The magnitude of oral health inequalities in <scp>C</scp>anada: findings of the <scp>C</scp>anadian health measures survey
Bibliographic record
Abstract
OBJECTIVES: This study aimed to measure the magnitude of income-related inequality for four oral health outcomes in Canada. The degree of oral health inequality according to sex was also compared. METHODS: Data for this study are from the year 2007 to 2009 Canadian Health Measure Survey (CHMS). The sample size consisted of 4951 Canadians aged 6-79 (2409 men and 2542 women). The oral health indicators used were the number of decayed teeth, number of missing teeth, number of filled teeth, and oral pain in the past year. Socioeconomic status was measured as equivalized household income. We used the relative concentration index to quantify health inequalities. Data analyses were performed using STATA 11.1 and ADePT (4.0). RESULTS: The number of decayed teeth, the number of missing teeth and the prevalence of oral pain decreased with increasing income, while the number of filled teeth increased with increasing income. The relative concentration indices for decayed teeth, missing teeth, filled teeth and for oral pain were -0.264, -0.157, 0.085, and -0.120, respectively. There was a statistically significant deviation from equality for the four oral health outcomes and this was generally present for both sexes. The relative concentration indices for decayed teeth were statistically significantly larger than other oral health outcomes. The relative concentration indices for women were greater than those of males indicating a greater magnitude of inequality among women. CONCLUSIONS: There was a higher concentration of decayed teeth, missing teeth and oral pain in the worse off, while the more affluent had a greater concentration of filled teeth. The numbers of decayed teeth was the most unequal aspect of oral health comparatively. There was a sex difference in the pattern of oral health inequalities with greater magnitude of inequality present among women in terms of the number of decayed and missing teeth. Health policymakers should consider the magnitude of health inequalities according to outcome and between sexes in their decision to tackle oral health 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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".