THE ASSOCIATION BETWEEN OCCLUSAL FEATURES AND CRANIOFACIAL STRUCTURE
Safavi S.M.R., Soodeh Tahmasbi, S H Shoai
Abstract
Safavi S.M.R., Soodeh Tahmasbi, S H Shoai
Abstract
Purpose: To investigate the relationship between craniofacial skeletal structure and occlusion. Materials & Methods: Data were obtained from lateral cephalometric radiographs and study casts of 60 patients with various malocclusions, with the mean age of 13.3±1.5 years. Thirteen angular and 14 linear skeletal measures as well as 5 occlusal measures including; overjet, overbite, molar relation, maxillary and mandibular crowding were applied. Relations were examined by use of univariate and multivariate statistical methods. Results: Simple correlation analysis between individual skeletal measures and individual occlusal characteristics showed that the strongest linear correlation exists between overbite and Pal-GoMe angle (r=-0.451, P-value≤0.01). Stepwise multiple regression was carried out for quantitative occlusal variables. The prediction formula for overjet had the highest multiple R and R 2 values (multiple R=0.654, R 2 = 0.428), which shows that multiple skeletal features explained 43% of the variance in overjet. Conclusion: Individually and in combination, skeletal measures were poorly associated with individual features of occlusion, so that variations in skeletal structure account for at most 43% of the variations in occlusion.
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Purpose: To investigate the relationship between craniofacial skeletal structure and occlusion. Materials & Methods: Data were obtained from lateral cephalometric radiographs and study casts of 60 patients with various malocclusions, with the mean age of 13.3±1.5 years. Thirteen angular and 14 linear skeletal measures as well as 5 occlusal measures including; overjet, overbite, molar relation, maxillary and mandibular crowding were applied. Relations were examined by use of univariate and multivariate statistical methods. Results: Simple correlation analysis between individual skeletal measures and individual occlusal characteristics showed that the strongest linear correlation exists between overbite and Pal-GoMe angle (r=-0.451, P-value≤0.01). Stepwise multiple regression was carried out for quantitative occlusal variables. The prediction formula for overjet had the highest multiple R and R 2 values (multiple R=0.654, R 2 = 0.428), which shows that multiple skeletal features explained 43% of the variance in overjet. Conclusion: Individually and in combination, skeletal measures were poorly associated with individual features of occlusion, so that variations in skeletal structure account for at most 43% of the variations in occlusion.
Key concepts: Overjet, Overbite, Craniofacial, Occlusion, Orthodontics, Dental occlusion, Cephalometry, Malocclusion