Allometry Between Measures of Body Size and Shape in a Large Population-Based Cohort

Abstract

Traditional manual anthropometrics have been used extensively in practice to derive indicators of health risk, such as growth disorders or obesity; however, these approaches typically reduce the complex shape of human bodies to a series of simple size measures. Three-dimensional (3D) imaging systems capture detailed and accurate images of human morphology which have the potential for use within health applications. However, previous studies utilising 3D imaging have only assessed body shape based on combinations and relative proportions of large numbers of size measures. Geometric morphometrics - established mathematical methods within the fields of anthropology and evolutionary biology - analyse morphological variation and allometric relationships between the size and shape of organisms. The aim of this study was to investigate allometry between traditional measures of body size and novel measures of body shape. Developed analytical procedures were utilised to extract scale-invariant features of torso shape from 3D imaging data of 4,405 male participants in the LIFE-Adult cohort, obtained using a Vitus Smart XXL laser scanner. Partial least squares regression (PLSR) models were created to determine how human body shape changes with increases in body size. This study demonstrated that linear combinations of size measures can explain between 3.2 - 84.4 % of the variation in individual body shape features. These results indicate that measures of human body shape show a complex dependence on body size, providing complementary anthropometric features of the human body. The aim of future studies will be to investigate the efficacy of these measures in clinical epidemiology.