MENOPAUSE HISTORY AND COGNITIVE FUNCTION IN THE IGNITE TRIAL
Bibliographic record
Abstract
Abstract Lifetime exposure to estrogen, a neuroprotectant, is associated with cognitive aging and dementia. Surgically induced menopause (ovariectomy) is associated with poorer cognitive performance, while use of hormone therapy (e.g., birth control, menopausal hormone therapy) has shown mixed associations with cognitive performance. We investigated these associations in IGNITE, a 12-month, multi-site, randomized exercise trial. We measured cognition via the Montreal Cognitive Assessment (MoCA), and factor analysis-derived composite scores for episodic memory, processing speed, working memory, attentional control, and visuospatial processing. In 461 female participants, we estimated relationships between ovariectomy, hormone-use, and baseline cognitive performance accounting for age, education, APOE ε4 carrier status, and race. Ovariectomy predicted worse MoCA scores (B=0.22, p=.038), but was unrelated to cognitive composite scores. African American race accounted for the largest proportion of variance in this model (R2Change=.09). Menopausal hormone therapy was associated with better performance on episodic memory (B=.109, p=.018) and working memory (B=.101, p=.021). Birth control use predicted better performance on MoCA (B=.090, p=.033), working memory (B=.094, p=.017), and attentional control (B=.099, p=.015). The association of ovariectomy with MoCA and not with other domains may indicate an association with dementia, not with typical cognitive aging. Meanwhile menopausal hormone therapy was associated with higher order cognitive performance, not the dementia screener. Birth control was associated with both. Our results validate prior evidence that lifetime exposure to estrogen is an important predictor of older women’s cognitive health and indicate further investigation is needed to clarify differential associations of menopause history and cognitive performance in African American women.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".