Data on the association between age at natural menopause and physical function in older women from the International Mobility in Aging Study (IMIAS)
Bibliographic record
Abstract
Women experience worse physical function and greater physical decline than men at similar ages. These sex differences are heterogeneous across settings and plausibly linked to gender inequality, with evidence of increasing disadvantage for women in increasingly iniquitous societies. As described in "Age at natural menopause and physical function in older women from Albania, Brazil, Colombia and Canada: A life-course perspective" [Velez et al., 2019] we assessed the association between age at natural menopause (ANM) and objectives markers of physical function (i.e., gait speed and grip strength) in older women from the International Mobility in Aging Study (IMIAS). For all sites combined, women with ANM ≥55 had higher gait speed than those with ANM 50-54. Women with ANM <40 had significantly lower grip strength compared with all other groups. In this article, we describe the region-specific associations between ANM, gait speed, and grip strength in 775 women aged 65-74, from the Southeastern European site (Tirana, Albania), Latin American sites (Manizales, Colombia and Natal, Brazil), and Canadian sites (Kingston, Ontario and Saint-Hyacinthe, Quebec). In region-specific analyses, ANM was associated with grip strength in Albania and Latin America and with gait speed in Albania only. No associations were observed in Canada.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 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".