A CROSS-SECTIONAL STUDY ON MENOPAUSAL SYMPTOMS, SLEEP QUALITY, AND COGNITIVE FUNCTION IN WOMEN
Bibliographic record
Abstract
Objective: This cross-sectional study investigated the relationships between menopausal symptoms, sleep quality, and cognitive function in women during the menopausal transition, examining whether sleep quality mediates the association between menopausal symptoms and cognitive performance. Methods: A sample of 586 women aged 40–60 years, stratified by menopausal stage (perimenopause or postmenopause), was recruited from a tertiary care hospital. Menopausal symptoms were assessed using the Menopause Rating Scale (MRS), sleep quality with the Pittsburgh Sleep Quality Index (PSQI), and cognitive function with the Montreal Cognitive Assessment (MoCA), Digit Span Test, and Trail Making Test (TMT). Multivariable linear regression and mediation analyses, adjusted for age, education, BMI, and psychological distress (Hospital Anxiety and Depression Scale), were conducted. Results: Participants (mean age 50.4 ± 5.2 years) reported moderate menopausal symptoms (MRS score 18.5 ± 7.9), with 62.8% experiencing poor sleep quality (PSQI >5). Postmenopausal women had higher MRS (20.1 ± 8.2 vs. 16.9 ± 7.3, p < 0.001) and PSQI scores (8.9 ± 4.3 vs. 7.5 ± 3.8, p = 0.002) than perimenopausal women. Higher MRS scores were associated with poorer sleep quality (β = 0.42, p < 0.001) and lower MoCA scores (β = -0.19, p = 0.01). Sleep quality partially mediated (34.8%) the relationship between menopausal symptoms and cognitive function (Sobel test, p = 0.01). Conclusion: Menopausal symptoms are associated with poorer sleep quality and cognitive performance, with sleep quality partially mediating this relationship. Interventions targeting sleep may mitigate cognitive challenges during menopause.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".