Gender Difference in the Prediction of Crown Widths of Unerupted Permanent Canines and Premolars with Crowded Teeth

Aims: To determine whether the accuracy of the prediction of the summed widths of unerupted permanent canines and premolars depend on the patient's gender and to examine whether there are differences between sexes in the best combination of independent variables for predicting and to developing new predicting equations for crowding patient for both jaws and both sexes. Materials and methods: The sample consisted of eighty dental casts (40 males and 40 females). The age ranged between (14-22) years and all patients have anterior crowding. The mesiodistal crown diameters of the central incisors, the lateral incisors, the canines, the first premolar, the second premolar, and the first molars in the maxillary and mandibular arch were measured on dental casts. Basal arch lengths and intermolar distances for the upper arch and for the lower arch were also recorded. Predicted sum widths of permanent canines and premolars in both dental arches were calculated using backward multiple regression analysis by using statistical package for social science (SPSS). Results: In the male subject group, there were statistically significant correlations between central incisor and lateral incisor widths in the maxilla (r=0.456) and in the mandible between lower central and lateral incisor widths and lower basal arch length (r=0.682), and in the female subject group, there were statistically significant correlations between the central incisor and the lateral incisor widths, upper first molar, upper basal arch length and upper inter molar distance (r=0.742). For the mandible, lower central and lateral incisor and lower first molar widths (r=724). Also the correlation coefficients (r) and determination coefficients (R2 ) for female group are greater when compared with those for the male subject group. Conclusions: Four regression equations for crowding patients for both gender are establish and the best combination of independent variables for prediction was found to differ between sexes.