Body shape: implications in the study of obesity and related traits

NAVARRO, PABLO; RAMALLO, VIRGINIA; CELIA CINTAS; RUDERMAN, A.; DE AZEVEDO, SOLEDAD; CAROLINA PASCHETTA; ORLANDO PERÉZ; BRUNO PAZOS; CLAUDIO DELRIEUX; GONZÁLEZ-JOSÉ, ROLANDO

AMERICAN JOURNAL OF HUMAN BIOLOGY

WILEY-LISS, DIV JOHN WILEY & SONS INC

Lugar: New York; Año: 2019

1042-0533

Objectives. The diagnosis and treatment of obesity are usually based on traditional anthropometric variables including weight, height, and several body perimeters. Here we present a three-dimensional image-based computational approach aimed to capture the distribution of abdominal adipose tissue as an aspect of shape rather than a relationship among classical anthropometric measures. Methods. A morphometric approach based on landmarks and semi-landmarks placed upon the 3D torso surface was performed in order to quantify abdominal adiposity shape variation and its relation to classical indices. Specifically, we analyzed sets of body crosssectional circumferences collectively defining each specimen, along with anthropometric data taken on 112 volunteers. Results. Principal Component Analysis (PCA) was performed on 250 circumferences located along the abdominal region of each volunteer. PC1 (12.5%) and PC2 (7.5%) represented 20% of the total variation. ANCOVA model was used to compare shape variables (PCs) against anthropometric data (weight, height and waist and hip circumferences). The observed shape patterns are mainly related to nutritional status, followed by sexual dimorphism. In PCA calculated independently by sex, linear regression analyses provide statistically significant associations between PC1 and the three classical indexes: Body Mass Index (BMI), Waist-to-Height ratio (WHtR) and Waist-Hip ratio (WHR). Conclusion. Shape indicators predict well the behavior of classical markers but also evaluate three- dimensional and geometric features with more accuracy as related to the body shape under study. This approach also facilitates diagnosis and follow-up of therapies by using accessible 3D technology.