Sleep disturbances are associated with cognitive impairment in postmenopausal women
Bibliographic record
Abstract
To evaluate the association between severe sleep problems and mild cognitive impairment (MCI) in postmenopausal women, we conducted a sub-analysis of a cross-sectional, multinational investigation between January and November 2023 among postmenopausal women younger than 70 years attending gynecological consultations in nine Latin American countries. MCI was assessed using the Montreal Cognitive Assessment (MoCA) tool, and severe sleep problems were evaluated with two validated instruments: the third question of the Menopause Rating Scale (MRS, score ≥3) and the Jenkins Sleep Scale (JSS, total score ≥12). Two adjusted logistic regression models were used to examine the association between the two measures of severe sleep problems and MCI, adjusting for relevant covariates. The analysis included 1,185 postmenopausal women with a mean age of 56.9 years. Severe sleep problems were significantly more frequent among women with MCI compared to those without MCI, whether assessed by the MRS (28.3 percent vs. 16.6 percent) or the JSS (31.6 percent vs. 18.4 percent; both p < .001). In adjusted regression models, severe sleep problems remained independently associated with MCI (MRS: aOR = 1.81, 95 percent CI: 1.26–2.60; JSS: aOR = 1.88, 95 percent CI: 1.31–2.69). Additional factors associated with a higher likelihood of MCI included physical inactivity and greater parity, while ever-use of menopausal hormone therapy and higher educational attainment were associated with a reduced likelihood of MCI. In this sample of postmenopausal Latin American women, severe sleep problems were associated with a higher likelihood of MCI, and factors such as physical inactivity, educational attainment, parity, and ever use of menopausal hormone therapy were also independently related to this condition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".