Impact of Oral Hygiene Practices in Reducing Cardiometabolic Risk, Incidence, and Mortality: A Systematic Review
Bibliographic record
Abstract
Cardiometabolic diseases share many modifiable risk factors. However, periodontitis, a chronic inflammatory condition of the gums, is a risk factor that is rarely publicized. This systematic review aims to evaluate the impact of oral hygiene practices on the risk, incidence, and/or mortality rate of cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM), and chronic kidney disease (CKD). Searches were conducted using MEDLINE, Embase, Scopus, and CINHAL. Randomized controlled trials (RCTs), quasi-RCTs, and observational studies were included. Eligible studies reported on associations of toothbrushing, interdental cleaning, mouthwash, or toothpaste use, either alone or in combination with CVD, CKD, and/or T2DM outcomes in adults ≥ 18 years. Fifty-five studies were included. Cochrane’s risk of bias tool and the Newcastle–Ottawa Scale were used for quality assessment. Data synthesis is narratively presented. Toothbrushing and interdental cleaning were associated with lower risk of developing T2DM or hypertension HR 0.54 [p < 0.001] and a lower mortality risk in those with CVD HR = 0.25 [p = 0.03]. Mouthwash use reportedly increased the risk of developing hypertension and diabetes by 85% and 55%, respectively. This review highlights how simple oral hygiene practices can reduce cardiometabolic risk. Non-dental clinicians could integrate the findings into chronic disease health promotion.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".