Oral and cardiometabolic health through the lens of biobanks and large-scale epidemiologic research

Oral diseases and cardiometabolic disorders are among the most prevalent non-communicable conditions worldwide and share common inflammatory, metabolic, and social determinants. Over the past two decades, growing evidence has linked poor oral health—particularly periodontitis and tooth loss—to cardiometabolic outcomes such as type 2 diabetes and cardiovascular disease. However, progress in this field has long been constrained by fragmented data systems and limited availability of large-scale resources capturing both oral health exposures and cardiometabolic endpoints. Recent advances in biobank infrastructure, population-based cohorts, and electronic health record linkage have transformed this landscape, enabling robust secondary analyses at unprecedented scale. This narrative review synthesizes current evidence from major biobanks and large-scale epidemiologic datasets relevant to oral–cardiometabolic research. We describe how oral health and cardiometabolic outcomes are operationalized across data ecosystems, critically appraise the strengths and limitations of key resources, and integrate epidemiologic findings with established biological mechanisms, including chronic systemic inflammation, microbial dysbiosis, metabolic dysfunction, and vascular impairment. We further highlight the bidirectional nature of the relationship, whereby cardiometabolic disease can also exacerbate oral inflammatory conditions. Methodological challenges—such as exposure misclassification, residual confounding, and reverse causation—are discussed alongside emerging solutions, including data linkage, multi-omics integration, and advanced analytic approaches. Harnessing large-scale data sources offers a powerful opportunity to reposition oral health within cardiometabolic disease research and prevention. Strategic integration of dental and medical data has the potential to inform precision public health approaches and support more holistic models of chronic disease prevention.