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Association between serum uric acid/high-density lipoprotein cholesterol ratio and hypertension among reproductive-aged women

Journal of Health, Population and Nutrition volume 42, Article number: 123 (2023) Cite this article

Abstract

Background

Uric acid/high-density lipoprotein cholesterol ratio (UHR) is a novel index of inflammation and metabolism that has been investigated in various diseases. However, association between UHR and hypertension among reproductive-aged women is unclear.

Methods

In this cross-sectional study, we investigated the association between serum UHR and hypertension among 5485 women aged 20–44 years based on the National Health and Nutrition Examination Survey (NHANES) database using various methods, including univariate and multivariate logistic regression analysis, stratified analysis, and spline regression. P < 0.05 was considered statistically significant.

Results

There was significant difference in UHR between the women with and without hypertension (P < 0.001). After adjusting for several covariates, UHR was positively correlated with hypertension (OR > 1, P < 0.001). In the subgroup analysis, the positive correlations still remained between UHR and hypertension in women with various age and those with BMI ≥ 30 kg/m2 (P < 0.05) excepted for adjusting for all covariates. We further found an inflection point of the threshold effect for UHR, and the prevalence of hypertension showed different increased trends below and above the threshold.

Conclusion

This study indicated a positive association between serum UHR and hypertension among reproductive-aged women, indicating that UHR is a potential clinical marker of hypertension in women.

Background

Hypertension is a common disease that seriously endangers the human health worldwide. It is universally acknowledged that hypertension is a risk factor for cardiovascular disease [1], renal disease [2, 3], stroke [4], and vascular dementia [5]. It is reported that the prevalence of hypertension was 45.4% in 2017–2018 among adults aged 18 years and over in the USA [6]. Although its prevalence was lower among women (39.7%) than men (51.0%), hypertension in women still deserves great attention. For example, increased life stress and work-related anxiety generally affect women with hypertension more significantly than men [7]. Additionally, women with chronic hypertension have a significantly increased risk of developing preeclampsia during pregnancy, affecting the safety of the mother and fetus [8]. Although there are many drugs to treat hypertension, early prediction and diagnosis of hypertension are of great importance, especially among reproductive-aged women. Currently, several objective indicators, such as Angiotensin II and aldosterone [9], may be helpful for clinical management of hypertension, but it is necessary to continue to explore the novel biomarkers or clinical indexes for prediction or diagnosis of hypertension among reproductive-aged women.

Hypertension is characterized by chronic, low-grade inflammation and metabolic imbalance [10]. Recently, several studies indicated that uric acid/high-density lipoprotein cholesterol ratio (UHR) is a novel index of inflammation. To our knowledge, association between UHR and inflammatory diseases, such as thyroiditis [11], diabetic nephropathy [12], and non-alcoholic fatty liver disease [13], has been well established. Therefore, studying UHR in hypertension may make sense. Notably, G. Aktas et al. [14] found that the level of UHR was significantly high among the participants with poor blood pressure control. However, no previous studies have specifically investigated the association between UHR and hypertension among reproductive-aged women. Our study was designed to fill this knowledge gap. Therefore, the study was performed to investigate whether UHR is a potential index of hypertension in reproductive-aged women.

Materials and methods

Study design and population

The National Health and Nutrition Examination Survey (NHANES) is a research project of the National Center for Health Statistics that collects data on the health and nutritional status of the civilian, non-institutionalized population of the USA. The survey data are released every 2 years. In addition, all participants have written informed consent for data collection before any data collection [15].

A total of 8000 women aged 20–44 years were recorded in the NHANES database from 1999 to 2018. Therein, participants with the following characteristics were excluded: (1) women who were pregnant (n = 1227) and missing pregnancy status (n = 546); (2) those with missing information of hypertension (n = 266), serum uric acid (n = 20), and high-density lipoprotein cholesterol (n = 318); (3) those with missing education (n = 4), marital status (n = 48), diabetes mellitus (n = 47), smoking status (n = 4), body mass index (BMI) values (n = 31), and triglyceride (n = 4). Therefore, 5485 women were finally included in this analysis (Fig. 1).

