- Cukurova Medical Journal
- Vol: 48 Issue: 2
- Estimation of sex using craniofacial dimensions: a study of CT scan images in Kaduna State, Nigeria
Estimation of sex using craniofacial dimensions: a study of CT scan images in Kaduna State, Nigeria
Authors : Aliyu Jaafar, Tanko Murdakai, Moses Asongu Tersoo, Abdulrazak Muhammad, Zainab M. Bauchi, Usman Farrau, Ibrahim Sambo Aliyu, Lawan H. Adamu, Muhammad Zaria Ibrahim, Yusuf Nadabo Abdullahi, Zaharaddeen Muhammad Zaharaddeen Muhammad Yusuf, Amiru Jaafar
Pages : 607-615
Doi:10.17826/cumj.1219426
View : 129 | Download : 126
Publication Date : 2023-07-02
Article Type : Research Article
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 (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 (13.49±0.57 cm), maximum cranial length (18.11±0.74 cm), and bizygomatic length (12.64±0.58 cm) of males were significantly greater than in females (13.35±0.49 cm), (17.82±0.66 cm) and (12.22±0.59 cm) respectively. The bizygomatic length on the receiver operating characteristic curve (Area under the curve = 0.711), logistic regression (odd ratio = 1.254), and discriminant function analysis (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 (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