Dietary patterns and hearing loss in older men enrolled in the Caerphilly Study
Bibliographic record
Abstract
The association between dietary patterns (DP) and prevalence of hearing loss in men enrolled in the Caerphilly Prospective Study was investigated. During 1979-1983, the study recruited 2512 men aged 45-59 years. At baseline, dietary data were collected using a semi-quantitative FFQ, and a 7-d weighed food intake (WI) in a 30 % subsample. Five years later, pure-tone unaided audiometric threshold was assessed at 0·5, 1, 2 and 4 kHz. Principal component analysis (PCA) identified three DP and multiple logistic and ordinal logistic regression models examined the association with hearing loss (defined as pure-tone average of frequencies 0·5, 1, 2 and 4 kHz >25 dB). Traditional, healthy and high-sugar/low-alcohol DP were found with both FFQ and WI data. With the FFQ data, fully adjusted models demonstrated significant inverse association between the healthy DP and hearing loss both as a dichotomous variable (OR=0·83; 95 % CI 0·77, 0·90; P<0·001) and as an ordinal variable (OR=0·87; 95 % CI 0·81, 0·94; P<0·001). With the WI data, fully adjusted models showed a significant and inverse association between the healthy DP and hearing loss (OR=0·85; 95 % CI 0·73, 0·99; P<0·03), and a significant association between the traditional DP (per fifth increase) and hearing loss both as a dichotomous variable (OR=1·18; 95 % CI 1·02, 1·35; P=0·02) and as an ordinal variable (OR=1·17; 95 % CI 1·03, 1·33; P=0·02). A healthy DP was significantly and inversely associated with hearing loss in older men. The role of diet in age-related hearing loss warrants further investigation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".