ArticleObesity (Silver Spring, Md.)2021
A pose-independent method for accurate and precise body composition from 3D optical scans.
Article in Obesity (Silver Spring, Md.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Smartphone prediction of skeletal muscle mass: model development and validation in adults.The American journal of clinical nutrition · 2023Trial
- Validation of digital anthropometric measurements during pregnancy: a longitudinal study.European journal of clinical nutrition · 2026Article
- Monitoring growth and body composition in children with 3-dimensional optical imaging: a pilot observational study.The American journal of clinical nutrition · 2026Observational
- Voxel-based Deep Regression for Enhanced Body Composition Estimation from 3D Body Scans.SN computer science · 2026Article
- Avatar generator: a tool for prediction of three-dimensional humanoid avatars from manual anthropometric measurements.Frontiers in nutrition · 2026Article
- Visual demonstration of weight loss and health risk improvement with a dual GIP and GLP-1 receptor agonist.International journal of obesity (2005) · 2025Article
- 3D convolutional deep learning for nonlinear estimation of body composition from whole body morphology.NPJ digital medicine · 2025Article
- Strengths and Limitations of BMI in the Diagnosis of Obesity: What is the Path Forward?Current obesity reports · 2024Review
- Evaluation of body shape as a human body composition assessment in isolated conditions and remote environments.NPJ microgravity · 2024Article
- Mobile phone applications for 3-dimensional scanning and digital anthropometry: a precision comparison with traditional scanners.European journal of clinical nutrition · 2024Article
- Generative deep learning furthers the understanding of local distributions of fat and muscle on body shape and health using 3D surface scans.Communications medicine · 2024Article
- Associations between 3D surface scanner derived anthropometric measurements and body composition in a cross-sectional study.European journal of clinical nutrition · 2023Article
- Cross-sectional assessment of body composition and detection of malnutrition risk in participants with low body mass index and eating disorders using 3D optical surface scans.The American journal of clinical nutrition · 2023Article
- Automated body composition estimation from device-agnostic 3D optical scans in pediatric populations.Clinical nutrition (Edinburgh, Scotland) · 2023Article
- Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity.The American journal of clinical nutrition · 2023Observational
- Monitoring body composition change for intervention studies with advancing 3D optical imaging technology in comparison to dual-energy X-ray absorptiometry.The American journal of clinical nutrition · 2023Article
- Modification and refinement of three-dimensional reconstruction to estimate body volume from a simulated single-camera image.Obesity science & practice · 2023Article
- Emergence of the adolescent obesity epidemic in the United States: five-decade visualization with humanoid avatars.International journal of obesity (2005) · 2022Observational
- Emergence of the obesity epidemic: 6-decade visualization with humanoid avatars.The American journal of clinical nutrition · 2022Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
objectiveThe aim of this study was to investigate whether digitally re-posing three-dimensional optical (3DO) whole-body scans to a standardized pose would improve body composition accuracy and precision regardless of the initial pose.
methodsHealthy adults (n = 540), stratified by sex, BMI, and age, completed whole-body 3DO and dual-energy X-ray absorptiometry (DXA) scans in the Shape Up! Adults study. The 3DO mesh vertices were represented with standardized templates and a low-dimensional space by principal component analysis (stratified by sex). The total sample was split into a training (80%) and test (20%) set for both males and females. Stepwise linear regression was used to build prediction models for body composition and anthropometry outputs using 3DO principal components (PCs).
resultsThe analysis included 472 participants after exclusions. After re-posing, three PCs described 95% of the shape variance in the male and female training sets. 3DO body composition accuracy compared with DXA was as follows: fat mass R
conclusionsRe-posed 3DO body shape PCs produced more accurate and precise body composition models that may be used in clinical or nonclinical settings when DXA is unavailable or when frequent ionizing radiation exposure is unwanted.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.