Long-Term Trends in Access to Dental Care in Canada.
Bibliographic record
Abstract
OBJECTIVES: Although routine dental care is essential for both oral and overall health, in Canada, access to such care is uneven. Those with low or medium income and no workplace dental coverage often face financial barriers in accessing dental care. However, the factors that affect access - income, employer-provided health benefits and public dental care subsidy programs - have changed over the decades. This study examines the net impact of these factors on long-term trends in dental care access among different groups in Canada over the past 5 decades. METHODS: Using data from 1 235 268 respondents to 20 Canadian cross-sectional surveys administered between 1972 and 2017, we estimated the proportion of people who had at least 1 consult with a dental professional over the past 12 months. Prevalence trends by region, age group, education and income level were compared. RESULTS: In each age group, the proportion of people consulting a dental professional at least annually gradually increased over the last 5 decades. During the recession of the early 1990s, a temporary drop in use occurred, particularly among younger age groups. We noted significant regional differences in use among individuals in the same age group: rates were highest in Ontario and British Columbia and lowest in Quebec and the Atlantic provinces. Marked differences in use by level of education and income persisted over the 5 decades. Dental care use was significantly higher among those with higher levels of education and higher incomes. The increase in overall rates of dental care use suggest that an increasing fraction of Canadians have higher incomes or are better educated, or both. Nevertheless, about a third of Canadians ≥ 15 years did not receive dental care in 2015. CONCLUSIONS: Given that dental care is almost wholly privately funded and displays a high degree of income-related inequity, there is an urgent need for policy action to address unequal access to dental care in Canada.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".