Association of Low Physical Activity Levels With Gait Patterns Considered at Risk for Clinical Knee Osteoarthritis...

Area of Science:

• Biomechanical Engineering
• Orthopedics
• Physical Therapy

Background:

• Gait analysis quantifies joint loading magnitude and patterns.
• Accelerometry measures loading frequency and physical activity levels.
• Understanding these loading components is crucial for managing knee osteoarthritis (OA) progression.

Purpose of the Study:

• To investigate the relationship between gait patterns associated with OA progression and accelerometer-derived loading frequency metrics.
• To determine if accelerometer metrics predict total knee arthroplasty (TKA) over a 3.5-year follow-up.

Main Methods:

• Fifty-seven knee OA patients underwent gait analysis and one week of accelerometer monitoring.
• Spearman correlations assessed relationships between gait and accelerometer data.
• Jonckheere-Terpstra tests analyzed differences across step count quartiles.
• Mann-Whitney U-tests compared baseline metrics between TKA and non-TKA groups.

Main Results:

• Gait variables linked to OA progression correlated with step count and moderate-to-vigorous physical activity.
• Individuals with lower step counts (~4000 steps/day) showed gait patterns associated with progression.
• No significant baseline accelerometer differences were found between patients who did or did not undergo TKA.

Conclusions:

• Complex interactions exist between gait, physical activity, and knee OA progression.
• Accelerometer metrics offer unique insights into loading for active individuals.
• For less active individuals, gait analysis may sufficiently predict short-term clinical progression risk.