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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".