation Temperature Others V02max
Training status Fatigue Mood state
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ning economy. The differences in the ventilatory requirement for a given submaximal ~02 between trained and untrained individuals are well known. Endurance-trained subjects demand a lower VE at a standard absolute ~02 than do untrained subjects (Martin et al. 1979). At a given submaximal power output, endurance-trained subjects produce less lactate and have a higher blood pH. Consequently, the bicarbonate buffer system is less taxed and the volume of carbon dioxide that must be 'blown off is not as great in endurance-trained subjects. The advantage of a reduced ventilatory response in endurance-trained runners is obvious. The energy that is saved by a reduced ventilatory response may act to decrease whole body oxygen cost. Myocardial oxygen consumption also constitutes a significant fraction of whole body oxygen consumption during exercise. Kitamura and associates (1972) have shown myocardial oxygen cost during moderate exercise to be 1 to 2% of whole body ~02. As with ventilatory work, it appears that a reduction in myocardial oxygen consumption could result in a reduced whole body ~02 and, therefore, an improved running economy. Assuming that haemoglobin concentration, haematocrit and oxygen demand of the working muscles are constant, the rate at which blood is supplied to the working muscles and cardiac output would be constant at a given submaximal workload. Therefore, any reduction in myocardial oxygen consumption at a given external resistance would have to result from a more efficient combination of heart rate and stroke volume, specifically, a reduction in heart rate and an increase in stroke volume. Existing evidence demonstrates that, when cardiac output is held constant, myocardial oxygen cost can be reduced in isolated canine hearts when heart rate is significantly slowed (Tanaka et al. 1988). A reduction in heart rate from 200 to 75 beats/min resulted in a reduction in myocardial oxygen consumption of approximately 10 mlfmin/ loog myocardial tis~ue when cardiac output was maintained at 1.2 L/min. Extrapolation of this data to whole body ~02 in humans is at best tenuous; however, it appears safe to hypothesise that any
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realistic reduction in heart rate at a given external resistance would not result in a biologically significant reduction in whole body V02. For example, in the scenario provided above, a reduction of 20 beats/min in heart rate would only result in a reduction of 1.6 mljmin/ lOOg of myocardial tissue in myocardial oxygen consumption. This would only result in an 8 mljmin reduction in whole body oxygen consumption if the heart weighed 500g. Manipulation of heart rate, and its subsequent effect on whole body V02 while performing submaximal work, has been assessed in humans through the use of drugs that alter chronotropic status of the heart (i.e. ~-blockers). For example, Kalis and associates (1988) found subjects treated with propranolol to have significantly lower heart rates and submaximal oxygen consumption values (V02submax) while cycling at 40% OfV02max. The magnitudes of these reductions were approximately 35 beats/min and 0.1 L/min for heart rate and V02, respectively. The reduction in V02submax observed in these types of investigations should not, however, be interpreted to be an exclusive result of a reduction in heart rate. As the authors indicate, t12-blockade also acts to inhibit lipolysis leading to a greater reliance on carbohydrates for energy production. This effect in itself could act to reduce V02submax. Furthermore, it is also possible that t12-blockade can reduce ventilation which, as described above, could also act to reduce V02submax. The preceding discussion supports the conclusion that improvements in running economy could result from improved efficiency of key components of the system that delivers oxygen to the working muscles. However, much more experimentation must be completed before any conclusion as to the practicality of such manipulation and its effect on running economy can be made. It has been well documented that endurance training results in significantly lower heart rates and ventilation at a given submaximal workload. The specific effects of training on running economy will be discussed later in the review.
2.2 Thermoregulation The effects of temperature on running economy are complex. Different investigations have reported V02 submax to be increased, decreased, and unchanged by elevations in core temperature (Brooks et al. 1970, 1971; Dill 1965; Maron et al. 1976; Rowell et al. 1969; Saltin & Stenberg 1964). Those investigators who have found an increased V02submax with an increased core temperature cite increased energy requirements for peripheral circulation, increased sweat gland activity, hyperventilation, and reduced efficiency of muscle metabolism as possible mechanisms. Conversely, investigators reporting V02submax to be reduced or unchanged with an increase in core temperature believe that it is possible that the efficiency of muscle metabolism is improved (i.e. the amount of 02 needed to produce a given amount of ATP is reduced) as muscle temperature is increased. It is entirely possible that both phenomena operate and V02submax is reduced slightly as muscle temperature is moderately increased but eventually increases as the mechanisms involved in heat dissipation are activated to a greater extent. The economy of running in a heat stress environment should be improved by heat acclimatisation. Acclimatisation, accompanied by exercise training, can increase plasma volume up to 12%. Increased plasma volume assists in the maintenance of stroke volume and consequently minimises myocardial work in a heat stress environment. Further, an increased plasma volume improves sweating capacity and enables the body to tolerate greater internal heat production. 2.3 Substrate Utilisation As mentioned earlier, it may be possible to alter running economy by altering the type of fuel (i.e. carbohydrate or fat) used to produce energy. When carbohydrate is used for energy production 5.05 kcal of energy are produced for every litre of oxygen consumed, whereas when fat is used for energy metabolism 4.70 kcal of energy are produced for every litre of oxygen consumed (Brooks & Fahey 1985).
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Consequently, greater carbohydrate use during running at a given speed should be associated with lower oxygen cost. This type of manipulation can potentially be accomplished by either increasing the supply of carbohydrate to the working muscles or by minimising the availability of fatty acids to the muscles. Ingestion of carbohydrate during prolonged exercise has been shown to improve endurance performance and increase respiratory exchange ratio, indicating that more carbohydrate is being used for energy production. However, oxygen cost has been minimally reduced under such manipulations, indicating that ingestion of carbohydrate during prolonged exercise probably has little effect on running economy. This concept has been exemplified by Davis and associates (1988) who observed the changes in oxygen consumption and respiratory exchange ratio in subjects who consumed 275ml every 20 minutes of either a flavoured placebo, a 2.5% carbohydrate beverage or a 6% carbohydrate beverage during 2 hours of cycling at ~75% V02max. Over the 2-hour period, respiratory exchange ratio was significantly greater when the subjects consumed the 6% carbohydrate beverage, indicating that a significantly greater amount of carbohydrate was being used to produce the energy needed to perform the work. However, rate of oxygen consumption was similar under all 3 conditions.
