Children's untreated decay is positively associated with past caries experience and with current salivary loads of mutans Streptococci; negatively with self‐reported maternal iron supplements during pregnancy: a multifactorial analysis
Bibliographic record
Abstract
OBJECTIVES: This study explored the association of children's salivary characteristics, past caries experience, birth weight, and reported maternal prenatal vitamin and mineral supplementation with the dental untreated decay of the child. METHODS: This cross-sectional study, a sub-study of Griffith University Environments for Healthy Living birth cohort study, was conducted on 174 mother-child dyads. Mother's prenatal usage of vitamin and mineral supplements; child's birthweight; salivary pH, buffering capacity, and levels of salivary MS and LB were explored as risk indicators. Dental caries experience was assessed using International Caries Detection and Assessment System criteria. Path analysis was conducted to evaluate the association of risk indicators with children's current and past dental caries experience. RESULTS: Children's past caries experience (β = 0.332, p = 0.018), and salivary MS counts (β = 0.215, p = 0.032) were positively associated with untreated decay at time of examination. With a trend towards significance, children whose mothers had reported taking iron supplements during pregnancy experienced lower levels of past caries (β = -0.137, p = 0.068) and untreated dental caries (β = -0.046, p = 0.051). CONCLUSIONS: This study confirms that a child's levels of untreated decay is positively associated with their past caries, and that it correlates with current levels of salivary MS. Children of mothers who reported to have taken iron supplements during pregnancy experienced less caries throughout their lives. These observations confirm the importance to offspring of monitoring maternal health throughout pregnancy and of early monitoring of children's oral health in preventing future dental disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".