Serum uric acid to high-density lipoprotein cholesterol ratio is a promising marker for identifying metabolic syndrome in nondiabetic Chinese men

ABSTRACT

Objectives

To explore the relationship between serum uric acid (UA) and high-density lipoprotein cholesterol (HDL-C) ratio (UHR) and metabolic syndrome (MetS) in nondiabetic individuals.

Methods

A total of 15,760 nondiabetic participants were screened from the China National Diabetes and Metabolic Disorders Study. Pearson correlation was used to determine the correlation between the components of MetS and UHR, HDL-C, and UA. Receiver operating characteristic curves were used to evaluate the ability of UHR, HDL-C, and UA to identify MetS in the nondiabetic population.

Results

A total of 6,386 men and 9,374 women were enrolled in this study. There were 1,480 (23.2%) men and 1,828 (19.5%) women with MetS. UHR significantly correlated with the components of MetS in men and women, especially with waist circumference  and triglyceride. In men, although HDL-C showed a higher specificity index, UHR presented higher sensitivity index and area under the curve (AUC) than HDL-C (P = 0.0001) and UA (P < 0.0001), with AUC (95% CI) of 0.762 (0.752–0.773). Higher AUCs of UHR relative to HDL-C and UA were also observed in the age groups <40 and 40–59 years. There was no significant difference in AUC between UHR and HDL-C in the age group ≥60 years (P = 0.370). However, similar results were not observed in women.

Conclusion

UHR significantly correlated with the components of MetS and could serve as a novel and reliable marker for identifying the population at a high risk of MetS in nondiabetic men, especially in younger adults.

KEYWORDS:

• Metabolic syndrome
• nondiabetic population
• high-density lipoprotein
• uric acid
• uric acid to high-density lipoprotein cholesterol ratio
• inflammation

Declaration of financial/other relationships

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Acknowledgments

The authors thank all physicians and participants of the study, for their cooperation and generous participation.

Author contributions

QJ, XY, BG, and FS conceived and designed the study. JM, SL, WZ, LW, QL, and QX contributed to the data collection. LW and LS contributed to the data extraction, and interpreted the results. XY and BG performed the data analysis. XY and FS wrote the first draft.

Data availability statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Supplemental data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/00325481.2023.2263372.

Additional information

Funding

This manuscript was funded by the Key Research and Development Program of Shaanxi Province, China (No. 2017ZDCXLSF0201), and the National Key R&D Program: Multi-factorial Integrative Management of Type 2 Diabetes (MiDiab) [No. 2017YFC1309803, 2017YFC1309804]. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.