Volumetric differences in body shape among adults with differing body mass index values: An analysis using three-dimensional body scans

Kinematic Analysis of Water Polo Player in the Vertical Thrust Performance to Determine the Force-Velocity and Power-Velocity Relationships in Water: A Preliminary Study

BACKGROUND

To date, studies on muscle force and power-velocity (F-v and P-v) relationships performed in water are absent.

AIM

The goal of this study is to derive the F-v and P-v regression models of water polo players in water vertical thrust performance at increasing load.

METHODS

After use of a control object for direct linear transformation, displacement over the water and elapsed time was measured, by using a high-speed 2D-videoanalysis system, on 14 players involved in the study.

RESULTS

Intra-operator and player's performance interclass correlation coefficient (ICC) reliability showed an excellent level of reproducibility for all kinematic and dynamic measurements considered in this study with a coefficient of variation (CV) of less than 4.5%. Results of this study have shown that an exponential force-velocity relationship seems to explain better the propulsive force exerted in the water in lifting increasing loads compared to the linear one, while the power and velocity have been shown to follow a second-order polynomial regression model.

CONCLUSION

Given the accuracy of the video analysis, the high reliability and the specificity of the results, it is pointed out that video analysis can be a valid method to determine force-velocity and power-velocity curves in a specific environment to evaluate the neuromuscular profile of each water polo player.

body2vec: 3D Point Cloud Reconstruction for Precise Anthropometry with Handheld Devices

Current point cloud extraction methods based on photogrammetry generate large amounts of spurious detections that hamper useful 3D mesh reconstructions or, even worse, the possibility of adequate measurements. Moreover, noise removal methods for point clouds are complex, slow and incapable to cope with semantic noise. In this work, we present body2vec, a model-based body segmentation tool that uses a specifically trained Neural Network architecture. Body2vec is capable to perform human body point cloud reconstruction from videos taken on hand-held devices (smartphones or tablets), achieving high quality anthropometric measurements. The main contribution of the proposed workflow is to perform a background removal step, thus avoiding the spurious points generation that is usual in photogrammetric reconstruction. A group of 60 persons were taped with a smartphone, and the corresponding point clouds were obtained automatically with standard photogrammetric methods. We used as a 3D silver standard the clean meshes obtained at the same time with LiDAR sensors post-processed and noise-filtered by expert anthropological biologists. Finally, we used as gold standard anthropometric measurements of the waist and hip of the same people, taken by expert anthropometrists. Applying our method to the raw videos significantly enhanced the quality of the results of the point cloud as compared with the LiDAR-based mesh, and of the anthropometric measurements as compared with the actual hip and waist perimeter measured by the anthropometrists. In both contexts, the resulting quality of body2vec is equivalent to the LiDAR reconstruction.

Obesity, genomic ancestry, and socioeconomic variables in Latin American mestizos

OBJECTIVES

This article aims to assess the contribution of genomic ancestry and socioeconomic status to obesity in a sample of admixed Latin Americans.

METHODS

The study comprised 6776 adult volunteers from Brazil, Chile, Colombia, Mexico, and Peru. Each volunteer completed a questionnaire about socioeconomic variables. Anthropometric variables such as weight, height, waist, and hip circumference were measured to calculate body indices: body mass index, waist-to-hip ratio and waist-to-height ratio (WHtR). Genetic data were extracted from blood samples, and ancestry was estimated using chip genotypes. Multiple linear regression was used to evaluate the relationship between the indices and ancestry, educational level, and economic well-being. The body indices were dichotomized to obesity indices by using appropriate thresholds. Odds ratios were calculated for each obesity index.

RESULTS

The sample showed high percentages of obesity by all measurements. However, indices did not overlap consistently when classifying obesity. WHtR resulted in the highest prevalence of obesity. Overall, women with low education level and men with high economic wellness were more likely to be obese. American ancestry was statistically associated with obesity indices, although to a lesser extent than socioeconomic variables.

CONCLUSIONS

The proportion of obesity was heavily dependent on the index and the population. Genomic ancestry has a significant influence on the anthropometric measurements, especially on central adiposity. As a whole, we detected a large interpopulation variation that suggests that better approaches to overweight and obesity phenotypes are needed in order to obtain more precise reference values.

