Visual Impairment, Eye Disease, and 3-Year Cognitive Decline: The Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
PURPOSE: To examine the longitudinal association between vision-related variables and the 3-year change in cognitive test scores in a community-dwelling sample of adults and to explore whether sex, education, or hearing loss act as effect modifiers. METHODS: Data came from two waves of a 3-year population-based prospective cohort study (Canadian Longitudinal Study on Aging), which consisted of 30,097 randomly selected people aged 45-85 years from 7 Canadian provinces. Visual impairment (VI) was defined as binocular presenting visual acuity worse than 20/40. Participants were asked if they had ever had a diagnosis of age-related macular degeneration (AMD), glaucoma, or cataract. Cognitive change over 3 years was examined by calculating the difference between baseline and follow-up scores for the Rey Auditory Verbal Learning Test (RAVLT) and the RAVLT delayed test (memory tests), the Controlled Oral Word Association Test (COWAT) and the Animal Naming Test (ANT) (verbal fluency tests), and the Mental Alternation Test (MAT) (processing speed test). Multiple linear regression was used. RESULTS: VI, AMD, and cataract were not associated with 3-year changes on any of the 5 cognitive tests after adjusting for age, sex, ethnicity, education, income, smoking, diabetes, stroke, heart disease, and province. A report of glaucoma was associated with greater declines in MAT scores (β = -0.60, 95% CI -1.03, -0.18). No effect modification was detected. CONCLUSIONS: Glaucoma was associated with worsening processing speed. Further research to confirm this finding and to understand the possible reason is necessary.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".