ArticleScientific reports2025
Genetic ancestry influences body shape and obesity risk in Latin American populations.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Genetic and epigenetic contribution of ABCG2 to gout susceptibility: a case-control study.Molecular biology reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
27 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Obesity is not simply a matter of excess weight. It also involves changes in structure and proportion in body morphology that can vary between populations and within individuals as they develop and age. Anthropometric measurements and their derived indices are widely used to study obesity. However, they present limitations to capture variations of fat distribution in the human body within a given population, and among different populations. Particularly, currently a problem in epidemiology is that cut-off points and health risk classifications based on anthropometric measures such as BMI, WHR or WHtR may not be equally valid for all population groups, especially when there are differences in genetic ancestry. Using data from [Formula: see text] Latin American adults, we evaluated the accuracy of traditional indices across gradients of Native American, European, and African ancestry, and a comparison with three-dimensional (3D) body shape analysis, which offers a promising venue for capturing these complexities. We found that traditional indices systematically misclassified obesity-related risk in certain ancestry groups, with WHR and WHtR showing ancestry-specific biases. In contrast, 3D body shape promises to capture nuanced variations in fat distribution and reduced ancestry-related misclassification. By leveraging techniques based on advanced geometric morphometry and image and data processing, we can better characterize the interaction between genetic ancestry and body composition, ultimately improving the accuracy of obesity diagnosis and stratification in Latin American populations. These results highlight the need for ancestry-aware obesity diagnostics and demonstrate that integrating advanced 3D morphometric techniques can improve risk assessment and guide precision public health strategies in Latin America and beyond. We demonstrate that incorporating 3D body shape data alongside genetic ancestry data improves the accuracy of obesity risk stratification in Latin American populations. Our proposed methods could be adapted, expanded and applied to other populations.
Indexed as
Identifiers
What Socratic 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 Socratic graph.