Self-reported sleep disturbances are associated with poorer cognitive performance in older adults with hypertension: a multi-parameter risk factor investigation
Bibliographic record
Abstract
OBJECTIVES: Given the evidence of multi-parameter risk factors in shaping cognitive outcomes in aging, including sleep, inflammation, cardiometabolism, and mood disorders, multidimensional investigations of their impact on cognition are warranted. We sought to determine the extent to which self-reported sleep disturbances, metabolic syndrome (MetS) factors, cellular inflammation, depressive symptomatology, and diminished physical mobility were associated with cognitive impairment and poorer cognitive performance. DESIGN: This is a cross-sectional study. SETTING: Participants with elevated, well-controlled blood pressure were recruited from the local community for a Tai Chi and healthy-aging intervention study. PARTICIPANTS: One hundred forty-five older adults (72.7 ± 7.9 years old; 66% female), 54 (37%) with evidence of cognitive impairment (CI) based on Montreal Cognitive Assessment (MoCA) score ≤24, underwent medical, psychological, and mood assessments. MEASUREMENTS: CI and cognitive domain performance were assessed using the MoCA. Univariate correlations were computed to determine relationships between risk factors and cognitive outcomes. Bootstrapped logistic regression was used to determine significant predictors of CI risk and linear regression to explore cognitive domains affected by risk factors. RESULTS: The CI group were slower on the mobility task, satisfied more MetS criteria, and reported poorer sleep than normocognitive individuals (all p < 0.05). Multivariate logistic regression indicated that sleep disturbances, but no other risk factors, predicted increased risk of evidence of CI (OR = 2.00, 95% CI: 1.26-4.87, 99% CI: 1.08-7.48). Further examination of MoCA cognitive subdomains revealed that sleep disturbances predicted poorer executive function (β = -0.26, 95% CI: -0.51 to -0.06, 99% CI: -0.61 to -0.02), with lesser effects on visuospatial performance (β = -0.20, 95% CI: -0.35 to -0.02, 99% CI: -0.39 to 0.03), and memory (β = -0.29, 95% CI: -0.66 to -0.01, 99% CI: -0.76 to 0.08). CONCLUSIONS: Our results indicate that the deleterious impact of self-reported sleep disturbances on cognitive performance was prominent over other risk factors and illustrate the importance of clinician evaluation of sleep in patients with or at risk of diminished cognitive performance. Future, longitudinal studies implementing a comprehensive neuropsychological battery and objective sleep measurement are warranted to further explore these associations.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".