Predicting Facial Anthropometry: A Novel Guide for Facial Reconstruction Using a Nigerian Igbo Sample

Nicholas Asiwe; Oghenefego Michael Adheke; Michael Okon; Josiah Soipiriala Hart

doi:10.18778/1898-6773.88.4.03

Authors

Nicholas Asiwe Department of Human Anatomy, Faculty of Basic Medical Sciences, University of Delta, Agbor, Nigeria https://orcid.org/0009-0007-0680-8843
Oghenefego Michael Adheke Department of Human Anatomy, Faculty of Basic Medical Sciences, Delta State University of Science and Technology, Ozoro, Nigeria https://orcid.org/0000-0002-6306-279X
Michael Okon Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, University of Port Harcourt, Choba, Nigeria https://orcid.org/0000-0003-3260-4848
Josiah Soipiriala Hart Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, University of Port Harcourt, Choba, Nigeria https://orcid.org/0009-0006-4396-5226

DOI:

https://doi.org/10.18778/1898-6773.88.4.03

Keywords:

facial morphometry, predictive models, Igbo ethnicity, baseline data, Nigerian anthropometry

Abstract

The present study was conducted to generate facial anthropometry baseline data for adult males and females of Igbo ethnicity in south-eastern Nigeria and to develop facial anthropometric prediction and correlation models. This cross-sectional, descriptive study design involved using 200 males and 200 females. The study criteria included subjects with no history of facial surgery and were within the age interval of 18–35 years. With the aid of spreading and digital caliper, different percutaneous facial measurements were obtained and data collected were analyzed both descriptively and inferentially. There were statistically significant sex differences in all metrics. Mandibular width (MW) correlated with both forehead width (FHW), lower facial height (LFH) and nasal width (NW) for both sexes. Total facial height (TFH) correlated with NW, upper facial height (UFH), mid-facial height (MFH), and lower facial height (LFH), while NW correlated with MW, UFH, MFH, and LFH. Predictive models developed using univariate regression analysis for both sexes showed that MW was a strong predictor of FHW, while UFH, MFH, and LFH were individually strong predictors of TFH (p<0.05). Further, MFH and LFH were significant predictors of FH for both sexes. By using multivariate regression analysis, it was revealed that the combination of both FW and FHW were strong predictors of MW, while the combination of UFH, MFH, and LFH were significant predictors of TFH. Conclusively, these new data should aid forensic and surgical efforts in Nigerian contexts. Our models can be tested on other underrepresented populations to better understand current methods in facial anthropometry.

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