Oral health inequalities between young Aboriginal and non‐Aboriginal children living in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVES: To investigate (i) oral health inequalities between off-reserve Aboriginal and non-Aboriginal children entering junior kindergarten (JK) in the Thunder Bay District, Northwest Ontario, Canada, (ii) oral health inequalities between kindergarten-aged (4 years old) Aboriginal children living on reserves in the Sioux Lookout Zone (SLZ), Northwest Ontario and those living off-reserve in the Thunder Bay District and (iii) early childhood caries (ECC) trends among SLZ children between 2001 and 2005. METHODS: Cross-sectional oral health data (dmft/s Indices) for 416 (2003/2004), 687 (2004/2005) and 544 (2005/2006) 3- to 5-year olds attending JK in the Thunder Bay District were collected by calibrated dental hygienists with the District's Health Unit. Secondary analysis of oral health status data from two studies conducted in the SLZ between 2001 and 2005 provided the dmft of random samples of children younger than 6 years of age living in 16-20 First Nations communities. RESULTS: When compared with non-Aboriginal children aged 3-5 years attending the same schools in the Thunder Bay District between 2003 and 2006, off-reserve Aboriginal children had 1.9 to 2.3 times the risk of having ECC (dmft > 0), 2.9 to 3.5 times the risk of a dmft > 3 and 1.8 to 2.5 times the risk of untreated decayed teeth after adjusting the prevalence ratios for child's age and sex, school's risk level and clustered-correlated data. The mean dmft of on-reserve Aboriginal 4-year olds in 2005 was 11.2 and 5.9 for their off-reserve Aboriginal counterparts. In 2001, the mean dmft scores (95% confidence interval) of 2-, 3- and 4-year-old Aboriginal children in the SLZ were: 9.1 (8.3-9.9), 12.4 (11.8-13.1), 13.1 (12.1-14.2). In 2005, similarly aged SLZ children had a mean dmft of: 6.2 (5.2-7.1), 8.9 (8.2-9.6), 11.2 (10.5-11.9), representing significant reductions in caries severity (32%, 28% and 14.5%, respectively). CONCLUSIONS: Significant disparities in caries experience exist between off-reserve Aboriginal and non-Aboriginal children living in the same locales and between Aboriginal children living on- and off-reserve in northwestern Ontario. The study showed decreased trends in the severity of ECC for children in the SLZ occurring over the 5-year period. Despite this progress, the oral health of young Aboriginal children in Ontario continues to lag far behind that of non-Aboriginal children, demanding further programs and policies to tackle the social determinants of oral health and resolve these inequalities.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".