Runners can be classified as either rearfoot, midfoot, or forefoot strikers depending on the part of the foot that makes initial contact with the ground. A rearfoot strike (RFS) can be defined as when the heel of the foot/shoe makes initial contact with the ground. A midfoot strike (MFS) can be defined as when the heel and ball of the foot land simultaneously, and a forefoot strike (FFS) can be defined when the ball of the foot makes initial contact with the ground followed by the heel (6,21).
Although an RFS is more predominant among long-distance runners versus an MFS and an FFS, the percentage of an MFS and an FFS has been found to be greater among elite distance runners (14,16) (although this may be related, in part, to increased running speed). The higher prevalence of an FFS in elite runners has contributed to a recent subculture among recreational and competitive runners to adopt an FFS pattern, despite the majority naturally preferring an RFS (1,11). Of the hypothesized performance advantages for adopting an FFS running technique purported by certain members of the running community, among the most common is a reduction in the prevalence of lower limb injuries (23). Although a study by Walther (33) concluded that the overall injury prevalence is similar between foot strike techniques, with differences only observed in the nature and/or location of the injuries, a recent retrospective study by Daoud et al. (7) has shown that injury rates may indeed be lower among FFS when compared with RFS runners. Given the high incidence of running-related injuries (19.4%–79.3% of runners incur a lower limb injury annually (9,31)), it is becoming common practice for coaches to recommend an athlete change their foot strike technique (1) in attempts to mitigate injury risk.
However, despite the alleged advantage of FFS running for lowering injuries, how mechanical alterations are linked to differences/similarities in running mechanics and injury risk between foot strike techniques remains poorly understood. As a result, there is little empirical evidence supporting the rationale for switching between a habitual RFS to an imposed FFS technique (or vice versa). In context of sports injury prevention, misinterpretation of the factors that can contribute to injury and/or improve performance can have unintentional negative effects such as the implementation of an unsuccessful training intervention, or worse, unintentionally increasing an athletes’ risk of injury (2,8).
Recent studies indicate that joint kinetics may play a key functional role in differentiating between RFS and FFS running (35) and may help to reveal how different foot strike techniques could offer potential functional advantages/disadvantages. For example, greater peak plantarflexion moments, negative instantaneous joint power (power absorption), and negative work have been reported at the ankle in habitual FFS running, whereas greater peak knee flexion torque, negative power, and negative work are observed at the knee in habitual RFS running (13,17,19,25,27,35). Most of these alterations can be replicated by switching from an RFS to an FFS, notwithstanding the high ankle moments and peak negative ankle power in stance in habitual FFS runners (35). The different distribution of joint moments, negative power, and work observed between FFS and RFS runners may subsequently alter muscle and tendon function, leading to changes in the prevalence, location, and risk of musculoskeletal injury.
Although these previous studies investigating joint kinetics have provided crucial knowledge concerning foot strike biomechanics (13,17,19,25,27,35), none have provided a comprehensive analysis of the lower limb joint kinetics between RFS and FFS running that includes an analysis of both habitual and imposed techniques in both groups. To start with, the large majority of studies into foot strike technique have focused on the ankle and knee. No study to the authors’ knowledge has reported the effect of habitual and imposed foot strike techniques on joint moments, powers, and work at all of the major lower limb joints or their combined effect on the overall lower limb mechanics. This consideration is important given that any difference in ankle or knee joint mechanics may lead to functional adaptations at the hip joint that could also affect injury susceptibility and/or overall lower limb mechanics and thus running performance. Secondly, few articles report positive power, and to the authors’ knowledge, none report positive work in the context of foot strike technique. This is surprising because positive power and work affect muscular fatigue and energy use (26,30), and their inclusion can prove essential for understanding the complex interaction between foot strike technique, gait mechanics and energetics, and injury risk. Thirdly, and importantly, no study has examined rates of joint loading (average moment rate) or work production/absorption (average joint power) despite the known association between loading rates and injury (22,32) and the higher stride frequency in FFS running (12,28). Finally, with the exception of Hamill et al. (13), studies addressing the mechanics of altering foot strike technique have focused nearly exclusively on habitual RFS runners, and the effect on the above parameters when habitual FFS runners alter their technique to an RFS remains largely unknown. Consequently, our understanding of the potential merits of switching between either technique remains incomplete.
