Visual Impairment, Eye Disease, and the 3-year Incidence of Depressive Symptoms: The Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
PURPOSE: Our goal was to explore the longitudinal association between vision-related variables and incident depressive symptoms in a community-dwelling sample of older adults and to examine whether sex, education, or hearing loss act as effect modifiers. METHODS: A 3-year prospective cohort study was performed using data from the Canadian Longitudinal Study on Aging consisting of 30,097 individuals aged 45-85 years. Visual acuity was evaluated with habitual distance correction using an illuminated Early Treatment of Diabetic Retinopathy Study chart. Visual impairment was defined as binocular presenting visual acuity worse than 20/40. Incident depressive symptoms was defined using a cut-off score of 10 or greater on the Center for Epidemiologic Studies Depression scale. Participants were asked if they had ever had a physician diagnosis of age-related macular degeneration (AMD), glaucoma, or cataract. Multivariable Poisson regression was used. RESULTS: Of 22,558 participants without depressive symptoms at baseline, 7.7% developed depressive symptoms within 3 years. Cataract was associated with incident depressive symptoms (relative risk = 1.20, 95% confidence interval 1.05, 1.37) after adjusting for age, sex, income, education, partner status, smoking, level of comorbidity, hearing loss, and province. Visual impairment, AMD, and glaucoma were not associated with incident depressive symptoms. No effect modification was detected. CONCLUSIONS: Our longitudinal data confirm that the risk of depressive symptoms is higher in those who report ever having a cataract. Further research should confirm this and interventions should be considered.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".