Stature estimation from the combination of clavicle, scapula, and sternum from 3D-VRT images in Chinese population.

Abstract

The objective of the present study was to generate multiple regression models for stature estimation on the basis the combination of the clavicle, scapula and sternum derived from 3D-VRT images in Chinese population. The study sample comprised 363 individuals from China, including 159 females and 204 males, with documented ages between 19 and 82 years. Separate multiple linear regression equations for estimating stature on the basis of the measurements from the clavicle, scapula and sternum were then devised for males and females. For assessing the correlation between the stature and measurements of the clavicle, scapula and sternum, the Pearson's correlation coefficient was calculated and its significance was tested by Students t test. Finally, the multiple regression equations calculated from the measurements of the clavicle, scapula and sternum in relation to stature for each sex were established in the present study. The accuracy of stature prediction ranged from 4.777 to 5.313 cm for male and from 4.388 to 4.658 cm for female. In conclusion, the present results provide indications that the combination of the clavicle, scapula and sternum should be used as alternatives for stature estimation, and the multiple equations presented for stature estimation seem to be a more accurate than the equations from single bone.