Urinary Fluoride Levels among Canadians with and without Community Water Fluoridation
Bibliographic record
Abstract
Drinking water is a major source of dietary fluoride intake in communities with water fluoridation. We examined the association between urinary fluoride adjusted for specific gravity (UFSG) and tap water fluoride levels, by age and sex, among individuals living in Canada. Participants included 1629 individuals aged 3 to 79 years from Cycle 3 (2012–2013) of the Canadian Health Measures Survey. We used multiple linear regression to estimate unique associations of tap water fluoride levels, age, sex, ethnicity, body mass index (BMI), use of fluoride-containing dental products, smoking in the home, and tea consumption with UFSG. UFSG concentration was significantly higher among participants who received fluoridated drinking water (mean = 1.06 mg/L, standard deviation = 0.83) than among those who did not (M = 0.58 mg/L, SD = 0.47), p < 0.01. UFSG increased over adulthood (ages 19 to 79). Higher UFSG concentration was associated with being female, tea drinking, and smoking in the home. In conclusion, community water fluoridation is a major source of contemporary fluoride exposure for Canadians. Lifestyle factors including tea consumption, as well as demographic variables such as age and sex, also predict urinary fluoride level, and are therefore important factors when interpreting population-based fluoride biomonitoring data.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".