Skip to main content
Download PDF

Association between serum uric acid and homocysteine levels among adults in the United States: a cross-sectional study

BMC Cardiovascular Disorders volume 23, Article number: 599 (2023) Cite this article

Abstract

Background

Many studies have shown that both elevated serum uric acid (SUA) levels and hyperhomocysteinemia are risk factors for atherosclerosis. However, the relationship between the two has not been thoroughly investigated.

Objective

This study aimed to explore the possible link between SUA levels and homocysteine (Hcy) levels.

Methods

In this cross-sectional study, 17,692 adults aged > 19 years in National Health and Nutrition Examination Survey from 1999 to 2006 were analyzed. Multivariable linear regression analysis was performed to assess the association between SUA and Hcy levels. In addition, smooth curve fitting (penalized spline method) and threshold effect analysis were performed.

Results

Multivariable linear analysis showed that Hcy levels increased by 0.48 µmol/L (β = 0.48, 95%CI: 0.43–0.53) for every 1 mg/dL increase in SUA levels. We found a nonlinear relationship between SUA and Hcy levels. The results of threshold effect analysis showed that the inflection point for SUA levels was 7.1 mg/dL (β = 0.29, 95% CI: 0.23–0.36 and β = 1.05, 95% CI: 0.67–1.43 on the left and right sides of the inflection point, respectively). The p-values was less than 0.001 when using the log likelihood ratio test. This nonlinear relationship was also found in both sexes. The inflection point for SUA levels was 5.4 mg/dL in males and 7.3 mg/dL in females, respectively.

Conclusions

This cross-sectional study showed that the SUA levels were positively correlated with Hcy levels. And we found a nonlinear relationship between SUA and Hcy levels.

Peer Review reports

Introduction

Serum uric acid (SUA) is the final oxidized product of purine metabolism and is widely used as a biological marker for gout. Epidemiological data have shown that elevated SUA levels are associated with the occurrence and development of various atherosclerosis-related diseases, such as hypertension [1], coronary heart disease (CHD) [2], and stroke [3]. The progression of atherosclerosis caused by SUA may involve the following mechanisms: (i). a reduced production of nitric oxide (NO) which induces endothelial dysfunction [4], decreases the bioavailability of NO, and reduces the dependent vasodilation of the effect [5]; and (ii). stimulation of the vascular endothelial cells by SUA to produce angiotensin II [6].

Homocysteine (Hcy) is a non-essential amino acid derived from methionine metabolism [7]. Hcy has been identified as a common and potent factor in coronary, cerebral, and peripheral atherosclerotic vascular diseases and arteriovenous embolism [8, 9]. Hyperhomocysteinemia (HHcy) is an independent risk factor for peripheral arterial disease [10, 11]. In a cross-sectional study by Tribouilly et al. [12], plasma Hcy levels were positively correlated with thoracic aortic atherosclerosis severity scores and aortic intimal lesion severity. The mechanism by which Hcy causes atherosclerosis includes impairment of endothelial function and reverse cholesterol transport [13].

Hyperuricemia and HHcy have been well studied in relation to cardiovascular disease, and both have an impact on the development of atherosclerosis. However, only a limited number of studies have discussed the relationship between SUA levels and Hcy levels. A recent cross-sectional study showed a positive correlation between Hcy levels and SUA levels among American adolescents aged 12–19 years [14]. Wang et al. [15] found that elevated SUA levels were associated with HHcy in Chinese hypertensive population. While, there are fewer studies on the correlation between SUA levels and Hcy levels in the whole population. Therefore, we used the National Health and Nutrition Examination Survey (NHANES) 1999–2006 database to investigate the possible relationship between SUA levels and Hcy levels among adults in the United States.

