Applicability of Bolton's Analysis and Regression-Based Tooth-Size Prediction Methods in a Young Adult Cohort

Introduction Accurate assessment of interarch tooth-size relationships is essential for orthodontic diagnosis, space analysis, and treatment planning. Bolton's analysis and regression-based methods such as Tonn's and Abhi's formulas are commonly used to predict incisor dimensions, but their applicability across different populations remains uncertain. Methods This observational validation study was conducted on 56 dental study models of young adults aged 18-25 years. Mesiodistal widths of maxillary and mandibular anterior teeth were measured using a digital Vernier caliper. Actual tooth dimensions were compared with values predicted using Bolton's anterior ratio, Tonn's formula, and Abhi's formula. Statistical analysis included paired t-test, Pearson correlation analysis, Bland-Altman agreement analysis, and linear regression analysis. Results The mean anterior Bolton's ratio was 78.02% ± 2.05%, significantly higher than Bolton's standard value of 77.2% (p = 0.003). Abhi's formula underestimated mandibular incisor width by 0.67 mm (p < 0.001), whereas Tonn's formula overestimated maxillary incisor width by 1.67 mm (p < 0.001). Bland-Altman analysis showed a mean bias of +1.67 mm for Tonn's formula, with 95% limits of agreement from -0.30 to +3.70 mm, and a mean bias of -0.67 mm for Abhi's formula, with 95% limits of agreement from -2.40 to +1.10 mm. Linear regression analysis showed a moderate positive relationship between the sum of maxillary and mandibular incisor widths (r = 0.725, R² = 0.526, standard error of estimate (SEE) = 0.92 mm). The derived equation showed good internal validation, with the predicted anterior Bolton's ratio of 78.11% showing no significant difference from the actual anterior Bolton's ratio of 78.02% (p = 0.977). Conclusions Bolton's analysis, Tonn's formula, and Abhi's formula demonstrated significant bias in the present cohort. Population-specific regression equations showed improved predictive accuracy and may provide more reliable guidance for orthodontic diagnosis and treatment planning.