Perímetro abdominal: evidências para a predição da gordura corporal subcutânea em meninos escolares

Geraldo de Albuquerque Maranhão Neto; Leonardo Gomes de Oliveira Luz; Bruno Cleiton Macedo do Carmo; Rodrigo Cunha de Mello Pedreiro; Samara Sezana Costa; Arnaldo Tenório da Cunha Junior

doi:10.5585/conssaude.v14n4.6028

Authors

Geraldo de Albuquerque Maranhão Neto Universidade Salgado de Oliveira - UNIVERSO
Leonardo Gomes de Oliveira Luz Universidade Federal de Alagoas - Campus Arapiraca
Bruno Cleiton Macedo do Carmo Universidade Federal de Alagoas - Campus Arapiraca
Rodrigo Cunha de Mello Pedreiro Universidade Salgado de Oliveira - UNIVERSO
Samara Sezana Costa Universidade Salgado de Oliveira - UNIVERSO
Arnaldo Tenório da Cunha Junior Universidade Federal de Alagoas - Campus Arapiraca

DOI:

https://doi.org/10.5585/conssaude.v14n4.6028

Keywords:

Anthropometry, Regression Analysis, Abdominal Girth, Skinfold Thickness.

Abstract

Introduction: The diagnosis of overweight and obesity can be accomplished by anthropometry, for ease of implementation and low cost. Considering the concern for the distribution of fat, new strategies could be developed for the diagnosis of body composition from anthropometric measurements. Objectives: To investigate the association of the abdominal girth (AG) and waist girth (WG) separately, with the sum of two skinfolds (SF), triceps and subscapular; and include the girth with higher correlation levels in a regression equation to estimate the SF sum. Methods: A sample of 1,729 boys (9 and 14), the evaluation of body composition was composed by simple and compound anthropometric measurements. The Spearman correlation was used to determine the association between AG and WG with the sum of SF. A multiple linear regression was applied including AG and age to estimate the sum of SF. Results: The following equation was generated: Sum of SF = 1.16397 (AG) - 1.414922 (age) - 36.33021 (R = 0.83). The area under the ROC curve (AUC) was 83% for correctly identifying individuals below or above the 85th percentile of the SF sum. Conclusions: AG, together with age, becomes a good predictor of body fat, characterized as the sum of two SF in children and adolescent males.