3. External Energy and Running Economy Within the context of this review article, external energy is defined as the energy expended in overcoming an external resistance. Improvement of running economy can theoretically be achieved by reducing the amount of external energy needed to overcome a resistance. As detailed in table I, we believe that age, segmental mass distribution, stride length, and other biomechanical variables play a significant role in determining external energy demand.
3.1 Stride Length and Other Biomechanical Variables Manipulation of biomechanical variables may be the most realistic avenue through which running economy can be altered. The effects of stride length manipUlation on running economy are fairly well known. Hogberg (1952) was the first to document that stride length variation from that which was freely chosen by a runner resulted in an increase in submaximal oxygen consumption. Hogberg's investigation was replicated by Cavanagh and Williams (1982) with a larger sample size (n = 10). Consistent with Hogberg's results, Cavanagh and Williams found runners to be most economical at their freely chosen stride length and described overstriding to be less economical than understriding. The relationship between stride length and running economy appears to be consistent and predictable; however, it appears that experienced runners freely chose their optimal stride length. Consequently, efforts to improve running economy via stride length manipulation would probably be fruitless, unless the runner's freely chosen stride length is not economically optimal. Stride length and running economy have been shown to differ between experienced and novice runners, with experienced runners possessing longer stride lengths and greater running economy. Therefore, it can be hypothesised that with training a novice will develop a longer stride length and greater running economy than that observed at the onset of training. Bailey and Messier (1991), however, found that neither stride length nor running economy changed significantly over a 7-week training period in novice male runners. It may be that changes in stride length and running economy take several months, if not years to develop. Williams and Cavanagh (1987) conducted an extensive investigation of the relationships between running economy and a large array of biomechanical variables in trained runners. The results presented by these authors indicate that the most economical runners possessed a significantly lower force peak at heel strike, greater shank angle with vertical at heel strike, smaller maximal plan-
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tar flexion angle following toe off, greater forward trunk lean, and lower minimum velocity of a point on the knee during foot contact. Williams and Cavanagh (1987) also reported that 54% of the variation in running economy could be attributed to variation in biomechanical variables. The authors suggest that it may be possible to systematically vary aspects of an individual's running style with an ultimate goal to modify selected variables to a more desired level precipitating an improved running economy. With this hypothesis in mind, Messier and Cirillo (1989) implemented a verbal and visual feedback system in an effort to systematically alter running mechanics, and therefore running economy, in a group of novice female runners. Through the use of their system, the authors found that it was possible to significantly alter running mechanics in the desired fashion over a 5-week period. However, the improvement in running economy observed in the group subjected to experimental intervention was not significantly different from that observed in a control group that trained in a similar manner but received no verbal or visual feedback. It may be useful to implement a similar intervention with a group of trained runners to determine if changes in running mechanics can cause improvements in running economy independent of changes in training status. 3.2 Segmental Mass Distribution Segmental mass distribution is perhaps the most subtle of all the variables discussed in this review. Several investigations have described significant inverse relationships between body mass and running economy (Pate et al. 1989; Williams & Cavanagh 1986, 1987). These relationships have been proposed to result from individual differences in distribution of mass among limb segments (Cavanagh & Kram 1985). Furthermore, it has been hypothesised that a smaller individual possesses a relatively greater amount of his or her body mass in the extremities, and would thereby have to perform a relatively greater amount of work moving body segments during running than a larger indi-
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vidual (Myers & Steudel 1985). This hypothesis has been supported by several investigations which indicate that the increased oxygen cost of carrying an added load is greater when it is carried on an extremity than when it is carried on the trunk (Catlin & Dressendorf 1979; Cureton et al. 1978; Inman et al. 1981; Jones et al. 1984; Myers & Steudel 1985). Although the effects of segmental mass distribution on running economy have been described, avenues for improvement in running economy through changes in segmental mass distribution are not obvious. For example, it would appear to be completely illogical to advise an athlete to gain weight in his/her trunk in an effort to improve running economy. Such a manipulation could have a positive effect on weight distribution, but would negatively affect weight-relative V02max and distance running performance. Weight reduction from the extremities could have a positive effect on running economy; however, effective practical means to reach this end do not exist to our knowledge. 3.3 Age The relationship between age and running economy appears to be parabolic. Running economy has been shown to be lower in younger children than in older children or adults (Daniels & 01dridge 1971; Krahenbuhl et al. 1985, 1989; Leger & Mercier 1984; MacDougall et al. 1983). Furthermore improvements in distance running performance during adolescence have been shown to be more dependent on improvements in running economy than improvements in V02max (Krahenbuhl et al. 1989). These differences have been suggested to be due to variations in both internal and external energy. Internal energy demand may be greater in children due to higher basal metabolic rates and a greater reliance on lipolysis for energy production when compared to their older counterparts. In comparison external energy demand for a given resistance may be lower in adolescents due to greater leg lengths and stride lengths and lower body surface area to body mass ratios. The differences in running economy between
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younger and older adults are not as well defined; however, it appears that running economy is reduced with increasing age (Larish et al. 1987; Sidney & Shepard 1977; Waters et al. 1983). Reduced muscle elasticity and antagonistic muscle relaxation as a result of aging have been sited as possible mechanisms for this relationship. Both of these responses to aging may reduce the ability of skeletal muscles to store and use elastic energy during running, which would subsequently increase the amount of external energy needed to run at a given velocity. Consequently, the reduction in running economy seen with aging might be dampened through the maintenance of muscle elasticity; however, this has not yet been demonstrated experimentally.
