Is the rearfoot pattern the most frequently foot strike pattern among
Physical Therapy in Sport 16 (2015) 29e33 Contents lists available at ScienceDirect Physical Therapy in Sport journal homepage: www.elsevier.com/ptsp Original research Is the rearfoot pattern the most frequently foot strike pattern among recreational shod distance runners? Matheus Oliveira de Almeida a, b, *, Bruno Tirotti Saragiotto a, b, Tiê Parma Yamato a, b, Alexandre Dias Lopes a, b a b Masters Program in Physiotherapy, Universidade Cidade de São Paulo (UNICID), Rua Cesário Galeno 448, Tatuapé, CEP 03071-000, São Paulo, SP, Brazil São Paulo Running Injury Group (SPRunIG), São Paulo, Brazil a r t i c l e i n f o a b s t r a c t Article history: Received 10 June 2013 Received in revised form 5 February 2014 Accepted 13 February 2014 Objective: To determine the distribution of the foot strike patterns among recreational shod runners and to compare the personal and training characteristics between runners with different foot strike patterns. Design: Cross-sectional study. Setting: Areas of running practice in São Paulo, Brazil. Participants: 514 recreational shod runners older than 18 years and free of injury. Outcomes measures: Foot strike patterns were evaluated with a high-speed camera (250 Hz) and photocells to assess the running speed of participants. Personal and training characteristics were collected through a questionnaire. Results: The inter-rater reliability of the visual foot strike pattern classiﬁcation method was 96.7% and intra-rater reliability was 98.9%. 95.1% (n ¼ 489) of the participants were rearfoot strikers, 4.1% (n ¼ 21) were midfoot strikers, and four runners (0.8%) were forefoot strikers. There were no signiﬁcant differences between strike patterns for personal and training characteristics. Conclusion: This is the ﬁrst study to demonstrate that almost all recreational shod runners were rearfoot strikers. The visual method of evaluation seems to be a reliable and feasible option to classify foot strike pattern. Ó 2014 Elsevier Ltd. All rights reserved. Keywords: Running Jogging Biomechanics Sports 1. Introduction Foot strike patterns during running have been the subject of investigation for the past three decades (Cavanagh & Lafortune, 1980; Kerr, Beauchamp, Fikhkr, & Neil, 1983); however comparisons between studies are difﬁcult because different classiﬁcation criteria exist (Lieberman, 2012). Conventionally, foot strike patterns are deﬁned by the part of the foot that ﬁrst contacts the running surface and this is typically divided into three categories: (1) rearfoot strike, when the runner lands with the heel; (2) midfoot strike, when the runner simultaneously lands with the heel and ball of the foot; and (3) forefoot strike, when the ball of the foot lands ﬁrst (Fellin, Rose, Royer, & Davis, 2010; Lieberman et al., 2010). Several factors can inﬂuence the adoption of foot strike patterns during running. The use of running shoes with cushioning on the * Corresponding author. Universidade Cidade de São Paulo, Rua Cesário Galeno 448, Tatuapé, São Paulo, SP, CEP 03071-000, Brazil. Tel.: þ55 11 982737246. E-mail address: [email protected] (M.O. de Almeida). http://dx.doi.org/10.1016/j.ptsp.2014.02.005 1466-853X/Ó 2014 Elsevier Ltd. All rights reserved. posterior portion of the shoe may induce a rearfoot pattern (Lieberman et al., 2010; Squadrone & Gallozzi, 2009), while running speed and instructions from coaching staff could also inﬂuence the pattern adopted by runners (Giandolini et al., 2013; Nilsson & Thorstensson, 1989). The adoption of certain foot strike strategies has received special attention because how the foot lands during running can lead to different kinematic and kinetic characteristics of the lower extremities (Goss & Gross, 2012b). The rearfoot pattern is characterized by a rapid, high impact peak in the ground reaction force after the initial contact with the ground (Cavanagh & Lafortune, 1980; Laughton, McClay Davis, & Hamill, 2003; Lieberman et al., 2010), generating high vertical loading rates (Arendse, Noakes, Azevedo, Romanov, Schwellnus, & Fletcher, 2004; Shih, Lin, & Shiang, 2013; Williams, McClay, & Manal, 2000). On the other hand, forefoot and midfoot patterns do not demonstrate a marked impact peak, and the vertical forces are transmitted to the lower extremities in a more spread out way, attenuating the overload that occurs when the foot collides with the ground through eccentric control of the triceps surae (Cavanagh & Lafortune, 1980; Lieberman et al., 2010). 