Mohammad Afzal Khan, Muhammad Naeem Chaudhry, Faris Mohammed Nour Altaf.
CRANIAL MEASUREMENTS; Estimation of stature from cranial measurements.
Professional Med J Jan ;22(8):1034-8.

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.

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