Methods

Study design and population

Data from the NHANES 1999–2006, a complex, stratified, multi-stage probability sample of the non-institutionalized population in the US, were analyzed. These cross-sectional surveys were conducted at the National Center for Health Statistics (NCHS). More information on the NHANES survey design is available at www.cdc.gov/nchs/nhanes/. The study protocol was approved by the NCHS Ethics Review Committee, and all participants of the NHANES consented to the use of their anonymous information for research purposes.

Study variables

In this study, SUA levels was the exposure variable. Between 1999 and 2001, Hitachi 704 Multichannel Analyzer (Boehringer Mannheim,) or Roche Hitachi Model 917 were used to measure SUA levels, while Beckman Synchron Lx20 has been in use since 2002. Hcy levels were measured using an Abbott IMx analyzer between 1999 and 2000, an Abbott Homocysteine IMx analyzer in 2001, and an Abbott AxSYM analyzer in 2002. If the covariates altered the regression coefficient by at least 10% when added to the model, they were adjusted as potential confounders. The following potential confounders were included: age, sex, race/ethnicity, education status, alcohol consumption, smoking, physical activity, CHD, hypertension, diabetes, BMI, total polyunsaturated fatty acids, total saturated fatty acids, total protein, dietary fiber, serum vitamin B12, RBC folate, serum folate, and estimated glomerular filtration rate (eGFR). These covariates were adjusted for in the multivariable adjusted model. More information on the covariates analyzed and how the SUA and Hcy levels were measured is available at http://www.cdc.gov/nchs/nhanes/.

Statistical analysis

The statistical analyses were conducted according to the Centers for Disease Control and Prevention guidelines (https://wwwn.cdc.gov/nchs/nhanes/tutorials/default. Aspx). Significant differences were calculated using the proposed weighting method. Continuous variables are expressed as means (standard error (SE)), and categorical variables as percentages (SE). Weighted chi-square tests (categorical variables) and weighted linear regression analyses (continuous variables) were used to calculate the SUA quartile differences. A multivariable linear regression model was employed to investigate the relationship between SUA and Hcy levels. Three models were constructed as follows: model 1, no covariates were adjusted; model 2, minimally adjusted model for age and sex; and model 3, adjusted for the potential confounders. To evaluate the nonlinear properties of SUA and Hcy levels, smooth curve fitting (penalized spline method) were used. When a non-linear correlation was noted between SUA and Hcy levels, a two-piecewise linear regression model was used to calculate the inflection point of SUA on Hcy. The likelihood-ratio test was used for nonlinearity. A subgroup analysis was performed using a stratified linear regression analysis.

All tests were two-sided and statistical significance was set at p < 0.05. All analyses were performed using the statistical software packages R (http://www.R-project.org, The R Foundation), EmpowerStats (http://www.empowerstats.com, X&Y Solution, Inc., Boston, MA) and Free Statistics software.

Results

Participant selection

A total of 20,311 participants aged > 19 years were selected from the NHANES 1999–2006 database. After excluding those with missing Hcy (n = 2361) and SUA values (n = 257) and with SUA levels > 17.6 mg/dL (n = 1), 17,692 eligible participants were included in the final analysis (Fig. 1).

Fig. 1
figure 1

Flow chart of participants

Full size image

Participant characteristics

The participants’ mean age was 46.07 years, and approximately 48% were male. According to the SUA quartiles, the selected participants’ social demographic characteristics and the weighted distribution of the other characteristics were shown in Table 1. The SUA quartile ranges for Q1 to Q4 were < 4.2, 4.2–5.1, 5.1–6.2, and ≥ 6.2 mg/dL, respectively. Compared with participants in the other groups, those in Q4 with higher SUA levels, had higher BMI, SBP, DBP, TMFA, TPFA, TSFA, total fat intakes, protein intakes, energy intake and Hcy levels. However, they had lower vitamin B6 and folic acid supplement, serum folate, serum vitamin B12 and eGFR. Participants in the Q4 group were slightly older, more male, tended to smoke, consume alcohol, live a sedentary lifestyle, and have CHD, hypertension and diabetes.

