Estradiol-based Menopausal Hormone Therapy is associated with improved episodic and prospective memory scores in the Canadian Longitudinal Study of Aging
Bibliographic record
Abstract
Abstract Introduction Menopause and menopausal hormone therapy (MHT) can influence cognition in postmenopausal women, but previous literature remains equivocal about their effects. MHT varies based on formulation and route of administration, both of which influence dose of estradiol (E2), the estrogen with the greatest affinity to the estrogen receptor. Transdermal E2 avoids hepatic conversion and results in higher plasma levels of E2 than oral E2 formulations. The cognitive domains of executive functions, episodic memory and prospective memory are diminished with age, but may be differentially sensitive to MHT, dependent on the brain regions recruited during the task. There is a lack of research investigating the effects of the age of menopause and estradiol (E2)-based MHT on different cognitive domains. Methods Using baseline data from the Canadian Longitudinal Study of Aging, we examined the associations between age of menopause and E2 based MHT on performance in three cognitive domains: episodic memory, prospective memory, and executive functions. Our cohort included 7,251 postmenopausal women who were cognitively healthy, with models adjusted for age, education, and body mass index. Results Earlier age at menopause was significantly associated with lower scores across all cognitive domains. However, for the executive functions domain, an earlier age of menopause was associated with lower scores only in those with grand parity (4 or more children) and there was a greater effect size among APOE ε4 carriers. We found that transdermal E2 was associated with higher episodic memory scores, whereas oral E2 was associated with higher prospective memory scores compared to no MHT. Neither administration route significantly affected executive function. Conclusion These results highlight the differential effects of E2-based MHT depending on route of administration and cognitive domain, and underscore the importance of considering age of menopause and individual characteristics such as reproductive history and genotype status. This work provides clarity to inconsistencies in the literature and informs the development of precision medicine approaches for cognitive aging in postmenopausal people.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".