Abstract
Objectives:
To operationalize a new definition for bladder health, we examined the distribution and impact of lower urinary tract symptoms (LUTS), along with risk factors, among men in the Coronary Artery Risk Development in Young Adults (CARDIA) study.
Methods:
LUTS were defined by American Urologic Association Symptom Index (AUASI) scores and impact on quality of life (QoL). Separate questions assessed urinary incontinence (UI) and post-void dribbling. We performed cluster analyses using AUASI scores, with and without urine incontinence and post-void dribbling, and impact collected in 2010–11. We performed analyses to evaluate sociodemographic and cardiovascular risk factors between clusters.
Results:
Among CARDIA men (mean age 50.0, SD=3.6; range 42–56 years) with complete LUTS data (n=929), we identified and compared 4 clusters: men who reported no or very mild symptoms and no impact on well-being (bladder health, n=696, 75%), men with moderate symptoms and moderate impact on well-being (moderate symptoms/impact, n=84, 9%), men with high symptoms and high impact on well-being (severe symptoms/impact, n=117, 13%), and a separate group that reported moderate symptoms and UI with a high impact on well-being (UI+moderate symptoms/severe impact, n=32, 3%). Exploration of the groupings showed a large percentage of post-void dribbling across groups (overall 69%). Sociodemographic and cardiovascular risk factors were not associated with symptom/impact groups.
Conclusions:
Bladder health clustered into four categories. A majority of middle-aged men in the community showed no or mild bladder symptoms without impact on QoL. Post-void dribbling is pervasive but did not cluster with a specific LUTS or impact category.
Keywords: bladder health, lower urinary tract symptoms, cluster analysis, health-related quality of life, men
BACKGROUND:
Lower urinary tract symptoms (LUTS) include storage symptoms, such as urgency, frequency, post-void dribbling, incontinence, and nocturia; emptying symptoms during urination, such as weak stream, hesitancy, and interrupted stream, and post-micturition symptoms, such as incomplete emptying.1 LUTS are common in middle-aged and older men (40–70%), have a negative impact on quality of life, and can be costly.2–5 In women, the Prevention of Lower Urinary Tract Symptoms (PLUS) Research Consortium defines bladder health as “a complete state of physical, mental, and social well-being related to bladder function [that] permits daily activities [and] allows optimal well-being.”6,7 The same definition could be applied to evaluate the distribution of bladder health in men. No identified research to date has focused on the distribution of bladder health in men, in contrast to a few studies reporting a bladder health rate of 18–44% among women.8,9
To evaluate the distribution of bladder health among men, few studies have extensive LUTS symptom data that would enable the evaluation according to the PLUS Consortium definition.10,11 A prior publication from Cinar et al. sought to quantify the spectrum of LUTS among men aged 40 years and older who completed the Boston Area Community Health (BACH) Survey. Using cluster analytic methodology, this study found distinct clusters varying from the absence of LUTS (30% asymptomatic) to mild LUTS (Cluster 1, 35%) and more moderate to severe/very severe LUTS clusters (Clusters 2 through 6, 35%). In the more symptomatic clusters, urinary incontinence (UI) and post-void dribbling were often present, with prevalence ranging from 50% to 70%. In the BACH cluster analysis among men, the authors did not account for the impact of LUTS on daily activities and quality of life.
To address this gap, we evaluated the distribution of bladder health and LUTS with data from the population-based Coronary Artery Risk Development in Young Adults (CARDIA) study that also studies cardiovascular factors.7,12 Many population-based studies examining men with LUTS have found that having increased cardiovascular risk and metabolic syndrome also increased the risk of having LUTS.13,14 These findings suggest that shared risk factors for LUTS and cardiovascular disease may exist among men.12 Our goals were thus twofold: to determine the distribution of bladder health among male CARDIA participants, and to evaluate whether cardiovascular factors were associated with LUTS clusters.