Fig. 1
figure 1

Flowchart of participant selection from the NHANES 1999–2018

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The exposure and outcome variables' definition

The exposure variable was the UHR, which was determined as serum uric acid divided by high-density lipoprotein cholesterol. Hypertension diagnosis was determined by a combination of self-reported physician diagnosis, use of medication for hypertension, and having a systolic blood pressure ≥ 130 or/and a diastolic blood pressure ≥ 80 mmHg according to the American Heart Association/American College of Cardiology 2017 guideline for monitoring and diagnosis of hypertension [16].

Covariates

The covariates are demographic information, physical examinations, laboratory data, and questionnaire data. Demographic information included age, race, education level, and marital status. Laboratory data included triglycerides and total cholesterol. Physical examinations included BMI. Additionally, questionnaire data included smoking behavior and diabetes mellitus (yes or no). Therein, the smoking status was defined as current (smoked > 100 cigarettes in their lifetime and currently smoked some days or every day), past (smoked > 100 cigarettes in their lifetime but currently did not smoke at all), and never (smoked < 100 cigarettes in their lifetime) [17].

Statistical analyses

Categorical variables were presented using percentages [n (%)]. For continuous variables, we first performed a normality test; those that obeyed the normal distribution were presented using mean ± standard deviation, whereas those that did not obeyed the normal distribution were presented using median and quartiles [M (Q1, Q3)]. We found that the UHR data are unevenly distributed and clearly skewed to the right. Therefore, prior to conducting regression analysis, the values of UHR need to be in-transformed. Univariable logistic regression analysis was used to screen covariates, and variables with statistically significant were included in multivariable logistic regression analysis. Three models were established to evaluate the association between UHR and hypertension. Model 1 was a univariable logistic regression model, model 2 was a multivariable logistic regression model adjusted for age, race, education, and marital status, and model 3 was a multivariable logistic regression model adjusted for age, race, education, marital status, diabetes mellitus, BMI, smoking status, triglycerides, and total cholesterol. The odds ratio (OR) with 95% confidence interval (CI) was used to report associations. Stratified analyses were performed based on age (< 35 years and ≥ 35 years) and BMI (< 25 kg/m2 and 25, < 30 kg/m2 and ≥ 30 kg/m2). Finally, a spline regression was ultimately used to assess whether there was a linear relationship between UHR and hypertension. R software and EmpowerStats were used for data analysis, and P < 0.05 was considered statistically significant.

Results

Baseline characteristics of the participants with or without hypertension

A total of 5485 reproductive-aged women were included in the final analysis. Compared to the non-hypertension group, participants in the hypertension group were more likely to be older, other Hispanic, high school education or below, widowed/divorced/separated, and with BMI ≥ 30 kg/m2. Significant differences were also observed between the two groups for smoking and diabetes mellitus status. Meanwhile, women with hypertension had higher level of serum uric acid, lower level of high-density lipoprotein cholesterol, and higher levels of UHR, triglycerides, and total cholesterol (Table 1).

Table 1 Basic characteristics of the research population with and without hypertension
Full size table

Associations between UHR and hypertension

Firstly, univariate logistic regression analysis was performed to analyze the associations between the collected variables and hypertension (Table 2). The results showed that several variables, including age, non-Hispanic Black, other Hispanic, widowed/divorced/separated, BMI ≥ 25 kg/m2, with diabetes mellitus, with smoking, uric acid, UHR, triglycerides, and total cholesterol, were significantly positively associated with hypertension. Additionally, more than high school education, never married, and high-density lipoprotein cholesterol were significantly negatively associated with hypertension.

Table 2 Univariate logistic regression for variables associating with hypertension
Full size table

The adjusted correlation between UHR and hypertension is presented in Table 3. In the unadjusted model (model 1), we found that the UHR were positively associated with the prevalence of hypertension (OR 3.02, P < 0.001). After adjusting for multiple covariates, the positive correlation between UHR and hypertension remained significant in the model 2 and 3 (model 2: OR 3.24, P < 0.001; model 3: OR 1.77, P < 0.001). After converting UHR to a categorical variable (quartiles), the UHR levels of the Q4 groups were still positively correlated with the prevalence of hypertension compared with the lowest quartile of UHR (Q1). In addition, the trend remained significant among different UHR quartile groups (P for trends < 0.05 in the three models) (Table 3). The subgroup analyses stratified by age and BMI are reported in Table 4. For women with different ages, those with higher UHR levels both had a higher incidence of hypertension than those with lower levels. Furthermore, we found that higher UHR levels were consistently associated with the increased risk of hypertension in the group with BMI ≥ 30 kg/m2 excepted for the model 3.

