Relationship Between Running Economy and Kinematic Parameters in Long-Distance Runners

Abstract

Pizzuto, F, Fonseca de Oliveira, C, Amorim Soares, TS, Rago, V, Silva, G, and Oliveira, J. Relationship between running economy and kinematic parameters in long-distance runners. J Strength Cond Res 33(7): 1921–1928, 2019—The purpose of this study was to explore the relationship between running economy (RE) and sagittal, frontal, and transverse plane kinematic parameters in long-distance runners. A secondary purpose was to identify the kinematic predictors of RE during running at the lowest RE value, representing an individual's most efficient running intensity. Twenty recreational long-distance runners ran 3 submaximal stages on a treadmill (65, 75, and 85% of velocity at maximum oxygen consumption). Respiratory data were collected using a portable gas analysis system. Kinematics were gathered using passive retroreflective markers and 8 high-resolution infrared cameras to collect the respective trajectories. Hip, knee, and ankle angles at foot strike and stance phase, as well as spatio-temporal parameters were calculated during each gait cycle. Knee flexion/extension range of motion (ROM), knee ab/adduction ROM, and hip ab/adduction ROM during the stance phase of the gait cycle showed positive moderate to large correlations with RE (r ± 90% confidence intervals = 0.51 ± 0.29; 0.49 ± 0.30; 0.53 ± 0.28, respectively). Knee and hip ab/adduction ROMs during the stance phase are predictors of RE, accounting for 44% of RE variance. Therefore, sagittal and frontal plane kinematics affect RE-inducing alterations in running performance. Coaches, athletic trainers, and anyone involved in running training prescription should consider a relationship between these parameters to ensure optimal technique and, consequently, to improve RE in recreational long-distance runners.

Introduction

Long-distance competitions, such as marathons, are practiced worldwide (³⁹). Consequently, determinants of running performance are of great interest among researchers and practitioners. Maximal oxygen consumption (Vo₂max), defined as the highest rate at which oxygen can be taken up and used by the body during severe exercise (ml·kg⁻¹·min⁻¹), has been used to describe physiological status in endurance runners (³). However, running economy (RE), described as the metabolic cost to cover a given distance (kcal·kg⁻¹·km⁻¹), has been considered a better predictor of endurance performance compared with Vo₂max in elite runners with similar Vo₂max (^7,35). Because an improved RE is considered extremely beneficial for the enhancement of performance in long-distance runners, an important purpose for applied sports science was to identify the determinants of optimal RE and their inherent mechanisms of action.

Sagittal plane kinematic parameters, such as flexion and extension of joints during running, affect RE (^38,41,42). For instance, reduced peak hip flexion during braking (³⁸), greater knee flexion during stance phase (⁴²), greater maximal thigh extension angle with the vertical (⁴¹), larger amplitude of the knee angle at foot strike (⁴¹), and less plantar-flexion at toe off (⁴¹) have been correlated to improve RE. Further findings included significant relationships between other kinematic parameters and RE in long-distance runners (^5,6,22). Indeed, kinematic aspects such as reduced center of mass (COM) vertical excursion (^5,27), self-chosen stride frequency/length (^6,25,42), as well as reduced plantar-flexion at high velocity during the terminal stance (⁴²), have been linked to a lower energy cost of running. Although significant differences and trends in some kinematic parameters have been observed between economical (lower RE values) and less economical (higher RE values) runners, studies have shown contradictory results (^9,27,34,41). These discrepancies are probably derived from a complex interrelationship between the multitudes of distinct mechanical descriptors of running technique that could globally influence RE. Consequently, more detailed analysis on this topic is needed.

Overall, the literature is inconsistent on the influence of frontal and transverse plane kinematics on RE in endurance runners. Thus, investigating whether frontal and transverse plane kinematic parameters affect RE could be crucial to bridge the gap between biomechanical factors affecting RE.

Given the above, the aim of this study was to analyze the association between RE and sagittal, frontal, and transverse plane kinematic parameters in long-distance runners. A secondary purpose was to identify the kinematic predictors of RE during running at the most economical submaximal speed (the lowest RE value of each runner, representing the most efficient individual intensity and thus the most interesting stage to investigate for the purpose of this study). This would provide practical information for endurance coaches and runners pursuing economical running technique.