30 M.O. de Almeida et al. / Physical Therapy in Sport 16 (2015) 29e33 It is believed that high vertical loading rates transmitted to the lower limbs during running may contribute to the high incidence of speciﬁcally running-related injuries (Pohl, Hamill, & Davis, 2009; Zadpoor & Nikooyan, 2011). Because of that, rearfoot strikers may be more susceptible to injuries characterized by overloads in the lower extremities, such as tibial stress fractures, plantar fasciitis, and anterior knee pain (Davis, Bowser, & Mullineaux, 2010; Pohl et al., 2009; Zadpoor & Nikooyan, 2011). In contrast, forefoot strikers, due to the increased eccentric activity of the triceps surae and high demand at the foot and ankle (Williams, Green, & Wurzinger, 2012; Williams et al., 2000), may be more at risk of developing Achilles tendinopathy and calf muscle injuries. Unfortunately, investigation of injury rates comparison between foot strike patterns is scarce in the literature. Only two retrospective studies examined and found signiﬁcantly higher rates of injury in rearfoot strikers (Daoud, Geissler, Wang, Saretsky, Daoud, & Lieberman, 2012; Goss & Gross, 2012a). Some studies (Hasegawa, Yamauchi, & Kraemer, 2007; Kerr et al., 1983; Larson et al., 2011) evaluated the distribution of the foot strike patterns among shod runners at different levels (elite, sub-elite and recreational) and found that the rearfoot pattern is the most common. However, important differences in the distribution of patterns were found, principally when elite runners are compared with recreational runners, suggesting that runners at different levels may demonstrate different foot strike patterns. Furthermore, all these studies were conducted during a competitive race setting and foot strike patterns were determined through the analysis of only a single stride. These factors may limit their ﬁndings of foot strike pattern distribution only to the conditions cited above. The previous studies (Hasegawa et al., 2007; Kerr et al., 1983; Larson et al., 2011) also did not account for running speed during data acquisition or other personal characteristics that may inﬂuence strike patterns. While the available literature highlights the possible effects of running pattern on injury risk, the knowledge of foot strike pattern distribution among recreational runners is an important ﬁrst step for clinicians and researchers that deal with running injuries. Therefore, the main objective of this study was to determine the distribution of the foot strike patterns among recreational shod runners not in race conditions. We also aimed to compare the personal and training characteristics between runners with different foot strike patterns. 2. Methods A convenience sample of 514 runners was used in this crosssectional study. The participants were recruited in areas of high runner trafﬁc (such as public parks) in São Paulo, Brazil. Participants were eligible for inclusion if they were recreational runners at least 18 years old and free of musculoskeletal injury at the time of data acquisition. Participants were evaluated in shod conditions (conventional running shoes). Hereafter, the participants were instructed to run two 25 m laps on the track and run back to the start. A high-speed digital camera (Casio EXFX1) recording at a frequency of 250 Hz was located perpendicular to the runway at 12.5 m from the starting point. The camera was positioned on a tripod 15 cm above the ﬂoor and 2 m away from the runway (Fig. 1). The participants were instructed to run at a comfortable speed that was measured by a photocell timing mode (TC-Timing System). All data acquisition was done by three researchers. 