4. Other Factors 4.1 ~02max The direct relationship between running economy and ~02max has not been well defined. Pate and colleagues (1989) have described the relationship between the two variables to be negative in nature. More specifically, the relationship between ~02max and running economy at 160 m/min (6 mph) was found to be significantly negative (p = 0.0001) [Pate et al. 1989]. In a somewhat similar vein, Pollock (1977) found ~02submax (at 4.5 and 5.4 m/sec) and ~02max to be significantly lower in elite marathoners than in elite middle-distance runners. The possible mechanisms underlying this negative relationship between running economy and ~02max are numerous. It is possible that a negative relationship between running economy and ~02max was observed because those runners who possessed high ~02max values were more accustomed to running at greater velocities than those used to assess running economy in the investigations described above. Consequently, runners with lower ~02max values may have trained more frequently at running velocities similar to those used in the above investigations and were more mechanically efficient at these velocities. It is also possible that individuals possessing greater ~02max values were more able to utilise fat for the pro-
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duction of similar amounts of energy. Since the amount of oxygen needed to produce a given amount of ATP is greater when fat is the fuel source as compared to carbohydrate or protein, oxygen cost for individuals better able to utilise fat for the production of energy would be greater. In addition, segmental mass distribution may have confounding effects on the relationship between running economy and ~02max. As described above, greater concentration of body mass in the trunk area appears to be advantageous in terms of running economy. Conversely, those individuals who possess greater percentages of their body mass in the arms and legs may be able to obtain higher ~02max values because a greater proportion of their lean muscle mass is active during running. Therefore, segmental mass distribution may have opposite effects on running economy and ~02max. 4.2 Training Status The most natural way to improve running economy would be through the alteration of training status. Several investigators believe that running economy is affected by training status; however, the relationship between the two is unclear. For example, middle and long distrance running programmes have been shown to have positive (Daniels et al. 1978a; Daniels & Oldridge 1971; Patton & Vogel 1977) and neutral (Daniels et al. 1978b; Petray & Krahenbuhl 1985; Wilcox & Bulbulian 1984) effects on running economy. The use of interval or high intensity training has had some success in improving running economy (Conley et al. 1981a, 1984; Sjodin et al. 1982). Improvements in running economy from this type of training have been attributed to alterations in running style and intracellular oxidative capacity. Improvement in running economy through the manipulation of training status may have potential, however, more research implementing several different training protocols must be completed before a conclusion can be made as to what is the best type of training for the improvement of running economy.
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4.3 Fatigue The onset of fatigue could potentially reduce running economy by increasing the demand for either external energy or internal energy. As glycogen is depleted from the working muscles, the reduction in respiratory exchange ratio due to the increase in free fatty acid oxidation could increase oxygen consumption. Martin and colleagues (1987), however, indicated that while respiratory exchange ratio and blood free fatty acid concentration were elevated I day after a hard training workout, no change in running economy was observed. It is also possible that alterations in running mechanics, which may occur as a result offatigue, can negatively effect running economy. Morgan et al. (1990) investigated this possibility by observing changes in running economy, respiratory exchange ratio, and several biomechanical variables in male distance runners on I, 2 or 4 days following an exhaustive treadmill run. Morgan's investigation again revealed that respiratory exchange ratio was significantly lower 1 and 2 days after the exhaustive exercise bout; however, variations in biomechanical variables and running economy were small. These investigations appear to indicate that fatigue, and the possible physiological and biomechanical pertubations that may be associated with it, have relatively little effect on running economy during subsequent exercise bouts. Further investigation is needed to determine if any of the consequences of fatigue significantly effect running economy within a single exercise bout. 4.4 Mood State Minimal research exists in reference to the psychological factors that may influence running economy. Recently, however, Williams et al. (1990) have investigated the effects of mood state on within subject variability in running economy. These authors found that a more positive mood state, as measured by the Profile of Mood States (POMS), was significantly correlated with greater running economy (r = 0.88). Furthermore, correlations determined between the 6 POMS subscales and run-
Sports Medicine 12 (4) 1991
ning economy indicated that tension held the strongest association (r = 0.81). The correlation between running economy and mood state described above may be the result ofa common underlying mechanism; however, these results do not indicate that a cause and effect relationship exists between the two. For example, mood state during exercise and running economy may be similarly affected by changes in heart rate, ventilation, running mechanics and substrate utilisation.
5. Can Running Economy be Improved? The purpose of this review was to discuss how running economy could be theoretically improved within an individual through the manipulation of factors that have been shown to be associated with running economy. The means of achieving this goal would be to reduce internal energy demand, external energy demand, or both at a given submaximal running velocity. Conceptually, internal energy demand can be reduced within an individual by reducing heart rate, lowering ventilation, and increasing the percentage of carbohydrates oxidised for energy production. Of these, it appears that manipulation of ventilation (by increasing tidal volume and reducing breathing rate) provides the only avenue through which running economy may be appreciably improVed. Internal energy demand while exercising in a heat stress environment can also be reduced within an individual by acclimatisation. Substantial improvements in running economy may be more likely to result from reduction of external energy requirements for a given running velocity. Such improvements would provide multiple benefits because internal energy demand would be affected as well. From the above discussion, it appears that external energy demand may be reduced within an individual by distributing a lower proportion of body mass in the extremities. While increasing the percentage of body mass in the trunk area may improve running economy, it is also likely that such manipulation would have adverse effects on weight-relative V02max and performance. In comparison, loss of mass in the extremities would
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Improving Running Economy
probably have a positive effect on running economy. However, to our knowledge there is no method for focusing weight loss exclusively in the extremities. Loss of muscle elasticity is believed to be a main mechanism through which running economy is reduced with aging. Consequently, maintenance of muscle elasticity may assist in the maintenance of running economy. Several biomechanical variables have shown to effect running economy including stride length, forward trunk lean, shank angle at heel strike, and maximal plantar flexion. Of these stride length has been most closely examined. Results from pertinent studies indicate that experienced runners freely choose a stride length that is optimal in terms of running economy. It is entirely possible that other biomechanical variables that have been found to effect running economy follow a similar pattern and that any manipulation within an individual will not result in an improved running economy. Alteration of training status may be the most fruitful avenue through which running economy may be improved. In particular, the use of high intensity interval training has produced positive results (Conley et al. 1981a, 1984; Sjodin et al. 1982). However, alterations in training status may precipitate changes in variables that both positively and negatively affect running economy. An enhanced training regimen may favourably change running economy by improving running style and intracellular oxidative capacity. Conversely, an enhanced training regimen could also reduce running economy by increasing mass distribution in the limbs and increasing V02max. A greater V02max may reduce running economy by increasing the percentage of fat oxidised for energy production at a given running speed. Lastly, running economy is apparently correlated with mood state. The question remains; can running economy be improved within an individual? The few direct attempts that have been made to improve running economy within a group of individuals have met with limited success. Most available evidence seems to indicate that relatively little improvement in running economy can be expected following conscious manipulation of factors that are associated
with running economy. However, manipulations of ventilation, segmental mass distribution, training status, and running style show some promise. Consequently, much more investigation of the relationships between these variables and running economy is needed before a definitive conclusion can be made concerning the feasibility of improving running economy within an individual.
