The economy of motion relates to the quantity of oxygen (ml.kg.min-1) required to move at a given speed or generate a specific amount of power. It has been shown to be an important predictor of endurance exercise performance in a number of endurance sports (cycling, swimming, running etc) and can help to explain differences in performance between individuals. The economy of motion is influenced by a number of factors including: neuro-muscular co-ordination, % type I muscle fibres, elastic energy storage, joint stability and flexibility.
Factors that influence exercise economy
- Neuromuscular co-ordination – every muscular contraction in the human body requires a co-ordinated contraction of muscles and muscle fibres. The greater the co-ordination the lower the energy cost and hence the greater the economy of motion/efficiency will be.
- The percentage of Type I muscle fibres – research has shown that the percent of type I muscle fibres affects exercise economy (Mogensen et al., 2006; Horowitz et al., 1993; Coyle 1992;) due to type I muscle fibres have a greater level of efficiency than type II muscle fibres.
- Elastic energy storage and return – an enhanced elastic energy storage and return is known to have a positive effect on exercise economy (Sawicki et al., 2009).
- Joint stability and decreased flexibility – both increased joint stability and decreased flexibility appear to enhance exercise efficiency in dynamic sports like walking and running. Research has shown that decreased joint flexibility – particularly in the hip and calf regions – is associated with improved running economy (Jones 2002; Craib et al. 1996; Gleim et al. 1990) and walking economy (Hunter et al., 2008; Gleim et al. 1990). In support of this the use of orthotics – often used to reduce excessive pronation and increase stability – have been shown to positively influence running economy at lower intensities (Burke and Papuga 2012). Interestingly it is known that the Sit and reach range of motion is negatively associated with running economy (Jones 2002; Brown et al., 2011) and when researchers looked at a gene that alters muscle tendon stiffness they found that the geneotype was significantly linked with endurance running performance (Brown et al., 2011). Researchers have also found that greater muscle stiffness and less power were associated with greater running economy (Dumke et al., 2010). Possible explanations for the inverse relationship between the economy of motion and flexibility include improved use of elastic energy (Hunter et al., 2008) and reduced recruitment of unproductive muscles for stabilization of the joints (Martin and Morgan 1992) in less flexible individuals.
- Genetics – there appears to be a strong genetic influence with regard to exercise economy with up to 20-30% variation in running economy observed amongst trained runners of similar ability (Morgan and Daniels, 1994).
Exercise economy and race performance
In a number of studies the economy of motion has been shown to be highly predictive of endurance exercise race performance (Hausswirth and Lehénaff 2001; Morgan et al., 1989; Williams and Cavanagh 1987; Scrimgeour et al., 1986; Conley and Krahenbuhl 1980;), with improvements in exercise economy leading to improved exercise performance (Coyle F, 2005; Jones, 1998; Toussaint and Hollander 1994 Krahenbuhl et al., 1989; Conley et al., 1984;). There appears to be wide variation in exercise economy between individuals with 30-40% variation in running economy between individual runners (Joyner, 1991; Conley & Krahenbuhl, 1980; Farrell et al. 1979;) and 20-30% variation in cycling economy between individual cyclists (Coyle, 1995).
A number of studies have found that running economy was found to account for a significant amount of variation in long distance running performance where it was found to be highly predictive of 10km race performance (Williams and Cavanagh 1987; Conley and Krahenbuhl 1980;) and Marathon race performance (Sjödin B, and Svedenhag J. 1985). However, research into the importance of running economy over middle distance events is less conclusive. Performance during an 800m running was not found to be predicted by running performance (Craig and Morgan 1998), whilst it was found to be modestly predictive of 3km race performance (Grant et al., 1997). When looking at 5km race distance and running economy there have been mixed results – one study found that running economy had only a modest effect on 5km running performance (Ramsbottom et al., 1987) whilst another study found it to be highly predictive of 5k running performance (Paavolainen et al., 1999).
Economy of motion is also believed to be an important factor in cycling (Leirdal and Ettema 2011; Joyner and Coyle 2008; Olds et al., 1995;) and swimming performance (Fernandes et al., 2006; Kjendlie et al., 2004; Toussaint and Hollander 1994; Toussaint and Beek 1992). Research in swimming suggests that improvements in propelling efficiency have a more beneficial effect on swimming performance than a proportional increase in either aerobic or anaerobic power (Toussaint and Hollander 1994). Recent research suggests that age associated declines in swimming performance may be due to an increase in the energy cost of swimming (Zamparro et al., 2012).
