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Facial anthropometry and sex discriminatory characteristics among University Of Ilorin students


A.S. Alabi
B.T. Oladimeji
S.B. Kareem
F.S. Lewu
A.T. Atoyebi
K.A. Akintunde
R.S. Opayemi

Abstract

Prediction of sex from different dimensions has considerable forensic value, not only for the identification of human remains but also in estimating sex from evidence at disaster sites and in corroborating reports from scientists. This study investigated the facial parameters and sexual dimorphism among University of Ilorin students.

A total of 376 students consisting of five major divisions in a university setting (sciences, social sciences, health sciences, technology and humanities) were used in the study. Standard anthropometric methods were used to measure facial height (LFH) and Bizygomatic Width (BZW) from a frontal repose photograph. Six different facial parameters were calculated. Data was analyzed using SPSS version 23 statistical software. Confidence level was set at 95%; as p-values ≤ 0.05 were considered significant.

Discriminant function analysis, mean standard deviation of mean and chi-square of the studied population were presented with P<0.05. For LFH in both sexes, a significant value of 0.010 was recorded indicating a statistically significant difference. For BZW in both sexes, a significant value of 0.039 was recorded also indicating a statistically significant difference.  For TFH in both sexes, 0.039 value was recorded also indicating a statistically significant difference in the measured facial parameters. UFH, MFH and F.I were found to be non-significant with recorded values of 0.077, 0.082 and 0.277 respectively. The p-value recorded for this non-significant values were greater than 0.05 (P>0.05).

The findings from this study clearly showed sex-associated difference in facial parameters but argue that a single set of facial parameters may not be applicable in sex grouping. Therefore, facial parameters can serve as adjunct in sex differentiation.

Keywords: Sexual dimorphism, Discriminant Function Analysis (DFA), University of Ilorin students, Facial parameters


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eISSN: 1117-4153