Effects and Thresholds of Young to Midlife Vascular Risks on Brain Health
Bibliographic record
Abstract
BACKGROUND: Vascular risk factors, particularly hypertension, are important contributors to accelerated brain aging. We sought to quantify vascular risk factor risks over adulthood and assess the empirical evidence for risk thresholds. METHODS: We used SBP (systolic blood pressure) and diastolic blood pressure, total cholesterol, fasting blood glucose, and body mass index measurements collected from participants in the CARDIA study (Coronary Artery Risk Development in Young Adults) at 2- to 5-year intervals through year 30. The Montreal Cognitive Assessment and domain-specific cognitive tests were performed at year 30. White matter hyperintensity volume was measured by magnetic resonance imaging. We used a 2-step method to fit longitudinal vascular risk factor exposures to optimized spline functions with mixed-effects models, then used the participant-specific random effects that characterized individual exposures over time in cross-sectional models adjusted for sex, race, age, and education to study effects on midlife brain health. RESULTS: Change in SBP up to 33 years of age was negatively associated with Montreal Cognitive Assessment scores (−0.29 Montreal Cognitive Assessment Z score per mm Hg/y change [95% CI, −0.49 to −0.09]; P =0.005), with similar effects for SBP changes from 33 to 49 years of age (−0.08 [95% CI, −0.16 to 0.01]; P =0.08). We observed comparable, significant associations between SBP exposure during those ages, midlife performance on specific cognitive domains, and volume of white matter hyperintensity (all P <0.05). SBP ≤111 mm Hg was the estimated threshold below which no harmful association with midlife cognitive performance was identified. CONCLUSIONS: SBP in early adulthood is the vascular risk factor most strongly associated with midlife cognitive performance and white matter hyperintensity burden, with SBP 111 mm Hg suggested as a harm threshold.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".