Online Appendix The main manuscript document provides a number of points regarding clinical interpretation of running economy. This online appendix provides some specific examples to further demonstrate the points of the main text, so that one can fully appreciate the nuances of interpreting running economy data. Does Running Economy Vary Across Different Running Speeds? Daniels and Daniels 1 performed numerous analyses of running economy data in elite runners to reach their conclusion that running economy is highly dependent upon the running speeds used. The interested reader is referred to their original paper to gain a greater appreciation of this topic. However, one example is seen when comparing the running economy of elite male marathon runners to that of other elite male long-distance runners (e.g., 5km and 10km specialists). Elite male marathoners were more economical than elite runners competing in shorter events at 3:44/km pace (268m/min; much slower than race pace), but had equal economy at marathon pace. If only speeds slower than race pace had been evaluated, marathon runners would be deemed “more economical” but when race pace is considered, they have no economical advantage. The influence of running speed on running economy is especially relevant in studies investigation footwear interventions (e.g., minimalist shoes, barefoot running, orthotics), since the effects of shoe weight on running economy are actually reduced at faster running speeds.2 In other words, if a shoe intervention improves economy at a slow pace (e.g., 4:21/km), this does not necessarily equate to improvements at marathon pace (e.g. <3:44/km) to translate to improved racing performance. This speed-specific principle can work in either direction, depending on the intervention. For instance, Reeves 3 reported that running economy during barefoot running was unchanged at 67 and 75% of VO2max, but was significantly lower (less aerobic demand) barefoot at 84% and 91% of VO2max (which would be approximately representative of half marathon through 10K race intensity).4 This finding would have been missed if only slower speeds were used (as they commonly are). Thus, it is possible that conclusions from studies examining only 60 and 70% of peak sustainable velocity 5 would have been different if faster speeds were examined. Likewise, when running economy is measured at only one speed (e.g,. running economy at ~80% VO2max does not change over a season of training), 6, it is impossible to know whether a negative finding is representative of running economy across multiple other intensities. Why Are Fixed-Speed Protocols Problematic For Comparing Heterogeneous Groups of Runners? Running test protocols are often chosen so that a heterogeneous group of subjects can all achieve the given treadmill speed, but fixed-speed running economy comparisons may be of 1 limited practical value when large differences in VO2max exist. Thus, comparisons of running economy between individuals of different fitness are ideally performed at similar relative 1 intensities (i.e., similar percentages of velocity at VO2max or a known racing pace). This may be demonstrated by Barnes; although males were slightly less economical in terms of absolute VO2 at a fixed speed, males were more economical when VO2 was expressed as a percentage of 7 VO2max at those same speeds. Thus, if fixed-speeds comparisons between groups are necessary, relative intensity may be more meaningful than running economy. In other cases, fixed treadmill speeds are selected without regard to the population of interest. For example, Warne 8 measured running economy at 11.0km/h because it had “previously been considered an appropriate steady state ‘‘endurance running’’ velocity.” However, the study they cited 9 reported a preferred “endurance running speed” of 11.9±1.4km/h (range 7.7-23.9km/h) in a mixed male and female sample of Kenyan runners of unreported fitness level. Although Warne concluded gait retraining did not influence running economy, the arbitrary treadmill speed used (incorrectly based on the average preferred speed from a very different group of runners) precludes accurate analysis of the intervention. Does Running Surface Influence Running Economy? Decisions regarding optimizing running economy in competitive athletes should consider competition surface and environment. For example, mechanical differences and wind resistance cause VO2 differences between treadmill and overground running, which may influence running economy. Although the significance of such differences are also speed-dependent, a 1% 10 treadmill grade generally produces a VO2 comparative to level ground. However, different treadmill designs (e.g., surface11 or motor12) and ground surfaces influence energy expenditure, thus this 1% equivalency is not necessarily universal. Numerous studies from the 1970’s 13 suggested running economy was worse (greater VO2) overground, but a recent study found running economy was superior (lower VO2) overground compared to 1% treadmill incline, which may be due to improved mobile measurement techniques and running surfaces.14 Does Habituation to an Intervention Influence Running Economy? Many studies have examined whether an intervention, such as a shoe or altered footstrike pattern, acutely influences running economy. However, the value of examining acute responses in running economy is of questionable clinical relevance, given that the physiological response to an unfamiliar movement may be different than the physiologic response which occurs after habituation. This concept is demonstrated in Warne’s study,15 in which running economy did not differ between minimalist and traditional running shoes at baseline, but was significantly improved following four weeks of using the minimalist shoes, and thus concluded minimalist shoes can be valuable for enhancing running economy. If only acute effects of minimalist shoes were evaluated, one would conclude minimalist shoes did not improve running economy. Although this study demonstrates how different conclusions may be reached, depending on whether acute or chronic effects are measured, it must be realized that there are some limitations which could influence the results. These include the lack of a control group that did not incorporate minimalist shoes into their training, the inclusion of exercises targeting the calves and foot, and the use of low relative intensities (~60-70% of VO2max, a limitation acknowledged by the authors). Given that acute changes to an intervention may not reflect chronic changes to an intervention, one must carefully consider the conclusions about running economy in studies which only measured an acute effect. For instance, Gruber 16 found that when habitual rearfoot strikers changed to a forefoot strike, they were less economical. While the data suggest that changing footstrike pattern does not seem to be detrimental in the short-term, lack of a habituation period limits information that could be used to make recommendations for training interventions. Interestingly, in that same study, when habitual forefoot strikers switched to rearfoot strike, their running economy remained unchanged. Thus, different conclusions about the effects of altering footstrike could be reached if either group was studied in isolation. It must also be noted that, the acute effects of footstrike type were speed-dependent, which further emphasizes that single-speed protocols may provide incomplete information and result in inappropriate conclusions. How Does Body Mass Influence Running Economy? Because body mass normalization is commonly used for running economy, body composition influences running economy and can cause confusion in running economy interpretation. For example, if a 60kg individual has an absolute VO2 of 2.0L/min while running at 10kph, his normalized VO2 is 33.3mL/kg/min and his running economy is 200mL/kg/km. However, if that person then gains 5kg of body fat and all other factors stay relatively unchanged, his normalized VO2 becomes 30.7mL/kg/min and his running economy “improves” to 184.6mL/kg/km. While gaining fat mass seems contradictory to enhancing efficiency, this example demonstrates the nuances of interpreting RE data. Thus, if an athlete undergoing intense training loses body fat, actual improvements in running economy may not be fully realized (though improvements in VO2max may arguably be exaggerated). Likewise, athletes of different competitive levels (i.e., world class vs. collegiate runners, elite vs. sub-elite, competitive vs. recreational, old vs. young, men vs. women) may have different body composition, which can further add to the difficulty of comparing running economy between groups. As such, body composition should be carefully considered when comparing running economy between heterogeneous groups or changes within an athlete. Are Terms Such as “Efficiency” and “Cost of Running” The Same As Running Economy? Running economy is specifically intended to represent VO2 related to a given running speed. A number of similar and related terms are used throughout the literature, including oxygen cost, cost of running, efficiency, metabolic demand, energy cost, etc.13 These terms should not be used synonymously with “running economy” as they can all represent different concepts, and inter-changeable use can cause confusion. For instance, “energy cost” or “cost of running” can include both aerobic and anaerobic components, and may be expressed in units of energy (i.e., kilocalories).13 As such, there are various