Influence of lack of posterior occlusal support on cognitive decline among 80‐year‐old Japanese people in a 3‐year prospective study
Bibliographic record
Abstract
AIM: Previous studies have reported significant associations between tooth loss or periodontal status and cognitive function; however, animal experimental studies have shown that occlusion might be a more important factor in cognitive decline. The purpose of the present study was to investigate the influence of a lack of posterior occlusal support by residual teeth on the decline of cognitive function over a 3-year period among 80-year-old Japanese people. METHODS: Participants were community-dwelling older adults (n = 515, age 79-81 years). Cognitive function was measured using the Japanese version of the Montreal Cognitive Assessment. At baseline, participants were divided into two groups: those with and without posterior occlusal support. Participants whose Japanese version of the Montreal Cognitive Assessment score decreased by ≥3 points over the 3-year period were defined as the declined group. Logistic regression was carried out for the decline in Japanese version of the Montreal Cognitive Assessment scores, including dental status and possible risk factors as independent variables. RESULTS: -test, P = 0.02). Logistic regression analysis showed that a lack of posterior occlusal support was a significant variable (odds ratio 1.55, P = 0.03) for cognitive decline, even after adjusting for other risk factors. However, the number of teeth or mean periodontal pocket depth was not significantly correlated with cognitive decline. CONCLUSIONS: The present findings suggest that a lack of posterior occlusal support predicted the incidence of cognitive decline, even after adjusting for possible risk factors in community-dwelling old-old people. Geriatr Gerontol Int 2018; 18: 1439-1446.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".