METHODOLOGY:
Study Population
CARDIA is a longitudinal cohort study that recruited from the populations of four U.S. cities (Birmingham, AL; Minneapolis, MN; Chicago, IL; and Oakland, CA). CARDIA initially was designed to study the evolution of cardiovascular risk and disease. At baseline (1985–1986), 5,115 Black and White women and men aged 18–30 years participated in interviews and examinations. Details on study design have been previously reported.15 Written informed consent was obtained at each exam, and the IRB at each center approved study protocols. In-person follow-up examinations were conducted 2, 5, 7, 10, 15, 20, 25 and 30 years after baseline with response rates of 91%, 86%, 81%, 79%, 74%, 72%, 72% and 71% of the surviving cohort, respectively.
Standardized protocols were used to collect data at each examination. At years 25 and 30, men fasted for at least 12 hours and were asked to avoid smoking or intensive physical activity for at least 2 hours before their clinic visit. All staff were trained and certified to collect study data for blood pressure measurement, weight and height, as well as abdominal girth. Fasting blood samples were obtained and processed in a central laboratory. CARDIA details are available at http://www.cardia.dopm.uab.edu.
Analytic Sample and LUTS Questionnaires
Following the Year 25 (2010–11) examination, an ancillary study about benign (non-cancerous) genitourinary conditions collected data on LUTS and their impact among CARDIA participants. Data were collected via questionnaire mailings between March 2012 and February 2013. Out of the 3,498 surviving CARDIA participants at the year 25 examination, LUTS questionnaires were completed by 996 of the 1,517 men (66%) and from the men completing questionnaires 929 men (93%) had complete data for this analysis.
Bladder Health and LUTS Definitions
The presence and severity of LUTS were measured with the American Urologic Association Symptom Index (AUASI) score, a composite of 7 individual LUTS, defined as LUTS storage items (urgency, frequency, and nocturia), LUTS emptying items (hesitancy, intermittency, and weak stream), and LUTS post-micturition (incomplete emptying) across the past month with response options related to frequency: “not at all, less than 1 in 5 times, less than half the time, about half the time, more than half the time, and almost always.” Scores ranged from 0–35 (higher scores indicated more severe LUTS).16 Based on the literature and to be consistent with the PLUS definition of LUTS, we further divided LUTS into storage, emptying, post micturition categories.17 We measured LUTS impact on quality of life (QoL) with the AUASI question that we collapsed into 4 categories: “pleased or delighted” (0 or 1); “mostly satisfied” (2); “mixed satisfied/dissatisfied” (3); and “mostly dissatisfied,” “unhappy,” or ”terrible” (4, 5, or 6). Urinary incontinence (UI) and post-void dribbling were assessed using a single item, “In the past month, have you ever dribbled or leaked urine when you did not mean to?” Response categories were “I only leaked larger amounts of urine at other times and did not dribble,” “I only dribbled a little urine after going to the bathroom,” “I dribbled a little urine after going to the bathroom and leaked larger amounts at other times, ” and “I did not dribble after going to the bathroom or leak urine at other times.” For this analysis, this item was recoded into categories that coded for the presence of either post-void dribbling or UI or the combination of both. Missing data rates on returned questionnaires for the bladder health items were N=9 (1%) for UI, n=40 (4%) for LUTS storage, n=25 (3%) for LUTS emptying, n=10 (1%) for LUTS post-micturition, and n=11 (1%) for LUTS QoL (not mutually exclusive). Men with missing data (n=67) were excluded from the analyses.
