Discriminant and Multiple Linear Regression Analysis for Sex and Stature Estimation Using Upper Arm and Forearm-Hand Length: A Study among Mgbidi Population of Imo State Nigeria
Published: 2024-06-03
Page: 295-305
Issue: 2024 - Volume 7 [Issue 1]
Nicholas Asiwe *
Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, University of Port Harcourt, Port Harcourt, Nigeria.
Oghenefego Michael Adheke
Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, University of Port Harcourt, Port Harcourt, Nigeria.
Ikechukwu Ezeah
Department of Surgery, Faculty of Clinical Sciences, University of Medical Sciences, Ondo, Ondo State, Nigeria and Department of Surgery, University of Medical Sciences Teaching Hospital, Ondo, Ondo State, Nigeria.
Michael Okon
Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, University of Port Harcourt, Port Harcourt, Nigeria.
Patrick Leo Filima
Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, University of Port Harcourt, Port Harcourt, Nigeria.
Oweiwari Victor Buseni
Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, University of Port Harcourt, Port Harcourt, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Background: The key aspect of forensic anthropology is the estimation of biological profile characteristics such as sex, age, stature, etc. Its application is wide across various disciplines like forensic science, anthropology, archaeology, and medical sciences. The study aims to estimate sex and stature using upper arm and forearm-hand length among the Mgbidi population of Imo State, Nigeria.
Methods: The study adopted a descriptive cross-sectional study design and a total of three hundred (150 males and 150 females) subjects were recruited for the study using multistage random sampling techniques. Data were obtained via direct measurements using mega-size calipers and a stadiometer. The obtained data was analyzed using IBM SPSS (version 25).
Results: The study shows that males are significantly higher in anthropometric values (p<0.05) than females. The multivariate regression among the sexes to estimate Stature using the right side anthropometry shows R=0.62 and SEE= 6.45 and on the left side anthropometry; R=0.61 and SEE=6.49. the stature predictive power of females was (R=0.52, 52.0% SEE= 5.35) and males (R=0.46, 46.0%, SEE=5.51) on the right and left side anthropometry shows females (R=0.49, 49.0%, SEE=5.42) and males was (R=0.45, 45.0%, SEE=5.72). the estimation for sex shows overall significance (X2=72.78, ƛ= 0.78, R=0.46, p<0.05) from the right side and the left side also shows significance in sexual estimation (X2= 71.84, ƛ=0.79, R=0.46, p<0.05).
Conclusion: The study reveals statistical differences in the upper arm and forearm-hand length compared to the sexes. Females are better predictors of stature using the upper arm and forearm-hand length than males and upper arm and forearm-hand length are good predictors of sex.
Keywords: Estimation, upper arm length, forearm-hand length, Mgbidi population, sex and stature