Abstract
BACKGROUND: Estimation of age, stature, sex, and ancestry contributes to the establishment of the biological profile of the deceased in forensic examinations. Assessment of the body weight aids in the approximation of the overall body size of the individual which may help in the forensic identification process. In clinical examinations, body weight assessment assumes importance in cases where body weight measurement is a challenging task due to illness and body deformity. OBJECTIVE: The present research was conducted to estimate the body weight from the percutaneous width of the bones and joints with the help of prediction equations. METHODS: The study was carried out on 344 adults (172 Females and 172 Males) aged between 18 and 25 years from the Himachal Pradesh State of North India. Eleven anthropometric measurements including height vertex, mid-arm circumference, humerus bicondylar width, transverse chest breadth, sagittal chest breadth, bi-iliac breadth, handbreadth, femur bicondylar breadth, ankle breadth, foot breadth, and body weight were taken on each individual. The sex differences were evaluated by using independent student t-test and Mann-Whitney U test and the correlation between the body weight and the anthropometric variables was investigated by using both Karl Pearson's correlation coefficient and Spearman's rank correlation coefficient depending upon the normality of the data. Regression models for the estimation of body weight were calculated. Further, a validation study was carried out to check the accuracy and utility of the derived regression models by calculating the mean absolute percent prediction error (MAPPE). RESULTS: Significant sex differences were observed among all the anthropometric variables. The transverse chest breadth and mid-arm circumference were strongly correlated with the body weight, whereas, a good correlation was also observed in other measurements except for the ankle breadth. The SEE (Standard error of estimate) of the derived linear regression models was compared, and it was found that multiple linear regression models show better accuracy than simple linear regression models. The MAPPE was found to be less in the case of multiple linear regression models than the linear ones. CONCLUSION: The present investigation concludes that regression models can be used in the estimation of body weight from the percutaneous measurements and joint widths with reasonable accuracy in an Indian population.