2.2. Image analysis The videos with foot strike images were captured and subsequently analyzed visually in a subjective way using a video analysis program (KinoveaÔ 0.8.15). Each video was evaluated independently by two observers. In instances where there was disagreement among the observers, a third one was used. The foot strike pattern for each participant was analyzed from the lateral view of the foot and evaluated four times; two times on each foot. When the same runner demonstrated different patterns, the most frequently chosen pattern was used in the analysis. Foot strike patterns were classiﬁed in three categories (Lieberman et al., 2010): (1) rearfoot, when the heel is the ﬁrst region to contact the ground (Fig. 2a); (2) midfoot, when the heel and ball of the foot simultaneously contact the ground (Fig. 2b); and (3) forefoot, when the ball of the foot contacts the ground prior to the heel (Fig. 2c). 2.3. Statistical analysis Descriptive analyses were used to evaluate the relationship between foot strike patterns and the participants’ characteristics. Normality of continuous data (age, weight, body mass index, weekly distance, years of practice, average speed and Hshoes) was evaluated using curve symmetry analysis. Data with normal distribution were described in mean and standard deviation. Median and interquartile ranges were used for non-normally distributed data. A KruskaleWallis test was conducted to compare the personal and training characteristics among rearfoot, midfoot and forefoot patterns. For all analyses, p < 0.05 was assumed to be statistically signiﬁcant. Intra and inter-rater reliabilities of the evaluation of the foot strike pattern from participants were evaluated using the agreement percentage. All analyses were performed in SPSS 17.0. 2.4. Sample size The sample size of this study was estimated based on a pilot study (Uribe, Almeida, Hespanhol Junior, & Lopes, in press) that 2.1. Data collection The 514 shod runners completed a questionnaire that contained demographic information (gender, age, weight and height) and running routine (predominant type of surface, special insoles, weekly distance, coach instruction and years of experience). Participants were also asked to identify any previous musculoskeletal injuries related to running in the last 12 months. The injury deﬁnition adopted was: “any musculoskeletal running related injury that was severe enough to prevent running practice during the last 12 months”. Fig. 1. Schematic representation of the area for image acquisition. M.O. de Almeida et al. / Physical Therapy in Sport 16 (2015) 29e33 31 Fig. 2. Foot strike patterns during running (2a e Rearfoot pattern; 2b e Midfoot pattern; 2c e Forefoot pattern). determined that 95% of participants would be rearfoot strikers. Statistical precision was assumed to be 2.5% with a signiﬁcance level of 0.01, which revealed a need for 506 runners. In this study, 514 runners were included to account for potential withdrawal or technical problems with data collection and video analysis. 3. Results Our sample was comprised of mostly males (68.9%, n ¼ 354), with a mean age of 41.7 (SD ¼ 12.2) years and a weekly running distance of 24.8 km (SD ¼ 20.7). The average speed from our sample during data collection was 12.2 km/h (SD ¼ 2.4). All the runners’ characteristics are detailed in Table 1. The inter-rater reliability of the visual foot strike pattern evaluation method was 96.7%, while the intra-rater reliability was 98.9%. None of the participants demonstrated an equal number of patterns (e.g., rearfoot twice and midfoot twice). 