1Professor and Head,
2Associate Professor,
3Associate Professor,
4Assistant Professor,
5Junior Resident,
*Corresponding Author: Dr. Akash Deep Aggarwal, Professor and Head,
Reconstructing stature from fragmented remains is an important part of the forensic identifying process. However, when non-native or skeletal-based regression equations applied to Indian populations, the errors are likely to be high in a view of ethnic differences in limb ratios. The objective of this study was to establish population-specific regression models for the estimation of stature using percutaneous measurements of long bones, arm span and digital segments in a North Indian young adult sample.
A cross-sectional study was conducted on 150 healthy North Indian students (77 males, 73 females) aged between 19 and 21 years. Stature, arm span and percutaneous lengths of the humeri, radii, ulnae, femora and tibiae as well as hand/ finger dimensions were taken. The formulas were calculated by regression analysis according to sex, based on Pearson’s correlation.
Sexual dimorphism was seen for all p< 0.001). The arm span correlated best with stature in men (r=0.68) and women (r=0.81), with the lowest SEE. Among the long bones, tibia and ulna were the most consistent predictors. Interestingly, digital dimensions such as index finger and hand length were found to be robust proxies when excluding principal long bones. The resulting percutaneous models showed superior performance compared with existing skeletal standards.
This research emphasizes that it is important to apply regional, sex-specific regression formulas in forensic practice. Arm span and hand measurements can be used in place of conventional long bone measures among North Indians.
Forensic Anthropology, Body Height, Anthropometry, Regression Analysis, Extremities, Sex Characteristics