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

Navarro, Pablo; Ramallo, Virgínia; Cintas, Celia; Ruderman, Anahí; Azevedo, Soledad de; Paschetta, Carolina; Pérez, Orlando J.; Pazos, Bruno; Delrieux, Claudio; González‐José, Rolando

doi:10.1002/ajhb.23323

Cited by 10 publications

(9 citation statements)

References 54 publications

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“…The SNPs were pruned to remove Linkage Disequilibrium and 90,000 SNPs were left for analysis after removing correlated, the ancestry estimation was performed with this SNP data. Supervised ancestry estimation using ADMIXTURE was performed, estimating three ancestry components for each individual: Native American, European, and African 1 , 45 .…”

Section: Methodsmentioning

confidence: 99%

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The impact of socioeconomic and phenotypic traits on self-perception of ethnicity in Latin America

Paschetta

Azevedo

Ramallo

et al. 2021

Sci Rep

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Self-perception of ethnicity is a complex social trait shaped by both, biological and non-biological factors. We developed a comprehensive analysis of ethnic self-perception (ESP) on a large sample of Latin American mestizos from five countries, differing in age, socio-economic and education context, external phenotypic attributes and genetic background. We measured the correlation of ESP against genomic ancestry, and the influence of physical appearance, socio-economic context, and education on the distortion observed between both. Here we show that genomic ancestry is correlated to aspects of physical appearance, which in turn affect the individual ethnic self-perceived ancestry. Also, we observe that, besides the significant correlation among genomic ancestry and ESP, specific physical or socio-economic attributes have a strong impact on self-perception. In addition, the distortion among ESP and genomic ancestry differs across age ranks/countries, probably suggesting the underlying effect of past public policies regarding identity. Our results indicate that individuals’ own ideas about its origins should be taken with caution, especially in aspects of modern life, including access to work, social policies, and public health key decisions such as drug administration, therapy design, and clinical trials, among others.

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Section: Methodsmentioning

confidence: 99%

“…The wealth variable were divided into three groups: low, medium and high. To allow comparisons across countries we converted an individual’s wealth score to a decile scale within each country 33 , 45 .…”

Section: Methodsmentioning

confidence: 99%

The impact of socioeconomic and phenotypic traits on self-perception of ethnicity in Latin America

Paschetta

Azevedo

Ramallo

et al. 2021

Sci Rep

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“…Participation was voluntary, without further selection criteria such as origin, demographic factors, or socioeconomic status [6]. A semimobile 3D photonic full-body scanner (Anthroscan VITUSbodyscan, Human Solution, Kaiserslautern, Germany) was used for body surface data acquisition, providing spatial resolution of <1 mm, with a point density of 300 data points per cm 3 . Comparative %BF (relative body fat) estimates were assessed by BIA (Seca mBCA 515, Reinach, Switzerland).…”

Section: Methodsmentioning

confidence: 99%

“…The use of 3D photonic body scans (BS) to assess body shape in epidemiologic studies and for daily fitness tracking is on the rise, thanks to developments in equipment and measurement methods that provide fast, reproducible, and increasingly accurate results [1][2][3][4][5][6][7]. However, an essential limitation of many currently available approaches is the lack of a precise approximation of adipose tissue distribution, particularly in more obese individuals, despite its relevance for assessing the risk for metabolic and cardiovascular diseases [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Associations between relative body fat and areal body surface roughness characteristics in 3D photonic body scans—a proof of feasibility

2021

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Introduction A reliable and accurate estimate of the percentage and distribution of adipose tissue in the human body is essential for evaluating the risk of developing chronic and noncommunicable diseases. A precise and differentiated method, which at the same time is fast, noninvasive, and straightforward to perform, would, therefore, be desirable. We sought a new approach to this research area by linking a person’s relative body fat with their body surface’s areal roughness characteristics. Materials and methods For this feasibility study, we compared areal surface roughness characteristics, assessed from 3D photonic full-body scans of 76 Swiss young men, and compared the results with body impedance-based estimates of relative body fat. We developed an innovative method for characterizing the areal surface roughness distribution of a person’s entire body, in a similar approach as it is currently used in geoscience or material science applications. We then performed a statistical analysis using different linear and stepwise regression models. Results In a stepwise regression analysis of areal surface roughness frequency tables, a combination of standard deviation, interquartile range, and mode showed the best association with relative body fat (R2 = 0.55, p < 0.0001). The best results were achieved by calculating the arithmetic mean height, capable of explaining up to three-quarters of the variance in relative body fat (R2 = 0.74, p < 0.001). Discussion and conclusion This study shows that areal surface roughness characteristics assessed from 3D photonic whole-body scans associate well with relative body fat, therefore representing a viable new approach to improve current 3D scanner-based methods for determining body composition and obesity-associated health risks. Further investigations may validate our method with other data or provide a more detailed understanding of the relation between the body’s areal surface characteristics and adipose tissue distribution by including larger and more diverse populations or focusing on particular body segments.

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“…As regards the potential use of multiple measures for a more precise prediction of body composition, previous studies only considered a limited number of predefined measures [42], and only few of them used automatic variable selection procedures to identify the best predictors [43][44][45]. Because some of the 150 standard measurements are strongly correlated among each other, model selection procedures and other techniques such as 3D surface geometry may have to account for these correlations [46][47][48][49][50][51]. Still, further research is needed to identify which of the 150 standard measurements are most relevant for the prediction of body composition, or whether multiple (and partly strongly correlated) measurements are relevant, and how they should be selected or combined to obtain the most reliable predictions.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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 (r 2 up to 0.92) and absolute fat mass (AFM, r 2 up to 0.87) but not for SMM (r 2 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 (r 2 up to 0.99) was achieved with models including 49 scanner measurements.

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

Cited by 10 publications

References 54 publications

The impact of socioeconomic and phenotypic traits on self-perception of ethnicity in Latin America

The impact of socioeconomic and phenotypic traits on self-perception of ethnicity in Latin America

Associations between relative body fat and areal body surface roughness characteristics in 3D photonic body scans—a proof of feasibility

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

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