Table 1 Characteristics of study participants
Full size table

Association between SUA levels and hcy levels

The association between SUA levels and Hcy levels were presented in Table 2. In the non-adjusted model, every 1 mg/dL increase in SUA levels was associated with a 1.03 µmol/L increase in Hcy levels (β = 1.03, 95% confidence interval (CI): 0.99–1.08, p < 0.001). In the multivariable-adjusted model, this trend was consistent. Every 1 mg/dL increase in SUA levels was associated with an increase in Hcy levels of 0.48 µmol/L (β = 0.48, 95% CI: 0.43–0.53, p < 0.001). To test the robustness of the results, SUA was treated as a categorical variable (quartiles) in an additional analysis, which showed no changes in the trend (Table 2).

Table 2 Association of homocysteine with serum uric acid
Full size table

Nonlinear relationship between SUA levels and hcy levels

Smooth curve fitting were used to show the dose-response relationship between SUA and Hcy levels. The multivariable adjusted smooth curve fitting showed a nonlinear association between SUA and Hcy levels (p < 0.001, Fig. 2). The nonlinear p-value was less than 0.001, which indicated a nonlinear relationship between SUA and Hcy levels. Since sex is a known confounder of the association between SUA and Hcy, we examined the nonlinear relationship between SUA and Hcy levels stratified by sex. The sex subgroup analysis generated similar findings (Fig. 3).

Fig. 2
figure 2

Dose-response relationship between serum uric acid levels and homocysteine levels. Analyses were adjusted for age, sex, race/ethnicity, education status, alcohol consumption, smoking, physical activity, coronary heart disease, hypertension, diabetes BMI, total polyunsaturated fatty acids, total saturated fatty acids, total protein, dietary fiber, serum vitamin B12, RBC folate, serum folate, estimated glomerular filtration rate

Full size image
Fig. 3
figure 3

Dose-response relationship between serum uric acid levels and homocysteine levels stratified by sex. Analyses were adjusted for age, race/ethnicity, education status, alcohol consumption, smoking, physical activity, coronary heart disease, hypertension, diabetes BMI, total polyunsaturated fatty acids, total saturated fatty acids, total protein, dietary fiber, serum vitamin B12, RBC folate, serum folate, estimated glomerular filtration rate

Full size image

Threshold effect analysis of SUA levels on hcy levels

Owing to the nonlinear correlation between SUA and Hcy levels, a two-piecewise linear regression model was used to calculate the inflection point of SUA on Hcy levels (Table 3). In the total population, the inflection point for SUA levels was 7.1 mg/dL. For every 1 mg/dl increase in SUA levels on the right side of the inflection point compared to the left side of the inflection point, the increase in Hcy levels was higher [β = 0.29, 95% CI (0.23–0.36) vs. β = 1.05, 95% CI (0.67–1.43)]. The p-values was less than 0.001 when using the log likelihood ratio test. A nonlinear relationship between SUA and Hcy levels was also supported in both males and females, but the inflection point value of SUA was different in males and females. The inflection point for SUA was 5.4 mg/dL in males and 7.3 mg/dL in females, respectively (Table 3).

Table 3 Threshold effect analysis of serum uric acid on homocysteine by sex
Full size table

Subgroup analysis

The results of the subgroup analysis of the association between SUA and Hcy levels were presented in Fig. 4. The association between SUA and Hcy levels in the stratified analysis was consistent with the findings of the multivariable linear regression analysis.