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Dill D. Marathoner DeMar: physiological studies. Journal of the National Cancer Institute 35: 185-191, 1965 Hogberg P. How do stride length and stride frequency influence the energy-output during running? Arbeitsphysiologie 14: 437441, 1952 Inman VT, Ralston HJ, Todd B. Human walking, pp. 62-77, Williams and Wilkins, Baltimore, 1981 Jones BM, Toner M, Daniels W, Knapik J. The energy cost and heart rate response of trained and untrained subjects walking and running in shoes and boots. Ergonomics 27: 895-902, 1984 Kalis JK, Freund BJ, Joyner MJ, Jilka SM, Nittolo J, et al. Effect of ,6-blockade on the drift in 02 consumption during prolonged exercise. Journal of Applied Physiology 64: 753-758, 1988 Kitamura K, Jorgensen CR, Gobel FL, Taylor HL, Wang Y. Hemodynamic correlates of myocardial oxygen consumption during upright exercise. Journal of Applied Physiology 32: 516522, 1972 Krahenbuhl GS, Morgan DW, Pangrazi RP. Longitudinal changes in distance-running performance of young males. International Journal of Sports Medicine \0: 92-96, 1989 Krahenbuhl G, Skinner J, Kohrt W. Developmental aspects of maximal aerobic power in children. Exercise and Sport Sciences Review 13: 503-538, 1985 Larish D, Martin P, Mungiole M. Characteristic patterns of gait in the healthy old. Annals of the New York Academy of Sciences SIS: 18-32, 1987 Leger L, Mercier D. Gross energy cost of horizontal treadmill and track running. Sports Medicme I: 270-277, 1984 MacDougall J, Roche P, Bar-Or 0, Moroz J. Maximal aerobic capacity of Canadian school children: prediction based on agerelated oxygen cost of running. International Journal of Sports Medicine 4: 194-198, 1983 Maron M, Horvath S, Wilkerson J, Gliner J. Oxygen uptake measurements during competitive marathon running. Journal of Applied Physiology 40: 836-838, 1976 Martin BJ, Sparks KE, Zwillich CW, Weil JV. Low exercise ventilation in endurance athletes. Medicine and Science in Sports and Exercise 11: 181-185, 1979 Martin P, Femall B, Krahenbuhl G. The effect of workout intensity on running economy and mechanics. Abstract. Hong Kong Sports Medicine Conference, Hong Kong, 1987 Messier SP, Cirillo KJ. Effects of a verbal and visual feedback system on running technique, perceived exertion and running economy in female novice runners. Journal of Sports Sciences 7: 113-126, 1989 Millie-Emili G, Petit JM, Deroanne R. Mechanical work of breathing during exercise in trained and untrained subjects. Journal of Applied Physiology 17: 43-49, 1962 Morgan D, Baldini F, Marti\! P, Kohrt W. Ten km performance and predicted velocity at V02max among well trained runners. Medicine and Science in Sports and Exercise 21: 78-83, 1989a Morgan DW, Martin P, Baldini S, Krahenbuhl G. Effects of a prolonged maximal run on running economy and running mechanics. Medicine and Science in Sports and Exercise 22: 834840,1990 Morgan DW, Martin PE, Krahenbuhl GS. Factors affecting running economy. Sports Medicine 7: 310-330, 1989b
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Myers M, Stuedel K. Effect of limb mass and its distribution on the energetic cost of running. Journal of Experimental Biology 116: 363-373, 1985 Pate RR, Macera C, Bartoli W, Maney C. Physiological and anatomical correlates of running economy in habitual runners. Medicine and Science in Sports and Exercise 21 (Suppl. 2): S26,1989 Patton J, Vogel J. Cross-sectional and longitudinal evaluations of an endurance training program. Medicine and Science in Sports and Exercise 9: 100-\03, 1977 Petray C, Krahenbuhl G. Running training, instruction on running technique, and running economy. Research Quarterly for Exercise and Sport 56: 245-250, 1985 Pollock ML. Submaximal and maximal working capacity of elite distance runners. Part I: Cardiorespiratory aspects. Annals of the New York Academy of Sciences 301: 310-322,1977 Rowell L, Brengelmann G, Murray J, Kraning K, Kisumi F. Human metabolic response to hyperthermia during mild to maximal exercise. Journal of Applied physiology 26: 395-402, 1969 Saltin B, Stenberg J. Circulatory response to prolonged severe exercise. Journal of Applied Physiology 19: 833-838, 1964 Sidney K, Shepard R. Maximum testing of men and women in the seventh, eighth and ninth decades of life. Journal of Applied Physiology 43: 280-287, 1977 Sjodin B, Jacobs I, Svendanhag J. Changes in onset of blood lactate accumulation (OBLA) and muscle enzymes after training at OBLA. European Journal of Applied Physiology 49: 45-57, 1982 Tanaka N, Yasumara Y, Nozawa T, Futaki S, Uenishi M, et al. American Journal of Physiology 23: R933-R943, 1988 Waters R, Hislop H, Perry J, Thomas L, Campbell J. Comparative cost of walking in young and old adults. Journal of Orthopaedic Research I: 73-76, 1983 Wi\cox A, Bulbulian R. Changes in running economy relative to V02max during a cross-country season. Journal of Sports Medicine and Physical Fitness 24: 321-326, 1984 Williams K, Cavanagh P. Relationship betwcen distance running mechanics, running economy, and performance. Journal of Applied Physiology 63: 1236-1245, 1987 Williams KR, Cavanagh PRo Biomechanical correlates with running economy in elite distance runners. Proceedings of the North American Congress on Biomechanics, Montreal, pp. 287288, 1986 Williams TJ, Krahenbuhl GS, Morgan DW. The relationship between the profile of mood states and running economy. Abstract. Medicine and Science in Sports and Exercise 22 (Suppl. 2): S92, 1990 Winter DA. Calculation and interpretation of mechanical energy of movement. Exercise and Sport Science Review 46: 79-83, 1979
Correspondence and reprints: Stephen P. Bailey. Department of Exercise Science, University of South Carolina, Columbia, SC 29208, USA.
