Better oral health for a healthy cognition: Investigation of a new pathway
Bibliographic record
Abstract
Background: Tooth loss has been suggested as a risk factor for cognitive decline. Several biologically plausible explanations have been put forward to explain this oral-systemic connection. However, these purported mechanisms fail to consider the role of age-related cholinergic neurons’ degeneration as a potential common cause behind this association.Objective: The overarching objective of this study was to investigate the association between cholinergic neurons’ activity, and oral and cognitive health. Specifically, we aimed to first identify oral health and cognitive health clustering patterns among middle-aged to elderly Canadians, and second, to investigate the extent to which these patterns could be explained by a proxy measure of the cholinergic neurons’ activity (bone mineral density).Methods: Baseline data from the Comprehensive cohort of the Canadian Longitudinal Study of Aging (CLSA), which recruited participants aged 45 to 85, was used to fulfill the aims of this project. First, I used latent class analysis to identify oral health and cognitive health clusters. Oral health was assessed by a self-report questionnaire, whereas seven task-based instruments measured cognitive health (i.e., retrospective and prospective memory, verbal fluency, and cognitive interference inhibition). Oral health and cognitive health clusters were then used as the outcome variables in multivariate nominal logistic regression models to investigate whether bone mineral density, a proxy for cholinergic activity, can explain the odds of being classified in a certain oral/cognitive health group. In our final multivariate analysis, we adjusted for age, sex, education, total household income, ethnicity, alcohol consumption, smoking, hypertension, and diabetes. Results: Our study sample (N=25,444: 13035 males, 12409 females) were grouped into 5 and 4 clusters based on their self-reported oral health status and performance on cognitive tasks, respectively. In the final multivariate regression models and after adjusting for all potential covariates, most 95% confidence intervals ranged from <1.0 to around 3.0, supporting a mild association between bone mineral density and odds of membership in any of oral health or cognitive health classes, compared to the classes with the worst oral and cognitive health. Conclusion: Middle-aged and elderly Canadians show different oral and cognitive health profiles, based on their denture wearing status and performance in memory and verbal fluency tests. Clustering of participants based on their oral health and cognitive health status could not be explained by a proxy of cholinergic activity after adjusting for sociodemographic factors, chronic conditions, and health-related behaviors
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".