Abdominal visceral-to-subcutaneous fat ratio in the prediction of metabolic syndrome risk in Japanese Americans followed prospectively for 10-years loses information.

Obes Res Clin Pract

Seattle Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, WA, USA; Department of Medicine, School of Medicine, University of Washington, Seattle, WA, USA.

Published: September 2024

Aims: Visceral fat predicts the development of metabolic syndrome (MetS), but it is not known whether the visceral to subcutaneous fat area ratio (VSR) measured using imaging predicts MetS risk as well or better. Thus, we aimed to examine if VSR predicted future risk of MetS over 10-years.

Methods: We followed 329 participants in the longitudinal Japanese American Community Diabetes Study without MetS at baseline for its development over 10 years. Intra-abdominal (VFA) and subcutaneous abdominal (SFA) fat areas were measured at baseline and 10-years and used to calculate VSR. Logistic regression was used to estimate the odds of incident MetS by baseline and 10-year change in VSR and other adipose depots with and without adjustment for baseline MetS features. Areas under ROC curves were calculated in predicting the development of MetS.

Results: 99 participants developed MetS over 10-years. Logistic regression models showed a higher odds of incident MetS with greater VSR and 10-year VSR change (OR = 1.67, 95 % CI 1.11-2.51; OR = 1.46, 95 % CI 1.06-2.01, respectively) adjusting for age, sex, and MetS features at baseline. However, VSR alone performed poorly at discriminating (AUROC 0.5807) compared to VFA (AUROC 0.6970, p < 0.001) or a logistic model incorporating VFA and SFA (AUROC 0.7221, p = 0.001).

Conclusions: VSR and VFA predict 10-year MetS risk in Japanese Americans, confirming the importance of relatively greater fat distribution in the visceral depot in the development of MetS. However, VSR is a weaker predictor of MetS development and provides less information compared to VFA alone, and its further use in predicting metabolic abnormalities is not recommended.

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http://dx.doi.org/10.1016/j.orcp.2024.09.001DOI Listing

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