Short sleep duration and hypertension: A double hit for the brain
Bibliographic record
Abstract
Abstract Background The mechanisms linking short sleep duration to increased dementia risk remain unclear. Sleep duration has a powerful influence on blood pressure (BP), with short sleep durations increasing hypertension risk. Since high BP is a dementia risk factor, short sleep may increase risk of cognitive impairment via adverse effects on vascular health. We assessed whether the association of sleep duration with cognition and vascular brain injury was moderated by hypertensive status. Method 684 dementia‐free participants (mean age 62±9 years; 53.1% female) from the community‐based Framingham Heart Study Offspring and Omni 1 cohort completed assessments of cognition, office BP, and self‐reported habitual sleep duration; 637 also completed brain MRI. Hypertensive status was defined as a combination of systolic BP ≥ 140mmHg and/or diastolic BP ≥90mmHg or use of anti‐hypertensive medication. Outcomes included the Trail Making Test B minus A, Visual Reproductions, Similarities, and white matter hyperintensity volume (WMHV) expressed as a percentage of intracranial volume. Linear regressions were performed between total sleep time and cognitive domains adjusted for demographic factors, APOE e4 positivity, use of sleeping pills, and BMI. An interaction term for hypertensive status was included in regression models. Result Short sleep durations of ≤5 hours/night occurred in 13% of participants and 35% were hypertensive. There were no direct associations between sleep duration and any of the outcomes. However, there was a significant interaction between sleep duration and hypertensive status when predicting the outcomes of executive function/processing speed (Trail Making) and WMHV. When data were stratified by hypertensive status, shorter sleep duration was associated with poorer executive function/processing speed scores in the hypertensive group (β±SE = 0.04±0.02 per hour increase in sleep duration, p = 0.02), but not in the normotensive group (β±SE = ‐0.01±0.01, p = 0.22). Similarly, shorter sleep duration was associated with higher WMHV burden in the hypertensive group (β±SE = ‐0.13±0.06, per hour decrease in sleep duration, p = 0.03), but not in the normotensive group (β±SE = 0.01±0.04, p = 0.760). Conclusion The combination of short sleep and hypertension is associated with worse cognitive performance and brain injury. Further work will examine this interaction more completely.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".