Neurodegenerative diseases among miners in Ontario, Canada, using a linked cohort
Bibliographic record
Abstract
OBJECTIVES: We examined employment in mining occupations and industries and its association with neurological disease incidence in a linkage cohort from Ontario, Canada. Outcomes included Alzheimer's disease (alone and with other dementias), Parkinson's disease, parkinsonism, motor neuron disease and amyotrophic lateral sclerosis (ALS). METHODS: The Occupational Disease Surveillance System cohort was created by linking workers' compensation data and healthcare usage records. This analysis included over 1.1 million male workers, followed between 1999 and 2016. Neurological diseases were ascertained using physician billing and hospital discharge records. Adjusted Poisson regression models were used to estimate incidence rate ratios (RR) comparing mining to non-mining workers overall and by ore (industry) and occupation group. RESULTS: Suggested elevations in incidence rates were observed for ALS among workers of metal mines (RR 2.21, 95% CI 1.04 to 4.69) and for motor neuron disease among those employed in mining occupations within metal mining industries (RR 1.96, 95% CI 1.01 to 3.79), though these were based on relatively few cases. In miscellaneous metal mines, workers who held mining occupations had an elevated rate of Alzheimer's disease (RR 1.27, 95% CI 0.92 to 1.77). Parkinson's disease rate was elevated among workers with rock and soil drilling occupations (RR 1.60, 95% CI 1.04 to 2.45). CONCLUSIONS: Mining hazards may be associated with elevated rates of neurodegenerative diseases among workers in mining occupations and industries. More work is needed to better understand mining exposures and their associations with neurodegenerative diseases.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".