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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References

Adekunle AA, Olowo AY, Adetona M, James O, Adamson OO, Agbogidi FO, Oladega A, Ogunlewe M, Adeyemo WL, Busch T, Mossey PA. 2021. Variations in facial anthropometric measurements among major ethnic groups in Nigeria: a 3-dimentional stereophotogrammetry analysis. Face 2(3): 236–43. https://doi.org/10.1177/27325016211029013 DOI: https://doi.org/10.1177/27325016211029013

Alam MK, Mohd Noor NF, Basri R, Yew TF, Wen TH. 2015. Multiracial facial golden ratio and evaluation of facial appearance. PloS one 10(11): e0142914. https://doi.org/10.1371/journal.pone.0142914 DOI: https://doi.org/10.1371/journal.pone.0142914

Andrades, P., Cuevas, P., Hernández, R., Danilla, S., & Villalobos, R. (2018). Characterization of the orbital volume in normal population. J Cranio-Maxillo Sur 46(4), 594–599. https://doi.org/10.1016/j.jcms.2018.02.003 DOI: https://doi.org/10.1016/j.jcms.2018.02.003

Appiah NK, Appiah AK, Tetteh J, Diby TK, Abaidoo CS. 2023. Anthropometric study of facial and nasal indices of the Akan ethnic population of Ghana. Sri Lanka J Forensic Med Sci Law 14(1). https://doi.org/10.4038/sljfmsl.v14i1.7924 DOI: https://doi.org/10.4038/sljfmsl.v14i1.7924

Asiwe N, Adheke OM, Ezeah I, Okon M, Filima PL, Buseni OV. 2024. Discriminant and Multiple Linear Regression Analysis for Sex and Stature Estimation Using Upper Arm and Forearm-Hand Length: A Study among Mgbidi Population of Imo State Nigeria. AJMPCP 7(1): 295–305. https://doi.org/10.9734/ajmpcp/2025/v8i1272 DOI: https://doi.org/10.9734/ajmpcp/2025/v8i1272

Brielmann AA, Pelli DG. 2018. Aesthetics. Curr Biol 28(16): R859–63. https://doi.org/10.1016/j.cub.2018.06.004 DOI: https://doi.org/10.1016/j.cub.2018.06.004

Darkwah WK, Kadri A, Adormaa BB, Aidoo G. 2018. Cephalometric study of the relationship between facial morphology and ethnicity. Transl Res Anat 12: 20–4. https://doi.org/10.1016/j.tria.2018.07.001 DOI: https://doi.org/10.1016/j.tria.2018.07.001

Dodangheh M, Mokhtari T, Mojaverrostami S, Nemati M, Zarbakhsh S, Arabkheradmand A, Hassanzadeh G. 2018. Anthropometric study of the facial index in the population of medical students in Tehran University of Medical Sciences. GMJ Med 2(1): 51–7. https://doi.org/10.29088/gmjm.2018.51 DOI: https://doi.org/10.29088/GMJM.2018.51

Ernest MA, Sanu OO, Utomi IL, Ibeabuchi MN. 2018. Sexual dimorphism in facial soft tissue anthropometry among young adult Nigerians. J World Fed Orthod 7(3): 94–101. https://doi.org/10.1016/j.ejwf.2018.07.001 DOI: https://doi.org/10.1016/j.ejwf.2018.07.001

Fawehinmi HB, Oghenemavwe LE, Okoh PD, Ebieto CE, Irozulike FC, Asiwe N. 2024. Stature and Sex Estimation Using Some Linear Anthropometric Parameters: A Cross-Sectional Study of the Igbo Ethnic Group of Nigeria. AJMPCP 7(2): 482–489. https://doi.org/10.9734/ajmpcp/2025/v8i1266 DOI: https://doi.org/10.9734/ajmpcp/2025/v8i1266

Gračanin A, Bylsma LM, Vingerhoets AJ. 2018. Why only humans shed emotional tears: Evolutionary and cultural perspectives. Hum Nat 29: 104–33. https://doi.org/10.1007/s12110-018-9312-8 DOI: https://doi.org/10.1007/s12110-018-9312-8

Gupta S, Narwal A, Kamboj M, Sharma P, Makkar V, Raman RK. 2019. Baseline data of facial parameters in the population of Haryana: An anthropometric study. J Forensic Dent Sci 11(1): 28–34. https://doi.org/10.4103/jfo.jfds_12_19 DOI: https://doi.org/10.4103/jfo.jfds_12_19

Hamid MM, Faragalla AI, Ibrahim WS, Eldin AB. 2021. Facial Anthropometry among Saudi Population. Ann Med Health Sci Res 11(4).

