A new study reveals that widely used obesity measures like BMI, waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) may misclassify health risks in Latin American populations due to genetic ancestry differences. Researchers analyzed data from over 7,700 adults across seven countries and found that traditional indices often fail to capture ancestry-specific body composition patterns, leading to inaccurate risk assessments.
Individuals with predominantly Native American ancestry were consistently classified as high-risk across all indices, especially WHR and WHtR. In contrast, BMI tended to flag more individuals with European ancestry. These discrepancies suggest that uniform diagnostic thresholds may overestimate or underestimate risk depending on ancestry, potentially reinforcing structural bias in healthcare.
The study also found that country of origin had no significant impact on body shape variation, while genetic ancestry did. “Body shape variation is influenced by genetic ancestry,” the authors concluded, emphasizing that geopolitical borders are less relevant than ancestry in shaping obesity-related traits.
To improve accuracy, researchers used 3D body scanning and morphometric analysis, which revealed distinct body shape profiles linked to ancestry. Native American ancestry was associated with centralized fat distribution—linked to higher cardiometabolic risk—while European ancestry showed more peripheral fat patterns.
The authors call for ancestry-aware diagnostic criteria and scalable technologies like AI-assisted video morphometry to ensure equitable obesity assessment. Without such updates, current models risk perpetuating health disparities in genetically diverse populations.
See: “Genetic ancestry influences body shape and obesity risk in Latin American populations” (October 24, 2025)
