Hearing and cognitive scores measured with the Montreal Cognitive Assessment Scale in The HUNT Study, Norway
Bibliographic record
Abstract
INTRODUCTION: Hearing impairment is associated with dementia. We aimed to clarify the association between hearing impairment and future cognitive test performance measured by the Montreal Cognitive Assessment Scale (MoCA), adjusted for confounders, avoiding reverse causation through long follow-up. METHODS: We used the Norwegian population-based longitudinal cohort study, The Trøndelag Health Study (HUNT). At baseline, we invited all residents 20+ for an audiometric hearing assessment, and at 20+ years follow-up, we cognitively assessed all persons 70+ including MoCA adjusted for hearing impairment. We analyzed the association using linear regression. RESULTS: We included 6879 persons (mean 56.1 years, standard deviation 6.2). At follow-up, the MoCA score was -0.25 (95% confidence interval [CI] -0.35, -0.14), per 10 dB increase in hearing threshold and for persons < 85 years, -0.31 (95% CI -0.42, -0.20). DISCUSSION: This study finds a long-term association between hearing impairment and dose related reduced cognitive performance, particularly in those aged < 85. CLINICAL TRIAL REGISTRATION: ID NCT04284384, hearing impairment as a risk factor for dementia in older adults. HIGHLIGHTS: Hearing loss predicts long-term cognitive decline measured by MoCA over 20+ years. Long follow-up is crucial to avoid reverse causation in the hearing-cognition relationship. A 10 dB hearing threshold increase is linked to a 0.25-point reduction in MoCA score. Strongest cognitive decline associations are seen in people aged below 85 years. The association remained after excluding hearing-dependent tasks in the MoCA.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".