1118 Orthopedics & Biomechanics

Authors

J. Santos-Concejero1, 2, N. Tam1, C. Granados2, J. Irazusta3, I. Bidaurrazaga-Letona2, J. Zabala-Lili2, S. M. Gil2

Affiliations

1

UCT/MRC Research Unit for Exercise Science and Sports Medicine, Human Biology, University of Cape Town, Cape Town, South Africa 2 Physical Education and Sport, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain 3 Physiology, University of the Basque Country UPV/EHU, Leioa, Spain

Key words

Abstract

▶ biomechanics ● ▶ ground contact ● ▶ performance ● ▶ correlation ● ▶ rearfoot ● ▶ midfoot/forefoot ●

accepted after revision February 20, 2014 Bibliography DOI http://dx.doi.org/ 10.1055/s-0034-1372640 Published online: June 30, 2014 Int J Sports Med 2014; 35: 1118–1123 © Georg Thieme Verlag KG Stuttgart · New York ISSN 0172-4622 Correspondence Dr. Jordan Santos-Concejero Human Biology UCT/MRC Research Unit for Exercise Science and Sports Medicine, University of Cape Town Sports Science Institute of South Africa Cape Town South Africa 7700 Tel.: + 27/745/233 168 Fax: + 27/216/867 530 jordan.santosconcejero@uct. ac.za



This study aimed to investigate the relationship between stride angle and running economy (RE) in athletes with different foot strike patterns. 30 male runners completed 4 min running stages on a treadmill at different velocities. During the test, biomechanical variables such as stride angle, swing time, contact time, stride length and frequency were recorded using an optical measurement system. Their foot strike pattern was determined, and VO2 at velocities below the lactate threshold were measured to calculate RE. Midfoot/forefoot strikers had better RE than rearfoot strikers (201. 5 ± 5.6 ml · kg − 1 · km − 1 vs. 213.5 ± 4.2 ml · kg − 1 · km − 1

Introduction



There has been much preoccupation with foot strike pattern and associated biomechanical variables on running economy [1, 22, 24]. Running economy is commonly defined as the steadystate oxygen uptake (VO2) required at a given submaximal velocity [21] and is the physiological measure that most studies use to discriminate between the most desirable foot strike patterns [8, 24]. In this regard, many researchers have reported no differences in running economy between rearfoot and forefoot strikers when running with their preferred strike pattern [6, 8, 24]. In contrast, Ogueta-Alday et al. [22] recently described a better running economy in rearfoot strikers. Of the possible explanations for these inconsistent findings, ground contact time has garnered the most attention as the biomechanical factor that influences running economy the most in runners with differing strike patterns [8]. What is agreed is that shorter ground contact times are associated with mid/forefoot strike patterns [10, 12, 13] and that at a given ground contact time midfoot strikers appear to be more

Santos-Concejero J et al. Interaction Effects of Stride … Int J Sports Med 2014; 35: 1118–1123

respectively; p = 0.019). Additionally, midfoot/forefoot strikers presented higher stride angles than rearfoot strikers (p = 0.043). Linear modelling analysis showed that stride angle is closely related to RE (r = 0.62, p < 0.001) and that the effect of stride angle on RE was different in the 2 groups. From an arbitrary value of 4 °, a rearfoot strike pattern is likely to be more economical, whereas at any lower degree, the midfoot/forefoot strike pattern appears to be more desirable. A biomechanical running technique characterised by high stride angles and a midfoot/forefoot strike pattern is advantageous for a better RE. Athletes may find stride angle useful for improving RE.

economical due to an absence of interaction effect between ground contact time and the strike pattern [8]. However, various studies have found conflicting associations between ground contact time and running economy, since some studies have found that longer contact times are associated with a better running economy [3, 8], whereas other researchers have reported the opposite [21, 23, 26]. Other biomechanical variables might exist that could help unravel the conflicting relationship between contact time and running economy in athletes with differing strike patterns. Recently, stride angle has been shown to be a novel indicator of running economy that indirectly influences ground contact time during running [26]. It is defined as the angle of the parable tangent derived from the arc traced by the ▶ Fig. 1). foot during a stride and the ground (● Santos-Concejero et al. [26] found that an increased stride angle implies efficient propulsion and an economical running pattern by allowing runners to minimize ground contact time. Since the absence of an interaction effect between ground contact time and the strike pat-

This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.

