The association of body mass index and severe early childhood caries in young children in Winnipeg, Manitoba: A cross‐sectional study
Bibliographic record
Abstract
BACKGROUND: Associations between body mass index (BMI) and caries have been reported. AIM: To evaluate the direction of the relationship between BMI and severe early childhood caries (S-ECC). DESIGN: Children were recruited as part of a larger prospective cohort study assessing changes in nutritional status following dental rehabilitation under general anaesthetic. Pre-operative anthropometric measurements were used to calculate BMI z-scores (BMIz). Operative reports were reviewed to calculate caries scores based on treatment rendered. Analysis included descriptive statistics, bivariate analyses, and simple and multiple linear regression. RESULTS: Overall, 150 children were recruited with a mean age of 47.7 ± 14.2 (SD) months; 52% female. Over 42% were at risk for overweight, overweight or obese. Although simple linear regression demonstrated a significant positive association between dmfs score and BMIz, adjusted multiple linear regression found no significant relationship between BMIz and dmfs, but highlighted a relationship between BMI z-score and family income, Registered First Nations Status and physical activity. CONCLUSIONS: Although a significant relationship between BMI and S-ECC was not found, poverty was a key confounding variable. As both S-ECC and obesity are known predictors of future disease, it is important for healthcare professionals to identify children at risk. Diet and behaviour modification may play a role in disease prevention.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".