Covariates
CARDIA participants completed questionnaires and had an in-person examinations that included information on sociodemographic variables (age, race, and educational attainment); body mass index (kg/m2 with obesity defined as ≥30 kg/m2); waist circumference; waist-to-hip ratio; hypertension; diabetes, and depression symptoms with continuous scores and categorized scores as yes/no (≥16) from the Center for Epidemiologic Studies-Depression Scale (CES-D).18 Self-reported benign prostatic hypertrophy (BPH) and erectile dysfunction was assessed at the same time as the LUTS assessment. Men meeting 3 out of 5 criteria met the definition of metabolic syndrome: waist circumference of more than 40 inches; fasting blood glucose levels of 100 mg/dL or above; blood pressure of 130/85 mmHg or above; blood triglycerides of 150 mg/dL or above; and high-density lipoprotein (HDL) levels of 40 mg/dL or lower.19
Further evaluation included cardiovascular health behaviors. The cardiovascular health behavior index (ranged from 0–6, higher scores indicated more health) included a physical activity score, tobacco use status at year 25, and dietary reports of specific sugar-sweetened beverages and fast-food meals.20
We evaluated a nonspecific biomarker of systemic inflammation, hs-CRP (range 0.175 to 1.100ug/mL) at year 25 using fasting plasma samples with a Roche latex-particle enhanced immunoturbidimetric assay kit read on the Roche Modular P Chemistry analyzer.21 From other studies, hs-CRP has been linked with both LUTS severity and hypertension.21,22
Cluster Analysis
Similar to the methods used by Cinar et al. in BACH,11 we standardized z-scores for 5 scales of interest (UI, LUTS storage, LUTS emptying, LUTS post-micturition, LUTS impact) (Mean=0, SD=1) to avoid biasing the clusters and used the standardized factors for a k-means cluster analysis. To identify an appropriate number of clusters, we considered the results in CARDIA women to maximize comparability of the results for men.9 We also utilized the elbow method that considers within cluster variability as a function of number of clusters. Based on these criteria, we chose four clusters. The centroids of these clusters in the original scaling are shown in Tables 1 and 2. To validate the clusters and to allow the classification of future analyses, we used the cluster memberships that the unguided k-means cluster provided as the basis of a supervised classification using Fishers discriminant analysis. Fishers discriminant analysis confirmed that the clusters were separable and that all variables provided incremental improvement of the classification algorithm, supporting the notion that all clusters provided unique information. In further sensitivity analysis (Supplemental Table 2), we also included PVD in the clusters for comparison to our primary approach (including PVD along with UI for the subscales of LUTS storage, LUTS emptying, LUTS post-micturition, LUTS impact).
Table 1.
Sociodemographic and Medical Characteristics According to Cluster Groups
| Total Sample (n=929) | Bladder Health (N=696) | Moderate Symptoms & Moderate Impact (n=84) | Severe Symptoms & Severe Impact (n=117) | UI+Moderate Symptoms & Severe Impact (n=32) | |
|---|---|---|---|---|---|
| Age (years) at Year 25, Mean ± SD | 50.0 (3.6) | 49.8 (3.6) | 50.3 (3.4) | 50.6 (3.4) | 49.8 (4.0) |
| Race | |||||
| Black | 386 (42%) | 291 (42%) | 38 (45%) | 40 (34%) | 17 (53%) |
