Changes in income‐related inequalities in oral health status in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVES: Oral health inequalities impose a substantial burden on society and the healthcare system across Canadian provinces. Monitoring these inequalities is crucial for informing public health policy and action towards reducing inequalities; however, trends within Canada have not been explored. The objectives of this study are as follows: (a) to assess trends in income-related inequalities in oral health in Ontario, Canada's most populous province, from 2003 to 2014, and (b) to determine whether the magnitude of such inequalities differ by age and sex. METHODS: Data representative of the Ontario population aged 12 years and older were sourced from the Canadian Community Health Survey (CCHS) cycles 2003 (n = 36,182), 2007/08 (n = 36,430) and 2013/14 (n = 41,258). Income-related inequalities in poor self-reported oral health (SROH) were measured using the Slope Index of Inequality (SII) and Relative Index of Inequality (RII) and compared across surveys. All analyses were sample-weighted and performed with STATA 15. RESULTS: The prevalence of poor SROH was stable across the CCHS cycles, ranging from 14.1% (2003 cycle) to 14.8% (2013/14 cycle). SII estimates did not change (18.7-19.0), while variation in RII estimates was observed over time (2003 = 3.85; 2007/08 = 4.47; 2013/14 = 4.02); differences were not statistically significant. SII and RII were lowest among 12- to 19-year-olds and gradually higher among 20- to 64-year-olds. RII was slightly higher among females in all survey years. CONCLUSION: Absolute and relative income-related inequalities in SROH have persisted in Ontario over time and are more severe among middle-aged adults. Therefore, oral health inequalities in Ontario require attention from key stakeholders, including governments, regulators and health professionals.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".