Discriminant and Multivariate Regression Analysis for Estimating Sex and Stature Model Using Upper Limb Anthropometric Measurements among the Yoruba Ethnic Group of Nigeria - Okoh, Peter Done; David, Lekpa Kingdom; Fawehinmi, Hakeem Babatunde; Oghenemavwe, Loveday Ese; Oparaocha, Chile A.; Ebieto, Celestine Ebieto; Amadi, Michael Anozie; Irozulike, Faustina Chiamaka (Asian Journal of Advanced Research and Reports, 2025)
Background: Estimating sex and stature using body measurements is an important aspect of forensic anthropology, bioarchaeology, and human identification. Aim: The study is aimed to articulate the stature model using arm length, forearm-hand length and arm span amongst the Yoruba ethnic group of Nigeria. Method: Standardized Anthropometric techniques were used to measure the data. The Statistical Package for the Social Sciences (SPSS), version 23, was used for data analysis.  Discriminant and multivariate regression were used to estimate sex and stature. A probability less than 0.05 (p<0.05) was considered statistically significant, and 95% was denoted as the confidence level. A total of 400 subjects (200 females and 200 males) between the ages of 18-40 years were recruited for the study. Result: The multivariate regression among the sexes to estimate stature using arm length, forearm-hand length, and arm span shows (R=0.82, SEE= 4.74), the stature predictive power of male was (R= 0.65, SEM=4.25) and the female stature (R= 0.75, SEM=4.14). The estimation for sex shows overall significance (X2=252.28, ƛ= 0.53, p<0.05). Conclusion: The study shows a stronger correlation in all subjects. Also, it indicates that there is a stronger correlation in females than in males. Therefore, arm length, forearm-hand length and arm span can be used to predict height.