A hierarchical cluster analysis to determine whether injured runners exhibit similar kinematic gait patterns.

Abstract:

:Previous studies have suggested that runners can be subgrouped based on homogeneous gait patterns; however, no previous study has assessed the presence of such subgroups in a population of individuals across a wide variety of injuries. Therefore, the purpose of this study was to assess whether distinct subgroups with homogeneous running patterns can be identified among a large group of injured and healthy runners and whether identified subgroups are associated with specific injury location. Three-dimensional kinematic data from 291 injured and healthy runners, representing both sexes and a wide range of ages (10-66 years), were clustered using hierarchical cluster analysis. Cluster analysis revealed five distinct subgroups from the data. Kinematic differences between the subgroups were compared using one-way analysis of variance (ANOVA). Against our hypothesis, runners with the same injury types did not cluster together, but the distribution of different injuries within subgroups was similar across the entire sample. These results suggest that homogeneous gait patterns exist independent of injury location and that it is important to consider these underlying patterns when planning injury prevention or rehabilitation strategies.

journal_name

Scand J Med Sci Sports

authors

Jauhiainen S,Pohl AJ,Äyrämö S,Kauppi JP,Ferber R

doi

10.1111/sms.13624

subject

Has Abstract

pub_date

2020-04-01 00:00:00

pages

732-740

issue

4

eissn

0905-7188

issn

1600-0838

journal_volume

30

pub_type

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