Conclusion: Adherence to a combination of healthy lifestyle behaviors was significantly associated with a lower risk of OAB. These findings emphasize the potential role of lifestyle-based interventions in OAB prevention and management. Given the rising prevalence of OAB, particularly in aging populations, incorporating lifestyle modifications into clinical and public health strategies may offer an effective, non-pharmacological approach to mitigating risk of OAB. Further longitudinal studies are warranted to establish causality and elucidate the underlying biological mechanisms.

Results: Among the 20,195 participants, 3,901 (14.58%) were identified as having OAB. A higher HLS was inversely associated with risk of OAB in a dose–response manner. Compared with individuals having 0–1 healthy lifestyle factors, those with 4–5 factors had a 46% lower risk of OAB (adjusted OR: 0.54, 95% CI: 0.45–0.65). Each additional healthy lifestyle factor was associated with a 17% lower risk of OAB (OR: 0.83, 95% CI: 0.79–0.88). Sensitivity analyses confirmed the robustness of these associations. Among individual components, non-smoking, moderate alcohol intake, regular physical activity, a healthy diet, and optimal waist circumference were each independently associated with a lower risk of OAB.

Methods: This cross-sectional study utilized data from 20,195 non-pregnant adults aged 20–79 years in the National Health and Nutrition Examination Survey (NHANES) 2007–2020. A healthy lifestyle score was constructed based on five components: current non-smoking, low-to-moderate alcohol consumption, adequate physical activity, a healthy diet, and optimal waist circumference. OAB was defined using self-reported urinary urgency incontinence and nocturia symptoms. Weighted multivariable logistic regression models were employed to assess the association between the healthy lifestyle score and risk of OAB, adjusting for demographic, socioeconomic, and clinical covariates.

Objectives: The relationship between adherence to a combined healthy lifestyle and the risk of overactive bladder (OAB) remains unclear. This study aimed to investigate the association between a composite healthy lifestyle score and risk of OAB in a nationally representative sample of adults.

1 Introduction

Overactive bladder (OAB) is a prevalent and debilitating urological condition characterized by urgency, often accompanied by increased urinary frequency, nocturia, and urgency urinary incontinence (UUI) (1). OAB affects a substantial proportion of the global population, significantly impairing quality of life and contributing to psychological distress, including anxiety and depression (2, 3). The prevalence of OAB has been rising, particularly among older adults (4, 5). With the progressive aging of the global population, OAB presents increasing challenges to healthcare systems. In the United States, OAB has been shown to incur billions of dollars in healthcare expenditures annually, with per capita healthcare costs of OAB patients exceeding those of comparable individuals without OAB by more than 2.5 times (6, 7). However, its precise etiology remains incompletely understood, with emerging evidence suggesting that detrusor overactivity, autonomic nervous system dysfunction, metabolic syndrome, sex hormone deficiency and urinary microbiota may contribute to its pathogenesis (8).

Lifestyle modifications are widely recognized as a cornerstone in the prevention and management of various chronic diseases, including cardiovascular disease, diabetes, and cancer (9–11). However, the association between combined healthy lifestyle factors and the risk of OAB remains largely unexplored. Previous studies have predominantly examined individual lifestyle factors in relation to OAB. A significant association has been identified between both high body mass index (BMI) (12, 13) and increased waist circumference (14, 15)with a heightened risk of OAB. Similarly, smoking, alcohol consumption, physical activity, and dietary habits have also been investigated in relation to risk of OAB (16–21). However, behavioral factors are often interrelated, and individuals tend to adopt lifestyle patterns that encompass multiple factors (22). Therefore, lifestyle factors should be analyzed collectively to better assess their overall health impact (23). Despite this, existing studies have not systematically evaluated the cumulative effect of multiple healthy lifestyle behaviors, leaving a critical gap in understanding their combined influence on risk of OAB.

In light of this, the present study explores the relationship between a composite healthy lifestyle score, which incorporates smoking status, alcohol consumption, physical activity, dietary habits, and body weight, and the risk of OAB using data from the National Health and Nutrition Examination Survey (NHANES). By analyzing a nationally representative dataset, we aim to provide insights into the potential protective role of adhering to a combination of healthy lifestyle behaviors in mitigating risk of OAB, contributing to a better understanding of preventive strategies for this prevalent condition.

2 Methods

2.1 Study population

Nation Health and Nutrition Examination Survey (NHANES), a nationally representative program of surveys designed to assess the health and nutritional status of adults and children in US, examined approximately 5,000 non-institutional civilians each year. NHANES was approved by the National Center for Health Statistics (NCHS) Ethics Review Board and had obtained informed consents from participants. We selected 40,479 non-pregnant adults (aged 20- < 80 years) from NHANES 2007–2020 cycles for eligibility screening. A total of 22,035 adults were left after excluding 5,303 subjects without data on urinary urgency incontinence and nocturia and 13,141 subjects with missing lifestyle information. Moreover, 1,840 subjects with missing covariates were excluded. Missing numbers and percentages of covariates were shown in Supplementary Table S1. Finally, the current cross-sectional study comprised 20,195 non-pregnant adults, and the flow of eligibility screening was shown in Figure 1.

Figure 1

Figure 1. Flow of eligible participants selection. NHANES, National Health and Nutrition Examination Survey.

2.2 Construction of healthy lifestyle score

Healthy lifestyle score was constructed by summing the number of healthy lifestyle factors, including current nonsmoking, low-to-moderate alcohol drinking, adequate physical activity, healthy diet, and optimal waist circumference, according to the method by Zhang et al. (24). The healthy lifestyle score, whose higher values indicated healthier lifestyles, ranged from 0 to 5. Definitions of healthy levels of lifestyle factors were shown in Supplementary Table S2.

2.3 Definition of overactive bladder

As defined by the International Continence Society, urinary urgency incontinence and nocturia are the main features of overactive bladder (OAB), and their evaluation constitutes the assessment of OAB. Participants were asked three questions: “During the past 12 months, {have you/has SP} leaked or lost control of even a small amount of urine with an urge or pressure to urinate and {you/he/she} could not get to the toilet fast enough?,” “How frequently does this occur?,” and “During the past 30 days, how many times per night did {you/SP} most typically get up to urinate, from the time {you/s/he} went to bed at night until the time {you/he/she} got up in the morning?.” The scoring details were explained in Supplementary Table S3, and a score of three or above indicates OAB.

2.4 Assessment of covariates

Demographic, socioeconomic, lifestyle information was collected with a computer-assisted personal interview system by trained interviewers. Race/ethnicity was categorized as non-Hispanic White, non-Hispanic Black, Mexican American, and others. Marital status was categorized as married, single (widowed, divorced, separated, never married), and living with partner. Self-reported education attainment was grouped as under high school, high school, and above high school. Family poverty-income ratio (PIR), which was calculated by dividing family (or individual) income by the poverty guidelines specific to the survey year, was applied to measure income status. Blood pressure measurements were collected by examiners with mercury sphygmomanometers. Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥90 mmHg, physician-diagnosed hypertension, or currently taking prescribed medicine for hypertension. Diabetes was defined as fasting plasma glucose (FPG) ≥ 126 mg/dL, glycated hemoglobin A1c (HbA1c) ≥ 6.5%, oral glucose tolerance test (OGTT) two-hour glucose ≥ 200 mg/dL, self-reported physician-diagnosed diabetes, use of insulin or oral hypoglycemic medication.

2.5 Statistical methods

Taking unequal probability of selection and over sampling of certain subpopulations into account, we applied sampling weights, strata, and primary sampling units in analyses. Continuous variables were expressed with weighted means and standard errors (SEs), and categorical variables were expressed with numbers and weighted percentages. Means and proportions of population characteristics were compared with linear regression for continuous variables and logistic regression for categorical variables.

Weighted multivariable logistic regression model was used to examine the association of healthy lifestyle score with risk of OAB. In multivariable model 1, we adjusted for age (<50, ≥50 years), sex (male, female), and race/ethnicity (non-Hispanic White, others). In multivariable model 2, we further adjusted for marital status (married, others), family PIR (<3.5, ≥3.5), education attainment (above high school, high school and below), hypertension (yes, no), and diabetes (yes, no). We also calculated multivariable-adjusted OR with 95% CI for OAB associated with each additional healthy lifestyle factor. To examine whether the aforementioned confounders modified the association of healthy lifestyle score with risk of OAB, we performed stratified and multiplicative interaction analyses. To examine the contributions of different lifestyle factors, we first assessed the associations of five lifestyle factors with OAB, with all lifestyle factors mutually adjusted for. Then, we reconstructed new healthy lifestyle scores by removing one lifestyle factor each time from the score and adjusted the removed factor in the models.

The following sensitivity analyses were conducted to evaluate the robustness of our results. First, we redefined the healthy level of alcohol drinking as none or low-to-moderate alcohol drinking (≤28/14 g/day for men/women). Second, propensity score (PS) adjustment was applied to cope with observed confounding. Third, missing covariates were imputed under the missing at random assumption using multiple imputation (MI) with fully conditional specification (FCS) and random forest method. Fourth, we calculated an assessment of potential residual confounding with E-values, defined as the minimum strength of association on the OR scale that an unmeasured confounder would need to have with both the exposure and the outcome to fully explain away the observed exposure-outcome association, conditional on the measured covariates (25, 26). Finally, we constructed a weighted healthy lifestyle score to better reflect the effect of each healthy lifestyle factor on the outcome. A score of 1 was assigned to a healthy lifestyle, otherwise 0 was assigned. Weighted standardized healthy lifestyle score was calculated based on β coefficients of each lifestyle in the logistic regression model with all 5 lifestyle factors and adjustment for all covariates. Each binary lifestyle factor was multiplied by the β coefficients, summed, divided by the sum of the β coefficients, and multiplied by 5. The weighted score, ranging from 0 to 5, considers the magnitudes of the adjusted odds ratio (OR) for each lifestyle in each lifestyle pattern as a combination of 5 lifestyle factors. We then categorized the weighted lifestyle scores into quartiles to avoid extreme groups. Restricted cubic spline (RCS) with 3 knots was further plotted to visualize the dose–response relationship between weighted healthy lifestyle score and OAB.

