Falls Risk and Hospitalization among Retired Workers with Occupational Noise-Induced Hearing Loss
Bibliographic record
Abstract
This study sought to ascertain whether occupational noise-induced hearing loss (NIHL) increased the risk of falls requiring hospitalization among retired workers. The study population consisted of males (age ≥ 65) with an average occupational noise exposure of 30.6 years and whose mean bilateral hearing loss was 42.2 dB HL at 3, 4, and 6 kHz. Seventy-two retired workers admitted to hospitals after a fall were matched with 216 controls from the same industrial sectors. Conditional logistic regression models were used to estimate the risk (odds ratio; [OR]) of falls leading to hospitalization by NIHL categories. Results showed a relationship between severe NIHL (≥ 52.5 dB HL) and the occurrence of a fall (OR: 1.97, CI95%: 1.001-3.876). Reducing falls among seniors fosters the maintenance of their autonomy. There is a definite need to acquire knowledge about harmful effects of occupational noise to support the prevention of NIHL and ensure healthier workplaces.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".