Sports Medicine 12 (4): 228-236, 1991 0112-1642/91/0010-0228/$04.50/0 © Adis International Limited. All rights reserved. SP010S1
Feasibility of Improving Running Economy Stephen P. Bailey and Russell R. Pate Department of Exercise Science, University of South Carolina, Columbia, South Carolina, USA
Running economy is defined as the rate of oxygen consumption (V02) at a given submaximal running velocity (Cavanagh & Williams 1982). Several investigators have demonstrated that running economy is correlated with endurance performance (Bransford & Howley 1988; Conley & Krahenbuhl 1980; Conley et al. 1981, 1984; Daniels 1985; Morgan et al. 1989), particularly within groups that are homogeneous in terms of maximal aerobic power (V02max). The factors that have been shown to be associated with running economy are numerous and include heart rate, ventilation, V02max, gender, age, temperature, fatigue, training status, body and segmental mass distribution, stride length and various other biomechanical variables (Daniels 1985; Morgan et al. 1989b; Pate et al. 1989). While various factors have been found to affect running economy, relatively little research exists in reference to the potential for improving running economy and endurance performance via manipulation of these factors. An evaluation of the practicality of improving running economy through the manipulation of these variables could assist the athlete and coach who hope to optimise endurance performance by improving running economy. The purposes of this review are to discuss, from a theoretical perspective, how running economy might be improved in a given athlete through the manipulation of pertinent variables and to examine the feasibility of such manipulation.
1. Factors Affecting Running Economy Oxygen cost for a given external workload is dependent on both the energy (A TP) needed to overcome the external resistance and the energy used when producing the former (Winter 1979). Throughout the following discussion, the energy needed to overcome external resistance will be referred to as 'external energy', and the energy used in the production of external energy will be referred to as 'internal energy'. Consequently oxygen cost at a given submaximal running velocity could be decreased by reducing the demand for external energy, internal energy or both. Of the factors that have been shown to affect running economy, stride length and segmental mass distribution are examples of factors that determine the demand for external energy, while ventilation and heart rate are factors that contribute to the demand for internal energy. Table I provides a categorical listing of the variables that have been shown to affect running economy. This categorisation of variables is used primarily for organisation. The authors recognise that not all variables fall neatly into a single category and that some researchers may not agree with the specifics of the categorisation.
2. Internal Energy Demand and Running Economy As described above, internal energy is that associated with oxygen delivery to the working muscles, thermoregulation and substrate metabol-
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ism. When attempting to improve the efficiency of these mechanisms, the overall goal is to minimise, the amount of ATP needed by the whole body to support production of a given amount of ATP in the working muscles. Following is a discussion of those variables that have been shown to affect the internal energy requirement of running. Emphasis is placed on the potential for improving running economy by manipulation of these variables. 2.1 Delivery of Oxygen to the Working Muscles The 2 variables that play an integral role in the delivery of oxygen to the working muscles and that have been shown to be significantly related to running economy are heart rate (beats/min) and ventilation (L/min) [Pate et al. 1989]. In both cases a significant and positive relationship has been shown to exist between the variable and oxygen cost while running at 160 m/min (6 mph) [Pate et al. 1989]. That is, as oxygen cost increased (or running economy decreased), heart rate and ventilation increased. The work of ventilation has been shown to constitute 7 to 8% of the total oxygen cost of exercise (Milic-Emili et al. 1962). Consequently, manipulation of the amount of ventilatory work necessary at a given running velocity could alter overall runTable I. Categorisation of the factors that affect running economy. External energy Age Segmental mass distribution Stride length Biomechanical variables Internal energy Heart rate Ventilation Temperature Others V02max
Training status Fatigue Mood state
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ning economy. The differences in the ventilatory requirement for a given submaximal ~02 between trained and untrained individuals are well known. Endurance-trained subjects demand a lower VE at a standard absolute ~02 than do untrained subjects (Martin et al. 1979). At a given submaximal power output, endurance-trained subjects produce less lactate and have a higher blood pH. Consequently, the bicarbonate buffer system is less taxed and the volume of carbon dioxide that must be 'blown off is not as great in endurance-trained subjects. The advantage of a reduced ventilatory response in endurance-trained runners is obvious. The energy that is saved by a reduced ventilatory response may act to decrease whole body oxygen cost. Myocardial oxygen consumption also constitutes a significant fraction of whole body oxygen consumption during exercise. Kitamura and associates (1972) have shown myocardial oxygen cost during moderate exercise to be 1 to 2% of whole body ~02. As with ventilatory work, it appears that a reduction in myocardial oxygen consumption could result in a reduced whole body ~02 and, therefore, an improved running economy. Assuming that haemoglobin concentration, haematocrit and oxygen demand of the working muscles are constant, the rate at which blood is supplied to the working muscles and cardiac output would be constant at a given submaximal workload. Therefore, any reduction in myocardial oxygen consumption at a given external resistance would have to result from a more efficient combination of heart rate and stroke volume, specifically, a reduction in heart rate and an increase in stroke volume. Existing evidence demonstrates that, when cardiac output is held constant, myocardial oxygen cost can be reduced in isolated canine hearts when heart rate is significantly slowed (Tanaka et al. 1988). A reduction in heart rate from 200 to 75 beats/min resulted in a reduction in myocardial oxygen consumption of approximately 10 mlfmin/ loog myocardial tis~ue when cardiac output was maintained at 1.2 L/min. Extrapolation of this data to whole body ~02 in humans is at best tenuous; however, it appears safe to hypothesise that any