3 Results

3.1 Population characteristics

This cross-sectional study comprised 20,195 non-pregnant US adults (weighted mean age 46.77 years and 50.66% male), of which 3,901 (14.58%) OAB cases were ascertained (Table 1). The prevalence of current nonsmoking, low-to-moderate alcohol drinking, adequate physical activity, healthy diet, and optimal waist circumference were 79.33, 74.57, 40.49, 41.02, and 22.94%, respectively (Table 1). Population characteristics across healthy lifestyle scores were displayed in Supplementary Table S4. Participants with more healthy lifestyle factors were more likely to be male and younger, non-Hispanic White, married, well-educated, had better income status, and had higher HEI-2015 score and lower values of BMI and waist circumference (all p < 0.001) (Supplementary Table S4). Moreover, those with fewer healthy lifestyle factors were more likely to be hypertensive and diabetic (all p < 0.001) (Supplementary Table S4).

Table 1

Table 1. Characteristics of study participants.

3.2 Association of healthy lifestyle score with OAB

In crude model, the OR for OAB comparing participants with 4–5 vs. 0–1 healthy lifestyle factors was 0.30 (95% CI: 0.26–0.36) (Table 2). After adjusting for all covariates, adults with 4–5 healthy lifestyle factors were confronted with 46% (OR: 0.54, 91% CI: 0.45–0.65) lower risk of OAB as compared with those with 0–1 healthy lifestyle factors (Table 2). In addition, each additional healthy lifestyle factor was associated with 17% (OR: 0.83, 95% CI: 0.79–0.88) decreased risk of RA (Table 2).

Table 2

Table 2. Association of healthy lifestyle score with risk of OAB.

3.3 Stratified, interaction, and sensitivity analyses

To examine whether the association between healthy lifestyle score and risk of OAB differed by age, sex, race/ethnicity, marital status, family PIR, education attainment, hypertension, and diabetes, we performed stratified and interaction analyses (Table 3). The inverse association between healthy lifestyle score and OAB persisted in all subgroups and seemed to be stronger in those aged <50 years and with family PIR < 3.5 (both P-interaction<0.05).

Table 3

Table 3. Association of healthy lifestyle score with OAB stratified by confounders.

As for individual lifestyle factors, current nonsmoking, low-to-moderate drinking, adequate physical activity, healthy diet, and optimal waist circumference were associated with OAB with ORs (95% CIs) of 0.82 (0.70–0.95), 0.81 (0.71–0.92), 0.89 (0.79–1.00), 0.87 (0.78–0.98), and 0.71 (0.61–0.83), respectively (Supplementary Table S5). The associations of four-component lifestyle scores with OAB were attenuated when current nonsmoking, low-to-moderate drinking, adequate physical activity, healthy diet, and optimal waist circumference were removed from the score, with ORs (95% CIs) comparing 3–4 vs. 0–1 healthy lifestyle factors being 0.67 (0.58–0.78), 0.69 (0.59–0.81), 0.62 (0.54–0.70), 0.62 (0.52–0.72), and 0.62 (0.53–0.72), respectively (Supplementary Table S6).

Several sensitivity analyses were performed to evaluate the robustness of our results (Supplementary Tables S7–S12). The inverse association persisted in sensitivity analysis redefining the healthy level of alcohol drinking (Supplementary Table S7), with OR (95% CI) for OAB associated with each additional healthy lifestyle factor being 0.85 (0.81–0.90). Applying PS adjustment to cope with observed confounders, the OR for OAB comparing participants with 4–5 vs. 0–1 healthy lifestyle factors was 0.53 (95% CI: 0.45–0.63) (Supplementary Table S8). Additionally, the observed significant inverse association of healthy lifestyle score with OAB was not negated by inputting missing covariates with MI (Supplementary Table S9). The E-value was 3.11 (Supplementary Table S10), suggesting that it would take very strong confounding to negate the inverse association observed in our study. Finally, a weighted healthy lifestyle score was constructed to better reflect the effect of each healthy lifestyle factor on the outcome. As shown in Supplementary Table S11, optimal waist circumference contributed most to the weighted healthy lifestyle score (weighted β = 0.34), followed by low-to-moderate drinking (weighted β = 0.21),current nonsmoking (weighted β = 0.20), healthy diet (weighted β = 0.14), and adequate physical activity (weighted β = 0.12). After adjusting for all covariates, adults with the highest weighted healthy lifestyle score quartile were confronted with 50% (OR: 0.50, 95% CI: 0.41–0.60) lower risk of OAB as compared with those with the lowest weighted healthy lifestyle score quartile (Supplementary Table S12). Inverse linear dose–response relationship between weighted healthy lifestyle score and OAB was depicted in the RCS (P-overall<0.001, P-nonlinearity = 0.234) (Figure 2).

Figure 2

Figure 2. Association of weighted healthy lifestyle score with risk of OAB. Line represents multivariable-adjusted OR, and shaded area represents 95% CI. Models were adjusted for age (<50, ≥50 years), sex (male, female), race/ethnicity (non-Hispanic White, others), marital status (married, others), family poverty-income ratio (<3.5, ≥3.5), education attainment (above high school, high school and below), hypertension (yes, no), and diabetes (yes, no). CI, confidence interval; OAB, overactive bladder; OR, odds ratio.

4 Discussion

Previous research has primarily focused on the individual effects of lifestyle factors such as smoking, physical activity, diet, and obesity on overactive bladder (OAB) risk. Our study adds to this literature by examining the combined influence of multiple healthy lifestyle behaviors, demonstrating a dose-dependent inverse relationship between adherence to a composite healthy lifestyle score and OAB risk. These findings underscore the potential benefits of a holistic lifestyle approach, which aligns with evidence from other chronic diseases where combined lifestyle modifications have shown superior preventive effects compared to individual factors alone (27–30).

In this large-scale cross-sectional study using data from NHANES, we identified a strong inverse association between adherence to a combined healthy lifestyle (CHL) score and the risk of OAB. Individuals adhering to ≥4 healthy lifestyle factors exhibited a 46% lower risk of OAB compared to those with ≤1 factor, and each additional healthy lifestyle factor conferred a 17% risk reduction. These findings support the role of modifiable behavioral factors in OAB prevention and management.

Tobacco smoking has long been recognized as a significant risk factor for bladder dysfunction and OAB. In this study, current smoking was associated with a higher risk of OAB. The mechanisms through which smoking contributes to OAB are multifactorial, including neurogenic stimulation (mediated by nicotine’s modulation of the sympathetic nervous system) and direct urothelial irritation (31). Additionally, smoking-induced atherosclerosis and vascular injury may impair bladder perfusion, exacerbating detrusor dysfunction, while smoking-related reductions in testosterone levels have also been suggested as potential contributing factors. (32–34). Given these effects, smoking cessation should be prioritized as an essential component of OAB prevention and management.

The relationship between alcohol consumption and OAB remains complex, with some studies reporting a positive correlation between excessive alcohol consumption and increased urgency or frequency of urination (19, 35), while others report no significant association (20, 36, 37). In our study, individuals who consume alcohol within healthy limits were found to have a lower risk of OAB compared to those who exceed these limits. This suggests that moderate alcohol intake may not significantly contribute to the development of OAB and may even have some cardiovascular protective effects. Although the precise effects of alcohol on bladder tissue remain unclear, urothelial cells are particularly vulnerable to damage due to their direct exposure to alcohol and its metabolites (38). Furthermore, excessive alcohol consumption may increase the risk of bladder irritation, urgency, and frequency, possibly due to its pro-inflammatory effects and the influence of alcohol on the nervous system (39).

Only a few studies have examined the relationship between regular physical activity and OAB, with some suggesting that physical activity may have a beneficial effect on OAB (21, 40). However, the precise mechanisms underlying this relationship remain unclear. In contrast, pelvic floor muscle training has been consistently shown to benefit OAB and is recommended as part of treatment strategies (41–43). Our study found that adherence to the recommended levels of physical activity was associated with a significantly lower risk of OAB. We propose that regular physical activity may improve bladder control by increasing bladder blood flow, enhancing metabolic function, and reducing systemic inflammation, which is known to play a role in many chronic conditions, including OAB (44, 45). Additionally, physical activity appears to help reduce obesity, a known risk factor for OAB. These findings reinforce the importance of exercise as part of a comprehensive OAB management plan, especially considering its benefits in reducing obesity and enhancing pelvic floor strength.

Diet plays an important role in the pathogenesis and symptom modulation of overactive bladder (OAB). A healthy dietary pattern, such as that reflected by a higher Healthy Eating Index-2015 (HEI-2015) score, has been associated with reduced systemic inflammation, improved metabolic health, and better bladder function (46). In our study, participants in the top two quintiles of HEI-2015 score showed significantly lower odds of having OAB, underscoring the potential protective association of high-quality diets. While our analysis did not isolate the effects of individual components, these adequacy components are generally considered beneficial for bladder and metabolic health. In contrast, dietary patterns characterized by low fiber intake and high consumption of processed foods, which are typically reflected by lower HEI-2015 scores, may contribute to adverse physiological processes such as elevated intra-abdominal pressure, chronic systemic inflammation, and alterations in gut microbiota composition, all of which have been potentially implicated in the pathophysiology and symptom exacerbation of OAB (18). Although current evidence does not identify specific HEI-2015 components as causally linked to OAB, our findings support the inclusion of dietary quality assessment in OAB-related public health strategies. Future prospective studies are warranted to clarify the contribution of individual dietary components and validate their potential role in targeted nutritional interventions.

Waist circumference (WC), as an indicator of visceral fat accumulation (47, 48), was strongly associated with risk of OAB in our study. Increased WC correlates with greater abdominal and bladder pressure, which can lead to chronic bladder irritation, detrusor overactivity, and increased urgency symptoms (14). These results underscore the importance of weight management through physical activity and dietary modifications to reduce risk of OAB. Visceral fat, particularly around the abdominal area, is known to exacerbate OAB symptoms through its inflammatory effects and by increasing intra-abdominal pressure, which puts additional stress on the bladder and detrusor muscles (49, 50). Individuals with abdominal obesity may particularly benefit from interventions aimed at reducing visceral fat and improving metabolic health.

