Associations of Serum Vitamin D With Dental Caries and Periodontitis: The HUNT Study
Bibliographic record
Abstract
OBJECTIVE: To study the relationships of serum 25-hydroxyvitamin D [25(OH)D] with dental caries and periodontitis in a general Norwegian adult population. METHODS: We analysed a subsample of 1605 participants from the Trøndelag Health Study (HUNT) in Norway that had serum 25(OH)D levels measured in HUNT3 (2006-08) and oral health assessed in the HUNT4 Oral Health Study (2017-19). Negative binomial and Poisson regression models were used to estimate the ratios of means (RMs; for count oral outcomes) and prevalence ratios (PRs; for dichotomous oral outcomes). RESULTS: Serum 25(OH)D was inversely associated with the number of decayed teeth in a dose-response gradient (<30.0 nmol/L: RM 1.41, 95% CI 1.07-1.85; 30.0-49.9 nmol/L: 1.14, 0.98-1.32 and ≥75.0 nmol/L: 0.84, 0.67-1.04, as compared to the 50.0-74.9 nmol/L group, P for trend <.001). Each 25 nmol/L decrease in 25(OH)D level was associated with a 15% (RM 1.15, 95% CI 1.05-1.26) increase in the mean number of decayed teeth. Serum 25(OH)D <30.0 nmol/L was associated with a 35% higher prevalence of severe periodontitis (PR 1.35, 95% CI 1.00-1.83). No association was observed between 25(OH)D and the number of natural teeth. CONCLUSION: The present study suggested that serum 25(OH)D level had an inverse and dose-response association with the number of decayed teeth, and serum 25(OH)D <30 nmol/L was associated with a higher prevalence of severe periodontitis in this Norwegian adult population.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".