Table 3 Logistic regression of UHR for the risk of hypertension
Full size table
Table 4 Subgroup analysis stratified by age and BMI
Full size table

Nonlinear results of UHR and hypertension

Smooth curve fitting was performed after adjusting for confounding factors in model 3, and the results indicated that the association between UHR and hypertension was nonlinear over the entire range of UHR (Fig. 2). We further found that the inflection point of the threshold effect for lnUHR was -1.86, and the prevalence of hypertension slowly increased with UHR below the threshold (OR 1.36, P = 0.037) and then significantly increased above the threshold (OR 8.64, P = 0.002) (Table 5).

Fig. 2
figure 2

The association between UHR and hypertension. The solid red line represents the smooth curve fit between variables. Blue bands represent the 95% confidence interval from the fit

Full size image
Table 5 Nonlinearity addressed through two-piecewise linear model
Full size table

Discussion

Using a nationally representative sample of the reproductive-aged women in the USA, the present study obtains several major findings. First, a significant difference existed in UHR between the women with and without hypertension. Second, the univariate logistic regression analysis showed that UHR was positively correlated with hypertension, and the positive correlations remained after adjusting for several covariates. Third, UHR was also correlated with hypertension in women with different age and those with BMI ≥ 30 kg/m2 when adjusting for several covariates. Finally, we found an inflection point of the threshold effect for UHR and the prevalence of hypertension showed different increased trends below and above the threshold.

Inflammation, oxidative damage, and endothelial dysfunction are involved in the pathophysiology of hypertension [18, 19]. Elevated uric acid can contribute to atherosclerosis by damaging blood vessel walls, which is closely associated with hypertension, dyslipidemia, and insulin resistance [20]. High level of uric acid activates the renin-angiotensin system and reduces the synthesis of insulin-induced nitric oxide in endothelial cells [21, 22]. Additionally, dyslipidemias, including elevated level of low-density lipoprotein cholesterol and decreased level of high-density lipoprotein cholesterol, is common in patients with hypertension. Among them, high-density lipoprotein cholesterol can protect vascular endothelial cells through anti-inflammatory effects [23]. Therefore, both high uric acid and low high-density lipoprotein cholesterol may be associated with an increased risk of hypertension, and their ratio, i.e., UHR, has been widely used in various inflammatory diseases, such as poorly controlled hypertension, type 2 diabetes mellitus, metabolic syndrome, or ischemic heart disease [14, 24,25,26] since a single parameter may not be enough to predict or diagnose diseases. To the best of our knowledge, this is the first study to explore UHR and the risk of hypertension in reproductive-aged women. However, the current evidence only supports this association and cannot be applied to clinical prediction or diagnosis.

In this study, we found that multiple variables, such as older age and widowed/divorced/separated status, were positively correlated with hypertension, whereas educational attainment was negatively correlated with it. It is widely knowledge that older age is a risk factors of hypertension [27]. Additionally, previous studies have indicated that widowhood can increase a woman’s risk of hypertension by 92% [28]. Although the mechanisms underlying the effect of marital status on hypertension are not fully understood, previous studies have suggested that this may be due to various factors, such as neuroendocrine pathways, psychopathological factors, health behaviors, or immune pathways [29]. For example, unhappy relationships may contribute to poorer health, and marital problems often predict psychopathology, such as mood and anxiety [30]. Distressed couples exhibit greater negative affect, possibly related to cardiovascular and neuroendocrine responsive biological mediators [31], for example, greater negative behavior during marital interactions is associated with elevated catecholamine levels [32]. Additionally, previous studies have indicated that education level was negatively associated with the prevalence of hypertension among both men and women [27]. Another study also showed an association between educational attainment and better awareness of blood pressure among women [33]. High educational attainment can improve the awareness and control of hypertension. People with higher education may have better blood pressure control. Studies have found that those with higher formal education were more aware of their overall health and are more likely to receive medication, which ultimately leads to better blood pressure control [34, 35]. Notably, social determinants of health have a greater impact on the prevalence of hypertension in women than in men [36]. Therefore, we adjusted these confounding factors in logistic regression models and found that UHR level is still positively correlated with hypertension among reproductive-aged women.

