The Correlation of Total Percent Fat With Alterations in Cholesterol and Triglycerides in Adults.

Abstract

Background:

To evaluate the detailed relationship between total percent fat (TPF) and cardiovascular disease (CVD)-related lipid biomarkers among adults and find a non-invasive indicator for screening and monitoring of the high CVD risk population.

Methods:

Data of 13,160 adults were obtained from the National Health and Examination Survey (NHANES) from 1999 to 2018. TPF was assessed by dual-energy x-ray absorptiometry (DXA), and CVD-related lipid biomarkers included total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). Multivariable linear regression models were used to examine associations between TPF with four kinds of lipid biomarkers, and smooth curve fittings and generalized additive models were used to address the non-linear relationship between them. The inflection points were calculated by the recursive algorithm when non-linearities were detected and then weighted two-piecewise linear regression models were constructed.

Results:

In multivariable regression, increasing TPF was positively associated with TC, TG, and LDL-C and negatively with HDL-C (all p < 0.001). In addition, the non-linear relationships between them were also identified by generalized additive models and smooth curve fittings. When further stratified TPF by sex, the fitted smooth curves were nearly inverted U-shaped and U-shaped curves, the inflection points were calculated, and the weighted two-piecewise linear regression models were constructed, respectively. The same results existed between android percent fat and these four lipid biomarkers.

Conclusions:

Total percent fat was significantly associated with CVD-related lipid biomarkers in adults, positively with TC, TG, and LDL-C and negatively with HDL-C. It could be used as a non-invasive screener and monitor of high CVD risk population when their TPF values were less than the inflection points.

• Authors: Juan Sun, Zimu Zhang, Zhen Liu, Jie Li, Weiming Kang
• Journal: Frontiers in nutrition (Front Nutr) Vol. 9 Pg. 881729 ( 2022) ISSN: 2296-861X [Print] Switzerland
• PMID: 35711546 (Publication Type: Journal Article)
• Copyright: Copyright © 2022 Sun, Zhang, Liu, Li and Kang.