Dataset Information

Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men.

ABSTRACT:

Introduction

Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering additional scan measurements.

Methods

We analysed 104 men aged 19-23. Bioelectrical Impedance Analysis was used to estimate whole body fat mass, visceral fat mass and skeletal muscle mass (SMM). For the 3D body scans, an Anthroscan VITUSbodyscan was used to automatically obtain 90 body shape measurements. Manual anthropometric measurements (height, weight, waist circumference) were also taken.

Results

Scanned and manually measured height, waist circumference, waist-to-height-ratio, and BMI were strongly correlated (Spearman Rho>0.96), however we also found systematic differences. When these variables were used to predict body fat or muscle mass, explained variation and prediction standard errors were similar between scanned and manual measurements. The univariable predictions performed well for both visceral fat (r2 up to 0.92) and absolute fat mass (AFM, r2 up to 0.87) but not for SMM (r2 up to 0.54). Of the 90 body scanner measures used in the multivariable prediction models, belly circumference and middle hip circumference were the most important predictors of body fat content. Stepwise forward model selection using the AIC criterion showed that the best predictive power (r2 up to 0.99) was achieved with models including 49 scanner measurements.

Conclusion

The use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models.

SUBMITTER: Sager R

PROVIDER: S-EPMC7289400 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men.

Sager Roman R Güsewell Sabine S Rühli Frank F Bender Nicole N Staub Kaspar K

PloS one 20200611 6

<h4>Introduction</h4>Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering ...[more]

PMID: 32525949

Similar Datasets

Project description: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).

Project description:IntroductionShort screenings of alcohol-related dependence are needed for population-based assessments. A clinical interview constitutes a reliable diagnosis often seen as gold standard, but it is costly and time consuming and as such, not suitable for population-based assessments. Therefore, self-reported questionnaires are needed (eg, alcohol use disorder (AUD) as in the Diagnostic and Statistic Manual of Mental Disorders (DSM) 5), but their reliability is questionable. Recent studies called for more evidence-based measurements for population-based screening (eg, heavy alcohol use over time (HAU)). This study aims to test the reliability of different self-reported measures of alcohol use.Methods and analysisBased on stratified random selection, 280 participants will be recruited from the French-speaking subgroup of the Swiss National Science Foundation-supported Cohort Study on Substance Use and Risk Factors (C-SURF). This cohort is a population-based sample of young Swiss men in their mid-20s (n=2668). The sample size calculation is based on a proportion non-inferiority test (alpha=5%, power=80%, margin of equivalence=10%, difference in sensitivity between self-reported AUD and HAU=5%, correlation between AUD and HAU=0.35, and drop-outs=15%). Assessment will include a clinical interview as the gold standard of alcohol-related dependence, self-reported alcohol measures (HAU, AUD and drinking patterns), biomarkers as gold standards of chronic excessive drinking, and health outcomes. To assess the validity of the self-reported alcohol measures, sensitivity analyses will be run. The associations between alcohol-related measures and health outcomes will be tested. A non-response analysis will be run using the previous waves of the C-SURF study using logistic regressions.Ethics and disseminationThe study protocol has been approved by the Human Research Ethics Committee of the Canton of Vaud, Switzerland (no. 2017-00776). The results will be submitted for publication in peer-reviewed journals and presented at national and international conferences.

Project description:Background and Aims: Internet gambling has recently grown in popularity, but relatively little is known about how online and the combination of online and offline (mixed) gambling are associated with gambling disorder (GD) and related problems. The present research examined in a cohort study sample of young Swiss men how their gambling activities and gambling-related problems differed across the spectrum from offline to online gambling. Sample: A general-population based sample from the Cohort Study on Substance Use Risk Factors (C-SURF), consisting of 5,352 young Swiss men (mean age 28.26 years old). Measures: The spectrum from exclusively offline to almost exclusively online (>90% of gambling money spent online) gambling was measured using one question about the proportion of gambling money spent online. Total money gambled and time spent on gambling were also assessed. GD severity (range 0-9) was measured using items reflecting the nine DSM-5 GD criteria. The number of gambling-related problems (e.g., financial difficulties, range 0-10), other addictive disorders and mental health problems were also inquired about. Methods: We estimated a generalised linear model using a count model (negative binomial link function) for GD severity and gambling-related problems associated with the amounts and proportions of money gambled online and offline. Results: The number of GD criteria were associated with money gambled online (IRR [95%CI] = 2.81 [2.43, 3.24]) and offline (IRR = 2.68 [2.40, 3.00]). This was also found for the number of gambling-related problems (IRR = 2.43 [2.13, 2.79] and IRR = 2.89 [2.59, 3.23]). Compared with exclusively-offline gamblers, mixed gamblers (26-90% of money gambled online) showed the highest levels of GD symptoms and gambling-related problems, followed by the almost-exclusively-online gamblers (≥91% money gambled online) and, overall, these associations were still significant after adjustment for overall involvement in gambling (time spent and money gambled). Levels of other addictive disorders and mental health problems were higher among mixed gamblers than among offline-only gamblers, but levels among almost-exclusively-online gamblers were not. Conclusions: Symptoms of gambling disorder and gambling related problems are highest among gamblers engaging in both offline and online gambling. Prevention efforts need to target the combination of offline and online gambling.

Project description:ObjectivesTo assess the benefit of waist circumference (WC) measurements during routine conscription medical examination in two military conscription centres in Switzerland. We compared the prevalence of overweight and obesity assessed by body mass index (BMI) with the prevalence of elevated disease risks assessed by WC and waist-to-height ratio (WHtR). We investigated how these measures were associated with systolic blood pressure, physical fitness performance and socioeconomic determinants.DesignCross-sectional survey.SettingTwo Swiss conscription centres in 2016.Participants1548 Swiss male conscripts, 18-22 years old.Main outcomePrevalences of elevated WC, WHtR and BMI values according to WHO categories. Secondary outcomes include systolic blood pressure, physical fitness performance and endurance performance.ResultsUsing BMI cut-points, 25.0% of all conscripts were overweight or obese. When applying WC cut-points, 9.2% had an increased disease risk, while 14.8% of the conscripts were at risk using WHtR cut-points. In the BMI range of 25.0-27.4?kg/m2, 3.6% showed an increased disease risk when using WC and 24.6% when using WHtR cut-points. Of the conscripts with a BMI of 27.5-29.9?kg/m2, 72.4% had an increased disease risk using WHtR, and 42.5% when using WC cut-points. Determinants of elevated BMI, WC and WHtR were low occupational status, rural residential area, older age and location in central and Northwest Switzerland. Systolic blood pressure increased with increasing BMI, WC and WHtR. Physical fitness and endurance test performances decreased with increasing BMI, WC and WHtR.ConclusionIn addition to BMI, WC and WHtR add relevant information to the health assessment of young men. However, the prevalence of overweight/increased health risk differed when using BMI, WC or WHtR. Further studies should include measures of body composition to test whether these differences arise from muscular young men within the overweight BMI range, who had a normal WC.

Dataset Information

Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men.

Introduction

Methods

Results

Conclusion

Publications

Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets