INTRODUCTION
The International Continence Society (ICS) defines nocturia as a need to wake up to urinate in the main sleeping period [1]. Nocturia is more prevalent in women than in men. As the nocturia becomes common after middle age (≥40 years), the prevalence in men exceeds that in women, particularly in the older population [2-4]. In a meta-analysis, nocturia was correlated with mortality, regardless of age and sex [5]. Nocturia interrupts sleep, disrupts circadian rhythms, contributes to cardio-metabolic disorders, and impacts mortality [6]. This means the impact of nocturia on mortality can vary depending on metabolic abnormalities.
Metabolic and inflammatory factors are increasingly recognized as contributors to lower urinary tract symptoms (LUTS) pathophysiology [7]. Serum uric acid (sUA) has been linked to systemic diseases independent of crystal deposition, resulting in obesity, insulin insensitivity, cardiovascular diseases, and metabolic syndrome [8]. Furthermore, sUA has emerged as a potential factor modulating prostate and bladder function [9-13]. Given that nocturia is one of the most bothersome LUTS, there is growing interest in understanding whether elevated sUA contributes to nocturia. However, the impact of uric acid on nocturia is underinvestigated.
Given the limited evidence, we conducted a large-scale analysis to explore the relationship between nocturia and mortality. Using robust statistical methods, our primary objective was to assess this association in middle-aged and older adults. Furthermore, we examined the potential mediating effects of sUA to evaluate its contribution to the nocturia-mortality pathway.
MATERIALS AND METHODS
Study Design and Data Source
The National Health and Nutrition Examination Survey (NHANES) is a cross-sectional, nationally representative survey conducted in the United States that collects comprehensive health-related information through structured interviews, physical examinations, and laboratory assessments. Mortality outcomes were ascertained by linkage to the National Death Index through 2019, with a median follow-up duration of 107.3 months.
Of the 50,965 individuals who participated across five cycles (2005–2014), those aged ≥40 years who had completed the nocturia questionnaire, sUA measurements, and metabolic risk factor assessments were considered for inclusion. After excluding 38,443 participants due to missing data on key variables or incomplete follow-up information, a total of 12,522 individuals were retained for preliminary statistical analyses.
Definition of Nocturia, sUA, and Cardiovascular Risks
We defined nocturia based on the self-reported data from the kidney condition questionnaire. Nocturia was defined as ≥2 nightly voids during the past year, as this threshold, although higher than the ICS definition (≥1 void), is generally regarded as bothersome and clinically meaningful [14].
sUA levels were measured using a timed endpoint enzymatic method with uricase on either the Beckman Synchron LX20 or the Beckman Coulter UniCel DxC800 platform, depending on the survey cycle. Uric acid is oxidized to allantoin and hydrogen peroxide, with the subsequent peroxidase-catalyzed chromogenic reaction monitored at 520 nm; the change in absorbance is directly proportional to the sUA concentration. All measurements adhered to the NHANES laboratory quality control protocol, incorporating internal and external reference standards to ensure accuracy and comparability across survey years.
For hypertension (HTN), participants were classified as hypertensive if their average of at least two blood pressure measurements met either a systolic threshold of 140 mmHg or higher, a diastolic threshold of 90 mmHg or higher, or if they were receiving antihypertensive medication. Individuals were considered to have dyslipidemia (DL) when fasting total cholesterol levels reached or exceeded 240 mg/dL, or if lipid-lowering drugs were in use. Diabetes mellitus (DM) was identified based on any of the following: random plasma glucose levels above 200 mg/dL, fasting plasma glucose levels of 126 mg/dL or higher, glycated hemoglobin (HbA1c) values of at least 6.5%, or ongoing treatment with antidiabetic medication.
Covariates
Baseline characteristics, including age, sex, race/ethnicity, body mass index (BMI), smoking status, alcohol consumption, sleep duration and comorbidities (e.g., HTN, DM, and DL) were adjusted for in the analysis.
Statistical Analysis
sUA levels were divided into quartiles (Q1–Q4) based on their distribution. Comparisons of baseline characteristics across sUA quartiles were performed using 1-way analysis of variance for continuous variables and the chi-square test for categorical variables. Kaplan-Meier survival analysis and Cox proportional hazards models were used to examine the association between nocturia and all-cause and cardiovascular mortality, adjusting for potential confounders. Hazard ratios (HRs) and 95% confidence intervals (CIs) were reported. For continuous mediators such as sUA, restricted cubic spline (RCS) models were applied to capture potential nonlinear relationships. The mediation effects of sUA in the pathway between nocturia and mortality were assessed using the “Regmedint” package. Estimates of direct, indirect, and total effects (TEs) were obtained. All statistical analyses were performed using R ver. 4.3.1 (R Foundation for Statistical Computing, Austria). Two-sided P-values less than 0.05 were considered statistically significant.
