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Volume 24, Issue 10, Pages 850-854 (December 2009)


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Static and dynamic correlates of the knee adduction moment in healthy knees ranging from normal to varus-aligned

Joaquin A. BarriosaCorresponding Author Informationemail address, Jill S. Higginsonbemail address, Todd D. Royercemail address, Irene S. Davisdemail address

Received 24 February 2009; accepted 27 July 2009. published online 25 August 2009.

Abstract 

Background

Individuals with medial knee osteoarthritis often present with varus knee alignment and ambulate with increased knee adduction moments. Understanding the factors that relate to the knee adduction moment in healthy individuals may provide insight into the development of this disease. Thus, this study aimed to examine the relationships of both static and dynamic lower extremity measures with the knee adduction moment. We hypothesized that the dynamic measures would be more closely related to this moment.

Methods

Arch height index, hip abduction strength and two static measures of knee alignment were recorded for 37 young asymptomatic knees that varied from normal to varus-aligned. Overground gait analyses were also performed. Correlation coefficients were used to assess the relationships between the static and dynamic variables to the knee adduction moment. Hierarchical regression analyses were then conducted using the static measures, the dynamic measures, and the static and dynamic measures together.

Results

Among the static measures, the tibial mechanical axis and the distance between the medial knee joint lines were correlated with the knee adduction moment. The best predictive static model (R2=0.53) included only the tibial mechanical axis. Among the dynamic variables, knee adduction and rearfoot eversion angles were correlated with the knee adduction moment. Knee adduction and rearfoot eversion, together, were the best dynamic model (R2=0.53). The static and dynamic measures together created the strongest of the three models (R2=0.59).

Conclusions

These results suggest that dynamic measures slightly enhance the predictive strength of static measures when explaining variation in the knee adduction moment.

a 300 College Park, University of Dayton, Dayton, OH45469, USA

b 201A Spencer Lab., University of Delaware, Newark, DE 19716, USA

c 144 Rust Ice Arena, 541 South College Avenue, University of Delaware, Newark, DE 19716, USA

d 305 McKinly Lab., University of Delaware, Newark, DE 19716, USA

Corresponding Author InformationCorresponding author.

PII: S0268-0033(09)00170-3

doi:10.1016/j.clinbiomech.2009.07.016


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