Earlier menopause is associated with higher risk of incident frailty in community‐dwelling older women in England
Bibliographic record
Abstract
BACKGROUND: Although it is well known that women have higher risk of frailty, mechanisms are not clear. Reproductive history may be related to the sex difference in frailty. METHODS: A total of 1249 community-dwelling women aged ≥60 in England were examined for associations between age at menopause and risk of developing frailty. Frailty defined by the frailty phenotype was measured at baseline and 4 years later. Age at menopause was used as a continuous variable and categorical groups: premature/early (10-45 years), normal (46-55 years), and late (56 years or older). Men with comparable conditions from the same cohort were also used as a comparison. RESULTS: Earlier age at menopause was significantly associated with higher risk of incident frailty. One year later menopause age was associated with a 3% decrease in incident frailty risk (Odds ratio [OR] = 0.97, 95%CI = 0.95-1.00, p = 0.02). Women with premature or early menopause had a significantly higher risk of developing frailty compared with those with normal menopause (OR = 1.90, 95%CI = 1.28-2.81, p = 0.001), while those with late menopause did not. In a supplementary analysis with older men, older women with premature or early menopause were more likely to develop frailty compared with older men (OR = 2.29, 95%CI = 151-3.48, p < 0.001), however, there was no significant difference between women with normal or late menopause. CONCLUSIONS: Earlier menopause was significantly associated with higher risk of developing frailty. Our findings suggest that menopause or its related factors, such as decline in estrogen after menopause, potentially play an important role in the sex difference in frailty.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".