The purpose of this study was therefore to expand upon the recent work of Hamill et al. (13) to further determine what mechanical differences exist between RFS and FFS techniques in competitive runners at each of the major lower limb joints, and their effect on the overall lower limb mechanics. More specifically, we addressed two related questions: 1) How do the peak joint moments and peak instantaneous joint powers (both positive and negative) at the ankle, knee, and hip differ between foot strike techniques? 2) How does the average moment rate and the average power generation/absorption (and work) differ between foot strike techniques, both at the individual joints and in the combined lower limb? In each of these questions, we compared both habitual RFS and FFS runners and, importantly, also addressed the effect of switching between habitual and imposed foot strike techniques in both groups.
Sixteen trained competitive male distance runners were recruited for the study, with eight habitual RFS and eight habitual FFS runners. Those who landed with the heel and ball of their foot simultaneously (MFS runners) were not included because of their variable kinematic and kinetic profiles (7). Foot strike technique was confirmed using high-speed video recording at 100 Hz positioned in the sagittal plane (Basler A602fc-2, Ahrensburg, Germany). Participants ran 89 ± 35 km·wk−1 (mean ± SD) with a history of 7.5 ± 4.7 yr of running experience (mean ± SD). All runners were experienced in using their imposed running technique and had practiced using this technique in training runs. There were no significant differences in the age, height, or weight between RFS and FFS groups (age: RFS 21.9 ± 3.3 yr, FFS 23.6 ± 4.1 yr; height: RFS 187.1 ± 5.6 cm, FFS 184.6 ± 6.7 cm; weight: RFS 76.4 ± 3.4 kg, FFS 73.1 ± 8.9 kg; mean ± SD). The participants had not experienced any lower limb injuries in the 6 months before testing and presented without any preexisting gait abnormalities. Participants provided written, informed consent before partaking in the study. All procedures were approved by The University of Western Australia (UWA) Human Research Ethics Committee before the commencement of testing.
Joint kinematics and kinetics.
Participants completed a 5-min warm-up on a force-plate instrumented treadmill (Bertec Corporation, Columbus, OH) at 3.33 m·s−1 in their habitual foot strike technique. Participants were then allowed as long as they needed to familiarize themselves with the imposed foot strike technique. After the warm-up, participants were allowed to rest and their HR (Polar F1 Heart Rate Monitor, Kempele, Finland) return to within 10% of their resting value before commencing the measurement trials. Two running trials at 4.5 m·s−1 (a speed commonly used in the participants’ training) were completed: 1) habitual foot strike technique and 2) imposed technique, the order of which was randomized. Each measurement trial lasted for 2 min. All participants were provided with the same lightweight running footwear (Nike Lunaracer™).
Joint kinematic and kinetic data for the ankle, knee, and hip were computed using three-dimensional (3D) inverse-dynamic gait analysis. 3D segment motion was recorded using an eight-camera near-infrared 200 Hz Vicon MX 3D motion capture system (Oxford Metrics, Oxford, UK). Segment kinematics were computed from 34 retroreflective markers attached to the pelvis, lower limbs, and shoes using the lower body marker set outlined in the study of Besier et al. (4). Ground reaction forces from the instrumented treadmill were recorded at 2000 Hz and synchronized with the kinematic data using a Vicon MX-Net control box (Oxford Metrics). Lower limb biomechanical modeling was performed in accordance with the UWA lower body model (4). Ankle joint centers were defined as the midpoint between the medial and lateral malleoli anatomical landmarks. A six-marker pointer was used to identify the medial and lateral femoral condyles, with a functional knee helical axis to define knee joint centers and knee axes orientation. A functional method was also used to define the hip joint centers. A custom foot alignment rig was used to measure calcaneus inversion/eversion and foot abduction/adduction to define the anatomical coordinate system of the foot segment. All marker trajectories were filtered using a zero-lag fourth-order low-pass Butterworth filter with cutoff frequencies typically at 11 Hz, which was determined by a custom residual analysis algorithm for each participant (MATLAB; The MathWorks Inc., USA). Ground reaction forces were filtered at the same cutoff frequency as the kinematic data to mitigate any artifacts in joint moments arising because of unaccounted segment acceleration (5,18).
