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Abdominal fat distribution phenotypes and metabolic risk in premenopausal Asian women: insights beyond general adiposity measures.

Created on 19 Jun 2026

Authors

Yeshe M Kway, Navin Michael, Narasimhan Kothandaraman, Jadegoud Yaligar, Mya Thway Tint, Kok Hian Tan, Keith M Godfrey, Peter D Gluckman, Yap Seng Chong, Melvin Khee-Shing Leow, Jerry K Y Chan, Shiao-Yng Chan, Marielle V Fortier, Johan G Eriksson, Jonathan Huang, Yung Seng Lee, Mengling Feng, S Sendhil Velan, Suresh Anand Sadananthan

Published in

Scientific reports. Jun 18, 2026. Epub Jun 18, 2026.

Abstract

The rising prevalence of metabolic syndrome (MetS) and gestational diabetes mellitus (GDM) in women of reproductive age highlights their growing susceptibility to future cardiometabolic diseases. Both conditions signal early metabolic dysfunction tied to abdominal adiposity. We investigated whether relative abdominal adipose tissue (AAT) distribution characterises metabolic risk beyond general adiposity. Using magnetic resonance imaging, we quantified superficial (SSAT) and deep (DSAT) subcutaneous, intraperitoneal (IPAT), and retroperitoneal (RPAT) adipose tissue compartments to derive AAT distribution phenotypes from their relative contributions. These phenotypes were characterized with respect to MetS, GDM risk, ectopic fat accumulation, and metabolic profiles. The relative AAT distribution of higher %IPAT and lower %DSAT was a significant determinant for MetS. Women with both lower %IPAT and higher %DSAT exhibited the most favourable metabolic profiles, whereas women with higher %IPAT and lower %DSAT showed increased prevalence of MetS, hepatic steatosis, elevated high-sensitivity C-reactive protein, and 5.36-fold higher odds of developing GDM (95% CI 1.12-27.85). Notably, metabolic differences were observed despite similar overall adiposity including total AAT, body fat percentage, body mass index, and waist circumference. This suggests that AAT accumulation, particularly preferential DSAT over IPAT, captures metabolic heterogeneity and may support precision risk stratification of cardiometabolic disease in women.

PMID:
42315653
Bibliographic data and abstract were imported from PubMed on 19 Jun 2026.

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