Abstract

BackgroundManual anthropometric measurements are time-consuming and challenging to perform within acceptable intra- and inter-individual error margins in large studies. Three-dimensional (3D) laser body scanners provide a fast and precise alternative: within a few seconds the system produces a 3D image of the body topography and calculates some 150 standardised body size measurements.ObjectiveThe aim was to enhance the small number of existing validation studies and compare scan and manual techniques based on five selected measurements. We assessed the agreement between two repeated measurements within the two methods, analysed the direct agreement between the two methods, and explored the differences between the techniques when used in regressions assessing the effect of health related determinants on body shape indices.MethodsWe performed two repeated body scans on 123 volunteering young men using a Vitus Smart XXL body scanner. We manually measured height, waist, hip, buttock, and chest circumferences twice for each participant according to the WHO guidelines. The participants also filled in a basic questionnaire.ResultsMean differences between the two scan measurements were smaller than between the two manual measurements, and precision as well as intra-class correlation coefficients were higher. Both techniques were strongly correlated. When comparing means between both techniques we found significant differences: Height was systematically shorter by 2.1 cm, whereas waist, hip and bust circumference measurements were larger in the scans by 1.17–4.37 cm. In consequence, body shape indices also became larger and the prevalence of overweight was greater when calculated from the scans. Between 4.1% and 7.3% of the probands changed risk category from normal to overweight when classified based on the scans. However, when employing regression analyses the two measurement techniques resulted in very similar coefficients, confidence intervals, and p-values.ConclusionFor performing a large number of measurements in a large group of probands in a short time, body scans generally showed good feasibility, reliability, and validity in comparison to manual measurements. The systematic differences between the methods may result from their technical nature (contact vs. non-contact).

Highlights

  • Body size and shape are directly linked to human health: being both underweight or overweight/obese is associated with increased morbidity and mortality risks (Engeland et al, 2003; World Health Organization (WHO), 2009; Faeh, Braun & Bopp, 2012; Flegal et al, 2013; Kit, Ogden & Flegal, 2014)

  • To test the repeatability and the agreement between the repeated measurements within each of the two methods (SM1–SM2 and MM1–MM2) we calculated mean differences, intraclass correlation coefficients (ICC), precision (Altman, 1999), and paired t -tests for two samples

  • We calculated mean differences, correlation coefficients, and paired t -tests for two samples

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Summary

Introduction

Body size and shape are directly linked to human health: being both underweight or overweight/obese is associated with increased morbidity and mortality risks (Engeland et al, 2003; World Health Organization (WHO), 2009; Faeh, Braun & Bopp, 2012; Flegal et al, 2013; Kit, Ogden & Flegal, 2014). The standard imaging methods used to precisely assess body composition and fat distribution (MRI, DEXA, CT) are either invasive or time-consuming, and expensive, and not suitable for large-scale monitoring studies (Machann et al, 2005; Lee & Gallagher, 2008). Mean differences between the two scan measurements were smaller than between the two manual measurements, and precision as well as intra-class correlation coefficients were higher. When comparing means between both techniques we found significant differences: Height was systematically shorter by 2.1 cm, whereas waist, hip and bust circumference measurements were larger in the scans by 1.17–4.37 cm. When employing regression analyses the two measurement techniques resulted in very similar coefficients, confidence intervals, and p-values

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