Natto, ZuhairAlhassan, Hameedaldeen2025-04-172025https://hdl.handle.net/20.500.14154/75222The objective was to assess the association between oral diseases and metabolic syndrome (MetS), examining both the individual and combined effects of MetS five components. Also, to validate the NHANES diagnostic criteria and Overjet artificial intelligent (AI) platform with the gold standard for periodontal disease diagnosis. First, a systematic review and meta-analysis were conducted by searching PubMed, Embase, and Web of Science for studies published between 1990 and 2023 that examined the association between Dental caries and MetS in adults. Two independent authors selected and analyzed articles, assessed risk of bias, and evaluated the overall evidence certainty. Meta-analyses were performed to estimate pooled odds ratios (ORs), or mean differences (MDs), and corresponding 95% confidence intervals (CIs) for decayed teeth (DT) and DMFT (Decayed, Missing, and Filled Teeth). Second, data from NHANES 2011-2018 were used to assess the association between MetS and oral diseases (dental caries and periodontal disease). The sample included adults over 29 years who completed laboratory and clinical assessments for MetS and oral diseases. Logistic regression models (OR and 95% CI) were used to assess associations between MetS and both untreated caries and periodontal disease. Negative binomial regression (mean ratio [MR] and 95% CI) was conducted to examine the association between MetS and DMFT score. Third, clinical and radiographic records of patients aged over 29 years were utilized to validate the NHANES diagnostic criteria (based on clinical measures alone) and the Overjet AI software (using full-mouth radiographs) for detecting periodontal disease. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess the accuracy of both clinical measures and the Overjet AI software, using a gold standard defined as a combination of clinical and radiographic analysis conducted by a periodontist. The meta-analysis (nine studies with 59,075 participants) revealed that there was a positive statistically insignificant association between DT and MetS (OR: 1.17, 95% CI: 0.87–1.58; MD: 0.22, 95% CI: -0.08–0.52). However, a significant positive association was found between MetS and DMFT (OR: 1.28, 95% CI: 1.08–1.51). Results from NHANES showed that participants with MetS were more likely to have untreated caries and high DMFT mean score by 34% and 10%, respectively. While there was no association between MetS and periodontal disease. Low HDL was the most significant MetS component associated with dental caries, while insulin resistance was the strongest component linked to periodontal disease. Having all five MetS components was associated with a 17% higher likelihood of a high DMFT score. Results from the validity study showed that detecting periodontal disease using clinical measures achieved 96% sensitivity and 99% specificity. While Overjet AI software achieved 100% sensitivity and 89% specificity. In conclusion, the study revealed a positive association between MetS and dental caries, while there was no association between MetS and periodontal disease. Future prospective cohort studies could provide a better understanding of these associations. The validity study demonstrated that both clinical measures and Overjet AI software achieved high accuracy in detecting periodontal disease.95en-USMetabolic SyndromeDental CariesPeriodontal DiseaseNHANESArtificial Intelligence in DentistryThesis