Interaction Effects of Stride Angle and Strike Pattern on Running Economy

tern cannot explain the inconsistent running economy findings in rearfoot and midfoot/forefoot strikers [8], the question arises whether stride angle may play a role in this complex interaction. Thus, this study aimed to investigate the influence of stride angle on the relationship between running economy and ground contact time in runners with different strike patterns.

Methods



Participants 30 experienced male runners (mean ± SD: age 31.6 ± 8.0 years, best 10-km time 32.9 ± 2.7 min, VO2peak 63.1 ± 5.0 mL · kg − 1 · min − 1) were recruited for this study from local running clubs. Inclusion criteria were current participation in races and a 10-km race time < 40.0 min. Before participation, runners underwent a medical examination to ensure that they were free of cardiovascular, musculoskeletal or metabolic disease. The Ethics Committee for Research on Human subjects of the University of the Basque Country (CEISH/GIEB) approved this study, which was conducted according to the ethical standards of the International Journal of Sports Medicine [11]. All runners were informed about all the tests and possible risks involved and provided written informed consent before testing. The athletes were asked to refrain from hard training sessions and competition 24 h prior to testing. They were also requested to maintain their pre-competition diets throughout the test procedures and to abstain from caffeine and alcohol intake the day prior to testing.

Anthropometry For descriptive purposes, height (cm) and body mass (kg) were determined by the use of a precision stadiometer and balance (Seca, Bonn, Germany). 8 skinfold sites (biceps, triceps, subscapular, supraspinale, abdominal, suprailiac, mid-thigh, and medial calf) were measured in duplicate with skinfold callipers (Holtain, Crymych, UK) by the same researcher to the nearest millimetre, and body fat percentage was calculated [30]. All measurements were taken following the guidelines outlined by the International Society for the Advancement of Kinanthropometry [28].

Peak treadmill speed test All participants completed a maximal incremental running test at 1 % slope on a treadmill (ERGelek EG2, Vitoria-Gasteiz, Spain), which started at 9 km · h − 1 without previous warm-up. The speed was increased by 1.5 km · h − 1 every 4 min until volitional exhaustion, with a 1-min recovery between each stage. The treadmill was calibrated using a measuring wheel (ERGelek, Vitoria-Gasteiz, Spain) with a measurement error < 0.5 m per 100 m interval. All testing sessions were performed under similar environmental conditions (20–24 °C, 45–55 % relative humidity at 600 meters of altitude). During the test, pulmonary variables were recorded breath-bybreath using a gas analyser system (Ergocard, Medisoft, Sorinnes, Belgium) calibrated before each session and verified after each test. Volume calibration and verification were performed at different flow rates with a 3 L calibration syringe (Medisoft, Sorinnes, Belgium), allowing an error ≤ 2 %. Gas calibration and verification were performed automatically by the system using both ambient and reference gases (CO2 4.10 %; O2 15.92 %) (Linde Gas, Germany).

Immediately after each exercise stage, capillary blood samples were obtained from the earlobe for the determination of lactate concentration by a portable lactate analyser (Lactate Pro, Arkray, KDK Corporation, Kyoto, Japan). Heart rate (HR) was recorded continuously by a heart rate monitor (Polar RS800, Kempele, Finland) and rating of perceived exertion (RPE) was assessed according to the 10-point Borg-scale [2]. Athletes were considered to have attained their maximal ability when 3 of the following criteria were fulfilled [15]: 1) a plateau in VO2, defined as an increase of less than 1.5 ml · kg − 1 · min − 1; 2) respiratory exchange ratio > 1.15; 3) HR within 5 beats · min − 1 of theoretical maximal HR (220-age); 4) lactate concentration > 8 mmol · L − 1; 5) RPE = 10. Peak treadmill speed (PTS) was defined as the speed of the last completed stage added to the product of the speed increment and the completed fraction of the incomplete stage calculated according to the equation: PTS = Vcomplete + (1.5 × t/240) where Vcomplete is the running speed of the last complete stage and t the number of seconds sustained during the incomplete stage [20].

