A Cluster Analysis of Oral and Cognitive Health Indicators in the CLSA: An Exploratory Study on Cholinergic Activity as the Link
Bibliographic record
Abstract
INTRODUCTION: Poor oral health has been suggested as a risk factor for cognitive decline. Yet, biologically plausible mechanisms explaining this relationship remain unknown. OBJECTIVES: We aimed (1) to identify oral and cognitive health clustering patterns among middle-aged to elderly Canadians and (2) to investigate the extent to which these patterns could be explained by bone mineral density (BMD), a proxy measure of the cholinergic neurons' activity. METHODS: This cross-sectional study used baseline data from the Comprehensive cohort of the Canadian Longitudinal Study of Aging (CLSA). Oral health was assessed by a self-report questionnaire, and 7 task-based instruments measured cognitive health. We identified oral and cognitive health clusters, our outcome variables, using latent class analysis. Two sets of multivariate logistic regression and 95% confidence intervals were used to investigate whether BMD explains the odds of membership in a certain oral and cognitive health group. The final models were adjusted for socioeconomic, health, and lifestyle factors. RESULTS: Our study sample (N = 25,444: 13,035 males, 12,409 females) was grouped into 5 and 4 clusters based on the oral health status and performance on the cognitive tasks, respectively. After adjusting for all potential covariates, increase in BMD was not associated with higher odds of membership in classes with better oral health (odds ratio [OR] = 1.58 [95% confidence interval {CI}: 0.85-2.92]) and cognitive health (OR = 1.61 [95% CI: 1-2.6]) compared with the groups with the least favorable oral and cognitive health status, respectively. CONCLUSION: Middle-aged and elderly Canadians show different oral and cognitive health profiles, based on their denture-wearing status and performance on cognitive tests. No evidence could be found to support BMD in place of cholinergic neurons' activity as the common explanatory factor behind the association between oral health and cognitive health. KNOWLEDGE TRANSFER STATEMENT: This study is probably the first of its kind to shed light on the cholinergic system as a potential pathway influencing oral and cognitive health. Our findings may support the notion that any potential association between poor oral health and cognitive health might be explained by common contributors, helping clinicians to find the common risk factors for both conditions.
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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 | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".