Measured Versus Calculated Small Dense LDL-Cholesterol and Cardiometabolic Traits in a South African Population

Indian journal of clinical biochemistry

article

M. Masoud¹  A. P. Kengne²  R. T. Erasmus⁴  G. M. Hon¹  M. Macharia⁴  T. E. Matsha¹ 

[1]Department of Biomedical Sciences, Faculty of Health and Wellness Science, Cape Peninsula University of Technology

[2]Non-Communicable Diseases Research Unit, South African Medical Research Council

[3]Department of Medicine, University of Cape Town

[4]Division of Chemical Pathology, Faculty of Health Sciences, National Health Laboratory Service (NHLS), University of Stellenbosch

关键词: Africa Diabetes Metabolic syndrome Lipids Small-dense low density lipoprotein;   

DOI  :  10.1007/s12291-018-0748-8

来源: Springer

【 摘 要 】

Small-dense low density lipoprotein (sdLDL) is increasingly viewed as a marker for evaluating atherogenic risk, however its clinical uptake is hampered by the cumbersomeness of available methods. Consequently, a number of alternative methods for the estimation of sdLDL have been developed and none have been tested in a population from Africa. We evaluated an equation to estimate sdLDL-C from classic lipid parameters in South Africans. This is a cross-sectional study involving 1550 participants in which direct measurement of sdLDL in 237 participants was performed using a homogeneous enzymatic assay. Their mean age (standard deviation, SD) was 54.2 (14.7) years. 156 (65.8%) were normotolerant, 29 (12.2%) prediabetes, 17 (7.2%) screen detected diabetes and 35 (14.8%) known diabetes. Measured sdLDL values ranged from 0.17 to 3.39 versus—1.85 to 2.52 mmol/L calculated sdLDL. There was a significant positive correlation between the two measurements with a Pearson correlation coefficient of 0.659 (95%CI: 0.581–0.726). In a regression model, the adjusted R2 was 0.440 after adding age, 0.441 after further adding gender, then 0.443 with dysglycemia and lastly 0.447 upon adding body mass index. With the exception of HDL-cholesterol levels that decreased across increasing quintiles of calculated sdLDL, our data showed significant correlations between sdLDL and cardiometabolic risk factors, all p values < 0.0001. In conclusion, this study has shown that calculated sdLDL can be efficiently used to approximate population levels of sdLDL; however the modest correlation indicate that at the individual level, it will poorly approximate true sdLDL levels, with possible implications for risk stratification.

【 授权许可】

Unknown