Factors Affecting Physical Activity of People with Knee Osteoarthritis in Southern Taiwan: A Multiple Logistic Regression Analysis
Bibliographic record
Abstract
Background: Physical activity (PA) is a basic and initiative conservative management for people with knee osteoarthritis (KOA). This study aimed to explore the potential indicators of PA levels in people with KOA. Methods: We designed a cross-sectional study where people with KOA were consecutively approached by the Orthopedic Outpatient Department in a hospital in southern Taiwan. People older than 50 years that could communicate and consent to the present study were enrolled. As a dependent variable, the Chinese version of the Physical Activity Scale for the Elderly (PASE-C) was used to assess the participant's PA levels. Considering differences in sex, a PASE-C score cut-off point of 140 for men and 120 for women was used. Participants were then divided into "active" and "inactive" groups. We measured independent variables consisting of the demographic and clinical characteristics, such as comorbidities measured by the Charlson Comorbidity Index (CCI), depression status measured by the Geriatric Depression Scale-5, body mass index, KOA history (<5, 5-<10, and ≥10 years), knee pain (unilateral or bilateral), the severity of symptoms measured by the Western Ontario and McMaster Universities Osteoarthritis Index, and 6-meter preferred walking speed. Multiple logistic regression was performed to identify significant relationships between PA among people with KOA. Results: = 51) of participants were categorized as "active PA" (male: 32.1%; female: 25.0%). Multiple logistic regression showed a positive association of 6-meter preferred walking speed with active PA (OR: 7.08; 95% CI:1.14-44.13), whereas advanced age and comorbidity (CCI≥1 vs. CCI<1) were negatively associated with active PA with an OR (95% CI) score of 0.91 (0.86-0.97) and 0.37 (0.15-0.87), respectively. Conclusions: People with KOA require appropriate lifestyle management to increase PA. Walking speed may be an effective factor for predicting PA among people with KOA. Healthcare providers treating KOA patients should be aware of their PA levels, especially those at risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".