Comparative Evaluation of Regional and Prabhu et al.’s Population-Specific Dental Age Estimation Models in South Indian Children

Introduction: Accurate dental age estimation is pivotal in forensic, legal, and clinical contexts, particularly in countries like India, where official birth records may be unreliable or missing. Given the cultural, genetic, and environmental diversity within South India, a unified dental age estimation model may not adequately represent regional variations. Although a population-specific regression model was recently proposed for South Indian children, its generalizability across different states had not been evaluated. Materials and Methods: A cross-sectional study was conducted using 2000 digital orthopantomographs (OPGs) of children aged 5 to 16 years from six South Indian states and one Union Territory. The seven left permanent mandibular teeth were assessed for dental maturity using the normalized open apices method. Age was estimated using the population-specific regression equation developed by Prabhu et al . To evaluate regional variation, five state-specific regression models were derived and compared with the population model using adjusted R ² values and interaction terms involving state dummy variables. Results: Regression analysis showed that the state-specific dummy variables were statistically nonsignificant. The adjusted R ² values for the state-specific models showed only marginal differences (range: −0.46 to 0.45) from the population model (adjusted R ²  = 73.4%). Minor variation in the influence of the “sum” variable was observed between Karnataka and Andhra Pradesh, but this did not translate into meaningful improvements in predictive performance. Conclusion: The study concludes that a single, population-specific regression equation developed by Prabhu et al . is sufficient for accurate dental age estimation in South Indian children. The development of separate equations for individual states is unnecessary, making this model suitable for broad forensic and legal use across South India.