The positive correlation between exercise economy and exercise performance have led to many researchers to view it as one of the most important factors in endurance performance. However, it must be remembered that a good economy in motion cannot make up for a low VO2 max. In fact research suggests that athletes with greater exercise economy tend to have a lower VO2max (Sawyer et al., 2010; Lucia et al., 2002; Pate et al., 1992), lower oxidative capacity within the muscle (Hunter et al., 2005) and greater weight (Pate et al., 1992). This suggests that a greater exercise economy may allow some athletes to compete successfully in endurance sports that they may not be otherwise physiologically suited to (e.g. they can compensate for a reduced VO2max, greater weight, lower oxidative capacity within the muscle – factors considered important for success in endurance sports).
The VO2-speed relationship
An important consideration with exercise economy is the relationship between VO2 and speed. As exercise intensity increases the oxygen cost should increase linearly, however the rate of increase (gradient) varies between individuals. This is particularly important when assessing running economy where athletes with a high rate of increase in oxygen cost tend to have greater efficiency at slower speeds (e.g. marathon pace) whereas athletes with a low rate of increase tend to have better economy over faster speeds such as 3k-5k pace (Daniels and Daniels, 1992). This can help to explain why some athletes are better suited to middle distance races whilst others are more suited to longer duration races. In fact research suggests that the VO2-speed relationship changes at speeds above the LT with a greater than 50% decrease in the slope of the VO2-velocity relationship at intensities above the LT (Bickham et al., 2004) and suggests that the economy of motion should be assessed at race pace.
Improving exercise economy with resistance/power training
Resistance training (particularly heavy resistance training) and or explosive strength training has been shown to lead to significant improvements in exercise economy in a number of endurance sports including: middle to long distance running (Cheng et al., 2012; Mikkola et al., 2011; Taipale et al., 2010; Guglielmo et al., 2009; Støren et al., 2008; Yamamoto et al., 2008; Spurrs et al., 2003; Paavolainen et al., 1999b), cycling (Louis et al., 2012; Rønnestad BR, et al., 2012; Sunde et al., 2010; Paton and Hopkins 2005), swimming (Girold et al., 2012 & 2006; Konstantaki et al., 2008) and cross country skiing (Hoff et al., 2002; Hoff et al., 1999;).
Heavy resistance training and explosive strength training has proved particularly effective at improving running economy with improvements of 6-8% recorded in some short term studies (Guglielmo et al., 2009; Paavolainen et al., 1999b). Similarly explosive and heavy resistance training have proved to be effective at improving cycling efficiency (Louis et al., 2012; Sunde et al., 2010). Interestingly, research looking at the benefits of resistance training (10 sets of 10 knee extensions at 70%RM) in master endurance athletes found that it alleviated the age related reductions in strength and efficiency (Louis et al., 2012).
Resistance training has also been shown to be beneficial for improving efficiency in swimmers (Girold et al., 2006 & 2012; Konstantaki et al., 2008) although it appears to require more swim specific forms of resistance training.
Exercise efficiency and training intensity
Training intensity appears to play a key role in the development of improved economy of motion. One important factor appears to be that improvements in the economy of motion occur at the speeds that are used during training. This is supported by research in running that found that running economy improved at the speed predominantly used during training (Beneke and Hütler 2005). Therefore, it appears that athletes should ensure that adequate training is performed at speeds close to race pace, in order to maximize improvements in the economy of motion.
Including training at intensities around or above the lactate threshold also appears to be an important method for improving the economy of motion. Researchers have found that cycling efficiency can be increased through the use of high intensity training (Hopker et al., 2010) and appears to be linked to the amount of training spent above OBLA (onset of blood lactate accumulation) and the total volume of training (Hopker et al., 2009). Research in runners found that training at 95 or 100% of vVO2 max (~3km-10km race pace) twice per week significantly increased running economy (Denadai et al., 2006).
Research suggests that the length of the training interval may be an important factor for improving the economy of motion. When researchers (Franch et al., 1998) compared the effects of three different training types, performed three times per week for 20-30minutes, on running economy they found that intensive training (tempo training/lactate threshold training) and long interval training were more effective at improving running economy than short interval training (~3% vs <1% improvement).
