An update of the prevalence of osteoporosis, fracture risk factors, and medication use among community-dwelling older adults: results from the Canadian Longitudinal Study on Aging (CLSA)
Bibliographic record
Abstract
The prevalence of self-reported and DXA-confirmed osteoporosis was 7.8% (males 2.2%; females 12.7%), and 3.6% (males 1.2%; females 5.9%), respectively. We found that most community-dwelling older adults at high fracture risk are not taking osteoporosis medication, particularly males. There is a major opportunity for improved primary fracture prevention in the community. PURPOSE: To provide an up-to-date prevalence estimate of osteoporosis, fracture risk factors, fracture risk, and the proportion of older Canadians at high fracture risk who are not taking an osteoporosis medication. METHODS: We included Canadian Longitudinal Study on Aging (CLSA) participants: a community-dwelling cohort aged 45 to 85 years who completed the baseline (2015) comprehensive interview and had dual-energy X-ray absorptiometry (DXA) scans (N = 30,097). We describe the age- and sex-stratified prevalence of (1) self-reported osteoporosis; (2) DXA-confirmed osteoporosis; (3) fracture risk factors and people who are at high risk (FRAX® major osteoporotic fracture probability ≥ 20%); and (4) people who are at high fracture risk not taking osteoporosis medications. Sampling weights, as defined by the CLSA, were applied. RESULTS: The mean age of participants was 70.0 (SD 10.3). Overall, 7.8% had self-reported osteoporosis (males 2.2%; females 12.7%) while 3.6% had DXA-confirmed osteoporosis (males 1.2%; females 5.9%), and 2.8% were at high fracture risk (males 0.3%; females 5.1%). Of people who had osteoporosis and were at high risk, 77.3% were not taking an osteoporosis medication (males 92.3%; females 76.8%). CONCLUSIONS: Our study provides an up-to-date prevalence estimate of osteoporosis for community-dwelling older Canadians. We found that most community-dwelling older adults at high fracture risk are not taking an osteoporosis medication, particularly males. There is a major opportunity for improved primary fracture prevention in the community.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.015 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".