F5‐02‐02: HIGHER LITERACY ASSOCIATES WITH BETTER BRAIN STRUCTURE AND COGNITION IN MIDDLE‐AGED INDIVIDUALS
Bibliographic record
Abstract
Education, occupational complexity, and cognitively stimulating leisure activities, were shown to be positively associated with brain structure and better cognitive function, suggesting that these may mitigate the deleterious effects of neurodegenerative processes. Association of literacy, which may reflect quality of education, with brain structure and cognition has not been thoroughly investigated. Participants were 616 adults (mean age of 55.1 ±3.6 years), 53% female and 40% black from the Coronary Artery Risk Development in Young Adults (CARDIA) study who had completed brain MRI, cognitive testing, and the Rapid Estimate of Adult Literacy in Medicine Short-form (REALM-SF), a literacy measurement. Total-brain and regional gray matter volumes were obtained from structural MRI, and total-brain and regional fractional anisotropy (FA) values, which are indirect measures of white matter integrity, were obtained from diffusion tensor imaging. Participants were grouped into high-literate (n=499, REALM-SF score=7), and low-literate groups (n=117, REALM-SF score<7), and MRI and cognitive test scores were standardized as z-scores. Logistic regression models were used to examine the associations between literacy and MRI and cognitive outcomes. All models were adjusted for age, sex, race, depression, exercise and hypertension. The high-literate group had higher total-brain FA (b=0.28, SE=0.13, p=0.03) and higher frontal (b=0.26, SE=0.13, p=0.04) and temporal (b=0.25, SE=0.12, p=0.04) FA compared to the low-literate group. The high-literate group had also better performance on all cognitive tests: Montreal Cognitive Assessment (b=0.36, SE=0.03, p<001), Digit Symbol Substitution Test (b=0.50, SE=0.09, p<001), Rey Auditory Verbal Learning Test (b=0.49, SE=0.09, p<001), Stroop Test (b=−0.54, SE=0.09, p<001), letter fluency (b=0.76, SE=0.10, p<001) and categorical fluency (b=0.49, SE=0.10, p<001). Higher literacy is associated with higher white matter integrity in frontal and temporal regions as well as with better cognitive performance. Future studies will determine whether having higher white matter integrity and better cognitive performance can mitigate the deleterious effects of neurodegenerative diseases.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".