Methods

Experimental Approach to the Problem

A correlational design was used to quantify the relationship between RE, sagittal, frontal, and transverse plane kinematics during submaximal running in recreational long-distance runners and to identify the kinematic predictors of RE. Participants visited the laboratory on 2 occasions, separated by a minimum of 72 hours and a maximum of 1 week. On the first occasion, anthropometric characteristics and Vo₂max were assessed. Anthropometrics were determined using a precision stadiometer and scale (Seca, Bonn, Germany). On the second occasion, subjects were tested to determine RE and kinematic parameters during running at 3 different submaximal speeds. Treadmill slope was 1% to reproduce the energetic cost of outdoor running for both Vo₂max and RE assessments (²¹).

Running economy and kinematic parameters were recorded over 3 submaximal 5-minute duration stages on a treadmill (65, 75, and 85% of Vo₂max). Although several studies have investigated RE, there is no clear consensus in the literature for the choice of submaximal percentages based on Vo₂max. Although some studies have used pre-established speeds (^2,25,40), others have focused on not exceeding the anaerobic threshold (blood lactate concentrations <4 mmol) (^11,12). In this study, submaximal intensities were based on the individual Vo₂max of each subject. For these reasons, we avoided pre-established speed stages. The multiple recording was based on the idea that RE should be compared between individuals at a similar relative intensity. Consequently, RE was measured at 3 submaximal intensities expressed as a percentage of velocity at Vo₂max (vVo₂max) to normalize for differences in economy associated with a supramaximal speed and to ensure steady-state oxygen consumption. Comparing different runners at the same absolute speed does not account for individual vVo₂max or individual substrate utilization associated with differences in intensity relative to Vo₂max. Steady-state condition and submaximal intensity during each stage were confirmed as maintenance of a respiratory exchange ratio (RER) of less than 1.0. In addition, based on the idea that economical running is associated to efficient running kinematics (¹²), among the 3 stages, only the most economical for each subject was considered for statistical analyses.

It was hypothesized that RE (a) would be associated to hip and knee angles during the stance phase of running and (b) would be predicted by hip and knee joint angles during stance phase of running at the most economical stage.

Subjects

Twenty male recreational long-distance runners (age 37.45 ± 4.85 years; body mass 72.41 ± 9.15 kg; height 174.88 ± 7.05 cm, mean ± SD) participated voluntarily in this study. Subjects had been regularly involved in regional, national, or international endurance events such as 10-km (38.41 ± 6.51 minutes), half-marathon (86.47 ± 12.43 minutes), and marathon (186.27 ± 19.01 minutes) during the last 5.45 ± 7.44 years. Inclusion criteria for subjects were: (a) having at least 1-year experience in long-distance running at recreational level; (2) running at least 50 km·wk⁻¹ (51.50 ± 22.54 km·wk⁻¹); and (c) maintaining a training frequency of 4 d·wk⁻¹ (4.25 ± 1.33 d·wk⁻¹). Thus, subjects represented a sample of the amateur runners' population. Runners were free of cardiovascular, musculoskeletal, and metabolic disease at the time of participation. Participants were asked to refrain from hard training sessions and competition 24 hours before testing. They were also requested to abstain from caffeine and alcohol intake the day before the test. Runners were experienced in treadmill running. All the subjects were informed of the purpose of the study and possible risks involved. Written informed consent was obtained from every subject in accordance with the “Declaration of Helsinki.” The study was approved by the Ethical Committee of the Faculty of Sports, University of Porto.