| White | 543 (58%) | 405 (58%) | 46 (55%) | 77 (66%) | 15 (47%) |
| Educational Attainment | |||||
| High school or less | 156 (17%) | 124 (18%) | 14 (17%) | 14 (12%) | 4 (12%) |
| Some college | 275 (30%) | 196 (28%) | 31 (37%) | 39 (33%) | 9 (28%) |
| College graduates | 498 (54%) | 376 (54%) | 39 (46%) | 64 (55%) | 19 (59%) |
| *Obesity, BMI ≥30 mg/kg2 N=843 | 339 (40%) | 260 (41%) | 29 (39%) | 37 (35%) | 13 (43%) |
| *BMI, Mean ± SD N=843 | 29.5 (6.0) | 29.6 (6.0) | 28.9 (5.2) | 28.8 (5.5) | 30.9 (9.1) |
| Waist Circumference, Mean ± SD N=845 | 98.8 (14.2) | 99.1 (14.1) | 98.1 (13.1) | 97.4 (13.9) | 100.7 (20.3) |
| Waist Hip Ratio Mean (SD) N=842 | 0.91 (0.07) | 0.91 (0.07) | 0.91 (0.07) | 0.92 (0.06) | 0.90 (0.08) |
| Hypertension, n (%) N=844 | 250 (30%) | 191 (30%) | 24 (32%) | 28 (26%) | 7 (23%) |
| Diabetes, n (%) N=844 | 79 (9%) | 53 (8%) | 12 (16%) | 9 (8%) | 5 (16%) |
| **Depression Score, CES-D, Mean ± SD N=839 | 8.7 (7.2) | 7.9 (6.8) | 11.8 (7.1) | 10.2 (7.8) | 12.4 (7.9) |
| **Depressive symptoms, CES-D>=16, n (%) N=839 | 118 (14%) | 69 (11%) | 13 (17%) | 28 (26%) | 8 (27%) |
| **BPH, self-report, n (%) | 65 (7%) | 29 (4%) | 9 (11%) | 24 (20%) | 3 (9%) |
| Erectile dysfunction Last Month, n (%) N=923 | 39 (4%) | 24 (3%) | 6 (7%) | 7 (6%) | 2 (6%) |
| Erectile dysfunction Last Year, n (%) | 37 (4%) | 22 (3%) | 3 (4%) | 9 (8%) | 3 (10%) |
| Metabolic Syndrome, n (%) | 166 (18%) | 123 (18%) | 16 (19%) | 20 (17%) | 7 (22%) |
| Physical activity (exercise units) | 406 (303) | 429 (303) | 365 (273) | 384 (310) | 407 (336) |
| *Tobacco use status at year 25 years, n (%) N=835 | |||||
| Never smokers or quit >12 months | 522 (62%) | 402 (64%) | 41 (55%) | 65 (62%) | 14 (48%) |
| Former smokers, quit ≤12 months | 159 (19%) | 116 (18%) | 16 (21%) | 19 (18%) | 8 (28%) |
| Current smokers | 154 (18%) | 108 (17%) | 18(21%) | 21 (20%) | 7 (24%) |
| Health Behavior Score (smoking, physical activity, and diet, higher is better), Mean ± SD | 8.6(2.2) | 8.7 (2.1) | 8.4 (2.3) | 8.7 (2.2) | 8.6 (2.2) |
| C-Reactive Protein (higher level, more inflammation) N=844 | 2.4 (4.7) | 2.4 (5.1) | 2.2 (2.9) | 2.2 (4.1) | 2.2 (2.5) |
Derived variables from CARDIA longitudinal data
p value = <0.01
Table 2:
Distribution of LUTS Burden and Impact from the AUASI (N=929)
| Continuous Distribution | AUASI Categorical Distribution** | ||||||
|---|---|---|---|---|---|---|---|
| Mean | SD | Range | No Symptoms N (%) | Mild N (%) | Moderate N (%) | Severe/Very Severe N (%) | |
| Symptoms | |||||||
| LUTS Severity – total score | 6.1 | 5.2 | 0–33 | 59 (6%) | 583 (63%) | 265 (29%) | 22 (2%) |
| Storage subscale | 3.7 | 2.8 | 0–13 | 74 (8%) | 312 (34%) | 469 (50%) | 74 (8%) |
| Emptying subscale | 1.8 | 2.5 | 0–15 | 408 (44%) | 269 (29%) | 226 (24%) | 26 (3%) |
| Post-micturition subscale | 0.6 | 1.0 | 0–5 | 561 (60%) | 235 (25%) | 76 (9%) | 57 (6%) |
| Impact | |||||||
| LUTS Impact* | 0.6 | 1.0 | 0–4 | 579 (62%) | 195 (21%) | 103 (11%) | 52 (6%) |
For LUTS Impact, responses for “mostly dissatisfied, unhappy, or terrible” were combined and labeled as severe.
For AUASI categories: No symptoms = score is 0, Mild = score 1–7, Moderate = score 8–19, and Severe/Very Severe = >19
We used descriptive statistics to compare covariates for sociodemographic and cardiovascular risk factors across the four cluster groups. We then conducted univariate analysis to test whether covariates were associated with cluster group membership.