There are several limitations in this study, such as the relatively small sample size. Besides, this is a cross-sectional study so we cannot infer a causal relationship between UHR and hypertension, and we do not know yet whether it can predict the onset of hypertension in advance. In order to promote the clinical application of UHR in hypertension, we should validate these correlations in women populations in other regions and explore whether elevated UHR levels could predict hypertension, including its sensitivity and specificity, through prospective cohort studies. In addition, whether we can combine UHR with other indicators to predict hypertension, as well as the timing of UHR measurement, are all questions that need to be answered before clinical translation. Further experiments will help to understand the underlying mechanisms behind the link between UHR and hypertension.

Conclusion

Serum UHR was independently and positively correlated with the prevalence of hypertension among reproductive-aged women. After converting UHR to quartiles, the Q4 of UHR was also positively correlated with hypertension. In the subgroup analysis, this association remained positive in various age stages as well as in the women with BMI ≥ 30 kg/m2 (except for the model 3). Furthermore, an inflection point of the threshold effect for lnUHR in the smooth curve fitting was found to be -1.86, and the prevalence of hypertension slowly increased with UHR below the threshold and then significantly increased above the threshold. However, further studies are warranted to validate these associations and to elucidate the mechanisms underlying these associations between serum UHR and hypertension.

Availability of data and materials

The data of this study are publicly available on the NHANES (http://www.cdc.gov/nchs/nhanes/).

Abbreviations

BMI:

Body mass index

CI:

Confidence interval

NHANES:

National Health and Nutrition Examination Survey

OR:

Odds ratio

UHR:

Uric acid/high-density lipoprotein cholesterol ratio

References

  1. Curfman G, Bauchner H, Greenland P. Treatment and control of hypertension in 2020: the need for substantial improvement. JAMA. 2020;324(12):1166–7.

    Article  PubMed  Google Scholar 

  2. Kobayashi K. Minimizing the cumulative burden of hypertension to reduce the risk of end-stage renal disease. Hypertens Res. 2021;44(12):1683–5.

    Article  PubMed  Google Scholar 

  3. Leiba A, Fishman B, Twig G, Gilad D, Derazne E, Shamiss A, et al. Association of adolescent hypertension with future end-stage renal disease. JAMA Intern Med. 2019;179(4):517–23.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Boehme AK, Esenwa C, Elkind MS. Stroke risk factors, genetics, and prevention. Circ Res. 2017;120(3):472–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Sharp SI, Aarsland D, Day S, Sonnesyn H. Alzheimer’s society vascular dementia systematic review G, Ballard C. Hypertension is a potential risk factor for vascular dementia: systematic review. Int J Geriatr Psychiatry. 2011;26(7):661–9.

    Article  PubMed  Google Scholar 

  6. Ostchega Y, Fryar CD, Nwankwo T, Nguyen DT. Hypertension prevalence among adults aged 18 and over: United States, 2017–2018. NCHS Data Brief. 2020;364:1–8.

    Google Scholar 

  7. Azizi Z, Alipour P, Raparelli V, Norris CM, Pilote L. The role of sex and gender in hypertension. J Hum Hyperten. 2023;37(8):589–95.

    Article  Google Scholar 

  8. Bartsch E, Medcalf KE, Park AL, Ray JG. High risk of pre-eclampsia Identification G. Clinical risk factors for pre-eclampsia determined in early pregnancy: systematic review and meta-analysis of large cohort studies. BMJ. 2016;353:i1753.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Xue B, Beltz TG, Yu Y, Guo F, Gomez-Sanchez CE, Hay M, et al. Central interactions of aldosterone and angiotensin II in aldosterone- and angiotensin II-induced hypertension. Am J Physiol Heart Circ Physiol. 2011;300(2):H555–64.

