Loading...
Validation of a recently proposed equation for the estimation of small, dense LDL particles from routine lipid measures in a population of mixed ancestry South Africans
Author(s)
Masoud, Mohamed Abdulsalam
Date Issued
2016
Type
Thesis
Publisher
Cape Peninsula University of Technology
Abstract
Cardiovascular diseases (CVD) are the leading cause of global mortality, of which over 75% occurred in low- and middle-income countries such as South Africa. The lipid profile, specifically decreased levels of high density lipoprotein cholesterol (HDL-C), elevated triglyceride levels and the presence of small-dense low density lipoprotein (sdLDL) has been reported associated with CVD. An increased number of sdLDL is also common in metabolic syndrome (MetS), visceral obesity and diabetes mellitus, the last a known risk factor for CVD. The modification of low density lipoprotein (LDL) size, or number of sdLDL particles, has been reported to significantly reduce CVD risk, but not conclusively so and needs further investigation. In this regard, sdLDL particles are seldom estimated routinely for clinical use because of financial and other limitations. Currently, an alternative approach for estimating sdLDL is to use equations derived from routine lipid measures, as has been proposed by several groups. However, there is a need for extensive evaluation of this equation across different ethnic and disease groups, especially since reports showed an inadequate performance of the equation in a Korean population. The aim of this study was to assess the performance of a recently proposed equation for the estimation of sdLDL in healthy and diabetic mixed ancestry South Africans. Furthermore, we also investigated the role of sdLDL as a cardiometabolic risk factor, as measured against known risk factors such as the glycemic and lipid profiles.
Additional information
Thesis (MSc (Biomedical Technology))--Cape Peninsula University of Technology, 2016.
File(s)![Thumbnail Image]()
Loading...
Name
214150860-Masoud-Mohamed-Abdulsalam-MSc-Biomedical-Technology-HWSci-2017.pdf
Description
Thesis
Size
1.56 MB
Format
Adobe PDF
Checksum
(MD5):d943d1f07ea4f9f6e1b48c90cb0e5292