ArticleNPJ digital medicine2024
Prediction of total and regional body composition from 3D body shape.
Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
What it found
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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
11 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Perception, assessment, and coaching: a systematic review and taxonomy of computer vision-based physical rehabilitation techniques.Frontiers in rehabilitation sciences · 2026Pooled it
- Smartphone and tablet-based 3D scanner for anthropometric assessments in adults: a systematic review of reliability, validity, and accuracy.Biomedical engineering online · 2025Pooled it
- BodyMAE: A Surface-Area Aware Masked Autoencoder for Body Composition Estimation from 3D Body Scans.medRxiv : the preprint server for health sciences · 2026Article
- Better BMI: Novel Digital Anthropometry Equations for Adiposity Assessment in the Chinese Population.Phenomics (Cham, Switzerland) · 2026Article
- 3D body shape-based phenotyping for precision risk stratification of metabolic syndrome.Lipids in health and disease · 2026Article
- Voxel-based Deep Regression for Enhanced Body Composition Estimation from 3D Body Scans.SN computer science · 2026Article
- Advancing Precision Diagnosis of Sarcopenic Obesity Through Digital Technologies, Wearables and Omics Data.Life (Basel, Switzerland) · 2025Review
- Obesity care in Chinese adults: from evidence to clinical practice.Precision clinical medicine · 2025Review
- Genetic ancestry influences body shape and obesity risk in Latin American populations.Scientific reports · 2025Article
- A Decade of Progress in Ultrasound Assessments of Subcutaneous and Total Body Fat: A Scoping Review.Life (Basel, Switzerland) · 2025Review
- Assessing alternative strategies for measuring metabolic risk.NPJ digital medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Accurate assessment of body composition is essential for evaluating the risk of chronic disease. 3D body shape, obtainable using smartphones, correlates strongly with body composition. We present a novel method that fits a 3D body mesh to a dual-energy X-ray absorptiometry (DXA) silhouette (emulating a single photograph) paired with anthropometric traits, and apply it to the multi-phase Fenland study comprising 12,435 adults. Using baseline data, we derive models predicting total and regional body composition metrics from these meshes. In Fenland follow-up data, all metrics were predicted with high correlations (r > 0.86). We also evaluate a smartphone app which reconstructs a 3D mesh from phone images to predict body composition metrics; this analysis also showed strong correlations (r > 0.84) for all metrics. The 3D body shape approach is a valid alternative to medical imaging that could offer accessible health parameters for monitoring the efficacy of lifestyle intervention programmes.
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.