Self‐reported oral health at baseline of the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
OBJECTIVES: To compare the prevalence of poor self-reported oral health (SROH) and dental service-use in a representative sample of Canadian residents, and to identify associations between SROH and psychosocial determinants of health at baseline of the Canadian Longitudinal Study on Aging. METHODS: Data from baseline interviews from 2010 to 2015 involving 93% of 51 388 adults (n = 47 761) were weighted to compare the prevalence of oral health characteristics adjusted for age, sex, socioeconomics, general health and residence. SROH was assessed as 'excellent', 'very good', 'good', 'fair' or 'poor', and dichotomized as 'fair/poor' and 'good/very good/excellent'. Multivariable logistic regression was used to assess the association of fair/poor oral health with psychosocial determinants of health. RESULTS: Most participants reported 'good/very good/excellent' oral health (92.5%), natural teeth (92.0%) and dental service-use in the previous year (79.6%), yet over 10% had discomfort when eating. Reports of 'fair/poor' oral health were significantly more frequent among participants who had dental concerns, had low socioeconomic status, smoked tobacco or reported poor general health. Dental service-use and tooth loss differed by province. The odds of poor/fair SROH were high (odds ratio ≥1.5) among participants who avoided foods, did not use dental services frequently, had low incomes, smoked tobacco, were depressed, felt unhealthy or had multiple chronic conditions, but by neither sex or age. There were no interprovincial differences. CONCLUSIONS: Most Canadian residents feel in good oral health and use dental services. Oral health inequality is evident between different socioeconomic groups and between healthy and unhealthy people. SROH is strongly associated with socioeconomic and general health status but not with place of residence. However, there were substantial differences in reports of tooth loss and dental service-use across provinces.
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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 | 0.005 | 0.001 |
| 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".