The intensity and duration of occupational noise exposure and cardiovascular disease in the United States: a nationally representative study, 2015 to 2020
Bibliographic record
Abstract
OBJECTIVES: Occupational noise exposure may be associated with an increased risk of cardiovascular disease (CVD). Yet the findings are inconclusive. This study aimed to examine the association between self-reported occupational noise exposure and CVD (using a broad composite case definition and by each condition) and identify how these associations vary with the intensity and duration of noise exposure, and combinations thereof. METHODS: This cross-sectional study included a nationally representative sample (n = 6,266) from the National Health and Nutrition Examination Survey (2015 to 2020), aged 20 and greater, in the United States. Survey-weighted logistic regression models were constructed from multiple imputed datasets. RESULTS: Relative to the unexposed, the adjusted odds ratio (95% confidence interval) of composite CVD was 1.33 (1.05 to 1.67) among the noise-exposed population, and ranged from 1.23 to 1.56 when examining CVD conditions separately. The odds ratios of composite CVD were 1.43 (1.06 to 1.93), 1.43 (1.04 to 1.95), and 1.51 (1.03 to 2.21) among those who had noise exposure with very loud intensity of any duration, with duration ≥10 years at any intensity, and with a combination of very loud noise ≥10 years, respectively, compared to those unexposed. CONCLUSIONS: Increased risk of CVD is associated with occupational noise exposure, particularly at higher intensities and longer durations. Policies and interventions for noise mitigation at workplaces are warranted, targeting individuals with chronic exposure to high-level noise.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".