Non-HDL Cholesterol and Remnant Cholesterol Predict Different Components of the Metabolic Syndrome in Type 2 Diabetes Mellitus Patients in a Regional Hospital

Author:

Nsiah Paul1,Acquah Samuel1,Bockarie Ansumana Sandy1,Adjei George1,Aniakwaa-Bonsu Ebenezer2,Togbe Eliezer2,Ossei Paul Poku Sampene2,Debrah Oksana1

Affiliation:

1. University of Cape Coast

2. Kwame Nkrumah University of Science and Technology

Abstract

Abstract Type 2 diabetes mellitus (T2DM) continues to increase in incidence within the ageing population of the globe. Patients with T2DM have a 2-4 times higher risk of experiencing an adverse cardiovascular event than their non-diabetic counterparts. Total cholesterol, low-density lipoprotein (LDL), triglycerides and high-density lipoprotein (HDL) cholesterol levels have been the routine biomarkers for lipid-based cardiovascular disease diagnostic and prognostic decisions in clinical practice. Recent evidence elsewhere suggests remnant cholesterol (RC) and Non-HDL cholesterol (Non-HDL-c) can serve as biomarkers with a higher predictive power for cardiovascular disease (CVD) than the aforementioned routine ones. In our context, there is limited information on the suitability and superiority of these emerging biomarkers for the assessment of CVD risk in T2DM. The current study therefore sought to examine the relationship between RC and non-HDL-c for predicting CVD in T2DM patients in the context of the obesity paradox. Apart from adiponectin level which was lower (P < 0.05), overweight/obese respondents exhibited higher (P < 0.05) mean levels for all the measured indices. Insulin resistance was independently predicted (R2 = 0.951; adjusted R2 = 0.951; P < 0.001) by RC, duration and fasting plasma glucose. However, Non-HDL-c predicted CVD risk (AOR = 4.31; P <0.001), hypertension (AOR = 2.24; P <0.001), resistin (AOR = 2.14; P <0.001) and adiponectin (AOR = -2.24; P <0.001) levels. Our findings point to different mechanisms by which RC and non-HDL-c contribute to the development of CVD.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3