Ethical Considerations
This study was conducted in accordance with the principles outlined in the Declaration of Helsinki. The dataset is publicly available and fully de-identified, and its use is approved by the Ethics Review Board (Protocols #2005–06 and #2011–17). Therefore, additional Institutional Review Board approval was not required for this analysis.
RESULTS
Baseline Characteristics
Table 1 presents the baseline characteristics of participants stratified by sUA quartiles. Individuals in higher sUA quartiles were older (mean age: 61.6 years in Q4 vs. 57.2 years in Q1) and demonstrated a higher prevalence of nocturia (≥2 episodes/night: 41.3% in Q4 vs. 35.4% in Q1). All-cause and cardiovascular mortality rates also increased across quartiles (all-cause mortality: 24.3% in Q4 vs. 12.9% in Q1; cardiovascular mortality: 7.2% vs. 2.9%). Participants with higher sUA levels exhibited a greater prevalence of HTN and DM, as well as higher BMI, waist circumference, systolic blood pressure, triglyceride levels, and serum creatinine. Conversely, they had lower HDL cholesterol and estimated glomerular filtration rate compared with those in lower quartiles. In contrast, participants in lower sUA quartiles were more likely to be female, have lower BMI and waist circumference, and report a lower burden of nocturia episodes. No significant differences were observed across quartiles in sleep duration or fasting glucose levels.
The Relationship Between Nocturia and Mortality
Kaplan-Meier survival analysis demonstrated a significant difference in mortality risk across sUA quartiles. For all-cause mortality, participants in the highest quartile (Q4) showed the lowest survival probability compared to the lower quartiles (Q1–Q3) (Fig. 1A). Similarly, cardiovascular mortality exhibited a graded increase with higher sUA quartiles, with Q4 dem-onstrating the steepest decline in survival (Fig. 1B). Cox proportional hazards regression confirmed these findings. As shown in Table 2, using Q4 as the reference category, Q1–Q3 showed significantly different risks of all-cause and cardiovascular mortality across all adjustment models. In the fully adjusted model (model 3), the HRs (95% CI) for all-cause mortality were 1.327 (1.164–1.513) for Q1, 1.227 (1.091–1.380) for Q2, and 1.256 (1.120–1.408) for Q3. For cardiovascular mortality, the corresponding HRs were 1.499 (1.157–1.942), 1.257 (1.006– 1.571), and 1.411 (1.131–1.761), respectively.
RCS regression demonstrated a significant nonlinear J-shaped association between sUA levels and mortality. For all-cause mortality, risk increased markedly at both low and high sUA concentrations, with the lowest risk observed around the midrange (χ²=109.91, P<0.001) (Fig. 2A). Cardiovascular mortality exhibited a comparable nonlinear association with a nadir in the intermediate range of sUA (χ²=64.01, P<0.001) (Fig. 2B).
Mediation Analyses
Mediation analyses revealed that sUA partially mediated the association between nocturia and all-cause mortality (Fig. 3A). The TE of nocturia on all-cause mortality was significant (HR, 1.984; 95% CI, 1.803–2.182), as were the total natural indirect effect (TNIE) (HR, 1.031; 95% CI, 1.018–1.044) and the total natural direct effect (TNDE) (HR, 1.909; 95% CI, 1.736–2.101). Similarly, for cardiovascular mortality (Fig. 3B), the TE of nocturia was significant (HR, 1.915; 95% CI, 1.617–2.267), with both the TNIE (HR, 1.031; 95% CI, 1.016–1.046) and TNDE (HR, 1.817; 95% CI, 1.534–2.153) demonstrating statistical significance, indicating a partial mediating role of sUA in this pathway.
DISCUSSION
In this nationally representative study, nocturia was independently associated with an increased risk of all-cause and cardio-vascular mortality, a finding consistent across subgroups defined by sex, age, and metabolic status. To our knowledge, this is the first study to demonstrate a significant positive association between nocturia and sUA, which appears to partially mediate the observed mortality risk. These findings reinforce previous evidence regarding the adverse health implications of nocturia and emphasize its clinical relevance [5,15,16]. In addition, the slightly elevated mortality risk at low sUA levels may reflect frailty [17], malnutrition [18], or sarcopenia [19], conditions that are strongly linked to cardiovascular mortality. Thus, while the risk increase at low sUA appeared modest, both low and high sUA concentrations may indicate vulnerable metabolic states linked to higher mortality risk.
