Association between coffee consumption and periodontal diseases: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Several studies have demonstrated association between coffee consumption and periodontal diseases. However, no systematic review and meta-analysis was performed. Therefore, we performed a systematic review and meta-analysis to evaluate the association between coffee intake and periodontitis. Methods We defined PICO statement as “Do coffee drinkers have a higher association of periodontitis or tooth loss than non-coffee drinkers?”. We searched for articles using the Embase and Medline databases. The odds ratio was used as an effect measure to evaluate the association between coffee and periodontitis We divided coffee intake doses into three groups: no intake (≤ 0.03 cups/day), low intake (0.03 < x < 1 cups/day), and high intake (≥ 1 cup/day). Cohort and cross-sectional studies were eligible for inclusion in this study. The Newcastle–Ottawa scale was used to qualitatively assess the risk of bias. The degree of heterogeneity between studies was quantified using I2statistics. Results Six articles were analysed, including two cohort studies and four cross-sectional studies. The pooled unadjusted odds ratios of periodontitis were 1.14 (0.93–1.39), 1.05 (0.73–1.52), 1.03 (0.91–1.16) and 1.10 (0.84–1.45) in the 4 meta-analyses (coffee drinker vs. non-coffee drinker, high intake vs. low intake, low intake vs. no intake, high intake vs. no intake), respectively. Conclusion This is the first meta-analysis to investigate the relationship between coffee consumption and periodontitis. There was no relationship between coffee consumption and periodontitis. Further studies are required to assess whether a relationship between coffee consumption and periodontitis exists or not. PROSPERO registration number: CRD42022301341.
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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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.040 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".