Fig. 4
figure 4

Association between serum uric acid levels and homocysteine levels according to subgroup. Analyses were adjusted for age, sex, race/ethnicity, education status, alcohol consumption, smoking, physical activity, coronary heart disease, hypertension, diabetes BMI, total polyunsaturated fatty acids, total saturated fatty acids, total protein, dietary fiber, serum vitamin B12, RBC folate, serum folate, estimated glomerular filtration rate. Abbreviations: CHD, coronary heart disease; eGFR, estimated glomerular filtration rate; 95% CI, 95% confidence interval

Full size image

Discussion

SUA levels was positively correlated with Hcy levels after adjusting for other covariates. Each 1 mg/dL increase in SUA was associated with a 0.48 µmol/L increase in Hcy (β = 0.48, 95% CI: 0.43–0.53). We found a nonlinear relationship between SUA and Hcy levels. Additionally, the subgroup analysis showed that the correlation between SUA and Hcy levels was stronger in those with lower vitamin B12 and folic acid, less alcohol consumption and lower eGFR.

Previous studies, conducted among patients with specific diseases such as diabetes [16] and cognitive impairment [17], have reported a positive correlation between SUA and Hcy levels. Hyperuricemia was also positively associated with HHcy in a study by Cohen [18], which is consistent with the findings of this study. Additionally, here, the relationship between SUA and Hcy levels was nonlinear after adjusting for many covariables using a two-piecewise linear regression model stratified by sex. Further, the inflection point was 5.4 mg/dL in males and 7.3 mg/dL in females.

Adenosine molecules may be responsible for the relationship between hyperuricemia and HHcy. In the methionine-Hcy cycle [19], methionine is converted to S-adenosyl-l-homocysteine (SAH), which is reversibly catabolized to adenosine and Hcy by SAH hydrolase [20]. Under normal conditions, SAH hydrolase also recirculates adenosine and Hcy back into SAH [21]. However, this requires a 1:1 stoichiometric ratio of Hcy to adenosine. Therefore, if one of these substances is missing, the circulation kinetics will be affected, leading to the accumulation of the other. In a hypoxic or ischemic state, there is an increased release of adenosine from the circulation. During purine metabolism, this is quickly degraded to SUA, resulting in elevated SUA levels and Hcy accumulation.

Folic acid and vitamin B12 are important coenzymes of Hcy metabolism. If deficiencies of folic acid and vitamin B12 exist, the conversion of Hcy is blocked and, subsequently, Hcy accumulates in the body. Several studies have shown that Hcy levels are negatively correlated with folic acid [22] and vitamin B12 levels [23, 24]. Here, in the subgroup analysis, the SUA levels increased more per 1 mg/dL of elevated Hcy in the low-folate and vitamin B12 groups than in the high-folate and vitamin B12 groups. It is important to consider that high SUA levels may exacerbate the impaired Hcy metabolism among people with low folic acid and vitamin B12 levels.

In the subgroup analysis, participants who drank < 5 g of alcohol per day had smaller increases in Hcy levels when SUA increased by 1 mg/dL, compared with those who drank > 5 g of alcohol per day. This may be owing to alcohol metabolism resulting in elevated adenosine levels [25]. Since SAH hydrolase recirculates adenosine and Hcy back to SAH in the methionine-Hcy cycle, Hcy clearance increases significantly in the presence of elevated adenosine levels.

Many studies investigating SUA and kidney disease [26] have shown that elevated SUA levels may lead to renal insufficiency, resulting in a decreased eGFR. Renal function plays an important role in Hcy metabolism, as decreased renal function equates to poorer clearance of Hcy [26, 27]. Similarly, the subgroup analysis showed a more pronounced increase in Hcy levels for every 1 mg/dL increase in SUA levels among those with low eGFR compared with those with high eGFR.

There is growing evidence suggesting that hyperuricemia and HHcy play a pivotal role in the development of atherosclerosis. We observed a direct correlation between SUA and Hcy levels, and this held true for both males and females. Numerous epidemiologic reports confirm that HHcy is an independent risk factor for cardiovascular diseases. Although combination therapy with folic acid and B vitamins has been shown to substantially reduce Hcy levels, the results of randomized placebo-controlled clinical trials examining the impact of combination therapy with folic acid and B vitamins on the outcomes of these diseases have yielded mixed but generally were not satisfactory [28]. Thus, although there is no doubt that folic acid and B vitamin supplementation reduce Hcy levels, further research is needed to determine which types of patients would benefit most from such treatments. From our study, it is clear that elevated SUA levels is associated with HHcy, suggesting that the benefit of combined treatment with folic acid and B vitamin supplements in reducing the risk of cardiovascular disease in patients with hyperuricemic could be further investigated.

