Tooth loss and dementia amongst older adults residing in long‐term care facilities in Vancouver: A case‐control study
Bibliographic record
Abstract
OBJECTIVE: The purpose of this case-control study was to determine the association between dementia and the number of missing teeth, functional occlusal units and denture use in older adults residing in Long-Term Care (LTC) facilities. BACKGROUND: Many studies have shown an association between dementia and tooth loss. However, few studies with a large sample size have been reported describing the relationship between dementia and the number of missing teeth, remaining teeth and functional occlusal units. METHODS: An oral health assessment database of 2160 older adults admitted to LTC facilities in Vancouver, Canada, between 2015-2019 was utilised. Participants with a diagnosis of dementia in their medical records (N = 1174) were compared to those without dementia (N = 986). Multiple logistic regression analysis was used to explore a potential association between the number of missing teeth, functional occlusal units and the use of dentures and dementia. RESULTS: The number of remaining teeth (OR = 1.0, 95% Confidence Interval = 1.0-1.0; P = .054) and number of functional occlusal units (OR = 1.0, 95% CI = 1.0-1.0; P = .059) were not associated with dementia after adjusting for age, sex, oral self-care and systemic conditions. Denture use (OR = 1.1, 95% CI = 0.5-2.4; P = .790) was not associated with dementia in edentulous patients. CONCLUSION: There was no association between dementia and the number of remaining teeth, functional occlusal units or wearing dentures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".