Self-reported occupational noise exposure and cardiovascular disease in Canada: Results from the Canadian Health Measures Survey
Bibliographic record
Abstract
Self-reported occupational noise exposure has been associated with impaired hearing, but its relationship with extra-auditory affects remains uncertain. This research assessed the association between self-reported occupational noise exposure and cardiovascular outcomes. Participants (n = 6318, ∼50% male) from the Canadian Health Measures Survey (2012-2015) aged 20-79 years were randomly recruited across Canada. An in-person household interview included basic demographics, perceived stress, diagnosed health conditions, and self-reported exposure to a noisy work environment. Direct physiological assessment in a mobile examination centre permitted the determination of biomarkers/risk factors related to cardiovascular function. Logistic or linear regression models explored the association between self-reported occupational noise exposure and several cardiovascular endpoints after adjusting for confounding variables. After adjustments, there was no evidence for an association between occupational noise and any of the evaluated endpoints, which included but were not limited to blood pressure, heart rate, blood glucose, insulin, lipids, diagnosed hypertension, medication for hypertension, myocardial infarction, stroke, or heart disease. There was no evidence that self-reported occupational noise exposure was associated with evaluated cardiovascular-related biomarkers, or cardiovascular diseases among Canadians aged 20-79 years. This study, and others like it, provides an important contribution to an evidence base that could inform policy related to occupational noise exposure.
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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 | 0.002 |
| 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".