Contribution of genetic and environmental factors to obesity indices and their overlap

(2026) Contribution of genetic and environmental factors to obesity indices and their overlap. Diabetes Obesity & Metabolism. pp. 3344-3354. ISSN 1462-8902

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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.<br /> Materials and Methods: We used four anthropometric measurements (height, weight, waist and hip circumference) from the baseline of the multi-generational Life-lines cohort study to calculate 12 indices of obesity and body fat distribution. Variance components attributable to genetic (h(2)), shared (c) and unique environmental (e(2)) factors along with pairwise phenotypic (r(p)), genetic (r(G)), shared (r(c)), and unique environmental (r(E)) correlations were estimated using ASReml software. Genetic and environmental contributions to the phenotypic correlations were also quantified.<br /> Results: A total number of 152 298 adult individuals (females 89 091, 58.4) were included. Strong correlations were observed among most indices. (r(p), r(G), r(C), r(E) > 0.8) A body shape index (ABSI) and hip index (HI) were weakly correlated with other indices, largely independent of body mass index (BMI) (rp < 0.1) r and had the highest e(2), accounting for 64.2 and 75.7 of their variance. Height showed the highest heritability (h(2) = 91.7) , whereas most other traits were moderately heritable (h(2) = 45 + (- 55)) =<br /> 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.

Item Type: Article
Keywords: anthropometry body mass body shape genetic correlation heritability obesity phenotypic correlation lean body-weight anthropometric estimation coronary-disease heritability association phenotypes mortality density Endocrinology & Metabolism
Page Range: pp. 3344-3354
Journal or Publication Title: Diabetes Obesity & Metabolism
Journal Index: ISI
Volume: 28
Number: 4
Identification Number: https://doi.org/10.1111/dom.70530
ISSN: 1462-8902
Depositing User: خانم ناهید ضیائی
URI: http://eprints.mui.ac.ir/id/eprint/33976

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