Association between oral health and cognitive function among Chinese older adults: the Taizhou imaging study
Bibliographic record
Abstract
BACKGROUND: We aimed to investigate the association between oral health and cognitive function in a sample of older adults from a Chinese rural community. METHODS: The cross-sectional cognitive function of 677 individuals were assessed by Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). A comprehensive profile of the oral health status was evaluated by questionnaire and clinical examination. RESULTS: Multiple covariates-adjusted regression models demonstrated decayed teeth (DT) and decayed/missing/filled teeth (DMFT) were negatively associated with MoCA score (all p < 0.05). Calculus index (CI) and clinical attachment loss (CAL) were significantly associated with the lower MoCA, short-term memory and executive function score, respectively (all p < 0.05). Additionally, participants with missing teeth unrestored tend to get lower MMSE and MoCA scores (p < 0.05). The results also showed that increased DT and CI were modestly associated with higher odds of cognitive impairment (p < 0.05). CONCLUSIONS: There is an association between oral health and global cognition. Poor periodontal status was strongly associated with worse global cognition performance, especially in the short-term memory and executive domain for the aging population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".