    Article  CAS  PubMed  Google Scholar 

  10. Mouton AJ, Li X, Hall ME, Hall JE. Obesity, hypertension, and cardiac dysfunction: novel roles of immunometabolism in macrophage activation and inflammation. Circ Res. 2020;126(6):789–806.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kurtkulagi O, Tel BMA, Kahveci G, Bilgin S, Duman TT, Erturk A, et al. Hashimoto’s thyroiditis is associated with elevated serum uric acid to high density lipoprotein-cholesterol ratio. Rom J Intern Med. 2021;59(4):403–8.

    PubMed  Google Scholar 

  12. Aktas G, Yilmaz S, Kantarci DB, Duman TT, Bilgin S, Balci SB, et al. Is serum uric acid-to-HDL cholesterol ratio elevation associated with diabetic kidney injury? Postgrad Med. 2023;135(5):519–23.

    Article  CAS  PubMed  Google Scholar 

  13. Zhang YN, Wang QQ, Chen YS, Shen C, Xu CF. Association between serum uric acid to HDL-cholesterol ratio and nonalcoholic fatty liver disease in lean Chinese adults. Int J Endocrinol. 2020;2020:5953461.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Aktas G, Khalid A, Kurtkulagi O, Duman TT, Bilgin S, Kahveci G, et al. Poorly controlled hypertension is associated with elevated serum uric acid to HDL-cholesterol ratio: a cross-sectional cohort study. Postgrad Med. 2022;134(3):297–302.

    Article  CAS  PubMed  Google Scholar 

  15. Zipf G, Chiappa M, Porter KS, Ostchega Y, Lewis BG, Dostal J. National health and nutrition examination survey: plan and operations, 1999–2010. Vital Health Stat 1. 2013;56:1–37.

    Google Scholar 

  16. Whelton PK, Carey RM, Aronow WS, Casey DE Jr, Collins KJ, Dennison Himmelfarb C, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: a report of the American college of cardiology/American heart association task force on clinical practice guidelines. Hypertension. 2018;71(6):e13–115.

    CAS  PubMed  Google Scholar 

  17. Naimi TS, Brewer RD, Mokdad A, Denny C, Serdula MK, Marks JS. Binge drinking among US adults. JAMA. 2003;289(1):70–5.

    Article  PubMed  Google Scholar 

  18. Xiu J, Lin X, Chen Q, Yu P, Lu J, Yang Y, et al. The aggregate index of systemic inflammation (AISI): a novel predictor for hypertension. Front Cardiovasc Med. 2023;10:1163900.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Serinkan Cinemre FB, Cinemre H, Bahtiyar N, Kahyaoglu B, Agac MT, Shundo H, et al. Apelin, Omentin-1, and Vaspin in patients with essential hypertension: association of adipokines with trace elements, inflammatory cytokines, and oxidative damage markers. Ir J Med Sci. 2021;190(1):97–106.

    Article  CAS  PubMed  Google Scholar 

  20. Moulin-Mares SRA, Oliosa PR, Faria ER, Zago-Gomes MP, Mill JG. Association of uric acid with cardiovascular risk in Brazilian children and adolescents. Nutr Metab Cardiovasc Dis. 2021;31(1):314–21.

    Article  CAS  PubMed  Google Scholar 

  21. 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 

  22. Choi YJ, Yoon Y, Lee KY, Hien TT, Kang KW, Kim KC, et al. Uric acid induces endothelial dysfunction by vascular insulin resistance associated with the impairment of nitric oxide synthesis. FASEB J. 2014;28(7):3197–204.

    Article  CAS  PubMed  Google Scholar 

  23. Hu J, Xi D, Zhao J, Luo T, Liu J, Lu H, et al. High-density lipoprotein and inflammation and its significance to atherosclerosis. Am J Med Sci. 2016;352(4):408–15.

    Article  PubMed  Google Scholar 

  24. Aktas G, Kocak MZ, Bilgin S, Atak BM, Duman TT, Kurtkulagi O. Uric acid to HDL cholesterol ratio is a strong predictor of diabetic control in men with type 2 diabetes mellitus. Aging Male. 2020;23(5):1098–102.

    Article  PubMed  Google Scholar 

  25. Yazdi F, Baghaei MH, Baniasad A, Naghibzadeh-Tahami A, Najafipour H, Gozashti MH. Investigating the relationship between serum uric acid to high-density lipoprotein ratio and metabolic syndrome. Endocrinol Diabetes Metab. 2022;5(1):e00311.