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realistic reduction in heart rate at a given external resistance would not result in a biologically significant reduction in whole body V02. For example, in the scenario provided above, a reduction of 20 beats/min in heart rate would only result in a reduction of 1.6 mljmin/ lOOg of myocardial tissue in myocardial oxygen consumption. This would only result in an 8 mljmin reduction in whole body oxygen consumption if the heart weighed 500g. Manipulation of heart rate, and its subsequent effect on whole body V02 while performing submaximal work, has been assessed in humans through the use of drugs that alter chronotropic status of the heart (i.e. ~-blockers). For example, Kalis and associates (1988) found subjects treated with propranolol to have significantly lower heart rates and submaximal oxygen consumption values (V02submax) while cycling at 40% OfV02max. The magnitudes of these reductions were approximately 35 beats/min and 0.1 L/min for heart rate and V02, respectively. The reduction in V02submax observed in these types of investigations should not, however, be interpreted to be an exclusive result of a reduction in heart rate. As the authors indicate, t12-blockade also acts to inhibit lipolysis leading to a greater reliance on carbohydrates for energy production. This effect in itself could act to reduce V02submax. Furthermore, it is also possible that t12-blockade can reduce ventilation which, as described above, could also act to reduce V02submax. The preceding discussion supports the conclusion that improvements in running economy could result from improved efficiency of key components of the system that delivers oxygen to the working muscles. However, much more experimentation must be completed before any conclusion as to the practicality of such manipulation and its effect on running economy can be made. It has been well documented that endurance training results in significantly lower heart rates and ventilation at a given submaximal workload. The specific effects of training on running economy will be discussed later in the review.
2.2 Thermoregulation The effects of temperature on running economy are complex. Different investigations have reported V02 submax to be increased, decreased, and unchanged by elevations in core temperature (Brooks et al. 1970, 1971; Dill 1965; Maron et al. 1976; Rowell et al. 1969; Saltin & Stenberg 1964). Those investigators who have found an increased V02submax with an increased core temperature cite increased energy requirements for peripheral circulation, increased sweat gland activity, hyperventilation, and reduced efficiency of muscle metabolism as possible mechanisms. Conversely, investigators reporting V02submax to be reduced or unchanged with an increase in core temperature believe that it is possible that the efficiency of muscle metabolism is improved (i.e. the amount of 02 needed to produce a given amount of ATP is reduced) as muscle temperature is increased. It is entirely possible that both phenomena operate and V02submax is reduced slightly as muscle temperature is moderately increased but eventually increases as the mechanisms involved in heat dissipation are activated to a greater extent. The economy of running in a heat stress environment should be improved by heat acclimatisation. Acclimatisation, accompanied by exercise training, can increase plasma volume up to 12%. Increased plasma volume assists in the maintenance of stroke volume and consequently minimises myocardial work in a heat stress environment. Further, an increased plasma volume improves sweating capacity and enables the body to tolerate greater internal heat production. 2.3 Substrate Utilisation As mentioned earlier, it may be possible to alter running economy by altering the type of fuel (i.e. carbohydrate or fat) used to produce energy. When carbohydrate is used for energy production 5.05 kcal of energy are produced for every litre of oxygen consumed, whereas when fat is used for energy metabolism 4.70 kcal of energy are produced for every litre of oxygen consumed (Brooks & Fahey 1985).
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Consequently, greater carbohydrate use during running at a given speed should be associated with lower oxygen cost. This type of manipulation can potentially be accomplished by either increasing the supply of carbohydrate to the working muscles or by minimising the availability of fatty acids to the muscles. Ingestion of carbohydrate during prolonged exercise has been shown to improve endurance performance and increase respiratory exchange ratio, indicating that more carbohydrate is being used for energy production. However, oxygen cost has been minimally reduced under such manipulations, indicating that ingestion of carbohydrate during prolonged exercise probably has little effect on running economy. This concept has been exemplified by Davis and associates (1988) who observed the changes in oxygen consumption and respiratory exchange ratio in subjects who consumed 275ml every 20 minutes of either a flavoured placebo, a 2.5% carbohydrate beverage or a 6% carbohydrate beverage during 2 hours of cycling at ~75% V02max. Over the 2-hour period, respiratory exchange ratio was significantly greater when the subjects consumed the 6% carbohydrate beverage, indicating that a significantly greater amount of carbohydrate was being used to produce the energy needed to perform the work. However, rate of oxygen consumption was similar under all 3 conditions.
3. External Energy and Running Economy Within the context of this review article, external energy is defined as the energy expended in overcoming an external resistance. Improvement of running economy can theoretically be achieved by reducing the amount of external energy needed to overcome a resistance. As detailed in table I, we believe that age, segmental mass distribution, stride length, and other biomechanical variables play a significant role in determining external energy demand.
