Impact of Limb Loading Asymmetry during Walking on Hip and Knee Function in Community-Dwelling Older Adults: A Prospective Cohort Study
Bibliographic record
Abstract
The aim of this study is to determine the impact of limb loading asymmetry while walking on hip and knee function in community-dwelling older adults. Our findings suggest that increased asymmetry of limb loading on midfoot during walking is a predictor of deterioration in hip and knee function. Given that biofeedback of limb loading has been reported to help improve movement patterns, providing biofeedback to patients with OA during exercise may prevent deterioration in hip and knee function. The findings of the present study have important implications for the prevention and management of hip and knee function deterioration in the community-dwelling older adults. Participants aged ≥ 65 years were registered at a community-based health check investigation in Fukushima, Japan They completed questionnaires on their medical history, underwent physical tests at baseline (T0; n = 98 [82 female]; mean age 74.8 ± 5.7 years), and were then prospectively followed for one year (T1; n = 67). The primary outcome measure was assessed using the Western Ontario and McMaster Universities Osteoarthritis index (WOMAC) at T0 and T1, and was defined as the WOMAC delta score (the WOMAC summary score at T0 minus the WOMAC summary score at T1). Limb loading was measured using force sensing insoles capable of measuring three foot regions (rearfoot, midfoot, and forefoot) as well as overall during a ten-meter walking test, and was defined as peak force asymmetry (PFA) and impulse asymmetry (IA) at T0. Associations between changes in WOMAC scores and both PFA and IA on three foot regions and overall were determined using correlation analyses. Multiple linear regression analyses were performed with changes in WOMAC scores as the outcome variable, PFA and/or IA of any region as the explanatory variables, and age, sex, body height and weight, foot posture, and walking speed as confounding variables. Overall PFA and midfoot IA were significantly correlated with changes in WOMAC scores (r = 0.244, r = 0.047; r = -0.290, r = 0.017, respectively). Multiple linear regression analysis with overall PFA and midfoot IA identified that the only characteristic retained was midfoot IA (β = -0.290, 95% CI: -0.685 to -0.068, p = 0.017).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".