Associations between Bone Mineral Density and WOMAC Scores in Healthy Individuals: Insights from the Qatar Biobank
Bibliographic record
Abstract
BACKGROUND: Bone mineral density (BMD) is an indicator of bone health that predicts future bone fractures. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) is used to assess the severity of symptoms related to pain, stiffness, and function in diseased hip and knee joints. Here we assessed whether BMD measured at specific sites predicts WOMAC scores in healthy individuals whilst controlling for sociodemographic variables. METHODOLOGY: BMD, sociodemographic, and WOMAC data were collected from 1764 healthy adult individuals attending the Qatar Biobank (QBB). Multiple linear regression was used to examine associations between sociodemographic factors, total body BMD and BMD related to specific skeletal sites (including femoral (femoral neck and trochanter), trunk, pelvis and total spine), and the three WOMAC subscales (pain, stiffness, and physical function). RESULTS: = 0.091, ΔF(7, 1724) = 3.762, p < 0.001) after controlling for sociodemographic variables, with a higher total body BMD associated with an increase in compromised physical function. CONCLUSION: Total body BMD seems to be a more important predictor of stiffness and physical function than specific skeletal sites BMD measures. Monitoring BMD may have important implications for osteoarthritis patients.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".