Abstract
Stroke, as the second leading cause of death globally, is characterized by high disability and mortality rates and urgently needs biomarkers for risk stratification. This study aims to use data from the China Health and Retirement Longitudinal Study (CHARLS) cohort to explore the association of the uric acid to HDL-C ratio (UHR), BMI with incident stroke. A total of 3756 participants aged 45 and above without a history of stroke were included from the CHARLS data from 2011 to 2020. Stroke events were confirmed through follow up data. UHR was calculated as the ratio of serum uric acid (mg/dL) to high density lipoprotein cholesterol (mg/dL). Statistical methods such as the Cox proportional hazards regression model, restricted cubic spline analysis, mediation effect test (Bootstrap method), and and multiplicative and additive interactions analysis were used to systematically evaluate the association of the combined UHR and BMI indicators with stroke risk. The UHR was significantly associated with stroke risk (HR = 1.03, p = 0.005), with the highest UHR group having 1.61 times the risk of the lowest group (p = 0.003). Subgroup analysis indicated that this association was significant in the non-diabetic population (p < 0.001) but not in the diabetic population (interaction p = 0.002). UHR mediated 18% of the association between BMI and stroke risk (95% CI 6.7–38%). No significant multiplicative and additive interactions were found between BMI and UHR on incident stroke.Restricted cubic spline analysis showed an approximately linear dose–response relationship between UHR and stroke risk (p for non linearity = 0.917). The study results indicate that UHR is significantly and positively correlated with stroke risk, and its value in stroke risk stratification is significantly enhanced when used in combination with BMI.
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The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. All data generated or analysed during this study are included in this published article.
References
Krishnamurthi, R. V., Ikeda, T. & Feigin, V. L. Global, regional and country-specific burden of ischaemic stroke, intracerebral haemorrhage and subarachnoid haemorrhage: A systematic analysis of the global burden of disease study 2017. Neuroepidemiology 54, 171–179 (2020).
GBD 2016 Stroke Collaborators. Global, regional, and national burden of stroke, 1990-2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 18, 439–458 (2019).
Sacco, R. L. et al. An updated definition of stroke for the 21st century: A statement for healthcare professionals from the American heart association/American stroke association. Stroke 44, 2064–2089 (2013).
Campbell, B. C. V. & Khatri, P. Stroke. Lancet 396, 129–142 (2020).
Wang, Y. et al. Associations of serum uric acid to high-density lipoprotein cholesterol ratio with trunk fat mass and visceral fat accumulation. Diabetes Metab. Syndr. Obes. Targets Ther. 17, 121–129 (2024).
Ahari, R. K. et al. Association of atherosclerosis indices, serum uric acid to high‐density lipoprotein cholesterol ratio and triglycerides‐glucose index with hypertension: A gender‐disaggregated analysis. J. Clin. Hypertens. 26, 645–655 (2024).
Cui, Y. & Zhang, W. Long-term cardiovascular risk and mortality associated with uric acid to HDL-C ratio: A 20-year cohort study in adults over 40. Sci. Rep. 15, 14242 (2025).
Kittelson, K. S., Junior, A. G., Fillmore, N. & da Silva Gomes, R. Cardiovascular-kidney-metabolic syndrome—An integrative review. Prog. Cardiovasc. Dis. 87, 26–36 (2024).
Yumuk, V. et al. European guidelines for obesity management in adults. Obes. Facts. 8, 402–424 (2015).
Zhao, Y., Hu, Y., Smith, J. P., Strauss, J. & Yang, G. Cohort profile: The China health and retirement longitudinal study (CHARLS). Int. J. Epidemiol. 43, 61–68 (2014).
Jiang, L. et al. Non-linear associations of atherogenic index of plasma with prediabetes and type 2 diabetes mellitus among Chinese adults aged 45 years and above: A cross-sectional study from CHARLS. Front. Endocrinol. 15, 1360874 (2024).
