Three-Dimensional Soft-Tissue Facial Morphometry in Caucasian Obese Adults.

Chiarella Sforza, Simona Bertoli, Alessandro Leone, Riccardo Rosati, Marcio de Menezes, Alberto Battezzati

Abstract


Objective: To evaluate the facial morphology of Caucasian obese adults in relation to normal weight peers, and to study the association between three-dimensional soft-tissue facial measurements and cardiometabolic risk factors. Material and Methods: Nineteen Caucasian obese subjects aged 25 to 73 years underwent anthropometric measurements, blood samples and a stereophotogrammetric facial scan. Soft-tissue facial linear distances, angles, and volumes were obtained and compared to those collected on normal weight subjects by computing z-scores. Spearman correlation was used to assess the associations between facial measurements and metabolic parameters. Logistic regression analysis adjusted for sex and age was used to assess the risk of metabolic syndrome associated to the facial measurements. Results: Overall, when compared to normal weight persons, obese adults had a wider face in the horizontal dimension, with a middle face (maxilla) that was larger both in absolute value and relatively to the lower face (mandible), and a larger right side gonial angle (Wilcoxon test, p < 0.01). Only the mean (left and right) gonial angle was positively associated to serum triglycerides level, while the other facial measurements were associated with none of the cardiometabolic parameters. Moreover, none of the facial measurements was associated with the risk of metabolic syndrome. Conclusion: Despite larger facial dimensions and altered mandible/maxilla volume ratio, three-dimensional soft-tissue facial morphometry in Caucasian obese adults is not related to cardiometabolic risk factors. The actual association between morphological facial characteristics and clinical information on the health conditions of patients is still to be investigated.


Keywords


Anthropometry; Metabolic Syndrome; Obesity.

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References


Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014; 384(9945):766-81. https://doi.org/10.1016/S0140-6736(14)60460-8

Pischon T, Boeing H, Hoffmann K, Bergmann M, Schulze MB, Overvad K, et al. General and abdominal adiposity and risk of death in Europe. N Engl J Med 2008; 359(20):2105-20. https://doi.org/10.1056/NEJMoa0801891

Zhang C, Rexrode KM, van Dam RM, Li TY, Hu FB. Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: Sixteen years of follow-up in US women. Circulation 2008; 117(13):1658-67. https://doi.org/10.1161/CIRCULATIONAHA.107.739714

Levine JA, Ray A, Jensen MD. Relation between chubby cheeks and visceral fat. N Engl J Med 1998; 339(26):1946-7. https://doi.org/10.1056/NEJM199812243392619

Coetzee V, Perrett DI, Stephen ID. Facial adiposity: a cue to health? Perception 2009; 38(11):1700-11. https://doi.org/10.1068/p6423

Reither EN, Hauser RM, Swallen KC. Predicting adult health and mortality from adolescent facial characteristics in yearbook photographs. Demography 2009; 46(1):27-41.

Tinlin RM, Watkins CD, Welling LL, DeBruine LM, Al-Dujaili EA, Jones BC. Perceived facial adiposity conveys information about women's health. Br J Psychol 2013; 104(2):235-48. https://doi.org/10.1111/j.2044-8295.2012.02117.x.1

Lee BJ, Kim JY. Predicting visceral obesity based on facial characteristics. BMC Complement Altern Med 2014; 14:248. https://doi.org/10.1186/1472-6882-14-248

Nadazdyova1 A, Samohyl M. Gender and BMI differences in adult craniofacial parameters in Caucasian population: A pilot study. Pesqui Bras Odontopediatria Clin Integr 2017; 17(1):e3836. https://doi.org/10.4034/PBOCI.2017.171.60

de Menezes M, Rosati R, Ferrario VF, Sforza C. Accuracy and reproducibility of a 3-dimensional stereophotogrammetric imaging system. J Oral Maxillofac Surg 2010; 68(9):2129-35. https://doi.org/10.1016/j.joms.2009.09.036

Sforza C, Grandi G, De Menezes M, Tartaglia GM, Ferrario VF. Age- and sex-related changes in the normal human external nose. Forensic Sci Int 2011; 204(1-3):205.e1-9. https://doi.org/10.1016/j.forsciint.2010.07.027

Sforza C, de Menezes M, Ferrario V. Soft- and hard-tissue facial anthropometry in three dimensions: what's new. J Anthropol Sci 2013; 91:159-84. https://doi.org/10.4436/jass.91007

Knoops PG, Beaumont CA, Borghi A, Rodriguez-Florez N, Breakey RW, Rodgers W, et al. Comparison of three-dimensional scanner systems for craniomaxillofacial imaging. J Plast Reconstr Aesthet Surg 2017; 70(4):441-9. https://doi.org/10.1016/j.bjps.2016.12.015

Sforza C, Dolci C, Dellavia C, Gibelli DM, Tartaglia GM, Elamin F. Abnormal variations in the facial soft tissues of individuals with Down syndrome: Sudan versus Italy. Cleft Palate Craniofac J 2015; 52(5):588-96. https://doi.org/10.1597/14-082

Sforza C, Dolci C, Tartaglia GM, Ferrario VF. Soft-tissue 3D facial imaging in children and adolescents: towards the definition of new reference standards. Pesqui Bras Odontopediatria Clin Integr 2018, 18(1):e3854. https://doi.org/10.4034/PBOCI.2018.181.ed3

