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J Dent Res. 2013 Jan;92(1):32-7. doi: 10.1177/0022034512463241. Epub 2012 Oct 11.

Clustering tooth surfaces into biologically informative caries outcomes.

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Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.


Dental caries affects most adults worldwide; however, the risk factors for dental caries do not necessarily exert their effects uniformly across all tooth surfaces. Instead, the actions of some risk factors may be limited to a subset of teeth/surfaces. Therefore, we used hierarchical clustering on tooth surface-level caries data for 1,068 Appalachian adults (ages 18-75 yrs) to group surfaces based on co-occurrence of caries. Our cluster analysis yielded evidence of 5 distinct groups of tooth surfaces that differ with respect to caries: (C1) pit and fissure molar surfaces, (C2) mandibular anterior surfaces, (C3) posterior non-pit and fissure surfaces, (C4) maxillary anterior surfaces, and (C5) mid-dentition surfaces. These clusters were replicated in a national dataset (NHANES 1999-2000, N = 3,123). We created new caries outcomes defined as the number of carious tooth surfaces within each cluster. We show that some cluster-based caries outcomes are heritable (i.e., under genetic regulation; p < 0.05), whereas others are not. Likewise, we demonstrate the association between some cluster-based caries outcomes and potential risk factors such as age, sex, educational attainment, and toothbrushing habits. Together, these results suggest that the permanent dentition can be subdivided into groups of tooth surfaces that are useful for understanding the factors influencing cariogenesis.


COHRA, Center for Oral Health in Appalachia, the principal study sample; C1-5, clusters 1-5, groups of similarly behaving tooth surfaces identified through hierarchical clustering; DMFS index, decayed, missing, or filled surfaces, a traditional caries measure representing the number of affected surfaces across the entire dentition; DMFS1-5, partial DMFS indices representing the number of affected surfaces within a hierarchical cluster; and NHANES, National Health and Nutrition Examination Survey, the secondary study sample.

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