Lower Extremity Geometry in Morbid Obesity-Considerations for Total Knee Arthroplasty

BACKGROUND

Obesity has been associated with varying adverse outcomes related to total knee arthroplasty (TKA) and has long been associated with various mechanical complications. Computational modeling holds promise for investigating biomechanical aberrations related to TKA in obese patients. However, basic anthropometric information regarding the shape of the lower extremity in obese patients is lacking. We, therefore, developed a method to determine lower extremity shape both generally and subject specific as a function of body mass index (BMI) and sex.

METHODS

A unique set of 4 radiographs (knee anteroposterior/lateral; EOS long-leg alignment anteroposterior/lateral) were reviewed for patients with BMI exceeding 30 kg/m² before undergoing TKA. Soft tissue thickness in both the coronal and sagittal planes, including anterior adipose tissue thickness overlying the tibial tubercle and patella, was measured. Elliptical parameters were then determined for any distance along the lower extremity. Additional measurements were obtained, including prepatellar thickness and pretubercular thickness and anteroposterior and mediolateral dimensions of the proximal tibia. A total of 232 obese subjects were analyzed.

RESULTS

Girth increased as a function of BMI. Anterior prepatellar and pretubercular subcutaneous fat thickness in females exceeded that in males for all values of BMI. Wide variation was seen with regard to overall patterns of adiposity among same-sex subjects with similar BMI. Proximal tibial osseous dimensions did not demonstrate an association with BMI; however, males were found to have deeper and wider tibias compared with females.

CONCLUSIONS

BMI and sex influence lower extremity shape. The prediction algorithms developed here holds implications for future biomechanical studies of TKA in obese patients.

A Smartphone Application for Personal Assessments of Body Composition and Phenotyping

Personal assessments of body phenotype can enhance success in weight management but are limited by the lack of availability of practical methods. We describe a novel smart phone application of digital photography (DP) and determine its validity to estimate fat mass (FM). This approach utilizes the percent (%) occupancy of an individual lateral whole-body digital image and regions indicative of adipose accumulation associated with increased risk of cardio-metabolic disease. We measured 117 healthy adults (63 females and 54 males aged 19 to 65 years) with DP and dual X-ray absorptiometry (DXA) and report here the development and validation of this application. Inter-observer variability of the determination of % occupancy was 0.02%. Predicted and reference FM values were significantly related in females (R² = 0.949, SEE = 2.83) and males (R² = 0.907, SEE = 2.71). Differences between predicted and measured FM values were small (0.02 kg, p = 0.96 and 0.07 kg, p = 0.96) for females and males, respectively. No significant bias was found; limits of agreement ranged from 5.6 to −5.4 kg for females and from 5.6 to −5.7 kg for males. These promising results indicate that DP is a practical and valid method for personal body composition assessments.

Body volume, body fatness, and metabolic syndrome

Body volume by three-dimensional body scanning (3DBS) may be an alternative index for evaluating body fatness. The aim of this study was to evaluate the association of body volume with body fatness and metabolic syndrome. This study included 38 Korean women whose body volume was measured using 3DBS. We measured body fatness using dual-energy X-ray absorptiometry and computed tomography. Participants with metabolic syndrome were defined as having three or more of the following components: high blood pressure (≥130/85 mmHg), elevated fasting glucose (≥100 mg/dl), hypertriglyceridemia (≥150 mg/dl), low high-density lipoprotein-cholesterol (<50 mg/dl), and abdominal obesity measured by waist circumference ≥80 cm. Total body, trunk, lower trunk, and limb volumes were significantly correlated with body mass index, waist circumference, total fat mass, percentage body fat, and abdominal fat areas. After adjustment for age, current smoking, at-risk drinking, and physical inactivity, the odds ratios (95% confidence intervals) for metabolic syndrome associated with total body, trunk, lower trunk, and limb volume were 1.08 (1.01-1.16), 1.11 (1.01-1.22), 1.20 (1.01-1.43), and 1.31 (1.04-1.66), respectively. Body volume by 3DBS was significantly associated with body fatness and metabolic syndrome. 3DBS may be a useful tool for detecting and monitoring body fatness and metabolic syndrome.