A Newly Proposed Regression Equation for Mixed Dentition Analysis Using the Sum of the Width of Permanent Mandibular Central Incisors and Permanent Mandibular First Molars as a Predictor of Width of Unerupted Canine and Premolars

Abstract

Objective: To determine linear regression equation to predict the mesiodistal widths of the permanent canines and premolars based on the sum of the widths of the two permanent mandibular first molars and two mandibular central incisors. Material and Methods: The sample consisted of 800 (400 males and 400 females) permanent dentition casts of Chhattisgarh population. Mesiodistal crown widths of teeth were measured with digital caliper. The correlation and linear regression equations between the calculated four teeth (two permanent mandibular first molars and two central incisors) and the canine-premolars segments of both the arches were developed. Results: No significant differences were found in right and left side of the arch. Sexual dimorphism was significant in teeth sizes with higher mesiodistal dimension in males. A good correlation values varying from 0.51 to 0.67 was found. New standardized regression equations were formulated for the prediction of the mesiodistal widths of unerupted canines and premolars for Chhattisgarh population. Conclusion: Calculating mesiodistal widths of unerupted canine and premolars with help of two permanent mandibular molars and two mandibular central incisors, which erupt early in the oral cavity, can be an alternative and best predictor for the mixed dentition analysis.

Application of Moyer’s mixed dentition analysis and establishing probability tables in a sample of Pakistani population

“…The findings of current study concur with those of other studies that claimed that only the mandibular permanent incisors are not better predictors of outcome. 8,10,16 According to other radiology and non-radio-graphic methods, the difference between the actual and predicted value in the current study, which used the maxillary first molar as predictors, is among the smallest overall, except in the mandible in girls, where mandibular incisors and the maxillary first molar were the best predictors. In comparison to mandibular first molars, maxillary first molars have an advantage because mandibular first molars are harder to measure because they are hidden by the distal gingival groove and are more susceptible to dental caries.…”

“…14,15 As other researchers have noted, the difference between tooth size in the right and left sides in the current study was very small and statistically insignificant. 8,10 As a result, the calculation used the mean value of the MD diameters of these teeth.…”

“…Lower incisors are not a better predictor for the estimation of the MDW of un-erupted canines and premolars, according to a recent report from several researchers. [8][9][10][11] These researchers introduced additional predictors with a higher degree of accuracy, namely the mandibular and maxillary permanent first molars. 10 To determine which tooth combinations in Pakistani populations provide the best predictions, various tooth combinations were used as predictors in the current study, and values of r, R2, and SEE were recorded.…”

“…[8][9][10][11] These researchers introduced additional predictors with a higher degree of accuracy, namely the mandibular and maxillary permanent first molars. 10 To determine which tooth combinations in Pakistani populations provide the best predictions, various tooth combinations were used as predictors in the current study, and values of r, R2, and SEE were recorded. We observed that regression equation centered on the width of maxillary first molars more precisely anticipate the size of both Ucps, Lcps in boys and Ucps in young female adolescents.…”

“…For each gender and arch, regression equations were developed separately. 10 The following was defined as a regression equation:…”