Procedures

Incremental Treadmill Running Protocol

Individual Vo₂max was assessed through an incremental test on AMTI's force-sensing tandem treadmill (Advanced Mechanical Technology, Inc., Watertown, MA, USA) adapted from Noakes et al. (²⁶). After a 4-minute warm-up at 6 km·h⁻¹, speed was 10 km·h⁻¹ and increased 1 km·h⁻¹ every 1-minute interval. The test was considered completed when participants were not able to withstand the physical effort imposed by the test, showing visual signs of volitional fatigue or wanted to stop the test because of discomfort, despite constant encouragement from the researchers. Once the maximum effort was reached, speed was reduced to 6 km·h⁻¹ for a 4-minute recovery period. Maximum effort was confirmed based on the presence of plateau in the oxygen consumption (maintenance of Vo₂ values [±2 ml·kg·min⁻¹], despite the increase in exercise intensity). Breath-by-breath gas exchange data were quantified through an automated open circuit metabolic cart (Oxycon Pro; Carefusion, San Diego, CA, USA), with JLAB system (version 5.30.0.155). Environmental temperature remained between 20 and 23° C. The highest 30-second value for Vo₂ was recorded as Vo₂max. The vVo₂max was the speed at which Vo₂max occurred that the athlete was able to sustain for the complete minute.

Running Economy Assessment

After a 6-minute warm-up period at a running speed of 6 km·h⁻¹, subjects ran at 3 different speeds for 5 minutes on a treadmill in the same order: 65, 75, and 85% of their vVo₂max. For each speed, the breath-by-breath Vo₂ was averaged every 30 seconds. Steady state was defined when the fluctuation of Vo₂ was <100 ml O₂ over the final 2 minutes of each intensity (¹¹). The average Vo₂ of every 30 seconds over the final 2 minutes was collected as the steady-state Vo₂ for that speed. The RER of every submaximal stage did not exceed a value of 1.0. Between stages, the subjects stood stationary on the treadmill for 5 minutes. Running economy at each speed was expressed as gross caloric unit cost (kcal·kg⁻¹·km⁻¹) based on Fletcher et al. (¹¹) and Shaw et al. (³⁶) (^11,36). Only the most economical stage among the 3 collected for each subject was analyzed for kinematic parameters associated with RE.

As for the incremental treadmill running protocol, breath-by-breath gas exchange data were quantified through an automated open circuit metabolic cart (Oxycon Pro; Carefusion), with JLAB system (version 5.30.0.155). Environmental temperature remained between 20 and 23° C.

Kinematic Analysis

Three-dimensional (3D) body segment kinematics data were captured through an eight-camera Oqus motion capture system (Qualisys, Inc., Gothenberg, Sweden) operating at 100 Hz. Adapting the protocol used by Shih et al. (³⁷), 31 retroreflective markers were placed on the participants' acromion process, xiphoid process, anterior and posterior-superior iliac spines, greater trochanter, femoral condyles, malleoli, first toe, fifth metatarsal head, and calcaneus. Additional tracking markers were positioned on the lateral aspects of the thigh and shank.

Visual3D (C-motion Inc., Rockville, MD, USA) software was used to process the kinematic data. Based on previous literature (^28,39), the marker trajectories were filtered using a fourth order low-pass butterworth filter with a cutoff frequency of 12 Hz. Kinematic variables were quantified for the stance phase of both lower limbs during the entire fourth minute (60-second running). Foot strike was defined as the maximum anterior-posterior position of the heel marker. Toe off was defined as the minimum anterior-posterior direction of the first metatarsal marker (⁴⁵). Three-dimensional kinematics of the lower-limb angles was calculated using an x-y-z (flexion/extension, ab/adduction, and internal/external rotation) Cardan sequence of rotations (x = sagittal plane, y = frontal plane, and z = transverse plane). Coordinate data from retroreflective markers were used to calculate 25 kinematic parameters (Table 1). Positive values denote joint flexion, dorsiflexion, abduction, eversion, and internal rotation while negative values correspond to joint extension, plantar flexion, adduction, inversion, and external rotation. For all kinematic parameters, the final values were the mean of all events recorded.

Table 1.: Kinematics values and respective correlations with running economy (RE) during the most economical stage of running.*

Statistical Analyses

Sample size was computed basing on the magnitudes of correlation observed in previous similarly designed research (⁴⁰). Power calculation revealed 19 subjects to yield a power of 0.80. Therefore, 20 recreational runners were examined. Data are reported as mean ± SD. All independent measures (kinematic parameters) were normally distributed. Correlations between variables were analyzed using magnitude-based inferences (¹⁸). Pearson's correlation coefficient (r, with 90% confidence intervals [CIs]) was used to analyze the bivariate relationship between the RE and kinematic parameters.

