Publication Date

2016

Journal or Book Title

PLoS ONE

Abstract

Background

Changes in knee kinematics have been identified in the early stages of osteoarthritis (OA). However, there is a paucity of information on the nature of kinematic change that occur with aging prior to the development of OA, This study applied a robust statistical method (Principal Component Analysis) to test the hypothesis that coupling between primary (flexion) and secondary (anterior-posterior translation, internal-external rotation) joint motions in walking would differ for age groupings of healthy subjects.

Methods

Seventy-four healthy participants divided into three groups with mean ages of 24 ± 2.3 years (younger), 48 ± 4.7years (middle-age) and 64 ± 2.4 years (older) were examined. Principal Component Analysis was used to characterize and statistically compare the patterns of knee joint movement and their relationships in walking.

Results

There were significant differences between the younger group and both the middle-age and older groups in the knee frontal plane angle and the coupling between knee flexion (PC1, p≤0.04) and the relative magnitudes of secondary plane motions in early and late stance (PC3, p<0.01). Two additional principal components (PC2, p = 0.03 and PC5, p<0.01) described differences in early stance knee flexion and relationship with secondary plane motion through-out stance for the older compared with middle-age group.

Conclusions

It appears there are changes in knee kinematics that occur with aging. The kinematic differences were identified for middle-aged as well as older adults suggesting midlife changes in neuromuscular physiology or behavior may have important consequences. These kinematic measures offer the potential to identify early markers for the risk of developing knee OA with aging.

DOI

http://dx.doi.org/10.1371/journal.pone.0167352

Volume

11

Issue

12

License

UMass Amherst Open Access Policy

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Funder

UMass SOAR Fund

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