AIM: Cluster analysis was conducted on data from 5,169 United States (U.S.) Arizona children, age's 5-59-months with the goal of delineating patterns of caries in the primary dentition of pre-school children without a priori pattern definitions. METHODOLOGY: Cluster analyses were conducted using all data for children ages 0-4 years in aggregate: (1) for all subjects, and (2) for subjects without crowned restored teeth. Each of these two sets of analyses consisted of 8 differently specified cluster analyses as a validation procedure. RESULTS: The caries patterns identified from the clustering analysis are: (1) smooth surfaces (other than the maxillary incisor), (2) maxillary incisor, (3) occlusal surfaces of first molars, and (4) pit and fissure surfaces of second molars. CONCLUSION: The cluster analysis findings were consistent with results produced by multidimensional scaling. These cross-validated patterns may represent resulting disease conditions from different risks or the timing of various risk factor exposures. As such, the patterns may be useful case definitions for caries risk factor investigations in children under 60 months of age.
AIM: Cluster analysis was conducted on data from 5,169 United States (U.S.) Arizona children, age's 5-59-months with the goal of delineating patterns of caries in the primary dentition of pre-school children without a priori pattern definitions. METHODOLOGY: Cluster analyses were conducted using all data for children ages 0-4 years in aggregate: (1) for all subjects, and (2) for subjects without crowned restored teeth. Each of these two sets of analyses consisted of 8 differently specified cluster analyses as a validation procedure. RESULTS: The caries patterns identified from the clustering analysis are: (1) smooth surfaces (other than the maxillary incisor), (2) maxillary incisor, (3) occlusal surfaces of first molars, and (4) pit and fissure surfaces of second molars. CONCLUSION: The cluster analysis findings were consistent with results produced by multidimensional scaling. These cross-validated patterns may represent resulting disease conditions from different risks or the timing of various risk factor exposures. As such, the patterns may be useful case definitions for caries risk factor investigations in children under 60 months of age.
Authors: J R Shaffer; X Wang; R S Desensi; S Wendell; R J Weyant; K T Cuenco; R Crout; D W McNeil; M L Marazita Journal: Caries Res Date: 2012-01-25 Impact factor: 4.056
Authors: J R Shaffer; E Feingold; X Wang; D E Weeks; R J Weyant; R Crout; D W McNeil; M L Marazita Journal: J Dent Res Date: 2012-10-11 Impact factor: 6.116
Authors: John R Shaffer; Deborah E Polk; Eleanor Feingold; Xiaojing Wang; Karen T Cuenco; Daniel E Weeks; Rebecca S DeSensi; Robert J Weyant; Richard Crout; Daniel W McNeil; Mary L Marazita Journal: Community Dent Oral Epidemiol Date: 2012-10-29 Impact factor: 3.383
Authors: John R Shaffer; Eleanor Feingold; Xiaojing Wang; Karen T Tcuenco; Daniel E Weeks; Rebecca S DeSensi; Deborah E Polk; Steve Wendell; Robert J Weyant; Richard Crout; Daniel W McNeil; Mary L Marazita Journal: BMC Oral Health Date: 2012-03-09 Impact factor: 2.757
Authors: Kimon Divaris; Gary D Slade; Andrea G Ferreira Zandona; John S Preisser; Jeannie Ginnis; Miguel A Simancas-Pallares; Cary S Agler; Poojan Shrestha; Deepti S Karhade; Apoena de Aguiar Ribeiro; Hunyong Cho; Yu Gu; Beau D Meyer; Ashwini R Joshi; M Andrea Azcarate-Peril; Patricia V Basta; Di Wu; Kari E North Journal: Int J Environ Res Public Health Date: 2020-11-01 Impact factor: 3.390
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