    Article  CAS  PubMed  Google Scholar 

  26. Park B, Jung DH, Lee YJ. Predictive value of serum uric Acid to HDL cholesterol ratio for incident ischemic heart disease in non-diabetic Koreans. Biomedicines. 2022;10(6):1422.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Hoang VM, Byass P, Dao LH, Nguyen TK, Wall S. Risk factors for chronic disease among rural Vietnamese adults and the association of these factors with sociodemographic variables: findings from the WHO STEPS survey in rural Vietnam, 2005. Prev Chronic Dis. 2007;4(2):A22.

    PubMed  Google Scholar 

  28. Ramezankhani A, Azizi F, Hadaegh F. Associations of marital status with diabetes, hypertension, cardiovascular disease and all-cause mortality: a long term follow-up study. PLoS ONE. 2019;14(4):e0215593.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Robles TF, Slatcher RB, Trombello JM, McGinn MM. Marital quality and health: a meta-analytic review. Psychol Bull. 2014;140(1):140–87.

    Article  PubMed  Google Scholar 

  30. Whisman MA, Baucom DH. Intimate relationships and psychopathology. Clin Child Fam Psychol Rev. 2012;15(1):4–13.

    Article  PubMed  Google Scholar 

  31. Robles TF, Kiecolt-Glaser JK. The physiology of marriage: pathways to health. Physiol Behav. 2003;79(3):409–16.

    Article  CAS  PubMed  Google Scholar 

  32. Kiecolt-Glaser JK, Glaser R, Cacioppo JT, MacCallum RC, Snydersmith M, Kim C, et al. Marital conflict in older adults: endocrinological and immunological correlates. Psychosom Med. 1997;59(4):339–49.

    Article  CAS  PubMed  Google Scholar 

  33. Lee HY. Socioeconomic disparities in the prevalence, diagnosis, and control of hypertension in the context of a universal health insurance system. J Korean Med Sci. 2017;32(4):561–7.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Satoh A, Arima H, Ohkubo T, Nishi N, Okuda N, Ae R, et al. Associations of socioeconomic status with prevalence, awareness, treatment, and control of hypertension in a general Japanese population: NIPPON DATA2010. J Hypertens. 2017;35(2):401–8.

    Article  CAS  PubMed  Google Scholar 

  35. Pandit AU, Tang JW, Bailey SC, Davis TC, Bocchini MV, Persell SD, et al. Education, literacy, and health: mediating effects on hypertension knowledge and control. Patient Educ Couns. 2009;75(3):381–5.

    Article  PubMed  Google Scholar 

  36. Wang L, Zhang H, Yao H, Gong C, Zhong J, Liu D, et al. Social determinants of health and hypertension in women compared with men in the United States: an analysis of the NHANES study. Clin Cardiol. 2023;46(8):958–66.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors appreciate the staff and the participants of the NHANES for their valuable contributions.

Funding

This study was supported by grants from the Natural Science Foundation of Guangdong Province, China (No. 2023A1515012741).

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Author notes

  1. Xiaoxue Han, Xuan Tan and Mengyuan Liu contributed equally to this work.

Authors and Affiliations

  1. Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, No. 613, Huangpu Road West, Tianhe District, Guangzhou, 510630, Guangdong, China

    Xiaoxue Han, Xuan Tan, Mengyuan Liu, Yiling Wei, Andong He, Ying Pan, Di Qiu & Ruiman Li

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Contributions

RL, XH, XT, and ML designed the study. YW, YP, and DQ acquired the data. XH, XT, ML, YW, AH, YP, and DQ performed the data analysis. Xiaoxue Han and Xuan Tan wrote the manuscript. RL, ML, YW, and AH revised or critically reviewed the manuscript. All authors approved the final manuscript.

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Correspondence to Ruiman Li.

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All protocols were approved by the ethics review board of the National Center for Health Statistics, and written informed consents were obtained from the participants.

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Han, X., Tan, X., Liu, M. et al. Association between serum uric acid/high-density lipoprotein cholesterol ratio and hypertension among reproductive-aged women. J Health Popul Nutr 42, 123 (2023). https://doi.org/10.1186/s41043-023-00458-3

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Journal of Health, Population and Nutrition

ISSN: 2072-1315

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