3.1 Stride Length and Other Biomechanical Variables Manipulation of biomechanical variables may be the most realistic avenue through which running economy can be altered. The effects of stride length manipUlation on running economy are fairly well known. Hogberg (1952) was the first to document that stride length variation from that which was freely chosen by a runner resulted in an increase in submaximal oxygen consumption. Hogberg's investigation was replicated by Cavanagh and Williams (1982) with a larger sample size (n = 10). Consistent with Hogberg's results, Cavanagh and Williams found runners to be most economical at their freely chosen stride length and described overstriding to be less economical than understriding. The relationship between stride length and running economy appears to be consistent and predictable; however, it appears that experienced runners freely chose their optimal stride length. Consequently, efforts to improve running economy via stride length manipulation would probably be fruitless, unless the runner's freely chosen stride length is not economically optimal. Stride length and running economy have been shown to differ between experienced and novice runners, with experienced runners possessing longer stride lengths and greater running economy. Therefore, it can be hypothesised that with training a novice will develop a longer stride length and greater running economy than that observed at the onset of training. Bailey and Messier (1991), however, found that neither stride length nor running economy changed significantly over a 7-week training period in novice male runners. It may be that changes in stride length and running economy take several months, if not years to develop. Williams and Cavanagh (1987) conducted an extensive investigation of the relationships between running economy and a large array of biomechanical variables in trained runners. The results presented by these authors indicate that the most economical runners possessed a significantly lower force peak at heel strike, greater shank angle with vertical at heel strike, smaller maximal plan-
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tar flexion angle following toe off, greater forward trunk lean, and lower minimum velocity of a point on the knee during foot contact. Williams and Cavanagh (1987) also reported that 54% of the variation in running economy could be attributed to variation in biomechanical variables. The authors suggest that it may be possible to systematically vary aspects of an individual's running style with an ultimate goal to modify selected variables to a more desired level precipitating an improved running economy. With this hypothesis in mind, Messier and Cirillo (1989) implemented a verbal and visual feedback system in an effort to systematically alter running mechanics, and therefore running economy, in a group of novice female runners. Through the use of their system, the authors found that it was possible to significantly alter running mechanics in the desired fashion over a 5-week period. However, the improvement in running economy observed in the group subjected to experimental intervention was not significantly different from that observed in a control group that trained in a similar manner but received no verbal or visual feedback. It may be useful to implement a similar intervention with a group of trained runners to determine if changes in running mechanics can cause improvements in running economy independent of changes in training status. 3.2 Segmental Mass Distribution Segmental mass distribution is perhaps the most subtle of all the variables discussed in this review. Several investigations have described significant inverse relationships between body mass and running economy (Pate et al. 1989; Williams & Cavanagh 1986, 1987). These relationships have been proposed to result from individual differences in distribution of mass among limb segments (Cavanagh & Kram 1985). Furthermore, it has been hypothesised that a smaller individual possesses a relatively greater amount of his or her body mass in the extremities, and would thereby have to perform a relatively greater amount of work moving body segments during running than a larger indi-
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vidual (Myers & Steudel 1985). This hypothesis has been supported by several investigations which indicate that the increased oxygen cost of carrying an added load is greater when it is carried on an extremity than when it is carried on the trunk (Catlin & Dressendorf 1979; Cureton et al. 1978; Inman et al. 1981; Jones et al. 1984; Myers & Steudel 1985). Although the effects of segmental mass distribution on running economy have been described, avenues for improvement in running economy through changes in segmental mass distribution are not obvious. For example, it would appear to be completely illogical to advise an athlete to gain weight in his/her trunk in an effort to improve running economy. Such a manipulation could have a positive effect on weight distribution, but would negatively affect weight-relative V02max and distance running performance. Weight reduction from the extremities could have a positive effect on running economy; however, effective practical means to reach this end do not exist to our knowledge. 3.3 Age The relationship between age and running economy appears to be parabolic. Running economy has been shown to be lower in younger children than in older children or adults (Daniels & 01dridge 1971; Krahenbuhl et al. 1985, 1989; Leger & Mercier 1984; MacDougall et al. 1983). Furthermore improvements in distance running performance during adolescence have been shown to be more dependent on improvements in running economy than improvements in V02max (Krahenbuhl et al. 1989). These differences have been suggested to be due to variations in both internal and external energy. Internal energy demand may be greater in children due to higher basal metabolic rates and a greater reliance on lipolysis for energy production when compared to their older counterparts. In comparison external energy demand for a given resistance may be lower in adolescents due to greater leg lengths and stride lengths and lower body surface area to body mass ratios. The differences in running economy between
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younger and older adults are not as well defined; however, it appears that running economy is reduced with increasing age (Larish et al. 1987; Sidney & Shepard 1977; Waters et al. 1983). Reduced muscle elasticity and antagonistic muscle relaxation as a result of aging have been sited as possible mechanisms for this relationship. Both of these responses to aging may reduce the ability of skeletal muscles to store and use elastic energy during running, which would subsequently increase the amount of external energy needed to run at a given velocity. Consequently, the reduction in running economy seen with aging might be dampened through the maintenance of muscle elasticity; however, this has not yet been demonstrated experimentally.
4. Other Factors 4.1 ~02max The direct relationship between running economy and ~02max has not been well defined. Pate and colleagues (1989) have described the relationship between the two variables to be negative in nature. More specifically, the relationship between ~02max and running economy at 160 m/min (6 mph) was found to be significantly negative (p = 0.0001) [Pate et al. 1989]. In a somewhat similar vein, Pollock (1977) found ~02submax (at 4.5 and 5.4 m/sec) and ~02max to be significantly lower in elite marathoners than in elite middle-distance runners. The possible mechanisms underlying this negative relationship between running economy and ~02max are numerous. It is possible that a negative relationship between running economy and ~02max was observed because those runners who possessed high ~02max values were more accustomed to running at greater velocities than those used to assess running economy in the investigations described above. Consequently, runners with lower ~02max values may have trained more frequently at running velocities similar to those used in the above investigations and were more mechanically efficient at these velocities. It is also possible that individuals possessing greater ~02max values were more able to utilise fat for the pro-
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duction of similar amounts of energy. Since the amount of oxygen needed to produce a given amount of ATP is greater when fat is the fuel source as compared to carbohydrate or protein, oxygen cost for individuals better able to utilise fat for the production of energy would be greater. In addition, segmental mass distribution may have confounding effects on the relationship between running economy and ~02max. As described above, greater concentration of body mass in the trunk area appears to be advantageous in terms of running economy. Conversely, those individuals who possess greater percentages of their body mass in the arms and legs may be able to obtain higher ~02max values because a greater proportion of their lean muscle mass is active during running. Therefore, segmental mass distribution may have opposite effects on running economy and ~02max. 4.2 Training Status The most natural way to improve running economy would be through the alteration of training status. Several investigators believe that running economy is affected by training status; however, the relationship between the two is unclear. For example, middle and long distrance running programmes have been shown to have positive (Daniels et al. 1978a; Daniels & Oldridge 1971; Patton & Vogel 1977) and neutral (Daniels et al. 1978b; Petray & Krahenbuhl 1985; Wilcox & Bulbulian 1984) effects on running economy. The use of interval or high intensity training has had some success in improving running economy (Conley et al. 1981a, 1984; Sjodin et al. 1982). Improvements in running economy from this type of training have been attributed to alterations in running style and intracellular oxidative capacity. Improvement in running economy through the manipulation of training status may have potential, however, more research implementing several different training protocols must be completed before a conclusion can be made as to what is the best type of training for the improvement of running economy.