489 (95.1%) of the runners were rearfoot strikers, 21 (4.1%) were midfoot strikers, and only four runners (0.8%) were forefoot strikers (Table 2). The rate of the midfoot pattern was higher in male runners (5.1%, n ¼ 18) than in female runners (1.9%, n ¼ 3). There was no signiﬁcant difference for the average speed when the characteristics between foot strike patterns were compared. The average speed was 12.2 km/h (SD ¼ 2.3) in rearfoot strikers, 12.9 km/h (SD ¼ 3.3) in midfoot strikers and 12.9 km/h (SD ¼ 8.8) in forefoot strikers. There were no statistical differences among the three patterns for the other personal and training characteristics (Table 3). 4. Discussion This is the ﬁrst study to evaluate foot strike patterns among recreational shod runners not in race conditions. We found that Table 1 Characteristics of the recreational runners included in the study. Gender Male Female Age (years) Weigth (kg) Heigth (m) BMI (kg/cm2) Average Speed (km/h) Km/week Time of practice (years)* Previous injury Yes No 68.9% (354) 31.1% (160) 41.7 (12.2) 71.6 (12.7) 1.71 (0.09) 24.4 (3.0) 12.2 (2.4) 24.8 (20.7) 5 (9) Insoles Yes No Coach instruction Yes No Surface Hard 14% (72) 86% (442) 47.1% (242) 52.9% (272) 83.3% (428) Sand Grass 6.4% (33) 0.6% (3) Treadmill 9.7% (50) nearly all of these recreational runners used a rearfoot pattern (95.1%) and only four runners (0.8%) were forefoot strikers. There were more male midfoot strikers compared with female runners. No signiﬁcant differences were noted between rearfoot, midfoot and forefoot patterns for personal and training characteristics. In this study, we found a greater number of rearfoot strikers compared to previous studies. Larson et al. (2011), Kerr et al. (1983) and Hasegawa et al. (2007) found, respectively, that 88%, 80% and 75% of their participants were rearfoot strikers. These differences may be attributed to the subject sample and lower self-selected running speed. While we evaluated recreational runners who ran at an average of 12.2 km/h, Hasegawa et al. (2007) evaluated elite marathoners who ran between 17.7 and 19.6 km/h. Similarly, Kerr et al. (1983) used a sample of competitive runners who ran between 12.4 and 19.9 km/h. In the study by Larson et al. (2011), participants ran at a slower average pace of 11 km/h, which may explain the higher rate of rearfoot strikers. This was similar to our ﬁndings. The higher percentage of rearfoot strikers in our study and in Larson et al. (2011) conﬁrms that runners at different levels use different foot strike patterns. It is also possible that different methodologies of image acquisition contributed to a lower incidence of rearfoot strikers in the previous studies. It has been shown that the accuracy of foot strike classiﬁcation is directly related to the image acquisition frequency (Fellin et al., 2010). Previous studies that used video acquisition to determine strike pattern used cameras with video capture rates of 60 Hz (Kerr et al., 1983) and 120 Hz (Hasegawa et al., 2007). When image acquisition frequency is low, the exact moment of initial foot contact may not be discernible. Thus, the foot strike pattern may be erroneously classiﬁed; in particular, those who may have been rearfoot strikers may be identiﬁed as midfoot strikers. The method used to classify foot strike pattern in this study demonstrated an inter-rater reliability and intra-rater reliability of 96.7% and 98.9%, respectively. So, it is possible to conclude that the subjective visual method of foot strike pattern classiﬁcation is a reliable method, besides being a cheap and feasible way in comparison to methods used in other studies (Altman & Davis, 2012). There was a higher percentage of female rearfoot strikers runners compared to male runners. Similarly, there was a higher percentage of male midfoot strikers than female midfoot strikers, which is consistent with the results from Hasegawa et al. (2007). Despite this difference in foot strike patterns between genders, Table 2 Foot strike patterns of recreational runners. 33.1% (170) 66.9% (344) Continuous data with normal distribution are expressed in mean and standard deviation. Continuous data with non-normal distribution are expressed in median and interquartile range (Time of practice*). Categorical data are expressed in percentage and number of runners. Rearfoot Midfoot Forefoot Total n ¼ 514 Males n ¼ 354 Females n ¼ 160 95.1 (489) 4.1 (21) 0.8 (4) 94.1 (333) 5.1 (18) 0.8 (3) 97.5 (156) 1.9 (3) 0.6 (1) All data were expressed in percentage and numbers of runners. 