Lactate threshold determination The lactate threshold was determined for each participant using the blood lactate concentrations (mmol · L − 1) measured after each stage of the treadmill maximal test. An exponential-plusconstant regression equation was calculated for blood lactate concentration vs. speed, as described by Santos-Concejero et al. [27]: [La−] (s) = a + (b · exp (c · s)) where [La−] (s) is the blood lactate concentration (mmol · L − 1) as a function of speed, s (m · s−1); a, b and c are the function parameters that were determined by non-linear regression analysis. The lactate threshold was identified as the point on the exponential-plus constant regression curve that yielded the maximal distance to the straight line formed by the 2 end points of the curve [4]. A slow increase in VO2 during a constant-work-rate exercise performed above the lactate threshold has been described, also known as the slow component of the VO2 [16]. Thus, to ensure steady-state VO2 values and to avoid possible biomechanical differences as a consequence of differing running speeds, VO2

Toe off

α

Max height

Ground contact

Stride length α= Stride Angle Fig. 1 Schematic representation of stride angle during running.

Santos-Concejero J et al. Interaction Effects of Stride … Int J Sports Med 2014; 35: 1118–1123

1119

This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.

Orthopedics & Biomechanics

1120 Orthopedics & Biomechanics

Biomechanics Although shoes were not standardized across participants, all athletes wore traditional road racing shoes weighing < 300 g for the test. Rudimentary foot strike pattern analysis was undertaken using a high-speed camera recording at 300 Hz (Casio Exilim Pro EX-F1, Japan), with each participant being filmed in the sagittal plane at foot level over a 30-s period during the fourth minute of the running stage corresponding to 13.5 km · h − 1. The video footage was then used to assign forefoot strike, mid-foot strike or heel-strike to the participant’s foot strike pattern by the same observer. A mid-foot strike was classified when there was no clear forefoot or heel initial contact. Runners who appeared to land on the ball of the foot first (i. e., forefoot) or who landed with the heel and ball of the foot simultaneously (i. e., midfoot) were grouped together as forefoot/midfoot strikers [19, 22]. Stride angle, ground contact time, swing time and stride length and frequency were measured for every step during the treadmill speed test using an optical measurement system (Optojump-next, Microgate, Bolzano, Italy) placed at treadmill belt level. This system was developed to measure at a 1 Khz sampling rate all flight and ground contact times while running. The Optojump-next system consists of 2 bars (size 100 cm × 3 cm × 4 cm), one containing the reception and control unit, the other embedding the transmission electronics. Each of these contains 32 LEDs (light-emitting diodes), positioned 0.3 cm from the bottom of the bar at 3.12 cm intervals. The LEDs on the transmitting bar communicate continuously with those on the receiving bar. Ground contact time was defined as the time from when the foot contacts the ground to when the foot toes off the ground and was determined by the disruption of the infrared gates of the Optojump-next system. Using the same principle, swing time was defined as the time from toe off to initial ground contact of consecutive footfalls of the same foot. Stride length and stride frequency were defined as the length the treadmill belt moves from toe off to initial ground contact in successive steps and as the number of ground contact events per minute, respectively. The Optojump-next system has previously been shown to accurately determine these variables [7]. Stride angle was defined as the angle of the parable tangent derived from the theoretical arc traced by a foot during a stride and the ground [26]. The theoretical parabola was calculated by the Optojump-next system through the stride length and the ▶ Fig. 1). The determaximal height of the foot during a stride (● mination of stride length was described above and the maximal height was calculated by the Optojump-next as follows: Height = g · (swing time)2/8, where g is the gravity (9.81 m · s−2).

Statistical analyses All values are expressed as mean ± standard deviation (SD) and coefficient of variation (CV). Statistical data analysis was performed using the Statistical Package for the Social Sciences 21.0 software package (StatSoft, Tulsa, OK, USA). Data were screened for normality of distribution and homogeneity of variances using a Shapiro-Wilk Normality Test and a Levene’s test, respectively. An

Table 1 Subject characteristics and maximal test results of the rearfoot strikes (n = 15) and midfoot/forefoot strikers (n = 15).

age, years 10-km time, min PTS, km · h−1 lactate threshold, km · h−1 VO2max, mL · kg−1 · min−1 RE, mL · kg−1 · km−1 height, cm mass, kg BMI % body fat

Rearfoot

Midfoot/forefoot

(n = 15)

(n = 15)

36.4 ± 7.0 34.3 ± 3.2 19.2 ± 1.8 16.4 ± 1.4 62.7 ± 6.2 213.4 ± 4.2 175.5 ± 6.0 65.2 ± 6.3 21.0 ± 1.5 10.4 ± 1.6

