https://orcid.org/0000-0003-3524-6783
Abstract
Background
The relationship between uric acid (UA) and benign prostatic hyperplasia (BPH) is controversial and has rarely been studied in American populations.
Methods
Data from two cycles of the National Health and Nutrition Examination Surveys, comprising data from 2005 to 2008, were used. The majority of BPH were identified by self-report. We investigated the relationship between UA and BPH using univariate and multivariate logistic regression analyses.
Results
2,845 participants were enrolled in the study, including 531 participants with BPH and 2,314 controls. After fully adjusting for all confounders, the risk of developing BPH was reduced by 18% for every 100 μmol/L increase in UA (OR = 0.82, 95% CI: 0.69–0.97, p = 0.023). Participants in the highest quartile of UA were found to have a reduced likelihood of developing BPH (ORQ4vs1 = 0.61, 95% CI: 0.41–0.91) in comparison to those in the lowest quartile of UA. Subgroup analyses found that among those younger than 60 years, non-Hispanic whites, former smokers, heavy drinkers, those without diabetes, or those with hypertension, high UA remained negatively associated with BPH.
Conclusions
The above results suggest that UA may be a potential protective factor for BPH, but the mechanism needs to be further explored.
1. Introduction
Benign prostatic hyperplasia (BPH) is a disease of excessive uncontrolled growth of epithelial and fibromuscular tissue in the migratory and urethral regions [Citation1]. It is a common disease in older men, manifesting mainly as lower urinary tract symptoms (LUTS), posing a serious threat to their health and quality of life [Citation2]. According to a 2019 study of the general population, BPH instances have increased by 105.7% since 1990, with the frequency being greatest in people between the ages of 65 and 69 [Citation3]. There are other risk factors for BPH in addition to age, such as unhealthy lifestyle choices, smoking, alcohol use, inflammation, hereditary factors, obesity, hypertension, diabetes, cardiovascular disease, and hypogonadism [Citation4]. The metabolic syndrome (MS) and its associated comorbidities, such as altered sex steroids and low-grade inflammation, are closely related to BPH [Citation5]. Patients with BPH who also had MS had faster prostate growth, according to a meta-analysis investigating the link between MS and BPH [Citation6].
The product of purine metabolism is uric acid (UA), an essential molecule in the body. According to studies, patients with MS had higher serum UA levels [Citation7,Citation8]. Gout is frequently caused by high levels of blood UA, and a survey of male patients with gout revealed that they had a higher incidence of BPH [Citation9]. UA was also positively correlated with the International Prostate Symptom Score (IPSS) [Citation10]. However, a recent study showed that participants with high levels of UA had the lowest chance of developing LUTS compared to those with lower UA [Citation11]. This may be mainly related to the different roles that UA plays in different chemical environments, where it can both promote oxidative stress and play an antioxidant role [Citation12]. UA also has an important role in the regulation of prostate cells [Citation11]. The link between UA and BPH has received increasing attention lately, but the relationship is not yet clear.
Therefore, based on representative data from the National Health and Nutrition Examination Survey (NHANES) 2005–2008, the objective of this study was to examine the link between various UA levels and BPH by weighting and controlling for relevant covariates. We also performed subgroup analyses according to several important factors associated with BPH and further explored potential associations.
2. Materials and methods
2.1. Research population
NHANES, a survey conducted by the National Center for Statistics, has the primary objective of obtaining representative demographic, relevant examination, and questionnaire data to assess nutritional and physical health through a complex sampling design. In this cross-sectional study, we used data related to BPH and UA from NHANES 2005–2008. We did not need to do a second review as all data utilized for the analysis is available on the official NHANES website, and all NHANES participants completed informed consent forms and passed ethical review as required by policy.
2.2. Outcome variable
All male participants were asked two questions about prostate enlargement. Question 1: “Are you ever been told that your prostate is enlarged?” When participants answered “No,” they were not considered to have BPH, and when participants answered “Yes,” they were asked Question 2, “Is it benignly enlarged?” Only participants who answered “Yes” were considered to have BPH. Cancerous enlargement and missing data were excluded [Citation13].
2.3. Exposure variable
Details of serum urate measurement and quality control have been described elsewhere [Citation14], and values are reported in micromoles per liter (μmol/L). First, we considered UA as a continuous variable for statistical analysis. Second, to further test the dose-response relationship, we also converted UA into categorical variables by quartiles based on the level of UA for all participants. The stratified median was used as a quasi-continuous variable in the model to calculate p-values for trends.