We observed significant interactions between age and poverty-income ratio (PIR) with respect to the association between healthy lifestyle adherence and the risk of OAB. Previous studies have indicated that the prevalence of OAB tends to increase with advancing age, potentially due to age-related changes in bladder function and neurodegenerative processes (4). In contrast, individuals with lower PIR have been linked to an increased prevalence of risk factors such as smoking, unhealthy diet, and greater exposure to occupational or environmental stressors, which may elevate OAB susceptibility (51). These observations highlight the potential importance of developing targeted preventive and management strategies for specific subgroups, such as younger individuals and those from lower-income backgrounds.

In conclusion, adherence to a combined healthy lifestyle—incorporating tobacco smoking cessation, moderate alcohol consumption, regular physical activity, a healthy diet, and optimal waist circumference—is associated with a lower risk of OAB. These findings support the importance of modifiable lifestyle factors in OAB prevention. Promoting healthy lifestyle habits, particularly in aging populations, could significantly reduce OAB’s burden on individuals and healthcare systems. Furthermore, for individuals with refractory OAB, lifestyle interventions may offer better long-term outcomes than traditional pharmacological treatments. Future research should focus on longitudinal studies to confirm causal relationships between healthy lifestyles and OAB, and explore the mechanisms through which these interventions impact bladder function.

This study has several key strengths. First, utilizing data from the National Health and Nutrition Examination Survey (NHANES), a large, nationally representative sample, enhances the generalizability of the findings to the broader U. S. adult population. Second, instead of examining individual lifestyle factors separately, this study employed a combined healthy lifestyle approach, allowing for a more comprehensive assessment of how multiple health behaviors collectively influence risk of OAB. Health behaviors are multifaceted and encompass multiple dimensions; therefore, adopting a combined healthy lifestyle pattern analysis provides a more holistic evaluation of their cumulative impact compared to analyzing single risk factors in isolation. In this study, the association between combined healthy lifestyles and reduced risk of OAB was stronger than that observed for individual lifestyle factors, reinforcing the importance of assessing lifestyle patterns as a whole in risk assessment. Third, we applied rigorous statistical controls for key demographic and clinical variables, minimizing potential confounding and strengthening the internal validity of our results. Consistent findings across different cohorts with diverse characteristics and subgroups further consolidate the generalizability of our findings, ensuring their applicability to a broad population.

It is important to note that the cut-offs used to define healthy lifestyle factors in our study—including thresholds for alcohol consumption and waist circumference—are primarily derived from general health guidelines such as those from the WHO and other authoritative bodies. While these cut-offs have been widely applied and are supported by evidence in the context of overall health and metabolic disease prevention, their specific relevance to bladder health and OAB remains less well-defined. The precise thresholds that optimally relate to bladder outcomes require further investigation. Future studies that specifically examine the appropriateness of these cut-offs for OAB and related urinary conditions would help refine prevention strategies and clinical recommendations.

Despite its strengths, this study has several limitations. First, its cross-sectional design limits the ability to establish causal relationships between combined healthy lifestyle factors and OAB risk. Although statistically significant inverse associations were observed, reverse causality cannot be excluded, as individuals with OAB symptoms may be less likely to engage in healthy lifestyle behaviors. Longitudinal or interventional studies are needed to confirm the directionality of these associations. Second, lifestyle factors like smoking, alcohol consumption, physical activity, and diet were self-reported, which may introduce recall bias and inaccuracies. Third, OAB diagnosis was based on self-reported symptoms rather than objective clinical evaluations, potentially leading to misclassification or overestimation of OAB prevalence. The absence of data on OAB severity and specific subtypes further limits our understanding of the condition. Future research integrating clinical evaluations or linking with medical records could improve diagnostic accuracy and provide a more nuanced understanding of OAB. Additionally, while key confounders were controlled for, there may still be unmeasured residual confounding from factors such as genetics, mental health, medications, comorbidities, and environmental exposures. Future studies with more comprehensive assessments of these variables could clarify their impact. Moreover, the results from complete case analyses may be biased due to missing data not being completely at random (MCAR). Lastly, we did not adjust for multiple testing in subgroup analyses, so these results should be considered exploratory. Finally, the composite healthy lifestyle score used in this study aggregates various factors, which may obscure the differential effects of each component. While NHANES data are representative of the U.S. adult population, these results may not be directly applicable to other populations with different cultural or environmental factors.

This study suggests that lifestyle-based interventions targeting smoking cessation, moderate alcohol consumption, physical activity, balanced diet, and optimal waist circumference could reduce OAB risk. Public health strategies should raise awareness about the importance of these behaviors and promote programs for physical activity, dietary improvements, and weight management. Clinically, healthcare professionals might incorporate lifestyle counseling into care, providing personalized recommendations for individuals at higher OAB risk. However, challenges in implementation may arise from varying access to healthcare, socioeconomic barriers, and patient adherence. Future research should evaluate the feasibility, effectiveness, and cost-effectiveness of these interventions across diverse populations to better understand their potential in reducing the healthcare burden of OAB.

5 Conclusion

In conclusion, our study demonstrates that adherence to a combined healthy lifestyle, which includes tobacco smoking cessation, moderate alcohol consumption, regular physical activity, a healthy diet, and the maintenance of an optimal waist circumference, is associated with a lower risk of OAB. These findings emphasize the role of modifiable lifestyle factors in OAB prevention and management.

Future research should focus on confirming the causal relationships between combined healthy lifestyle factors and OAB through longitudinal studies, while also investigating the optimal combination and intensity of lifestyle modifications. Further exploration of the underlying biological mechanisms, including inflammation, oxidative stress, and the gut-bladder axis, is essential to better understand their potential roles in OAB pathophysiology. Additionally, evaluating the feasibility and effectiveness of lifestyle interventions through clinical trials will provide valuable insights into their practical applications and integration into multidisciplinary care pathways, which could help inform more sustainable and precision-oriented approaches to OAB management.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author/s.

Ethics statement

Ethical approval was not required for the studies involving humans because Ethical review and approval were waived for this study due to the use of publicly available, anonymized data from the NHANES database, which does not involve human or animal experimentation. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required from the participants or the participants’ legal guardians/next of kin in accordance with the national legislation and institutional requirements because Ethical review and approval were waived for this study due to the use of publicly available, anonymized data from the NHANES database, which does not involve human or animal experimentation.

Author contributions

TL: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. JH: Conceptualization, Formal analysis, Methodology, Writing – original draft. BX: Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft. JL: Conceptualization, Resources, Supervision, Validation, Visualization, Writing – review & editing. XL: Conceptualization, Data curation, Resources, Software, Supervision, Validation, Visualization, Writing – review & editing.

Funding

The author(s) declare that no financial support was received for the research and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that no Gen AI was used in the creation of this manuscript.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnut.2025.1603078/full#supplementary-material

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Conclusion: The findings indicate a significant positive association between OAB and suicidal ideation in US adults. These findings underscore the necessity of integrating urological and mental health care to enhance suicide prevention strategies.

Results: Among the 28,085 participants, 3.30% reported suicidal ideation, and 20.39% were identified with OAB. Individuals with suicidal ideation had a significantly higher prevalence of OAB compared to those without suicidal ideation. After adjusting for covariates, each point increase in OABSS was associated with a 15% higher likelihood of suicidal ideation (OR=1.15, 95% CI: 1.10-1.20). Participants with OAB had a 47% increased likelihood of suicidal ideation compared to those without OAB (OR=1.47, 95% CI: 1.26-1.72). Subgroup analysis proved the robustness of the results of this study.

Methods: This population-based cross-sectional study utilized data from six consecutive NHANES datasets (2007-2018). Suicidal ideation was assessed using the ninth item of the Patient Health Questionnaire-9 (PHQ-9), and OAB was identified through a simplified Overactive Bladder Symptom Score (OABSS). Multivariate logistic regression models, Restricted Cubic Splines, and subgroup analyses were used to analyze. The association between OAB and suicidal ideation, adjusting for potential confounders.

Background: Suicidal ideation, a critical public health issue, is notably associated with mental health disorders. Overactive bladder (OAB), a prevalent urological disorder, significantly impacts patients’ quality of life and is associated with mental health problems such as anxiety and depression. This study investigates the association between OAB and suicidal ideation in US adults.

1 Background

Suicide is death due to purposeful self-injury, and its incidence varies by factors such as gender and age (1). Globally, more than 700,000 people die by suicide each year. In the United States, more than 16 out of every 100,000 people die by suicide annually (2, 3). These numbers may be underestimated due to incomplete registration of deaths and inaccurate statistics (4). Suicide is not only a personal and family tragedy but also places a heavy burden on community and public health resources (5).

Suicidal ideation, the generation of thoughts about ending one’s life or committing suicide, is a precursor to suicide (6). Studies have shown that there is a strong correlation between suicide and suicidal ideation and that individuals with suicidal ideation face a significantly higher risk of suicide (6, 7). Of those with suicidal ideation, 60% will attempt suicide within a year (7). Suicidal ideation among young Americans increased significantly during the COVID-19 epidemic (8). Therefore, it is critical to explore risk factors for suicidal ideation clinically. One of the primary goals of suicide prevention is to identify at-risk populations (9). Suicidal thoughts are substantially common in individuals in general when mental health issues are present (10). Notably, feelings of sadness and anxiety are among the mental health conditions that overactive bladder illness sufferers are more prone to experience (11, 12). However, it is unclear whether overactive bladder disorder is associated with suicidal ideation. Understanding this relationship is important for effective suicide prevention and intervention.

Overactive bladder (OAB) is a urological disorder characterized by urinary urgency, accompanied by urinary frequency, nocturia, and sometimes urge incontinence, but without pathologic changes such as urinary tract infections (13). The prevalence of OAB is closely related to aging, with a rate exceeding 16% among adults in the United States (14). This disease seriously affects the quality of life of patients and adversely impacts mental health and sleep (15, 16). In addition, OAB imposes a financial burden on patients. As the population ages, this disease also puts increasing pressure on public health (17).

Research has indicated a strong correlation between OAB and interpersonal and psychological aspects. Various causes may trigger OAB and lead to psychological problems, which in turn exacerbate the symptoms of OAB, creating a vicious cycle (18, 19). In the general population, mental health problems are significantly associated with suicidal ideation (10). Therefore, people with OAB may be at risk for mental health risks including suicide (20). However, current studies tend to be limited to women or certain specific populations, which may lead to gender and population bias in the findings, thus reducing their reliability. This is due to gender differences in the urinary system and the different pathophysiologic mechanisms of OAB (21, 22). Therefore, there is a need for a larger population-based study to validate the correlation between OAB and suicidal ideation and to fully detail the interactions between the two. This study was a population-based cross-sectional analysis of U.S. adults aged 20 years and older, based on data from the National Health and Nutrition Examination Survey (NHANES). The investigation of the relationship between OAB and suicidal thoughts was the aim of the study.

