Prevalence of Early Childhood Caries in a Population of Children with History of Maltreatment
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to investigate the prevalence of early childhood caries (ECC) in a population of maltreated children in Toronto, Ontario, Canada. METHODS: The sample consisted of preschool-aged children (2 to 6 years) admitted to the care of the Children's Aid Society of Toronto (CAST) between 1991 and 2004. Data were collected by reviewing the dental and social workers' records of CAST ECC was determined using the decayed, missing, and filled deciduous teeth (dmft) index. The type and severity of maltreatment were obtained from the Eligibility Spectrum. RESULTS: The study included 66 children: 37 (56 percent) boys and 29 (44 percent) girls, with an average age of 4.1 years [standard deviation (SD) = 1.2]. Four (6 percent) children had evidence of dental injury, and none had teeth filled or extracted as a result of decay ECC was observed in 58 percent of the abused children. Of these, the mean decayed teeth ("dt") value was 5.63 (SD = 4.17, n = 38) and 3.24 (SD= 4.21) for the whole sample (n = 66). The proportion of children with untreated caries was 57 percent among "neglected" children (n = 53) and 62 percent in physically/sexually abused cases (n = 13). Logistic regression revealed that children in permanent CAST care and those in its care more than once were significantly less likely to have experienced caries. CONCLUSIONS: Abused and neglected young children had higher levels of tooth decay than the general population of 5-year-olds in Toronto (30 percent prevalence, mean dt= 0.42, SD = 1.20, n = 3185). However, this study did not find any difference in ECC prevalence between children with different types of maltreatment. The study did find that CAST services had a protective effect on children's oral health, which supports the recommendation that child protection services should investigate possible dental neglect in physical/sexual abuse and neglect cases.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".