The prevalence of hearing and vision loss in older Canadians: An analysis of Data from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
Objective: To describe the prevalence of hearing loss (HL), vision loss (VL) and dual sensory loss (DSL) in Canadians aged 45-85. Methods: Data from the first wave of the Canadian Longitudinal Study on Aging were used. Audiometry and visual acuity were measured. Prevalence proportions for 2012-2015 and counts for 2011 and 2016 were estimated.Results: In 2016, 1.5 million Canadian males aged 45-85 had HL, 1.8 million had VL, and 570,000 had DSL. Among females, 1.2 million had HL, 2.2 million had VL, and 450,000 had DSL. Prevalence counts increased 8.7-16.9% between 2011 and 2016. Prevalence proportions increased with age but decreased exponentially with severity of impairment. Males were more likely to have HL and DSL; VL was more common in females.Conclusion: HL, VL and DSL are highly prevalent among older Canadian 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".