Huo, R.-R., Liao, Q., Zhai, L., You, X.-M. & Zuo, Y.-L. Interacting and joint effects of triglyceride-glucose index (TyG) and body mass index on stroke risk and the mediating role of TyG in middle-aged and older Chinese adults: A nationwide prospective cohort study. Cardiovasc. Diabetol. 23, 30 (2024).
Kanbay, M. et al. The role of uric acid in the pathogenesis of human cardiovascular disease. Heart 99, 759–766 (2013).
Zhong, C., Zhong, X., Xu, T., Xu, T. & Zhang, Y. Sex-specific relationship between serum uric acid and risk of stroke: A dose-response meta-analysis of prospective studies. J. Am. Heart. Assoc. 6, e005042 (2017).
Jiang, Q. et al. Serum uric acid to high-density lipoprotein cholesterol ratio is associated with stroke in the elderly: A population-based study. Front. Neurol. 16, 1594080 (2025).
Zhu, T., He, Y. & Bei, E. Increased uric acid to high-density lipoprotein ratio positively correlated with stroke risk. Front. Neurol. 16, 1577077 (2025).
Nofer, J.-R. et al. HDL and arteriosclerosis: Beyond reverse cholesterol transport. Atherosclerosis 161, 1–16 (2002).
Pammer, A. et al. Impaired HDL antioxidant and anti-inflammatory functions are linked to increased mortality in acute heart failure patients. Redox. Biol. 76, 103341 (2024).
Rye, K.-A. Biomarkers associated with high-density lipoproteins in atherosclerotic kidney disease. Clin. Exp. Nephrol. 18, 247–250 (2014).
You, Y., Zhao, Y., Chen, M., Pan, Y. & Luo, Z. Effects of empagliflozin on serum uric acid level of patients with type 2 diabetes mellitus: A systematic review and meta-analysis. Diabetol. Metab. Syndr. 15, 202 (2023).
Matsunaga, T. et al. Glycated high-density lipoprotein regulates reactive oxygen species and reactive nitrogen species in endothelial cells. Metabolism 52, 42–49 (2003).
Aktas, G. et al. Poorly controlled hypertension is associated with elevated serum uric acid to HDL-cholesterol ratio: A cross-sectional cohort study. Postgrad. Med. 134, 297–302 (2022).
Kim, S. C. et al. Clinical and health care use characteristics of patients newly starting allopurinol, febuxostat, and colchicine for the treatment of gout. Arthritis Care Res. (Hoboken) 65, 2008–2014 (2013).
Cao, J. Y. et al. Uric acid predicts long-term cardiovascular risk in type 2 diabetes but does not mediate the benefits of fenofibrate: The FIELD study. Diabetes Obes. Metab. 22, 1388–1396 (2020).
Theofilis, P., Tsimihodimos, V., Vordoni, A. & Kalaitzidis, R. G. Serum uric acid levels and cardiometabolic profile in middle-aged, treatment-naïve hypertensive patients. High Blood Press. Cardiovasc. Prev. 29, 367–374 (2022).
Chen, R., Ovbiagele, B. & Feng, W. Diabetes and stroke: Epidemiology, pathophysiology, pharmaceuticals and outcomes. Am. J. Med. Sci. 351, 380–386 (2016).
Ruan, Z. & Zhao, J. Differential ischemic stroke risk linked to novel subtypes of type 2 diabetes: Insights from a Mendelian randomization analysis. Endocrine 84, 980–988 (2024).
Kong, X. et al. Relationship of admission uric acid to high density lipoprotein cholesterol ratio with unfavorable prognosis among acute ischemic stroke patients. Lipids Health. Dis. 24, 381 (2025).
Wang, P. et al. Perivascular adipose tissue-derived visfatin is a vascular smooth muscle cell growth factor: Role of nicotinamide mononucleotide. Cardiovasc. Res. 81, 370–380 (2009).