This study has several limitations that should be considered when interpreting the results. First, owing to the nature of cross-sectional studies, determining the causal relationship between SUA and Hcy is difficult. Future large prospective studies or bidirectional Mendelian randomization studies need to be performed to determine a causal relationship between the two. Second, since the study participants were adults from the United States, the generalizability of the findings to other populations may be limited. Third, as an observational study, uncontrolled confounding or reverse causality could not be completely excluded.

Conclusion

In conclusion, SUA levels was positively correlated with Hcy levels among adults in the United States and the associations were more significant among those with low folic acid levels, vitamin B12 levels, alcohol consumption, and eGFR. Further investigation using a prospective cohort study comparing SUA and Hcy levels is necessary to confirm these findings.

Data Availability

The NHANES datasets are publicly available at:www.cdc.gov/nchs/nhanes/.

Abbreviations

SUA:

Serum uric acid

Hcy:

Homocysteine

HHcy:

Hyperhomocysteinemia

NO:

Nitric oxide

NCHS:

National Center for Health Statistics

NHANES:

National Health and Nutrition Examination Survey

SAH:

S-adenosyl-l-homocysteine

SE:

Standard error

eGFR:

Estimated glomerular filtration rate

References

  1. Cannon PJ, Stason WB, Demartini FE, Sommers SC, Laragh JH. Hyperuricemia in primary and renal Hypertension. N Engl J Med. 1966;275(9):457–64.

    Article  CAS  PubMed  Google Scholar 

  2. Tuttle KR, Short RA, Johnson RJ. Sex differences in uric acid and risk factors for coronary artery Disease. Am J Cardiol. 2001;87(12):1411–4.

    Article  CAS  PubMed  Google Scholar 

  3. Holme I, Aastveit AH, Hammar N, Jungner I, Walldius G. Uric acid and risk of Myocardial Infarction, Stroke and Congestive Heart Failure in 417,734 men and women in the apolipoprotein MOrtality RISk study (AMORIS). J Intern Med. 2009;266(6):558–70.

    Article  CAS  PubMed  Google Scholar 

  4. Khosla UM, Zharikov S, Finch JL, Nakagawa T, Roncal C, Mu W, Krotova K, Block ER, Prabhakar S, Johnson RJ. Hyperuricemia induces endothelial dysfunction. Kidney Int. 2005;67(5):1739–42.

    Article  PubMed  Google Scholar 

  5. Schwartz IF, Grupper A, Chernichovski T, Grupper A, Hillel O, Engel A, Schwartz D. Hyperuricemia attenuates aortic nitric oxide generation, through inhibition of arginine transport, in rats. J Vasc Res. 2011;48(3):252–60.

    Article  CAS  PubMed  Google Scholar 

  6. Yu MA, Sanchez-Lozada LG, Johnson RJ, Kang DH. Oxidative stress with an activation of the renin-angiotensin system in human vascular endothelial cells as a novel mechanism of uric acid-induced endothelial dysfunction. J Hypertens. 2010;28(6):1234–42.

    Article  PubMed  Google Scholar 

  7. Petri M, Roubenoff R, Dallal GE, Nadeau MR, Selhub J, Rosenberg IH. Plasma homocysteine as a risk factor for atherothrombotic events in systemic Lupus Erythematosus. Lancet. 1996;348(9035):1120–4.

