Hormone therapy use in the Canadian Longitudinal Study on Aging: a cross-sectional analysis
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to assess the prevalence and factors associated with hormone therapy (HT) use among Canadian women. METHODS: Baseline data from the Tracking cohort of the Canadian Longitudinal Study on Aging (CLSA) was used for this analysis. The main outcome was HT use among women aged 45-85 years, defined as current, past, and never users. Multinomial logistic regression models were used to examine the differences between current, past, and never HT users in terms of sociodemographic, health behavior, and health-related variables. RESULTS: Overall, 9.5% of the sample reported current use of HT, whereas 21.9% reported past use. The main factors associated with a lower likelihood of current HT use were older age (>80 y), nonwhite ethnic background, current employment, regular smoking, obesity, and breast cancer. By contrast, alcohol consumption, and the presence of allergies or mood disorders were positively associated with current HT use. CONCLUSIONS: These findings provide a recent national picture of HT use in Canada that may be used to inform opportunities for improved physician-patient communication regarding menopause management.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".