23.8 ± 10.8a 31.7 ± 1.4aa 20.6 ± 1.0a 17.8 ± 1.5a 63.5 ± 3.6 201.5 ± 5.6a 178.3 ± 5.5 66.0 ± 4.4 20.8 ± 1.4 9.5 ± 1.1

ES 1.38 1.05 0.96 0.96 0.15 2.40 0.48 0.14 0.13 0.65

Values are means ± SD. n, number of subjects; PTS, peak treadmill speed; BMI, body mass index; VO2max, maximum oxygen uptake; RE, running economy. ES, effect sizes (Cohen’s d). a Significantly different from rearfoot strikers (p < 0.05)

independent Student’s t-test was used to compare the means of both groups. Pearson’s product-moment correlations were used to assess the relationships between the stride angle and ground contact time with RE across the different rearfoot and midfoot/ forefoot groups. The relationships between ground contact time and RE were also analysed factoring in stride angle. The magnitude of differences or effect sizes (ES) were calculated according to Cohen’s d [5] and interpreted as small ( > 0.2 and < 0.6), moderate ( ≥ 0.6 and < 1.2) and large ( ≥ 1.2 and < 2) according to the scale proposed by Hopkins et al. [14]. Linear regressions were performed to analyse the relationships between stride angle with RE in rearfoot and midfoot/forefoot strikers, and 95 % confidence intervals were calculated. Linear regression assumptions were checked using residual vs. fitted, normal QQ and Cook’s distance plots. Significance for all analyses was set at p < 0.05.

Results



Descriptive characteristics and maximal treadmill test results of ▶ Table both rearfoot and midfoot/forefoot strikers are listed in ● 1. The midfoot/forefoot strikers were faster (p = 0.012, ES = 0.96) according to their best 10-km time than the rearfoot strikers. Similarly, midfoot/forefoot strikers achieved significantly faster PTS (p = 0.007, ES = 1.05), had a higher lactate threshold (p = 0.011, ES = 0.96) and a better RE than their rearfoot striking counter▶ Table 1). No significant differences parts (p = 0.019, ES = 2.40) (● were found in anthropometrical parameters between groups. No differences were found in stride length or stride frequency when running at 13.5 km · h − 1 between rearfoot and midfoot/ ▶ Fig. 2a, b). However, rearfoot strikers preforefoot strikers (● sented lower stride angles than the midfoot/forefoot strikers ▶ Fig. 2c) despite the absence of differ(p = 0.043; ES = 0.83) (● ▶ Fig. 2d). ences in the ground contact and swing time (● Considering the whole sample of runners (n = 30), and ignoring the effect of strike pattern, a simple linear regression analysis showed a significant relationship between stride angle and RE ▶ Fig. 3a). When analysing the relationship (r = 0.62, p < 0.001) (● between stride angle and RE according to the foot strike pattern, the correlation remained significant for both rearfoot strikers (r = 0.60, p = 0.019), and to a lesser extent, the forefoot strikers ▶ Fig. 3b). (r = 0.54, p = 0.037) (● To check the homogeneity of the regression slopes, the linear model including the stride angle and strike pattern interaction

Santos-Concejero J et al. Interaction Effects of Stride … Int J Sports Med 2014; 35: 1118–1123

This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.

(mlO2 · kg − 1 · min − 1) values collected during the last 30 s of the fastest velocity under the lactate threshold for all athletes (13.5 km · h − 1) were averaged and designated as steady-state running economy (mlO2 · kg − 1 · km − 1) for data analysis.

Orthopedics & Biomechanics

1121

Discussion

200 100 0

d

5 4

*

3 2 1 0

3 2 1 0

0.30

Time (seconds)

Stride angle (degrees)

c

0.25 0.20 0.15 0.10 0.05 0.00

Rearfoot strikers



4

Contact time

Swing time

Midfoot/forefoot strikers

Fig. 2 Stride length a, stride frequency b, stride angle c and ground contact and swing time d in rearfoot and midfoot/forefoot strikers at 13.5 m · s−1. *Significantly different from rearfoot strikers (p < 0.05).

