Applicability of Snodgrass method for age estimation from thoracic osteophytes: A computed tomographic study in an Indian population

Age estimation is fundamental to personal identification and biological profiling. Vertebral osteophytes are degenerative bony projections that progress with advancing age. This study aimed to validate the applicability of the Snodgrass method for age estimation from thoracic vertebral osteophytes in an Indian population using computed tomography (CT). CT scans of 400 individuals (200 males, 200 females), aged 18-90 years, who underwent chest/thoracic CT examination for clinical purposes were assessed using Snodgrass's five-stage scoring system. Observer reliability yielded quadratic-weighted Cohen's kappa (κ = 0.953-1). Osteophyte scores demonstrated strong positive correlations with age in males (R = 0.901), females (R = 0.815), and the total sample (R = 0.859). Linear regression models showed substantial predictive strength (R² = 0.665-0.811; SEE = 7.267-9.741 years; RMSE = 7.855-9.425; accuracies between 82.51%-85.81%) and minimal bias. Osteophyte scores increased progressively across decadal age groups, with a caudo-cranial direction and is predominated at T9-T12 thoracic levels during the 18 to 49 years and extended towards T1-T4 with advancing age. Thoracic level-specific regressions showed significant age associations in males (R = 0.581-0.764), females (R = 0.508-0.681), and the total sample (R = 0.568-0.718; all p < 0.01). T10 was the strongest predictor in males (R = 0.764; accuracy = 78.99%), T9 in females (R = 0.681; accuracy = 76.06%), and T9 in the total sample (R = 0.718). Decadal age-group models achieved greater than 96% accuracy in individuals aged 70 years and above. ANCOVA confirmed age as a significant predictor of osteophyte development (p < 0.001), whereas sex had no significant effect (p = 0.811). These findings provide baseline evidence supporting the applicability of Snodgrass method for forensic age estimation in the Indian population.