    Article  CAS  PubMed  Google Scholar 

  8. Papatheodorou L, Weiss N. Vascular oxidant stress and inflammation in hyperhomocysteinemia. Antioxid Redox Signal. 2007;9(11):1941–58.

    Article  CAS  PubMed  Google Scholar 

  9. Refsum H, Ueland PM, Nygard O, Vollset SE. Homocysteine and Cardiovascular Disease. Annu Rev Med. 1998;49:31–62.

    Article  CAS  PubMed  Google Scholar 

  10. Rong D, Liu J, Jia X, Al-Nafisee D, Jia S, Sun G, Li Y, Lu W, Li H, Zhang H, et al. Hyperhomocysteinaemia is an Independent risk factor for peripheral arterial Disease in a Chinese Han population. Atherosclerosis. 2017;263:205–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kaul S, Zadeh AA, Shah PK. Homocysteine hypothesis for atherothrombotic Cardiovascular Disease: not validated. J Am Coll Cardiol. 2006;48(5):914–23.

    Article  CAS  PubMed  Google Scholar 

  12. Tribouilloy CM, Peltier M, Iannetta Peltier MC, Trojette F, Andrejak M, Lesbre JP. Plasma homocysteine and severity of thoracic aortic Atherosclerosis. Chest. 2000;118(6):1685–9.

    Article  CAS  PubMed  Google Scholar 

  13. Abraham JM, Cho L. The homocysteine hypothesis: still relevant to the prevention and treatment of Cardiovascular Disease? Cleve Clin J Med. 2010;77(12):911–8.

    Article  PubMed  Google Scholar 

  14. Shi Y, Wu Z, Wu J, Chen Z, Li P. Serum homocysteine level is positively correlated with serum uric acid level in U.S. adolescents: A Cross Sectional Study. Front Nutr. 2022;9:818836.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Wang W, Wang Q, Yang N. Serum uric acid concentration is associated with hyperhomocysteinemia in hypertensive Chinese adults. Blood Press Monit. 2022;27(3):147–51.

    Article  PubMed  Google Scholar 

  16. Markovic-Boras M, Causevic A, Curlin M. A relation of serum homocysteine and uric acid in Bosnian diabetic patients with acute Myocardial Infarction. J Med Biochem. 2021;40(3):261–9.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Kim HJ, Sohn IW, Kim YS, Jun JB. The different relationship between homocysteine and uric acid levels with respect to the MTHFR C677T polymorphism according to gender in patients with cognitive impairment. Nutrients 2020, 12(4).

  18. Cohen E, Levi A, Vecht-Lifshitz SE, Goldberg E, Garty M, Krause I. Assessment of a possible link between hyperhomocysteinemia and hyperuricemia. J Investig Med. 2015;63(3):534–8.

    Article  CAS  PubMed  Google Scholar 

  19. Palmer JL, Abeles RH. The mechanism of action of S-adenosylhomocysteinase. J Biol Chem. 1979;254(4):1217–26.

    Article  CAS  PubMed  Google Scholar 

  20. Tehlivets O, Malanovic N, Visram M, Pavkov-Keller T, Keller W. S-adenosyl-L-homocysteine hydrolase and methylation disorders: yeast as a model system. Biochim Biophys Acta. 2013;1832(1):204–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. De La Haba G, Cantoni GL. The enzymatic synthesis of S-adenosyl-L-homocysteine from adenosine and homocysteine. J Biol Chem. 1959;234(3):603–8.

    Article  PubMed  Google Scholar 

  22. Atmaca M, Tezcan E, Kuloglu M, Kirtas O, Ustundag B. Serum folate and homocysteine levels in patients with obsessive-compulsive disorder. Psychiatry Clin Neurosci. 2005;59(5):616–20.

    Article  CAS  PubMed  Google Scholar 

  23. Stolzenberg-Solomon RZ, Miller ER 3rd, Maguire MG, Selhub J, Appel LJ. Association of dietary protein intake and coffee consumption with serum homocysteine concentrations in an older population. Am J Clin Nutr. 1999;69(3):467–75.

