High frequency hearing impairment and cardiovascular disease in Canada: Results from the Canadian Health Measures Survey
Bibliographic record
Abstract
Noise-induced stress may precipitate cardiovascular diseases. This research assessed the association between sensorineural bilateral high frequency hearing loss (HFHL), as an indication of excessive noise exposure, and cardiovascular outcomes. Participants (n = 6318, ∼50% male) 20-79 years were recruited through the cross-sectional Canadian Health Measures Survey. Questionnaires included several demographic and health-related variables. Audiometry and blood/urine collection took place in a mobile examination centre. Average thresholds ≥25 dB averaged across 3, 4, and 6 kHz defined HFHL. Logistic or linear regression models explored associations between HFHL and cardiovascular-related risk factors/outcomes. Adjusted models indicated elevated diastolic blood pressure in respondents with normal hearing, X¯ = 72.52 (95% confidence interval: 71.85-73.18) compared to the group with bilateral HFHL, X¯ = 70.28 (95%CI: 69.13-71.43), p < 0.05. Average total cholesterol, high-density lipoprotein, low-density lipoprotein and apolipoprotein A1 were elevated in the normal hearing group (p < 0.05). Insulin, high-sensitivity C-reactive protein, and average resting heart rate were elevated in the group with bilateral HFHL, p < 0.05. A stratified analysis by sex- and age, or history of loud occupational noise exposure, did not change the overall results. Although some findings warrant further exploration, the overall analysis did not provide compelling evidence for an association between HFHL and cardiovascular-related biomarkers, or cardiovascular diseases among Canadians aged 20-79 years.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".