Badellino, K. O., Wolfe, M. L., Reilly, M. P. & Rader, D. J. Endothelial lipase concentrations are increased in metabolic syndrome and associated with coronary atherosclerosis. PLoS. Med. 3, e22 (2006).
Hahn, B. H. et al. Pro-inflammatory high-density lipoproteins and atherosclerosis are induced in Lupus-prone mice by a high-fat diet and leptin. Lupus 19, 913–917 (2010).
Sorrentino, S. A. et al. Endothelial-vasoprotective effects of high-density lipoprotein are impaired in patients with type 2 diabetes mellitus but are improved after extended-release niacin therapy. Circulation 121, 110–122 (2010).
Sasahara, T., Yamashita, T., Sviridov, D., Fidge, N. & Nestel, P. Altered properties of high density lipoprotein subfractions in obese subjects. J. Lipid Res. 38, 600–611 (1997).
Ford, E. S., Li, C., Cook, S. & Choi, H. K. Serum concentrations of uric acid and the metabolic syndrome among US children and adolescents. Circulation 115, 2526–2532 (2007).
Holmes, M. V. et al. Causal effects of body mass index on cardiometabolic traits and events: A mendelian randomization analysis. Am. J. Hum. Genet. 94, 198–208 (2014).
Liu, X. et al. A J-shaped relation of BMI and stroke: Systematic review and dose-response meta-analysis of 4.43 million participants. Nutr. Metab. Cardiovasc. Dis. 28, 1092–1099 (2018).
Wang, X. et al. The relationship between body mass index and stroke: A systemic review and meta-analysis. J. Neurol. 269, 6279–6289 (2022).
Moskowitz, M. A., Lo, E. H. & Iadecola, C. The science of stroke: Mechanisms in search of treatments. Neuron 67, 181–198 (2010).
Anrather, J. & Iadecola, C. Inflammation and stroke: An overview. Neurotherapeutics 13, 661–670 (2016).
Brea, D. Post-stroke immunosuppression: Exploring potential implications beyond infections. Eur. J. Neurosci. 58, 4269–4281 (2023).
Acknowledgements
We thank the China Health and Retirement Longitudinal Study, CHARLS for providing the data and the selfless contributions of all participants.
Funding
This research was supported by Science and Technology Planning Project of Yunnan Provincial Department of Science and Technology.[grant numbers:202401AY070001-108],Open Project of the Clinical Medical Research Center, The First People’s Hospital of Yunnan Province[grant numbers: 2023YJZX-LN09].
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Shan Li—Conceptualization; Funding acquisition; Data curation; Formal analysis; Investigation; Project administration; Resources; Supervision; Validation; Visualization; Writing—original draft. Jie Liu—Methodology; Software; Formal analysis; Validation; Visualization; Writing—original draft. Kui Zhang—Data curation; Investigation; Formal analysis; Validation; Visualization; Writing—original draft. Kai Zhao—Data curation; Investigation; Software; Validation; Writing—review & editing. Yan Li—Investigation; Resources; Validation; Writing—review & editing. Hangyu Ma—Investigation; Resources; Validation; Writing—review & editing. Yutao Fu—Investigation; Resources; Validation; Writing—review & editing. Jianzhun Chen—Conceptualization; Methodology; Project administration; Supervision; Resources; Validation; Writing—review & editing. Qianhao Zhao—Conceptualization; Methodology; Project administration; Supervision; Resources; Validation; Writing—review & editing.
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Each participant in CHARLS cohort which was conducted under Peking University’s ethics review committee gave their informed permission before taking part (IRB00001052-11015). In addition, the Declaration of Helsinki was followed during our research. The necessary standards and legislation were followed in the execution of all procedures, including the declarations in “Declarations” section.
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Li, S., Liu, J., Zhang, K. et al. Association of serum uric acid to high density lipoprotein cholesterol ratio with stroke. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41894-5
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DOI: https://doi.org/10.1038/s41598-026-41894-5