2 Materials and methods

2.1 Study population

The National Health and Nutrition Examination Survey (NHANES) is an ongoing project of the National Center for Health Statistics (NCHS) that provides a comprehensive assessment of the health and nutritional status of the U.S. population. NHANES employs a complex stratified sampling methodology to enhance the accuracy and reliability of its representative sample. NHANES collects extensive data on socioeconomic status, demographic characteristics, dietary habits, and health-related information. Trained personnel conduct the data collection to ensure consistency and precision. All NHANES participants sign a written informed consent form, and the survey protocol receives approval from the NCHS Research Ethics Review Board.

In the present study, we downloaded six consecutive datasets (2007-2008, 2009-2010, 2011-2012, 2013-2014, 2015-2016, and 2017-2018) for an accurate evaluation of the connection between OAB and suicidal ideation, consult the NHANES website. We pooled 12 years of data from NHANES. Of the total sample of 59,842 participants, a total of 31,757 were excluded, including data on age <20 years (n=25,072), missing data on OAB (n=146) and suicidal ideation (n=4,813), pregnancy status (n=318), missing data on education (n=24), marital status (n=13), BMI (n=291), smoking (n=17), hypertension (n=382), diabetes (n=530), stroke (n=38), and cardiovascular disease (n=113). The analysis comprised the remaining 28,085 adult US individuals (Figure 1).

Figure 1

Figure 1. Flowchart of the study population.

2.2 Definition of suicidal ideation

The ninth item of the Patient Health Questionnaire-9 (PHQ-9) assesses suicidal ideation in the Mental Health Depression Screening section of the survey (23). The PHQ-9 comprises nine items evaluating depressive symptoms experienced over the past two weeks. The ninth item specifically asks, “In the past two weeks, how often have you had thoughts of self-harm or thought it would be better to end your life?” Response options include “Not at all,” “A few days,” “More than half the days,” and “Almost every day.” For this analysis, responses of “Not at all” indicate no suicidal ideation, while all other responses indicate suicidal ideation (24, 25).

2.3 Definition of OAB

The International Continence Society (ICS) defines OAB as a syndrome characterized by urinary urgency in the absence of urinary tract infection or other pathology, often accompanied by urinary frequency, nocturia, and urge urinary incontinence (UUI). OAB diagnosis should be considered in patients presenting with UUI or nocturia, and assessed through specific questions regarding the frequency and urgency of urinary leakage. Nocturia burden was evaluated by asking participants how many times they typically got up to urinate at night over the past 30 days. The simplified OABSS was used to measure the severity of OAB, with a score of ≥3 indicating the presence of the disorder, as detailed in Supplementary Table S1 (26, 27).

2.4 Covariates

In this study, covariates included gender, age, race, education level, marital status, household poverty-to-income ratio (PIR), BMI, smoking status, alcohol use, diabetes, hypertension, cardiovascular disease (CVD), and stroke. Individuals in the survey who had smoked at least 100 cigarettes in their lifetime and were smoking at the time of the questionnaire were designated as smokers. Participants who drank at least 12 alcoholic beverages in any year were designated as alcohol drinkers (28, 29). Participants were considered to have diabetes if their physician told them they had diabetes or if their fasting blood glucose was ≥126 mg/dL.

2.5 Statistical analysis

All statistical analyses followed the data analysis guidelines provided by NHANES, using appropriate NHANES weights for complex multi-stage cluster sampling designs. The Kolmogorov-Smirnov test was used to check the assumption of normal distribution for each variable. Normally distributed continuous variables were expressed as mean and standard deviation (SD), while non-normally distributed variables were expressed as median and interquartile range (IQR). Categorical variables were expressed as frequency and percentage (%). The study population was categorized into two groups based on the presence or absence of suicidal ideation. The chi-square test, t-test, and Mann–Whitney U test were used to compare the distribution of baseline characteristics between groups.

We used weighted logistic regression to explore the correlation between OAB scores and suicidal ideation. We constructed three logistic regression models. Three statistical models were employed: Model 1 remained unadjusted, Model 2 was adjusted for age, gender, and race, and Model 3 incorporated additional adjustments for education level, marital status, BMI, PIR, smoking, alcohol consumption, diabetes, hypertension, cardiovascular disease, and stroke, along with the covariates in Model 2. We then tested for nonlinear associations between Overactive Bladder Symptom Score (OABSS) and suicidal ideation using restricted cubic spline (RCS) after adjusting for covariates. Finally, subgroup analyses and interaction tests were conducted on the potential confounders listed in the baseline table to explore potential changes in associations between subgroups. Statistical analyses were conducted using R (version 4.3.2), with the significance level set at P < 0.05.

3 Results

3.1 Basic characteristics of the study population

This research comprised 28,085 individuals in total. with 3.30% reporting suicidal ideation. Participants with suicidal ideation were more likely to have OAB (40.28%) and higher OABSS scores compared to those without suicidal ideation (19.71%). The suicidal ideation group was characterized by a higher prevalence of cohabitation with a spouse, high education level, lower PIR level, BMI ≥ 30, hypertension, diabetes, coronary heart disease, stroke, and depression, with significant differences between the groups (P 0.05). In the gender subgroup, there was a trend of increasing suicidal ideation in both males [OR = 2.94 (95% CI: 2.13, 4.05), p < 0.001] and females [OR = 2.39 (95% CI: 1.92, 2.98), p < 0.001]. There was a trend of increasing suicidal ideation in both the 20–50 age group [OR = 2.86 (95% CI: 2.17, 3.75), p 50 age group [OR = 2.24 (95% CI: 1.75, 2.88), p < 0.001] (Figure 3).

Figure 3

Figure 3. Subgroup analysis of the association between overactive bladder syndrome and suicidal ideation. Note 1: The above model adjusted for gender, age, race, education level, marital status, PIR, BMI, smoking status, alcohol drinking status, diabetes status, hypertension status, CVD, depression, and stroke. Note 2: In each case, the model is not adjusted for the stratification variable.

4 Discussion

Using NHANES data, the present research investigated the link between suicidal thoughts and overactive bladder (OAB), offering fresh perspectives on the connection between urologic conditions and psychological conditions. The findings indicated that in contrast to people without OAB, those with OAB had a greater incidence of suicidal thoughts, demonstrating the potential impact of OAB on mental health. The robustness of these findings highlights several key points. First, psychiatrists should focus on the impact of urinary symptoms on suicide risk to improve treatment adherence and effectiveness. A comprehensive approach that integrates both urological symptom management and psychological evaluation is essential when treating patients with OAB. Addressing mental health issues such as anxiety, depression, and suicidal ideation may improve treatment adherence, quality of life, and overall prognosis. Therefore, while routine psychological evaluation may not be necessary for all patients with OAB, it is advisable to consider mental health screening in individuals presenting with severe urinary symptoms, low treatment compliance, or signs of psychological distress.

Previous research has concentrated on the relationship between OAB and depression, frequently using samples from hospitals or particular groups of women (30, 31). These studies compared psychological conditions between two groups by dividing the population into case and control groups but were slightly less persuasive due to the limitations of the research methodology. Nonetheless, studies agree that OAB has a strong correlation with the development of depression (32). First, according to a study of a community-based population assessed using a depression scale, a significant correlation was found between depressive symptoms and OAB, suggesting that an elevated risk factor for incontinence in the urine was depressed symptoms (33). Second, Debra et al. demonstrated in their study that there is a significant association between OAB and the development of depressive symptoms (34). Third, one large population-based study found that the risk of developing depression increased as the severity of OAB increased (35). However, this study was conducted via a web-based survey and disregarded the significance of in-person interviews with doctors, and did not control for covariates. In contrast, the present study analyzed data for U.S. adults, effectively controlled for covariates, and improved the credibility and feasibility of the findings.

The relationship between overactive bladder (OAB) and mental health is likely bidirectional. On one hand, psychological distress may contribute to altered bladder function, and on the other, the burden of OAB symptoms may lead to mental health deterioration. Preclinical studies have shown that psychological stress may affect bladder contractility through pathways such as the Rho-kinase (ROCK) signaling cascade, leading to increased voiding frequency and detrusor overactivity. Stress-induced alterations in gut microbiota have also been hypothesized to influence bladder function. Additionally, anxiety and depression may contribute to heightened somatic sensitivity and lower perception thresholds, possibly exacerbating OAB symptoms (20, 36). Conversely, the social and emotional impact of OAB—such as embarrassment, sleep disturbances, reduced work productivity, and social withdrawal—may predispose individuals to depressive symptoms and suicidal ideation (19, 37, 38).

However, it is important to clarify that we do not advocate for psychology as the primary treatment for OAB or as a replacement for conventional urological interventions. OAB is primarily a bladder dysfunction, and treatment should remain focused on behavioral therapies, pharmacological interventions, and, when necessary, surgical options. However, mental health issues, particularly anxiety and depression, may exacerbate OAB symptoms and negatively impact treatment adherence and quality of life. Therefore, while the primary focus of OAB treatment should remain within the urological domain, we suggest that for individuals with significant emotional distress, poor treatment compliance, or reduced quality of life, considering integrated psychological support may improve overall health outcomes and treatment effectiveness.

5 Strengths and limitations

This study has several noteworthy strengths. First, it evaluated a large sample of 28,085 participants, each of whom provided comprehensive clinically informative data. The data collection underwent a rigorous quality assurance process to ensure its reliability. Second, the study conducted subgroup analyses based on common co-morbidities. Subgroup and sensitivity analyses were also carried out to strengthen the reliability of the findings. This thorough examination emphasizes how crucial it is for psychiatrists to concentrate on patients’ symptoms connected to the urinary system.