Net hip, knee, and ankle joint moments and instantaneous power from the right leg across the gait cycle were calculated using BodyBuilder software (Oxford Metrics). Peak positive and negative instantaneous powers and peak moments in the sagittal, frontal, and transverse planes were calculated during the stance phase and normalized to body mass. Net positive work (J·kg−1) and net negative work (J·kg−1) for each joint were computed by integrating the positive and negative instantaneous joint power data with respect to time, respectively:
where j represents the joint (ankle, knee or hip), P the joint power, and ti and tf represent the start and end time the integration respectively.
Positive and negative work at each joint (ankle, knee, and hip) was computed separately for the stance (as defined by a ground reaction force threshold of 10 N) and swing phases. The total combined limb work of the entire stride was subsequently computed as the sum of each joint’s (ankle, knee, and hip) work production. The rate of work production/absorption (referred to here as average power) during running was computed by multiplying the right leg’s joint work (either positive or negative, equations 1 and 2) at each joint across the stride by two (assuming bilateral symmetry) to represent both legs and dividing by the participant’s stride time. As an index of cumulative joint loading, the average rate of joint moment production (referred to here as average moment rate) was computed as the average joint moment during stance divided by the stride time ( N·m·s−1). We computed the average moment rate for both sagittal and nonsagittal moments. The percentage each joint contributed to the total stance positive and negative work and average power was computed by dividing the individual joint work during stance by the total stance work.
Five strides for each participant from each trial were selected for analysis and used to compute participant mean data. These data were used to assemble group mean data for each running condition (habitual RFS, habitual FFS, imposed RFS, and imposed FFS). Two-way mixed-model multivariate analyses of variance (MANOVA) were performed to determine whether any significant differences in peak joint moments and instantaneous powers, work and average power, and average moment rates existed between foot strike groups (between-subjects factors) and habitual versus imposed conditions (within-subjects factors). To address our questions, several multivariate analyses were performed. Joint level analyses included (a) peak joint moments and average moment rate (dependent variables: sagittal and nonsagittal plane moments and average moment rates in stance), (b) peak instantaneous power (dependent variables: positive and negative peak power in stance), and (c) work and average power (dependent variables: positive and negative work and average power in stance). A MANOVA was also performed on total lower limb work and total average power (dependent variables: total positive and negative work and average power over the stride) and the percentage contribution of each joint to the total positive and negative work/average power in stance (dependent variables: positive and negative contribution from the hip, knee, and ankle during stance). When significant multivariate effects were found (P < 0.05), we considered the univariate effects to determine what extent individual dependent variables contributed. As univariate effects only informed us of the significance at the dependent variable level, post hoc analyses were run to determine which foot strike/condition groups were significantly different from one another. Habitual RFS versus habitual FFS groups were compared using independent samples t-tests, and habitual RFS versus imposed FFS and habitual FFS versus imposed RFS were compared using paired samples t-tests. To guard against inflation of type I error rates due to multiple comparisons, a Bonferroni adjustment was applied to the univariate MANOVA results and subsequently also to the t-tests. The P value was set at 0.025 for peak moment, peak power, and average moment rate, to 0.0125 for work and average power, and to 0.0167 for the individual joint percentage contributions to total lower limb stance work and average power. The P value was set at 0.0167 for all t-tests.
Spatial–temporal gait parameters.
Stride and stance time were on average greater (4.4% and 13%, respectively) and stride frequency smaller (3.4%) in habitual RFS versus habitual FFS (Table 1). Of these, only stance time was statistically different (P = 0.013), which is in line with the literature (24,28). Swing times and duty factor (the fraction of the time spent in contact with the ground) were similar between habitual RFS and FFS. The only difference in spatial–temporal variables between habitual and imposed techniques was an increase in stride time when habitual FFS runners switched to an imposed RFS (Table 1, P = 0.037).
The effect of habitual and imposed foot strike techniques on peak joint moments and instantaneous power.
