When, Where and How Osteoporosis-Associated Fractures Occur: An Analysis from the Global Longitudinal Study of Osteoporosis in Women (GLOW)
Bibliographic record
Abstract
OBJECTIVE: To examine when, where and how fractures occur in postmenopausal women. METHODS: We analyzed data from the Global Longitudinal Study of Osteoporosis in Women (GLOW), including women aged ≥55 years from the United States of America, Canada, Australia and seven European countries. Women completed questionnaires including fracture data at baseline and years 1, 2 and 3. RESULTS: Among 60,393 postmenopausal women, 4122 incident fractures were reported (86% non-hip, non-vertebral [NHNV], 8% presumably clinical vertebral and 6% hip). Hip fractures were more likely to occur in spring, with little seasonal variation for NHNV or spine fractures. Hip fractures occurred equally inside or outside the home, whereas 65% of NHNV fractures occurred outside and 61% of vertebral fractures occurred inside the home. Falls preceded 68-86% of NHNV and 68-83% of hip fractures among women aged ≤64 to ≥85 years, increasing with age. About 45% of vertebral fractures were associated with falls in all age groups except those ≥85 years, when only 24% occurred after falling. CONCLUSION: In this multi-national cohort, fractures occurred throughout the year, with only hip fracture having a seasonal variation, with a higher proportion in spring. Hip fractures occurred equally within and outside the home, spine fractures more often in the home, and NHNV fractures outside the home. Falls were a proximate cause of most hip and NHNV fractures. Postmenopausal women at risk for fracture need counseling about reducing potentially modifiable fracture risk factors, particularly falls both inside and outside the home and during all seasons of the year.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".