Diet Practices, Body Mass Index, and Oral Health-Related Quality of Life in Adults with Periodontitis- A Case-Control Study
Bibliographic record
Abstract
Objectives: To assess and compare diet practices, body mass index (BMI), and oral health-related quality of life (OHRQoL) in adults with and without periodontitis. Methods: Demographics, health-related behaviors, BMI, dental and periodontal parameters, diet practices, and Oral Health Impact Profile-14 (OHIP-14) were collected from 62 periodontitis patients and 100 controls without periodontitis. Results: Having periodontitis was positively associated with male sex (p = 0.004), older age (p < 0.001), smoking pack-years (p = 0.006), weight (p = 0.008), BMI (p = 0.003), number of meals per day (p < 0.001) and had a negative association with decayed teeth (p = 0.013), alcohol (p = 0.006), and sweets (p = 0.007) consumption. Periodontitis patients were more likely to avoid carbonated beverages (p = 0.028), hot (p = 0.003), and cold drinks (p = 0.013), cold (p = 0.028), hard textured (p = 0.002), and fibrous foods (p = 0.02) than the controls, and exhibited higher global OHIP-14 (p < 0.001) and most domain scores. Age (p < 0.001), BMI (p =0.045), number of meals per day (p = 0.024), and global OHIP-14 score (p < 0.001) remained positively associated with periodontitis in the multivariate analysis. Conclusions: Periodontitis patients exhibited higher BMI and altered diet practices and OHRQoL as compared to controls. Assessment of diet practices, BMI, and OHRQoL should be part of periodontal work-up. Dentists and dietitians should collaborate to design strategies to address these challenges.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".