Exercise Efficiency and Training Volume
Training volume appears to be a key factor with regards to exercise economy (Hopker et al., 2009; Scrimgeour et al., 1986). When researchers looked at the effects of training volume, prior to competition, they found that the runners with a training volume of more than 100km/week had the greatest running economy (Scrimgeour et al., 1986). The most important factor with regard to training volume and exercise economy/efficiency appears to be to do with the amount of training performed at race pace. Therefore athletes should ensure that an adequate amount of training time is devoted to training at or near race pace in order to improve efficiency at race pace. For most athletes competing in events of 30-60minutes duration this would be best approached through lactate threshold training performed at or just below the lactate threshold. It is important to remember that the improvements in exercise efficiency that occur in response to increases in training volume are very gradual, and therefore gradual increases in training volume and the volume of race pace training should be viewed as part of a long term strategy.
Stretching and Exercise Economy
It’s known that decreased flexibility is associated with improved running economy and as such it has been proposed that stretching may negatively impact on the economy of motion. However, this idea is controversial and whilst there is clear evidence that decreased flexibility is linked to improved economy of motion, there is conflicting research with regards to the effects of stretching and running economy. Research looking at the effects of stretching on running economy, have generally found that running economy doesn’t appear to be negatively influenced by stretching (Mojock et al., 2011; Hayes and Walker 2007; Nelson et al., 2001). However, research looking at the effects of stretching and cycling has found reduced cycling efficiency following stretching (Esposito and Limonta 2011; Wolfe et al 2011). Static stretching has been found to reduce cycling efficiency (Esposito and Limonta 2011; Wolfe et al 2011) and has led to the researchers recommended that highly trained endurance cyclists should avoid static stretching prior to moderate intensity cycling (Wolfe et al 2011).
Training experience and the economy of motion
Training experience may play an important role in the development of improved exercise economy, with improvements occurring gradually over a period of years through continued endurance training. Research is limited in this respect to two case studies which have shown improved running economy (14% improved running economy over 5 years) and cycling efficiency (8% improved cycling efficiency over 7 years) in elite athletes (Jones 2006; Coyle 2005;).
Specific considerations for cycling
Research has shown that the technical aspects of bike setup and pedalling efficiency can have a significant effect on cycling efficiency. Pedalling efficiency appears to play a significant role particularly during endurance cycling. It’s affected by both the ability to generate a constant aplication of force throughout the pedal stroke and the cadence.
One area that has received a lot of interest is the effect of cadence on cycling efficiency. Current research is not completely clear on the most efficient pedal rate (Ettema and Lorås, 2009) – some research has found that triathletes and cyclists are more efficient and economical when cycling at 60rpm rather than faster pedal rates (Jacobs et al., 2012; Sacchetti et al., 2010) whilst other researchers have found higher pedal rates (80-90rpm) to be more efficient (Dantas et al., 2009; Foss and Hallén, 2004). Research suggests that lower pedalling rates appear to be more economical amongst older (~65years) cyclists (Sacchetti et al., 2010). In terms of training research suggests that low-cadence interval training (70rpm) may be more effective than high cadence interval training (110-120rpm) for improving measures of cycling performance including exercise economy (Paton et al., 2009).
Other factors that appear to influence cycling efficiency include the pedalling technique (Canon et al., 2007; Zameziati et al., 2012) and saddle height (Peveler and Green 2011) – researchers looking at the effect of saddle height on cycling economy found that oxygen consumption was significantly lower when saddle height was set so that there was a 25° knee angle.
Exercise Economy Summary
- Exercise economy is influenced by a number of factors including: Neuromuscular co-ordination, % type I muscle fibres, elastic energy storage, joint stability and genetics.
- Endurance race performance is strongly linked to exercise economy in sports like running, swimming and cycling. It appears to play a greater role with increasing race duration.
- Improvements in exercise economy have been shown to occur following heavy resistance/explosive training, and as such it should be viewed as important training type for endurance athletes looking to improve exercise economy. High intensity interval training has also been shown to positively affect exercise economy and should be viewed as equally important for improving exercise economy.
- Since improvements in exercise economy appear to occur at the speed predominantly used in training and it is important that athletes include adequate training at or around race pace.
- Other training factors that can influence exercise economy include the volume of training, the intensity of training, and the amount of training performed above OBLA (onset of blood lactate accumulation).
- There is evidence that stretching may negatively influence cycling efficiency, however research in runners has not found any link between stretching and changes in exercise economy.
- Exercise economy may improve gradually over a period of years and therefore carefully controlling training intensity and volume, so as to avoid periods of interrupted training caused by overuse injuries, illness, and overtraining may be particularly important for long term progression.
- Cycling has a number of specific factors that may influence cycling efficiency including cadence, cadence used in training, saddle height, and pedalling efficiency.