Severe menopausal symptoms linked to cognitive impairment: an exploratory study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association between menopausal symptoms and cognitive decline in postmenopausal women. METHODS: This was a subanalysis of a cross-sectional, observational study conducted among women attending gynecological consultations across nine Latin American countries. The survey involved late postmenopausal women who were asked to complete a general questionnaire and the Menopause Rating Scale (MRS) to assess menopausal symptoms, with the Montreal Cognitive Assessment used to evaluate cognitive function as an outcome. A Montreal Cognitive Assessment score of less than 21 was used to define women with mild cognitive impairment (MCI). RESULTS: The study included 1,287 postmenopausal women with a mean age of 55.5 years and a mean body mass index of 26.3 kg/m 2 . On average, participants had 13.8 years of education and 2.3 ± 1.8 children, with 72.8% reporting having a partner. Additionally, 36.7% ever used menopausal hormone therapy. Regarding lifestyle factors, 50.3% engaged in a sedentary lifestyle, whereas 70.5% had never smoked. 15.3% of women had MCI exhibited significantly more intense menopausal symptoms compared with those without MCI (MRS total score 15.24 ± 12.58 vs 10.53 ± 8.84, respectively, P < 0.001). Logistic regression analysis revealed a significant association between severe menopausal symptoms (MRS total score ≥14 points) and MCI (odds ratio [OR], 1.74; 95% CI, 1.25-2.42). Conversely, a lower body mass index (OR, 0.96; 95% CI, 0.95-0.98), sexual activity (OR, 0.70; 95% CI, 0.51-0.96), physical exercise (OR, 0.55; 95% CI, 0.39-0.76), menopausal hormone therapy use (OR, 0.36; 95% CI, 0.24-0.55), and higher educational level (OR, 0.31; 95% CI, 0.21-0.46) were associated with lower odds for MCI. CONCLUSION: Severe menopausal symptoms in postmenopausal women were associated with cognitive impairment. This study highlights the intricate interplay between hormonal, lifestyle, and sociodemographic factors and cognitive health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".