Magnitudes of correlation (r) were defined as: trivial (≤0.1), small (0.1–0.3), moderate (0.3–0.5), large (0.5–0.7), very large (0.7–0.9), and almost perfect (0.9–1.0). If the 90% CI overlapped positive and negative values, the magnitude was deemed unclear (¹⁸). Practical inferences of the correlation coefficients were also considered. The default threshold of r was considered 0.1 based on Cohen's assumption of the smallest clinically important correlation. Quantitative probabilities of higher or lower differences were evaluated qualitatively as: <1% = almost certainly not, 1–5% = very unlikely, 5–25% = unlikely, 25–75% = possible, 75–95% = likely, 95–99% = very likely, and >99% almost certain (¹⁶). If the probabilities of the effect being higher or lower than the smallest worthwhile difference were simultaneously >5%, the effect was deemed unclear. Otherwise, the effect was clear and reported as the magnitude of the observed value.

Subsequently, 25 kinematic parameters were modeled as predictors of RE. A stepwise method with forward selection was used removing the independent variables with p ≥ 0.05 in the final step. The coefficient of determination (R², with associated 90% CIs) was computed to quantify the amount of explained variance in RE.

Statistical Package for Social Science version 23.0 for Mac OS and a modified Excel spreadsheet (¹⁷) were used for statistical analysis.

Results

Of 20 recreational runners, 5 (25%) showed the most economical running at the first intensity, 4 (20%) at the second intensity, and 11 (55%) at the third intensity. Descriptive values of kinematic parameters and respective correlations with RE are reported in Table 1. Average RE at the individual most economical stage was 1.07 kcal·kg⁻¹·km⁻¹ (range = 0.86–1.18). On the sagittal plane, a very likely large correlation was observed between RE and knee flexion/extension range of motion (ROM) during the stance phase (r [90% CIs] = 0.51 [0.22–0.80]; % of chances = 97.2/2.5/0.3). On the frontal plane, RE showed moderate to large correlations with hip adduction/abduction angle at foot strike (r [90% CIs] = 0.37 [0.04–0.70]; % of chances = 88.3/9.6/2.2), hip adduction/abduction ROM during stance phase (r [90% CIs] = 0.49 [0.19–0.79]; % of chances = 96.4/3.2/0.4), and knee adduction/abduction ROM during stance phase (r [90% CIs] = 0.53 [0.25–0.81]; % of chances = 97.8/2.0/0.2). On the transverse plane, no correlations were found between RE and any kinematic parameters.

Two prediction models were reached in 2 steps with no parameters removed. First, knee ad/abduction ROM during the stance phase explained a 28% of the total amount of variance in RE (p = 0.01; R² [90% CIs] = 0.28 [0.04–0.51]; F (1, 18) = 7.07). Finally, adding hip ad/abduction ROM during the stance phase improved the model by 15% with these variables explaining 43% of the total amount of variance in RE (p < 0.01; F (1, 17) = 4.72; R² [90% CIs] = 0.43 [0.18–0.67]). A detailed representation of the regression model is reported in Figure 1.

Figure 1.: Running economy (RE); black circles indicate knee adduction/abduction range of motion, and white circles indicate hip adduction/abduction range of motion; traced lines indicate 95% confidence intervals. ROM = range of motion.

Discussion

The first aim of this study was to analyze the relationship between RE and sagittal, frontal, and transverse plane kinematics. Among the 25 kinematic parameters analyzed, 1 sagittal plane and 2 frontal plane kinematic parameters resulted positively correlated with RE in long-distance athletes running at the most economical submaximal speed.