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4.3 Fatigue The onset of fatigue could potentially reduce running economy by increasing the demand for either external energy or internal energy. As glycogen is depleted from the working muscles, the reduction in respiratory exchange ratio due to the increase in free fatty acid oxidation could increase oxygen consumption. Martin and colleagues (1987), however, indicated that while respiratory exchange ratio and blood free fatty acid concentration were elevated I day after a hard training workout, no change in running economy was observed. It is also possible that alterations in running mechanics, which may occur as a result offatigue, can negatively effect running economy. Morgan et al. (1990) investigated this possibility by observing changes in running economy, respiratory exchange ratio, and several biomechanical variables in male distance runners on I, 2 or 4 days following an exhaustive treadmill run. Morgan's investigation again revealed that respiratory exchange ratio was significantly lower 1 and 2 days after the exhaustive exercise bout; however, variations in biomechanical variables and running economy were small. These investigations appear to indicate that fatigue, and the possible physiological and biomechanical pertubations that may be associated with it, have relatively little effect on running economy during subsequent exercise bouts. Further investigation is needed to determine if any of the consequences of fatigue significantly effect running economy within a single exercise bout. 4.4 Mood State Minimal research exists in reference to the psychological factors that may influence running economy. Recently, however, Williams et al. (1990) have investigated the effects of mood state on within subject variability in running economy. These authors found that a more positive mood state, as measured by the Profile of Mood States (POMS), was significantly correlated with greater running economy (r = 0.88). Furthermore, correlations determined between the 6 POMS subscales and run-
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ning economy indicated that tension held the strongest association (r = 0.81). The correlation between running economy and mood state described above may be the result ofa common underlying mechanism; however, these results do not indicate that a cause and effect relationship exists between the two. For example, mood state during exercise and running economy may be similarly affected by changes in heart rate, ventilation, running mechanics and substrate utilisation.
5. Can Running Economy be Improved? The purpose of this review was to discuss how running economy could be theoretically improved within an individual through the manipulation of factors that have been shown to be associated with running economy. The means of achieving this goal would be to reduce internal energy demand, external energy demand, or both at a given submaximal running velocity. Conceptually, internal energy demand can be reduced within an individual by reducing heart rate, lowering ventilation, and increasing the percentage of carbohydrates oxidised for energy production. Of these, it appears that manipulation of ventilation (by increasing tidal volume and reducing breathing rate) provides the only avenue through which running economy may be appreciably improVed. Internal energy demand while exercising in a heat stress environment can also be reduced within an individual by acclimatisation. Substantial improvements in running economy may be more likely to result from reduction of external energy requirements for a given running velocity. Such improvements would provide multiple benefits because internal energy demand would be affected as well. From the above discussion, it appears that external energy demand may be reduced within an individual by distributing a lower proportion of body mass in the extremities. While increasing the percentage of body mass in the trunk area may improve running economy, it is also likely that such manipulation would have adverse effects on weight-relative V02max and performance. In comparison, loss of mass in the extremities would
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probably have a positive effect on running economy. However, to our knowledge there is no method for focusing weight loss exclusively in the extremities. Loss of muscle elasticity is believed to be a main mechanism through which running economy is reduced with aging. Consequently, maintenance of muscle elasticity may assist in the maintenance of running economy. Several biomechanical variables have shown to effect running economy including stride length, forward trunk lean, shank angle at heel strike, and maximal plantar flexion. Of these stride length has been most closely examined. Results from pertinent studies indicate that experienced runners freely choose a stride length that is optimal in terms of running economy. It is entirely possible that other biomechanical variables that have been found to effect running economy follow a similar pattern and that any manipulation within an individual will not result in an improved running economy. Alteration of training status may be the most fruitful avenue through which running economy may be improved. In particular, the use of high intensity interval training has produced positive results (Conley et al. 1981a, 1984; Sjodin et al. 1982). However, alterations in training status may precipitate changes in variables that both positively and negatively affect running economy. An enhanced training regimen may favourably change running economy by improving running style and intracellular oxidative capacity. Conversely, an enhanced training regimen could also reduce running economy by increasing mass distribution in the limbs and increasing V02max. A greater V02max may reduce running economy by increasing the percentage of fat oxidised for energy production at a given running speed. Lastly, running economy is apparently correlated with mood state. The question remains; can running economy be improved within an individual? The few direct attempts that have been made to improve running economy within a group of individuals have met with limited success. Most available evidence seems to indicate that relatively little improvement in running economy can be expected following conscious manipulation of factors that are associated
with running economy. However, manipulations of ventilation, segmental mass distribution, training status, and running style show some promise. Consequently, much more investigation of the relationships between these variables and running economy is needed before a definitive conclusion can be made concerning the feasibility of improving running economy within an individual.
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Correspondence and reprints: Stephen P. Bailey. Department of Exercise Science, University of South Carolina, Columbia, SC 29208, USA.