RE (mL·kg–1 ·km–1)

a

250 230

All runners r= 0.62 ; p < 0.001

210 190 170

RE (mL·kg–1 ·km–1)

b

250 230

Midfoot/forefoot strikers r= 0.54 ; p= 0.037

210

Rearfoot strikers r= 0.60 ; p = 0.019

190 170 0

2 4 Stride angle (degrees)

Rearfoot strikers

6

Midfoot/forefoot strikers

Fig. 3 Relationships between stride angle and running economy for all runners a and for rearfoot and midfoot/forefoot runners taken separately b. 95 % confidence intervals are presented.

was compared in a model including only the main effects. An interaction effect was found as the model fit was significantly different between the 2 models (p < 0.001). This finding can be confirmed by a visual inspection of the plot of RE as a function of ▶ Fig. 3b). stride angle within the 2 groups (● Lastly, ground contact time was strongly related to RE (r = 0.60, p < 0.001), indicating that shorter ground contact times are associated with economical runners. However, when controlling for stride angle this significant relationship disappeared (r = 0.250, p = 0.350), evidencing the influence of stride angle on the relationships between RE and ground contact time.

The major finding of this study was that stride angle was significantly related to running economy in both rearfoot and midfoot/ forefoot strikers, although an interaction between stride angle and foot strike pattern was also observed. This is the first study in which the relationship between stride angle and running economy has been analysed while controlling for foot strike pattern. Stride angle was the only biomechanical variable in this study that differed between rearfoot and midfoot/forefoot strikers ▶ Fig. 2c). Additionally, the negawhen running at 13.5 km/h − 1 (● tive relationship found between running economy and stride angle in the whole sample of runners is consistent with previous studies reporting that higher stride angles are related to more efficient biomechanical running patterns [26]. Interestingly, when separating the runners into rearfoot and midfoot/forefoot strikers the slope of the regression lines ▶ Fig. 3b). between stride angle and running economy deviates (● This signifies the influence of foot strike pattern on the interaction between running economy and stride angle. Thus, when running at a stride angle < 4 °, midfoot/forefoot strikers appear to be more economical than rearfoot strikers. However, when the stride angle exceeds the aforementioned threshold, the relationship crosses over, suggesting a better running economy with a rearfoot striking pattern. The question arises whether this phenomenon would also occur when comparing a homogenous group of runners, since midfoot/forefoot strikers participating in this study were younger and faster than their rearfoot striking counterparts, which may contribute to the differences found in RE between groups. Previously, researchers have analysed the effect of other biomechanical variables on running economy, such as ground contact time, while controlling for the effect of strike pattern [8]. Di Michele et al. [8] reported no-interaction effect between strike patterns and ground contact times, implying that for a given contact time, midfoot strikers were more economical than rearfoot strikers, and more importantly, that longer contact times were related to a better running economy. Other studies reported no relationship between contact time and running economy [18, 29]. In contrast, this study found that shorter ground contact times are associated with economical runners (r = 0.60, p < 0.001), which is consistent with previous research [21, 23, 26]. Despite the positive relationship between ground contact time and RE described in this study, this relationship was not found when controlling for stride angle. Therefore, stride angle appears to affect not only the relationship between RE and strike pattern, but also the relationship between RE and ground contact time. This may explain why some studies found rearfoot strikers (with longer ground contact times) more economical than midfoot/ forefoot strikers [22], despite shorter contact times being associated with better RE [21, 26]. Similarly, the absence of differences in RE between midfoot/forefoot and rearfoot strikers was reported in other studies [6, 8, 24], since stride angle was a measure that was not controlled for. To the best of our knowledge, this is also the first study reporting a better running economy in midfoot/forefoot strikers than rearfoot strikers, although authors acknowledge that this difference may be partly due to differences in performance between groups and not just differences in the foot strike pattern. Other reasons include a better stretching of the foot arch and release of elastic energy from the Achilles tendon, which may allow both midfoot

Santos-Concejero J et al. Interaction Effects of Stride … Int J Sports Med 2014; 35: 1118–1123

This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.

b

300

Stride frequency (Hz)

Stride length (cm)

a

1122 Orthopedics & Biomechanics Acknowledgements



This study was supported by the Basque Government scholarship (ref. BFI08.51) to Jordan Santos-Concejero and by the Department of Physical Education and Sport of the University of the Basque Country (UPV/EHU).

