Open AccessApproximation of Height of an Individual Using Somatometry of Human Male Skull
Author(s) -
Jenash Acharya,
B. Suresh Kumar Shetty,
Rabin Shrestha,
Tanuj Kanchan
Publication year - 2017
Publication title -
journal of nepal medical association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.176
H-Index - 19
eISSN - 1815-672X
pISSN - 0028-2715
DOI - 10.31729/jnma.3140
Subject(s) - skull , medicine , standard deviation , statistics , standard error , regression analysis , population , linear regression , random variate , regression , demography , mathematics , surgery , environmental health , sociology , random variable
Numerous population specific studies conducted on skeletal remains have aimed to standardize the identification process. Known for ethnic and sexual variations, skull bone can also assist the identification process by estimating stature of the individual. The present study focuses on estimation of stature from skull bone using uni-variate and multi-variate regression models in south Indian population.Methods: Stature and Maximum cranial length, Maximum cranial Breadth, Bi-Pterion breadth, Parietal Cord and upper facial breadth were measured in wet skulls of 113 males, autopsied at Government Hospital of Kudla, Karantaka.Results: All five measurements showed significant correlation with stature (P value<0.001). MCL showed the highest (r=0.77) and UFB the lowest (r=0.42) degree of correlation. Standard error of estimate was lowest for MCL (4.90 cm) in the derived uni-variate regressions models. In the regression model obtained from the multi-variate analysis using all five skull measurements the β-coefficients were significant (P value<0.001) and the Standard Error of Estimation of the model was observed to be 4.45 cm. Bland-Altman analysis was conducted to explore the agreement between the actual length and the estimated lengths from the multivariate regression model. The mean of difference was 0.105 with a standard deviation of 4.3 and the upper and lower limits of agreement were 8.5 and -8.3 respectively.Conclusions: The study concludes that stature can be estimated from skull measurements with reasonable accuracy, observations of multi-variate regression models being more precise than the uni-variate regression models. Data collected from South India was compared with data available for Nepalese population and validates the use of data of Indian population for extrapolation in Nepalese population.Keywords: identification; linear regression; stature; skull; South India. [PubMed]