Peak plantarflexion moments were greater in both habitual and imposed FFS compared with habitual and imposed RFS, although these differences were not significant following the Bonferroni adjustment (Table 2 and Fig. 1). Ankle internal rotation moments were not different between habitual RFS and habitual FFS runners; however, they significantly increased when habitual RFS runners switched to an imposed FFS (33% increase, P = 0.012; Table 2 and Fig. 1). Similarly, peak instantaneous ankle power production increased between habitual RFS and imposed FFS running (21% increase, P = 0.005; Table 2 and Fig. 1). Peak instantaneous ankle power absorption was significantly greater in habitual FFS runners versus habitual RFS runners (45% greater, P = 0.011; Table 2 and Fig. 1), increased when habitual RFS runners switched to an imposed FFS (85% increase, P = 0.001), and decreased when habitual FFS runners switched to an imposed RFS (−21% decrease, P = 0.016).
Peak extension moments at the knee were not significantly different between habitual RFS and habitual FFS runners. However, when habitual FFS runners switched to an imposed RFS, the knee extension moment increased by 29% (P = 0.016). Knee abduction moments were significantly smaller in habitual FFS versus habitual RFS runners (−105%, P = 0.010), but when either group changed to their imposed foot strike technique, they did not alter their abduction moments (Table 2 and Fig. 1). Peak instantaneous power absorption at the knee was greater in all RFS conditions compared with FFS. There were no significant differences in either peak moments or powers at the hip joint between habitual RFS versus habitual FFS or when runners switched to an imposed technique (Table 2 and Fig. 1).
The effect of habitual and imposed foot strike techniques on work, average power, and average moment rate at the ankle, knee, and hip joints during stance.
No significant main effect of foot strike or condition was present in work, average power, average moment rate, or percentage contribution of each joint to total work and average power. However, there were significant interaction effects in all multivariate analyses (Tables 3 and 4). Significantly greater negative ankle average power (49.5%, P = 0.003; Table 3) was observed in habitual FFS versus habitual RFS runners. Post hoc tests also revealed a significant increase in ankle negative average power during stance in imposed FFS versus habitual RFS running (63%, P = 0.001) and habitual FFS versus imposed RFS (49%, P = 0.004) (Table 3). Positive average ankle power was not different between habitual RFS versus habitual FFS runners; however, when habitual RFS runners switched to an imposed FFS, it increased by 19.3% (P = 0.012). Similar differences in ankle work were observed to those of ankle average power (Table 3). The percentage contribution of the ankle joint to total negative lower limb work and average power during stance was significantly lower in an RFS technique compared with an FFS technique both when comparing habitual and imposed conditions (Fig. 2). The average plantarflexion moment rate was significantly greater in habitual FFS versus habitual RFS (31%, P = 0.001) and versus an imposed RFS (24%, P = 0.008) (Table 4). The average ankle internal rotation moment rate was significantly greater when habitual RFS runners switched to an imposed FFS (34%, P = 0.011; Table 4).
Negative knee average power during stance was significantly different across all conditions. Post hoc tests revealed that habitual RFS runners had 49% (P = 0.003) greater negative average power at the knee than habitual FFS runners and 45% (P < 0.001) greater negative average power than when they performed an imposed FFS technique. When habitual FFS runners switched to an imposed RFS, they had 40% (P = 0.001) greater negative average power at the knee (Table 3). The percentage contribution of the knee joint to total negative lower limb work and average power during stance was significantly greater in an RFS technique compared with an FFS technique both when comparing habitual and imposed conditions (Fig. 2). Similar to peak knee moments, the average knee extension moment rate was significantly greater when habitual FFS runners switched to an imposed RFS (16%, P = 0.002; Table 4). Despite not being statistically significant after a Bonferroni adjustment (P = 0.028), the knee abduction moment rate was 87% greater in habitual RFS versus habitual FFS runners, whereas there was only a 3% and 16% difference (nonsignificant) in habitual RFS versus imposed FFS and habitual FFS versus imposed RFS, respectively (Table 4).
