CRANIAL MEASUREMENTS

ESTIMATION OF STATURE FROM CRANIAL MEASUREMENTS

Abstract

Human body exhibits regular age, sex and race dependent proportions amongst
its various segments relative to its height. Knowledge of the cranial morphometry is important
from clinical and forensic view point. The stature of a person being genetically predetermined
is an inherent characteristic, the estimation of which is considered to be important assessment
in identification of human remains. Norms of regression formulae for calculation of height are
required for different populations. Objectives: To document norms for cranial dimensions and
present linear regression formulae for stature prediction in adult male and female population
of Southern Punjab. Place and duration of study: The study was conducted at the Multan
Medical and Dental College, Multan and took about fourteen months to complete. Material
and methods: The study was conducted on 672 adult individuals (430 males and 242 females)
from in and around the city of Multan in Punjab. Measurements of the head including maximum
cranial length (glabella-inion length), maximum cranial breadth (maximum bi-parietal diameter)
and maximum auricular head height were taken. Results were expressed as mean ± SD.
Height was measured in standing anatomical position. Correlation coefficient of Pearson
was used to find the relationship between various cranial dimensions using which the linear
regression formulae to predict the stature were derived. Results: The mean height of the study
population was found to be significantly different between genders. The males appeared to
be considerably taller than females. The mean cranial length, cranial breadth and auricular
head height the measurements were larger significantly in the males as compared to females.
Pearson’s correlation coefficient between stature and cranial measurements was found to be
highly positive for both sexes. Linear regression formulae to predict the stature from the cranial
dimensions were derived. Conclusion: The study is conducted to document norms for cranial
dimensions and it presented gender specific linear regression models for stature prediction in
adult South Punjab population.