Assessing the Impact of Diet on Enamel Hypoplasia in Children
Bibliographic record
Abstract
A BSTRACT Background: Enamel hypoplasia is a developmental defect of enamel characterized by incomplete or defective enamel formation. It is often influenced by genetic, systemic, and environmental factors, including diet. Materials and Methods: A cross-sectional study was conducted on 200 children aged 6–12 years from urban and rural schools. Data were collected through structured dietary questionnaires and oral examinations to assess the presence and severity of enamel hypoplasia. Dietary intake was classified into groups based on sugar frequency, calcium-rich foods, and vitamin D levels. Enamel hypoplasia was graded using the Modified Developmental Defects of Enamel Index (DDE Index). Statistical analysis was performed using Chi-square tests and logistic regression to evaluate associations. Results: Out of 200 children, 72 (36%) exhibited signs of enamel hypoplasia. High sugar consumption was significantly associated with enamel hypoplasia ( P < 0.001), with 48% of children in the high-sugar group presenting with defects compared to 18% in the low-sugar group. Calcium-rich diets were protective, as only 10% of children with adequate calcium intake showed enamel hypoplasia ( P < 0.05). Vitamin D deficiency was identified in 62% of affected children, indicating a strong correlation ( P < 0.01). Logistic regression revealed that high sugar intake increased the odds of enamel hypoplasia by 2.8 times (OR = 2.8, 95% CI: 1.6–4.7). Conclusion: Diet plays a pivotal role in the development of enamel hypoplasia in children. High sugar consumption and vitamin D deficiency are key contributors, while calcium-rich diets offer protection.
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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 | 0.001 | 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".