Suboptimal Oral Health, Multimorbidity, and Access to Dental Care
Bibliographic record
Abstract
INTRODUCTION: Emerging studies on the links between suboptimal oral health and multimorbidity (MM), or the co-existence of multiple chronic conditions, have raised controversy as to whether enhancing access to dental care may mitigate MM in those with suboptimal oral health. In this study, we aim to assess the extent of the association between suboptimal oral health and MM and whether access to dental care can modify this association. METHODS: We conducted a cross-sectional analysis using data from the Canadian Longitudinal Study on Aging (CLSA) (N = 44,815, 45 to 84 y old). Edentulism, self-reported oral health (SROH), and other oral health problems (e.g., toothache, bleeding gums) were used as indicators of suboptimal oral health. MM was defined according to the Public Health Agency of Canada as having 2 or more of the following chronic conditions: cancer, cardiovascular diseases, chronic respiratory diseases, diabetes, and mental illnesses. For robustness, we also used a cutoff of having 3 or more of these chronic conditions. Variables for access to dental care included (1) dental visits within the past year, (2) availability of dental insurance, and (3) cost barriers to dental care. We constructed robust Poisson regression models to estimate the association between suboptimal oral health and MM and then assessed the effect measure modification by indicators of access to dental care on a multiplicative scale. We also calculated the relative excess risk due to interaction for prevalence ratio (PR) on an additive scale. RESULTS: Indicators of suboptimal oral health were significantly associated with MM (edentulism PR 1.17, 95% confidence interval [CI] 1.08, 1.27; poor SROH PR 1.44, 95% CI 1.33, 1.54; other oral health problems PR 1.52, 95% CI 1.44, 1.78). The magnitude of this association was higher in individuals who reported fewer dental visits within the past year, lacked dental insurance, and avoided dental care due to costs. CONCLUSION: The association between suboptimal oral health and MM may be exacerbated by barriers to accessing dental care. Policies aiming to enhance access to dental care may help mitigate MM in middle-aged and older Canadians with suboptimal oral health. KNOWLEDGE TRANSFER STATEMENT: This study offers insights into the connection among suboptimal oral health, multimorbidity, and access to dental care factors in middle-aged and older Canadians. The findings can be of value for clinicians and policy makers aiming to enhance medical-dental integration and improve accessibility to dental care and to patients seeking information about the connections between oral health and chronic conditions. Implementation has the potential to enhance individual well-being and drive systemic improvements in health care.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".