Prevalence of hearing loss among Canadians aged 20 to 79: Audiometric results from the 2012/2013 Canadian Health Measures Survey.
Bibliographic record
Abstract
BACKGROUND: In Canada, population-level estimates of hearing loss have been based on self-reported data, yielding estimates of 4% or 5%. Self-reported hearing difficulties may result in underestimates of hearing loss, particularly among people with mild loss and among older adults. DATA AND METHODS: The 2012/2013 Canadian Health Measures Survey (cycle 3) collected audiometric and self-reported data to estimate the prevalence of hearing loss and limitations in a population-based sample of Canadians aged 20 to 79. Weighted frequencies and cross-tabulations were used to calculate measured and self-reported hearing levels by sociodemographic characteristics. All estimates were weighted at the person-level to represent the population. RESULTS: Based on a pure-tone average of four frequencies that are important in speech, 19.2% of Canadians aged 20 to 79 had measured hearing loss in at least one ear; 35.4% had high-frequency hearing loss. These levels exceeded the self-reported estimate of hearing difficulty--3.7%--derived from responses to questions from the Health Utilities Index Mark 3. The prevalence of measured hearing loss rose with age from no more than 10% among people younger than 50 to 65% at ages 70 to 79. Men were more likely than women to have a hearing loss, a difference that emerged around age 60. Canadians with low household income and/or educational attainment were more likely than those in higher income/education households to have a hearing loss. INTERPRETATION: This analysis presents the first population-based audiometric data on the prevalence of hearing loss among the adult household population of Canada, and highlights the disparity between measured and self-reported outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".