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Journal of Translational Medicine
Published in: Journal of Translational Medicine 1/2022

Open Access 01-12-2022 | Research

Evaluation of the value of conventional and unconventional lipid parameters for predicting the risk of diabetes in a non-diabetic population

Authors: Guotai Sheng, Maobin Kuang, Ruijuan Yang, Yanjia Zhong, Shuhua Zhang, Yang Zou

Published in: Journal of Translational Medicine | Issue 1/2022

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Abstract

Background

Conventional and unconventional lipid parameters are associated with diabetes risk, the comparative studies on lipid parameters for predicting future diabetes risk, however, are still extremely limited, and the value of conventional and unconventional lipid parameters in predicting future diabetes has not been evaluated. This study was designed to determine the predictive value of conventional and unconventional lipid parameters for the future development of diabetes.

Methods

The study was a longitudinal follow-up study of 15,464 participants with baseline normoglycemia. At baseline, conventional lipid parameters such as low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) were measured/calculated, and unconventional lipid parameters such as non-HDL-C, remnant cholesterol (RC), LDL/HDL-C ratio, TG/HDL-C ratio, non-HDL/HDL-C ratio, TC/HDL-C ratio and RC/HDL-C ratio were calculated. Hazard ratio (HR) and 95% confidence interval (CI) were estimated by Cox proportional hazard regression adjusting for demographic and diabetes-related risk factors. The predictive value and threshold fluctuation intervals of baseline conventional and unconventional lipid parameters for future diabetes were evaluated by the time-dependent receiver operator characteristics (ROC) curve.

Results

The incidence rate of diabetes was 3.93 per 1000 person-years during an average follow-up period of 6.13 years. In the baseline non-diabetic population, only TG and HDL-C among the conventional lipid parameters were associated with future diabetes risk, while all the unconventional lipid parameters except non-HDL-C were significantly associated with future diabetes risk. In contrast, unconventional lipid parameters reflected diabetes risk better than conventional lipid parameters, and RC/HDL-C ratio was the best lipid parameter to reflect the risk of diabetes (HR: 6.75, 95% CI 2.40–18.98). Sensitivity analysis further verified the robustness of this result. Also, time-dependent ROC curve analysis showed that RC, non-HDL/HDL-C ratio, and TC/HDL-C ratio were the best lipid parameters for predicting the risk of medium-and long-term diabetes.

Conclusions

Unconventional lipid parameters generally outperform conventional lipid parameters in assessing and predicting future diabetes risk. It is suggested that unconventional lipid parameters should also be routinely evaluated in clinical practice.
Appendix
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Metadata
Title
Evaluation of the value of conventional and unconventional lipid parameters for predicting the risk of diabetes in a non-diabetic population
Authors
Guotai Sheng
Maobin Kuang
Ruijuan Yang
Yanjia Zhong
Shuhua Zhang
Yang Zou
Publication date
01-12-2022
Publisher
BioMed Central
Published in
Journal of Translational Medicine / Issue 1/2022
Electronic ISSN: 1479-5876
DOI
https://doi.org/10.1186/s12967-022-03470-z

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