32 M.O. de Almeida et al. / Physical Therapy in Sport 16 (2015) 29e33 Table 3 Comparison of the recreational runners’ characteristics between foot strike patterns. Gender Male Female Age (years) Weigth (kg) Heigth (m) BMI (Kg/cm2) Average speed (km/h) Distance (km/week) Experience (years)a Previous injury Yes No Insoles Yes No Coach instruction Yes No Surface Hard Sand Grass Treadmill Rearfoot n ¼ 489 Midfoot n ¼ 21 Forefoot n¼4 68.1% (333) 31.9% (156) 41.7 (12) 71.6 (12.7) 1.70 (0.1) 24.4 (2.3) 12.2 (2.3) 24.4 (20.7) 5 (9) 85.6% (18) 14.4% (3) 40.9 (14.9) 73.4 (13.9) 1.74 (0.1) 24 (3) 12.9 (3.3) 28.4 (17.9) 5 (9) 75% (3) 25% (1) 39.5 (48)a 63.5 (17.1)a 1.70 (0.1)a 21.4 (3.5)a 12.9 (8.8)a 37.5 (66)a 15 (36) 33.1% (162) 66.9% (327) 28.6% (6) 71.4% (15) 50% (2) 50% (2) 14.3% (70) 85.7% (419) 0% (0) 100% (21) 50% (2) 50% (2) 46.4% (227) 53.6% (262) 57.1% (12) 42.9% (9) 75% (3) 25% (1) 83.2% (407) 6.3% (31) 0.4% (2) 10% (49) 85.6% (18) 4.8% (1) 4.8% (1) 4.8% (1) 75% (3) 25% (1) 0% (0) 0% (0) p 0.22 0.90 0.32 0.26 0.10 0.52 0.09 0.26 0.70 0.06 0.33 0.90 Continuous data with normal distribution are expressed in mean and standard deviation. Categorical data are expressed in percentage and number of runners. a Continuous data with non-normal distribution are expressed in median and interquartile range. researchers who evaluated biomechanical variables found no signiﬁcant differences between genders for kinematic variables at the ankle, foot joint or the knee joint during the foot’s initial contact during running (Chumanov, Wall-Schefﬂer, & Heiderscheit, 2008; Ferber, Davis, & Williams, 2003). However, the inﬂuence of foot strike pattern was not speciﬁcally evaluated in those previous studies. Interestingly, we found no signiﬁcant differences in personal or training characteristics among the different foot strike patterns. Despite the low number of runners with midfoot and forefoot patterns that limited the comparative analyses, we expected to ﬁnd signiﬁcant differences between patterns, in particular, related to running speed and previous injuries. We believed that speed would be slower in rearfoot strikers as compared to midfoot and forefoot runners, as found in previous studies (Hasegawa et al., 2007; Kerr et al., 1983), but the difference was not signiﬁcant. We think a threshold of speed may exist to differentiate rearfoot strikers who are normally slower than midfoot and forefoot runners. Regarding previous injuries, 33% of the participants reported previous injuries in the last 12 months, but the difference was also not signiﬁcant among the different foot strike patterns. Although the possible effects of foot strike patterns on injury development has been not established in the literature, this rate of previous injury may be attributed to the fact that almost all of the participants in our study were rearfoot strikers. Because a rearfoot pattern is characterized by increased vertical loading rates, as compared to forefoot and midfoot patterns (Arendse et al., 2004; Shih et al., 2013; Williams et al., 2000), rearfoot strikers may be more susceptible to developing running injuries that are commonly related to overuse in the lower extremities (Hreljac, 2005). Despite a large sample size and high frequency of image acquisition, this study does have some limitations. Firstly, despite the subjective visual method of foot strike pattern classiﬁcation being a reliable and feasible method, it has limited ability to accurately classify runners with the midfoot pattern (Altman & Davis, 2012). Maybe the use of automatic foot strike detection algorithms could be an alternative method to avoid bias on foot strike classiﬁcation (De Witt, 2010; Hreljac & Marshall, 2000). Secondly, the time at which runners participated in this study was not standardized and thus occurred either before or after