Factors associated with the use of oral health care services among seniors in Canada
Bibliographic record
Abstract
Background: This study explores the link between dental insurance, income, and oral health care access among seniors (aged 65 and over) in Canada. It contributes to the understanding of oral health care among seniors before the implementation of the Canadian Dental Care Plan. Data and methods: This study uses data from the 2019/2020 Canadian Health Survey on Seniors (n=41,635) to report descriptive statistics and logistic regression model results and examine factors associated with seniors living in the community and access to oral health care services. Results: At the time of the survey (2019/2020), 72.5% of seniors in Canada reported having had a dental visit in the past 12 months, with 83.0% of insured and 65.3% of uninsured seniors reporting visits. Seniors reporting excellent or very good oral health had a higher prevalence of visits (79.2%) compared with those with good, fair, or poor oral health (62.3%). Among seniors who had not visited a dental professional in three years, 56.3% deemed it unnecessary, and 30.8% identified cost as the major barrier. After sociodemographic characteristics were controlled for, insured seniors were more likely to have had a dental visit in the past 12 months (adjusted odds ratio [OR]: 2.27; 95% confidence interval [CI]: 2.03 to 2.54) and were less likely to avoid dental visits because of cost (OR: 0.18; 95% CI: 0.12 to 0.28) compared with their uninsured counterparts. Interpretation: This study underscores the role of dental insurance in seniors' oral health care access. While insurance is associated with seniors' access to oral health care services, the study also emphasizes the need to consider social determinants of oral health such as income, gender, age, level of education, and place of residence when assessing oral health care access for seniors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".