Contribution of Genetic and Environmental Factors to Obesity Indices and Their Overlap Publisher Pubmed



Ani A ; Nolte IM ; Vaez A ; Snieder H
Source: Diabetes, Obesity and Metabolism Published:2026

Abstract

Aims: Numerous indices have been developed to quantify obesity and the distribution of body fat; however, none are sufficient alone, and combined usage is complicated by their potential intercorrelation. This study aims to quantify genetic and environmental influences on anthropometric measures, 12 derived obesity indices and the extent of their overlap. Materials and Methods: We used four anthropometric measurements (height, weight, waist and hip circumference) from the baseline of the multi-generational Lifelines cohort study to calculate 12 indices of obesity and body fat distribution. Variance components attributable to genetic (h2), shared (c2) and unique environmental (e2) factors along with pairwise phenotypic (rP), genetic (rG), shared (rC), and unique environmental (rE) correlations were estimated using ASReml software. Genetic and environmental contributions to the phenotypic correlations were also quantified. Results: A total number of 152 298 adult individuals (females = 89 091, 58.4%) were included. Strong correlations were observed among most indices. (rP, rG, rC, rE > 0.8). A body shape index (ABSI) and hip index (HI) were weakly correlated with other indices, largely independent of body mass index (BMI) ((Formula presented.) < 0.10), and had the highest (Formula presented.), accounting for 64.2% and 75.7% of their variance. Height showed the highest heritability ((Formula presented.) = 91.7%), whereas most other traits were moderately heritable ((Formula presented.) = 45%–55%). Conclusion: The high correlation between the majority of obesity indices implies their redundancy. In contrast, ABSI and HI were relatively independent of BMI and other indices and showed the greatest influence from individual-specific environmental factors, suggesting their potential utility as complementary tools in epidemiological research, clinical risk prediction, and monitoring of targeted interventions. © 2026 The Author(s). Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.