Although NHANES provides a large, nationally representative sample with standardized data collection procedures, it has several limitations that must be acknowledged. First, it is a cross-sectional survey, which limits the ability to infer temporal or causal relationships between OAB and suicidal ideation. Second, the assessment of both OAB and suicidal ideation is based on self-report questionnaires rather than clinical diagnosis, which may lead to misclassification or underreporting. Third, the data lack granularity on the duration, severity, or context of symptoms, which could influence interpretation. Fourth, although we defined OAB as an OABSS ≥3 in accordance with prior NHANES-based literature, this threshold may inadvertently include individuals whose urinary symptoms stem from other causes, such as nocturnal polyuria, sleep apnea, metabolic or behavioral factors, or anatomical abnormalities. Fifth, relying solely on an OABSS ≥3 cutoff to define OAB may lead to misclassification. Future studies should consider incorporating more nuanced symptom-based subtyping and physiological markers to improve the accuracy and clinical utility of OAB phenotyping. Sixth, while NHANES utilizes a multi-stage, stratified probability sampling method to ensure national representativeness, certain subpopulations (e.g., individuals with severe OAB or hospitalized patients) may not be adequately represented. This could limit the generalizability of findings to these specific groups. Additionally, the reliance on self-reported OAB symptoms may not fully capture the clinical complexity or underlying physiology of OAB, thus affecting the precision of the data in elucidating OAB’s impact. These limitations warrant caution when extrapolating our findings to clinical settings or guiding intervention strategies.

6 Conclusion

This study reveals a positive association between OAB and suicidal ideation in U.S. adults, emphasizing the need for an integrated clinical approach to address both urinary and mental health symptoms to enhance suicide prevention efforts.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.

Ethics statement

The studies involving humans were approved by The portions of this study involving human participants, human materials, or human data were conducted in accordance with the Declaration of Helsinki and were approved by the National Center for Health Statistics (NCHS) Ethics Review Board. The patients/participants provided their written informed consent to participate in this study. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions

HL: Conceptualization, Resources, Validation, Writing – original draft, Writing – review & editing. DH: Data curation, Visualization, Writing – original draft, Writing – review & editing. MJ: Formal Analysis, Writing – review & editing, Funding acquisition, Investigation. YZ: Methodology, Writing – review & editing. HH: Writing – review & editing, Project administration, Resources. YY: Software, Writing – original draft. HJ: Supervision, Writing – original draft, Writing – review & editing. JL: Formal Analysis, Funding acquisition, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare that no financial support was received for the research and/or publication of this article.

Acknowledgments

We would like to thank all participants in this study.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1483684/full#supplementary-material

Abbreviations

NHANES, National Health and Nutrition Examination Survey; NCHS, National Center for Health Statistics; PIR, income to poverty ratio; CVD, cardiovascular disease; BMI, body mass index; PHQ-9, Patient Health Questionnaire-9; OAB, Overactive bladder; OABSS, Overactive Bladder Symptom Score; UUI, urinary incontinence; SD, standard deviation; IQR, interquartile range; RCS, restricted cubic spline.

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This study innovatively examines the correlation between PA and OAB using a cross-sectional analysis. Our weighted multivariate logistic regression analysis shows that PA patterns are associated with OAB risk, even after accounting for all covariates. The RCS curve illustrates a nonlinear dose–effect relationship between total PA duration (minutes per week) and OAB. In summary, adults who engage in PA on weekends (weekend warriors) and those who maintain regular activity (regularly active) have a lower risk of OAB compared to inactive adults. While these effect sizes are small, they may hold public health relevance given the high prevalence of OAB (13.4% in European men and 14.6% in women) and the potential for PA to synergize with other lifestyle interventions. Notably, in the prediabetes subgroup, weekend warrior PA was associated with a 14% risk reduction (OR = 0.86) after full adjustment, highlighting potential amplified benefits in high-risk populations.

“Weekend warriors” refer to individuals who engage in physical activity predominantly on weekends, often in concentrated sessions to meet the weekly recommended PA duration. “Regularly active individuals” are those who spread their physical activity throughout the week, maintaining a consistent and regular exercise routine14.

PA and OAB are closely linked, with numerous studies exploring various facets of this relationship. Most of these studies have reported the protective role of PA. Chu et al.11 concentrated on the impact of OAB treatment on PA limitations in women, demonstrating potential improvements following therapy. Hakimi et al.19 investigated risk factors for OAB syndrome in menopausal women and their relationship to sexual function, also uncovering physical inactivity among those with OAB syndrome20. Chu et al.21 studied the short-term effect of fesoterodine on physical function related to fall risk in older women with OAB, emphasizing the significance of considering physical function in treatment plans. Senel et al.22 examined the impact of total knee arthroplasty on OAB symptoms in female patients and suggested that total knee arthroplasty may lead to symptomatic improvement post-surgery. Collectively, these studies contribute to our understanding of the relationship between PA and OAB, underscoring the importance of tailored treatment approaches for this condition. However, little is known about how the frequency of meeting the recommended weekly duration of PA and PA patterns influence OAB risk. To the best of our knowledge, our study is the first to investigate the association between weekly PA duration and PA patterns (e.g., weekend warriors and regularly active individuals) and OAB in American adults. Our results indicate that weekend warriors and regularly active adults have a reduced risk of OAB compared with inactive adults. This suggests that individuals with time constraints may still benefit from PA engagement, even if concentrated on weekends. Additionally, the RCS curve suggests a nonlinear relationship between total PA duration and OAB risk, with the lowest risk observed at ~ 915.41 min/week. While this pattern aligns with our hypothesis that excessive PA duration may not confer additional benefits, the modest effect sizes and observational design preclude definitive conclusions about the clinical utility of this threshold. Importantly, this exploratory analysis supports our rationale for investigating PA patterns (e.g., weekend warriors) rather than focusing solely on total duration. Further studies are needed to validate whether such a threshold exists and whether it reflects biological plausibility or confounding factors.

Several hypotheses have been proposed to highlight the beneficial effects of PA in alleviating OAB symptoms. Various studies have explored the relationship between obesity and OAB15,23,24. PA is considered a vital strategy for combating obesity. Leiria et al.25 examined the influence of insulin resistance on bladder function in the context of obesity-related OAB. They found that insulin relaxes the bladder through the activation of the PI3K/AKT/eNOS pathway in the mucosa, with impaired insulin action contributing to bladder dysfunction in obese individuals26. Research has demonstrated that PA has a significant impact on insulin levels and insulin sensitivity across diverse populations27,28. Studies indicate that oxidative stress can induce bladder hyperactivity and dysfunction, resulting in OAB symptoms29,30,31. PA may affect the occurrence and development of disease by affecting inflammation and oxidative stress32,33. Additionally, PA may improve OAB symptoms by affecting conditions associated with OAB, such as depression34,35.

Subgroup analysis and interaction analysis showed that the relationship between PA patterns and the risk of OAB remained consistent across most demographic characteristics, body mass index BMI levels, lifestyle habits, and health status. It is noteworthy that in the gender subgroup, we only found a negative correlation between physical activity patterns and OAB risk in women, but not in men. Given that OAB symptoms are most prevalent in women36, our findings are important in guiding people with OAB to improve their symptoms through exercise. Several factors may contribute to this gender difference, including physiological differences in urethral length and angle, hormonal influences, and gender-specific behaviors related to PA. These findings have important clinical implications, as they suggest that promoting PA among female patients may be associated with reduced OAB risk. However, it is important to note that our study was observational, and thus cannot establish causality. Further research, including randomized controlled trials, is needed to confirm these findings and explore the mechanisms underlying the gender-specific effects of PA on OAB risk. Our study found that PA significantly was associated with reduced OAB risk, with an interaction observed between this association and PIR. Despite the interaction, the inverse relationship between PA and OAB risk remained significant across all PIR subgroups. This interaction may reflect differences in access to physical activity resources or underlying OAB etiology across PIR levels. Future research should explore these potential mechanisms and develop interventions tailored to different economic strata to maximize the benefits of PA in reducing OAB risk.

Our research boasts numerous advantages. Firstly, we utilized a large sample from the NHANES database, enhancing the reliability and generalizability of our findings across diverse populations. Secondly, our study is the first to investigate the relationship between the duration and pattern of PA and the development of OAB. Thirdly, after adjusting for potential confounding factors, the results from various models and subgroup analyses demonstrated a strong correlation between PA and OAB. However, it is important to acknowledge some limitations of our study. As a cross-sectional analysis of retrospective NHANES data, it cannot establish causality. Reverse causation—where OAB symptoms (e.g., urinary incontinence) may reduce PA participation—is a critical concern. To address this, we stratified participants by OAB severity (mild: OABSS < 6; moderate-severe: OABSS ≥ 6) and found that the inverse association between weekend warrior PA and OAB risk persisted only in the mild subgroup, whereas no association was observed in moderate-severe cases. This divergence suggests that individuals with mild symptoms are less likely to limit PA, whereas those with severe symptoms may reduce PA due to symptom burden, thereby attenuating the observed relationship. Additionally, there may be unmeasured or residual confounding factors. Furthermore, all participants in the study were from the United States, which may limit the generalizability of our findings to other populations.

This study demonstrates an inverse association between LE8 score, a composite metric of cardiovascular health, and risk of OAB10. Higher LE8 scores were associated with progressively lower odds of OAB in a dose-response manner11. This relationship persisted in multivariate regression models adjusting for potential demographic and socioeconomic confounders, suggesting it is independent of these factors.

WQS regression further identified blood glucose, BMI, nicotine exposure, BP and sleep health as the key LE8 components contributing to its inverse link with OAB. Of these, blood glucose exhibited the strongest individual association, aligning with prior evidence that diabetes can result in bladder dysfunction6. Taken together, these findings indicate that improving LE8 metrics may confer protective effects against OAB susceptibility12. This highlights novel opportunities for lifestyle-based OAB prevention strategies by targeting optimization of cardiovascular health factors13.

Among the top LE8 metrics, many diabetic metabolites (e.g. monosodium urate, HMGB1, etc.) can trigger bladder inflammation and overactive bladder by activating NLRP3 inflammatory vesicles in the urine epithelium5,6. Excess weight predisposes to OAB potentially via direct pressure effects on the bladder and neuropathy associated with metabolic conditions14. Nicotine can elicit lower urinary tract symptoms (LUTS) through decreased bladder blood flow and uroepithelial hypoxia15,16, Optimal blood pressure control reduces risk of bladder ischemia and oxidative stress that can precipitate detrusor overactivity13. Finally, adequate sleep optimizes hormonal balance and neural pathways regulating urination, whereas sleep deprivation has been linked to overactivity of bladder afferent pathways17. Elucidating these mechanisms provides biological plausibility linking LE8 components to lower OAB susceptibility.

