Estimation of Stature by Using Percutaneous Measurements of Long Bones of Leg and Forearm In South Indian Population - A Cross Sectional Study

Abstract

BACK GROUND AND OBJECTIVES: ix ABSTRACT `“Identificat ion is an individual’s birth right”. Stature is an important primar y characterist ic which defines an individual’s ident ity. Only method available for stature estimation in south Indians is by using multiplication factors derived for Mysoreans and literature regarding regression equations of South Indian population is lacking, hence the current study was conducted with the primary aim of deriving regression equations and multiplication factors that can be applied for estimation of stature of South Indian population. MATERIALS AND METHODS: Stature and percutaneous lengths of Tibia, Fibula, Radius and Ulna on both sides of 300 students (Males-150, Females-150) between 20-30 year age group was measured using standard anthropometric instruments and analysed for Karl Pearson correlation. Simple regression equations and multiplication factors were established and validated. RESULTS : There was no significant difference in the percutaneous length of right and left bones in both sexes (p>0.05). There is a positive correlation between percutaneous lengths of Tibia, Fibula, Radius and Ulna with stature on both sides amongst both the sexes. A set of 24 regression formulae and 24 multiplication factors were derived for both sexes for right and left sides from percutaneous length of long bones of leg and forearm. In both sexes stature estimated by regression formulae and multiplication factors was similar to average measured stature with an error of less than 1cm which was statistically insignificant (p> 0.05). INTERPRETATION AND CONCLUSION: There is a positive correlation between the long bones of the forearm and leg with that of stature. We have come out with new set of regression equations and multiplication factors .The regression equations and multiplication factors of present study can be used upon the South Indian population with fair degree of accuracy.