Occupational Exposure to Low Dose Ionizing Radiation and the Incidence of Surgically Removed Cataracts and Glaucoma in a Cohort of Ontario Nuclear Power Plant Workers
Bibliographic record
Abstract
Ionizing radiation is a human carcinogen and has been shown to increase the risk of non-cancerous ocular disorders. Specifically, findings from epidemiological studies suggest that ionizing radiation leads to the development of cataracts and to a lesser extent glaucoma, however, there are uncertainties of these risks at lower exposures. We analyzed data from a cohort of 60,874 Ontario Nuclear Power Plant (NPP) workers within the Canadian National Dose Registry (NDR). These workers were monitored for whole-body exposure to ionizing radiation using dosimeters, with exposure estimates derived for each year of employment. Incident cases of surgically removed cataracts and glaucoma were identified through the record linkage of occupational histories to administrative health data for Ontario between 1991 and 2022. We compared the incidence of surgically removed cataracts and glaucoma in the cohort to Ontario's general population using indirect age- and sex-standardization with matching by place of residence. We evaluated exposure-response relationships with internal cohort comparisons using age-, sex-, and calendar-period-adjusted Poisson regression. The relative risks of cataract and glaucoma were estimated across categorical measures of whole-body dose [Hp(10)] from exposure to radiation (lagged 5 years). In total, 32,855 of the 60,874 workers (58%) had a positive cumulative dose exceeding the minimum reportable threshold. Among these workers, the mean cumulative whole-body lifetime dose at end of follow-up was 23.7 mSv (interquartile range: 1.1-26.4 mSv, maximum = 959.3 mSv). Overall, 4,401 (7.2%) of workers developed glaucoma, while 2,939 (4.8%) underwent cataract-removal surgery. There was no evidence of a dose-response relationship between cumulative whole-body dose ionizing radiation (lagged 5 years) and glaucoma, but some for surgically removed cataracts. Specifically, among workers with a cumulative exposure of greater than 50 mSv relative to those with an exposure of less than 0.25 mSv, the relative risks of incident glaucoma and cataract removal surgery were 0.91 (95% CI: 0.81-1.05) and 1.13 (95% CI: 0.97-1.33), respectively. The linear excess risks per 100 mSv (lagged 5 years) for cataract removal surgery was 0.055 (95% CI: -0.042 to 0.163). Our findings provide some evidence that ionizing radiation increases the risk of cataracts but not glaucoma in an occupational cohort whose lifetime cumulative dose rarely exceeded 30 mSv.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".