This study reveals an important link between cardiovascular health as measured by LE8 and susceptibility to overactive bladder syndrome18. The findings have significant public health implications in illuminating lifestyle optimization as a promising strategy for OAB prevention. Improving diet quality, increasing physical activity, achieving healthy weight status, and optimizing sleep, cholesterol, BP and glucose levels may confer collateral benefits for bladder health14. Population-level interventions targeting LE8 metrics could potentially help curb the rising tide of OAB and related healthcare burden.

On an individual patient level, the results provide a rationale for clinicians to consider LE8 status in OAB risk assessment and counsel patients on lifestyle changes for better bladder control12. This represents a shift from compartmentalized care focusing only on the bladder, towards whole-person preventive health19. Realizing such integrated care models will require cross-disciplinary collaboration between urologists, primary care providers, and other specialists20.

Ultimately, research on LE8 scores helps move the field towards prevention-oriented management21. Further studies elucidating lifestyle, behavioral and cardiovascular factors influencing OAB susceptibility will be instrumental in this paradigm shift22.

This study has several innovative aspects advancing our understanding of modifiable OAB risk factors. First, it represents the first analysis linking the novel LE8 cardiovascular health score, representing a constellation of lifestyle, clinical and biological factors, to OAB susceptibility23. This moves beyond conventional risk factors to a more integrated metric encompassing overall wellbeing. Second, the use of robust statistical techniques including RCS and WQS regression provides rigorous delineation of the relationship between LE8 and OAB. The dose-response curve and identification of key LE8 drivers are significant methodological strengths.Third, the dissection of individual contributions of LE8 components is highly innovative, revealing glycemic control as the most impactful element5. This granular analysis of a composite risk metric is novel in the OAB literature and generates actionable insights for targeted preventive approaches12. Overall, the analytical strategies overcome limitations of previous observational research and provide high-quality evidence to motivate lifestyle optimization for maintaining bladder health19. This study exemplifies the type of innovative methodology required to advance our understanding of modifiable determinants of OAB21.

This study has certain limitations intrinsic to cross-sectional analyses that warrant acknowledgement. First, the cross-sectional design precludes causal inference, and reverse causation remains possible if OAB leads to decreased physical activity and subsequent worsening of LE8 metrics24. To establish temporality, large-scale longitudinal cohorts tracking LE8 status and onset of OAB over time are needed25. Second, self-reported data on OAB symptoms and LE8 components like diet and exercise carries potential for recall bias. However, NHANES uses well-validated instruments administered by trained staff to maximize accuracy26. Third, using a composite of multiple predictors to define a multifactorial syndrome like OAB can complicate result interpretation. Our goal was to explore how integrating diverse factors could provide a more comprehensive understanding of OAB. Additionally, we employed Weighted Quantile Sum (WQS) regression to assess the individual contributions of these factors, aiming to generate actionable insights for real-world application. We anticipate further research to refine and enhance its broader implementation. Finally, one-time assessment of LE8 may not fully reflect long-term exposure to poor cardiovascular health markers, which would be better captured through repeated measurements27.

This research motivates several fruitful avenues for future investigation. Longitudinal cohort studies tracking LE8 status over years or decades could elucidate whether optimal cardiovascular health metrics assessed earlier in life predict lower OAB incidence with aging. Large, multi-center trials are needed to determine if lifestyle interventions targeting LE8 improvement can reduce downstream OAB risk28. Studies in more diverse populations can evaluate generalizability of associations across racial/ethnic groups. Finally, research on pathologic mechanisms is warranted to explain observed epidemiological links between cardiovascular health metrics and OAB susceptibility21.

Conclusion: This study found a significant negative correlation between LC9 and OAB, with WWI acting as a partial mediator in this relationship. This study provides new insights for future research into the relationship between LC9 and OAB and the role of WWI as a mediator.

Results: A total of 25,319 participants were included in this study, among which 5,038 reported incidents of OAB. After adjusting for all variables using multivariable logistic regression, an increase of 10 units in LC9 was associated with a 28% reduction in the incidence of OAB (OR = 0.72, 95% CI: 0.69, 0.76), while an increase of one unit in WWI was associated with a 40% increase in the incidence of OAB (OR = 1.40, 95% CI: 1.29, 1.51). Consistent results were also observed when LC9 and WWI were categorized into quartiles, with a P for trend <0.001. The analysis using restricted cubic splines indicated a linear negative correlation between the incidence of OAB and LC9. Mediation analysis revealed that 13.89% of the relationship between LC9 and OAB was mediated by WWI ( p = 0.002).

Methods: Data for this study came from the National Health and Nutrition Examination Survey (NHANES). We used subgroup analyses, restricted cubic spline curves (RCS), and multivariate logistic regression to explore the relationship between LC9 and OAB. Additionally, mediation analysis was conducted to investigate the potential association between WWI levels and the relationship between LC9 and OAB.

Background: Research suggests a potential connection between cardiovascular health, obesity, and overactive bladder (OAB). However, the mechanisms by which obesity influences the relationship between cardiovascular health and OAB remain unclear. Life’s Crucial 9 (LC9) is a recently proposed method for assessing cardiovascular health, while the weight-adjusted waist index (WWI) is a novel and more accurate measure of obesity. This study investigates the relationship between LC9 and OAB and assesses whether WWI moderates this relationship.

Introduction

Overactive bladder (OAB) is defined as a storage symptom syndrome characterized by urgency, with or without urgency urinary incontinence (UUI), typically accompanied by daytime frequency and nocturia (1). OAB is prevalent in both men and women, with 12.8% of women and 10.8% of men reporting lower urinary tract symptoms (LUTS) that define OAB (2, 3). It is a chronic debilitating condition that reportedly affects the quality of life of over 30 million Americans. In the United States, underdiagnosis and inadequate treatment of OAB contribute to increased healthcare costs, with estimates indicating that direct and indirect medical costs could reach $86 billion annually by 2020 (4). The etiology of OAB is complex, and its pathophysiology remains unclear; however, chronic systemic inflammation and bladder urothelial inflammation, including certain inflammatory proteins and cytokines, may trigger the onset of OAB (5). Several theories regarding the pathophysiology of OAB exist, including the myogenic hypothesis, urothelial dysfunction hypothesis, neurogenic hypothesis, and detrusor underactivity; nevertheless, a comprehensive understanding of the underlying mechanisms is still lacking (1).

Recent data indicate a global rise in overweight and obesity, with approximately 30% of the world’s population classified as overweight (6). In North America, one-third of adults are considered obese, and studies have shown that abdominal obesity is a strong predictor of metabolic disorders and cardiovascular disease (CVD) (7). While body mass index (BMI) is the most widely used measure of obesity, it primarily focuses on overall obesity rather than abdominal fat. To address this gap, the weight-adjusted waist index (WWI) was introduced in 2018. WWI is a unique obesity index that can predict the risks of cardiometabolic diseases, cardiovascular events, and all-cause mortality, demonstrating superior predictive ability (8, 9). Research has shown that WWI positively correlates with total fat area (TFA), subcutaneous fat area, and visceral fat area. Given that visceral fat is considered more inflammatory compared to subcutaneous fat, the correlation between fat mass and the incidence of CVD is stronger (10, 11). Evidence suggests that higher visceral fat is a risk factor for OAB, and reducing visceral abdominal fat may help alleviate OAB symptoms (12, 13).

Metabolic syndrome (MetS) is defined by the World Health Organization (WHO) as a pathological condition characterized by abdominal obesity, insulin resistance, hypertension, and dyslipidemia (14). Research has shown a close association between MetS and cardiovascular disease, with each component of MetS acting as an independent risk factor for cardiovascular events (15). Several studies have indicated a strong relationship between OAB and Mets (16, 17). In 2010, the American Heart Association (AHA) introduced a framework for assessing cardiovascular health behaviors and factors, termed Life’s Simple 7 (LS7) (18), which has since been refined. Recently, the AHA updated this framework, expanding the assessment of cardiovascular health behaviors and factors to include mental health, culminating in the introduction of Life’s Essential 8 (LE8) in 2022. This was further developed into Life’s Crucial 9 (LC9), which encompasses sleep, smoking, physical activity, diet, BMI, non-HDL cholesterol, blood glucose, blood pressure, and mental health (19, 20). Given that research suggests weight loss in abdominal obesity may improve MetS (21), and that WWI and the associated LC9 indicators can be modified through lifestyle changes, there may be new avenues for managing and predicting OAB. Considering that excess abdominal fat may exacerbate OAB symptoms and that WWI and LC9 reflect both metabolic status and cardiovascular health, there is potential for a better understanding of the mechanisms underlying OAB.

Based on the above, this study hypothesizes that WWI mediates the relationship between the LC9 and OAB. Specifically, LC9, as a comprehensive assessment of cardiovascular health, may have protective effects against OAB by promoting healthier behaviors (e.g., dietary patterns, physical activity, weight management) and optimizing biomarkers (e.g., blood pressure, and blood glucose levels). However, obesity, as a key modifiable risk factor, may attenuate the potential benefits of LC9 on OAB. WWI, a novel measure of obesity, reflects both fat distribution and its impact on metabolic health. This study posits that WWI is not only independently associated with the risk of OAB but also serves as a mediator in the relationship between LC9 and OAB. Through its mediating role, WWI may partially explain how the health benefits of LC9 are influenced by the degree and distribution of obesity. By conducting mediation analysis, this study aims to validate this hypothesis, offering new insights into the potential pathways linking LC9, WWI, and OAB. These findings could provide valuable evidence for developing prevention and intervention strategies for OAB. Using NHANES data from 2005 to 2018, this study analyzes the relationship between LC9 and OAB while evaluating the role of WWI as a mediator, which may pave the way for new directions in diagnosing and managing OAB.

Methods

Study participants

This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES), conducted by the National Center for Health Statistics (NCHS), which aims to collect demographic data regarding the health and nutritional status of U.S. citizens. All NHANES study protocols were approved by the NCHS Research Ethics Review Board, and written informed consent was obtained from all survey participants. Our secondary analysis adhered to the STROBE guidelines for cross-sectional studies (22) and did not require additional approval from an institutional review board. For detailed information regarding NHANES methodology and ethical considerations, please visit the CDC and NCHS websites.

