Arsenic from community water fluoridation: quantifying the effect
Bibliographic record
Abstract
Community water fluoridation is a WHO recommended strategy to prevent dental carries. One debated concern is that hydrofluorosilicic acid, used to fluoridate water, contains arsenic and poses a health risk. This study was undertaken to determine if fluoridation contributes to arsenic in drinking water, to estimate the amount of additional arsenic associated with fluoridation, and compare this to the National Sanitation Foundation/American National Standards Institute (NSF/ANSI) standard and estimates from other researchers. Using surveillance data from Ontario drinking water systems, mixed effects linear regression was performed to examine the effect of fluoridation status on the difference in arsenic concentration between raw water and treated water samples. On average, drinking water treatment was found to reduce arsenic levels in water in both fluoridated and non-fluoridated systems by 0.2 μg/L. However, fluoridated systems were associated with an additional 0.078 μg/L (95% CI 0.021, 0.136) of arsenic in water when compared to non-fluoridated systems (P = 0.008) while controlling for raw water arsenic concentrations, types of treatment processes, and source water type. Our estimate is consistent with concentrations expected from other research and is less than 10% of the NSF/ANSI standard of 1 μg/L arsenic in water. This study provides further information to inform decision-making regarding community water fluoridation.
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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) | 0.000 | 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) | 0.000 | 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".