Vision, Eye Disease, and the Onset of Balance Problems: The Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
PURPOSE: To understand the relationship between visual impairment, self-reported eye disease, and the onset of balance problems. DESIGN: Population-based prospective cohort study. METHODS: Baseline and 3-year follow-up data were used from the Canadian Longitudinal Study on Aging. The Comprehensive Cohort included 30,097 adults aged 45 to 85 years recruited from 11 sites across 7 provinces. Balance was measured using the 1-leg balance test. Those who could not stand on 1 leg for at least 60 seconds failed the balance test. Presenting visual acuity was measured using the Early Treatment of Diabetic Retinopathy Study chart. Participants were asked about a previous diagnosis of cataract, macular degeneration, or glaucoma. Logistic regression was used. RESULTS: Of the 12,158 people who could stand for 60 seconds on 1 leg at baseline, 18% were unable to do the same 3 years later. For each line worse of visual acuity, there was a 15% higher odds of failing the balance test at follow-up (odds ratio [OR] = 1.15, 95% confidence interval [CI] 1.10, 1.20) after adjustment. Those with a report of a former (OR = 1.59, 95% CI 1.17, 2.16) or current cataract (OR = 1.31, 95% CI 1.01, 1.68) were more likely to fail the test at follow-up. Age-related macular degeneration and glaucoma were not associated with failure on the balance test. CONCLUSION: These data provide longitudinal evidence that vision loss increases the odds of balance problems over a 3-year period. Efforts to prevent avoidable vision loss are needed, as are efforts to improve the balance of visually impaired people.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".