Iroanya OO, Oyeyemi MT, Egwuatu TF. 2019. Sexual dimorphism and anthropometric comparison of craniofacial features of Igbo and Yoruba Undergraduate Students of University of Lagos, Nigeria. Braz J Forensic Sci Med Law Bioeth 9(1): 8–91. https://doi.org/10.17063/bjfs9(1)y201968 DOI: https://doi.org/10.17063/bjfs9(1)y201968

Jones AL. 2018. The influence of shape and colour cue classes on facial health perception. Evol Hum Behav 39(1): 19–29. https://doi.org/10.1016/j.evolhumbehav.2017.09.005 DOI: https://doi.org/10.1016/j.evolhumbehav.2017.09.005

Kleisner K, Tureček P, Roberts SC, Havlíček J, Valentova JV, Akoko RM, Leongómez JD, Apostol S, Varella MA, Saribay SA. 2021. How and why patterns of sexual dimorphism in human faces vary across the world. Sci Rep 11(1): 5978. https://doi.org/10.1038/s41598-021-85402-3 DOI: https://doi.org/10.1038/s41598-021-85402-3

Kundu A, Streed M, Galzi PJ, Johnson A. 2021. A detailed review of forensic facial reconstruction techniques. Med Leg J 89(2): 106–16. https://doi.org/10.1177/0025817221989591 DOI: https://doi.org/10.1177/0025817221989591

Monteiro LC, Ripardo RC, Torro-Alves N, Souza GS. 2023. Facial morphometric differences across face databases: influence of ethnicities and sex. Front Neurosci 17: 1130867. https://doi.org/10.3389/fnins.2023.1130867 DOI: https://doi.org/10.3389/fnins.2023.1130867

Pandey N, Gogoi P, Budathoki D, Gopal KC. 2015. Anthropometric study of facial index of Medical students. JKMC 4(4): 131–4. https://doi.org/10.3126/jkmc.v4i4.18256 DOI: https://doi.org/10.3126/jkmc.v4i4.18256

Richmond S, Howe LJ, Lewis S, Stergiakouli E, Zhurov A. 2018. Facial genetics: a brief overview. Front Genet 9: 462. https://doi.org/10.3389/fgene.2018.00462 DOI: https://doi.org/10.3389/fgene.2018.00462

Rokaya D, Suttagul K, Sapkota B, Maharjan SK. 2018. Gender based comparison of the relationships of maxillary anterior teeth and facial measurements. J Int Dent Med Res 11(2): 465–9.

Rostovtseva VV, Butovskaya ML, Mezentseva AA, Dashieva NB, Korotkova AA, Kavina A, Singh M. 2024. Cross-cultural differences in perception of facial trustworthiness based on geometric morphometric morphs. J Cross-Cult Psychol 55(2): 216–35. https://doi.org/10.1177/00220221231220013 DOI: https://doi.org/10.1177/00220221231220013

Sarna K, Sonigra KJ, Ngeow WC. 2023. A cross-sectional study to determine and compare the craniofacial anthropometric norms in a selected Kenyan and Chinese population. Plast Surg 31(1): 84–90. https://doi.org/10.1177/22925503211024763 DOI: https://doi.org/10.1177/22925503211024763

Ulrich L, Dugelay JL, Vezzetti E, Moos S, Marcolin F. 2019. Perspective morphometric criteria for facial beauty and proportion assessment. Appl Sci 10(1): 8. https://doi.org/10.3390/app10010008 DOI: https://doi.org/10.3390/app10010008

Villanueva NL, Afrooz PN, Carboy JA, Rohrich RJ. 2019. Nasal analysis: considerations for ethnic variation. Plast Reconstr Surg 143(6): 1179e–88e. https://doi.org/10.1097/prs.0000000000005619 DOI: https://doi.org/10.1097/PRS.0000000000005619

Virdi SS, Wertheim D, Naini FB. 2019. Normative anthropometry and proportions of the Kenyan-African face and comparative anthropometry in relation to African Americans and North American Whites. Maxillofac Plast Reconstr Surg 41:1–4. https://doi.org/10.1186/s40902-019-0191-7 DOI: https://doi.org/10.1186/s40902-019-0191-7

Voegeli R, Schoop R, Prestat-Marquis E, Rawlings AV, Shackelford TK, Fink B. 2021. Cross-cultural perception of female facial appearance: A multi-ethnic and multi-centre study. Plos one 16(1): e0245998. https://doi.org/10.1371/journal.pone.0245998 DOI: https://doi.org/10.1371/journal.pone.0245998

Zacharopoulos GV, Manios A, Kau CH, Velagrakis G, Tzanakakis GN, de Bree E. 2016. Anthropometric analysis of the face. J Craniofac Surg 27(1): e71–5. https://doi.org/10.1097/scs.0000000000002231 DOI: https://doi.org/10.1097/SCS.0000000000002231