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Biomechanical predictors of retrospective tibial stress fractures in runners

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Pohl, Michael B., Mullineaux, David R., Milner, Clare E., Hamill, Joseph, Davis, Irene S.·2008·Journal of Biomechanics

Abstract

Both kinematics and kinetics of the lower limb have been shown separately to be related with a history of tibial stress fractures (TSFs) in female runners. However, it is likely that these factors interact together to increase the risk of a TSF. This study was conducted to determine which combination of kinematic and kinetic factors are the best predictors of retrospective TSF in female distance runners. Total 30 female runners who had previously sustained a TSF were recruited, along with an age and mileage matched control group (n=30). Subjects ran overground at 3.7m/s while kinematic and kinetic data were recorded. Five trials from each subject were used for data analysis and ensemble means were calculated for both groups. The kinematic variables of peak hip adduction (HADD), peak knee internal rotation (KIR) and knee adduction (KADD), peak rearfoot eversion (RFEV) were entered into a binary logistic regression along with the kinetic variables of vertical instantaneous load rate (VILR) and absolute free moment (FM). The variables HADD, FM and RFEV were able to correctly predict a history of TSF in 83% of cases. Increases in HADD, FM and RFEV (odds ratios of 1.29, 1.37 and 1.18) were associated with an elevated risk of having a history of TSF. The addition of VILR, KIR and KADD did not improve the ability to predict previous injury. Based on these results, HADD, FM and RFEV appear to be the most important of the variables of interest in terms of predicting retrospective TSF in female runners.

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Crossref · 10.1016/j.jbiomech.2008.02.001

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Metadata

Authors
Pohl, M. B., Mullineaux, D. R., Milner, C. E., Hamill, J., & Davis, I. S.
Venue
Journal of Biomechanics
Publisher
Elsevier BV
Published
2008
Volume
41
Issue
6
Pages
1160-1165
ISSN
0021-9290 (ISSN-L)
OpenAlex
W2125127344
Cited by
333
References
0
FWCI
4.48
Type
journal article
Language
en
Open access
green

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