In the present research, sagittal plane analysis showed that the increment of knee flexion/extension ROM during stance phase is correlated with higher values of gross caloric unit cost of running, which is a worse RE. In this context, the positive correlation confirms that the energy cost of running generally increases with higher knee flexion/extension ROM during stance phase. Because the value of r (r [90% CIs] = 0.51 [0.22–0.80]; % of chances = 97.2/2.5/0.3) indicates that the relationship is very likely large, but not perfect, we can expect the knee flexion/extension ROM during stance phase to vary slightly, even among runners with similar RE values. In addition, it is important to highlight the limitations of this relationship. Indeed, no subject showed a completely flexed/extended knee during the stance phase of running (knee flexion/extension ROM during stance phase = 0). Consequently, even if a linear relationship was found, we can logically deduce that a total absence of knee ROM during stance phase would not correspond to a better RE. Indeed, many factors support an increased economy related to a lower, but not absent, flexion/extension ROM of the knee during stance phase. A major gain may be associated with the optimal involvement of the stretch-shortening mechanisms, which may result in increased elastic energy storage and reuse (²⁰). Indeed, Ito et al. (²⁰) have found that efficient kinematics during stance phase were related to a progressive increase in the elastic energy stored and shortened coupling time. Consequently, a more efficient elastic energy storage and reuse mechanism during the concentric phase was associated to improved RE (^2,20). Although leg stiffness was not measured in our study, this finding seems to be in agreement with the importance of leg stiffness to improve RE (²⁰). A further consequence of the narrower range of joint motion is the maintenance of the working range of sarcomere length close to the plateau region of the force-length relation. This more efficient mechanism contributes to increasing the efficiency of force production of cross-bridge formation (¹⁹). Another contribution likely derives from the gradual shortening of stance phase duration (^22,27), which could be explained by the reduced time for the braking force to decelerate the body's forward motion. Although previous investigations have shown a relationship between RE and several sagittal kinematic parameters (^6,22,27), no studies have reported knee flexion/extension ROM during stance phase as a parameter related with RE. Further studies simultaneously investigating the musculotendinous involvement and the stretch-shortening mechanisms would help clarify the ideal biomechanical running form that may assist athletes and recreational runners to optimize RE and improve performance.

The analysis of the frontal plane showed a relationship between RE and knee ab/adduction ROM and hip ab/adduction ROM during the stance phase. In other words, an increment of knee and hip ab/adduction ROM during stance phase corresponds to the increment of gross caloric unit cost of running, meaning a worse RE. In addition, for the second purpose of our study, the same 2 frontal plane kinematic parameters were found to be the kinematic predictors of RE during running at the most economical submaximal speed in recreational long-distance runners. Analyzing previous literature regarding RE and frontal plane kinematics, a void is noted. In the only study that aimed to investigate the relationship between RE and frontal plane kinematic parameters of the joints, no correlation was found (⁴⁰). However, frontal plane kinematics during submaximal running have mostly received attention in relation to clinical aspects. For instance, abnormal hip kinematics were commonly related to an increased dynamic knee valgus that is linked with numerous knee injuries (^30,44). Increased knee adduction during the stance phase has been associated with patellofemoral joint dysfunction (^29,33). Although excessive frontal plane motion has been linked with injury previously, this study also suggests these kinematic parameters may be less economical. Based on our findings, a more accurate focus on hip and knee frontal plane angles during the stance phase of running could help to identify less economical aspects of running technique. Accordingly, appropriate corrections of technique and a more targeted training process should be adopted with the purpose of improving kinematics of frontal plane parameters and, consequently, improve RE in recreational long-distance runners. Further research simultaneously investigating the musculotendinous contribution, the kinetics and the kinematics of frontal plane parameters during running would aid to point out the running technique with the purpose of optimizing RE and therefore improving overall running performance.

Considering the transverse plane, in our study, no correlation was observed among the 4 kinematic parameters investigated and RE. To the best of our knowledge, only one study to date has attempted to analyze the relationship between RE and transverse plane kinematics. Anderson and Tseh (¹) analyzed energy cost of running and angular velocity of shoulder rotation and angular displacement of the hips and shoulders about the polar axis of the trunk. However, in our study, no correlation was observed among the 4 kinematic parameters investigated and RE. To bridge this gap in literature, future studies should be focused on the relationship between transverse plane kinematics and physiological aspects of running.