At the physiological level, uric acid is an antioxidant that scavenges superoxide, hydroxyl radicals, and singlet oxygen. However, at higher levels, uric acid can promote oxidative and renal damage, especially under metabolically morbid conditions. Konta et al. [9] reported that sUA levels were correlated with all-cause and cardiovascular mortality. This association was J-shaped with sUA at baseline in both men and women. Emerging evidence suggests that reducing uric acid levels may have a beneficial effect on LUTS and possibly nocturia, although direct proof for nocturia is limited, especially in women. Bang et al. [10] reported that gout (hyperuricemia and crystal arthritis) was associated with benign prostate hyperplasia (BPH) (treated ≥2 times) in the Korean population. Kukko et al. [11] reported that allopurinol use was negatively correlated with the risk of BPH diagnosis, surgery and related-medication use (5α-reductase inhibitors). In animal studies, urate-lowering medication inhibited prostatic inflammation and protected against ischemic injury of the bladder [12,20]. However, in a clinical longitudinal study, Hwang et al. [13] reported that higher sUA was associated with lower LUTS incidence in middle-aged men. This apparent discrepancy may reflect differences in study populations, baseline metabolic profiles, and the dual role of uric acid as both an antioxidant and a pro-oxidant depending on concentration and metabolic context. However, these results cannot be generalized to older, metabolically unhealthy individuals and women.
There are multiple mechanisms through which sUA may mediate the nocturia-mortality relationship. Circadian dysregulation caused by nocturia impairs insulin sensitivity, increases chronic inflammation, and promotes oxidative stress, all of which increase the risk of cardiovascular and renal diseases, which promotes hyperuricemia and further causes mortality. Conversely, elevated sUA promotes cardiovascular events by regulating molecular signals like NLRP3 (NOD-like receptor family, pyrin domain containing 3) inflammasome, triggering chronic systemic inflammation, which exacerbates oxidative stress, and endothelial dysfunction [21]. Although the mediation analyses demonstrated statistically significant indirect effects via sUA and metabolic syndrome (MetS), the magnitudes of these effects were modest. Therefore, these results should be interpreted with caution, and the clinical significance of these pathways remains limited. Further longitudinal and mechanistic studies are warranted to clarify whether sUA and MetS play substantial roles in the nocturia-mortality relationship. Another common comorbidity of nocturia is obstructive sleep apnea syndrome (OSAS). OSAS increases intermittent hypoxia, and the sleep fragmentation due to disordered breathing causes arousal, increases sympathetic tone, and causes nocturia [22]. Also, the obstruction of airflow during sleep decreases intrathoracic pressure and consequently increases venous return, dilates the right atrium, secretes atrial natriuretic peptide, and stimulates the excretion of sodium and water by the kidneys, particularly in the distal tubules and collecting ducts [23]. In OSAS patients, degradation of adenosine triphosphate increases sUA levels, which promotes cardiovascular and metabolic dysfunction [24-26].
Although the mediation analysis indicated that sUA partly mediated the relationship between nocturia and mortality, the effect size was modest. Therefore, this finding should be interpreted with caution, and its clinical significance appears limited.
There are a few limitations in our study. First, although a selfreported, simplified quantitative questionnaire for nocturia may facilitate data collection, it should not be considered a substitute for validated assessment tools such as the Nocturia Quality of Life questionnaire, voiding diaries, or urodynamic evaluations. Second, this dataset only contains nocturia status and metabolic changes at the initial visit, but the changes during the follow-up period were not accounted for in this study. Third, we used statistical methods to control for confounders, but the confounding effect on mediation analysis cannot be fully excluded. These limitations require further longitudinal prospective studies to verify the relationship.
In conclusion, this study identified nocturia as an independent predictor of all-cause mortality, even after adjusting for major metabolic risk factors. The observed mediation effect of sUA suggests that uric acid may contribute to the pathway linking nocturia to increased mortality risk. These findings highlight the importance of comprehensive management strategies that address both nocturia and underlying metabolic abnormalities. Future studies are warranted to determine whether targeted interventions, including metabolic optimization and uratelowering therapies, can reduce nocturia-associated mortality.
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