2.4. Potential confounders
We considered the following variables as covariates, including age, race, education, marital status, economic situation, body mass index (BMI), history of smoking, alcohol consumption, hypertension, diabetes, and cardiovascular disease. Education levels were classified as less than high school, high school, and above high school. There were two main types of marital situation, married/living with partner or living alone. The poverty-to-income ratio (PIR) was classified as < 1.5, 1.5–3.5, and ≥ 3.5. BMI was divided into four categories, including < 20, 20–25, 25–30, and ≥ 30. A non-smoker was defined as someone who has never smoked more than 100 cigarettes in their entire life, while the remaining participants are categorized as current and former smokers depending on their current smoking status. Alcohol consumption was classified according to the amount of alcohol consumed and is divided into none, light (1–2 drinks/day), and heavy (>2 drinks/day). Participants were identified as hypertensive if their mean systolic and diastolic blood pressure levels were greater than or equal to 140/90 mmHg or if they had previously received a diagnosis of hypertension. Those with a history of diabetes or whose fasting blood glucose levels were above 126 mg/dL were regarded as diabetics. Men were deemed to have cardiovascular disease if they had previously been diagnosed with angina, a heart attack, or coronary artery disease [Citation15].
2.5. Statistical analysis
We considered sampling weights as required by the NHANES analysis, and the last four years of data were obtained by using two years of MEC weights multiplied by 0.5. A statistical description of baseline data was calculated according to BPH quartiles and serum UA. Continuous variables were checked for normality, normal distribution-conforming variables underwent independent samples t-tests or ANOVA tests, and nonnormal distribution-conforming variables underwent nonparametric tests. The chi-square test was used to compare categorical variables.
Univariate and multivariate logistic regression analyses were used to investigate the relationship between UA and BPH. There is no adjustment for any confounding factors in Model 1. Model 2 was adjusted for PIR, age, race, education, and marital status. Model 3 was adjusted for BMI, history of smoking, alcohol consumption, hypertension, diabetes, and cardiovascular disease based on Model 2. Subgroup analyses stratified by age, race, history of smoking, alcohol consumption, hypertension, and diabetes. All statistical analyses were performed in Stata 15 and SPSS 27, and a two-sided p < 0.05 was regarded as statistically significant.
3. Results
3.1. Characteristics
Our study includes 2845 individuals in total, which approximately represents 54 million US citizens (). Each participant was older than 40. With a mean age of 64.03 in the BPH group and 54.39 in the control group, shows the baseline characteristics of all participants classified according to BPH. The mean UA levels were 365.77 μmol/L in the control group and 358.04 μmol/L in the BPH group. In , the baseline characteristics are described by grouping according to quartiles of UA. When compared to the first quartile, participants whose UA levels were in the fourth quartile tended to be non-Hispanic whites, with a BMI ≥ 30 and a history of hypertension.
Figure 1. Flow chart of the screening process for participants included in this study.
Table 1. Weighted characteristics of participants according to BPH classification.
Table 2. Weighted characteristics of participants according to UA classification.
3.2. UA and BPH
In model 3, which fully adjusted for all confounders, the risk of developing BPH was reduced by 18% for every 100 μmol/L increase in UA (OR = 0.82, 95% CI: 0.69–0.97, p = 0.023). In model 1, the second (ORQ2vs1 = 0.67, 95% CI: 0.47–0.95, p = 0.024) and fourth quartiles (ORQ4vs1 = 0.70, 95% CI: 0.50–0.98, p = 0.038) were negatively correlated with BPH compared to the first quartile. In model 2, the fourth quartile (ORQ4vs1 = 0.67, 95% CI: 0.46–0.98, p = 0.040) had a negative correlation with BPH compared to the first quartile. In model 3, the fourth quartile (ORQ4vs1 = 0.61, 95% CI: 0.41–0.91, p = 0.015) had a negative correlation with BPH (). And in model 3, the P for trend test was 0.028.
Table 3. Association between UA and BPH, weighted.
3.3. Subgroup analyses
displayed the outcomes of the subgroup analysis. Among those younger than 60 years (ORQ4vs1 = 0.49, 95% CI: 0.24–0.98), non-Hispanic white (ORQ4vs1 = 0.56, 95% CI: 0.35–0.88), former smoker (ORQ2vs1 = 0.50, 95% CI: 0.28–0.89; ORQ4vs1 = 0.42, 95% CI: 0.23–0.74), heavy alcohol consumers (ORQ2vs1 = 0.41, 95% CI: 0.20–0.85; ORQ4vs1 = 0.45, 95% CI: 0.21–0.96), those without diabetes (ORQ2vs1 = 0.62, 95% CI: 0.40–0.98; ORQ4vs1 = 0.54, 95% CI: 0.33–0.86), or those with hypertension (ORQ4vs1 = 0.51, 95% CI: 0.31–0.84), UA was negatively correlated with BPH.
Table 4. Weighted or (95% CI) of UA and BPH in each subgroup.
