Recognition of Foot Strike Pattern in Asian Recreational Runners - PubMed
- ️Tue Jan 01 2019
Recognition of Foot Strike Pattern in Asian Recreational Runners
Aurélien Patoz et al. Sports (Basel). 2019.
Abstract
Close to 90% of recreational runners rearfoot strike in a long-distance road race. This prevalence has been obtained from North American cohorts of runners. The prevalence of rearfoot strikers has not been extensively examined in an Asian population of recreational runners. Therefore, the aim of this study was to determine the prevalence of rearfoot, midfoot, and forefoot strikers during a long-distance road race in Asian recreational runners and compare this prevalence to reported values in the scientific literature. To do so, we classified the foot strike pattern of 950 recreational runners at the 10 km mark of the Singapore marathon (77% Asian field). We observed 71.1%, 16.6%, 1.7%, and 10.6% of rearfoot, midfoot, forefoot, and asymmetric strikers, respectively. Chi-squared tests revealed significant differences between our foot strike pattern distribution and those reported from North American cohorts (P < 0.001). Our foot strike pattern distribution was similar to one reported from elite half-marathon runners racing in Japan (Fisher exact test, P = 0.168). We conclude that the prevalence of rearfoot strikers is lower in Asian than North American recreational runners. Running research should consider and report ethnicity of participants given that ethnicity can potentially explain biomechanical differences in running patterns.
Keywords: asymmetry; biomechanics; endurance; foot strike pattern; running.
Conflict of interest statement
The authors declare no conflict of interest.
Figures
![Figure 1](https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec34/6628358/465e37a5c753/sports-07-00147-g001.gif)
Prevalence of rearfoot strike (RFS), midfoot strike (MFS), and forefoot strike (FFS) patterns by position of individuals in race (groups of 100 runners) at the 10 km mark of the Singapore marathon. Dashed lines depict linear least square regressions together with the respective coefficient of determination (R2).
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