Racial Differences in the Relationship Between Blood Pressure and Cognitive Decline
Bibliographic record
Abstract
Abstract Background Cognition may be influenced by health-related factors such as blood pressure (BP). However, variations in BP may differentially affect cognition as a function of race. This study investigates the relationship between normal, high, and variable BP and cognitive decline in older Black and White adults. Methods 2284 participants (1139 Blacks, 1145 Whites, M Age =73.4, SD =6.6) from 3 harmonized cohorts of older adults from the Rush Alzheimer’s Disease Center, were divided into 3 groups (normal, high, variable) based on systolic BP mean and standard deviation. Cognitive scores were computed from multiple assessments in 5 domains (i.e., episodic memory, semantic memory, working memory, processing speed, visuospatial ability). Performance across 19 tests were averaged to create a measure of global cognition. Linear mixed-effects models examined racial differences between BP and cognitive change over an average of 6.7 years. Results White adults with high or variable BP had faster rates of decline in global cognition compared to Black adults. White adults with high BP declined faster in perceptual speed, semantic memory, and working memory compared to Black adults with high BP, whereas White adults with variable BP had faster rates of decline in all cognitive domains compared to Black adults with variable BP. No racial differences were observed in individuals with normal BP. Conclusions White older adults with elevated or fluctuating BP show faster rates of cognitive decline compared to older Black adults. Findings highlight the complex interplay between BP and cognitive health, emphasizing the need for targeted interventions to address racial disparities in cognitive well-being.
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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) | 0.000 | 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) | 0.001 | 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".