The Association Between Cognitive Function and Oral Health in Home Dwellers and Nursing Home Residents: The <scp>HUNT</scp> Study
Bibliographic record
Abstract
OBJECTIVES: To evaluate the relationships of cognitive function and care dependency with oral health in a Norwegian older adult population. METHODS: This cross-sectional study included 2623 participants aged 70 and older from the fourth wave of the Trøndelag health study (HUNT4 70+) and the city of Trondheim (Trondheim 70+). Neurocognitive disorders (NCDs) were diagnosed by clinical experts according to the DSM-5 framework. Care dependency referred to nursing home residency. Oral health was assessed by using the Revised Oral Assessment Guide-Jönköping (ROAG-J). Individuals were considered as 'having oral problem' if the score was two or three in at least one of the nine ROAG-J items. Poisson regression was used to estimate prevalence ratios (PRs) and 95% confidence intervals (CIs). RESULTS: The prevalence of having oral problems was 19% higher in participants with NCDs than those with normal cognitive function after adjusting for potential confounders (PR 1.19, 95% CI: 1.09-1.29). Further analysis showed a higher prevalence of having oral problems for home dwellers with NCDs (PR 1.23, 95% CI: 1.13-1.33) and nursing home residents (PR 1.32, 95% CI: 1.20-1.45) compared to home dwellers with normal cognitive function. CONCLUSIONS: NCDs were associated with an increased prevalence of oral problems in this Norwegian older adult population. The study suggests the need for increasing oral care for home dwellers with NCDs and nursing home residents.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".