Hearing, β-Amyloid Deposition and Cognitive Test Performance in Black and White Older Adults: The ARIC-PET Study
Bibliographic record
Abstract
BACKGROUND: Hearing loss is a risk factor for dementia; whether the association is causal or due to a shared pathology is unknown. We estimated the association of brain β-amyloid with hearing, hypothesizing no association. As a positive control, we quantified the association of hearing loss with neurocognitive test performance. METHODS: Cross-sectional analysis of Atherosclerosis Risk in Communities-Positron Emission Tomography study data. Amyloid was measured using global cortical and temporal lobe standardized uptake value ratios (SUVRs) calculated from florbetapir-positron emission tomography scans. Composite global and domain-specific cognitive scores were created from 10 neurocognitive tests. Hearing was measured using an average of better-ear air conduction thresholds (0.5-4 kHz). Multivariable-adjusted linear regression estimated mean differences in hearing by amyloid and mean differences in cognitive scores by hearing, stratified by race. RESULTS: In 252 dementia-free adults (72-92 years, 37% Black race, and 61% female participants), cortical or temporal lobe SUVR was not associated with hearing (models adjusted for age, sex, education, and APOE ε4). Each 10 dB HL increase in hearing loss was associated with a 0.134 standard deviation lower mean global cognitive factor score (95% CI: -0.248, -0.019), after adjustment for demographic and cardiovascular factors. Observed hearing-cognition associations were stronger in Black versus White participants. CONCLUSIONS: Amyloid is not associated with hearing, suggesting that pathways linking hearing and cognition are independent of this pathognomonic Alzheimer's-related brain change. This is the first study to show that the impact of hearing loss on cognition may be stronger in Black versus White adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".