RESULTS:
With the cluster approach among men with complete data (Figure 1, n=929), we classified four clusters of men: (1) no or very mild symptoms of LUTS and no impact (defined as bladder health, 75%, n=696), (2) moderate symptoms/moderate impact without UI (9%, n=84), (3) severe symptoms/severe impact without UI (13%, n=117), and (4) moderate symptoms with UI/severe impact (3%, n=32). Table 1 shows that cluster groups did not differ across any of the sociodemographic and cardiovascular covariates examined. The self-report of BPH (p<0.01) and depressive symptoms (p<0.01) were the only variables that differed among the clusters, with higher likelihood of BPH and more depressive symptoms in participants that were clustered in the severe symptoms/severe impact without UI category.
FIGURE 1:
Spider Plot for Bladder Health and LUTS Severity/Impact Cluster Analysis
To further explain our cluster approach using the AUASI for Figure 1, Table 2 shows the mean values for the total score and for the subscales (LUTS storage, LUTS emptying, LUTS post micturition, LUTS QoL). Only 6% of men were categorized as having no symptoms on the total score (see first row of data in Table 2). More men with emptying symptoms (44%) and post-micturition symptoms were categorized in the no symptom group compared to men with storage (8%) or post-micturition symptoms (0%). For symptom categories defined by AUASI cutoff scores, the majority with LUTS reported mild symptoms (53%), with only 2% reporting severe LUTS (see first row of data in Table 2). The majority also reported no impact on QoL from LUTS (62%); Very few reported being “mostly dissatisfied, unhappy, or terrible” about their QoL with LUTS (6%) (see bottom row of Table 2). Table 3 shows that 30% of men reported the absence of UI or post void dribbling. The majority reported post void dribbling (69%), with 3% reporting UI only (see second column of Table 3).
Table 3.
Prevalence of Urinary Incontinence and Post-Void Dribbling
| Absence | Presence | |
|---|---|---|
| Any Urinary incontinence (UI) | 897 (97%) | 32 (3%) |
| Any Post-void dribbling (PVD) | 286 (31%) | 643 (69%) |
| Both, UI and PVD | 903 (97%) | 26 (3%) |
| Either UI or PVD | 280 (30%) | 649 (70%) |
The addition of post void dribbling into the cluster analysis produced different results (supplemental Table 2). In this sensitivity analysis, the moderate symptom groups were further subdivided by having no symptom impact and having moderate symptom impact. Given these results and the high prevalence of post-void dribbling, we utilized clusters that involved UI because of the association with symptom impact.
DISCUSSION:
Three out of four men (75%) met our definition of bladder health based on symptoms and impact on QoL in this cluster analysis. Overall, middle-aged men participating in CARDIA reported low symptom burden on the AUASI. Post-void dribbling was very common among men (69%), while UI was rare (3%). Surprisingly, most men did not report a large impact of LUTS on their QoL, even after reporting high rates of post-void dribbling. In contrast to women from the CARDIA cohort study, we did not find associations of cardiovascular risk factors with LUTS/impact clusters in men.9 Cardiovascular risk factors are associated with LUTS in men in other cohort studies.13,14,23–26 The present study combined self-reported symptoms and impact on QoL to create an index of bladder health. This, in addition to the narrow age range of men from this cross-sectional analysis of Year 25 CARDIA data, could explain discrepancies in findings from the present study of men and the broader literature.
