James D Beck1,2, Kevin L Moss2, Thiago Morelli2,3, Steven Offenbacher2,3. 1. Department of Dental Ecology, School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC. 2. Center for Oral and Systemic Diseases, School of Dentistry, University of North Carolina at Chapel Hill. 3. Department of Periodontology, School of Dentistry, University of North Carolina at Chapel Hill.
Abstract
BACKGROUND: This paper focuses on the Periodontal Profile Class (PPC) System that may be more informative and representative of periodontitis phenotypes than current case definitions of periodontitis. This study illustrates the unique aspects of the PPC compared with other periodontal indices for studying associations between periodontal disease and prevalent systemic conditions. METHODS: We computed odds ratios and 95% confidence intervals to compare associations between periodontal disease and prevalent systemic conditions using our new PPC and two traditional indices. We used the Bayesian Information Criterion (BIC) to determine the fit of the model and the magnitude of the contribution attributable to periodontal disease beyond traditional risk factors. The Atherosclerosis Risk in Communities (ARIC) Study (1996-1998) results were compared with results from the combined National Health and Nutrition Examination Survey 2009-2014 datasets. RESULTS: In the ARIC Study, high gingival inflammation, tooth loss, severe tooth loss, and severe disease PPC components were significantly associated with diabetes, coronary heart disease (CHD), high-sensitivity C-reactive protein, and interleukin (IL)-6, while only severe disease was associated with stroke. Severe disease was associated with CHD using the Centers for Disease Control/American Academy of Periodontology index, and the European Periodontal index was associated with CHD and IL-6. CONCLUSIONS: The addition of the PPC to traditional variables associated with prevalent diabetes, stroke, CHD, and systemic measures of inflammation resulted in very strong improvement of the overall models, while the traditional indices were less likely to be associated and, if present, the associations were weaker. The PPC system provides specific insight into the individuals and periodontal characteristics of the phenotype that are associated with systemic conditions that may be useful in designing treatment interventions.
BACKGROUND: This paper focuses on the Periodontal Profile Class (PPC) System that may be more informative and representative of periodontitis phenotypes than current case definitions of periodontitis. This study illustrates the unique aspects of the PPC compared with other periodontal indices for studying associations between periodontal disease and prevalent systemic conditions. METHODS: We computed odds ratios and 95% confidence intervals to compare associations between periodontal disease and prevalent systemic conditions using our new PPC and two traditional indices. We used the Bayesian Information Criterion (BIC) to determine the fit of the model and the magnitude of the contribution attributable to periodontal disease beyond traditional risk factors. The Atherosclerosis Risk in Communities (ARIC) Study (1996-1998) results were compared with results from the combined National Health and Nutrition Examination Survey 2009-2014 datasets. RESULTS: In the ARIC Study, high gingival inflammation, tooth loss, severe tooth loss, and severe disease PPC components were significantly associated with diabetes, coronary heart disease (CHD), high-sensitivity C-reactive protein, and interleukin (IL)-6, while only severe disease was associated with stroke. Severe disease was associated with CHD using the Centers for Disease Control/American Academy of Periodontology index, and the European Periodontal index was associated with CHD and IL-6. CONCLUSIONS: The addition of the PPC to traditional variables associated with prevalent diabetes, stroke, CHD, and systemic measures of inflammation resulted in very strong improvement of the overall models, while the traditional indices were less likely to be associated and, if present, the associations were weaker. The PPC system provides specific insight into the individuals and periodontal characteristics of the phenotype that are associated with systemic conditions that may be useful in designing treatment interventions.
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