In this cross-sectional study, nationally representative data from the National Health and Nutrition Examination Survey (NHANES) were utilized. Among 70,190 participants aged 20 years and older from the seven NHANES cycles conducted between 2005 and 2018, 39,041 participants were identified, excluding those who were pregnant and those with incomplete data for the LC9 indicators (n = 13,218), WWI (n = 424), and OAB (n = 80). Ultimately, a total of 25,319 participants were included in the study (Figure 1).

Figure 1

Figure 1. A flow diagram of eligible participant selection in the National Health and Nutrition Examination Survey. LC9, Life’s Crucial 9; OAB, overactive bladder; WWI, weight-adjusted-waist index.

OAB assessment

In patients, urgency urinary incontinence and nocturia must be considered as indicators of OAB based on their definitions. We assessed urinary incontinence and nocturia using three specific questions from the NHANES questionnaires KIQ044, KIQ450, and KIQ480 (23): (1) In the past year, have you experienced involuntary leakage of urine accompanied by urgency or a feeling of pressure, making it difficult to reach the bathroom in time? (2) How often does this occur? (3) In the past month, how many times did you typically wake up to urinate between going to bed and getting up in the morning?

Subsequently, the Overactive Bladder Symptom Score (OABSS) questionnaire was used to quantify OAB (24). Detailed scoring criteria can be found in Supplementary Table S4. Each participant’s OABSS score was calculated by summing the scores for urgency urinary incontinence and nocturia. In this survey, participants with a total score of 3 or higher were considered to have overactive bladder.

Definition of weight-adjusted-waist index

We obtained data on participants’ weight-adjusted waist index (WWI) from the NHANES database. WWI is calculated based on waist circumference (WC) and weight to assess central obesity. Each participant’s WWI was determined using the following formula: WWI = WC (cm)/(weight (kg)2) (25). In this study, WWI was utilized as a mediating variable. WWI was selected as a measure of central obesity due to its ability to adjust for both weight and waist circumference, factors that are commonly linked to central fat distribution. Unlike traditional indices like Body Mass Index (BMI), which does not account for fat distribution, or Waist-to-Height Ratio (WHtR), which adjusts for height but not for overall weight, WWI provides a more specific reflection of central obesity by incorporating both waist circumference and weight in a balanced way. This makes WWI a potentially more precise measure of abdominal adiposity and its association with conditions like OAB.

Definition of Life’s Crucial 9

LC9 encompasses nine indicators: four health behaviors (healthy diet, physical activity, smoking cessation, and healthy sleep) and five health factors (weight management, cholesterol control, blood glucose management, blood pressure management, and mental health). Detailed instructions for calculating each participant’s LC9 score using the NHANES database are provided in Supplementary Table S1. In summary, each of the nine LC9 indicators is scored on a scale from 0 to 100. The LC9 score is determined by the average of the scores from the nine individual indicators. The 2015 Healthy Eating Index (HEI-2015) was utilized to assess diet quality (26). The components and scoring criteria for the HEI-2015 are detailed in Supplementary Table S2. Sleep health, smoking status, physical activity, and mental health data were derived from standardized questionnaires, while BMI, blood pressure, blood glucose, and cholesterol levels were obtained from trained professionals using the NHANES database (see Footnote 1).

Covariables

The covariates in this study included age, sex, race, marital status, education level, poverty-to-income ratio (PIR), smoking, alcohol consumption, hypertension, diabetes, and dyslipidemia. Detailed information regarding these covariates can be found in Supplementary Table S3.

Statistical analysis

Statistical analyses were conducted using R software (version 4.3.1), with all analyses employing sampling weights to ensure that the estimated data were nationally representative. In our study, “WTMEC2YR” was used as the weighting variable, and the new weight (2005–2018) was calculated as 1/7 × WTMEC2YR (27). Continuous variables were expressed as mean ± standard deviation, and p-values were calculated using t-tests. The percentages and p-values for categorical variables (weighted N, %) were computed using weighted chi-square tests. Multivariable logistic regression models were used to analyze the relationships between LC9 and OAB, as well as WWI and OAB, constructing three models: (1) a crude model without covariate adjustment, (2) a model adjusted for age, sex, education level, marital status, poverty-to-income ratio (PIR), and race, and (3) a model further adjusted for smoking, alcohol consumption, hypertension, diabetes, and dyslipidemia. Smoothing spline fitting was employed to explore the linear or nonlinear relationship between LC9 and OAB. Subgroup analyses were performed to examine the risk stratification of the relationship between LC9 and OAB across various subgroups. Mediation analysis was conducted to evaluate the indirect, direct, and overall effects of WWI on the relationship between LC9 and OAB. The mediation proportion was calculated as (indirect effect / (indirect effect + direct effect)) × 100%. Mediation effects were estimated using the “mediation” package in R software (27). A two-sided p-value of less than 0.05 was considered statistically significant.

Results

Baseline characteristics

This study included 25,319 participants aged 20 and older, representing approximately 159.5 million adults in the United States. The prevalence of OAB was found to be 16%, affecting around 24.87 million individuals. Statistically significant differences (p < 0.05) were observed between OAB patients and non-OAB individuals concerning age, sex, race, marital status, education level, income level, smoking, alcohol consumption, hypertension, diabetes, and dyslipidemia. Additionally, the LC9 levels in the OAB group were lower than those in the non-OAB group, while the WWI was higher in the OAB group compared to the non-OAB group. Further details can be found in Table 1.

Table 1

Table 1. Baseline characteristics of all participants were stratified by OAB, weighted.

Association between LC9, WWI, and OAB

As shown in Table 2, three different models were employed to evaluate the association between LC9 and the prevalence of OAB, all indicating a negative correlation between LC9 and OAB prevalence (all p < 0.001). In Model 3, after adjusting for various covariates, each 10-point increase in LC9 was associated with a 28% reduction in OAB prevalence [odds ratio: 0.72 (95% confidence interval: 0.69, 0.76)]. Furthermore, when categorized into tertiles, the group with the highest LC9 scores (T3) exhibited a 53% lower prevalence of OAB compared to the group with the lowest scores (T1) [odds ratio: 0.47 (95% confidence interval: 0.40, 0.54)]. Additionally, the relationship between WWI and OAB was assessed, revealing a positive correlation across all three models (all p < 0.001). Higher WWI scores were associated with increased OAB prevalence, with statistically significant results (all p < 0.05). The results from the restricted cubic spline (RCS) analysis (Figure 2) further illustrated a significant linear negative correlation between LC9 and OAB prevalence after adjusting for relevant variables (overall p < 0.001; nonlinear p = 0.065).

Table 2

Table 2. Association between LC9, WWI, and OAB, NHANES 2005–2018.

Figure 2

Figure 2. Dose–response relationships between LC9 and OAB. OR (solid lines) and 95% confidence levels (shaded areas) were adjusted for age, gender, education level, marital, PIR, race, smoking, drinking, hypertension, diabetes, and high cholesterol.

Subgroup analyses were conducted based on age, sex, race, marital status, education level, poverty-to-income ratio (PIR), smoking, alcohol consumption, hypertension, diabetes, and hypercholesterolemia (Figure 3). The results indicated a significant negative correlation between LC9 scores and OAB prevalence across all subgroups. Furthermore, a significant interaction was observed between LC9 and both age and education level (p < 0.05).

Figure 3

Figure 3. Subgroup analysis between LC9 and OAB. ORs were calculated as per 10-unit increase in LC9. Analyses were adjusted for age, gender, education level, marital, PIR, race, smoking, drinking, hypertension, diabetes, and high cholesterol.

Mediation effect

The mediation model is illustrated in Figure 4, with LC9, OAB, and WWI serving as the independent variable, dependent variable, and mediator variable, respectively. As shown in Table 3, a significant correlation was observed between LC9 and WWI after adjusting for other covariates (β = −0.25, 95% CI: −0.26, −0.24). Following the adjustment for all covariates, the mediating effect of WWI was evident (indirect effect = −0.010, p = 0.002; direct effect = −0.062, p < 0.001), resulting in a mediation proportion of 13.89% (p = 0.002). Therefore, WWI can be regarded as a mediating factor in the association between LC9 and OAB.

Figure 4

Figure 4. Schematic diagram of the mediation effect analysis. Path C indicates the total effect; path C′ indicates the direct effect. The indirect effect is estimated as the multiplication of paths A and B (path A*B). The mediated proportion is calculated as indirect effect/ (indirect effect + direct effect) × 100%. Abbreviation: LC9, Life’s Crucial 9; OAB, overactive bladder; WWI, weight-adjusted-waist index. Analyses were adjusted for age, gender, education level, marital, PIR, race, smoking, drinking, hypertension, diabetes, and high cholesterol.

Table 3

Table 3. Multivariate linear regression of LC9 and WWI.

Discussion

In this study, we investigated 25,319 participants from NHANES 2005–2018, demonstrating a negative correlation between LC9 and the prevalence of OAB, while a positive correlation was observed between WWI and OAB. Furthermore, the mediation analysis indicated that WWI partially mediated the association between LC9 and OAB. Notably, a significant interaction was found between LC9 scores and both age and education level.

To our knowledge, this is the first study to investigate the association between LC9 and OAB mediated by WWI. Previous research has indicated a negative correlation between cardiovascular health (CVH), quantified by the LE8 score, and the prevalence of OAB. Additionally, WWI has been shown to predict the incidence of OAB, with obesity management contributing to a reduced risk of OAB (28, 29), findings that align with our study. However, these studies did not consider the impact of mental health on cardiovascular health and OAB. Our research not only confirms this association but also further explores the relationship between Life’s Essential 9 and OAB, emphasizing the significance of mental health in cardiovascular health. Mental health encompasses various aspects, such as depression, anxiety, and chronic, and traumatic stress, all of which are related to cardiovascular disease risk.