Conflicts of interest: The authors report no conflict of interest. References 1 Ardigò LP, Lafortuna C, Minetti AE, Mognoni P, Saibene F. Metabolic and mechanical aspects of foot landing type, forefoot and rearfoot strike, in human running. Acta Physiol Scand 1995; 155: 17–22 2 Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 1982; 14: 377–381 3 Chapman RF, Laymon AS, Wilhite DP, McKenzie JM, Tanner DA, Stager JM. Ground contact time as an indicator of metabolic cost in elite distance runners. Med Sci Sports Exerc 2012; 44: 917–925 4 Cheng B, Kuipers H, Snyder AC, Keizer HA, Jeukendrup A, Hesselink M. A new approach for the determination of ventilatory and lactate thresholds. Int J Sports Med 1992; 13: 518–522 5 Cohen J. Statistical power analysis for the behavioural sciences. Hillsdale, NJ: Lawrence Erlbaum Associates, 1988 6 Cunningham CB, Schilling N, Anders C, Carrier DR. The influence of foot posture on the cost of transport in humans. J Exp Biol 2010; 213: 790–797 7 Debaere S, Jonkers I, Delecluse C. The contribution of step characteristics to sprint running performance in high-level male and female athletes. J Strength Cond Res 2013; 27: 116–124 8 Di Michele R, Merni F. The concurrent effects of strike pattern and ground-contact time on running economy. J Sci Med Sport 2013, doi:10.1016/j.jsams.2013.05.012 9 Dumke CL, Pfaffenroth CM, McBride JM, McCauley GO. Relationship between muscle strength, power and stiffness and running economy in trained male runners. Int J Sports Physiol Perform 2010; 5: 249–261 10 Gruber AH, Umberger BR, Braun B, Hamill J. Economy and rate of carbohydrate oxidation during running with rearfoot or forefoot strike patterns. J Appl Physiol 2013; 115: 194–201 11 Harriss DJ, Atkinson G. Ethical standards in sport and exercise science research: 2014 update. Int J Sports Med 2013; 34: 1025–1028 12 Hasegawa H, Yamauchi T, Kraemer WJ. Foot strike patterns of runners at the 15-km point during an elite-level half marathon. J Strength Cond Res 2007; 21: 888–893 13 Hayes P, Caplan N. Foot strike patterns and ground contact time during high-calibre middle-distance races. J Sports Sci 2012; 30: 1275–1283 14 Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc 2009; 41: 3–13 15 Howley ET, Bassett DR Jr, Welch HG. Criteria for maximal oxygen uptake: A review and commentary. Med Sci Sports Exerc 1995; 27: 1292–1301 16 Jones AM, Grassi B, Christensen PM, Krustrup P, Bangsbo J, Poole DC. Slow component of VO2 kinetics: mechanistic bases and practical applications. Med Sci Sports Exerc 2011; 43: 2046–2062 17 Kasmer ME, Liu XC, Roberts KG, Valadao JM. Foot-strike pattern and performance in a marathon. Int J Sports Physiol Perfom 2013; 8: 286–292 18 Kyrolainen H, Belli A, Komi PV. Biomechanical factors affecting running economy. Med Sci Sports Exerc 2001; 35: 45–49 19 Larson P, Higgins E, Kaminski J, Decker T, Preble J, Lyons D, McIntyre K, Normile A. Foot strike patterns of recreational and sub-elite runners in a long-distance road race. J Sports Sci 2011; 29: 1665–1673 20 Machado FA, Kravchychyn AC, Peserico CS, da Silva DF, Mezzaroba PV. Incremental test design, peak ‘aerobic’ running speed and endurance performance in runners. J Sci Med Sport 2013; 16: 577–582 21 Nummela A, Keränen T, Mikkelsson LO. Factors related to top running speed and economy. Int J Sports Med 2007; 28: 655–661 22 Ogueta-Alday A, Rodríguez-Marroyo JA, García-López J. Rearfoot striking runners are more economical than midfoot strikers. Med Sci Sports Exerc 2013 [Epub ahead of print] 23 Paavolainen LM, Nummela AT, Rusko HK. Neuromuscular characteristics and muscle power as determinants of 5-km running performance. Med Sci Sports Exerc 1999; 31: 124–130

Santos-Concejero J et al. Interaction Effects of Stride … Int J Sports Med 2014; 35: 1118–1123

This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.