Numerous studies showed that in elite runners, improved RE was associated with spatiotemporal parameters of running. However, this investigation analyzed 7 spatiotemporal parameters observing no statistically significant correlations with RE. Runners seem to naturally choose an economical stride frequency/length (^6,25,42). Some investigations have reported a trend of RE to increase in a curvilinear way as stride length is modified (lengthened or shortened) (^6,31). Our nonsignificant relationships between RE and these specific spatiotemporal parameters is in contrast with these studies. In this study, speeds for each stage were based on individual vVo₂max, and no instructions on running technique were given. Additional investigations examining other spatiotemporal parameters have found that generally increasing vertical excursion of COM corresponds to an increase of Vo₂ values (^13,15). However, the vertical oscillation changes were minimal and increases in Vo₂ were large (^13,15), meaning other physiological and biomechanical parameters could be the cause of the alteration in Vo₂ (^23,25). Our study showed no relationship between vertical and lateral COM excursion and RE; this is consistent with other studies suggesting other parameters may influence RE more (^23,25). Further literature concerning stance phase time and flight time of the foot presented contradictory results regarding its association with RE. Although some investigations have observed a better RE associated with longer ground contact times (^9,41) and others the opposite (shorter ground contact times) (^27,34), several studies have failed to find any relationship between stance phase time and RE (^22,42). Some ambiguous evidences were found for flight time, with various authors reporting increased swing phase time along improved RE (^2,34,42), whereas others did not observe any relationship (^2,43). Our findings showed no relationship between RE, stance phase time, and flight time of the foot during running. Further research is needed to clarify the relationship between spatiotemporal parameters and RE.

Our data revealed that the most economical submaximal stage differed across the group. Indeed, 5 of 20 (25%) subjects resulted to be more economical running at the first intensity, 4 (20%) at the second intensity, and 11 (55%) at the third intensity. This study did not focus on the analysis of the potential reasons behind this difference across the group. Because RE is complex and multifactorial, the differences in most economical intensity for individuals in our study may have been due to other metabolic, cardiorespiratory, and musculoskeletal characteristics not assessed (^2,11,35). Individual training history and physical fitness could influence RE at different running intensities (³⁵). Future studies could assess interindividual variability and RE. However, average RE of the most economical intensities of each subject was 1.07 kcal·kg⁻¹·km⁻¹ (range = 0.86–1.18), consistent with previous studies (^4,11,36).

Some limitations in our study should be noted. The first limitation of the present research was the difference in kinematics between overground and motorized treadmill running. Data collected during laboratory treadmill testing sessions typically underestimate the actual energy demand imposed by overground running because running technique kinematics on a treadmill differ to outdoor activity (³²). Nonetheless, a slight slope on the treadmill gradient (1%) can be used to increase the energy demand in compensation for the lack of air resistance experienced during overground running (²¹). Therefore, treadmill-based and overground sessions have been suggested to be comparable without biasing the final outcomes (³²). The second limitation concerns about the use of RER (<1) (⁷) as the unique physiological parameter to verify the steady-state condition during submaximal running. In this study, RER was evaluated to confirm the maintenance of values of less than 1.0 during every stage to ensure that anaerobic threshold was not exceeded. Therefore, submaximal running intensity was ensured, probably preserving blood lactate concentration closer to baseline level. With the aim of ensuring submaximal running intensities, confirming blood lactate concentration below 4 mmol could be a more reliable solution for further research (²⁴). Finally, although our results add support to the important role of biomechanics on RE, practical application of these findings may be limited considering the conflicting results of prior studies on modification of running technique (^8,10,14). There seems to be a clear relationship between hip and knee kinematics and RE, but further research is needed on whether manipulations to these kinematic parameters are worthwhile to improve RE.

Practical Applications

With limited previous evidence on frontal plane kinematics and RE, our study adds knee ab/adduction ROM and hip ab/adduction ROM during the stance phase as novel predictors of RE. Coaches, athletic trainers, and anyone involved in running exercise prescription should consider these kinematic aspects during training. Reducing excessive frontal plane knee kinematics may be beneficial with respect of both injury mitigation and RE.