After post hoc tests, there were no statistically significant differences in work, average power, or average moment rate at the hip joint between foot strike techniques or conditions (Tables 3 and 4). Although habitual RFS and habitual FFS runners produced a similar amount of positive average power during stance, a trend was present for greater (82%; P = 0.035) average power when habitual RFS runners switched to an imposed FFS. On the contrary, when habitual FFS runners switched to an imposed RFS, they produced 43% less average power (P = 0.091; Table 3). The hip contributed approximately the same percentage of total positive and negative work and average power (Fig. 2) in both RFS and FFS techniques.
The effect of habitual and imposed foot strike techniques on total lower limb work and average power.
Significant interaction effects were found for both total lower limb positive and negative average power (P < 0.001 and P = 0.002, respectively; Table 3). Post hoc tests revealed a significant increase in the total limb positive average power when habitual RFS runners switched to an imposed FFS (17%, P = 0.002; Table 3) and a significant decrease in the total lower limb positive average power when habitual FFS runners switched to an imposed RFS (−10.5%, P = 0.014; Table 3). There was a significant increase in the average total negative power when habitual RFS runners switched to an imposed FFS (8.9%, P = 0.007; Table 3). Differences in total lower limb work between habitual and imposed techniques were similar to those for average power and outlined in Table 3.
The higher prevalence of FFS running among elite athletes and the claims by some of reduced injury rates (7) have led to a tendency for both high-level and recreational athletes to adopt an FFS technique despite naturally preferring RFS running. In this investigation, we assessed joint- and limb-level mechanical differences both between habitual RFS and habitual FFS runners, as well as the effect of changing between foot strike techniques.
The difference between habitual running technique joint mechanics.
Our finding that habitual RFS and FFS runners did not differ in the amount of total lower limb mechanical work or average power when running at 4.5 m·s−1 indicates that one technique does not offer a clear-cut mechanical advantage over the other. This corroborates the recent finding by Gruber et al. (12) that no difference in metabolic cost exists between habitual RFS and FFS runners. It may instead be the altered loading profile and distribution of work and average power between lower limb joints, resulting in varying mechanical demands on the musculoskeletal system, that explains the functional effect of foot strike technique and injury risk.
The current study reinforces the notion that habitual RFS runners place more demand on the knee joint in both the sagittal and frontal planes, whereas habitual FFS runners placed more demand on the ankle joint in the sagittal plane (13,25,35). In a systematic review by van Gent (31), it is reported that 19.4%–79.3% of runners experience lower limb injuries each year with the knee being the predominant site of injury (7.2%–50%). Given that 75% of runners adopt an RFS technique (14), the high occurrence of knee injuries compared with other joints may be associated with the large mechanical demand that occurs at the knee during stance in RFS running. Although the lower mechanical demand at the knee might place habitual FFS runners at a lower risk of knee injury, the higher mechanical demand at the ankle might, on the other hand, place FFS runners at a greater risk of ankle-related injuries such as Achilles tendinopathy and/or rupture or eccentric loading injuries in the triceps surae group.
Although the mechanics of the stance phase itself dictates most of the differences between foot strike techniques, our study also shows, for the first time, that the rate of mechanical loading and thus the cumulative work and moment production also plays an important role. Indeed, we found a more pronounced difference in the average ankle moment rate and average negative ankle power in FFS versus RFS runners compared with differences in peak ankle moments and negative ankle work. In contrast, differences in the average knee moment rates and average negative knee power between foot strike techniques were smaller than those observed for peak knee moments and negative work. These findings suggests that the ankle in FFS running might be especially susceptible to cumulative overload injury, although the relative importance of peak and cumulative joint loading to musculoskeletal injury remains unclear.
By extending our measurements to include positive work and average power, we found that the ankle contributed equal amounts of positive work in habitual RFS and FFS running (Fig. 2A and E) even though there is greater negative work at the joint in FFS running. It is well known that the Achilles tendon is capable of storing energy absorbed at the ankle (negative work) as elastic strain energy and returning this energy to provide positive ankle joint work in the second half of stance (3,10,15,20). It is possible, therefore, that elastic recoil provides a greater contribution to positive work at the ankle in FFS runners. However, if this is the case, it does not translate to a benefit in the total metabolic cost of running (12).
The effect of switching technique: RFS to FFS.