a recreational run. It is possible that fatigue may have affected the running pattern in these individuals, although the effect of fatigue on strike pattern preference has not been evaluated. Thirdly, we did not ask the participants about the length of time that they had been free of injury. We also did not attempt to measure the typical training pace of the participants which would have allowed us to conﬁrm if the speed collected during data acquisition was truly representative of the participants’ typical pace. Another limitation of this study was that we did not evaluate the stride length and step frequency of participants, although there is no consensus in the literature as to whether there are signiﬁcant differences among the different foot strike patterns regarding these aspects (Ardigo, Lafortuna, Minetti, Mognoni, & Saibene, 1995; Arendse et al., 2004; Squadrone & Gallozzi, 2009). Lastly, our study lacks additional comparative analysis between foot strike patterns due to the low number of runners from the midfoot and forefoot groups, preventing any inference from such analysis. The results of the present study are important because they demonstrated for the ﬁrst time that the great majority of recreational shod runners, when evaluated not in race conditions, are rearfoot strikers. The knowledge that the rearfoot pattern, the most common, is important for clinicians who that should be aware about the biomechanical characteristics of this pattern and its implications on running practice. Future studies should elucidate the possible relationship between foot strike pattern and injuries in recreational runners through studies with longitudinal design. Conclusions This is the ﬁrst study done not in race conditions to show that almost all recreational runners are rearfoot strikers. There were no signiﬁcant differences in personal or training characteristics between the three foot strike patterns. The visual method of evaluation seems to be a reliable and feasible option to classify foot strike pattern. Conﬂict of Interest None declared. Ethical Approval This study was approved in April 2011 by the Ethics Committee of the University of the City of São Paulo. Funding None declared. Acknowledgments The authors acknowledge Raphael Pereira, Luiz Hespanhol Júnior and Thais Lyrio for their help with this paper. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.ptsp.2014.02.005 M.O. de Almeida et al. / Physical Therapy in Sport 16 (2015) 29e33 References Altman, A. R., & Davis, I. S. (2012). A kinematic method for footstrike pattern detection in barefoot and shod runners. Gait and Posture, 35, 298e300. Ardigo, L. P., Lafortuna, C., Minetti, A. E., Mognoni, P., & Saibene, F. (1995). Metabolic and mechanical aspects of foot landing type, forefoot and rearfoot strike, in human running. Acta Physiologica Scandinavica, 155, 17e22. Arendse, R. E., Noakes, T. D., Azevedo, L. B., Romanov, N., Schwellnus, M. P., & Fletcher, G. (2004). Reduced eccentric loading of the knee with the pose running method. Medicine and Science in Sports and Exercise, 36, 272e277. Cavanagh, P. R., & Lafortune, M. A. (1980). Ground reaction forces in distance running. Journal of Biomechanics, 13, 397e406. Chumanov, E. S., Wall-Schefﬂer, C., & Heiderscheit, B. C. (2008). Gender differences in walking and running on level and inclined surfaces. Clinical Biomechanics, 23, 1260e1268. Daoud, A. I., Geissler, G. J., Wang, F., Saretsky, J., Daoud, Y. A., & Lieberman, D. E. (2012). Foot strike and injury rates in endurance runners: a retrospective study. Medicine and Science in Sports and Exercise, 44, 1325e1334. Davis, I. S., Bowser, B., & Mullineaux, D. (2010). Do impacts cause running injuries? A prospective investigation. ASB, 2010 [cited 2011 Dec 9]. Available from http:// www.asbweb.org/conferences/2010/abstracts/472.pdf. De Witt, J. K. (2010). Determination of toe-off event time during treadmill locomotion using kinematic data. Journal of Biomechanics, 43, 3067e3069. Fellin, R. E., Rose, W. C., Royer, T. D., & Davis, I. S. (2010). Comparison