    Article  CAS  PubMed  Google Scholar 

  24. Huang X, Qin X, Yang W, Liu L, Jiang C, Zhang X, Jiang S, Bao H, Su H, Li P, et al. MTHFR Gene and serum Folate Interaction on serum homocysteine lowering: Prospect for Precision Folic Acid Treatment. Arterioscler Thromb Vasc Biol. 2018;38(3):679–85.

    Article  CAS  PubMed  Google Scholar 

  25. Faller J, Fox IH. Ethanol-induced hyperuricemia: evidence for increased urate production by activation of adenine nucleotide turnover. N Engl J Med. 1982;307(26):1598–602.

    Article  CAS  PubMed  Google Scholar 

  26. Zhang H, Li Y, Hao M, Jiang X, Wang J, Jin L, Bao Z, Wang X. Kidney function decline is associated with an accelerated increase in plasma homocysteine in older adults: a longitudinal study. Br J Nutr 2021:1–7.

  27. Stabellini G, Calastrini C, Mariani G, Gioia M, Caramelli E, Gagliano N, Dellavia C, Moscheni C, Vizzotto L, Calvi EM. Extracellular glycosaminoglycan changes in healthy and overgrown gingiva fibroblasts after cyclosporin A and cytokine treatments. J Oral Pathol Med. 2004;33(6):346–53.

    Article  CAS  PubMed  Google Scholar 

  28. Armitage JM, Bowman L, Clarke RJ, Wallendszus K, Bulbulia R, Rahimi K, Haynes R, Parish S, Sleight P, Peto R, et al. Effects of homocysteine-lowering with folic acid plus vitamin B12 vs placebo on mortality and major morbidity in Myocardial Infarction survivors: a randomized trial. JAMA. 2010;303(24):2486–94.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank all the staff members of the NHANES study for their valuable contributions. The authors also thank Jie Liu of Department of Vascular and Endovascular Surgery, Chinese PLA General Hospital, Haibo Li of Fujian Maternity and Child Health Hospital. We would like to thank Editage (www.editage.cn) for English language editing.

Funding

This work was supported by Zhejiang Province Health Science and Technology Project (Grant No. 2021KY467).

Author information

Author notes

  1. Jiangsha Wang, Jie Zhou contributed equally to this work.

Authors and Affiliations

  1. Department of Cardiology, Jiande Hospital of Integrated Traditional Chinese and Western Medicine, Hangzhou, Zhejiang, China

    Jiangsha Wang & Zhengping Shao

  2. Center for General Practice Medicine, General Practice and Health Management Center, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, 310014, China

    Jie Zhou, Xi Chen & Wenyan Zhao

  3. Department of Neurosurgery, De Qing People’s Hospital, Deqing, Zhejiang, China

    Zhenhai Yu

Authors
  1. Jiangsha Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jie Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhengping Shao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xi Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhenhai Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Wenyan Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Jiangsha Wang wrote the original manuscript. Jie Zhou designed this study. Zhengping Shao was responsible for data download. Xi Chen verified the paper. Zhenhai Yu contributed to the statistical analysis. Wenyan Zhao reviewed and edited the paper. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Zhenhai Yu or Wenyan Zhao.

Ethics declarations

Ethics approval and consent to participate

The National Center for Health Statistics (NCHS) Ethics Review Board approved the NHANES program and released its documents for public use. Written informed consent was obtained from each participant.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, J., Zhou, J., Shao, Z. et al. Association between serum uric acid and homocysteine levels among adults in the United States: a cross-sectional study. BMC Cardiovasc Disord 23, 599 (2023). https://0-doi-org.brum.beds.ac.uk/10.1186/s12872-023-03586-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s12872-023-03586-0

Keywords

BMC Cardiovascular Disorders

ISSN: 1471-2261

Contact us