Racial discrimination and cognitive function: An instrumental variable analysis
Bibliographic record
Abstract
Racial inequities in cognitive function persist with mixed evidence regarding the impacts of racial discrimination on cognitive outcomes. We examined the association between experiences of racial discrimination within institutional settings, such as getting a job or housing, and multiple measures of cognitive function among middle-aged adults using analytic methods to strengthen the existing evidence base and provide potential points for intervention. We used cross-sectional data from 2895 participants in Wave 8 (M age = 50.20, range: 43–55) and 2618 participants in Wave 9 (M age = 55.20, range: 48–60) of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Self-reported racial discrimination was operationalized using the Experiences of Discrimination Scale. Cognitive measures included were the Stroop Interference Test, Rey Auditory Verbal Learning Test, Digit Symbol Substitution Test, and the Montreal Cognitive Assessment. Analyses were conducted using ordinary least squares regression (OLS) and instrumental variable (IV) analysis using reflectance meter-measured skin color as the instrument. We find that increased experiences of racial discrimination are associated with poorer performance on cognitive assessments across OLS and IV analyses. For example, reporting one additional experience of racial discrimination was associated with approximately 0.50 SD lower auditory verbal learning scores using IV and 0.08 SD lower scores using OLS (Wave 8 IV 95% CI: −0.54, −0.41; OLS 95% CI: −0.10, −0.06). Such results in a relatively young sample yield insight into the potential implications of navigating a racialized society over one's life course in contributing to inequities in cognitive decline in older age. • Relationships between racial discrimination and cognitive health vary in the field. • Increased discrimination was associated with adverse outcomes in all cognitive tools. • Racism contributes to cognitive inequities at a relatively young age.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".