Estimation of sex using craniofacial dimensions: a study of CT scan images in Kaduna State, Nigeria

Authors : Aliyu JAAFAR, Tanko MURDAKAİ, Moses Asongu TERSOO, Abdulrazak MUHAMMAD, Zainab M. BAUCHİ, Usman FARRAU, Ibrahim Sambo ALİYU, Lawan H. ADAMU, Muhammad Zaria IBRAHİM, Yusuf NADABO ABDULLAHİ, Zaharaddeen Muhammad ZAHARADDEEN MUHAMMAD YUSUF, Amiru JAAFAR

Pages : 607-615

Doi:10.17826/cumj.1219426

View : 130 | Download : 125

Publication Date : 2023-07-02

Article Type : Research Paper

Abstract :Purpose: The aim of this study is to evaluate the potential of craniofacial dimensions in estimating sex in a sample population in Kaduna State, Nigeria. Materials and Methods: This is a retrospective study of normal CT scan images of 399 Crania insert ignore into journalissuearticles values(comprising 236 males and 163 females); of age range 18–95 years that came for CT scans for the diagnostic purpose at the National Ear Care Centre, Kaduna between the years of 2017–2019. The images were randomly taken at the archives of the Radiology Department of the institute on an axial plane. The five craniofacial dimensions were measured directly from the computer screen using Vitrea CT Software. Results: Maximum cranial width insert ignore into journalissuearticles values(13.49±0.57 cm);, maximum cranial length insert ignore into journalissuearticles values(18.11±0.74 cm);, and bizygomatic length insert ignore into journalissuearticles values(12.64±0.58 cm); of males were significantly greater than in females insert ignore into journalissuearticles values(13.35±0.49 cm);, insert ignore into journalissuearticles values(17.82±0.66 cm); and insert ignore into journalissuearticles values(12.22±0.59 cm); respectively. The bizygomatic length on the receiver operating characteristic curve insert ignore into journalissuearticles values(Area under the curve = 0.711);, logistic regression insert ignore into journalissuearticles values(odd ratio = 1.254);, and discriminant function analysis insert ignore into journalissuearticles values(percentage accuracy after cross validation = 67.4 %.); was the best single variable for estimating sex. Bizygomatic and maximum cranial length were selected as the significant estimators of sex by multivariate logistic regression with Adjusted Odd Ratios of 1.412 and 3.984 respectively, as well as discriminant function analysis insert ignore into journalissuearticles values(percentage accuracy after cross validation = 66.9%);. Conclusion: Among the sample population in Kaduna State, Nigeria, there is sexual dimorphism in some of the craniofacial variable found in CT scan images. Multivariate logistic regression may be the best model to utilize for predicting sex among the Kaduna State sample group.
Keywords : Adli bilim, kraniyofasiyal, cinsiyet tahmini, antropoloji