ADULT STATURE RECONSTRUCTION FROM FACIAL ANTHROPOMETRY BY REGRESSION ANALYSIS IN THE RAJASTHAN POPULATION

Abstract

Background: Stature estimation is an important component of forensic identification, particularly when complete skeletal remains are not available. Facial anthropometry may provide useful supplementary predictors of stature; however, population-specific regression equations are required for reliable application. This study aimed to assess the relationship between facial anthropometric measurements and adult stature and to develop sex-specific regression equations for the Rajasthan population. Materials and Methods: An observational cross-sectional study was performed in the Department of Anatomy at Pacific Medical College and Hospital, located in Bhilon Ka Bedla, Udaipur, Rajasthan. The study included 600 healthy adults, comprising 300 men and 300 women. Stature, maximum facial height (MFH), and maximum facial breadth (MFB) were assessed using established anthropometric methods. . Pearson’s correlation, coefficient of determination (R²), simple linear regression, and multiple linear regression analyses were performed using SPSS version 26.0. Statistical significance was set at p < 0.05. Results: Mean stature was significantly higher in males (170.05 ± 7.553 cm) than in females (155.54 ± 8.216 cm; p < 0.0001). Maximum facial height and maximum facial breadth were also significantly greater in males than females (p < 0.0001). MFH showed a positive correlation with stature in males (r = 0.276) and females (r = 0.330), while MFB showed correlations of r = 0.331 and r = 0.374, respectively (p < 0.001). The MFH explained 7.6% of the stature variation in males and 10.9% in females whereas the MFB have 11.0% stature variation in males and 14.0% in females. Conclusion: Facial anthropometric measurements, particularly maximum facial height, demonstrated significant associations with adult stature. The combined regression models provided improved predictive performance compared with individual facial measurements. These findings support the use of sex and population-specific facial anthropometric regression equations as a supplementary method for forensic stature estimation in the Rajasthan population.