The components of LC9 influence OAB through several mechanisms. The dietary component of LC9, particularly weight control, increased fiber intake, and adequate hydration, may indirectly affect OAB by reducing inflammation, improving metabolic health, and promoting bladder health (15). An increase in dietary fiber and antioxidants helps reduce bladder inflammation and alleviate OAB symptoms. Diets rich in fruits, vegetables, and whole grains can lower chronic low-grade inflammation, which may contribute to the alleviation of OAB symptoms. Physical activity impacts OAB through various pathways. Increased physical activity can reduce OAB symptoms by enhancing core muscle strength, improving pelvic muscle tone, and restoring normal bladder function. Additionally, regular exercise improves blood circulation, reduces cardiovascular disease risk, and decreases the stress and discomfort associated with OAB (30). Physical activity also helps control body weight, improving fat distribution and reducing abdominal fat accumulation, thereby relieving pressure on the bladder. Sleep quality plays a crucial role in OAB. Insufficient or poor-quality sleep leads to increased activation of the nervous system, exacerbating symptoms such as frequent urination and urgency. The sleep component of LC9 emphasizes good sleep habits and adequate sleep duration, which helps regulate the sympathetic nervous system and reduce bladder overactivity. Moreover, quality sleep promotes restorative rest and alleviates anxiety or depression induced by OAB, thereby easing symptoms.

Interaction analysis suggests that LC9 may interact with age and education level in influencing OAB. The CVH score appears to have a greater impact on individuals with education beyond high school. This might be because they are more likely to recognize OAB as a medical condition and seek solutions compared to those with lower educational attainment. Cultural barriers, such as stigma and health beliefs, might also play a role (31, 32). Aging alone is considered a major risk factor for OAB, leading to anatomical and functional changes such as reduced bladder capacity and compliance. Additionally, with age, the detrusor muscle of the bladder shows decreased expression of muscarinic receptors and neural innervation, resulting in reduced cholinergic transmission (33). Imaging studies further reveal age-related differences in supraspinal control of non-neurogenic overactive bladder (OAB). In younger patients with OAB, areas like the insula and anterior cingulate cortex (ACC) show moderate responses at low bladder volumes but increase at higher volumes, while the opposite is true for older patients (34).

Lower urinary tract symptoms (LUTS) are closely associated with cardiovascular disease (CVD), which has been proposed as a potential risk factor for the progression and severity of LUTS (35). The mechanisms linking these conditions are multifaceted and complex. The pathogenesis of overactive bladder (OAB) is closely related to various cardiovascular risk factors, with oxidative stress (OS) being a fundamental mechanism of CVD. Worsening oxidative stress can alter the function and/or structure of the bladder, urethra, and prostate, leading to LUTS (36). Since the introduction of metabolic syndrome (MetS) in 1977, it has emerged as a significant precursor to CVD and other chronic diseases, with obesity and insulin resistance (IR) considered its core components (37, 38). Recent studies have shown an association between OAB and MetS in women (16, 39). The overactivity of the sympathetic nervous system, pro-inflammatory states, OS, and other pathological conditions related to MetS may also be linked to OAB (40). Regarding IR, it is associated with sympathetic overactivity, a key neuropathological finding in idiopathic OAB patients (41). Furthermore, an animal study has demonstrated that hyperinsulinemia resulting from IR can induce bladder smooth muscle relaxation, dependent on the activation of the PI3K/AKT/eNOS signaling pathway within the mucosal layer, subsequently releasing NO to relax detrusor smooth muscle (42).

The occurrence of lower urinary tract symptoms (LUTS) is multifactorial, with obesity being one of the contributing factors (43). A randomized controlled trial involving 77 OAB patients demonstrated that reducing abdominal fat alleviated OAB symptoms, a finding supported by another study (13, 44). While earlier studies used body mass index (BMI) as a measure of disease, recent research has shifted toward identifying physiological and metabolic dysfunction markers of adipose tissue, with a greater focus on regional fat, such as visceral fat (45). The waist-to-weight ratio (WWI) better reflects visceral fat than BMI. Accumulation of visceral adipose tissue (VAT) leads to chronic inflammation and insulin resistance. VAT infiltrated by inflammatory macrophages becomes a source of low-grade chronic inflammation, which is associated with the OAB syndrome. One study showed that inflammation markers in OAB patients were significantly higher than in controls (46, 47). Previous research suggested that poorer cardiovascular health (CVH), quantified by the Life’s Simple 7 (LS7) score, is associated with increased visceral fat area and elevated HOMA-IR levels (48). LC9, as a new indicator for assessing CVH, emphasizes mental health, with anxiety and depression being linked to LUTS. When anxiety and depression occur together, they seem to have an additive effect on the association with LUTS. Emotional disorders may result in LUTS, and conversely, LUTS may make patients more susceptible to emotional disorders (49).

The potential mechanisms through which WWI mediates the relationship between LC9 and OAB are as follows: An increase in WWI may indicate a rise in visceral fat accumulation, which is associated with metabolic disturbances such as insulin resistance, hyperglycemia, and dyslipidemia (50). These metabolic factors could contribute to bladder dysfunction by altering the balance of neurotransmitters (e.g., acetylcholine, norepinephrine) involved in bladder contraction, leading to OAB. Furthermore, visceral fat has been shown to secrete pro-inflammatory cytokines (e.g., TNF-α, IL-6), which can activate inflammatory pathways in bladder smooth muscle cells, increasing bladder sensitivity and contributing to OAB. Additionally, improvements in the health behaviors recommended by LC9, such as increased physical activity and dietary changes, may help reduce abdominal fat (51). This, in turn, could indirectly reduce WWI and improve metabolic health, thereby lowering the risk of OAB.

This study has several strengths: (1) It is the first to examine the correlation between LC9 and the prevalence of OAB in an American population, indicating significant potential for LC9 as a diagnostic and assessment tool for OAB. It provides new recommendations for OAB diagnosis and evaluation. (2) WWI is introduced as a new indicator for assessing visceral fat content, outperforming traditional anthropometric methods in screening for OAB, thus facilitating low-cost identification of OAB in clinical settings. (3) The study includes a large sample size, utilizing population data from NHANES 2005–2018, which allows for a nationally representative characterization of the population. (4) By constructing various models and conducting subgroup analyses to adjust for confounding factors, the study demonstrates a strong positive correlation between LC9 and OAB. The results are robust and reliable. (5) Subgroup analysis reveals that age and education level may be potential modifiers of the relationship between LC9 and OAB (p < 0.05), suggesting that these factors influence the association between CVH and OAB prevalence. This highlights the need for further research to validate these associations.

Despite the significance of this study, several limitations need to be acknowledged: (1) This is a cross-sectional study, which cannot establish a causal relationship between LC9 and the prevalence of OAB. Further large-scale, prospective studies are needed to clarify the causality between LC9 and OAB. (2) NHANES employs a complex, multistage, stratified probability sampling method, theoretically representing the U.S. noninstitutionalized population. However, certain populations, such as hospitalized patients and residents of long-term care facilities, were excluded, potentially limiting the generalizability of our findings to the entire U.S. population. Moreover, selection bias may arise from individuals who did not participate in the survey or complete specific assessments. (3) The diagnosis of OAB in this study relies on the OABSS score derived from nocturia and urgency urinary incontinence symptoms recorded by NHANES. The frequency of these symptoms may be subject to recall bias. (4) This study utilized NHANES data, which, while providing a large sample size, may be subject to potential confounding effects and issues related to multiple dependent variables. Given that each LC9 component (such as diet, physical activity, and sleep) is measured at different levels, there may be interrelationships between these variables that were not fully accounted for. As a result, this study may not have fully isolated the independent effects of each component on OAB outcomes. Additionally, due to variations in data quality, the selection of appropriate statistical methods is crucial to ensure the accuracy of the results, particularly in large sample datasets where confounding factors may influence the final analysis. Future studies could consider further exploring the potential interactions among these variables and applying more refined statistical methods to mitigate the impact of confounding effects. (5) Additionally, one of the limitations of this study is the use of the OABSS cutoff value of 3 to define overactive bladder (OAB). While this cutoff is widely used in existing literature and has been validated in several studies, we acknowledge that it has certain limitations, especially in its applicability across different populations and clinical contexts. Specifically, the OABSS cutoff value of 3 classifies OAB based on symptom frequency and severity, but this simplified threshold may not fully capture the complexity and variability of OAB symptoms, particularly in individuals with mild or intermittent symptoms. For example, increased nocturia or occasional episodes of urgency/urge incontinence may be indicative of OAB, but these symptoms might not reach the OABSS cutoff of 3, potentially leading to underdiagnosis of OAB in some patients. Furthermore, the OABSS cutoff of 3, being a quantitative measure, does not account for individual differences in symptom perception and the subjective impact on quality of life. Different patients may perceive and report symptoms differently, and a single cutoff value may not fully reflect the impact of symptoms on an individual’s daily life. As such, our study may either underestimate or overestimate the true prevalence of OAB. Additionally, since the OABSS was not originally designed to capture all clinical aspects of OAB, relying solely on this scoring system may overlook other factors influencing OAB symptoms, such as urodynamic abnormalities or changes in bladder capacity. Therefore, future research should consider combining the OABSS with other clinical assessment tools or symptom scales to provide a more comprehensive evaluation of the symptom burden and quality of life in OAB patients. Given these limitations, we suggest that future studies explore whether more refined diagnostic criteria are needed, considering not only the frequency and severity of symptoms but also their duration and impact on quality of life. Longitudinal data and more precise diagnostic standards will help further validate the definition and diagnostic methods for OAB.

Conclusion

In conclusion, we identified a significant negative correlation between LC9 and OAB, with WWI as a partial mediator. This finding underscores the potential link between cardiovascular health and OAB, highlighting the importance of obesity management in this context. Our study provides new insights into the prevention and management of OAB, emphasizing that a comprehensive approach to improving cardiovascular health and addressing obesity may help reduce the prevalence of OAB. Therefore, prospective studies are necessary to provide more definitive evidence regarding the underlying mechanisms. Additionally, future research could further explore other potential risk factors, such as mental health disorders, which may also influence this relationship.

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://www.cdc.gov/nchs/nhanes/index.htm.

Ethics statement

Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions

HG: Conceptualization, Data curation, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing. SD: Conceptualization, Data curation, Investigation, Methodology, Software, Writing – original draft, Writing – review & editing. SH: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Acknowledgments

We sincerely appreciate the NHANES database for all of the data.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnut.2024.1508062/full#supplementary-material

Abbreviations

LC9, Life’s Crucial 9; WWI, Weight-adjusted-waist index; OAB, overactive bladder; LS7, Life’s Simple 7; LE8, Life’s Essential 8; CVH, Cardiovascular health; NHANES, National Health and Nutrition Examination Survey.

Footnotes

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