For switching techniques to be effective as an injury prevention/management strategy, the aim is for the imposed technique to replicate the habitual mechanics. When habitual RFS runners were instructed to switch to an FFS technique, they were able to replicate the sagittal plane mechanics observed during habitual FFS running. However, despite there being no difference in ankle internal rotation moments or average moment rate between habitual RFS and habitual FFS runners, an imposed FFS increased these variables by 33% and 34%, respectively, (P = 0.012 and P = 0.011). In addition, the lower abduction moments about the knee joint in habitual FFS versus RFS runners reported here and in the study of Kulmala et al. (19) were not replicated in imposed FFS running. Considering that knee abduction moments possibly have a stronger link to knee injuries (29,34), as well as the increase in ankle transverse plane loading in imposed FFS running, calls to question the advice some coaches are giving to their athletes to change from an RFS to an FFS to reduce their injury risk.
Furthermore, when habitual RFS runners switched to an imposed FFS technique, the total positive average power and the total negative average power increased by 17% and 9%, respectively, (Table 3). This increase in mechanical cost is possibly related to an increase in muscle work and power and thus may be detrimental to running performance. This provides a possible explanation for the recent results of Gruber et al. (12) who found oxygen consumption increased when habitual RFS runners changed to an imposed FFS. The source of the increase in positive average power in imposed FFS running is primarily at the ankle and hip joints (despite a nonsignificant difference at the hip joint after Bonferroni correction), whereas the increase in negative average power is primarily at the ankle joint. It is possible that the elastic mechanisms at the ankle are not as well developed in habitual RFS runners, and therefore, increased work at the hip joint is required to maintain the required work output. The prospect that the calf musculature in habitual RFS runners may limit their ability to effectively adopt an FFS technique was highlighted in a study by Williams et al. (35) where RFS runners who performed a training session using an FFS experienced significant calf fatigue and delayed onset muscle soreness.
The effect of switching technique: FFS to RFS.
In contrast to habitual RFS runners switching technique, when habitual FFS runners adopt RFS running, they are able to replicate all of the joint mechanical characteristics of habitual RFS runners with the exception that they do not increase their frontal plane knee loads (peak abduction moment and average moment rate were 62% and 61% lower than habitual RFS running, respectively). In addition, performing an imposed RFS required 10.5% less positive mechanical average power in the limb to maintain the same running speed. These findings were surprising, suggesting that switching to an imposed RFS could prove a useful strategy for injury rehabilitation while not affecting mechanical performance negatively. More specifically, using an imposed RFS in training may be useful to lower the ankle and Achilles tendon loading in athletes with ankle instability or tendon pathology/injury while at the same time reducing the overall average power, which may help mitigate fatigue.
Contrary to popular claims by some in the running community, this study found no clear mechanical advantage of habitual FFS running over habitual RFS running. Switching between RFS and FFS running techniques may have implications for injury reduction/recovery given the altered distribution in loading between joints but should be weighed against possible overall performance decrements/improvements. Switching from a habitual RFS to an imposed FFS may be detrimental to overall performance because of an increase in both positive and negative average lower limb power, which can help explain the recent finding that imposed FFS running also requires more metabolic energy (12). Furthermore, considering that the high knee abduction moments were not reduced by adopting an FFS technique questions the extent that switching technique will lower knee injury susceptibility. Habitual FFS runners can replicate the joint dynamics of a habitual RFS technique without incurring high knee abduction moments while, surprisingly, also lowering their positive average limb power. In this last regard, FFS runners adopting an imposed RFS technique, rather than the opposite, may prove the most useful training/rehabilitation strategy given the absence of clear mechanical performance decrements. It should be stated, however, that further research is needed to determine whether these findings hold following a training intervention. Nevertheless, this study stands in contrast to the strategy of switching from an RFS to an FFS which is avidly promoted by certain members of the running community (11,23).
The authors would like to thank the participants for taking part in this study, Dr. Ben Jackson from the University of Western Australia for his assistance with the statistics analysis, and two anonymous referees for their valuable comments and constructive suggestions.
S. M. S. was supported through an Australian Postgraduate Award scholarship.
No external funding was received for this work. None of the authors involved in the present study have any conflict of interest, financial, personal, or otherwise, that would influence this research, and the results do not constitute endorsement by the American College of Sports Medicine.
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