Tanaka-johnston mixed dentition analysis for indian population

In diagnostic procedures, the critical area in mixed dentition research is finding sufficient room for permanent teeth erupting. Various analytical methods are available regarding mixed dentition; initially Tanaka and Johnston (TJ) space analysis was performed on a North European descent population. It is trust worthiness among various ethnic and racial groups to be predicted. In this analysis, the summation of MM (Maxillary & Mandibular) canine as well as premolars MWs associated with the sum of widths of 4 permanent mandibular incisors as well as the 1 permanent mandibular molar. Also, equations from linear regression were determined for estimating the number of permanent and premolar MWs. And finally, TJ analysis was evaluated with both the genders of Indian population. For study, two hundred Indian population subjects (100 of each sex) age group between 16-25 years are selected randomly, and research model was prepared to measure the MWs of permanent lower canines, incisors as well as premolars teeth. Both MM canine-premolar widths were also analyzed by using the TJ system. Data was used to estimate MM canine and premolar MWs via descriptive statistical analysis, correlation, Student’s t-test as well as regression analysis. Comparison was made of estimated and measured widths of both MM canines to premolars teeth. Thus, its findings showed that the estimated widths of MM canines to premolars teeth were overestimated as compared to their measured widths. New equations of linear regression were calculated by applying Y = a+b(X) formula, where "a" and "b" are constants, Y is expected canine premolar distance, and X is lower incisal-first molar distance. Equations of linear regression, for both genders (male and European Journal of Molecular & Clinical Medicine ISSN 2515-8260 Volume 08, Issue 03 , 2021 3548 female) were extracted separately. Overall, conclusion is that the original TJ process for Indian population is overestimated. Prediction tables as well as for linear regression new separate equations were created for both genders, which the clinician could use more conveniently.