Relationships between pain, physical activity and sleep quality among older adults with radiographic knee osteoarthritis: findings from the Hertfordshire Cohort Study
Bibliographic record
Abstract
AIMS: To determine if the relationship between joint pain and sleep quality among individuals with osteoarthritis (OA) differs according to physical activity level among older adults. METHODS: 169 community-dwelling older adults in the UK Hertfordshire Cohort Study (aged 71-80) with radiographic knee OA completed a questionnaire. This included: the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC); the Pittsburgh Sleep Quality Index (PSQI); the Longitudinal Aging Study Amsterdam Physical Activity Questionnaire; and the Hospital Anxiety and Depression (HAD) Scale. Logistic regression was used to examine the WOMAC knee pain score in relation to having poor sleep quality (PSQI > 5) with adjustment for sex, age, and anxiety and depression scores; analyses were performed with and without stratification by physical activity category (bottom sex-specific tertile vs. not). RESULTS: Knee pain prevalence (WOMAC pain score > 0) was 40.7% among men and 46.6% among women; 37.0% of men and 50.0% of women reported poor sleep quality (PSQI > 5). Higher WOMAC pain scores were related to increased risk of poor sleep quality; odds ratio (95% CI) per unit increase in pain score: 1.15 (1.01,1.32), p = 0.038). Relationships were similar across physical activity levels. CONCLUSIONS: Relationships between joint pain and poor sleep quality among older adults with radiographic knee OA were similar, regardless of physical activity level. Our results highlight the high prevalence of both sleep disturbance and significant knee pain in this group, illustrating the need to consider supportive measures as appropriate in this population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".