and forefoot strikers to save metabolic energy [24] and shorter ground contact times [8, 10, 12], which have been related to increased leg stiffness and subsequent better running economy [9, 21]. However, our findings contrast with previous studies that have reported no differences between running economy and strike patterns [1, 8] or even better running economy in rearfoot strikers [22]. As stated previously, rearfoot strikers were older than the midfoot/forefoot strikers, possibly complicating the comparison between groups. The prevalence of midfoot and forefoot strikers among elite runners has previously been observed [12, 17], which may indicate that a midfoot/forefoot strike pattern is a desirable biomechanical feature. Another limitation was that since a heterogeneous group of runners with best 10-km race times ranging from 29 to 38 min was analysed, the reported better running economy in midfoot/forefoot strikers could be due to differences in performance and not to a more efficient strike pattern. This may explain why other studies found opposite relationships when analysing homogenous group of runners [22]. An additional concern is that kinematics analysed in this study might vary from over-ground running and motorized treadmill running [25]. However, even if not strictly equivalent, the features of kinematic trajectories of treadmill gait have been found to be similar to over-ground gait. Therefore, treadmill-based analysis of running gait has been suggested to be reliable when running under well-controlled and reproducible condition [25], which was the case for our study. An additional factor to consider is that LEDs of the Optojump-next system are positioned at 0.3 cm from bottom of the bars and the bars are placed at the treadmill belt level. When running, the belt of the treadmill rebounds at the point of ground contact. Ground contact maybe influenced if the treadmill belt is not level with the LEDs of the optical measurement device as it may be deeper due to belt compression. Additionally, when running at a slow speed (13.5 km · h − 1) some runners may have struggled to disrupt the infrared gates of the Optojump-next system due to their short swing times. This may influence the maximum foot height calculated, consequently influencing stride angle. In summary, this study found that running economy at submaximal speed is affected by both strike pattern and stride angle and that the relationships between running economy and ground contact time are largely influenced by stride angle. The present results suggest that a biomechanical running technique characterised by high stride angles seems to be desirable in both midfoot/forefoot and rearfoot strikers. In addition, the interaction effect described in this study between the stride angle and the foot strike pattern provides an explanation for the discrepancies previously reported in the literature about which foot strike pattern is more economical. Thus, a midfoot/forefoot strike pattern is more desirable when running with a stride angle below an arbitrary value of 4 °, since it correlates to a better RE. In contrast, if this angle is higher than the aforementioned threshold, a rearfoot strike pattern is likely to be more economical. By working on the running technique and mechanics including specific exercises designed to achieve higher stride angles during running training sessions, athletes may find the way to improve their running economy independently of their preferred foot strike pattern.

Orthopedics & Biomechanics

28 Stewart A, Marfell-Jones M, Olds T, de Ridder H. International standards for anthropometric assessment. Lower Hutt: International Society for the Advancement of Kinanthropometry, 2011 29 Storen O, Helgerud J, Hoff J. Running stride peak forces inversely determine running economy in elite runners. J Strength Cond Res 2011; 25: 117–123 30 Yuhasz MS. Physical fitness Manual. London, Ontario: University of Western Ontario, 1974

This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.

24 Perl DP, Daoud AI, Lieberman DE. Effects of footwear and strike type on running economy. Med Sci Sports Exerc 2012; 44: 1335–1343 25 Riley PO, Dicharry J, Franz J, Della Croce U, Wilder RP, Kerrigan DC. A kinematics and kinetic comparison of overground and treadmill running. Med Sci Sports Exerc 2008; 40: 1093–1100 26 Santos-Concejero J, Tam N, Granados C, Irazusta J, Bidaurrazaga-Letona I, Zabala-Lili J, Gil SM. Stride angle as a novel indicator of running economy in well-trained runners. J Strength Cond Res 2013, doi:10.1519/ JSC.0000000000000325 27 Santos-Concejero J, Tucker R, Granados C, Irazusta J, BidaurrazagaLetona I, Zabala-Lili J, Gil SM. Influence of regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and running performance. J Sports Sci 2013; 32: 853–859

1123

Santos-Concejero J et al. Interaction Effects of Stride … Int J Sports Med 2014; 35: 1118–1123

Copyright of International Journal of Sports Medicine is the property of Georg Thieme Verlag Stuttgart and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.

Interaction effects of stride angle and strike pattern on running economy.

This study aimed to investigate the relationship between stride angle and running economy (RE) in athletes with different foot strike patterns. 30 mal...
361KB Sizes 5 Downloads 5 Views