of methods for kinematic identiﬁcation of footstrike and toe-off during overground and treadmill running. Journal of Science and Medicine in Sport, 13, 646e650. Ferber, R., Davis, I. M., & Williams, D. S., 3rd (2003). Gender differences in lower extremity mechanics during running. Clinical Biomechanics, 18, 350e357. Giandolini, M., Arnal, P. J., Millet, G. Y., Peyrot, N., Samozino, P., Dubois, B., et al. (2013). Impact reduction during running: efﬁciency of simple acute interventions in recreational runners. European Journal of Applied Physiology, 113, 599e609. Goss, D. L., & Gross, M. T. (2012a). Relationships among self-reported shoe type, footstrike pattern, and injury incidence. US Army Medical Department Journal, 25e30. Goss, D. L., & Gross, M. T. (2012b). A review of mechanics and injury trends among various running styles. US Army Medical Department Journal, 62e71. Hasegawa, H., Yamauchi, T., & Kraemer, W. J. (2007). Foot strike patterns of runners at the 15-km point during an elite-level half marathon. Journal of Strength Conditioning Research, 21, 888e893. Hreljac, A. (2005). Etiology, prevention, and early intervention of overuse injuries in runners: a biomechanical perspective. Physical Medicine and Rehabilitation Clinics of North America, 16, 651e667, vi. 33 Hreljac, A., & Marshall, R. N. (2000). Algorithms to determine event timing during normal walking using kinematic data. Journal of Biomechanics, 33, 783e786. Kerr, B., Beauchamp, L., Fikhkr, V., & Neil, R. (1983). Foot strike patterns in distance running. Biomechanical aspects of sport shoes and playing surface. Calgary, Alberta. In Proceedings of the International Symposium on Biomechanical Aspects of Sports and Playing Surfaces. Larson, P., Higgins, E., Kaminski, J., Decker, T., Preble, J., Lyons, D., et al. (2011). Foot strike patterns of recreational and sub-elite runners in a long-distance road race. Journal of Sports Sciences, 29, 1665e1673. Laughton, C. A., McClay Davis, I., & Hamill, J. (2003). Effect of strike pattern and orthotic intervention on tibial shock during running. Journal of Applied Biomechanics, 19, 153e168. Lieberman, D. E. (2012). What we can learn about running from barefoot running: an evolutionary medical perspective. Exercise and Sports Science Reviews, 40, 63e72. Lieberman, D. E., Venkadesan, M., Werbel, W. A., Daoud, A. I., D’Andrea, S., Davis, I. S., et al. (2010). Foot strike patterns and collision forces in habitually barefoot versus shod runners. Nature, 463, 531e535. Nilsson, J., & Thorstensson, A. (1989). Ground reaction forces at different speeds of human walking and running. Acta Physiologica Scandinavica, 136, 217e227. Pohl, M. B., Hamill, J., & Davis, I. S. (2009). Biomechanical and anatomic factors associated with a history of plantar fasciitis in female runners. Clinical Journal of Sporst Medicine, 19, 372e376. Shih, Y., Lin, K. L., & Shiang, T. Y. (2013). Is the foot striking pattern more important than barefoot or shod conditions in running? Gait and Posture, 38, 490e494. Squadrone, R., & Gallozzi, C. (2009). Biomechanical and physiological comparison of barefoot and two shod conditions in experienced barefoot runners. Journal of Sports Medicine and Physical Fitness, 49, 6e13. Uribe, J. D. V., Almeida, M. O., Hespanhol Junior, L. C., & Lopes, A. D. Determination of the foot strike pattern in runners belonging to a running team. International SportMed Journal (in press) Williams, D. S., Green, D. H., & Wurzinger, B. (2012). Changes in lower extremity movement and power absorption during forefoot striking and barefoot running. International Journal of Sports Physical Therapy, 7, 525e532. Williams, D. S., McClay, I. S., & Manal, K. T. (2000). Lower extremity mechanics in runners with a converted forefoot strike pattern. Journal of Applied Biomechanics, 16, 210e218. Zadpoor, A. A., & Nikooyan, A. A. (2011). The relationship between lower-extremity stress fractures and the ground reaction force: a systematic review. Clinical Biomechanics, 26, 23e28.