Masticatory Function in Elderly Individuals Living in Long‐Term Care Facilities in Brazil: Associations Between Objective and Subjective Measurements
Bibliographic record
Abstract
BACKGROUND: Although objective and subjective masticatory function measures may correlate, associated oral health-related factors may differ, highlighting the need for comprehensive assessment to support tailored care in long-term care facilities (LTCFs). OBJECTIVE: To investigate the association between objective and subjective masticatory function and the oral health status of older LTCF residents in Brazil. MATERIALS AND METHODS: This cross-sectional study included 187 residents (mean age = 78.7 ± 9.2 years) from nine LTCFs. Masticatory function was evaluated objectively (bi-coloured chewing gum) and subjectively ('Do you have trouble biting or chewing any kind of food?'). Oral health status was assessed by self-perceived oral health, the number of natural teeth and posterior occluding pairs (POPs), xerostomia and dental prosthesis requirement. Data were analysed using multiple regression (α = 0.05). RESULTS: Objective and subjective masticatory function were associated (p < 0.001). Older age (p = 0.006), low number of natural teeth (p = 0.001) and POPs (p = 0.004) and the dental prosthesis requirement (p = 0.016) were associated with poorer objective masticatory function. Poor self-perceived oral health (p = 0.001), low number of POPs (p = 0.013), severe xerostomia symptoms (p = 0.001) and dental prosthesis requirement (p = 0.030) were associated with poor subjective masticatory function. CONCLUSION: Objective and subjective masticatory functions were associated and shared some common factors, number of POPs and the need for dental prostheses. However, objective measures (e.g., number of teeth) were linked to objective masticatory function, whereas self-perceived factors (e.g., perceived oral health and xerostomia) were associated with subjective masticatory function.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".