Facial Analysis and Malocclusion of Children Attending a Dental School Clinic

Volume 4 - Issue 2

Estthelamares Lúcio da Silva Mello¹, Maria das Graças Duarte², Sônia Maria Soares da Silva³, Guilherme Soares Gomes da Silva⁴, Maria da Conceição de Barros Correia⁴, Leonardo Cavalcanti Bezerra dos Santos⁴, Marcela Silva de Vasconcelos⁴, Kátia Maria Gonçalves Marques⁴, Niedje Siqueira de Lima⁴ and Luciana de Barros Correia Fontes⁴*

Received: December 07, 2019;   Published: January 27, 2020

DOI: 10.32474/MADOHC.2020.04.000184

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Abstract

Objective: To characterize the face and the malocclusion type of children treated at a dental school. Materials and Methods: Retrospective analysis of clinical data with orofacial measurements of 103 children of 6 to 9 years of age with mixed dentition, who received the first care between 2016 and 2017. The data were obtained from the anthropometric measurements, using a caliper and digital technology. This work is linked to an extension project. The research project was approved by the Ethics Committee on Human Research of the Federal University of Pernambuco, Recife, northeast of Brazil, under protocol number 77741417.0.0000.5208. Statistical treatment was performed, with a margin of error of 5%.

Results: Most records occurred in male children (57.3%), mean age 7±0.9 years and brachyfacial type (40.8%), with significant differences according to gender (p<0.05). The mesofacial type was more frequent in males while the brachyfacial type was found in females. Regarding the distribution of malocclusions, there was a higher percentage for Angle Class I (40.8%) and for unilateral posterior crossbite (29.1%). Gender significant differences (p<0.05) occurred between lower third of the face height, dolichofacial type and class II malocclusion (together), all higher in males than in females. Conclusion: The most frequent type of face in children with mixed dentition was the brachyfacial and Angle Class I malocclusion. Morphological evaluation can be used in place of digital analysis because it has equivalence to it; despite different approaches to the measures.

Keywords: Face; Image processing; Computer-assisted; Child

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