Association between iron status, iron deficiency anaemia, and severe early childhood caries: a case–control study
Bibliographic record
Abstract
BACKGROUND: Severe tooth decay is known to affect the health and well-being of young children. However, little is known about the influence of Severe Early Childhood Caries (S-ECC) on childhood nutritional status. The purpose of this study was to contrast ferritin and haemoglobin levels between preschoolers with S-ECC and caries-free controls. METHODS: Children were recruited as part of a larger case-control study examining differences in nutritional status between those with and without S-ECC. Preschoolers with S-ECC were recruited on the day of their dental surgery, while caries-free controls were recruited from the community. Parents completed a questionnaire and the child underwent venipuncture. The study was approved by the University's Health Research Ethics Board. Statistics included descriptive, bivariate and logistic regression analyses. A p value ≤ .05 was significant. A total of 266 children were recruited; 144 with S-ECC and 122 caries-free. RESULTS: The mean age was 40.8 ± 14.1 months. The mean ferritin concentration for all children was 29.6 ± 17.9 μg/L while the mean haemoglobin level was 115.1 ± 10.1 g/L. Children with S-ECC were significantly more likely to have low ferritin (p=.033) and low haemoglobin levels (p>.001). Logistic regression analyses revealed that children with S-ECC were nearly twice as likely to have low ferritin levels and were over six times more likely to have iron deficiency anaemia than caries-free controls. CONCLUSIONS: Children with S-ECC appear to be at significantly greater odds of having low ferritin status compared with caries-free children and also appear to have significantly lower haemoglobin levels than the caries-free control group. Children with S-ECC also appear to be at significantly greater odds for iron deficiency anaemia than cavity-free children.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".