A new insight into masticatory function and its determinants: a latent class analysis
Bibliographic record
Abstract
OBJECTIVE: Masticatory function is an important factor for preservation of general health. Epidemiologic data on masticatory function and its determinants among Iranian population are sparse, and no study has evaluated masticatory function using latent class analysis (LCA). This study was conducted to investigate the masticatory function and its determinants among a large sample of Iranian adults. METHODS: In a cross-sectional study among 8691 adults, masticatory function was investigated using a validated questionnaire. LCA and latent class regression (LCR) were applied to identify classes of masticatory function and its potential determinants, respectively. In addition, multigroup LCA was conducted based on gender and age categories. RESULTS: In total, 11.24% and 24.87% of participants had poor and moderate masticatory function, respectively. Males (class size: 14.33%) were more likely to have poor masticatory function than females (class size: 2.35%) (P < 0.001). The results of LCR showed that higher age [adjusted odds ratio (OR): 1.09, 95% confidence interval (95% CI): 1.07-1.11, P < 0.001], male gender (OR: 1.37, 95% CI: 1.01-1.87, P < 0.05), and low physical activity (OR: 1.41, 95% CI: 1.08-1.85, P < 0.05) were associated with poor masticatory function. Nonsmokers had a lower chance of being in poor masticatory function class than heavy smokers (OR: 0.21, 95% CI: 0.11-0.38, P < 0.001). CONCLUSION: The prevalence of poor masticatory function is high among Iranian adults. Aging, male gender, low levels of physical activity, and smoking were found to be associated with poor 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".