The impact of cardiovascular risk factors on cognition in Hispanics and non-Hispanic whites
Bibliographic record
Abstract
Among non-Hispanic whites, cardiovascular risk factors are associated with increased mortality and poorer cognition. Prevalence of cardiovascular risk factors among aging Hispanics is also high and Hispanics generally have poorer access to healthcare, yet they tend to have advantageous cardiovascular disease rates and outcomes and live longer than non-Hispanic whites, an epidemiological phenomenon commonly referred to as the Hispanic or Latino health paradox. Although robust data support these ethnic benefits on physical health and mortality, it is unknown if it extends to include cognition resilience advantages in older adulthood. The present study compared relationships between cardiovascular risk and cognition (executive functions and episodic memory) in late middle age and older Hispanics ( n = 87) and non-Hispanic whites ( n = 81). Participants were selected from the National Alzheimer's Coordinating Center and Alzheimer's Disease Neuroimaging Initiative databases. Hispanics and non-Hispanic white groups were matched on age (50–94 yr, mean age = 72 yr), education, gender, cognitive status (i.e., cognitively healthy versus mildly cognitively impaired), and apolipoprotein E4 status. History of hypertension and higher body mass index were both associated with poorer executive functions among Hispanics but not non-Hispanic whites. Our findings suggest greater vulnerability to impairments in executive functions among Hispanics with hypertension and obesity, contrary to the notion of a Hispanic health paradox for cognitive aging.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".