4. Discussion
Our study conducted a cross-sectional study that was nationally representative to explore if serum UA is correlated with BPH. There is a paucity of research on this topic, and there has been no uniform understanding. UA negatively correlates with the risk of BPH. Compared to the UA level in the first quartile, our study indicated that the fourth quartile had a negative correlation with BPH. In addition, this association is still held in people younger than 60 years, non-Hispanic whites, former smokers, heavy alcohol consumers, hypertensive, and without diabetes.
One of the most common causes of LUTS in elderly men is BPH. The etiology of BPH is uncertain, despite the fact that various probable contributing variables have been found [Citation16]. The development of BPH is thought to be influenced by androgens, estrogens, and inflammation, as well as the effects of age and aging [Citation1]. In a cross-sectional study, a negative correlation was found between serum UA and testosterone [Citation17]. In humans, UA is the product of purine degradation and is a weak organic acid that exists mainly as sodium urate at physiological pH values. Hyperuricemia is related to various human diseases, and in addition to gout, the link between hyperuricemia and cardiovascular mortality has attracted a lot of attention. Several studies have demonstrated that having a high UA level puts one at risk of developing hypertension and dying from cardiovascular disease [Citation18,Citation19]. Hyperuricemia, on the other hand, may benefit bone and lung health in healthy middle-aged people, as well as play a significant role in human health by serving as an antioxidant [Citation20,Citation21]. About half of the antioxidant capacity of human plasma is made up of UA, which has antioxidant capabilities comparable to those of ascorbic acid [Citation22]. The antioxidant effect of UA may be the basis for its action against aging, cancer, and cardiovascular disease [Citation23,Citation24]. Higher blood UA levels were linked to a lower likelihood of LUTS, according to a recent Korean study encompassing 101,091 individuals [Citation11]. This finding raises the possibility that UA may be involved in suppressing LUTS. Our study also demonstrates a negative correlation between high blood UA levels and the incidence of BPH, which we hypothesize may be because UA has an antioxidant impact that protects the prostate.
The role does serum UA play in the prostate gland has been a matter of debate among researchers. In contrast to the previous protective effect, UA levels are positively correlated with prostate cancer risk, according to a prospective study. Sangkop et al. found that plasma or intracellular UA levels may be associated with glucose transporters 9 (GLUT9) and a urate efflux transporter, that elevated extracellular UA has a pro-growth effect, and that lowering UA levels in patients with prostate cancer may be an effective therapeutic measure [Citation25]. An animal study showed that cinnamaldehyde is a compound that can improve prostate hyperplasia, and its main mechanism of action may be to inhibit the IL-6/JAK1/STAT3 inflammatory pathway and reduce serum UA levels [Citation26]. But one other study showed that there was no correlation between UA and prostate cancer risk [Citation27]. In summary, the role of UA in malignant prostate proliferation remains unclear. A clinical investigation with 14,427 participants revealed that prostate cysts, BPH, and UA were all separate risk factors for prostate stones, which can be associated with local urate deposition [Citation28]. Local deposition of UA can cause inflammation and tissue damage, which is detrimental to health, so in participants with BPH, monitoring of UA in blood and urine should be intensified.
Balasar et al. demonstrated no difference in prostate-specific antigen (PSA) among the different UA-level groups [Citation29]. However, another study revealed that UA was positively correlated with PSA and negatively correlated with total or free PSA [Citation10]. According to the findings of earlier research, the need for PSA monitoring in people with BPH and hyperuricemia should be emphasized. This study has suggested a negative correlation between high levels of UA and BPH, and the possible hypothesis is that UA has a protective role in the development of BPH. Therefore, it is vital for clinicians to carefully consider whether to improve the symptoms of males with BPH by using drugs that lower UA.
Although our study identified a potential correlation between UA and the risk of BPH, there are several restrictions. First, the data used for analysis came from an old dataset. Second, this was a cross-sectional study, and a possible causal association between UA and BPH could not be derived. Finally, BPH was diagnosed mainly by self-report, and the specifics of the disease are unknown. Also, as mentioned earlier, there is diversity in the relationship between UA and prostate, and we suggest a review of this issue to draw more comprehensive conclusions.
5. Conclusion
The above results suggest that UA may be a potential protective factor for BPH. Not only because of the limitations of our study but also because of the complexity of UA and BPH status, further prospective studies will still be required.
Ethical statement
We did not need to do a second review as all data utilized for the analysis are available on the official NHANES website, and all NHANES participants completed informed consent forms and passed ethical review as required by policy.
Author contributions
HZ designed the study, performed the data analysis, and wrote the manuscript. MMX and XXH analyzed and interpreted the data; ZNX, and YP collected and examined the data. XQL provided ideas for the study and optimized the final manuscript. The final manuscript was reviewed and approved by all writers.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
All data applied in this study can be searched on the NHANES website (https://www.cdc.gov/nchs/nhanes/index.htm), and more detailed analysis data can be obtained by contacting the corresponding author.
Additional information
Funding
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