Compared to other studies, we found a higher prevalence of men with bladder health and with low rates of LUTS in CARDIA (75%) as compared to the BACH cohort (65%, when combining men without any symptoms and those reported as “rarely”).11 This variation could be due to key difference in study design and the age range of men from each study. In the BACH study, men ranged in age from 40–80+ years, whereas in CARDIA, the age range of men during the survey period was much narrower (median age of 50 with a range of 46–54). Other key differences between these two studies that may account for observed variation in bladder health prevalence include racial and ethnic diversity, regional and geographic differences, and in participation rates. With regard to the latter, the CARDIA study has a long study duration and high retention rates compared with the design of the BACH study. In addition, 6% of men in CARDIA did not endorse having any LUTS compared to 30% in the BACH study.11 Given the high prevalence post-void dribbling and low UI prevalence in men, we put more weight on a bladder health definition using the lack of impact on quality of life, rather than the absence of LUTS, partially meeting the PLUS Consortium definition of bladder health.7
Our findings did not support associations between cardiovascular risk factors and the clustering of men’s bladder health. More data are needed to test associations between cardiovascular risk factors and men’s bladder health across the life course, especially regarding newer definitions for cardiovascular health. The newer definition of cardiovascular health includes the presence of both ideal health behaviors (nonsmoking, body mass index <25 kg/m2, physical activity at goal levels, and pursuit of a diet consistent with current guideline recommendations) and ideal health factors (untreated total cholesterol <200 mg/dL, untreated blood pressure <120/<80 mm Hg, and fasting blood glucose <100 mg/dL), as well as getting adequate sleep.12,27 In a recent systematic review of metabolic syndrome and LUTS in men, the authors concluded that good evidence existed to support a relationship between metabolic syndrome and prostatic enlargement, but not for LUTS.26 Only 7% of the men in CARDIA (average age 50 years ± 3.6 years) reported having a diagnosis of prostate enlargement. The low numbers of men who reported having prostate enlargement may be one reason that an association between metabolic syndrome and bladder health and symptom clusters was not observed in the present study. Evidence from observational and clinical studies suggest that serum markers of inflammation may be associated with prostatic enlargement, which may impact overactive bladder symptoms and LUTS.28–31 However, we did not find any associations with CRP levels and symptom clusters among men.
From this community-based study with well-characterized cardiovascular risk factors and extensive LUTS data, limitations existed. The AUASI only had one question that addressed the impact of LUTS on well-being to use in this analysis. Despite this limitation, the AUASI has been used for other cluster analyses among men with LUTS seeking treatment and in community cohorts. 11,33 We also were limited by not having validated questionnaires for UI and post void dribbling. Given this limitation, we performed a sensitivity analysis using post void dribbling in the cluster analysis for comparison. An additional limitation is that we chose not to do the cluster analysis based on individual LUTS, but did attempt to use LUTS categories based symptom types, similar to other recent analyses.11,32,33 Lastly in this analysis, we did not assess treatments for LUTS and did not include data on prostate cancer. We also did not complete clinical assessments for prostate enlargement.
We utilized the PLUS Research Consortium definition of bladder health that included LUTS and the impact on quality of life. Three quarters of midlife men endorsed this definition of bladder health. While this study did not find associations between cardiovascular health and bladder health, additional studies may be needed, especially in cohort studies that include longitudinal measures among men across the lifespan.
Supplementary Material
CARDIA acknowledgements:
The Coronary Artery Risk Development in Young Adults Study (CARDIA) is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the University of Alabama at Birmingham (HHSN268201800005I & HHSN268201800007I), Northwestern University (HHSN268201800003I), University of Minnesota (HHSN268201800006I), and Kaiser Foundation Research Institute (HHSN268201800004I). Data about benign genitourinary conditions were collected through the Adult Life Predictors of Genitourinary Disorders CARDIA ancillary study (DK084997/115-9107-01-M1; PI: Van Den Eeden). This manuscript has been reviewed by CARDIA for scientific content.
Funding Statement:
Writing of this manuscript was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) through R01 DK125274 (MPIs: Brady and Markland) and the National Institute on Aging (NIA) through K24 AG073586 (PI: Markland).
Footnotes
Conflict of Interest Disclosure: Authors did not report any conflicts of interest with this submission.
Ethics of Approval Statement: All the authors mentioned in the manuscript have agreed for authorship, read and approved the manuscript, and given consent for submission and subsequent publication of the manuscript based on the ICMJE guidelines.
Patient Consent Statement: Written informed consent was obtained at each exam, and the IRB at each center approved study protocols, (UAB - Birmingham, AL; UMN - Minneapolis, MN; Northwestern - Chicago, IL; and Kaiser - Oakland, CA).
Clinical Trial Registration: No clinical trial number to report; retrospective data analysis of an observational cohort study.
Data Availability Statement:
Data are publicly available for access through the data coordinating center: Home (uab.edu)
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data are publicly available for access through the data coordinating center: Home (uab.edu)