The Influence of Weather Conditions on Joint Pain in Older People with Osteoarthritis: Results from the European Project on OSteoArthritis
Bibliographic record
Abstract
OBJECTIVE: This study examined whether daily weather conditions, 3-day average weather conditions, and changes in weather conditions influence joint pain in older people with osteoarthritis (OA) in 6 European countries. METHODS: Data from the population-based European Project on OSteoArthritis were used. The American College of Rheumatology classification criteria were used to diagnose OA in older people (65-85 yrs). After the baseline interview, at 6 months, and after the 12-18 months followup interview, joint pain was assessed using 2-week pain calendars. Daily values for temperature, precipitation, atmospheric pressure, relative humidity, and wind speed were obtained from local weather stations. Multilevel regression modelling was used to examine the pain-weather associations, adjusted for several confounders. RESULTS: The study included 810 participants with OA in the knee, hand, and/or hip. After adjustment, there were significant associations of joint pain with daily average humidity (B = 0.004, p < 0.01) and 3-day average humidity (B = 0.004, p = 0.01). A significant interaction effect was found between daily average humidity and temperature on joint pain. The effect of humidity on pain was stronger in relatively cold weather conditions. Changes in weather variables between 2 consecutive days were not significantly associated with reported joint pain. CONCLUSION: The associations between pain and daily average weather conditions suggest that a causal relationship exist between joint pain and weather variables, but the associations between day-to-day weather changes and pain do not confirm causation. Knowledge about the relationship between joint pain in OA and weather may help individuals with OA, physicians, and therapists to better understand and manage fluctuations in pain.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".