Computed Tomography-based Investigation of the Correlation of Abdominal Fat Areas with Metabolic Syndrome

Kai Yuan Cheng, Tsung Hsien Yen, Jay Wu, Pei Hsuan Li, Tian Yu Shih*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: The population of individuals with obesity is gradually increasing, and excessive subcutaneous and visceral fat accumulated in the body can increase the risk of metabolic syndrome (MetS). Therefore, clinical attention has been drawn to the degree of harm chronic metabolic diseases can have on health. Materials and Methods: This study analyzed the abdominal computed tomography (CT) images of 60 participants. The axial cross-sectional images of the midsection of their livers; third, fourth, and fifth lumbar vertebrae (L3, L4, and L5); and ilium were circled for measurement of subcutaneous and visceral fat areas (VFA). Visceral-to-subcutaneous fat ratios (VSR) were obtained and were followed by a statistical analysis to evaluate their correlation with physical examination results associated with complications of obesity, including fasting blood glucose levels, waist circumference, high-density lipoprotein levels, systolic blood pressure, and triglyceride levels. In addition, the feasibility of using CT imaging to assess MetS was analyzed. Results: The VSR in the abdominal were 0.189–0.921. The median VFA in the L3 cross-sections were 257.7 cm2 and 180.9 cm2 in men and women, respectively. A significant association was identified between the median visceral fat area in the L3 cross-sections and the number of MetS–risk factors for obesity complications (P < 0.01). Significant associations were also identified between the number of MetS risk factors and the fat area of some cross-sections. Conclusions: Measuring subcutaneous fat areas and visceral fat through abdominal CT can assist in predicting MetS.

Original languageEnglish
Article numbere00003
JournalJournal of Radiological Science
Volume48
Issue number1
DOIs
StatePublished - 2023

Keywords

  • Computed tomography
  • metabolic syndrome
  • subcutaneous fat
  • viscera fat

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