Al-Khatib AR, Rajion ZA, Masudi SM, Hassan R, Anderson PJ, Townsend GC. Stereophotogrammetric analysis of nasolabial morphology among Asian Malays: influence of age and sex. Cleft Palate Craniofac J 2012; 49(4):463-71. https://doi.org/10.1597/11-151

Djordjevic J, Lawlor DA, Zhurov AI, Toma AM, Playle R, Richmond S. A population-based cross-sectional study of the association between facial morphology and cardiometabolic risk factors in adolescence. BMJ Open 2013; 3(5):e002910. https://doi.org/10.1136/bmjopen-2013-002910

Gibelli D, Pucciarelli V, Cappella A, Dolci C, Sforza C. Are portable stereophotogrammetric devices reliable in facial imaging? A validation study of VECTRA H1 device. J Oral Maxillofac Surg 2018; 76(8):1772-84. https://doi.org/10.1016/j.joms.2018.01.021

Tanikawa C, Zere E, Takada K. Sexual dimorphism in the facial morphology of adult humans: A three-dimensional analysis. Homo 2016; 67(1):23-49. https://doi.org/10.1016/j.jchb.2015.10.001

Pucciarelli V, Bertoli S, Codari M, De Amicis R, De Giorgis V, Battezzati A, et al. The face of Glut1-DS patients: A 3D craniofacial morphometric analysis. Clin Anat 2017; 30(5):644-52. https://doi.org/10.1002/ca.22890

Dolci C, Pucciarelli V, Gibelli DM, Codari M, Marelli S, Trifirò G, Pini A, Sforza C. The face in marfan syndrome: A 3D quantitative approach for a better definition of dysmorphic features. Clin Anat 2018; 31(3):380-386. https://doi.org/10.1002/ca.23034

Fang F, Clapham PJ, Chung KC. A systematic review of interethnic variability in facial dimensions. Plast Reconstr Surg 2011; 127(2):874-81. https://doi.org/10.1097/PRS.0b013e318200afdb

Ohrn K, Al-Kahlili B, Huggare J, Forsberg CM, Marcus C, Dahllöf G. Craniofacial morphology in obese adolescents. Acta Odontol Scand 2002; 60(4):193-7.

Ferrario VF, Dellavia C, Tartaglia GM, Turci M, Sforza C. Soft tissue facial morphology in obese adolescents: A three-dimensional noninvasive assessment. Angle Orthod 2004; 74(1):37-42.

Sadeghianrizi A, Forsberg CM, Marcus C, Dahllöf G. Craniofacial development in obese adolescents. Eur J Orthod 2005; 27(6):550-5. https://doi.org/10.1093/ejo/cji048

Banabilh SM, Suzina AH, Dinsuhaimi S, Samsudin AR, Singh GD. Craniofacial obesity in patients with obstructive sleep apnea. Sleep Breath 2009; 13(1):19-24. https://doi.org/10.1007/s11325-008-0211-9

Sforza C, Grandi G, Catti F, Tommasi DG, Ugolini A, Ferrario VF. Age- and sex-related changes in the soft tissues of the orbital region. Forensic Sci Int 2009; 185(1-3):115.e1-8. https://doi.org/10.1016/j.forsciint.2008.12.010

Lohmann TG, Roche AF, Martorell R. Anthropometric Standardization Reference Manual. Human Kinetics Books, Champaign, IL, USA, 1988.

Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr 1974; 32(1):77-97.

Siri WE. Body composition from fluid spaces and density: Analysis of methods. 1961. Nutrition 1993; 9(5):480-91.

Weinberg SM, Raffensperger ZD, Kesterke MJ, Heike CL, Cunningham ML, Hecht JT, et al. The 3D facial norms database: part 1. A web-based craniofacial anthropometric and image repository for the clinical and research community. Cleft Palate Craniofac J 2016; 53(6):e185-e197. https://doi.org/10.1597/15-199

Kook MS, Jung S, Park HJ, Oh HK, Ryu SY, Cho JH, et al. A comparison study of different facial soft tissue analysis methods. J Craniomaxillofac Surg 2014; 42(5):648-56. https://doi.org/10.1016/j.jcms.2013.09.010

Andrade LM, Rodrigues da Silva AMB, Magri LV, Rodrigues da Silva MAM. Repeatability study of angular and linear measurements on facial morphology analysis by means of stereophotogrammetry. J Craniofac Surg 2017; 28(4):1107-11. https://doi.org/10.1097/SCS.0000000000003554

Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, et al. Joint national committee on prevention, detection, evaluation, and treatment of high blood pressure. National heart, lung, and blood institute; National high blood pressure education program coordinating committee. Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure. Hypertension 2003; 42(6):1206-52. https://doi.org/10.1161/01.HYP.0000107251.49515.c2

Alberti KGMM, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009; 120(16):1640-5. https://doi.org/10.1161/CIRCULATIONAHA.109.192644

Windhager S, Patocka K, Schaefer K. Body fat and facial shape are correlated in female adolescents. Am J Hum Biol. 2013;25(6):847-50. https://doi.org/10.1002/ajhb.22444

Lee BJ, Do JH, Kim JY. A classification method of normal and overweight females based on facial features for automated medical applications. J Biomed Biotechnol 2012; 2012:834578. https://doi.org/10.1155/2012/834578




DOI: http://dx.doi.org/10.4034/PBOCI.2019.191.06

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