NDLI: Assessment of whole-body and regional body fat using abdominal quantitative computed tomography in Chinese women and men

Content Provider	Springer Nature : BioMed Central
Author	Mai, Jinci Wu, Qiulian Wu, Huanhua Zeng, Chunyuan Li, Yingxin Shang, Jingjie Wu, Biao Cai, Qijun Du, Junbi Gong, Jian
Abstract	Background Being overweight or obese has become a serious public health concern, and accurate assessment of body composition is particularly important. More precise indicators of body fat composition include visceral adipose tissue (VAT) mass and total body fat percentage (TBF%). Study objectives included examining the relationships between abdominal fat mass, measured by quantitative computed tomography (QCT), and the whole-body and regional fat masses, measured by dual energy X-ray absorptiometry (DXA), as well as to derive equations for the prediction of TBF% using data obtained from multiple QCT slices. Methods Whole-body and regional fat percentage were quantified using DXA in Chinese males (n = 68) and females (n = 71) between the ages of 24 and 88. All the participants also underwent abdominal QCT measurement, and their VAT mass and visceral fat volume (VFV) were assessed using QCT and DXA, respectively. Results DXA-derived TBF% closely correlated with QCT abdominal fat percentage (r = 0.89–0.93 in men and 0.76–0.88 in women). Stepwise regression showed that single-slice QCT data were the best predictors of DXA-derived TBF%, DXA android fat percentage and DXA gynoid fat percentage. Cross-validation analysis showed that TBF% and android fat percentage could be accurately predicted using QCT data in both sexes. There were close correlations between QCT-derived and DXA-derived VFV (r = 0.97 in men and 0.93 in women). Conclusion Clinicians can assess the TBF% and android and gynoid fat percentages of Chinese women and men by analysing existing abdominal CT-derived data using the QCT technique.
Related Links	https://lipidworld.biomedcentral.com/counter/pdf/10.1186/s12944-024-02034-y.pdf
Ending Page	11
Page Count	11
Starting Page	1
File Format	HTM / HTML
DOI	10.1186/s12944-024-02034-y
Journal	Lipids in Health and Disease
Issue Number	1
Volume Number	23
Language	English
Publisher	BioMed Central
Publisher Date	2024-02-14
Access Restriction	Open
Subject Keyword	Lipidology Medical Biochemistry Clinical Nutrition Quantitative computed tomography Dual-energy X-ray absorptiometry Total body fat percentage Android Gynoid
Content Type	Text
Resource Type	Article
Subject	Endocrinology Clinical Biochemistry Endocrinology, Diabetes and Metabolism Biochemistry (medical)
Journal Impact Factor	3.9/2023
5-Year Journal Impact Factor	4.3/2023

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