“Dental Cluster” Versus “Metabolic Cluster”: Analyzing the Associations of Planned and Delivered Dental Procedures with Metabolic Syndrome, Utilizing Data from the Dental, Oral, Medical Epidemiological (DOME) Cross-Sectional Record-Based Nationwide Study

There are conflicting results existing regarding the association between dental status and metabolic syndrome (MetS). The present research analyzed the associations of the sum of the stan-dard dental unit (SDU) scores of planned (SDU-P) and delivered (SDU-D) dental procedures per patient with MetS components, consequences, and related conditions. The SDU score of each dental procedure represents the time and complexity of the executed procedure. This cross-sectional study analyzed data from the Dental, Oral, Medical Epidemiological (DOME) repository, which includes comprehensive socio-demographic, medical, and dental databases of a nationally representative sample of 132,529 military personnel. Univariate analyses revealed that SDU-P had statistically significant positive associations with all systemic morbidities related to MetS, while the SDU-D exhibited positive associations with some of the systemic morbidities and with lower ORs. SDU-P and SDU-D were associated with worse scores of auxiliary examinations used in the assessment of MetS components. SDU-P retained significant positive associations in the multivariate analysis with impaired glucose tolerance (IGT) (OR = 7.40 (1.91–28.57)), deep vein thrombosis (DVT) (OR = 5.61 (1.53–20.83)), obstructive sleep apnea (OSA) (OR = 5.05 (2.40–10.63)), and fatty liver (OR = 1.82 (1.17–2.84)). In contrast, obesity was the only systemic parameter retaining a significant association with SDU-D following multivariate analysis (OR = 1.47 (1.23–1.76)). It can be concluded that SDU-P, but not SDU-D, is a better predictor of systemic morbidities related to MetS. In other words, MetS is associated with a higher dental treatment needs burden, rather than with dental treatments performed de facto. Dental and general health authorities should collaborate and share information and focus on reducing common health-related risk factors, such as smoking and sugar consumption, in particular among high-risk populations, such as immigrants and those with lower SES and rural locality.